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Education and Health as Social Determinants: The Econeurobiology of Brain Development

December 2024

Publisher: Frontiers in Public Health
ISBN: ISBN 978-2-8325-5722-8

Authors:

Raed Mualem

Oranim Academic College of Education

Calixto Machado

Institute of Neurology and Neurosurgery Havana Cuba

The development of the human brain is a dynamic and complex process, profoundly influenced by the surrounding environment during childhood. Early life experiences and educational enrichment play a crucial role in brain development, highlighting the interplay between genetic and environmental factors (1). The field of econeurobiology provides an essential framework for understanding how these factors interact to shape neurobiological development. This perspective is particularly significant in recognizing how education and health function as critical social determinants that influence cognitive and behavioral outcomes in children.

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Shir Shance

Edited by

Raed Z. Mualem, Calixto Machado and Leon Morales-Quezada

Published in

Frontiers in Public Health

Frontiers in Pediatrics

Frontiers in Neuroscience

Education and health as

social determinants: the

econeurobiology of

brain development

November 2024

Frontiers in Public Health 1frontiersin.org

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ISSN 1664-8714

ISBN 978-2-8325-5722-8

DOI 10.3389/978-2-8325-5722-8

November 2024

Frontiers in Public Health 2frontiersin.org

Education and health as

social determinants: the

econeurobiology of brain

development

Topic editors

Raed Z. Mualem — Oranim Academic College, Israel

Calixto Machado — Instituto de Neurología y Neurocirugía, La Habana, Cuba

Leon Morales-Quezada — Spaulding Research Institute, Spaulding Rehabilitation

Hospital, United States

Topic coordinator

Shir Shance — Econeurobiology Research Group, Oranim Academic College, Israel

Citation

Mualem, R. Z., Machado, C., Morales-Quezada, L., Shance, S., eds. (2024).

Education and health as social determinants: the econeurobiology of brain

development. Lausanne: Frontiers Media SA. doi: 10.3389/978-2-8325-5722-8

November 2024

Frontiers in Public Health 3frontiersin.org

05 Editorial: Education and health as social determinants: the

econeurobiology of brain development

Raed Mualem, Leon Morales-Quezada, Shir Shance and

Calixto Machado

08 Prevalence and determinants of meeting minimum dietary

diversity among children aged 6–23 months in three

sub-Saharan African Countries: The Demographic and Health

Surveys, 2019–2020

Djibril M. Ba, Paddy Ssentongo, Xiang Gao, Vernon M. Chinchilli,

John P. Richie Jr., Mamoudou Maiga and Joshua E. Muscat

18 Emotional impact on children during home confinement in

Spain

Francisco Sánchez-Ferrer, Evelyn Cervantes-García,

César Gavilán-Martín, José Antonio Quesada, Ernesto Cortes-Castell

and Ana Pilar Nso-Roca

26 Associations between life-course household wealth mobility

and adolescent physical growth, cognitive development and

emotional and behavioral problems: A birth cohort in rural

western China

Jiaxin Tian, Yingze Zhu, Shuang Liu, Liang Wang, Qi Qi, Qiwei Deng,

Amanuel Kidane Andegiorgish, Mohamed Elhoumed, Yue Cheng,

Chi Shen, Lingxia Zeng and Zhonghai Zhu

36 Cross-sectional associations between adolescents’ physical

literacy, sport and exercise participation, and wellbeing

Paulina S. Melby, Peter Elsborg, Peter Bentsen and Glen Nielsen

48 Barriers to adequate nutrition care for child malnutrition in a

low-resource setting: Perspectives of health care providers

Ghada Wahby Elhady, Sally kamal Ibrahim, Enas S. Abbas,

Ayat Mahmoud Tawfik, Shereen Esmat Hussein and

Marwa Rashad Salem

57 Correlation of fundamental movement skills with

health-related fitness elements in children and

adolescents: A systematic review

Cong Liu, Yuxian Cao, Zhijie Zhang, Rong Gao and Guofeng Qu

69 Association of elevated plasma CCL5 levels with high risk for

tic disorders in children

Hai-zhen You, Jie Zhang, Yaning Du, Ping-bo Yu, Lei Li, Jing Xie,

Yunhui Mi, Zhaoyuan Hou, Xiao-Dong Yang and Ke-Xing Sun

77 Relationships of the gut microbiome with cognitive

development among healthy school-age children

Yelena Lapidot, Maayan Maya, Leah Reshef, Dani Cohen,

Asher Ornoy, Uri Gophna and Khitam Muhsen

90 How understanding and strengthening brain networks can

contribute to elementary education

Michael I. Posner and Mary K. Rothbart

Table of

contents

November 2024

Frontiers in Public Health 4frontiersin.org

95 Positive or negative environmental modulations on human

brain development: the morpho-functional outcomes of

music training or stress

Carla Mucignat-Caretta and Giulia Soravia

106 Econeurobiology and brain development in children: key

factors affecting development, behavioral outcomes, and

school interventions

Raed Mualem, Leon Morales-Quezada, Rania Hussein Farraj,

Shir Shance, Dana Hodaya Bernshtein, Sapir Cohen, Loay Mualem,

Niven Salem, Rivka Riki Yehuda, Yusra Zbedat, Igor Waksman and

Seema Biswas

TYPE Editorial

PUBLISHED 26 September 2024

DOI 10.3389/fpubh.2024.1488824

OPEN ACCESS

EDITED AND REVIEWED BY

Tim S. Nawrot,

University of Hasselt, Belgium

*CORRESPONDENCE

Raed Mualem

raed.mualem@oranim.ac.il

RECEIVED 30 August 2024

ACCEPTED 11 September 2024

PUBLISHED 26 September 2024

CITATION

Mualem R, Morales-Quezada L, Shance S and

Machado C (2024) Editorial: Education and

health as social determinants: the

econeurobiology of brain development.

Front. Public Health 12:1488824.

doi: 10.3389/fpubh.2024.1488824

and Machado. This is an open-access article

distributed under the terms of the Creative

Commons Attribution License (CC BY). The

use, distribution or reproduction in other

forums is permitted, provided the original

author(s) and the copyright owner(s) are

credited and that the original publication in

this journal is cited, in accordance with

accepted academic practice. No use,

distribution or reproduction is permitted

which does not comply with these terms.

Editorial: Education and health as

social determinants: the

econeurobiology of brain

development

Raed Mualem1*, Leon Morales-Quezada2, Shir Shance1and

Calixto Machado3

1Econeurobiology Research Group, Research Authority, Oranim Academic College, Kiryat Tiv’on,

Israel, 2Department of Physical Medicine and Rehabilitation, Harvard Medical School, Spaulding

Rehabilitation Hospital, Boston, MA, United States, 3Department of Clinical Neurophysiology, Institute

of Neurology and Neurosurgery, The University of the Medical Sciences of Havana, Habana, Cuba

KEYWORDS

public health, econeurobiology, brain development, education, health

Editorial on the Research Topic

Education and health as social determinants: the econeurobiology of

brain development

Introduction

The development of the human brain is a dynamic and complex process, profoundly

inﬂuenced by the surrounding environment during childhood. Early life experiences and

educational enrichment play a crucial role in brain development, highlighting the interplay

between genetic and environmental factors (1). The ﬁeld of econeurobiology provides an

essential framework for understanding how these factors interact to shape neurobiological

development. This perspective is particularly signiﬁcant in recognizing how education

and health function as critical social determinants that inﬂuence cognitive and behavioral

outcomes in children.

This Research Topic of Frontiers in Public Health brings together a collection of studies

that explore these interactions in depth, emphasizing the key factors that impact brain

development and the long-term eﬀects on children’s behavior and academic performance.

The research underscores the profound inﬂuence of early-life experiences—from the

positive eﬀects of supportive educational environments to the harmful consequences

adverse childhood experiences (ACE), toxic stress and trauma (2).

By focusing on the concepts of developmental neuroplasticity and brain connectivity,

these studies oﬀer valuable insights into the mechanisms by which environmental

conditions shape the developing brain. Moreover, the integration of Gardner’s multiple

intelligences into educational strategies is emphasized as a means to enhance cognitive and

emotional resilience (3). Collectively, the articles in this Research Topic provide essential

knowledge for educators, policymakers, and healthcare professionals dedicated to fostering

optimal development in children.

Frontiers in Public Health 01 frontiersin.org

Mualem et al. 10.3389/fpubh.2024.1488824

Key factors shaping brain development

The studies in this Research Topic demonstrate that the

environment plays a crucial role in brain development, signiﬁcantly

inﬂuencing cognitive and behavioral outcomes.

Mualem et al. emphasize six critical factors in brain

development: a nurturing environment, adequate nutrition,

physical activity, music, sleep, and brain connectivity as explained

by Gardner’s multiple intelligences. The study highlights how

these elements promote cognitive and emotional growth, while

also noting the detrimental eﬀects of trauma and deprivation on

long-term health and learning outcomes.

Tian et al. explore the relationship between life-course

household wealth mobility and adolescent health in rural China.

Key ﬁndings show that upward wealth mobility, especially during

early childhood, is associated with better physical growth, cognitive

development, and lower behavioral problems, underscoring the

critical role of socioeconomic conditions in shaping long-term

health and development outcomes.

Sánchez-Ferrer et al. examine the emotional impact

of COVID-19 home conﬁnement on children in Spain.

Findings indicate that nearly 40% of children experienced

poor emotional states, including fear, sadness, and irritability.

Factors such as sleep disturbances, lack of outdoor access,

and parental anxiety exacerbated these eﬀects, while creative

communication and having pets mitigated emotional

distress.

Mucignat-Caretta and Soravia review how environmental

factors, both positive and negative, inﬂuence human brain

development. Music training is highlighted as a beneﬁcial

factor that enhances cognitive and motor skills through

brain plasticity, while stress is shown to negatively impact

brain structure and function. The ﬁndings underscore the

signiﬁcant role of environmental inputs in shaping cognitive and

emotional development.

Liu et al. systematically review the relationship between

fundamental movement skills (FMS) and health-related

ﬁtness in children and adolescents. They ﬁnd strong evidence

linking FMS with better cardiopulmonary function, muscle

strength, and endurance, while also showing a negative

correlation with body composition. The review underscores

the importance of developing FMS for overall physical health

and ﬁtness.

Melby et al. examine the associations between adolescents’

physical literacy, sport and exercise participation (SEP),

and wellbeing. Findings reveal that higher physical literacy

correlates positively with SEP and various aspects of wellbeing,

including self-esteem and life satisfaction. These associations

are particularly strong among girls, suggesting that physical

literacy is crucial for enhancing adolescents’ emotional and

social wellbeing.

Lapidot et al. investigate the connection between the gut

microbiome and cognitive development in school-aged children,

ﬁnding that greater microbial diversity is positively linked to

higher cognitive function as reﬂected in IQ scores. Recent research

highlights how dietary preferences, particularly traditional

vs. processed foods, aﬀect cognitive performance and social

behavior in kindergarten children, underscoring nutrition’s

vital role in early development (4). Socioeconomic status

also signiﬁcantly inﬂuences gut microbiome composition and

cognitive outcomes.

Ba et al. examine the prevalence and determinants of meeting

minimum dietary diversity (MDD) among children aged 6–23

months in three sub-Saharan African countries (Gambia, Liberia,

and Rwanda). The ﬁndings reveal that only 23.2% of children meet

MDD, with signiﬁcant variations by country, socioeconomic status,

maternal education, and access to healthcare, highlighting critical

disparities in child nutrition.

Elhady et al. identify multiple barriers to providing adequate

nutrition care for child malnutrition in a low-resource setting. Key

barriers include insuﬃcient training for healthcare providers, a

shortage of nutritional supplements, inadequate patient education

materials, and systemic issues like workforce shortages. These

challenges hinder eﬀective nutrition care, emphasizing the need

for targeted improvements in resources, training, and health

system management.

Posner and Rothbart discuss how understanding and

strengthening brain networks can enhance elementary education.

Key insights include the role of brain networks in reading, writing,

number processing, attention, and motivation. Strengthening these

networks through targeted educational strategies can improve

learning outcomes and foster a growth mindset, highlighting

the importance of neuroscience-informed teaching practices in

early education.

You et al. identify elevated plasma levels of CCL5 as a potential

risk factor for developing tic disorders in children. Elevated

CCL5, along with other cytokines like PDGF-AA, was signiﬁcantly

associated with tic disorder development, though not with tic

severity. These ﬁndings suggest CCL5 could serve as a biomarker

for predicting the onset of tic disorders.

Finally, in a key article, Mualem et al. illustrate the

inﬂuence of neural pathways on classroom learning, using the

example of story writing. The optimal development of these

connections is vital for fostering both quick, intuitive thinking

and more deliberate analysis, leading to what is referred to as

the “optimized brain.” Additionally, the article introduces the

“Econeurobiology of the Brain for Healthy Child Development”

model, showing how a child’s ecological environment aﬀects

neurological development. This interaction shapes cognitive

abilities, emotional regulation, and overall wellbeing, underscoring

the importance of a supportive and enriching environment for

optimal brain development.

Conclusion

In conclusion, this Research Topic provides a comprehensive

exploration of how environmental and social determinants,

particularly education and health, play a pivotal role in brain

development. The insights oﬀered in these articles underscore the

importance of a multidisciplinary approach to fostering optimal

cognitive and emotional growth in children, emphasizing the

critical need for supportive environments that enhance brain

connectivity and overall wellbeing.

Frontiers in Public Health 02 frontiersin.org

Mualem et al. 10.3389/fpubh.2024.1488824

Author contributions

RM: Writing – review & editing, Writing – original draft,

Conceptualization. LM-Q: Writing – review & editing, Writing –

original draft, Conceptualization. SS: Writing – review & editing,

Writing – original draft. CM: Writing – review & editing, Writing

– original draft.

Funding

The author(s) declare ﬁnancial support was received

for the research, authorship, and/or publication of

this article. The research was supported by Oranim

Academic College.

Conﬂict of interest

The authors declare that the research was conducted in the

absence of any commercial or ﬁnancial relationships that could be

construed as a potential conﬂict of interest.

Publisher’s note

All claims expressed in this article are solely those of the

authors and do not necessarily represent those of their aﬃliated

organizations, or those of the publisher, the editors and the

reviewers. Any product that may be evaluated in this article, or

claim that may be made by its manufacturer, is not guaranteed or

endorsed by the publisher.

References

1. Leisman G, Mualem R, Mughrabi SK. The neurological development of the

child with the educational enrichment in mind. Psicología Educativa. (2015) 21:79–

96. doi: 10.1016/j.pse.2015.08.006

2. Bucci M, Marques SS, Oh D, Harris NB. Toxic stress in children

and adolescents. Adv Pediatr. (2016) 63:403–28. doi: 10.1016/j.yapd.2016.

04.002

3. Maja G, Chandrasekaran MJ, Shuxiang A, Malin A, Larasati K. Multiple

intelligences-based learning innovation towards Era 5.0. World Psychol. (2023) 1:106–

22. doi: 10.55849/wp.v1i3.382

4. Mualem R, Jadon N, Shance S, Hussein Farraj R, Mansour R, Cohen S, et al.

The eﬀect of dietary preferences on academic performance among kindergarten-aged

children. J Neurosci Neurol Surg. (2023) 13:277. doi: 10.31579/2578-8868/277

Frontiers in Public Health 03 frontiersin.org

TYPE Original Research

PUBLISHED 23 August 2022

DOI 10.3389/fpubh.2022.846049

OPEN ACCESS

EDITED BY

Ademola Braimoh,

World Bank Group, United States

REVIEWED BY

Therese Mwatitha Gondwe,

Independent Researcher,

Lilongwe, Malawi

Emmanuel Biracyaza,

University of Rwanda, Rwanda

*CORRESPONDENCE

Djibril M. Ba

djibrilba@phs.psu.edu

SPECIALTY SECTION

This article was submitted to

Children and Health,

a section of the journal

Frontiers in Public Health

RECEIVED 05 January 2022

ACCEPTED 08 August 2022

PUBLISHED 23 August 2022

CITATION

Ba DM, Ssentongo P, Gao X,

Chinchilli VM, Richie JP Jr, Maiga M

and Muscat JE (2022) Prevalence and

determinants of meeting minimum

dietary diversity among children aged

6–23 months in three sub-Saharan

African Countries: The Demographic

and Health Surveys, 2019–2020.

Front. Public Health 10:846049.

doi: 10.3389/fpubh.2022.846049

Richie, Maiga and Muscat. This is an

open-access article distributed under

the terms of the Creative Commons

Attribution License (CC BY). The use,

distribution or reproduction in other

forums is permitted, provided the

original author(s) and the copyright

owner(s) are credited and that the

original publication in this journal is

cited, in accordance with accepted

academic practice. No use, distribution

or reproduction is permitted which

does not comply with these terms.

Prevalence and determinants of

meeting minimum dietary

diversity among children aged

6–23 months in three

sub-Saharan African Countries:

The Demographic and Health

Surveys, 2019–2020

Djibril M. Ba1*, Paddy Ssentongo1, Xiang Gao2,3,

Vernon M. Chinchilli1, John P. Richie Jr.1, Mamoudou Maiga4

and Joshua E. Muscat1

1Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, United States,

2Department of Nutritional Sciences, Penn State University, State College, PA, United States,

3Department of Nutrition and Food Hygiene, School of Public Health, Fudan University, Shanghai,

China, 4Northwestern University, Department of Biomedical Engineering, Evanston, IL, United States

Background: Dietary diversity is an indicator of nutritional adequacy, which

plays a signiﬁcant role in child growth and development. Lack of adequate

nutrition is associated with suboptimal brain development, lower school

performance, and increased risk of mortality and chronic diseases. We aimed

to determine the prevalence and determinants of meeting minimum dietary

diversity (MDD), deﬁned as consuming at least ﬁve out of eight basic food

groups in the previous 24-h in three sub-Saharan African countries.

Methods: A weighted population-based cross-sectional study was conducted

using the most recent Demographic and Health Surveys (DHS). MDD data

were available between 2019 and 2020 for three sub-Saharan African countries

(Gambia, Liberia, and Rwanda). The study population included 5,832 children

aged 6–23 months. A multivariable logistic regression model was developed

to identify independent factors associated with meeting MDD.

Results: Overall, the weighted prevalence of children who met the MDD was

23.2% (95% CI: 21.7–24.8%), ranging from 8.6% in Liberia to 34.4% in Rwanda.

Independent factors associated with meeting MDD were: age of the child (OR)

=1.96, 95% CI: 1.61, 2.39 for 12–17 months vs. 6–11 months], mothers from

highest households’ wealth status (OR =1.86, 95% CI: 1.45–2.39) compared

with the lowest,and mothers with secondary/higher education (OR =1.69,

95% CI: 1.35–2.12) compared with those with no education. Mothers who were

employed, had access to a radio, and those who visited a healthcare facility in

the last 12 months were more likely to meet the MDD. There was no signiﬁcant

association between the child’s sex and the odds of fulﬁlling the MDD.

Frontiers in Public Health 01 frontiersin.org

Ba et al. 10.3389/fpubh.2022.846049

Conclusions: There is substantial heterogeneity in the prevalence of MDD

in these three sub-Saharan African countries. Lack of food availability or

aordability may play a signiﬁcant role in the low prevalence of MDD.

The present analysis suggests that policies that will eectively increase the

prevalence of meeting MDD should target poor households with appropriate

materials or ﬁnancial assistance and mothers with lower literacy. Public health

interventions working with sectors such as education and radio stations to

promote health education about the beneﬁts of diverse diets is a critical step

toward improving MDD in sub-Saharan Africa and preventing undernutrition.

KEYWORDS

sub-Saharan Africa, dietary diversity, children, nutrition, DHS

Introduction

Undernutrition has decreased globally but remains endemic

in several regions such as southeastern Asia and sub-Saharan

Africa (SSA) (1, 2). Between 2000 and 2020, the number of

children aﬀected by stunting under age 5 worldwide declined

from 203.6 million to 149.2 million (3). However, during the

same time, the numbers have increased at an alarming rate in

SSA—from 22.8 million to 29.3 million (3). Child undernutrition

is an important cause of preventable disease burden of public

health signiﬁcance aﬀecting children, speciﬁcally those living in

SSA (4). Lack of adequate nutrition is associated with inadequate

brain development, lower school performance, increased risk

of mortality, and chronic diseases (5). According to the United

Nations Children’s Fund (UNICEF), about 3.1 million children

die from undernutrition each year (6). Globally, in 2020,

approximately 45.4 million children under age 5 were wasted

and 38.9 million were overweight (7). According to the WHO,

the risk of a child dying before reaching 5 years of age in

Africa is nearly 8 times higher than in Europe (76.5 per 1,000

live births vs. 9.6 per 1,000 live births) (8). Child dietary

diversity has been shown to be positively associated with the

mean micronutrient adequacy of the diet (9, 10). Therefore, the

minimum dietary diversity (MDD) can be eﬀective in assessing

a population-level picture of infant and young child diet

quality and appropriate complementary feeding practices in low

resource settings such as SSA. Enhanced child feeding practices

by providing adequately diversiﬁed food such as meeting MDD

can result in improved energy and nutrient intake, which can

lead to better nutritional status and children’s overall health and

well-being (11).

The MDD score is a population-level indicator developed

by the World Health Organization (WHO) to assess diet

diversity as part of infant and young child feeding (IYCF)

practices among children 6–23 months old (12). The WHO

has recommended that a child consumes the MDD of ≥5

of 8 pre-deﬁned food groups during the previous 24-h to

meet daily energy and essential nutrients requirements (13).

Diversiﬁed diet assists children to have the proper nutrients

needed to maintain optimal child growth and development

during critical periods (14, 15). A diverse diet is more likely

to meet both macro-and micronutrient needs for human

health (16).

According to previous studies, sociodemographic-economic

factors such as household wealth index (17–20), maternal age

(20), maternal education (18, 20, 21) maternal employment

status (20, 22, 23), contact with health care facility (21), place

of residence (22, 24), and exposure to mass media such as

radio (17, 18, 20) have been suggested to aﬀect MDD among

children aged 6–23 months in low-and middle-income countries

(LMICs) including SSA. In addition, child factor such as age has

also been associated with MDD in SSA (19, 20, 24). To improve

the proportion of children fed with a diet meeting MDD in SSA,

it is essential to fully understand regional and country-speciﬁc

variations in the prevalence of MDD and associated factors. Such

knowledge will assist in putting in place regional initiatives to

prioritize intervention strategies for the most at-risk countries in

SSA and assist stakeholders to adequately identifying potential

contributing factors for the low prevalence of meeting MDD.

However, these estimates are lacking because most previous

studies that have examined the determinants of meeting MDD in

SSA such as access to media, level of education, and wealth status

were mainly limited to individual countries such as Ethiopia

(17, 25, 26). Thus, we aimed to ﬁll this critical gap in our

knowledge by conducting a multi-country population-based

cross-sectional study of the prevalence of meeting MDD in three

combined SSA countries; and examining the associated socio-

demographic-economic factors using the available and most

recent Demographic and Health Surveys (DHS) data from 2019–

2020.

Frontiers in Public Health 02 frontiersin.org

Ba et al. 10.3389/fpubh.2022.846049

Methods

Data source and participants

For the present cross-sectional study, we included all SSA

countries that participated in the DHS most recent years (2019–

2020) and collected data on MDD among children aged 6–

23 months old. There was a total of three countries that

had conducted DHS surveys in the years since 2019 and

had asked mothers about the types of food their child had

consumed during the day or night before the interview. These

countries included Gambia, Liberia, and Rwanda. The mean

response rate across surveys was 97.9% (range, 99–97.7%). This

study followed the Strengthening the Reporting of Observation

Studies in Epidemiology (STROBE) reporting guideline (27).

Each host country collected data in coordination with ICF

International, a global consulting technology services company

located in Rockville, MD (28). The DHS surveys are nationally

representative household surveys supported by the US Agency

for International Development (USAID) for over 30 years. The

DHS surveys data included over 300 surveys conducted in more

than 90 World Bank-deﬁned LMICs worldwide.

The surveys used multistage cluster sampling and a

stratiﬁed sampling design to collect detailed information

such as sociodemographic characteristics, health behaviors,

child’s health and nutrition indicators, HIV and AIDS, and

reproductive health (29, 30). The ﬁrst stage involves dividing

the country into geographic regions. Then within these regions,

populations are stratiﬁed either by urban or rural areas. The

primary sampling units (PSUs) were selected with a probability

proportional to the size within each stratum. All households

within the cluster were listed in the second stage of sampling,

and approximately 25 households were randomly selected for an

interview using equal probability systematic sampling.

The children’s records or kid’s records (KR) DHS datasets

were used for the present study. According to the DHS guideline

for assessing MDD among children (https://dhsprogram.co

m/data/Guide-to-DHS-Statistics/Minimum_Dietary_Diversity.

htm), the present weighted analysis was limited to the last-born

children aged 6–23 months who were living with their mothers

and fed with an MDD during the day or night preceding the

survey (n=5,832).

Study variables

Outcome variables

The MDD is a population-level indicator designed by the

WHO to assess diet diversity among children 6–23 months old.

This indicator is one of the eight IYCF indicators developed

by the WHO to provide simple, valid, and reliable metrics

for determining IYCF practices (31). MDD data are collected

from a questionnaire administrated to the child’s mothers or

caregivers as part of the IYCF module. Based on June 2017 expert

consultation, the WHO updated the version of MDD-7 (7 food

groups) to MDD-8 to reﬂect the inclusion of breast milk as

an 8th food group. Therefore, the criterion for meeting MDD

changed from 4 of 7 groups to 5 of 8 groups (32). The outcome

of interest for the present study was the proportion of children’s

diets meeting MDD during the previous day. According to the

most recent WHO (13) and DHS (33), we deﬁned meeting

MDD among children aged 6–23 months as at least 5 out of 8

food groups fed during the day or night preceding the survey.

The components of the 8 food groups included: (1) breastmilk,

(2) grains, roots, and tubers, (3) legumes and nuts, (4) dairy

products (infant formula, milk, yogurt, cheese), (5) ﬂesh foods

(meat, ﬁsh, poultry, and liver/organ meats), (6) eggs, (7) vitamin

A-rich fruits and vegetables, (8) other fruits and vegetables. The

response options for each food group were 1 for “consumed”

and 0 for not “consumed.” A cumulative score was calculated by

combining the scores of all the food groups. A binary outcome

variable for meeting an MDD was created by assigning “1” for

children who consumed ≥5 out of 8 food groups and “0” for

those who consumed <5 food groups (18).

Explanatory variables

We selected country of residence, and child and maternal

factors as potential determinants because they have been shown

to be correlated with MDD (17, 18, 34). The child’s factors

included the child’s age and sex. The maternal factors included

age, antenatal care visits (ANC), household wealth index

status, educational status, marital status, place of residence,

employment status, household owning a radio, household

owning a television, and if visited a healthcare facility in the

last 12 months. Both child and maternal factors were collected

through self-report questionnaires. Wealth index quintiles were

determined using a principal component analysis approach of

household assets (household ownership of several items such as

television, car, radio, and other wealth-related characteristics).

Detailed information on determining wealth index quintiles

has been described elsewhere (35). The wealth index was

recategorized from quintiles into three categories by combining

the poorest and poorer into one category (called “lowest”);

middle wealth level into the second category (called “middle”);

and richer and richest into the third category (called “highest”),

as done in previous studies (36–38). We also recategorized

maternal age from a continuous scale into three groups for this

study (15–29, 30–39, and 40–49 years old).

Statistical analysis

We performed statistical analyses using SAS statistical

software version 9.4 (SAS Institute, Cary, NC, USA) and

R version 3.4.3 (R Foundation for Statistical Computing,

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Ba et al. 10.3389/fpubh.2022.846049

Vienna, Austria). Consistent with the DHS guideline for

analyzing the DHS data and to ensure that the estimates were

nationally representative, all analyses were conducted using

appropriate survey weights, clustering, and stratiﬁcation to

account for the complex sampling design (39). Univariable

analyses were performed using frequency distributions for

categorical variables to describe the characteristics of the study

participants. The prevalence of meeting MDD was calculated

as the number of children who met the MDD divided by the

total number of children in that category multiplied by 100%.

Multivariable logistic regression models (proc surveylogistic;

SAS institute) were used to examine each independent factor’s

association with meeting MDD. A stratiﬁed analysis was also

conducted to examine the prevalence of each of the 8 nutrient-

rich food groups described above by country. In addition, to

better understand between-country diﬀerences, we also analyzed

each demographic/social factor of MDD stratiﬁed by country.

A Variance Inﬂation Factor (VIF) was performed to measure

the degree of multicollinearity among independent variables,

which did not indicate any substantial multicollinearity from

the full adjusted model, with VIF values of 3 or less. Among

our selected factors, 8 participants had missing data for ANC

visits, 157 participants for access to a radio, and 157 participants

for access to a TV. Considering that the proportion of missing

data was very low (2.6%), a complete case analysis approach

was adopted. To test the robustness of our results, we also

conducted a sensitivity analysis using a multivariable binomial

regression in which the outcome variable was the number

of food groups (numerator) divided by eight (denominator).

Descriptive statistics are presented as the weighted prevalence of

meeting MDD, and the multivariable logistic regression results

are presented as adjusted odds ratios (OR) with 95% conﬁdence

intervals (CIs). Statistical tests were reported as signiﬁcant at

p-values <0.05, and all p-values were 2-sided.

Ethical considerations

Each country’s procedures and questionnaires for standard

DHS surveys were reviewed and approved by the ICF

International Institutional Review Board (IRB) and the IRBs

of each host country. Before the survey, written or oral

informed consent was obtained from each participant or proxy.

Survey participants were not coerced into participation (40),

and all data are completely de-identiﬁed with no names or

household addresses in the data ﬁles. Thus, no further IRB

approval was needed by the authors’ institutions of the present

manuscript. Details on the ethical matters are described in

the DHS methodology, protecting the Privacy of DHS Survey

Respondents (41).

Results

Sociodemographic characteristics of the

participants

A total of 5,832 children aged 6–23 months from three

SSA who live with their mothers were included in this analysis

(Table 1). The mean age (SE) of the children was 14.2 (0.01)

months. The majority of the children were between 6–11 months

and were males (51.0%). More than one-half of these children’s

mothers were younger (15–29 years old) (54.5%), had four or

more antenatal care visits than <4 (69.7%), and were mostly

from the lowest household wealth index status (44.1%) than the

middle and highest. In addition, more than one-half of mothers

had access to a radio (51.0%), visited a healthcare facility in the

last 12 months (82.5%), lived in rural areas (57.4%), and were

employed (63.6%) (Table 2).

Prevalence of meeting MDD in these SSA

countries

Overall, the weighted prevalence of children who met the

MDD was 23.2% (95% CI: 21.7%-24.8%), ranging from 8.6%

in Liberia to 34.4% in Rwanda (Table 1). The prevalence of

meeting MDD among children fed during the day or night

preceding the survey was higher among older children aged

12–17 months (26.7%) and 18–23 months (27.2%) compared

to aged 6–11 months (16.5%) and males (23.6%) compared

to female (22.9%). In addition, maternal factors such as older

(40–49 years old) age (26.7%), higher wealth status (31.8%),

secondary/higher education (28.7%), employment, access to a

radio, and visited healthcare facility in the past 12 months had

the highest prevalence of meeting MDD (Table 2).

Country-stratiﬁed analysis (Supplementary Table 1)

indicated that the prevalence of meeting MDD also varied

widely between countries in relation to diﬀerent maternal

factors such as ANC visits, household wealth status, education

level, marital status, employment status, access to a radio, and

visited healthcare facility in the last 12 months. For all countries,

children whose mothers had four or more ANC visits, had the

highest household wealth status, were married/living with a

partner, were currently employed, had access to a radio, and

visited a healthcare facility in the last 12 months had the highest

prevalence of meeting MDD consistently. Liberia and Gambia

had the highest prevalence of meeting MDD among mothers

with secondary/higher education regarding the educational

level. For Rwanda, mothers with primary education had the

highest prevalence of fulﬁlling the MDD. For all countries,

children aged 12–17 months consistently had the highest

prevalence of meeting MDD.

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Ba et al. 10.3389/fpubh.2022.846049

TABLE 1 Background characteristics of the weighted survey participants, the prevalence of meeting minimum dietary diversity by countr y and

survey year (N=5,832).

All participants Minimum dietary diversity

Countries Survey year Response rate (%) Na(%b)Nc(%)

Overall 5,832 1,356 (23.3)

Liberia 2019–2020 99 1,360 (23.3) 117 (8.6)

Gambia 2019–2020 97 2,109 (36.2) 425 (20.2)

Rwanda 2019–2020 97.7 2,363 (40.5) 814 (34.4)

Na, Weighted sample size of the combined dataset that is represented by that survey for each country.

%b, The % of the combined dataset represented by that survey.

Nc, Prevalence of minimum dietary diversity.

Figure 1 shows the prevalence of each of the 8 nutrient-

rich food groups included in the MDD stratiﬁed by country.

There was disparity regarding the 8 nutrients-rich food groups

across countries. Rwanda had the highest prevalence of

breastmilk, legumes/nuts, and vitamin A-rich fruits/vegetable

consumption. Interestingly, the prevalence of receiving protein

sources (eggs), dairy products, and other fruits/vegetables was

lower in all countries than breastmilk, legumes/nuts, ﬂesh

foods, grain/roots/tubes, and vitamin A-rich fruits/vegetables

that contribute to low MDD. In addition, eggs were the least food

group consumed in all countries. Breastmilk consumption and

grains/roots/tubes were consistently higher in all countries than

in other food groups (Figure 1).

Factors associated with meeting MDD

The babies aged 12–17 months were almost 2 times more

likely to meet MDD (OR =1.96; 95% CI: 1.61, 2.39, p<

0.001) and aged 18–23 months (OR =1.92; 95% CI: 1.58,

2.33, p<0.001) when compared to those aged 6–11 months

(Table 2). The respondents from the households whose wealth

index were middle (OR =1.45; 95% CI: 1.16, 1.81, p=

0.001) and highest (OR =1.86; 95% CI: 1.45, 2.39, p<0.001)

had greater odds to meet MDD than those from the lowest

(Table 2). The babies whose mothers had secondary/higher

were almost 2 times more likely to meet MDD (OR =1.69;

95% CI: 1.35, 2.12, p<0.001) compared to those with no

formal education (Table 2). Furthermore, the babies whose

mothers had employment had higher likelihood to achieve

MDD (OR =1.20; 95% CI: 1.01, 1.44, p=0.04) than those

from mothers who had no employment (Table 2). The babies

whose mothers had a radio in the households had higher

odds to meet MDD (OR =1.30; 95% CI: 1.09, 1.56, p=

0.004) than those who did not have a radio (Table 2). Lastly,

children whose mothers visited a healthcare facility in the

last 12 months were almost 2 times more likely to meet

MDD (OR =1.57; 95% CI: 1.27, 1.92, p<0.001) (Table 2).

Interestingly, we did not observe a signiﬁcant association

between the child’s sex and the odds of fulﬁlling the MDD.

These results remained consistent in the sensitivity analysis

using multivariable binomial regression.

Discussion

The purpose of this study was to conduct a population-based

cross-sectional study to determine the prevalence of meeting

MDD in three combined SSA countries and the associated socio-

demographic-economic factors. Our pooled results showed that

the mean of the weighted prevalence of children 6–23 months

who met the MDD was low (23%) in these three SSA countries

and exhibited substantial between-country variation. The low

prevalence of meeting MDD among children in these low-

resource countries is concerning and has the potential to

increase the risk of mortality and chronic diseases in the future.

Disparities due to wealth are signiﬁcant, and children’s diets

are more likely to meet MDD in wealthier households. More

importantly, children whose mothers had more education, were

employed, had access to a radio, and visited healthcare facilities

in the last 12 months were more likely to meet the MDD.

The child’s age was also signiﬁcantly associated with meeting

MDD. We found a similar non-signiﬁcant trend for access to a

TV, which could be due to a smaller proportion of households

owning a TV. Conversely, we did not observe any signiﬁcant

associations between a child’s sex and the odds of meeting

MDD. This study showed disparity regarding the 8 nutrients-

rich food groups across these three SSA countries. Protein

sources such as eggs were the least food group consumed in

all countries.

The observed low prevalence of meeting MDD in this study

is consistent with a previous study conducted in Ethiopia (17).

Lack of food availability or aﬀordability may play a signiﬁcant

role in the low prevalence of meeting MDD observed in

this study. Our ﬁnding agrees with previous studies that also

indicated a signiﬁcant positive association between a child’s age

and meeting MDD (18, 42, 43). A potential explanation for

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Ba et al. 10.3389/fpubh.2022.846049

TABLE 2 Background characteristics of the weighted survey participants, the prevalence of meeting minimum dietary diversity, and the

multivariable-adjusted odds ratio (N=5,832).

All participants Minimum dietary diversity Multivariable-adjusted analysis

Characteristics Na(%b)Nc(%) (OR) (95% CI) p-value

Child characteristics

Age of child

6–11 months 2,070 (35.5) 342 (16.5) ref.

12–17 months 2,020 (34.6) 539 (26.7) 1.96 (1.61, 2.39) <0.001

18–23 months 1,742 (30.0) 474 (27.2) 1.92 (1.58, 2.33) <0.001

Sex of child

Male 2,958 (50.7) 697 (23.6) ref.

Female 2,874 (49.3) 658 (22.9) 0.97 (0.83, 1.15) 0.75

Maternal factors

Age groups

15–29 3,176 (54.5) 675 (21.3) ref.

30–39 2,173 (37.3) 551 (25.4) 1.05 (0.88, 1.25) 0.57

40–49 483 (8.3) 129 (26.7) 1.16 (0.87, 1.55) 0.32

ANC visits

<4 1,768 (30.4) 491 (27.8) ref.

≥4 4,059 (69.7) 864 (21.3) 0.97 (0.81, 1.17) 0.78

Wealth index status

Lowest 2,572 (44.1) 412 (16.0) ref.

Middle 1,177 (20.2) 281 (23.9) 1.45 (1.16, 1.81) 0.001

Highest 2,083 (35.7) 662 (31.8) 1.86 (1.45, 2.39) <0.001

Place of residence

Urban 2,486 (42.6) 576 (23.2) ref.

Rural 3,346 (57.4) 779 (23.3) 0.90 (0.71, 1.14) 0.37

Maternal education

No education 1,617 (27.7) 230 (14.2) ref.

Primary 2,294 (39.3) 573 (25.0) 1.14 (0.91, 1.43) 0.24

Secondary/Higher 1,921 (32.9) 552 (28.7) 1.69 (1.35, 2.12) <0.001

Marital status

Never married 700 (12.0) 131 (18.7) ref.

Married/Living with partner 4,848 (83.1) 1,161 (23.9) 1.09 (0.81, 1.47) 0.55

Widowed/Divorced/Separated 284 (4.9) 63 (22.2) 1.13 (0.71, 1.78) 0.61

Maternal employment

No 2,125 (36.5) 423 (19.9) ref.

Yes 3,707 (63.6) 932 (25.1) 1.20 (1.01, 1.44) 0.04

Household has radio

No 2,790 (49.1) 560 (20.1) ref.

Yes 2,887 (50.9) 765 (26.5) 1.30 (1.09, 1.56) 0.004

Household has television

No 3,887 (68.5) 851 (21.9) ref.

Yes 1,791 (31.5) 474 (26.5) 1.00 (0.78, 1.29) 0.99

Visited healthcare facility last 12 months

No 1,020 (17.5) 169 (16.6) ref.

Yes 4,812 (82.5) 1,186 (24.6) 1.57 (1.27, 1.92) <0.001

ANC, Antenatal care.

Na, Weighted sample size of the combined dataset.

%b, The % of the combined dataset.

Nc, Prevalence of meeting minimum dietary diversity.

Ref, reference.

Model fully adjusted for country of residence, age of the child (categorical), sex of child (male/female), age of mother (categorical), antenatal care visits (<4/≥4), education status

(categorical), marital status (categorical), wealth index status (categorical), place of residence (urban/rural), employment status (yes/no), household having a radio (yes/no), household

having a television (yes/no), visited health care facility in the last 12 months (yes/no).

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Ba et al. 10.3389/fpubh.2022.846049

FIGURE 1

Weighted prevalence of intake of 8 nutrient-rich food groups for children 6–23 months.

this association could be due to older children’s willingness

to accept diverse foods with diﬀerent tastes and textures and

their familiarity with foods than younger children (18, 44). The

positive association between wealthier households and meeting

MDD observed in this study is consistent with the ﬁndings

from previous studies conducted in Ethiopia (17) and Indonesia

(18). Consistent with earlier studies from other LMICs (18–

20, 42), we found that mothers with higher educational levels

were more likely to feed their children with more diversiﬁed

foods. Socioeconomic inequalities represent a major threat

to optimal feeding practices (45). It postulated that poorer

households’ factors and lack of maternal education regarding an

adequate diet for young children could drive these disparities

in complementary feeding practices. Therefore, closing the

gap in dietary inequalities between countries is critical to

preventing long-term socioeconomic and health inequalities.

Highly educated mothers might have access to more resources

that promote the beneﬁts of a diversiﬁed diet and a better

understanding of nutritional health education messages (18).

This study also found that respondents who had exposure to

mass media (radio) had greater odds of achieving MDD. The

media such as national radio stations are usually considered to

be a reliable source of health and nutrition-related information

in low-resource countries, thus its messages are more likely

to be embraced (20, 46). This is a similar ﬁnding to a

study conducted in Ethiopia (17). Additionally, our ﬁnding

of a signiﬁcant association between maternal employment and

meeting MDD is consistent with previous studies (20–22).

Lastly, our observed positive association between mothers who

visited a healthcare facility in the last 12 months and the odds of

meeting MDD is also consistent with a previous study conducted

in Nigeria (21).

Public health recommendations

The Sustainable Development Goals, part of the call for

action toward appropriate diets for children, aim to address

goals 2 (zero hunger) and 3 (good health and well-being) (47).

Implementing policies and programs to reduce wealth-related

inequalities is essential for optimal child nutrition. Recent

estimates suggest that more than 11 million cases of stunting

could have been averted if the proportion of children’s diets

meeting MDD was 90% (48). However, in the present study

from these three SSA countries, the rates of meeting MDD did

not reach the threshold of 50%. Previous studies have observed

the critical role of dietary diversity in impacting the relationship

with child anthropometry (49, 50).

MDD is a simple yet valid and reliable population-level

indicator of IYCF practices and is critical for assessing national

and subnational comparisons, and is relevant for identifying

populations at risk and targeting interventions. Our current

analysis suggests that policies that will eﬀectively increase the

prevalence of meeting MDD should target poor households with

appropriate materials or ﬁnancial assistance and mothers with

lower literacy. In a recent pooled analysis of 80 low- and middle-

income countries, dietary diversity was higher when absolute

household income exceeded ∼US$20,000 (51). Additionally,

public health interventions working with other sectors such

as education and radio stations to promote health education

about the beneﬁts of diverse diets (18), especially among

teenage girls, are critically needed. Targeting teenage girls with

nutrition-related interventions before becoming pregnant may

signiﬁcantly increase the prevalence of meeting MDD. More

importantly, providing ﬁnancial assistance to poorer households

or the availability of food pantries may also play an essential

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Ba et al. 10.3389/fpubh.2022.846049

role in ensuring each child consumes adequately diverse foods

to meet their nutritional requirements (34).

Study strengths and limitations

The strength of this study is the analysis of a nationally

representative sample of children aged 6–23 months from three

SSA countries using 2019–2020 DHS data. To the best of our

knowledge, this is one of the few comprehensive studies to

investigate the prevalence and determinants of meeting MDD

using the most recent DHS data across multiple SSA countries

with high response rates. In addition, we used the most updated

MDD indicator with eight food groups, which is a valid and

reliable metric for assessing IYCF feeding practices at the

population level developed by the WHO (9).

Notwithstanding, the present study has a few limitations

that are worth mentioning. First, the cross-sectional nature of

the survey does not allow for determining causality. Secondly,

almost all low-income countries are found in SSA. Most recent

MDD data was limited to only three of the 48 countries in SSA,

and thus, our ﬁndings may lack external validity for other SSA

low-income countries. Moreover, MDD was based on maternal

recall, which may be subject to recall bias and social desirability

(18, 25). Additionally, this study did not adjust for total energy

due to a lack of data on calorie consumption from the DHS

database. Lastly, a single 24-diet recall is not considered to be

representative of habitual diet at an individual level. Because it

doesn’t account for day-to-day variation.

Conclusions

In this study using three SSA countries, few children

were fed a diet that met MDD on the day of recall.

Interestingly, the prevalence of eggs, dairy products, and

other fruits/vegetables being consumed remained very low in

all countries. Maternal education, household wealth status,

employment status, access to a radio, visited healthcare facilities

in the last 12 months, and age of the child was the signiﬁcant

determinant of meeting the WHO recommended feeding

practice indicator of MDD among the youngest children in

these three SSA countries. We did not observe a signiﬁcant

association between the child’s sex and the odds of fulﬁlling

the MDD. The ﬁndings highlighted the need to target mothers,

especially those with low education and lower household wealth

status, through health education about the importance of

adequately diversiﬁed foods and ﬁnancial assistance to ensure

optimal child growth in these low-resource countries and

prevent undernutrition.

Data availability statement

Publicly available datasets were analyzed in this study. This

data can be found at: https://dhsprogram.com/data/.

Author contributions

Designed research (project conception, development of

overall research plan, and study oversight) and analyzed

data, or performed statistical analysis: DB. Wrote the

ﬁrst draft of the manuscript: DB and PS. All authors

reviewed and commented on subsequent drafts of the

manuscript and have read and approved the ﬁnal version of

the manuscript.

Conﬂict of interest

The authors declare that the research was conducted in the

absence of any commercial or ﬁnancial relationships that could

be construed as a potential conﬂict of interest.

Publisher’s note

All claims expressed in this article are solely those of the

authors and do not necessarily represent those of their aﬃliated

organizations, or those of the publisher, the editors and the

reviewers. Any product that may be evaluated in this article, or

claim that may be made by its manufacturer, is not guaranteed

or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found

online at: https://www.frontiersin.org/articles/10.3389/fpubh.

2022.846049/full#supplementary-material

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Frontiers in Public Health 10 frontiersin.org

TYPE Original Research

PUBLISHED 14 October 2022

DOI 10.3389/fpubh.2022.969922

OPEN ACCESS

EDITED BY

Khadijeh Irandoust,

Imam Khomeini International

University, Iran

REVIEWED BY

Luis Felipe Reynoso Sánchez,

Universidad Autónoma de

Occidente, Mexico

Maghsoud Nabilpour,

University of Mohaghegh Ardabili, Iran

*CORRESPONDENCE

José Antonio Quesada

jquesada@umh.es

SPECIALTY SECTION

This article was submitted to

Children and Health,

a section of the journal

Frontiers in Public Health

RECEIVED 15 June 2022

ACCEPTED 26 September 2022

PUBLISHED 14 October 2022

CITATION

Sánchez-Ferrer F, Cervantes-García E,

Gavilán-Martín C, Quesada JA,

Cortes-Castell E and Nso-Roca AP

(2022) Emotional impact on children

during home conﬁnement in Spain.

Front. Public Health 10:969922.

doi: 10.3389/fpubh.2022.969922

Cervantes-García, Gavilán-Martín,

Quesada, Cortes-Castell and

Nso-Roca. This is an open-access

article distributed under the terms of

the Creative Commons Attribution

License (CC BY). The use, distribution

or reproduction in other forums is

permitted, provided the original

author(s) and the copyright owner(s)

are credited and that the original

publication in this journal is cited, in

accordance with accepted academic

practice. No use, distribution or

reproduction is permitted which does

not comply with these terms.

Emotional impact on children

during home conﬁnement in

Spain

Francisco Sánchez-Ferrer1,2, Evelyn Cervantes-García1,

César Gavilán-Martín1,2, José Antonio Quesada3*,

Ernesto Cortes-Castell2and Ana Pilar Nso-Roca1,2

1San Juan de Alicante University Hospital, Sant Joan d’Alacant, Spain, 2Department of

Pharmacology, Pediatrics and Organic Chemistry, Miguel Hernández University Medical School,

Miguel Hernández University of Elche, Sant Joan d’Alacant, Spain, 3Department of Clinical Medicine,

Miguel Hernández University Medical School, Miguel Hernández University of Elche, Sant Joan

d’Alacant, Spain

Introduction: The COVID-19 pandemic has brought about important changes.

On March 14, 2020, a strict home conﬁnement was decreed in Spain. Children

did not attend school and were not allowed to leave their homes. The aim of

this study was to determine the emotional state of these children, as well as

associated factors.

Material and methods: A cross-sectional descriptive study was conducted

using an online questionnaire sent by cell phone. This survey includes

sociodemographic items and questions concerning the emotional impact

of the lockdown. With the questions on emotions, two categories of

emotional state were established with the variables fear, irritability, sadness and

somatization: those who were less or more emotionally aected. A multivariate

logistic model was used to estimate the associations between the variables.

Results: A total of 3,890 responses were obtained. The mean age of the

children was 6.78 years (range 0 to 16). A score indicating poor emotional state

was reported by 40.12%. The multivariate logistic model for poor emotional

state was directly associated with having less appetite, sleep disturbances, and

with parents’ beliefs that their child will have diculties returning to normal

life after lockdown. A better emotional state was associated with being an only

child, access to outdoor spaces at home, having pets, and parents informing

their children about the pandemic using creative explanations.

Conclusions: During strict home conﬁnement, a considerable emotional

impact was observed in children as described by their parents. Speciﬁc

elements were associated with a better or poorer emotional state.

KEYWORDS

conﬁnement, COVID-19, emotional impact, sadness, irritability, children

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Sánchez-Ferrer et al. 10.3389/fpubh.2022.969922

Introduction

The outbreak of severe acute respiratory syndrome

coronavirus 2 (SARS-CoV-2), which was ﬁrst reported in

Wuhan, China, in December 2019, had a tremendous impact

initially in China and subsequently throughout the world. While

most patients infected with SARS-CoV-2 had mild illness, about

5% of patients experienced severe lung injury or multi-organ

dysfunction, resulting in a 1–4% case fatality rate (1).

Restrictive measures in the general population were

necessary to reduce the rate of virus transmission.

Quarantines and pandemic disasters have demonstrated

negative psychological eﬀects, including confusion, anger, and

post-traumatic distress (2,3).

During the ﬁrst outbreak in Europe in March 2020, a strict

lockdown took place in Spain with the population conﬁned

to their homes. Only essential work was permitted, and the

population was allowed to leave their homes only for basic

activities. In Spain, this strict lockdown was declared as of

March 13, 2020. In addition to schools being closed, children

were not allowed to leave their homes under any circumstances

(except to go to the doctor or to accompany their parents for

essential activities if they would have been left at home alone).

As of April 26, children were allowed to leave their homes

for a reduced period of time. Prior to COVID-19, a review in

The Lancet on quarantines revealed their broad and potentially

long-lasting negative psychological consequences (3). Another

general population study compared mental health during the

pandemic period and in the same time period 3 years prior. A

clear psychological deterioration was found, with an increase in

depression that was more pronounced in young adults (4).

Conﬁnements have produced an emotional impact on the

entire population (5) and children (6). The eﬀects of the

lockdown on emotional well-being have been perceived as

negative (3,7), with increased stress, anger, fear, and confusion

(8). In children, it has also been shown that the COVID-

19 pandemic has had a signiﬁcant psychological impact (9).

Children are frightened, nervous, sad, bored, and angry but

also feel safe, calm, and happy to be with their families (10).

Nonetheless, these negative feelings have been more prevalent

and can aﬀect the entire family (11). In adolescents, this has been

associated with depression and anxiety (12).

During the conﬁnement, daily routines have been altered,

such as sleep habits (13,14). These changes may have long-

term emotional eﬀects (15). Other habits, such as eating patterns,

have also undergone changes in this period (16). In addition,

activities that help improve the emotional health of young

people, such as exercise (17), physiotherapy, relaxation, and

academic performance, were restricted (18).

The emotional impact depends on many biological and

sociodemographic factors that must be taken into account (19).

The degree to which parents are aﬀected also inﬂuences their

children (20,21). These eﬀects on the family and children, as

well as their needs during the ﬁrst outbreak, were not taken into

consideration (22,23).

Studies on emotional health in children during the COVID-

19 pandemic have been conducted mainly in the Chinese

population (24). There are many methodological limitations in

the studies carried out, such as small sample sizes or being

performed after the period of conﬁnement with the resulting

recall bias, among other limitations (12).

The studies in children during this period of conﬁnement are

highly relevant because of the great emotional impact described

and because they enable us to determine the sociodemographic

characteristics of the children at greatest risk. In addition, there

are variables that may involve a greater emotional impact on

children, such as the direct or indirect consequences of COVID

in the family (23), the presence of some type of disability (24) or

having parents who are essential workers during the pandemic

(25). On the other hand, variables such as having pets (26)

or having outdoor access at home can be protective (17). This

information is important in order to be able to implement

measures to limit the eﬀects of future conﬁnement on the

emotional health of children.

The aim of this study was to assess the degree of emotional

impact on children as perceived by their parents during the

strict lockdown and to identify the factors associated with

emotional state.

We analyzed the most common sociodemographic variables,

paying special attention to housing conditions (due to the

situation of conﬁnement) and examined several dimensions that

may be associated with emotional state, such as communication

with the children, parental perception of after eﬀects, the eﬀect

on illnesses or the physical repercussions on the children.

Materials and methods

Participants

A cross-sectional descriptive study was carried out through

a questionnaire that was sent by instant messaging via cell

phone to parents for completion. There was no sample

selection. The inclusion criteria were residing in Spain and

agreeing to complete the questionnaire. The questionnaire

was available from April 22, 2020 to April 26, 2020. A

total of 3,890 questionnaires were collected during the

study period.

A panel of local experts met to construct a speciﬁc

questionnaire to study the eﬀect of the pandemic on children.

Given the exceptional nature of the situation, with strict

conﬁnement, the previously validated questionnaires were

considered unsuitable. To construct the questionnaire and select

the possible variables related to emotional states, previous

questionnaires that assess fear, anxiety and sadness were

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Sánchez-Ferrer et al. 10.3389/fpubh.2022.969922

consulted, such as the KIDSCREEN (27,28), the Liebowitz

social anxiety scale (29), the Spielberger State-Trait Anxiety

Inventory (STAI) (30,31) or the Emotional Eating Scale

Adapted for Children and Adolescents (EES-C) (32). Given the

relationship of this emotional situation with somatization (3,33)

it was also included as an emotional variable. The presence of

somatization signs was also included in the measurements due

to its relationship with the emotional state.

Patient and public involvement

It was not appropriate or possible to involve patients or the

public in the design, or conduct, or reporting, or dissemination

plans of our research.

Variables

The ﬁrst part includes the following variables: Age (years),

Sex (boy/girl), Autonomous community (Spanish province), Do

you have other children at home? (yes/no), Number of children

at home (number), Number of adults at home (number),

Location of home (no answer/urban/rural), Size of home

(no answer/less 60 m2/60–120 m2/more 120 m2), Outdoor

space at home (no answer/yes/no), Average academic grade

(no answer/excellence/very good/satisfactory/unsatisfactory),

Educational support (yes/no), Parents are health sector workers

(yes/no), Parents are law enforcement workers (yes/no),

Parents are other essential workers (yes/no), Have had Covid-

19 (yes/no), Pets in the home (yes/no), and Underlying

disease (yes/no).

Questionnaire

The questionnaire for families, developed by a local group

of experts, was divided into 5 dimensions with several questions

in each:

Communication: Do you feel that you have given your child

age-appropriate information (in words he/she can understand)

about what is happening? (yes/no/I am not sure), To what

extent have you given information to your child? (honest

including negative aspects/honest avoiding negative aspects/no

information), How have you approached the information

given to your child? (realistic information/information by

embellishing or misrepresenting the negative aspects/creative

information/no information).

Normality during and after the pandemic: Do you feel that

your child has accepted and adapted to the current situation?

(yes/no/I am not sure), Do you think your child might have

trouble returning to “normal” daily activities? (yes/no/I am

not sure).

Control of disease: Only answer this question if your child

has a medical condition. How do you think the conﬁnement has

aﬀected the condition? (negative/positive/no changes), During

this period, did you need to consult a medical professional

because you were concerned about any aspect of your child’s

health? (yes/no).

Non-emotional involvement: Do you feel that your child is

having trouble falling asleep or is sleeping worse than usual?

(yes/no/I am not sure), Do you think there have been changes

in your child’s appetite? (yes/no/I am not sure), Regarding

nutrition, do you feel that there have been changes in the quality

of the diet during this period? (improved/worse/no changes/I

am not sure), With regard to the time spent in front of screens

(video consoles, television, electronic tablets, cell phones, etc.),

indicate the average time spent daily by your child (in relation

to the current situation) (1/1–2/2–3/3–4/more than 4 h/does

not use).

Emotional involvement: Do you think your child has ever

felt sad (in relation to the current situation)? (yes/no/I am not

sure), Do you think your child has ever felt afraid (in relation

to the current situation)? (yes/no/I am not sure), Do you think

your child is more irritable? Example: more temper tantrums,

less obedient, more sensitive (yes/no/I am not sure), During

the conﬁnement period, has your child had symptoms such as

headache, abdominal pain, musculoskeletal pain, tiredness, etc.

for no apparent reason and without this type of pain being usual

previously? (somatization) (yes/no/I am not sure).

As a response variable, the dimension of emotional state

was constructed from 4 items (sadness, fear, irritability and

somatization) in the following way: A value of 1 is given to the

response “yes” and 0 to the response “no” in each of the items.

The total score for the response variable is the sum of all the

items, ranging between 0 and 4, with 4 being the worst emotional

state. It was grouped as scores of 3–4 vs. 0–2.

Statistical analysis

A descriptive analysis of all the variables was performed by

calculating frequencies for qualitative variables and minimum,

maximum, mean, and standard deviation for quantitative

variables. The factors associated with emotional state and type of

information given to the child were analyzed using contingency

tables applying the chi-squared test for qualitative variables and

comparison of the mean values for quantitative variables using

Student’s t-test.

To estimate the magnitude of the associations with poor

emotional state, multivariate logistic models were ﬁtted. The

total sample without missing data in the variables (n=1,501)

was randomly split into a training sample and a test sample at

a ratio of 2/3 and 1/3. The model was adjusted in the training

sample to arrive at an optimal model, applying the Homer-

Lemeshow calibration test. Odds ratios (OR) were estimated,

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Sánchez-Ferrer et al. 10.3389/fpubh.2022.969922

TABLE 1 Values of the variables analyzed in the total sample

(abbreviated table).

Variable N(%); mean ±SD

Mean age of children (years) 6.78 (3.24)

Sex (Male) 772 (51.4)

Only child 338 (22.5)

Mean number of children in the family 1.93 (0.78)

Mean number of adults 2.03 (0.48)

Urban housing 3,108 (85.6)

Living area >120 m21,061 (29.2)

Home with garden 1,732 (47.7)

Pets 1,152 (39.9)

Chronic illness 422 (10.8)

Sleep (worse) 1,689 (44.7)

Good emotional state (0–2) 1,349 (59.9)

N=1,501.

*Table of the complete description of all the variables analyzed in

Supplementary materials 1,2.

together with their 95% conﬁdence intervals. A stepwise variable

selection procedure based on the Akaike information criterion

was performed. A validation process was conducted on the

test sample, calculating the area under the ROC curve and its

95% conﬁdence interval, Alpha level 0.05. All analyses were

performed using R version 4.0.2.

Results

The general characteristics of the sample are shown in

Table 1. Women made up 48.6% of the sample, with a mean

age of 6.78 years. Most of the respondents were preschool-

age (36.3%) and school-age children (51.3%). The sample was

primarily urban (77.7%) but almost half of the sample owned

a house with a garden. Concerning the emotional state of the

children, 44.9% were afraid, 67.5% sad, 64.2% irritable, and

29.6% experienced somatization of an illness. According to the

constructed variable “emotional state,” in 33.8% this was poor

(presence of 3 or 4 variables) (abbreviated Table 1 and complete

tables in Supplementary materials 1,2).

Certain variables were signiﬁcantly associated (p<0.05)

with a poorer emotional state, such as not being an

only child, having sleep disturbances, not having a terrace

or garden, parents believing that they will have problems

returning to normal life after the pandemic, and giving

honest information about the situation were signiﬁcantly

related to a worse emotional state. These variables are

shown in Table 2 (abbreviated Table 2 and complete tables in

Supplementary materials 3,4).

The multivariate logistic model performed to explain poor

emotional state is shown in Table 3. Receiving information

through creative explanations (OR 0.22, CI 0.073–0.70), having

a home with a garden (OR 0.578, CI 0.35–1.00), being an only

child (OR 0.68, CI 0.45–0.98), children not asking about the

pandemic situation (OR 0.34, CI 0.24–0.48) or not having sleep

disturbances (OR 0.41, CI 0.30–0.57) are elements that were

associated with a better emotional state In contrast, not having

pets (OR 1.44, CI 1.04–1.97), having less appetite (OR 2.30,

CI 1.45–3.65), or parents who believe that life will not return

to normal after the pandemic (OR 2.72 CI 1.79–4.15) were

associated with a poor emotional state.

The model has an area under the ROC curve in the

test sample of 0.812 (95% CI: 0.773–0.850), good calibration

(Homer-Lemeshow test: p-value 0.713), and a success rate in the

test sample of 75.4% (95% CI: 0.773–0.850) (Table 3).

Discussion

The results of this study reveal the considerable emotional

impact on children during the lockdown, identifying factors

associated with a poor emotional state. Giving children

information using creative explanations, living in a home with

a garden, being an only child, and having pets were factors

associated with less emotional distress. Conversely, having less

appetite, disturbed sleep, or a parent who believes that the

situation will not return to normal after conﬁnement were

associated with a greater impact on the emotional state of

the child.

The period of strict home conﬁnement of children in Spain

in the spring of 2020 was one of the longest experienced.

Children were unable to leave their homes for 6 weeks.

We sought to quantify this impact by means of a

questionnaire for parents, in which they assessed the emotional

situation of their child as well as providing various medical and

sociodemographic variables. The start date of the survey was

just 4 days before the end of the lockdown (following 38 days

without leaving the home and up to the time when the lockdown

oﬃcially ended).

Emotional experience was subjectively assessed by the

parents through the items concerning their child’s perception

of sadness, fear, irritability, and physical symptoms. These

values were answered dichotomously (Yes or No). With these

data, we deﬁned the emotional state as “good” (score 0–2)

or “poor” (score 3–4). The ﬁndings indicate that conﬁnement

had an important eﬀect, with 40.1% having a poor emotional

state, with feelings of sadness and irritability experienced by

approximately two-thirds of the children. These data are data

are consistent with the existing literature (8,9), with no gender

diﬀerences found.

The emotional impact of the COVID-19 lockdown has also

been described in children, and in all cases the eﬀects are similar

to our results (10,11,21,25,26). These eﬀects have also been

studied in adolescents and adults (7) as well as in parents (20).

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Sánchez-Ferrer et al. 10.3389/fpubh.2022.969922

TABLE 2 Summarized bivariate analysis of the variables analyzed with respect to emotional state (good 0–2 negative emotions or bad 3–4 negative

emotions, including sadness, fear, irritability, and physical symptoms)**.

0–2 negative emotions 3–4 negative emotions

n%n%p-value

Information adapted

to the age of the

children

I have tried to be

honest with them

931 65.2% 496 34.8% <0.001

I have preferred not

to give information

63 85.1% 11 14.9%

Situation will

normalize after the

pandemic

Yes 922 72.3% 354 27.7% <0.001

No 72 32.0% 153 68.0%

Only child No 719 64.0% 405 36.0% 0.001

Yes 275 72.9% 102 27.1%

Type of information

given to the children

Realistic

information

695 65.2% 371 34.8% <0.001

Information

misrepresenting the

negative aspects

172 60.6% 112 39.4%

Creative

explanations

62 83.8% 12 16.2%

No information 65 84.4% 12 15.6%

Information adapted

to the age of the

children

Yes 931 65.2% 496 34.8% <0.001

No 63 85.1% 11 14.9%

Sleep disturbances Yes 284 47.9% 309 52.1% <0.001

No 710 78.2% 198 21.8%

Return to activity

after pandemic

Yes 261 51.3% 248 48.7% <0.001

No 733 73.9% 259 26.1%

Outdoor access at

home (garden or

terrace)

Yes 501 71.9% 196 28.1% <0.001

No 405 60.7% 262 39.3%

N=1,501.

**Table of the complete bivariate analysis of all variables analyzed in Supplementary materials 3,4.

Most of these studies show a negative emotional impact that is

greater in the younger population (5) and relatively smaller at

older ages.

Multivariate analysis indicated that having siblings in the

home increased emotional risk during the pandemic and could

be explained by greater parental stress and household turmoil

(21). Decreased appetite and sleep disturbances were also

associated with a poor emotional state (13,14,27). Both of these

elements are known to aﬀect emotional well-being (28).

Similarly, parents’ beliefs that their child may not be able to

return to normal life after the pandemic could be associated with

greater emotional distress, since it is the parents themselves who

value their children emotionally and are aware of the diﬃculties

they may have readapting to normal life after the lockdown.

By contrast, the existence of a garden at home was linked

to a better emotional state in children in that they can “leave”

the house to take a walk or to be in the sun, both elements

traditionally associated with happiness, as well as increased

access to physical exercise (18). In addition, having a garden was

associated with another key element for the protection of mental

health, namely, having greater economic resources (19). It is of

note that the size of the house showed no signiﬁcant association.

The connection observed between children having a good

emotional state and parents providing creative explanations

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Sánchez-Ferrer et al. 10.3389/fpubh.2022.969922

TABLE 3 Multivariate logistic model for poor emotional state (presence of 3–4 negative items).

Betha OR* CI 95% p-value

Type of information given to the child Realistic information 0 1

Information

misrepresenting the

negative aspects

0.05372 1.055 (0.712–1.565) 0.789

Creative explanations −1.48621 0.226 (0.073–0.700) 0.009

No information −0.58049 0.560 (0.227–1.378) 0.206

Appetite Has more 0 1

No change −0.30185 0.739 (0.510–1.072) 0.111

Has less 0.83570 2.306 (1.454–3.658) 0.001

Home with garden No answer 0 1

Yes −0.54739 0.578 (0.335–1.000) 0.049

No −0.10606 0.899 (0.525–1.542) 0.699

Sleep disturbance No −0.88301 0.414 (0.300–0.570) <0.001

Parent believes situation will not normalize No 1.00382 2.729 (1.791–4.157) <0.001

Only child Yes −0.40418 0.668 (0.453–0.983) 0.040

Pets in the home No 0.36440 1.440 (1.047–1.979) 0.024

Children ask about what is happening No −1.06831 0.344 (0.243–0.485) <0.001

Return to activity No −0.43769 0.646 (0.464–0.898) 0.009

Age 0.04036 1.041 (0.986–1.100) 0.148

Sex (Female) 0.16531 1.180 (0.867–1.605) 0.292

Training sample n=1,000; test sample n=501; number of children with a poor emotional state (3–4 items) in the training sample =347; area under the ROC curve in the test sample =

0.812 (95% CI 0.773–0.850). Homer-Lemeshow p-value =0.713; accuracy rate in the test sample =75.4%. Nagelkerke’s R2=0.339. Likelihood ratio chi-squared test =281.8 (p<0.001).

*Model adjusted for control of disease.

about the coronavirus could be could be due to the age of these

children. Younger children would normally be given imaginative

stories, while older children are given factual information

and would be more aﬀected. This coincides with studies

demonstrating a greater impact on older children. In our study,

the mean age of the children who did not receive information

was 2.26 years and those who did receive information was

6.76 years, with a signiﬁcant diﬀerence (p<0.001). Finally,

having pets in the home was associated with a good emotional

state. Research postulates that animals provide greater social

competence (29), which would be helpful to children in this

context. In our paper, the physical activity is not studied. It

is interesting that in other studies this physical activity (34)

does not aﬀect the emotional state (30). On the other hand,

Cognitive-Behavioral Therapy in adolescents with low academic

performance decreased their stress (31).

Recognizing that conﬁnement can have a detrimental eﬀect

on mental health, especially in certain conditions such as the

ones described above, provides incentives for measures to limit

this eﬀect, such as increased communication with parents,

information about the disease with age-appropriate information

and, of course, early access to mental health services (32). Public

health authorities must take into consideration these emotional

eﬀects, not prolonging the conﬁnement or quarantine for longer

than necessary (3).

Further research in this area can help to better understand

the factors associated with home conﬁnement and the degree

of emotional impact on children, which can be instrumental in

identifying those at higher risk and to implement interventions

to enhance emotional well-being in this more vulnerable group

and even to introduce preventive measures for potential future

home conﬁnements, as proposed by the Chinese government

(30). We believe it is of great interest to examine the

consequences of the recent lockdown through follow-up of

the child population during the post-pandemic period in the

long term.

As potential limitations of the study, it should be mentioned

that since this was an online questionnaire and there was no

statistical sampling, the sample may not accurately represent

the general pediatric population due to possible selection bias,

although the large sample size may reﬂect a wide variability in

the population. Moreover, the cross-sectional design prevents

establishing causal relationships. Another limitation is that the

scales used have not been validated in the pediatric population.

The authors did not believe that in the situation of strict

pandemic conﬁnement, the anxiety, depression or irritability

scales were appropriate, since they were validated in a context

other than strict pediatric conﬁnement. The questionnaire was

developed by an ad hoc panel of experts. Based on information

from other studies (33,35–41), and the opinion of the expert

Frontiers in Public Health 06 frontiersin.org

Sánchez-Ferrer et al. 10.3389/fpubh.2022.969922

panel, the diﬀerent dimensions were constructed to obtain a

questionnaire that would meet the objective of our study in

this particular context. Thus, the “emotional state” scale was

created from the emotions reported by the parents to each of the

questions in a dichotomous manner, which allows for simplicity

in the responses of the parents since the survey was online, but it

can be a limitation because it does not collect response gradient

as a Likert scale does. And so, the yes/no dichotomy can lead to

a loss of information.

As strengths, we highlight the large sample size and that

the data collection was carried out at the very end of the

lockdown, which limits recall bias and focuses responses on the

real experiences of the families during the lockdown.

Conclusions

During home conﬁnement in Spain, an elevated percentage

of children experienced important emotional eﬀects as perceived

by their parents. The factors associated with greater or lesser

emotional impact on children during strict home conﬁnement

that should be taken into account to reduce these negative eﬀects

in future conﬁnements are described.

Data availability statement

The original contributions presented in the study are

included in the article/Supplementary material, further inquiries

can be directed to the corresponding author/s.

Ethics statement

The studies involving human participants were reviewed and

approved by the San Juan de Alicante University Hospital Ethics

Committee. Verbal consent was obtained from the participants

legal guardian/next of kin. Written informed consent from

the participants legal guardian/next of kin was not required

to participate in this study in accordance with the national

legislation and the institutional requirements.

Author contributions

EC-G, JQ, CG-M, AN-R, FS, and EC-C: conception and

design of the study, data collection, analysis, interpretation,

drafting and critical revision of the manuscript, with

important intellectual contributions, and approval of the

ﬁnal draft for publication. All authors having revised

and discussed the manuscript, take responsibility, and

serve as guarantors for the accuracy and integrity of

the report.

Acknowledgments

The authors thank Maria Repice for their help with the

English version of the text.

Conﬂict of interest

The authors declare that the research was conducted in the

absence of any commercial or ﬁnancial relationships that could

be construed as a potential conﬂict of interest.

Publisher’s note

All claims expressed in this article are solely those of the

authors and do not necessarily represent those of their aﬃliated

organizations, or those of the publisher, the editors and the

reviewers. Any product that may be evaluated in this article, or

claim that may be made by its manufacturer, is not guaranteed

or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found

online at: https://www.frontiersin.org/articles/10.3389/fpubh.

2022.969922/full#supplementary-material

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Frontiers in Public Health 08 frontiersin.org

TYPE Original Research

PUBLISHED 02 February 2023

DOI 10.3389/fpubh.2023.1061251

OPEN ACCESS

EDITED BY

Songlin He,

Chongqing Medical University, China

REVIEWED BY

Xianliang Wang,

National Institute of Environmental

Health, China

Jonas Augusto Cardoso da Silveira,

Federal University of Paraná, Brazil

Meng Li,

Zhengzhou University, China

*CORRESPONDENCE

Zhonghai Zhu

zhuzhonghai@hotmail.com

Lingxia Zeng

tjzlx@mail.xjtu.edu.cn

†These authors have contributed equally to this

work

SPECIALTY SECTION

This article was submitted to

Children and Health,

a section of the journal

Frontiers in Public Health

RECEIVED 04 October 2022

ACCEPTED 16 January 2023

PUBLISHED 02 February 2023

CITATION

Tian J, Zhu Y, Liu S, Wang L, Qi Q, Deng Q,

Andegiorgish AK, Elhoumed M, Cheng Y,

Shen C, Zeng L and Zhu Z (2023) Associations

between life-course household wealth mobility

and adolescent physical growth, cognitive

development and emotional and behavioral

problems: A birth cohort in rural western China.

Front. Public Health 11:1061251.

doi: 10.3389/fpubh.2023.1061251

Andegiorgish, Elhoumed, Cheng, Shen, Zeng

and Zhu. This is an open-access article

distributed under the terms of the Creative

Commons Attribution License (CC BY). The use,

distribution or reproduction in other forums is

permitted, provided the original author(s) and

the copyright owner(s) are credited and that

the original publication in this journal is cited, in

accordance with accepted academic practice.

No use, distribution or reproduction is

permitted which does not comply with these

terms.

Associations between life-course

household wealth mobility and

adolescent physical growth,

cognitive development and

emotional and behavioral

problems: A birth cohort in rural

western China

Jiaxin Tian1†, Yingze Zhu1† , Shuang Liu2, Liang Wang1, Qi Qi1,

Qiwei Deng1, Amanuel Kidane Andegiorgish1, Mohamed Elhoumed1,

Yue Cheng3, Chi Shen4, Lingxia Zeng1,5*and Zhonghai Zhu1*

1Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health

Science Center, Xi’an, Shaanxi, China, 2Sichuan Center for Disease Control and Prevention, Institute of

Tuberculosis Control and Prevention, Chengdu, China, 3Department of Nutrition and Food Safety Research,

School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an, Shaanxi, China, 4School of

Public Policy and Administration, Xi’an Jiaotong University, Shaanxi, China, 5Key Laboratory of Environment

and Genes Related to Diseases, Xi’an Jiaotong University, Ministry of Education, Xi’an, Shaanxi, China

Background: Parental household wealth has been shown to be associated with

ospring health conditions, while inconsistent associations were reported among

generally healthy population especially in low- and middle- income countries (LMICs).

Whether the household wealth upward mobility in LMICs would confer beneﬁts to

child health remains unknown.

Methods: We conducted a prospective birth cohort of children born to mothers

who participated in a randomized trial of antenatal micronutrient supplementation in

rural western China. Household wealth were repeatedly assessed at pregnancy, mid-

childhood and early adolescence using principal component analysis for household

assets and dwelling characteristics. We used conditional gains and group-based

trajectory modeling to assess the quantitative changes between two single-time

points and relative mobility of household wealth over life-course, respectively. We

performed generalized linear regressions to examine the associations of household

wealth mobility indicators with adolescent height- (HAZ) and body mass index-for-

age and sex z score (BAZ), scores of full-scale intelligent quotient (FSIQ) and emotional

and behavioral problems.

Results: A total of 1,188 adolescents were followed, among them 59.9% were male

with a mean (SD) age of 11.7 (0.9) years old. Per SD conditional increase of household

wealth z score from pregnancy to mid-childhood was associated with 0.11 (95% CI

0.04, 0.17) SD higher HAZ and 1.41 (95% CI 0.68, 2.13) points higher FSIQ at early

adolescence. Adolescents from the household wealth Upward trajectory had a 0.25

(95% CI 0.03, 0.47) SD higher HAZ and 4.98 (95% CI 2.59, 7.38) points higher FSIQ than

those in the Consistently low subgroup.

Conclusion: Household wealth upward mobility particularly during early life

has beneﬁts on adolescent HAZ and cognitive development, which argues for

Frontiers in Public Health 01 frontiersin.org

Tian et al. 10.3389/fpubh.2023.1061251

government policies to implement social welfare programs to mitigate or reduce the

consequences of early-life deprivations. Given the importance of household wealth

in child health, it is recommended that socioeconomic circumstances should be

routinely documented in the healthcare record in LMICs.

KEYWORDS

birth cohort, household wealth mobility, adolescent, physical growth, cognition,

behavioral health

1. Introduction

The national economic growth in low- and middle- income

countries (LMICs) has been rapidly developing for decades,

potentially resulting in the improvement of child health. According to

country-level data, the global under-ﬁve mortality rate substantially

decreased by 53%, from 90.6 in 1990 to 42.5 deaths per 1,000

livebirths in 2015 (1). In general population, individual households

have varying patterns and/or degrees of household wealth mobility.

Based on demographic and health surveys in 39 LMICs, Winskill et al.

(2) reported that children in the poorest households had a higher

probability of co-occurring fever, acute respiratory infection, diarrhea

and wasting. However, a study using data of 121 demographic and

health surveys in 36 LMICs between 1990 and 2011 observed a

quantitatively very small to null association between increases in

per-head gross domestic product and reductions in early childhood

malnutrition (3).

These discrepancies may be explained by the single-time point

measurement of household wealth and cross-sectional nature of

demographic and health surveys among these studies, which are

unable to capture the mobility of individual household wealth.

We only noted two studies conducted in high-income countries

that measured socioeconomic status (SES) at multiple-time points,

which, however, manually categorized the sample into subgroups by

merging the low-, medium-, and high-SES at single-time point in

an un-nuanced manner. They both reported that upward shift of

household SES from baseline had beneﬁts on later cardiovascular

health (4,5). However, household wealth as the largest contributor to

child health among individual SES measures (6,7), the associations

between household wealth mobility and child heath remain unclear.

Besides, household wealth can vary by years as compared to stable

parental education and occupation. In addition, as the theory

of Developmental Origins of Health and Disease describes that

exposures to deprivations during early life may lay the foundations

for long-term health (8), it remains unclear whether the upward

mobility of postnatal household wealth would buﬀer against the

negative eﬀects of prenatal disadvantaged environment on child long-

term health (4). Finally, household wealth and its mobility may exert

positive or negative eﬀects on child and adolescent speciﬁc health

outcome (9).

Abbreviations: BAZ, body mass index-for- age and sex z score; CI, conﬁdence

interval; FSIQ, full-scale intelligent quotient; HAZ, height-for- age and sex

z score; LMIC, low- and middle- income country; MUAC, mid-upper arm

circumference; PRI, perceptual reasoning index; PSI, processing speed index;

SD, standard deviation; SES, socioeconomic status; VCI, verbal comprehension

In this study, we used data from a birth cohort in rural western

China where national economy has been rapidly developing for

decades. In our village setting, individual families have wider range

and higher diversities of household wealth as compared to those

in eastern metropolitan cities in last decade, i.e., during our study

period, providing the unique opportunity to assess the household

wealth mobility. We prospectively followed participants at birth, mid-

childhood (7–9 y) and early adolescence (10–14 y) and repeatedly

assessed household wealth at each visit. We aimed to examine the

associations of household wealth at single-time point, conditional

increase between two single-time points and life-course relative

mobilities (trajectories) from pregnancy to early adolescence with

adolescent multiple health outcomes, including physical growth,

cognitive development, and emotional and behavioral problems.

2. Materials and methods

2.1. Study design and participant

We conducted a prospective birth cohort of children born to

mothers who participated in a cluster-randomized, double-blind trial

in rural western China conducted between August 2002 and February

2006 (ISRCTN08850194) (10). Brieﬂy, all pregnant women from

every village in two counties were eligible to enroll in this trial and

were randomized to take a daily capsule of folic acid, iron/folic acid,

or multiple micronutrients until delivery. Among 4,488 singleton live

births eligible to enroll in long-term follow-up after excluding birth

defects, and/or deaths (online Supplementary Figure 1), we followed

1,744 children at mid-childhood (age 7–10 years) between 2012 and

2013, and among them, 1,188 were followed at early adolescence (age

10–14 years) between June-December 2016. The procedure details of

the parent trial and follow-up studies were described elsewhere (10–

12). The trial and follow-up evaluation protocols were approved by

the Ethics Committee in Xi’an Jiaotong University Health Science

Center. Written informed consent was obtained from the biological

parents or caregivers, and verbal consent was obtained from all the

participants depending on their age.

2.2. Household wealth index

We repeatedly assessed household wealth at enrollment of

parent trial (<28 gestational weeks), mid-childhood and early

index; WISC-IV, Wechsler Intelligence Scale for Children, Fourth Edition; WMI,

working memory index.

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adolescence, which was derived from principal component analysis

for household assets and dwelling characteristics. The following items

were included at pregnancy: (i) goods, bicycle, motor, orchard, radio,

TV/VCD, refrigerator, washer, poultry, goat/sheep/pig, cattle/cow

and car/tractor; (ii) characteristics of the house, house types (soil

cave-dwelling, brick-cave dwelling, soil wall, brick/concrete wall, and

apartment), materials for the ﬂoor, and availability of electricity,

running water and household toilet. In addition to these, phone,

computer, air conditioner and automatic water heater were included

at mid-childhood and early adolescence. Brieﬂy, household assets

and dwelling characteristics were classiﬁed into Having/Yes and Not

having/No. The household wealth index was priorly constructed and

locally validated (13). We categorized the household wealth index to

indicate low-, medium- and high-wealth households by its tercile.

2.3. Measurements of adolescent health at

adolescence-stage visit

2.3.1. Physical growth

All anthropometric measures were taken by the same ﬁled worker

following standardized procedures in a local school classroom.

Standing height was measured to 1 mm precision using a stadiometer

(SZG-210, Shanghai JWFU Medical Apparatus Corporation) and

weight after losing heavy clothes was measured to nearest the 0.1 kg

(BC-420, Tanita Corporation, Tokyo, Japan). Height-for-age and sex

zscore (HAZ) and body mass index-for-age and sex zscore (BAZ)

were derived using World Health Organization growth standards

(14). Adolescent stunting and overweight/obesity was deﬁned as HAZ

<−2 standard deviation (SD) and BAZ >+1 SD, respectively. Body

mass index (kg/m2) was calculated as weight in kilograms divided by

the square of height in meters.

2.3.2. Cognitive development

We used a validated Chinese version of the Wechsler Intelligence

Scale for Children, Fourth Edition (WISC-IV) (15). The full-scale

intelligent quotient (FSIQ) was derived to represent adolescent

general cognitive development. Besides, other aspects of adolescent

cognitive development including verbal comprehension (VCI),

perceptual reasoning (PRI), working memory (WMI), and processing

speed index (PSI) were derived.

2.3.3. Emotional and behavioral problems

Adolescents actively completed the scale of the Chinese version

of Achenbach Youth’s Self-Report (2001 version) under the guidance

of ﬁeld workers (16). Three continuous scores were derived, with

lower scores indicating better emotional and behavioral outcome.

Internalizing score was composed of withdrawn, anxious/depressed

and somatic complaints, externalizing score was composed of

delinquent/rule-breaking and aggressive behavior, and the total

behavioral problem score was composed of all symptoms above and

social problem, thought problem and attention problem. Both of

the cognitive development and emotional and behavioral problem

assessments were administrated in a local school meeting room free

of distraction.

2.4. Other covariables

We collected the following covariables by face-to-face interview

using standard procedures in the parent trial. We included parent

age (continuous), education (<3 years, primary, secondary, ≥high

school) and occupation (farmer, others), antenatal randomized

regimens with durations (folic acid or folic acid plus iron <180

days, folic acid plus iron ≥180 days, multiple micronutrients

<180 days, and multiple micronutrients ≥180 days) accounting

for prior ﬁndings (12), maternal parity (0, ≥1), maternal mid-

upper arm circumference at enrollment (<21.5 cm, ≥21.5 cm),

and birth outcomes [small-for-gestational age by <10th centile by

INTERGROWTH (17) and sex].

2.5. Statistical analyses

To assess the conditional increase of household wealth, we

calculated the conditional gains of household wealth index between

two single-time points, which was the standardized residual of

regressing household wealth index at prior time point on household

wealth index at later (18). To assess the life-course relative mobility

of household wealth from pregnancy to early adolescence, we

performed group-based trajectory modeling that assigned individuals

with similar features of household wealth mobility trajectories

into distinct, exclusive subgroups (19), using the “traj” command

implemented in Stata software. Models with two or more subgroups

were conducted after accounting for the varying trajectory shapes

of linear, quadratic and/or cubic terms. Data-based parameters and

principles were applied to decide the ﬁnal subgroups (19), including

(i) Bayesian and Akaike information criterion value, (ii) average

of the posterior probabilities of group membership for individuals

assigned to each group >0.7, (iii) odds of correct classiﬁcation

based on the posterior probabilities of group membership >5,

and (iv) minimizing overlap in conﬁdence intervals (CIs) and

capturing the distinctive features of the data as parsimonious

as possible.

We took adolescent HAZ, BAZ, FSIQ, and scores of total

behavioral problems, externalizing and internalizing behavioral

problems as primary outcomes, and other aspects of cognitive

development and emotional and behavioral problems as secondary

outcomes, respectively. We performed generalized linear regressions

with Gaussian distribution and identity link to examine the

associations of household wealth mobility indicators with adolescent

health outcomes separately. The adjusted mean diﬀerences with their

95% CIs were estimated after including the covariables above. In

addition, we performed stratiﬁed analyses by parental education (low

and high educational level) and adolescent sex (male and female)

after obtaining the interaction P-values that were estimated from

likelihood ratio tests comparing models including and excluding the

interaction terms.

For sensitive analyses addressing the lost to follow-up, we

conducted inverse probability weighting, and randomly sampled

the lowest and highest 80% wealth households at pregnancy and

repeated the analyses for primary outcomes. The weight of each

participant is given by the inverse of the predicted probability for

followed participant in a logistic regression model, which included

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parental education, occupation and age, maternal parity and mid-

upper arm circumference, randomized regimens by duration, small-

for-gestational age, and adolescent sex and age. In addition, we

used E-value approach to assess the impact extent of potential

unmeasured confounder on aﬀecting the estimates above (20). All

statistical analyses were conducted in Stata 15.0 (Stata Corp, College

Station, Texas, USA). A two-sided P-value <0.05 was considered

statistically signiﬁcant.

3. Results

3.1. Background characteristics

Among 1,188 adolescents included in the ﬁnal analyses (Table 1),

59.9% were male, and the mean age was 11.7 (SD, 0.9) years

old. Majority of their parents had secondary education and

lived on farming. The percentage of adolescent stunting and

overweight/obesity was 2.3% (27/1,181) and 14.2% (166/1,167),

respectively. The mean (SD) of adolescent HAZ, BAZ, FSIQ, total

behavioral problem score, internalizing and externalizing score was

0.07 (1.07), −0.27 (1.15), 97.2 (12.4) points, 49.0 (24.1) points, 11.2

(7.6) points, and 8.4 (7.1) points, respectively. Adolescents born to

parents who had higher education level, were non-farmers and came

from high-wealth households were more likely to be lost to follow-

up (Table 1). However, the characteristics of birth outcomes between

adolescents followed and those lost to follow-up were balanced.

3.2. Household wealth mobility and

adolescent health

3.2.1. Household wealth at single-time point

As shown in Table 2, per SD increase of household wealth

index at pregnancy was associated with 0.09 (95% CI 0.04, 0.14)

SD higher HAZ, 0.71 (95% CI 0.11, 1.31) points higher FSIQ,

and −1.54 (95% CI −2.84, −0.24) points lower scores of total

behavioral problems and −0.47 (95% CI −0.85, −0.09) points lower

scores of externalizing behavioral problems at early adolescence.

Similar results were observed for household wealth index at mid-

childhood and early adolescence, and for other aspects of adolescent

cognitive development (Supplementary Table 1). While, we observed

null associations of household wealth at mid-childhood and early

adolescence with adolescent socioemotional scores, respectively

(Table 2 and Supplementary Table 2).

3.2.2. Conditional increase of household wealth

between two single-time points

We observed positive associations of conditional increase/gain of

household wealth between two single-time points, i.e., quantitative

increase of household wealth, with adolescent HAZ and cognitive

development, while null associations for BAZ and scores of emotional

and behavioral problems in Table 3 and Supplementary Tables 1,2.

Speciﬁcally, per SD of household wealth conditional increase from

pregnancy to mid-childhood was associated with 0.11 (95% CI 0.04,

0.17) SD higher HAZ and 1.41 (95% CI 0.68, 2.13) points higher

FSIQ at early adolescence, respectively. Similar associations between

conditional increase of household wealth from mid-childhood to

early adolescence and adolescent HAZ and cognitive development

(FSIQ and other aspects) were observed.

3.2.3. Life-course trajectories (relative-scale

mobility) of household wealth and adolescent

health

We identiﬁed four distinct life-course trajectories of household

wealth, which could be characterized as: (i) Consistently low (53.8%

of the sample), (ii) Upward (11.4%), (iii) Downward (22.2%),

and (iv) Consistently high (12.6%) (Supplementary Figure 2). The

parameters of deciding the ﬁnal trajectories were summarized in

Supplementary Table 4 while accounting for the distinctive features

of the data as parsimonious as possible.

Adolescents from the Upward subgroup had a 0.25 (95% CI

0.03, 0.47) SD higher HAZ than those in the Consistently low

subgroup, while adolescents from the Downward subgroup had a

−0.31 (95% CI −0.55, −0.07) SD lower HAZ as compared to those

in the Consistently high subgroup (Table 4). The corresponding

estimates were 4.98 (95% CI 2.59, 7.38) and −4.03 (−6.66, −1.41)

points for adolescent FSIQ. Similar positive associations were

observed for other aspects of adolescent cognitive development

(Supplementary Table 1), while null associations for adolescent BAZ

and scores of emotional and behavioral problems (Table 4 and

Supplementary Table 2).

3.2.4. Stratiﬁed analyses by parental education and

adolescent sex

The P-values of interactions between parental education

and adolescent sex and household wealth mobility indicators

were presented in Supplementary Table 4, most of which

were beyond 0.05. Further, we performed stratiﬁed analysis

by maternal education (Supplementary Tables 5,6), paternal

education (Supplementary Tables 7,8), and adolescent sex

(Supplementary Tables 9,10). The beneﬁts of household wealth

increase on adolescent HAZ and cognitive development were

more pronounced among adolescents from households with higher

maternal and paternal education. In addition, the beneﬁts were

doubled among adolescent females as compared with males.

3.3. Sensitivity analyses

Finally, the sensitivity analyses accounting for the lost to follow-

up showed comparable results (Supplementary Tables 11–13) to

those in Tables 2–4. The results of E-value approach indicated that

an unmeasured confounder with strong strength would be required

to explain away the observed associations (Supplementary Table 14),

suggesting the robustness of our results.

4. Discussions

We observed that household wealth upward mobility particularly

during early life was associated with adolescent higher HAZ

and better cognitive development in a birth cohort in an

undeveloped setting. Further, adolescents from wealthier households

at pregnancy had lower (better) scores of emotional and behavioral

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TABLE 1 Comparison of background characteristics between adolescents followed and those lost to follow-up in a birth cohort in rural western China.

Factors Adolescents followed from

pregnancy through

mid-childhood into early

adolescence/number (%)

Adolescents lost to

follow-up /number (%)

P-values

n1,188 (100.0) 3,300 (100.0)

Maternal age years/mean (SD) 24.8 (4.5) 24.6 (4.3) 0.18

Maternal education <0.001

<3 years 77 (6.5) 173 (5.3)

Primary 371 (31.3) 798 (24.3)

Secondary 600 (50.6) 1,811 (55.1)

High school and above 137 (11.6) 503 (15.3)

Maternal occupation <0.001

Farmer 1,030 (87.1) 2,710 (82.7)

Others 152 (12.9) 565 (17.3)

Paternal age (years)/Mean (SD) 28.0 (4.2) 27.8 (4.1) 0.10

Paternal education <0.001

<3 years 20 (1.7) 40 (1.2)

Primary 188 (15.9) 387 (11.8)

Secondary 735 (62.0) 2,033 (61.9)

High school and above 243 (20.5) 824 (25.1)

Paternal occupation <0.001

Farmer 951 (80.3) 2,400 (72.9)

Others 234 (19.7) 890 (27.1)

Household wealth index at pregnancy/enrollmenta−0.14 (1.4) 0.09 (1.5) <0.001

Low (Q1) 412 (34.7) 1,021 (30.9) 0.003

Medium (Q2) 429 (36.1) 1140 (34.6)

High (Q3) 347 (29.2) 1,139 (34.5)

Parity at enrollment 0.19

0 757 (63.7) 2,172 (65.8)

≥1 431 (36.3) 1,128 (34.2)

Maternal MUAC (cm) 0.341

<21.5 225 (19.1) 582 (17.9)

≥21.5 953 (80.9) 2,678 (82.1)

Randomized regimens 0.12

Folic acid 732 (34.6) 853 (36.0)

Folic acid plus iron 676 (32.0) 795 (33.5)

Multiple micronutrient 707 (33.4) 725 (30.5)

Ospring sex <0.001

Male 712 (59.9) 1,773 (53.7)

Female 476 (40.1) 1,527 (46.3)

Birth weight (gram) /Mean (SD) 3,205 (416) 3,194 (416) 0.46

Gestational weeks at delivery /Mean (SD) 39.8 (1.6) 39.8 (1.7) 0.63

Preterm (<37 gestational weeks) 50 (4.2) 158 (4.8) 0.42

Low birth weight (<2,500 g) 47 (4.1) 99 (3.2) 0.14

Small-for-gestational age (<10th) 138 (12.4) 374 (12.4) 0.99

Age at adolescence (years)/mean (SD) 11.7 (0.9) 11.7 (0.9) 0.55

SD, standard deviation; MUAC, mid-upper arm circumference.

aHousehold wealth at enrollment was derived from principal component analysis for household assets and dwelling characteristics, and was further categorized by its terciles.

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TABLE 2 Associations between household wealth index at single-time point and adolescent HAZ, BAZ, cognitive development, and emotional and behavioral problems in a birth cohort in rural western China (n=

1,188).

Household wealth index Zscores of physical growthaCognitive developmentaScores of emotional and behavioral problemsa

HAZ BAZ FSIQ Total problem Internalizing Externalizing

Pregnancy/per SD 0.09 (0.04, 0.14) 0.03 (−0.03, 0.09) 0.71 (0.11, 1.31) −1.54 (−2.84, −0.24) −0.31 (−0.73, 0.10) −0.47 (−0.85, −0.09)

Low (Q1) Ref. Ref. Ref. Ref. Ref. Ref.

Medium (Q2) 0.06 (−0.09, 0.22) −0.02 (−0.19, 0.15) 0.01 (−1.67, 1.68) −3.09 (−6.69, 0.51) −0.46 (−1.62, 0.69) −0.60 (−1.65, 0.45)

High (Q3) 0.24 (0.06, 0.42) 0.12 (−0.08, 0.32) 2.43 (0.41, 4.45) −5.24 (−9.62, −0.87) −1.30 (−2.70, 0.10) −1.75 (−3.02, −0.47)

Mid–childhood/per SD 0.10 (0.06, 0.15) 0.03 (−0.02, 0.08) 1.18 (0.70, 1.67) −0.002 (−1.07, 1.07) −0.11 (−0.45, 0.23) −0.06 (−0.37, 0.25)

Low (Q1) Ref. Ref. Ref. Ref. Ref. Ref.

Medium (Q2) 0.16 (0.01, 0.31) 0.10 (−0.07, 0.27) 0.14 (−1.54, 1.81) 0.46 (−3.19, 4.12) 0.08 (−1.09, 1.24) 0.12 (−0.94, 1.19)

High (Q3) 0.38 (0.22, 0.55) 0.07 (−0.12, 0.25) 3.37 (1.53, 5.21) −0.32 (−4.36, 3.72) −0.50 (−1.79, 0.80) −0.23 (−1.41, 0.95)

Early adolescence/per SD 0.11 (0.06, 0.16) 0.05 (0.003, 0.11) 1.48 (0.97, 1.99) −0.48 (−1.60, 0.64) −0.28 (−0.64, 0.08) −0.14 (−0.47, 0.19)

Low (Q1) Ref. Ref. Ref. Ref. Ref. Ref.

Medium (Q2) 0.22 (0.07, 0.37) 0.24 (0.08, 0.41) 1.14 (−0.48, 2.75) −2.12 (−5.66, 1.43) −0.99 (−2.13, 0.14) −0.04 (−1.08, 1.00)

High (Q3) 0.34 (0.17, 0.51) 0.14 (−0.05, 0.33) 5.16 (3.27, 7.05) −1.68 (−5.84, 2.48) −1.12 (−2.46, 0.21) −0.48 (−1.69, 0.74)

HAZ, height-for- age and sex z score; BAZ, body mass index-for- age and sex z score; FSIQ, full-scale intelligent quotient.

aData are presented with adjusted mean diﬀerences and their 95% conﬁdence intervals. The adjustments included parental education, occupation and age, maternal parity and mid-upper arm circumference, randomized regimens by duration, small-for-gestational age,

and adolescent sex and age.

problems. Although the interaction P-values did not reach statistical

signiﬁcance, the beneﬁts of household wealth increase on adolescent

HAZ and cognitive development were more pronounced among

households with higher maternal or paternal education level.

Furthermore, the corresponding beneﬁts were doubled among female

adolescents as compared with their counterparts.

We used household assets and dwelling characteristics to

construct household wealth index, which is a robust measure

in LMICs as compared to income and consumption, suﬀering

from information bias. Our study is one of the few studies to

comprehensively assess the mobility and trajectories of household

wealth from pregnancy to early adolescence, evaluate adolescent

health in multiple domains and examined their relationships in

a nuanced manner. Our results show that postnatal household

wealth conditional increase could confer the beneﬁts to adolescent

HAZ and cognitive development after accounting for the inﬂuence

of household wealth at pregnancy. Besides, the eﬀect size of

household wealth conditional increase between pregnancy and mid-

childhood seems to be larger than that between mid-childhood and

early adolescence, although with conﬁdence interval overlapping.

This ﬁnding is in line with the hypothesis that the plasticity

of child development is larger during early life, particularly

during the ﬁrst 1,000 days. Another explanation was that school

education may have relatively larger impact on adolescent cognitive

development as compared to household wealth mobility after mid-

childhood/primary school age, given the national strategy of 9-

year compulsory education well-implemented in China. In the

meantime, some nutritional intervention programs were conducted

among school, e.g., the Yingyangbao strategy widely covered in

rural areas in China (21), which potentially buﬀer against the

health consequences of disadvantaged families. In addition, on the

relative scale (position change) of household wealth in our sample

from pregnancy to early adolescence, our trajectory results show

the consistency of wealth-driven health disparities in LMICs (22).

Of note, adolescents from Upward household wealth trajectory

had comparable HAZ and cognitive development to those from

Consistently high household wealth trajectory. These results suggest

that postnatal household wealth upward mobility may have long-

lasting beneﬁts on adolescent health, particularly for household

wealth increase during early life. Majority of studies considered that

the household wealth was a proxy of oﬀspring access to health care,

optimal diets, clean water and sanitation, home environment and

other resources (23). Nevertheless, mediation analyses reported that

the mediators above could not completely explain the associations

between household wealth and health outcomes at later life (24–26).

Among adults, Zhang and colleagues reported that healthy lifestyle

only mediated a small proportion (3.0% to 12.3%) of the association

between low SES and higher risk of mortality and cardiovascular

diseases (27). These results suggest that poor household wealth

at early life may have a direct or causal link to suboptimal life-

course health outcomes, which may result from persistent structural

changes due to deprivations during pregnancy (28). Our results

that household wealth at pregnancy was associated with adolescent

HAZ, cognitive development and emotional and behavioral health

agree well with this hypothesis. Taken together, to improve child

health and development in public health practices, much eﬀorts

should be made as early as practicable to lay the foundation and

target the high-risk population in disadvantaged households. In

public health implications, we suggested that deprived families

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TABLE 3 Associations between conditional gains of household wealth among periods and adolescent HAZ, BAZ, cognitive development and emotional and behavioral problems in a birth cohort in rural western China

(n=1,188).

Household wealth Zscores of physical growthaCognitive developmentaScores of emotional and behavioral problemsa

HAZ BAZ FSIQ Total problem Internalizing Externalizing

Gains from pregnancy to

mid–childhood/per SD

0.11 (0.04, 0.17) 0.03 (−0.05, 0.10) 1.41 (0.68, 2.13) 0.69 (−0.90, 2.28) −0.02 (−0.53, 0.49) 0.12 (−0.34, 0.59)

Low (Q1) Ref. Ref. Ref. Ref. Ref. Ref.

Medium (Q2) 0.04 (−0.11, 0.19) 0.07 (−0.10, 0.23) 0.87 (−0.79, 2.53) 0.47 (−3.18, 4.12) −0.17 (−1.33, 1.00) −0.10 (−1.17, 0.96)

High (Q3) 0.21 (0.05, 0.37) 0.06 (−0.12, 0.24) 2.82 (1.08, 4.57) 0.98 (−2.83, 4.79) −0.23 (−1.45, 0.99) 0.24 (−0.87, 1.36)

<=0 Ref. Ref. Ref. Ref. Ref. Ref.

>0 0.24 (0.11, 0.37) 0.05 (−0.09, 0.19) 1.98 (0.55, 3.41) 1.6 (−1.53, 4.73) 0.19 (−0.82, 1.19) 0.45 (−0.47, 1.36)

Gains from mid–childhood to

early adolescence/per SD

0.06 (−0.01, 0.12) 0.05 (−0.02, 0.12) 1.07 (0.38, 1.76) −0.43 (−1.93, 1.07) −0.26 (−0.74, 0.22) −0.08 (−0.52, 0.36)

Low (Q1) Ref. Ref. Ref. Ref. Ref. Ref.

Medium (Q2) 0.17 (0.02, 0.32) 0.28 (0.12, 0.45) 0.64 (−1.03, 2.30) 0.35 (−3.27, 3.97) −0.02 (−1.18, 1.14) 0.11 (−0.95, 1.17)

High (Q3) 0.19 (0.04, 0.34) 0.19 (0.01, 0.36) 2.58 (0.87, 4.28) 0.01 (−3.71, 3.73) −0.46 (−1.65, 0.73) 0.29 (−0.79, 1.38)

<=0 Ref. Ref. Ref. Ref. Ref. Ref.

>0 0.11 (−0.02, 0.23) 0.12 (−0.02, 0.26) 1.69 (0.30, 3.07) −0.53 (−3.56, 2.51) −0.23 (−1.20, 0.74) −0.17 (−1.06, 0.71)

Gains from pregnancy to early

adolescence/per SD

0.11 (0.04, 0.18) 0.06 (−0.01, 0.14) 1.74 (1.00, 2.47) 0.06 (−1.56, 1.67) −0.24 (−0.76, 0.28) 0.03 (−0.44, 0.50)

Low (Q1) Ref. Ref. Ref. Ref. Ref. Ref.

Medium (Q2) 0.14 (−0.005, 0.29) 0.23 (0.07, 0.39) 0.58 (−1.04, 2.19) −0.99 (−4.54, 2.55) −0.57 (−1.70, 0.57) 0.24 (−0.79, 1.28)

High (Q3) 0.29 (0.13, 0.45) 0.17 (−0.01, 0.35) 3.92 (2.14, 5.70) −0.76 (−4.66, 3.13) −0.91 (−2.16, 0.34) −0.27 (−1.41, 0.87)

<=0 Ref. Ref. Ref. Ref. Ref. Ref.

>0 0.15 (0.03, 0.28) 0.12 (−0.02, 0.26) 1.95 (0.55, 3.36) −1.25 (−4.34, 1.83) −0.76 (−1.75, 0.23) −0.48 (−1.38, 0.42)

HAZ, height-for- age and sex z score; BAZ, body mass index-for- age and sex zscore; FSIQ, full-scale intelligent quotient.

and adolescent sex and age.

Frontiers in Public Health frontiersin.org

Tian et al. 10.3389/fpubh.2023.1061251

TABLE 4 Associations between life-course household wealth trajectories and adolescent HAZ, BAZ, cognitive development, and emotional and behavioral problems in a birth cohort in rural western China (n=1,188).

Household wealth Zscores of physical growthaCognitive developmentaScores of emotional and behavioral problemsa

HAZ BAZ FSIQ Total problem Internalizing Externalizing

Upward vs. Consistently low 0.25 (0.03, 0.47) −0.01 (−0.25, 0.24) 4.98 (2.59, 7.38) 0.18 (−5.15, 5.52) −0.56 (−2.27, 1.15) 0.08 (−1.47, 1.64)

Downward vs. Consistently

low

0.19 (0.02, 0.36) −0.03 (−0.23, 0.16) 2.62 (0.74, 4.51) −1.47 (−5.67, 2.73) −0.75 (−2.09, 0.60) −0.47 (−1.70, 0.76)

Consistently high vs.

Consistently low

0.49 (0.25, 0.73) 0.10 (−0.17, 0.37) 6.66 (4.00, 9.32) −3.67 (−9.64, 2.30) −1.07 (−2.98, 0.84) −1.52 (−3.26, 0.22)

Upward vs. Consistently high −0.24 (−0.52, 0.04) −0.11 (−0.42, 0.21) −1.67 (−4.76, 1.41) 3.86 (−3.17, 10.88) 0.51 (−1.74, 2.76) 1.60 (−0.45, 3.65)

Downward vs. Consistently

high

−0.31 (−0.55, −0.07) −0.13 (−0.40, 0.13) −4.03 (−6.66, −1.41) 2.20 (−3.80, 8.20) 0.32 (−1.60, 2.24) 1.05 (−0.70, 2.80)

Upward vs. Downward 0.08 (−0.16, 0.32) 0.01 (−0.27, 0.30) 2.28 (−0.34, 4.90) 1.05 (−4.93, 7.03) 0.04 (−1.93, 2.00) 0.40 (−1.34, 2.14)

HAZ, height-for- age and sex z score; BAZ, body mass index-for- age and sex z score; FSIQ, full-scale intelligent quotient.

and adolescent sex and age.

should be included in social welfare programs at the beginning

of pregnancy.

In addition, the potential beneﬁts of household wealth

increase over time may diﬀer by speciﬁc health outcome. We

observed consistent signiﬁcance for adolescent HAZ and cognitive

development which may result from the appropriate infant feeding,

diets, stimulation, and home environment among higher wealth

households, all of which have been shown to be causes of child

linear growth and development (29). Prior study reported lower

(better) scores of emotional and behavioral problems among

children from wealthier households (30). Our study further

contributes to the literature that higher household wealth at

pregnancy but not postnatal household wealth increase has beneﬁts

on adolescent socioemotional outcomes. In addition, the transition

of overweight/obesity from the wealthy to the poor along with the

national economy increasing was documented in other LMICs (31).

We only observed statistically positive associations of adolescent

BAZ with household wealth at early adolescence, suggesting the

likely minimal impact of household wealth mobility at early life

on adolescent weight. However, we could not provide more details

on the underlying mechanisms linking household wealth to a

speciﬁc outcome, and mediation analyses examining corresponding

mediators are needed in future. Overall, postnatal household

wealth increase has some long-term beneﬁts on adolescent health

particularly for adolescents being born and raised in consistently

wealthy families, which argue for government policies to implement

social welfare programs such as cash transfer and health insurance to

mitigate or reduce the consequences of early-life deprivations (32).

Furthermore, we examined the modiﬁcations of parent education

and oﬀspring sex on the relationship between household wealth

mobilities and adolescent health, although majority of these

interaction P-values were not statistically signiﬁcant. In the present

study, the beneﬁts of postnatal household wealth increase on

adolescent health were more pronounced among adolescents

from households with higher parental education. Similarly, prior

study reported that higher maternal education might buﬀer

against the negative eﬀects of higher household wealth on child

overweight/obesity (33). Besides, Conger and colleagues reported

that higher parent education level would increase their family

investments on child care and consequently lead to the improvement

of child health (34). We hypothesized that households with higher

parental education were more likely to take advantage of the

wealth and transfer resources into appropriate practices of child

care, consequently improving adolescent health (35). As for the sex

modiﬁcation, the beneﬁts of household wealth increase on adolescent

health were observed both among female and male adolescents, but

the eﬀect sizes particularly for cognitive development were doubled

among adolescent females. Prior study reported that adolescent

females relate to males were more likely to follow the parenting on

healthy life styles (36). Similarly, we previously reported a statistically

signiﬁcant interactions of maternal education and sex for adolescent

anemia (37). In addition, the relationship of household wealth at

pregnancy and adolescent emotional and behavioral health was only

observed among males in the present study, which may be due to the

statistical power, and/or that adolescent males had higher prevalence

of externalizing behavioral problems as compared to females (38).

However, the sex modiﬁcation of the relationship between SES and

children emotional and behavioral outcomes were not consistent in

the literature (39), warranting conﬁrmations in future studies.

Frontiers in Public Health 08 frontiersin.org

Tian et al. 10.3389/fpubh.2023.1061251

Our ﬁndings have a few limitations. Firstly, adolescents were

born to mothers who had participated in an antenatal micronutrient

supplementation trial which might limit the generalization. However,

this community-based trial enrolled all eligible pregnant women in

every village and we adjusted for randomized regimens in all analyses.

Besides, this micronutrient intervention strategy would be expected

to weaken the tie between household wealth and adolescent health

for its ability to reduce the wealth-driven equity (40). Secondly,

as with other cohorts with long-term follow-up periods, loss of

participants may lead to the selection bias. Households with higher

parental education and wealth are more likely to move out of

study area into cities and thus be lost to follow, resulting in the

underestimates in our study. We have partly addressed this by

performing inverse probability weighting and repeating analyses

among the lowest and highest 80% wealth households at baseline,

all of which showed comparable results. Thirdly, the household

wealth index derived from assets and dwelling characteristics might

be country-speciﬁc, although it was commonly used in LMICs.

Besides, the wealth mobility deﬁned by household wealth index may

not indicate the actual increase of inﬂation-adjusted family income,

which however mainly suggested wealth positional change among

our participants. Finally, residual confounding was always possible

due to the nature of observational design, and causal inference could

be pursued under the counterfactual outcome framework in future

studies as the reviewer suggested. However, our sensitivity analyses

of E-value approach suggested that the contribution of unmeasured

confounding to biasing our results was likely minimal.

Higher prenatal household wealth and postnatal household

wealth increase particularly during early life had wide beneﬁts

on adolescent HAZ and cognitive development, and possibly

socioemotional outcomes. To improve adolescent health and human

capital outcomes, public health programs targeting at all life-course

stages are warranted and should be accompanied by strategies

to reach the most vulnerable populations at the beginning of

pregnancy. Given the importance of household wealth and other

related SES indicators in child health, it is recommended that

socioeconomic circumstances should be routinely documented in the

healthcare record.

Data availability statement

The original contributions presented in the study are included in

the article/Supplementary material, further inquiries can be directed

to the corresponding authors.

Ethics statement

The studies involving human participants were reviewed and

approved by Ethics Committee in Xi’an Jiaotong University Health

Science Center. Written informed consent to participate in this study

was provided by the participants’ legal guardian/next of kin.

Author contributions

YC, LZ, and ZZ designed the study. JT, SL, LW, QQ, QD, AA,

ME, and ZZ conducted the study. JT, YZ, and ZZ analyzed data and

interpreted results. JT, YZ, and ZZ wrote the paper. LZ and ZZ had

primary responsibility for ﬁnal content. All authors reviewed, revised,

and approved the ﬁnal paper.

Funding

This work was supported by the National Natural Science

Foundation of China (Grant 82103867 to ZZ and 81872633 to LZ),

China Postdoctoral Science Foundation (Grant 2021M702578 to ZZ),

and National Key Research and Development Program of China

(Grants 2017YFC0907200 and 2017YFC0907201).

Acknowledgments

We thank all ﬁeld workers who helped with data collection. We

are also grateful to all participants and their families.

Conﬂict of interest

The authors declare that the research was conducted in the

absence of any commercial or ﬁnancial relationships that could be

construed as a potential conﬂict of interest.

Publisher’s note

All claims expressed in this article are solely those of the

authors and do not necessarily represent those of their aﬃliated

organizations, or those of the publisher, the editors and the reviewers.

Any product that may be evaluated in this article, or claim that may

be made by its manufacturer, is not guaranteed or endorsed by the

publisher.

Supplementary material

The Supplementary Material for this article can be found

online at: https://www.frontiersin.org/articles/10.3389/fpubh.2023.

1061251/full#supplementary-material

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Frontiers in Public Health 10 frontiersin.org

TYPE Original Research

PUBLISHED 28 February 2023

DOI 10.3389/fpubh.2022.1054482

OPEN ACCESS

EDITED BY

Stevo Popovic,

University of Montenegro, Montenegro

REVIEWED BY

Seyed Morteza Tayebi,

Allameh Tabataba’i University, Iran

Jaroslava Kopcakova,

University of Pavol Jozef

Šafárik, Slovakia

*CORRESPONDENCE

Paulina S. Melby

paulina.sander.melby@regionh.dk

SPECIALTY SECTION

This article was submitted to

Children and Health,

a section of the journal

Frontiers in Public Health

RECEIVED 26 September 2022

ACCEPTED 25 November 2022

PUBLISHED 28 February 2023

CITATION

Melby PS, Elsborg P, Bentsen P and

Nielsen G (2023) Cross-sectional

associations between adolescents’

physical literacy, sport and exercise

participation, and wellbeing.

Front. Public Health 10:1054482.

doi: 10.3389/fpubh.2022.1054482

Nielsen. This is an open-access article

distributed under the terms of the

Creative Commons Attribution License

(CC BY). The use, distribution or

reproduction in other forums is

permitted, provided the original

author(s) and the copyright owner(s)

are credited and that the original

publication in this journal is cited, in

accordance with accepted academic

practice. No use, distribution or

reproduction is permitted which does

not comply with these terms.

Cross-sectional associations

between adolescents’ physical

literacy, sport and exercise

participation, and wellbeing

Paulina S. Melby1,2,3*, Peter Elsborg1,2,4, Peter Bentsen4,5 and

Glen Nielsen1

1Department of Nutrition, Exercise and Sports, University of Copenhagen, Frederiksberg, Denmark,

2Health Promotion, Steno Diabetes Centre Copenhagen, The Capital Region of Denmark, Gentofte,

Denmark, 3Danish School Sports, Nyborg, Denmark, 4Center for Clinical Research and Prevention,

Copenhagen University Hospital, Bispebjerg and Frederiksberg, Frederiksberg, Denmark,

5Department of Geosciences and Natural Resource Management, University of Copenhagen,

Frederiksberg, Denmark

Background: Adolescence is a signiﬁcant period in one’s development of

positive emotional and social wellbeing. Physical literacy (PL) is considered

a determinant of physical health and wellbeing and is thought to be the

foundation for an individual’s engagement in physical activities. Yet, limited

evidence exists on PL’s association with adolescents’ health and physical

activity behavior. This study aims to (1) explore the associations between

Danish adolescents’ PL and their emotional and social wellbeing, (2) examine

whether these associations are mediated by sport and exercise participation

(SEP), and (3) consider if the associations dier across sex.

Methods: Cross-sectional data from a national population survey were

collected in 2020. The sample consisted of 1,518 Danish adolescents aged

13–15 years. PL was assessed with the validated MyPL questionnaire. The

weekly time engaged in sports and exercise was self-reported. Self-esteem,

life satisfaction, body satisfaction, and loneliness were measured with items

from the standardized HBSC questionnaire, and a wellbeing composite score

was calculated from these four measures. We constructed structural equation

models with PL and sports and exercise participation as independent variables

and the ﬁve aspects of wellbeing as dependent variables.

Results: Positive associations were observed between PL and SEP (β=0.33,

p<0.001) and between PL and the ﬁve aspects of wellbeing with β-values

between 0.19 and 0.30 (p<0.001). These associations were greater among

girls. The association between PL and four of the ﬁve wellbeing outcomes were

partly mediated by SEP with indirect eects (β) between 0.03 and 0.05.

Conclusions: Results from this study support the hypotheses that

PL is important for children and adolescents’ wellbeing and physical

activity behavior.

KEYWORDS

mental health, SEM, youth, quality of life, children, physical literacy, sport

participation, exercise participation

Frontiers in Public Health 01 frontiersin.org

Melby et al. 10.3389/fpubh.2022.1054482

Background

Adolescents’ emotional and social wellbeing has been in

a worrying decline over recent years (1) and is currently

considered one of the greatest disease burdens among

adolescents (2). Additionally, the prevalence of issues in

emotional and social well-being are more common among

adolescent girls compared to boys (3,4). This is unfortunate,

as adolescents’ emotional and social wellbeing is crucial to their

academic, cognitive, and social development (5,6), and low

wellbeing is connected to increased risks of non-communicable

diseases (7,8) and mortality (9). Wellbeing promotes mental

health and alleviates related issues (2), and the World Health

Organization (WHO) has declared that emotional and social

wellbeing combine to form the foundation of well-functioning

individuals and communities (10).

Emotional and social wellbeing, also commonly referred to

as mental health (11), are associated with individual, social,

and environmental factors (12), including lifestyle factors such

as physical activity and sport participation (13–15). Numerous

personal aspects are thought to be closely related to wellbeing,

such as self-esteem (16), life satisfaction (17), body satisfaction

(18), and loneliness (19). Self-esteem is deﬁned as an individual’s

feelings and thoughts about their own importance and worth

and is an essential part of one’s self-concept (20). Self-esteem

has shown to be associated with mental health in adolescence

and adulthood (16). Life satisfaction is deﬁned as an individual’s

cognitive appraisal of life quality from their own set of criteria

(21) and is as an essential component within positive mental

health (17). Body satisfaction, an aspect of body image, is deﬁned

as an individual’s appraisal of their physical appearance and

body based on their thoughts, feelings, and attitudes toward

their body (22). Body satisfaction is seen as an element in

mental health that has increased importance during adolescence

(18). Loneliness is a negative feeling produced by disagreement

between an individual’s desired and existing social relations (23)

and is associated with mental health problems (24).

Adolescence is a life-stage with increased vulnerability

to mental health problems, which makes it a signiﬁcant

period in the development of positive mental health (25).

Promoting positive mental health and preventing health

problems, especially in early life-stages, is generally more

eﬀective than treating diseases (26,27), and thus it is important

to identify factors related to positive mental health in children

and adolescents.

A concept that has gained increased attention for its

potential in promoting physical health and wellbeing is that of

physical literacy (PL) (28,29). PL describes important individual

attributes and prerequisites in engaging in and adhering

to physical activities throughout life (30) and is therefore

thought to be a determinant of health (31). While various

deﬁnitions exist, most include the elements cardiovascular

ﬁtness, strength, motor competence, motivation, conﬁdence,

knowledge, and understanding, which are encompassed in

three overall domains: physical, aﬀective and cognitive. It has

been argued that PL “can make signiﬁcant contributions to

quality of life” [(30), p. 32] and that higher levels of PL will

lead to self-esteem, an important part of psychological well-

being in physical activities (30). Further, drawing on ﬁndings

in self-determination theory research, it has been previously

suggested that PL could be a determinant of overall well-being

(32,33). This belief stems from the positive relation between

autonomous motivation and contextual wellbeing (34), which

both are strengthened by the perception of competences (i.e., the

PL element of conﬁdence), and from the fact that wellbeing in

physical activities can transfer to other contexts (35) and may

also transfer to overall wellbeing (36). Two recent studies have

found positive correlations between PL and aspects of mental

health in children and young adolescents (32,33).

PL is thought to lay the foundation of engagement

in sports and other physical activities (30,31) that can

positively aﬀect children’s and adolescents’ wellbeing (13–15).

A recent systematic review found that the extant evidence

demonstrates a positive association between PL and physical

activity (37), with emerging longitudinal evidence supporting

the assumption that PL is important for physical activity

later in life (37,38). However, most studies have investigated

PL and its associations with health and physical activity

among children up to the age of 12 years, with only a few

studies focusing on adolescents (39) and young adults (40).

These studies observed similar associations as those found

among children.

Therefore, our objectives are to (a) investigate the

associations between PL and aspects of emotional and social

wellbeing among adolescents aged 13–15 years, (b) explore

to what degree these associations are mediated by sport and

exercise participation (SEP), and (c) investigate how these

associations diﬀer among boys and girls. We hypothesized that

adolescents’ PL would be associated with their SEP and their

wellbeing and that the relationship would diﬀer between the

sexes. We further hypothesized that the relationship between PL

and aspects of well-being would be partly mediated by SEP (see

the hypothesized paths in Figure 1).

Methods

Study population

Our data came from a large-scale national survey conducted

between October 29 and December 21, 2020 by Rambøll

Management Consulting for the Danish Institute for Sports

Studies (41). The sample of adolescents aged 13–15 years old was

randomly drawn by the Danish Health Data Authority.

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FIGURE 1

Hypothesized associations between study variables. This ﬁgure illustrates the theorized structural equation model, with aspects of emotional

and social wellbeing serving as the outcomes.

A slightly diﬀerent questionnaire was sent to the age-groups

7–12 years old and 13–15 years old. An invitation with a

weblink to the online survey was sent via digital mail to the

parents/guardians of 9,000 children and adolescents aged 7–15

years. Two reminders were sent via parents/guardians’ digital

mail to the adolescents who had not yet completed the survey.

In parallel, telephone follow-ups with the parents/guardians

were conducted, encouraging the adolescents and children

to participate in the survey. During the call and in the e-

mails, parents/guardians could also provide the adolescents

or children’s private e-mail address, allowing Rambøll

Management Consulting to send the invitation directly to the

adolescent or child. The survey links were accessible for ∼2

months. By then, 4,379 children and adolescents aged 7–15

years (48.7 % of those invited) had completed the survey,

of which 1,518 were adolescents aged 13–15 years and thus

included for analysis in this study. All completed answers had

full data.

Measurements

Measurement of physical literacy

We measured PL with the MyPL questionnaire, a context-

speciﬁc questionnaire suitable for population survey, developed

by the authors of this study and validated in the same

sample of this study. The MyPL is a PL assessment tool

that strives to account for how PL diﬀers across diﬀerent

social and physical environments for physical activity, as

described in the conceptualization by Whitehead (30), and

to ensure that PL items will be interpreted similarly across

respondents, compared to other PL assessment tools wherein

participants are probed on their generic relationship toward

physical activity. Conﬁrmatory factor analysis of the model

showed good ﬁt indices (CFI =0.938; TLI =0.925; RMSEA

=0.065 (90% CI 0.062–0.068); SRMR =0.055). The MyPL

also showed good internal consistency and reliability for

the total PL scale was 0.778 (Cronbach’s alpha) and 0.783

(McDonald’s Omega). The results of development and initial

validation of the MyPL questionnaire is unfolded in a study

be Elsborg et al. entitled “From global domains to physical

activity environments: development and initial validation

of a questionnaire-based physical literacy measure designed

for large-scale population surveys,” which is prepared for

submission. The questionnaire items and responds methods can

be found in Appendix 1.

The 21-item PL scale consisted of 5 subscales: a PL for

ball- and running-based activities (7 items), which consist

of the elements autonomous motivation and conﬁdence

for ball and running activities combined with the physical

competences of ball skills, endurance, and strength; a PL

for playground-based activities (5 items) consisting of

autonomous motivation and conﬁdence for skating and

climbing activities, as well as the physical competence

of balance; a PL for gymnastic-based activities (4 items)

consisting of autonomous motivation and conﬁdence for

gymnastics, along with physical competences for gymnastic

and skipping; a PL for water-based activities (3 items)

consisting of autonomous motivation and conﬁdence for water

activities combined with physical competences for swimming;

and a general (not environment-speciﬁc) knowledge and

understanding PL domain [3 item from the CAPL-2 (42)],

which consisted of knowledge about the transfer of skills

between diﬀerent sports, knowledge about the importance of

daily physical activity, and conceptual knowledge of strength

and health.

Measurement of sport and exercise

participation

Weekly time spent on SEP was measured with the question

“How many hours do you normally use on sport/exercise per

week (not counting time used on transportation)?” Participants

typed in hours and minutes. Answers above 20 h were not

included to minimize the risk of participants mistaking hours

with minutes.

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Measurement of aspects of mental health

Self-esteem

We assessed self-esteem with three items measuring

participants’ conceptions of others’ thoughts about them and

their positive self-conceptions. The participants responded to

the prompts “I like myself,” “I am good enough as I am,”

and “Others my age like me” using a ﬁve-point Likert scale

from strongly agree to strongly disagree. The self-esteem score

was calculated as the mean of the three items. The three-item

self-esteem scale has showed good reliability (α=0.89) in

similar population (43) and is used in the standardized HBSC

questionnaire (44).

Life satisfaction

We assessed life satisfaction with the Cantril Ladder (45),

which is based on the above deﬁnition. Participants were

presented with a ladder from zero to ten and asked to indicate

“Where on the ladder do you feel you stand at the moment?”

with zero indicating the worst possible life and 10 indicating the

best possible (46). The Cantril Ladder has demonstrated good

reliability and convergent validity (45) and is widely used, such

as in the HBSC study [e.g., (47)]. Furthermore, it has shown to

be related to psychological wellbeing, mood, emotions, and self-

perception (48) and thus seems to be a suitable indicator of life

satisfaction among adolescents.

Body satisfaction

We measured body satisfaction with a single item from the

Body Investment Scale (49), which reﬂects the above deﬁnition.

Participants are asked “How satisﬁed are you with your body

(physical appearance)?” and using a 5-point Likert scale from

very dissatisﬁed to very satisﬁed.

Loneliness

We measured global loneliness with a single item.

Participants responded to the question “Do you feel lonely?”

using a four-point Likert scale from “Yes, very often” to “No.” A

high score reﬂects minor to no feelings of loneliness and is thus

a positive emotional health indicator. The single-item measure

of global loneliness has shown a signiﬁcant relationship with the

UCLA Loneliness Scale, which is an indirect multi-item scale to

measure loneliness (19).

Wellbeing composite score

To better compare results to other studies, we decided to use

a wellbeing composite score, which is the mean of the self-esteem

scale (the mean of the three items) and the three single-item

scores for life satisfaction, body satisfaction, and loneliness.

Data analysis

Descriptive statistics and reliability coeﬃcients were

calculated in SPSS 25.0 (IBM Corp, Armonk, NY, USA). We

used Cronbach’s alpha and McDonald’s omega (50) to examine

the reliability of the psychometric subscales and combined

scales. We considered values above 0.7 acceptable (51). For

scales measuring psychological constructs with fewer than ﬁve

items (i.e., self-esteem and mental health), values above 0.6

were considered acceptable (52). The values of all variables were

normalized into a zero to one range to avoid high variation in

the structural equation models (SEMs).

We used R studio and the lavaan packages (53) to perform

an SEM with each of the aspects of wellbeing as the outcome

and PL and SEP as the predictor and mediator, respectively (see

the hypothesized model in Figure 1). We adjusted all models for

age, and the models with the total sample were also adjusted for

sex. We allowed all exogenous variables to covariate. To estimate

missing values, we applied a maximum-likelihood estimation

with robust standard error (MLR) values. Study variables were

normally distributed (see Skewness and Kurtosis in Table 1). To

inspect the model-ﬁt indexes, we followed recommended cut-oﬀ

criteria: the Tucker-Lewis index (TLI >0.95), the comparative

ﬁt index (CFI >0.95), and the root mean square error of

approximation (RMSEA <0.06) (54). Signiﬁcance tests were

two-tailed, and we considered P-values below 0.05 statistically

signiﬁcant. We only report standardized coeﬃcients.

Results

Descriptive statistics

The sample size was 1,518, with 51.3% being girls and a

mean age of 14 years. The mean scores, standard deviations,

minimum, maximum, skewness, and kurtosis for all scales and

variables are reported in Table 1.

Reliability

The internal consistency of the scales where evaluated with

Cronbach’s alpha and McDonald’s omega (55) and are presented

in Table 1. The reliability coeﬃcients for the mental health and

self-esteem scale were all above our minimum requirements.

Reliability coeﬃcients for the PL scale and the PL subscales were

acceptable to good, except for the cognitive domain, where -

was below acceptable and αwas almost zero.

Association between physical literacy,

sports and exercise participation, and

aspects of wellbeing

The unadjusted intercorrelations (Pearson’s R or r) among

all study variables are presented in Table 2. In the total sample,

PL correlated with SEP (r =0.29, p<0.001) and with all

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TABLE 1 Sample descriptive and scale reliability.

Mean SD Min. Max. Skewness Kurtosis α

Competitive activities (7 items) 0.62 0.18 0.00 1.00 −0.28 −0.33 0.78 0.79

Playground activities (5 items) 0.55 0.18 0.00 1.00 −0.20 −0.19 0.68 0.68

Gymnastic-based activities (3 items) 0.48 0.27 0.00 1.00 0.14 −0.89 0.78 0.78

Water-based activities (3 items) 0.63 0.22 0.00 1.00 −0.39 −0.37 0.66 0.66

Cognitive domain (3 items) 0.75 0.23 0.00 1.00 −0.46 −0.45 0.06 0.54

Physical literacy (21 items) 0.60 0.12 0.13 0.92 −0.27 −0.09 0.84 0.73

SEP (hours/week) 5.26 3.49 0.00 19.00 1.03 0.82

Life satisfaction (1 item) 0.73 0.17 0.00 1.00 −0.83 0.71

Body satisfaction (1 item) 0.66 0.23 0.00 1.00 −0.58 0.17

Loneliness (1 item) 0.85 0.22 0.00 1.00 −1.48 2.12

Self-esteem (3 items) 0.72 0.20 0.00 1.00 −0.89 1.11 0.86 0.87

Wellbeing composite (6 items) 0.74 0.16 0.17 1.00 −0.83 0.66 0.75 0.76

Min, Minimum; Max, Maximum; SD, Standard deviation; α, Cronbach’s alpha; Ω, Omega (ML).

wellbeing outcomes with r-values between 0.14 and 0.20. SEP

correlated with wellbeing outcomes with r-values between 0.07

and 0.14.

SEMs were conducted for each wellbeing outcome—life-

satisfaction, body satisfaction, loneliness, self-esteem, and the

wellbeing composite score—and performed by total sample

separately for boys and girls. The standardized regression

coeﬃcients (β), standard error (SE), and p-values for each of

the models are presented in Table 3. The path from PL to SEP

is included in all models. All models showed good ﬁts (for all

ﬁve models: CFI =1.000, TLI =1.000, and RMSEA =0.000).

The SEMs showed that PL was signiﬁcant and positively

associated with SEP (β=0.33, p<0.001) and with all aspects

of mental health. Table 3 and Figure 2 show information about

path coeﬃcients from the ﬁve structural equation models. We

observed signiﬁcant positive associations between PL and all

wellbeing outcomes for the total sample: wellbeing composite

score (β=0.24, p<0.001), self-esteem (β=0.24, p<0.001),

life satisfaction (β=0.19, p<0.001), loneliness (β=0.23, p<

0.001), and body satisfaction (β=0.30, p<0.001). We found

that SEP was associated with all aspects of wellbeing except

for self-esteem, and only partly and to a small extent mediated

the association between PL and the wellbeing composite score

(indirect eﬀect: β=0.03, p<0.001), life-satisfaction (indirect

eﬀect: β=0.04, p<0.001), loneliness (indirect eﬀect: β=0.03,

p<0.05), and body-satisfaction (indirect eﬀect: β=0.03, p

<0.05).

Sex dierences in the associations

The SEMs conducted separately for boys and girls showed

that PL was found to be signiﬁcantly associated with all wellbeing

outcomes for both sexes, with β-coeﬃcients ranging from 0.10 to

0.23 among boys and 0.27 to 0.36 among girls. In boys, SEP was

associated with all wellbeing outcomes except self-esteem, with

β-coeﬃcients between 0.09 and 0.13. In girls, SEP only correlated

with the wellbeing composite score (β=0.10, p<0.05) and life

satisfaction (β=0.14, p<0.01).

We observed higher β-coeﬃcients for the direct association

between PL and wellbeing measures among girls compared to

boys in all models (boys/girls)—wellbeing composite score: β=

0.16 /β=0.31; life satisfaction: β=0.10 / β=0.29; loneliness:

β=0.16 / β=0.29; body satisfaction: β=0.23 / β=0.36; and

self-esteem: β=0.16 / β=0.33. Among boys, we observed a

signiﬁcant association between SEP and the wellbeing composite

score (β=0.09, p=0.011), life satisfaction (β=0.10, p=0.000),

loneliness (β=0.10, p=0.050), and body satisfaction (β=

0.13, p=0.014) but no signiﬁcant association with self-esteem.

Among girls, SEP was signiﬁcantly associated with the wellbeing

composite score (β=0.10, p=0.016) and life satisfaction (β=

0.14, p=0.001) but not with the other aspects.

Discussion

The results of this study indicate that PL is positively

associated with SEP. In the total sample, we observed an

association b between PL and SEP, with a β-value of 0.33. This

ﬁnding is in accordance with previous studies of cross-sectional

design. Choi et al. (39) observed an adjusted association between

self-reported PL and self-reported time spent in physical

activities among 1945 Chinese adolescents (12–18 years of

age) with a β-value of 0.23 (39), Coyne et al. (56) observed

an adjusted association between PL and pedometer measured

physical activity among 1,000 Canadian children (8–12 years

of age) with a β-value of 0.18 (56), Melby et al. (33) found an

adjusted association between PL and accelerometer measured

physical activity among 647 Danish children (7–13 years of

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TABLE 2 Variable intercorrelation matrix (Pearson’s R).

1 2 3 4 5 6 7

1. Age

2. Physical literacy −0.09

Boys −0.08*

Girls −0.11

3. SEP 0.03 0.29

Boys 0.06 0.26

Girls 0.00 0.33

4. Life satisfaction −0.07 0.16 0.14

Boys −0.06 0.11 0.11

Girls −0.09* 0.23 0.16

5. Body satisfaction −0.07* 0.17 0.09 0.47

Boys −0.08* 0.17 0.08* 0.38

Girls −0.06 0.20 0.08* 0.50

6. Loneliness −0.07 0.14 0.07 0.46 0.31

Boys −0.08* 0.12 0.07 0.42 0.21

Girls −0.07 0.17 0.07 0.46 0.33

7. Self-esteem −0.03 0.15 0.09 0.49 0.53 0.41

Boys −0.03 0.11 0.04 0.43 0.42 0.35

Girls −0.03 0.21 0.11 0.51 0.58 0.42

8. Wellbeing composite −0.08 0.20 0.12 0.77 0.77 0.72 0.79

Boys −0.09* 0.18 0.10 0.74 0.70 0.70 0.76

Girls −0.08* 0.26 0.13 0.77 0.80 0.72 0.81

Bold text indicates a p-value under 0.01; *indicates a p-value under 0.05.

age) with a β-value of 0.39 (33), Yli-Piipari et al. (57) found

that physical literacy explained 29% of their overall physical

activity participation among 450 Finnish 11-year-old children

(57), and, in a sample of 2,879 Canadian children (8–12 years of

age), Belanger et al. (58) found that children scoring above the

recommended levels of PL had higher odds of meeting physical

activity guidelines (58).

The results of this study indicate that PL is positively

associated with important aspects of adolescent’s wellbeing. In

the total sample, we observed an association between PL and

emotional and social wellbeing, with β-values ranging from

0.23 to 0.30. This result is in line with previous studies. A

study by Jeﬀeries et al. (59) found an unadjusted association

between PL and resilience among 227 Canadian children (9–

12 years of age) with a β-value of 0.21, a study by Caldwell

et al. (60) observed a positive association between PL and

health-related quality of life among 222 Canadian children

(mean age 10.7 years), a study by Blain et al. (32) found an

unadjusted associations between PL and positive and negative

aﬀect among 187 young adolescents (mean age 12.8 years)

with β-values of −0.25 and 0.38 (p<0.05), and a study

by Melby et al. (33) found adjusted associations between PL

and four aspects of wellbeing among 647 Danish children (7–

13 years of age) with β-values of 0.21–0.38. However, only

few studies have investigated the association between PL and

wellbeing outcomes.

Stratifying the sample by sex, we observed more pronounced

associations between PL and wellbeing among girls compared to

boys, with approximately double-sized β-values. The transition

into adolescence is a vulnerable period (25), and girls may

be particularly vulnerable to developing mental health issues

(1,61). The strong relationship between PL and emotional

and social wellbeing among girls is therefore noteworthy, as it

indicates that PL could potentially mitigate or reduce mental

health issues among adolescents, especially amongst girls.

To our knowledge, this is the ﬁrst study to investigate

sex diﬀerences in the association between PL and wellbeing.

Previous studies have found sex diﬀerences in the associations

between SEP and wellbeing, reporting that girls have greater

beneﬁts compared to boys, especially in team sports (62,

63). However, in this study, among girls, we only observed

associations between SEP and loneliness and the wellbeing

composite score, which means that, when including PL in the

models, SEP’s relation to adolescent girls’ body satisfaction,

loneliness, and self-esteem were not signiﬁcant. Further, β-

values of the associations between PL and wellbeing outcomes

were greater than those of SEP and wellbeing. In sum, the results

of this study indicate that PL is more important for adolescent

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TABLE 3 Regression coecients for the models with aspects of emotional mental health as outcomes.

All Boys Girls

Paths Std B SE PStd B SE PStd B SE P

PL →Sport (all models) 0.33 0.03 0.000 0.32 0.04 0.000 0.34 0.04 0.000

1. Wellbeing composite score

PL→Wellbeing (direct) 0.24 0.03 0.000 0.16 0.05 0.000 0.31 0.05 0.000

Sport →Mental health 0.10 0.03 0.006 0.09 0.04 0.011 0.10 0.04 0.016

Indirect eﬀect 0.03 0.01 0.001 0.03 0.01 0.013 0.03 0.02 0.020

Total eﬀect 0.27 0.03 0.000 0.19 0.04 0.000 0.34 0.05 0.000

2. Life satisfaction

PL→Life satisfaction (direct) 0.19 0.04 0.000 0.10 0.05 0.042 0.27 0.06 0.000

Sport→Life satisfaction 0.12 0.03 0.000 0.10 0.04 0.000 0.14 0.04 0.001

Indirect eﬀect 0.04 0.01 0.000 0.03 0.01 0.020 0.05 0.02 0.003

Total eﬀect 0.23 0.04 0.000 0.14 0.05 0.006 0.32 0.05 0.000

3. Loneliness

PL→Loneliness (direct) 0.23 0.05 0.000 0.16 0.07 0.022 0.29 0.08 0.000

Sport→Loneliness 0.09 0.04 0.019 0.10 0.05 0.050 0.08 0.06 0.167

Indirect eﬀect 0.03 0.01 0.021 0.03 0.02 0.053 0.03 0.02 0.170

Total eﬀect 0.26 0.05 0.000 0.19 0.07 0.005 0.31 0.07 0.000

4. Body satisfaction

PL→Body satisfaction (direct) 0.30 0.05 0.000 0.23 0.07 0.000 0.36 0.08 0.000

Sport→Body satisfaction 0.10 0.04 0.014 0.13 0.05 0.014 0.08 0.06 0.224

Indirect eﬀect 0.03 0.01 0.015 0.04 0.02 0.016 0.03 0.02 0.227

Total eﬀect 0.33 0.05 0.000 0.27 0.06 0.000 0.39 0.07 0.000

5. Self-esteem

PL→Self-esteem (direct) 0.24 0.05 0.000 0.16 0.07 0.015 0.32 0.07 0.000

Sport→Self-esteem 0.07 0.04 0.071 0.04 0.05 0.423 0.10 0.06 0.093

Indirect eﬀect 0.02 0.01 0.075 0.01 0.02 0.427 0.03 0.02 0.101

Total eﬀect 0.26 0.04 0.000 0.17 0.06 0.006 0.35 0.06 0.000

Standardized regression coeﬃcient (Std B), standard error (SE), and p-values for structural equation models with aspects of emotional mental health as the outcomes. Controlled for age

and sex.

girls’ emotional and social wellbeing than SEP. Among boys,

SEP was associated with all aspects of wellbeing except self-

esteem, and the β-values of the associations between PL and the

wellbeing outcomes were similar (i.e., equal or a little higher)

to those of SEP and wellbeing. These ﬁndings suggest that both

PL and SEP are important for adolescent boys’ emotional and

social wellbeing.

The minimal or non-signiﬁcant indirect eﬀects of SEP on

the association between PL and wellbeing demonstrate that

PL is more relevant to adolescent’s wellbeing than SEP. Since

previous studies have found positive associations between SEP

and emotional wellbeing (64–66), we wonder if the type of sport

or exercise contributes to whether or not participation impacts

wellbeing positively, as demonstrated in other studies that have

shown that traditional team sports have a higher impact on

wellbeing outcomes compared to self-organized exercise or

individual sports (62,63). This could also explain why we

observed a stronger relationship between SEP and wellbeing

among boys compared to girls, as boys more commonly engage

in team sports, while girls engage more commonly in self-

organized exercise (41). This could also explain why previous

studies observed mixed ﬁndings, such as the study of Caldwell

et al. (60), that found no mediating eﬀect of accelerometer-

measured physical activity on the association of PL and health-

related quality of life (60) and the study of Melby et al.

(33) that found a mediating eﬀect of physical activity in the

relationship between PL and one out of ﬁve investigated aspects

of wellbeing (33).

The observed positive associations between PL and

wellbeing could also be understood and explained through the

lens of self-determination theory (34). Higher PL increases the

possibility that one’s basic psychological needs are satisﬁed in

terms of experiencing competence during SEP and, accordingly,

wellbeing in the activity (67). Similarly, an individual with low

PL will be more likely to experience competence frustration,

which will accordingly have a negative eﬀect on their sense

of wellbeing in the activity (68,69). According to basic

psychological needs theory, which has been formulated

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FIGURE 2

Path coecients of the signiﬁcant mediation analysis. This ﬁgure shows path coecients of the adjusted structural equation models with

aspects of wellbeing as the outcomes. All the shown parameters (β) are standardized and statistically signiﬁcant. Covariation between all

exogenous variables was allowed. **indicates a p-value under 0.01; *indicates a p-value under 0.05; ns, non-signiﬁcant association.

and supported in self-determination theory research, only

engagement in SEP that fosters need satisfaction will positively

impact overall wellbeing. Thus, SEP’s impact on wellbeing

strongly depends on how the SEP is delivered. This might

explain why sport-based interventions exhibit mixed eﬀects

on mental health (70). One study found that the association

between levels of physical activity and overall wellbeing in

children was mediated by their perception of the three basic

psychological needs (autonomy, competence, and relatedness)

in physical activity environments (71). This result supports our

theoretical assumption, outlined in the background section—

namely, that wellbeing in contexts of physical activity (i.e.,

experiencing satisfaction of basic psychological needs) can

transfer to other contexts and, ultimately, to the global level

(35,36).

Collectively, the results from this study suggest that it is

critical to identify how SEP and physical activities are delivered

in a way that fosters wellbeing. In this regard, supported

by the observed positive association between PL and mental

health in this study, it is useful to take a PL pedagogical

perspective, supported by principles of the basic psychological

need satisfaction, when delivering sport- or physical-activity-

based interventions to increase adolescents’ emotional and social

wellbeing. Emerging evidence on interventions, driven by the

theory of PL and aimed at increasing participation in physical

activities in children up to young adulthood, has shown promise

in this regard (72–74).

Implications for practice, policy, and

research

First, this study contributes to the limited evidence on the

association between PL and health, supporting the assumption

that PL is important for adolescents’ participation in physical

activities and their wellbeing. Secondly, the ﬁnding that PL

has a more signiﬁcant eﬀect than SEP suggests that focus

should be directed away from the current narrow focus

on increasing the amount and intensity of physical activity

here and now. Instead, the focus should be on supporting

the development of the prerequisites for physical activity

participation, i.e., the elements of PL. This so-called PL

perspective seems to be more advantageous for long-term

physical and mental health, including a lifelong engagement

in physical activities. Those working with the physical activity

of children and adolescents (e.g., physical education teachers,

sport coaches, parents, and school principals) should consider

how to support the development of PL by considering all

of its elements and should accordingly avoid hindering one

or more of these said elements. One way to achieve this is

to provide appropriate challenges and demand that matches

the level of participants’ competence to enable experiences

of need satisfaction (i.e., the need for competence), resulting

in a sense of mastery and contextual wellbeing and hence

autonomous motivation and conﬁdence. Creating a task-

solving/-learning environment for physical activity contexts—

instead of a result-oriented or competitive environment has

shown to be an eﬀective way to this and has also shown

to be beneﬁcial for the participants’ contextual wellbeing and

autonomous motivation, as well as the coaches/teachers’ facility

of a social learning climate with a high degree of autonomy

(75,76).

Policy makers should consider including a PL perspective

in addition to national guidelines on physical activity

so that they contain recommendations on how best

to foster the PL elements of motivation, conﬁdence,

physical competences, and knowledge and understanding

that enables children and adolescents to engage in

physical activities.

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Strength and limitations

A clear strength of this study was its use of a large and

randomly recruited sample. It was not possible to check for

representability in terms of socio-economic status in the sample

of 7–15-year olds, or control for socio-economic status, which

should be considered a limitation, as most health problems

follow a social gradient (77,78).

The single-item indicators of three of the aspects of

wellbeing (life satisfaction, body satisfaction, and loneliness)

reduced the reliability of these latent measures compared

to multi-item measures. However, some of these measures

have been used in similar samples and have been validated

against commonly used multiple-item scales (19). Nevertheless,

using the ﬁve diﬀerent aspects of wellbeing added valuable

information to the investigated relationships.

There was a limitation connected to the self-reported

measures of this study. First, SEP was measured with a single

item that prompted for the frequency of generic SEP. Secondly,

self-reported measures of children’s and adolescents’ physical

activities, such as SEP, may be considered less reliable compared

to objective measures (e.g., accelerometery). Thirdly, PL was

measured with a newly developed 21-item questionnaire, the

MyPL questionnaire, which assessed motivation, conﬁdence,

and physical competences connected to various disciplines and

contexts. The self-assessment of one’s physical competences

should especially be considered a limitation compared to

studies using more objective direct measures/tests. On the

other hand, we consider physical-activity-environment-speciﬁc

prompting in the MyPL questionnaire a strength, as it deals with

challenges connected to generically asking about motivation

and conﬁdence, making it further in line with the theory of

PL (30).

The main limitation was the cross-sectional design, which

presented vagueness about the direction of the investigated

associations and put a restrain on making claims about

causality. Future research should investigate the associations

between PL, physical activity/SEP, and wellbeing using

longitudinal and experimental designs and control for

socioeconomic status.

Conclusion

This study expands on the scarce evidence on PL’s

association with health. The study brings novel knowledge on

the association between adolescents’ PL, SEP, and emotional

and social wellbeing and the mediating role of SEP in the

association between PL and wellbeing. In accordance with our

hypothesis, we found that PL was positively associated with SEP

and all investigated aspects of emotional and social wellbeing.

We found stronger associations between PL and emotional

and social wellbeing among girls compared to boys, indicating

that PL is particularly beneﬁcial for adolescent girls’ wellbeing.

We found mixed results on the mediating role of SEP in

the association between PL and the ﬁve aspects of emotional

and social wellbeing. Results from this study indicate that PL

likely contribute to adolescents’ emotional and social wellbeing

beyond its association with SEP. Implications of these results

suggest focussing on supporting children’s and adolescents’

prerequisites for physical activity participation (i.e., the elements

of PL), instead of the narrow focus on cumulative physical

activity (i.e., amount and intensity).

Data availability statement

The datasets presented in this study can be found in

online repositories. The names of the repository/repositories

and accession number(s) can be found at: The dataset has

been submitted to the National Archives with the serial

number: FD.50354.

Ethics statement

According to a recent Danish legislation of The Danish Data

Protection Agency, it is no longer required to collect consent and

objectives of the research is in society’s interest (i.e., to improve

society) (79). Thus, this survey did not need to apply or register

for ethical approval at the Center of data review. All procedures

and handling of data were carried out based on this legislation.

Author contributions

The study was conceptualized and manuscript was drafted

by PM, PE, PB, and GN. Data management were conducted

by PM and PE. All authors revised and approved the ﬁnal

manuscript.

Funding

This study was supported by the Innovation Fund Denmark

(9065-00060B) and the Danish TrygFonden (ID: 125640). The

funders were not involved in any parts of this study.

Acknowledgments

We would like to thank Steﬀen Rask and Helene Kirkegaard

at the Danish Institute for Sports Studies for the collaboration.

We would also like to thank all the participating children

and adolescents.

Frontiers in Public Health 09 frontiersin.org

Melby et al. 10.3389/fpubh.2022.1054482

Conﬂict of interest

The authors declare that the research was conducted in the

absence of any commercial or ﬁnancial relationships that could

be construed as a potential conﬂict of interest.

Publisher’s note

All claims expressed in this article are solely those of the

authors and do not necessarily represent those of their aﬃliated

organizations, or those of the publisher, the editors and the

reviewers. Any product that may be evaluated in this article, or

claim that may be made by its manufacturer, is not guaranteed

or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found

online at: https://www.frontiersin.org/articles/10.3389/fpubh.

2022.1054482/full#supplementary-material

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Frontiers in Public Health 12 frontiersin.org

TYPE Original Research

PUBLISHED 09 March 2023

DOI 10.3389/fpubh.2023.1064837

OPEN ACCESS

EDITED BY

Terry Huang,

City University of New York, United States

REVIEWED BY

Kumar Gaurav Chhabra,

NIMS University, India

Farooq Ahmed,

Quaid-i-Azam University, Pakistan

*CORRESPONDENCE

Ghada Wahby Elhady

gwelhady@kasralainy.edu.eg

SPECIALTY SECTION

This article was submitted to

Public Health and Nutrition,

a section of the journal

Frontiers in Public Health

RECEIVED 08 October 2022

ACCEPTED 14 February 2023

PUBLISHED 09 March 2023

CITATION

Elhady GW, Ibrahim Sk, Abbas ES, Tawﬁk AM,

Hussein SE and Salem MR (2023) Barriers to

adequate nutrition care for child malnutrition in

a low-resource setting: Perspectives of health

care providers.

Front. Public Health 11:1064837.

doi: 10.3389/fpubh.2023.1064837

and Salem. This is an open-access article

distributed under the terms of the Creative

Commons Attribution License (CC BY). The use,

distribution or reproduction in other forums is

permitted, provided the original author(s) and

the copyright owner(s) are credited and that

the original publication in this journal is cited, in

accordance with accepted academic practice.

No use, distribution or reproduction is

permitted which does not comply with these

terms.

Barriers to adequate nutrition

care for child malnutrition in a

low-resource setting:

Perspectives of health care

providers

Ghada Wahby Elhady1*, Sally kamal Ibrahim2, Enas S. Abbas3,

Ayat Mahmoud Tawﬁk4, Shereen Esmat Hussein1and

Marwa Rashad Salem1

1Public Health and Community Medicine Department, Faculty of Medicine, Cairo University, Manial,

Cairo, Egypt, 2Pediatric Department, Faculty of Medicine, Cairo University, Manial, Cairo, Egypt,

3Pediatric Clinical Nutrition Department, National Nutrition Institute, Cairo, Egypt, 4Public Health and

Community Medicine Department, Faculty of Medicine, Port Said University, Port Said, Egypt

Introduction: Several studies in developing countries found that more

need-based training is required for health care providers (HCPs) in child

malnutrition management.

Methods: An exploratory cross-sectional study was conducted to explore barriers

to providing adequate nutrition care as perceived by the healthcare providers

(HCPs) in the child malnutrition clinic at a Children’s University Hospital in Egypt.

Participants were selected using the purposive sampling technique. Five out

of seven HCPs in the clinic were included (two male physicians, one female

physician, and two female nurses). Qualitative data were collected through

in-depth interviews. The interview guide consisted of semi-structured open-

ended questions. Quantitative data were the resulting scores from the scoring

system used to assess the understandability and actionability of the patient

education materials (PEMs) that are available in the clinic. The Patient Education

Materials Assessment Tool for Printable Materials (PEMAT-P) for the scoring.

Statistical analysis: The thematic content analysis technique was employed for

qualitative data. The percent score was generated for the PEM actionability and

understandability for quantitative data.

Results: Most common child malnutrition conditions encountered by HCPs

were nutritional deﬁciencies. Barriers to the delivery of adequate nutrition

care to children were physician-centered: limited nutrition education in the

medical school, health system-centered: an insucient number of HCPs, lack

of nutritional supplements, lack of patient education materials (PEMs) that suit

the characteristics of the served community, lack of updated standard of practice

(SOP) and guidelines, inadequate nutrition training of HCPs, and insucient time

for each patient, and caregivers-centered: the low socioeconomic status and false

cultural, nutritional beliefs.

Conclusion: There are dierent barriers to adequate nutrition care for child

malnutrition in low-resource healthcare settings. Mainly nutritional deﬁciencies.

Most of the barriers were health system-related in the form of insucient

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resources (shortage of workforce; concerning the high caseload, nutritional

supplements, and PEMs) and inadequate management of resources (lack of

skill-based training, lack of updated SOP and guidelines, and lack of properly

designed PEMs that facilitate communication with the target caregivers).

KEYWORDS

malnutrition, low-resource healthcare settings, skill-based training, updated standard of

practice, guidelines, nutritional supplements, patient education materials

Introduction

Malnutrition during infancy and childhood may lead to

impaired growth, delayed and improper social and cognitive

development, low academic achievement, and later in life, reduced

productivity (1).

Globally, malnutrition is still a signiﬁcant cause of death and

disease among children, especially those under 5 years (U5Y) of age.

Undernutrition type of malnutrition is associated with 45% of child

deaths.1Most of those deaths take place in low- and middle-income

countries that also have rising rates of childhood obesity (see

text footnote 1).2In 2020, 38.9 million children U5Y of age were

overweight worldwide, 45.4 million were wasted, and 149.2 million

were stunted (see text footnote 2). Stunting, which is deﬁned by

the World Health Organization (WHO) as a height that is more

than two standard deviations below the median child’s growth

standards, is largely irreversible3and associated with extremely

high health and economic costs4(2). Stunting is the impact of

chronic malnutrition aﬄicting the child during the ﬁrst 1,000 days

of life. The number of stunted children is declining in all world

regions except Africa (see text footnote 4).

Children’s nutritional status is a powerful and sensitive

indicator for assessing child health, food security, and the

need to improve economic, environmental, and health policies

(see text footnote 1). Although Egypt has achieved remarkable

progress in child health in the past two decades, the country’s

U5Y child mortality rate in 2013 was below the Millennium

Development Goal (MDG) 44 (see text footnote 4), (2) and far

below Sustainable Development Goal (SDG) 2 (3)5. The prevalence

of child malnutrition in Egypt is predominantly high, with 11% of

infants born with a low birth weightweight (see text footnote 2),

and 9.5% of children U5Y of age are underweight, which is higher

than the average for Africa (6.0%), and 22% are stunted, which is the

largest prevalence of stunting in the Middle East (see text footnote

1 Available online at: https://www.who.int/news-room/fact.sheets/detail/

malnutrition (accessed June 2, 2021).

2 Available online at: https://www.who.int/publications/i/item/

9789240025257 (accessed September 12, 2021).

3 Available online at: https://www.who.int/publications/i/item/WHO-

NMH-NHD-14.3 (accessed December 20, 2021).

4UNICEF Report. (2021). Available online at: https://www.who.int/

publications/i/item/9789240025257 (accessed December 20, 2021).

5 Available online at: https://egypt.un.org/en/sdgs/2 (accessed May 21,

2022).

4), (2,3). Furthermore, stunted growth is a public health problem

that has persisted in Egypt for a long time, as reported in EDHS

2014 (percent of stunted U5Y children was reported as 23, 23, 29,

and 22% in the years 2000, 2005, 2008, and 2014, respectively) (3).

Educating the caregivers of children has been proven in many

studies to not only increase their knowledge but also improve

the health outcomes of these children (4–6). A systematic review

to explore factors associated with successful nutrition education

interventions for children showed that engaging parents through

face-to-face education and identiﬁcation of speciﬁc child’s or

parent’s behaviors that needed to be modiﬁed were fundamental

factors (7). Thus, the role of health care providers (HCPs) in

educating caregivers is crucial to overcoming child malnutrition

(8). Several studies in developing countries found that there is a

need for more in-service, need-based, and skill-based training of

HCPs involved in child malnutrition management.

The main objective of the present study was to explore

barriers to providing adequate nutrition care services in the child

malnutrition clinic to inform future service delivery strategies

for managing child malnutrition, particularly in low-resource

healthcare settings.

Materials and methods

Design and context of the study

The current study is a clinic-based exploratory cross-sectional

study that used a qualitative approach. The study was conducted in

the Center of Social and Preventive Medicine (CSPM) Malnutrition

Clinic, Faculty of Medicine, Cairo University, Egypt, among HCPs

(physicians and nurses) of the clinic.

The study was performed in accordance with the Consolidated

Criteria for Reporting Qualitative Research CORE-Q (9).

Sampling technique and sample size

Participants were selected via a purposive sampling technique

(10). The interviews were continued until they reached data

saturation, where no new themes, subthemes, or explanations

emerged from the interviews (11). Eligibility criteria were any

HCPs (physicians and nurses) working in the CSPM malnutrition

clinic during the study duration who were willing to participate.

Out of seven HCPs, participants were ﬁve HCPs (two male

physicians, one female physician, and two female nurses) because

no new data were added starting from the third interview and

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saturation was achieved at the ﬁfth interview. The interviewed

physicians graduated between 1995 and 2001, and the interviewed

nurses graduated in 1985 and 1990. One physician was a general

practitioner; the other two were continuing their postgraduate

studies in family medicine and pediatrics, respectively. The median

number of working years mentioned by the HCPs was 6 years,

ranging from 8 to 20 years.

Data types and collection tools

Qualitative data were collected through in-depth, audiotaped

face-to-face interviews (each lasting up to 45 min) conducted by

one of the researchers, who has experience conducting interviews

and has worked on many qualitative studies. The interview guide

(Appendix 1), which was pilot-tested beforehand, consisted of

semi-structured, open-ended questions. The interview guide was

developed following systematic literature reviews (3,4,6,8,12). A

trained note-taker assisted the investigator in recording the sessions

using a voice recorder and written notes. Quantitative data were

the scoring system results used to assess the understandability and

actionability of the educational leaﬂets distributed to caregivers

by HCPs. For scoring, researchers used the Patient Education

Materials Assessment Tool for Printable Materials (PEMAT-P)

(13). The tool provides two scores for each material: a score

for understandability and a separate score for actionability. The

researchers scored the education material on each item of the

material content, excluding the non-applicable (NA) items. Each

item was given either 1 point (agree) or 0 points (disagree)

(Tables 1A,B). First, the total points for the material items were

summed up to calculate the score. Then, the sum was divided by the

total possible points: the number of items on which the material was

rated, excluding the items classiﬁed as NA. After that, the result was

divided by 100 to get a percentage (%). This percentage score is the

understandability score or the actionability score of the material on

the PEMAT; the more understandable or actionable the material,

the higher the score (13).

Statistical analysis

For qualitative data

Data processing was based on the thematic content analysis

technique (14,15), which aims to get descriptions of the

message content using a systematic and objective procedure. The

thematic analysis is a three-stage analysis. The ﬁrst stage involves

understanding the idea through comprehensive and repeated

readings of the data transcripts. The second stage is material

exploration, which involves selecting the participants’ statements

and organizing them into categories (themes). The third stage deals

with the processing and interpretation of results. The participants’

quotations were used to clarify the meaning of the themes and

summaries. Two investigators carried out the analysis. They read

the transcript multiple times, made meaningful statements, and

created themes and sub-themes.

For quantitative data

The PEMAT-P tool provides two scores for each material: a

score for understandability and a separate score for actionability.

TABLE 1A Assessment of printed patient education materials provided to

caregivers in CSPM (using PEMAT-P): understandability.

Health education items: Rating

Response options (rating): Agree: 1 Disagree: 0

Contents

1. The material makes its purpose completely evident. 0

2. The material does not include information or content that

distracts from its purpose

Word choice and style

3. The material uses common everyday language. 0

4. Medical terms are used only to familiarize the audience with the

terms and are deﬁned if used.

5. The material uses the active voice. 0

Use of numbers

6. Numbers appearing in the material are clear and easy to

understand. (If no number =NA)

7. The material does not expect the user to perform calculations. 1

Organization

8. The material breaks or “chunks” information into short sections.

(Very short material =NA)

9. The material’s sections have informative headers

(very short material =NA)

10. The material presents information in a logical sequence. 1

11. The material provides a summary. (Very short material =NA) 0

Layout and design

12. The material uses visual cues (e.g., arrows, boxes, bullets, bold,

larger font, highlighting) to draw attention to key points.

Use of visual aids

13. The material uses visual aids whenever they could make content

more easily understood (e.g., illustration of healthy portion size).

14. The material’s visual aids reinforce rather than distract from the

content. (No visual aids =NA)

15. The material’s visual aids have clear titles or captions. (No visual

aids =NA)

16. The material uses illustrations and photographs that are clear

and uncluttered (No visual aids =NA)

17. The material uses simple tables with short and clear row and

column headings. (No Tables =NA)

Total points =17; Total possible points =13; Total achieved points =7

Understandability score=7/13=54%

The researchers scored the education material on each item of

the material content, excluding the non-applicable (NA) items.

Each item was given either 1 point (agree) or 0 points (disagree)

(Tables 1A,B). First, the total points for the material items were

summed up to calculate the score. Then, the sum was divided by the

total possible points: the number of items on which the material was

rated, excluding the items classiﬁed as NA. After that, the result was

divided by 100 to get a percentage (%). This percentage score is the

understandability score or the actionability score of the material on

the PEMAT; the more understandable or actionable the material,

the higher the score (13).

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TABLE 1B Assessment of printed patient education materials provided to

caregivers in CSPM (using PEMAT-P): actionability.

Health education items: Rating

Response options (rating): Agree: 1

Disagree: 0

1. The material clearly identiﬁes at least one action the user can take. 1

2. The material addresses the user directly when describing actions. 0

3. The material breaks down any action into manageable,

explicit steps

4. The material provides a tangible tool (e.g., menu planners,

checklists) whenever it could help the user take action.

5. The material provides simple instructions or examples of how to

perform calculations. (No calculations =NA)

6. The material explains how to use charts, graphs, tables, or

diagrams to take action.

(No charts, graphs, tables, or diagrams =NA)

7. The material uses visual aids as much as possible rendering it

easier to act on the instructions.

Total points =7; Total possible points =5; Total achieved points =2

Actionability score =2/5 =40%

Ethical considerations

The study protocol was revised and approved by the Medical

Research Committee in the Public Health and Community

Medicine Department. All the study participants were treated

according to the Helsinki Declaration of biomedical ethics (16).

Written informed consent from each participant was obtained

after proper orientation regarding the study objectives. Data

conﬁdentiality and informant privacy were upheld throughout

the whole study. For each participant, we used “I” (interviewee)

followed by a number per the chronological order of the interviews

(I01, I02, I03..., etc.). The necessary municipal and federal

authorities approved the study to be carried out. Using the voice

recorder was authorized, and transcriptions of the recordings

were performed.

Results

Qualitative data analysis results

By analyzing the qualitative data derived from the interviews,

the researchers came up with the following themes:

•Views of HCPs toward malnutrition problems

HCPs mentioned that “the most frequent malnutrition

problems that come to seeking medical advice were rickets,

parasitism, underweight, kwashiorkor, and failure to thrive.”

Physicians mentioned that “laboratory investigation was the

best method to assess the nutritional status.”

To improve the child’s nutritional status, all HCPs conﬁrmed

the importance of “nutrition education, counseling, and provision

of supplements such as iron and vitamin D”during infancy.

•Barriers to providing nutrition care to children

HCPs aﬃrmed that there are three types of barriers that restrict

providing quality medical nutrition care.

Physician-centered barriers

•Limited opportunities for applied/clinical nutrition education

in medical schools

Physicians mentioned that “limited nutrition education in

medical school and even in postgraduate studies (namely master’s

degree)”is the major challenge for gaining an adequate medical

knowledge. Physicians said that “they learned the biochemistry

of nutrition but not the basic nutrition knowledge needed to

share with the patients.” They expressed dissatisfaction with their

medical school education “We believe that we are ill-qualiﬁed to

provide nutrition advice in the clinical setting.”

Furthermore, physicians explained that the nutrition course

they received was not applicable to patients. As a result, they were

not prepared to counsel caregivers. Some HCPs felt their clinical

rotations did not prepare them for the prevention or management

of childhood malnutrition from the nutritional aspect due to the

limited experience of tutors in clinical nutrition.

Health system-centered barriers

These include barriers related to the resources and process

components of the health system.

•Inadequate capacity building of HCPs in the workplace

Physicians expressed their views of inadequate nutrition

training programs for physicians: “Training prepared us

inadequately for work in low-resource settings.” One physician

delineated his participation in training programs at the Faculty

of Medicine, Cairo University. He said the ﬁrst hospital training

course started in June 2009 and included six sessions taught over

1 week. The training approach included theoretical educational

sessions, practical training, demonstration exercises, group-

based exercises, and case studies about breastfeeding. Another

HCP received a nutrition course at the Ministry of Health in

2004, including four sessions taught over 2 days about growth

monitoring. However, all respondents aﬃrmed that they do not

have access to regular refresher courses to reinforce their learning,

provide practice demonstrations, and keep them up to date. In

addition, they identiﬁed speciﬁc areas that are not satisfactorily

covered in their nutrition education: nutrition counseling, infant

and young children feeding, breastfeeding, and nutritional

treatment of micronutrient deﬁciencies.

HCPs mentioned that training is signiﬁcantly infrequent;

that they hadn’t received any nutrition care training in the past

year. The most recent source of information they had about the

contemporary infant feeding issues was the patients’ handouts

from the National Nutrition Institute. The only topic in which

HCPs received training was exclusive breast feeding (EBF) where

physicians and nurses have had similar exposure to training. Nurses

attended more training than physicians. However, there is a rapid

turnover of physicians and nurses, which makes such training

needed continuously.

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•Insuﬃcient time to provide quality nutrition care

Physicians ascertained that they could not provide quality

nutrition counseling in the CSPM malnutrition clinic due to the

high caseload for the small number of physicians and nurses.

Thus, they do not have enough time for growth monitoring

or caregiver education on EBF, infant nutrition, sick children’s

nutrition, and pregnant women’s nutrition. In addition, they added

that there are too many patients per day, patient contact time is

roughly 20–25 min long, and there are around 40 patients every

day, except on Saturdays, on which there are even more patients.

Three HCPs said local women are always interested in hearing

them talk and demonstrate rather than watching or reading

visual materials independently. HCPs explained that with so little

time spent with patients in the clinic, nutrition counseling is

quite challenging. One physician said, “In my opinion, there

are relatively few things that doctors can do to help set up the

malnutrition clinic because malnutrition is a complex problem

that necessitates behavioral intervention. However, there is not

enough time for that,” and “Physicians focus on immediate

medical concerns instead of the more long-term concern of

childhood nutrition.”

•Shortage in the workforce and lack of motivation

HCPs cited a shortage in staﬃng as a barrier to meeting

their clients health and nutrition needs. They all mentioned,

“There has been no new recruitment of residents and nurses,

no incentives or support in recognition of our hard work.”On

the other hand, the low salary (1200 LE per month), insuﬃcient

opportunities for ﬁnancial growth, and the lack of professional

advancement increased the turnover rate of the already-appointed

residents. Temporary contracts were used to hire all new doctors.

The consensus among HCPs was that “There is a need for more

service providers.”

•Shortage in logistics and supplies

HCPs demarcated the scarcity of visual PEM,resources for

demonstrations for nurses regarding infant feeding, especially

breastfeeding charts, posters (particularly those showing local foods

in food groups and demonstrating proper hygienic practices),

information leaﬂets, booklets, and picture information cards. In

general, the availability of PEM for caregivers was suboptimal for

all areas of child health except for child feeding starting at 6 months

up to 9 years of age.

Weighing scales (for babies and pregnant women), stature

measuring boards (for length and height), oral rehydration

solution (ORS), and infant formula milk for infants in particular

categories (6–24 months) were available. However, nutritional

supplements such as iron, zinc, folic acid, and vitamin A

were suboptimal and coupled with a marked shortage of PEM

addressing micronutrient deﬁciencies.

There were no CSPM-speciﬁc guidelines or national

protocols for the nutritional management of malnourished

children. Only educational and instructional leaﬂets from

the National Nutrition Institute for complementary feeding

are available.

Caregivers-centered barriers

•Low socioeconomic status (SES)

HCPs recognize that “childhood malnutrition is a complicated

problem inﬂuenced by numerous factors.”This concept makes

HCPs understand that there are barriers facing caregivers face in

trying to comply with nutritional advice. The most obvious barrier

is the low SES status with subsequent limited access to healthy food

and inability to recall the detailed medical advice provided.

Physicians mentioned that caregivers usually have limited

nutrition knowledge, preventing them from selecting and

preparing healthy complementary food. One HCP said, “Many

parents who are unaware of what is and is not healthy for

their children.”

•Culture and context:

Recognizing that people had prior speciﬁc cultural or

traditionally-rooted beliefs is critical. This included the belief that

breastfeeding after getting pregnant could cause kwashiorkor in

the breastfed child. The potential conﬂict between health workers’

counseling and cultural beliefs and perceptions is more general,

extending beyond nutrition issues, and has been well known.

Suggestions of HCPs to improve

performance in the malnutrition clinic

•Updating knowledge by continuing medical education (CME)

HCPs demanded more nutrition education, saying it could be

provided through periodic rotations and seminars. One physician

said, “We are provided periodic lectures on asthma; why we do not

have lectures on nutritional therapy for malnutrition? Not only to

teach us about malnutrition epidemiology, but to show us some of

the techniques and resources we could need in the future, as well

as to instruct us on how to deal with patients in the real world.”

One physician said, “To help parents improve their infants’

nutrition, doctors must be aware of the speciﬁc advice they

can give the caregivers regarding their infants’ feeding—what,

when, and how to feed.” HCPs expressed a need for speciﬁc

hints on preparing healthy food that could be shared with

patients. HCPs stated that they required evidence-based nutrition

expertise in addition to patient-friendly information. They valued

recommendations based on scientiﬁc literature.

HCPs mentioned the most needed topics to emphasize in

education: “breastfeeding, complementary feeding for 6- to 24-

month-old children, counseling skills, and communication skills.”

They recommended getting continuous support and training

through nutrition seminars and the introduction of software

programs on nutrition counseling to facilitate and ensure proper

quality performance of HCPs in malnutrition management, such as

history taking, diagnosis, and nutrition education and counseling,

including standardization of the nutrition counseling process. In

addition, the curriculum of undergraduate training for medical and

nursing students should include applied nutrition.

•Counseling skills

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HCPs aﬃrmed the need for “more capacity-building in

nutrition counseling”as practical training on counseling caregivers

is crucial for learning by doing.

Four out of ﬁve interviewees believed that physicians and

nurses have the greatest need to understand nutrition education,

communication, and counseling because they are in direct contact

with the target groups for nutrition care (mothers and children). In

Egypt, the public and patients usually seek nutritional advice and

counseling from physicians, who often lack nutrition knowledge.

Regarding service delivery, there was a consensus that CSPM

clinics needed to be strengthened by providing them with the

required staﬃng for nutrition care services, nutrition training

facilities (e.g., a working nutrition kitchen), and PEM to support

both preventive and curative nutrition care. HCPs expressed a

willingness to provide quality services if the necessary resources

were made available and the issue of a large caseload was addressed.

They also suggested increasing the availability of dieticians in

childcare clinics, including malnutrition clinics.

Counseling was a challenging demand as counselors, on the one

hand, try to simplify messages to make them easily understandable,

and simultaneously provide mothers with suﬃcient information to

make informed choices.

•Guidelines for eﬃcient and eﬀective nutrition care service

Guidelines must be developed on values that match the SES and

culture of the clients. Disregarding those aspects have numerous

and severe drawbacks, including infeasibility/inapplicability of the

medical recommendations, confusion among both mothers and

HCPs, and harmful feeding practices with diets that are inadequate

for meeting the nutritional needs of the children.

Quantitative data analysis results

The PEM provided to the caregivers at the malnutrition

clinic was assessed using the PEMAT-P scoring tool regarding the

understandability and actionability of the material.

The PEM had an understandability score of 54% and an

actionability score of 40%, respectively (Tables 1A,B).

Discussion

The current study explores the barriers to providing adequate

nutrition care to children as perceived by the workforce (HCPs)

at the CSPM malnutrition clinic which exists in a law-resource

setting (i.e., has minimal budget allocations and serves a low-

SES community). Although this clinic is logistically, ﬁnancially,

and legally aﬃliated with the MOH, it is located at the

Children’s Hospital of the Faculty of Medicine, Cairo University.

It is considered a reference center to which cases diagnosed

as malnutrition are referred from the hospital clinics. The

CSPM malnutrition clinic is considered a model center for

managing children’s malnutrition using nutritional supplements

and nutrition education to caregivers. Therefore, the conduction

of the current study was crucial to help in decision-making for

improving performance in the CSPM malnutrition clinic.

The study delineated that the most frequent malnutrition

problems encountered in the studied clinic were nutritional

deﬁciencies, namely rickets, underweight, kwashiorkor, and failure

to thrive. This ﬁnding is consistent with the existing evidence in

Egypt as per the Egypt Demographic and Health Survey (EDHS)

and other local studies (12). The evidence also demonstrates that

the signiﬁcant factors, namely poverty, low maternal education

level, and lack of health and nutrition awareness among parents,

contributing to the high prevalence of such nutritional problems

are related to the low SES of children caregivers (3,17).

The study revealed the barriers to providing adequate nutrition

care in three broad themes: physician-centered, health system-

centered, and caregiver-centered.

The physician-centered barriers included limited education

in clinical nutrition, mainly applied practical tactics, in medical

school during both the undergraduate and postgraduate programs.

HCPs perceived this barrier as the primary barrier. Many studies

assessing the situation of nutrition education in medical schools

have reported both undergraduate and postgraduate nutrition

curricula as insuﬃcient with a limited capacity of learners to

identify cases of malnutrition or provide nutrition education for

patients (18–20). However, other studies suggested that there is no

need for more nutrition education in medical schools. The only

requirement is to train future medical professionals to understand

the role of nutrition in health and to encourage them to refer

patients for nutrition counseling with a registered nutritionist

or registered dietitian who is more qualiﬁed to provide dietary

advice due to their greater education, training, and experience (21).

Nevertheless, physicians who lack the necessary nutrition training

could postpone making the initial diagnosis of malnutrition cases

with the subsequent delay in the referral of cases to nutritionists or

dieticians (7,22).

The WHO deﬁned the health system as all organizations,

people, and actions whose primary purpose is to promote, restore,

and maintain health (23). Therefore, as with any system, health

system components are resources (workforce, ﬁnances, technology,

and information, including updated standard of practice (SOP)

and guidelines, process (the way of resource management), and

output (range of provided services, e.g., how many of the clients

are covered with services).6In our study, health system-centered

barriers are related to the resources and process components of the

health system.

There was a workforce shortage due to insuﬃcient HCPs

regarding the high caseload. Hence, it was not only the lack of or

inadequate skills of HCPs that hindered the provision of adequate

nutrition counseling but also the insuﬃcient time available

for each patient. Individual needs should be considered when

developing and communicating nutrition advice (24). Accordingly,

afull assessment and understanding of the patient’s psychosocial

needs require roughly 15 min longer than simply comprehending

the patient’s initial complaint (22,25). With the limited time

concerning the high caseload, it is impossible to set aside that time

for a needs analysis or dietary counseling.

6 Available online at: https://healthmanager.ie/2011/03/the-dierences-

between-outputs- and-outcomes/ (accessed September 20, 2021).

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Our ﬁndings also revealed the failure of the CSPM

administration to recruit more HCPs, retain the competent

HCPs, or upgrade the nutrition-related knowledge and service

delivery skills of the existing HCPs, e.g., through providing updated

SOP or guidelines and conducting periodic skill-based training.

This situation led HCPs to try gaining updated information,

infrequently and irregularly, from another healthcare institute,

such as the National Nutrition Institute (NNI) at Cairo University.

In addition, HCPs complained of a lack of motivation due to

the absence of appropriate incentives. Although some studies found

that ﬁnancial incentives did not cause long term behavior changes

among physicians (26), yet, several other studies aﬃrmed that the

ﬁnancial and otherwise incentives inﬂuence the behavior of HCPs

in various ways, including adjustments to their output volume

and eﬀectiveness, as well as the type and standard of services they

provide to clients (27,28).

Nutritional supplementation with adequate nutrition

education is an evidence-based essential package of nutrition

interventions, particularly in low SES communities. To be eﬀective,

this package should be delivered during key life stages, such as

during pregnancy and throughout childhood (29,30). Hence,

the lack of health technology and supplies such as nutritional

supplements and PEM was viewed by the HCPs as a signiﬁcant

barrier to delivering adequate nutrition care. Moreover, the quality

of the existing PEM was described by the HCPs as inadequate.

This was also conﬁrmed by the low PEM understandability and

actionability scores (50 and 40%, respectively) which were far

below the lowest recommended level (70%) necessary for patients

to understand or act on the information they receive from the

material (13). This is expected because the communication section

of the MOH, which produces these PEMs, does not pre-test most of

the health education materials or update the channels of conveying

them. For instance, short educational videos that convey important

health messages in a simple and practical form are not available at

all at the CSPM.

Similar health system-centered barriers were stated by

physicians in several studies, such as the pivotal study conducted

by Kushner in 1995 and another study conducted 15 years later

(31,32). Those studies found that the most signiﬁcant barriers

to providing quality nutrition service were the lack of incentives

and time followed by the lack of updated knowledge. However, in

our study, HCPs ﬁrst stated the lack of updated knowledge and

refreshing training. This may be because Egypt’s health sector

workforce policy permits HCPs to work in both the public and

private health sectors, allowing HCPs to operate their private

clinics and increase their income.

Unfortunately, the insuﬃcient resource component of the

health system is a commonly encountered barrier in many

countries (8,31,32) because healthcare funds are skewed mainly

toward treatment, with little funds directed toward nutrition

education programs or malnutrition prevention in general (33,

34). However, the insuﬃcient resources barrier in child nutrition

care is more encountered in low-and-middle-income countries

and usually negatively impacts children under ﬁve the most.

This is unlike in higher-income countries where children who

are negatively impacted in nutrition care are those older than

5 years of age, usually hospitalized, with the barriers related

mainly to the process component of the health system (35).

Economic growth has been widely considered an eﬀective tool for

mitigating poverty and improving public health (4,33,36). In

Egypt, even though the total health expenditure- as an absolute

number- is increasing, the total health expenditure as a percentage

of the gross domestic product is declining. Also, the Egyptian

healthcare market is mainly based on out-of-pocket payments (the

expenses for healthcare that are not reimbursed by insurance)

(5,8,37). Thus, considering the progressively declining SES of the

Egyptian population, the Egyptian healthcare system, speciﬁcally

the preventive sector, whose budget is the primary source of

funds allocated for child nutritional care in the public sector,

is facing extreme ﬁnancial challenges (5,38). Cost-eﬀectiveness

(determining the expected gains and cost per gain) is central to the

health system’s success. Therefore, health system resources should

be directed to health services after making cost-eﬀective analyses

to decide on proper resource allocation, e.g., allocating resources

for nutrition care technology, such as nutritional supplements, and

speciﬁc community groups (39,40).

Implications

The study focused on a signiﬁcant public health problem

in Egypt and most developing and underdeveloped countries,

childhood malnutrition. This study tackled a crucial issue related to

the crucial role of pediatric clinical nutrition services in overcoming

such a problem. As well, the study provided valuable insight

into barriers to providing adequate nutrition care to children.

The identiﬁed barriers are essential when considering quality

improvement of nutrition care practices for malnourished children.

Strengths

First; the study was conducted in a model malnutrition clinic

in a Children’s Hospital, presenting a prototypical solution to

overcome children’s malnutrition problems and their impact on

growth and development. Second; the study was of a qualitative

research nature and thus provided an in-depth understanding

of barriers hindering the provision of adequate clinical nutrition

services and counseling. Third; using a speciﬁc approach for testing

the PEM added another dimension to the study, as it raised the

importance of capacity building in designing and testing the PEM.

And fourthly; the clinical nutrition concept was raised in the study

for speciﬁc pediatric clinics. The same concept could be applied to

other medical clinics.

Limitations

From our view, limitations of the study include that the

study was conducted in one center, the only reference center

for managing malnourished children. Additionally, as with any

exploratory operations research, information derived from the

study could not be generalized. However, the methodology used

in the study could be generalized to be used in diﬀerent medical

settings. Furthermore, the views of the clients (caregivers) were

not examined as it was beyond the scope of this study. Those

Frontiers in Public Health 07 frontiersin.org

Elhady et al. 10.3389/fpubh.2023.1064837

views may have led to more understating of nutrition services’

quality and barriers to adequate service. However, surprisingly,

previous studies, such as one conducted in Bangladesh, showed that

caregivers’ satisfaction was above average despite the low quality

of child nutritional services (27). The low expectations of the

caregivers in the low SES communities could explain this. Similarly,

a relatively high level of satisfaction could have been shown in

this study for the same reason and because there are not many

pediatric nutrition care clinics serving this district, making this

clinic a unique one-of-a-kind center.

Recommendations

To overcome barriers to providing adequate care in

malnutrition clinics, there are multifaceted approaches directed

to upgrading the resources and process components of the health

system as follows: Medical schools are encouraged to integrate

clinical nutrition in the pediatrics curriculum of undergraduate

and postgraduate medical students and nursing students. Also,

the specialty of clinical nutrition should be introduced into the

masters and doctorate degrees and clinical nutrition training

agenda should be included in the continuous medical education

program to improve nutrition-related knowledge, counseling

skills, and capacity building in designing and testing health

education materials. Furthermore, marketing for the unique

health and nutrition services provided to children in the nutrition

clinics motivates HCPs to work in such clinics and encourages

decision-makers to improve resources, especially regarding

nutritional supplements, to such clinics. Regarding MOH, we

recommend the establishment of pediatric clinical nutrition

fellowship programs, introducing clinical nutrition clinics in

the primary health care facilities and hospitals, increasing the

production and availability of nutritional supplements, particularly

for children’s most common nutritional deﬁciency problems, and

producing adequately designed and tested PEMs that suit the

sociodemographic characteristics of the served communities.

Conclusion

There are diﬀerent barriers to adequate nutrition care for

child malnutrition in low-resource healthcare settings. Mainly

nutritional deﬁciencies. Most of the barriers were health system-

related in the form of insuﬃcient resources (shortage of workforce;

concerning the high caseload, nutritional supplements, and PEMs)

and inadequate management of resources (lack of skill-based

training, lack of updated SOP and guidelines, and lack of

properly designed PEMs that facilitate communication with the

target caregivers).

Data availability statement

The raw data supporting the conclusions of this article will be

made available by the authors, without undue reservation.

Ethics statement

The studies involving human participants were reviewed and

approved by Faculty of Medicine, Cairo University (N-139-2022).

The patients/participants provided their written informed consent

to participate in this study.

Author contributions

GE has made substantial contributions to the

conception and design, analysis and interpretation of data,

and writing the manuscript. MS has made substantial

contributions to the acquisition of data and writing

the manuscript. AT, SH, EA, and SI were involved in

drafting the manuscript (Sections Methods and Results)

and revising it carefully for important intellectual content

and statistical analysis. All authors read and approved the

ﬁnal manuscript.

Conﬂict of interest

The authors declare that the research was conducted

in the absence of any commercial or ﬁnancial relationships

that could be construed as a potential conﬂict

of interest.

Publisher’s note

All claims expressed in this article are solely those of the

authors and do not necessarily represent those of their aﬃliated

organizations, or those of the publisher, the editors and the

reviewers. Any product that may be evaluated in this article, or

claim that may be made by its manufacturer, is not guaranteed or

endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found

online at: https://www.frontiersin.org/articles/10.3389/fpubh.2023.

1064837/full#supplementary-material

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Frontiers in Public Health 09 frontiersin.org

TYPE Review

PUBLISHED 27 March 2023

DOI 10.3389/fpubh.2023.1129258

OPEN ACCESS

EDITED BY

Catherine M. Capio,

The Education University of Hong Kong,

Hong Kong SAR, China

REVIEWED BY

Glauber Carvalho Nobre,

Ciência e Tecnologia do Ceará (IFCE), Brazil

Jovan Gardasevic,

University of Montenegro, Montenegro

*CORRESPONDENCE

Rong Gao

202021070001@mail.bnu.edu.cn

Guofeng Qu

201427070012@mail.bnu.edu.cn

Cong Liu

201831070001@mail.bnu.edu.cn

SPECIALTY SECTION

This article was submitted to

Children and Health,

a section of the journal

Frontiers in Public Health

RECEIVED 21 December 2022

ACCEPTED 13 March 2023

PUBLISHED 27 March 2023

CITATION

Liu C, Cao Y, Zhang Z, Gao R and Qu G (2023)

Correlation of fundamental movement skills

with health-related ﬁtness elements in children

and adolescents: A systematic review.

Front. Public Health 11:1129258.

doi: 10.3389/fpubh.2023.1129258

open-access article distributed under the terms

of the Creative Commons Attribution License

(CC BY). The use, distribution or reproduction

in other forums is permitted, provided the

original author(s) and the copyright owner(s)

are credited and that the original publication in

this journal is cited, in accordance with

accepted academic practice. No use,

distribution or reproduction is permitted which

does not comply with these terms.

Correlation of fundamental

movement skills with

health-related ﬁtness elements in

children and adolescents: A

systematic review

Cong Liu1*, Yuxian Cao2, Zhijie Zhang2, Rong Gao1*and

Guofeng Qu1*

1College of P.E. and Sports, Beijing Normal University, Beijing, China, 2Primary School Department,

Tianjin Binhai Foreign Language School, Tianjin, China

Objective: To examine the correlations between fundamental movement skills

and health-related ﬁtness elements (cardiopulmonary function, ﬂexibility, body

composition, muscle strength and endurance) in children and adolescents and

investigate the evaluation methods and tools of fundamental movement skills and

health-related ﬁtness.

Methods: Six electronic databases (Web of Science, PubMed, ProQuest,

Scopus, EBSCO and CNKI) were searched, and the research literature on the

correlation between children’s and adolescents’ fundamental movement skills and

health-related ﬁtness published since 2002 was collected. The guidelines of the

Strengthening the Reporting of Observational Studies in Epidemiology (STROBE)

statement and the Consolidated Standards of Reporting Trials (CONSORT)

statement were used to evaluate the quality of the literature, and the sources,

samples, measurement methods, main results and statistical data of the study were

analyzed, summarized and discussed.

Results: After applying the inclusion and exclusion criteria, 49 studies were

included. There were 13 tools for evaluating fundamental movement skills and 4

tools for evaluating comprehensive health-related ﬁtness in the included literature.

Sucient research evidence supports a signiﬁcant positive correlation between

fundamental movement skills and cardiopulmonary function (10, 100%) and

muscle strength and endurance (12, 100%), and most studies support the positive

correlation between fundamental movement skills and ﬂexibility (4, 66.7%), and

the signiﬁcant negative correlation between fundamental movement skills and

body composition (29, 67.4%). Studies used skinfold, AF%, BF%, FM, and FFMI as

evaluation methods. They showed a consistently signiﬁcant negative correlation

between body composition and fundamental movement skills (9, 100%), while

BMI or waist circumference as evaluation methods showed no consistent

signiﬁcant negative correlation result (20, 58.8%). Moreover, in the sub-item

evaluation of fundamental movement skills, object manipulation, locomotor and

balance skills were all signiﬁcantly and positively correlated with cardiopulmonary

function and muscle strength and endurance. In contrast, locomotor skills

were more closely related to body composition than object manipulation skills.

Frontiers in Public Health 01 frontiersin.org

Liu et al. 10.3389/fpubh.2023.1129258

Conclusion: A signiﬁcant correlation exists between children’s and adolescents’

fundamental movement skills and health-related ﬁtness elements.

KEYWORDS

fundamental movement skills, ﬂexibility, body composition, muscle strength and

endurance, cardiopulmonary function, health-related ﬁtness

1. Introduction

Fundamental movement skills are the basis for more advanced

and highly speciﬁc sports activities and are considered the “building

blocks” of more advanced, complex movements required to

participate in sports, games, or other context-speciﬁc physical

activities (1,2). Previous studies have conﬁrmed that fundamental

movement skills are associated with children’s physical, cognitive,

and social development and provide the basis for a positive

and healthy lifestyle (3,4). However, the relationship between

fundamental movement skills and physical health in the current

study has yet to be well documented, and whether fundamental

movement skills improve the individual’s physical health level

needs a more detailed discussion.

Health-related ﬁtness is closely related to health outcomes

and health indicators (5), which has been deﬁned by the

President’s Council on Physical Fitness as consisting of those

speciﬁc elements of physical ﬁtness that have a relationship

with good health, including body composition, cardiopulmonary

ﬁtness (cardiopulmonary function), and musculoskeletal ﬁtness

(ﬂexibility, muscle strength, and endurance) (6,7). Evaluating

health-related ﬁtness elements can provide data that help formulate

exercise prescriptions and establish reasonable and achievable

ﬁtness goals to motivate participants. Therefore, exploring

the correlations between health-related ﬁtness elements and

fundamental movement skills will help us understand the role of

fundamental movement skills in promoting physical health.

However, only a few studies have reviewed the association

between fundamental movement skills and health-related ﬁtness. In

a review of fundamental movement skills and the health beneﬁts of

children and adolescents, Lubans et al. (8) found that fundamental

movement skills were positively correlated with cardiopulmonary

ﬁtness (4 out of 4 studies) and negatively correlated with body

weight (6 out of 9 studies). Nevertheless, the relationship between

fundamental movement skills and musculoskeletal ﬁtness has not

been discussed due to the lack of relevant research at that time.

In 2016, Cattuzzoa et al. (9) reviewed the association between

motor competence and health-related ﬁtness elements. They

reported a positive association between motor competence and

cardiorespiratory ﬁtness and musculoskeletal ﬁtness and an inverse

association between body weight status. However, the motor

competence mentioned in this review study cannot be equated

with fundamental movement skills. Motor competence is a person’s

ability to execute diﬀerent motor acts (10), including fundamental

movement skills and motor coordination (11). Fundamental

movement skills are often described more precisely as basic

stability, object control and locomotor movements (2,12,13), while

motor coordination is a general term that encompasses various

aspects of movement competency (14), and needs the coordination

of complex neural networks (15). Moreover, there are diﬀerences

in the evaluation contents of motor competence and fundamental

movement skills. Therefore, Cattuzzoa et al. (9) conclusion cannot

be used to correlate fundamental movement skills and health-

related ﬁtness elements.

This review aims to systematically examine the correlations

between fundamental movement skills and health-related ﬁtness

elements, investigate the evaluation methods and tools of

fundamental movement skills and health-related ﬁtness, and

provide a scientiﬁc basis for theoretical and practical research on

fundamental movement skills and health-related ﬁtness.

2. Methods

2.1. Search of the literature

A structured electronic literature search was conducted under

the Preferred Reporting Items for Systematic Reviews and Meta-

Analyses (16). The search included six electronic databases (Web

of Science, PubMed, ProQuest, Scopus, EBSCO, and CNKI). The

retrieval was “[Title/Abstract] =(‘Fundamental Movement Skills’

OR ‘Motor skill’) AND [Title/Abstract] =(‘health related ﬁtness’

OR ‘health beneﬁts’ OR ‘body composition’ OR ‘body mass index’

OR ‘weight’ OR ‘fat percentage’ OR ‘cardiorespiratory ﬁtness’

OR ‘cardiopulmonary function’ OR ‘musculoskeletal ﬁtness’ OR

‘muscle strength’ OR ‘muscle endurance’ OR ‘ﬂexibility’). The

search was conducted from January 1, 2000, to November 23,

2022, and only literature in English and Chinese published in

peer-reviewed journals was considered.

Two researchers independently screened and reviewed the

literature and jointly determined the ﬁnal article list. If inconsistent

screening results occurred, a third researcher was asked to decide.

2.2. Eligibility criteria

A PECO (population, exposure, comparison and outcome)

approach (17) was used as inclusion criteria: (a) Population:

participants were 3–16 years old and were in preschool

education or school; (b) Exposure: fundamental movement

skills, including comprehensive fundamental movement skills or

subitems (locomotor, object manipulation, and balance skills); (c)

Comparison: health-related ﬁtness elements (cardiopulmonary

function, muscle strength and endurance, ﬂexibility, and body

Frontiers in Public Health 02 frontiersin.org

Liu et al. 10.3389/fpubh.2023.1129258

composition); (d) Outcome: report or data that makes it possible

to estimate associations.

The exclusion criteria were as follows: (a) research articles

on special groups, such as cardiovascular disease, developmental

coordination disorders, mental disorders, etc.; (b) intervention

study (literature on fundamental movement skills and health-

related ﬁtness association with an experimental intervention); (c)

study sample of fewer than 50 people; (d) no cross-sectional data

of fundamental movement skills and health-related ﬁtness; (e)

non-English or non-Chinese literature.

2.3. Data extraction and quality evaluation

The data extraction form retrieved the following information:

ﬁrst author and publication time, test method, health-related ﬁtness

elements, study design type, participant, and statistical method.

Two researchers independently completed the data extraction,

followed by discussion and cross-checking to ensure consistency

and accuracy.

The literature quality was assessed using the guidelines of

the Strengthening the Reporting of Observational Studies in

Epidemiology (STROBE) statement (18) and the Consolidated

Standards of Reporting Trials (CONSORT) statement (19), based

on Lubans et al. (8) and Cattuzzoa et al. (9). The quality

score for each study was based on six questions: (1) Did the

study describe the participant eligibility criteria? (2) Were the

participants randomly selected (or for the experimental studies,

was the randomization process clearly described and adequately

carried out)? (3) Did the study report the sources and details

of the FMS assessment, and did the instruments have acceptable

reliability for the speciﬁc age group? (4) Did the study report

the sources and details of the assessment of potential beneﬁts,

and did all the methods have acceptable reliability? (5) Did the

study report a power calculation, and was the study adequately

powered to detect the hypothesized relationships? (6) Did the

study report the numbers of individuals who completed each

of the diﬀerent measures, and did participants complete at least

80% of the FMS and beneﬁt measures? The above questions were

scored as 0 (missing or underdescribed) or 1 (clear description and

presence), and the scores for all questions were combined. Studies

scoring 0–2 were considered low-quality studies, studies scoring

3–4 were classiﬁed as medium-quality, and 5–6 were classiﬁed

as high-quality.

3. Results

3.1. Basic information about the literature

Figure 1 shows the study selection ﬂow chart. A total of

49 articles met the eligibility criteria. These articles all had

cross-sectional data, including 44 cross-sectional studies, four

longitudinal studies, and one long-term trend study. These articles

were published from January 2002 to November 2022. There were

42 English studies and 7 Chinese studies. Eight of the studies were

conducted in the UK, eight in China, six in the US, ﬁve in Australia,

ﬁve in Iran, four in Finland, four in Ireland, two in Croatia, and one

each in Canada, Slovenia, Brazil, Italy, the Czech Republic, South

Korea and South Africa. The study participants ranged from 50 (20)

to 6,917 (21). Details are given in Table 1.

3.2. Quality evaluation of the research

literature

The authors had a 94% consensus on the study assessment

criteria and reached a complete consensus after discussion. Twenty-

eight studies were identiﬁed as high-quality, 21 were rated

as moderate-quality, and none were classiﬁed as low-quality.

Most studies used valid and reliable measures of fundamental

movement skills assessment. All studies reported reliable data

on their potential beneﬁts, methods for valid calculations,

and whether the study had suﬃcient evidence to support the

hypothesis relationship.

3.3. Fundamental movement skills

assessment tools

The literature included 13 fundamental movement skill

assessment tools, as shown in Table 2. Because the research topics

were limited to fundamental movement skills, the literature using

Koperkoordination-Test fur Kinder (KTK) (81) and Bruininks-

Oseretsky Test of Motor Proﬁciency (BOTMP & BOT-2) (82),

mainly used to test motor coordination and ﬁne motor skills,

was omitted.

The included studies have diﬀerences in the selection of

fundamental movement skills evaluation tools. Thirty-ﬁve studies

(71.5%) used process assessment, including 20 studies that used

TGMD-2 as a single test, one used TGMD, 7 used POC, 3 used the

Fundamental motor skills Assessment, two used OSU-SIGMA, 1

used PDMS-2, and one used Passport for Life and PLAYbasic. Eight

(16.3%) studies used outcome assessments, 2 used the PE metric,

3 used the Move!, 1 study used POLYGON, and 2 used MABC-

2. Six (12.2%) studies used a combination of process and outcome

assessment, 5 of which used the TGMD-3 assessment tool, and 1

used the TGMD-2 and POLYGON.

3.4. Health-related ﬁtness assessment tools

Among the included literature, there were 4 tools for

comprehensive evaluation of health-related ﬁtness, including the

health-related ﬁtness test battery for children and adolescents

(ALPHA), FitnessGram assessment (FitnessGram), Monitoring

system for physical functional capacity (Move!) and National

Physical Fitness Test Standards Manual-Preschool part (NPFTSM-

Preschool).

ALPHA was published by Ruiz et al. (83) based on assessment

methodology for physical activity levels in the European Member

States. Testing included a 20-meter shuttle run, grip strength,

standing long jump, body mass index, skinfold thickness and

waist circumference.

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FIGURE 1

Flow chart of the literature review process.

FitnessGram is now the educational assessment of the

Presidential Youth Fitness Program (84). The test items include

pull-ups for boys/modiﬁed pull-ups for girls, straight leg sit-ups,

shuttle run, standing broad (long) jump, 50-yd dash, and softball

throw for distance, 600-yd run/walk, and three aquatic tests that

are rarely used.

Move! is a national physical functional capacity monitoring

and feedback system for Finnish 5th and 8th-grade pupils

(80). Move! consists of eight sections of measurements that

provide information about the state of physical functional

capacity. The sections measure pupils’ endurance, strength,

speed, mobility, balance, and fundamental movement

skills. The speciﬁc items are the 20-meter line run, ﬁve

continuous jumps, upper body lift, push-up, body mobility,

squat, lower back extension, right and left shoulders, and a

throw-catch combination.

NPFTSM-Preschool (85) was promulgated by the Ministry of

Education of the People’s Republic of China in 2003. The test

content included morphometric measures, a 10-meter return run,

standing long jump, tennis throwing, continuous jump, sit and

reach, and walking on the balance beam.

In addition to the above tools, some studies selected diﬀerent

evaluation tools for comprehensive utilization; for example, Behan

et al. (23) adopted BMI and waist circumference, sit and reach, grip

strength (86), plank (87), a 20 m sprint run (88) as health-related

ﬁtness assessment content.

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TABLE 1 Summary of the included literature.

Order References Date FMS test method Health-related ﬁtness

test method

Health-related

ﬁtness elements

Type of

study

Sample Statistical methods

1 Aalizadeh et al. (22) 2013 TGMD-2 BMI BC C 241 (age 7–10) Pearson correlation, multiple

linear regressions

2 Behan et al. (23) 2022 TGMD-3, vertical jump, balance BMI, WC, grip strength, plank,

sit and reach, PACER,

BC, CVE, MF, Flex C 2,098 (age 5–12) MANCOVA

3 Bolger et al. (24) 2019 TGMD-2 BMI, WC, 550-meter walk/run BC, CVE C 296 (mean age 7.9 ±2.0) Pearson correlation

4 Bryant et al. (25) 2014 POC BMI BC C 281 (age 6–11) MANOVA

5 Bryant et al. (26) 2014 POC BMI, BF% BC L T1: 281 (mean age 8.9 ±1.4);

T2: 252 (mean age 9.8 ±1.4)

Multiple linear regression

6 Butterﬁeld et al. (27) 2002 TGMD BMI B C C 65 (age 5–8) Multiple linear regressions

7 Chen et al. (28) 2016 PE metrics FitnessGram assessment CVE, MF, Flex C 565 (age 9–10) Multiple linear regressions

8 Comeau et al. (29) 2017 Passport for Life, PLAYbasic BMI, grip strength, PACER,

BF%

BC, CVE, MF C 145 (age 9–12) Pearson correlation, Multiple

linear regressions

9 Duncan et al. (30) 2017 POC BMI, BF% BC C 248 (age 6–11) MANCOVA

10 Duncan et al. (31) 2021 TGMD-2 BMI BC L T1: 177 (mean age 4.0 ±0.7);

T2: 91 (mean age 5.0 ±0.7)

Multiple linear regressions

11 Foulkes et al. (32) 2021 TGMD-2 BMI BC L T1: 240 (mean age 4.5 ±0.6);

T2: 181 (mean age 10 ±0.6)

Linear regression

12 Franjko et al. (33) 2012 TGMD-2, POLYGON BMI, BF% BC C 73 (Grade 2) Pearson’s correlation

13 Gu et al. (34) 2021 PE Metrics FitnessGram assessment, BMI BC, CVE, MF C 342 (mean age 8.4 ±0.50) Pearson correlation

14 Hardy et al. (21) 2012 POC PACER, BMI BC, CVE C 6,917 (age 7–14) Odds ratios (ORs)

15 Hua et al. (35) 2017 TGMD-2 BMI BC C 240 (age 7–10) One-way ANOVA

16 Huan et al. (36) 2019 TGMD-3 NPFTSM-Preschool MF, Flex C 646 (age 3–6) Canonical correlation

coeﬃcient

17 Hume et al. (37) 2008 Fundamental motor skills

Assessment

BMI BC C 248 (age 9–12) Pearson correlation

18 Huotari et al. (38) 2018 Move! BMI BC S T1: 2,390 (grade 9); T2: 1,346

(grade 9)

General linear model

19 Jaakkola et al. (39) 2019 Move! PACER, curl-up test, push-up CVE, MF L 491; T1: mean age 11.26; T2:

mean age 12.26

The standardized parameter

estimates of the multigroup

model

(Continued)

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TABLE 1 (Continued)

Order References Date FMS test method Health-related ﬁtness

test method

Health-related

ﬁtness elements

Type of

study

Sample Statistical methods

20 Jarvis et al. (40) 2018 POC ALPHA, 20-meter sprint BC, CVE, MF C n=553 (age 9–12) Zero order correlations

21 Jing et al. (41) 2019 TGMD-2 NPFTSM-Preschool MF C 498 (age 3–5) Partial correlation and

multiple regressions

22 Joensuu et al. (42) 2018 Move! FMI, FFMI BC C n=594 (mean age 12.4 ±1.3) Unstandardized regression

coeﬃcients

23 Jones et al. (43) 2010 POC BMI BC C 1,414 (age 9–11) One-way ANOVA

24 Kelly et al. (44) 2019 TGMD-3 BMI BC C n=414 (age 6–12) Independent samples t-tests

25 Kemp et al. (45) 2013 TGMD-2 Skinfolds, WC, BMI BC C 816 (mean age 6.87 ±0.39) One-way ANOVA

26 Khalaj and Amri (46) 2013 TGMD-2 BMI BC C 160 (age 4–8) One-way ANOVA

27 Kim and Lee (47) 2016 TGMD-2 BMI BC C 216 (age 5–6) Pearson correlation

28 Marinsek et al. (48) 2019 Eight FMS BMI BC C n=322 (age 5–10) MANCOVA

29 Morano et al. (49) 2011 TGMD-2 BMI BC C 80 (mean age 4.5 ±0.5) One-way ANOVA

30 Musalek et al. (50) 2017 MABC-2 Skinfolds, BMI BC C 152 (age 3–6) Variance ANOVA

31 Ner vik et al. (19) 2011 PDMS-2 BMI BC C 50 (age 3–5) Pearson correlation, multiple

regressions

32 Okely et al. (51) 2004 Fundamental motor skills

Assessment

BMI, WC BC C 4,363 (grades 2, 4, 6, 8, 10) Multiple linear regressions

33 Poulsen et al. (52) 2011 TGMD-2 BMI BC C 116 (mean age 8.6 ±1.4) Multiple linear regressions

34 R ainer and Jarvis (53) 2019 POC ALPHA BC, CVE, MF C 307 (age 10–11) Pearson product-moment

correlation

35 Roberts et al. (54) 2012 MABC-2 BMI BC C 4,650 (age 4–6) One-way ANOVA

36 Roscoe et al. (55) 2019 TGMD-2 BMI BC C 185 (age 3–4) Univariate ANOVA

37 Shengkou et al. (56) 2015 TGMD-2 NPFTSM-Preschool, BMI BC C 289 (age 3–6) Correlation analysis

38 Siahkouhian et al. (57) 2011 TGMD-2 BMI BC C 200 (age 7–8) Pearson correlation

39 Slotte et al. (58) 2015 TGMD-2 BF%, AF%, WC, BMI BC C 304 (age 8) Spearman’s correlations

40 Spessato et al. (59) 2012 TGMD-2 BMI BC C 178 (age 4–7) Multiple regression

41 Vameghi et al. (60) 2013 OSU-SIGMA BMI BC C 400 (age 4–6) Multiple regression

42 Vameghi et al. (61) 2013 OSU-SIGMA BMI BC C 600 (age 3–6) Kendall’s tau-b test

43 Webster et al. (62) 2021 TGMD-2 BMI, BF%, FMI, FFMI BC C 244 (mean age 6.05 ±2.01) Multiple linear regressions

44 Wesley et al. (63) 2016 TGMD-2 BMI BC C 85 (mean age 12.7 ±0.4) Multiple linear regressions

45 Yameng et al. (64) 2019 TGMD-3 NPFTSM-Preschool, BMI MF, Flex, BC C 201 (age 3–5) One-way ANOVA

(Continued)

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TABLE 1 (Continued)

Order References Date FMS test method Health-related ﬁtness

test method

Health-related

ﬁtness elements

Type of

study

Sample Statistical methods

46 Yang et al. (65) 2015 TGMD-2 BMI BC C 1,200 (age 3–7) One-way ANOVA

47 Yanmin et al. (66) 2021 TGMD-3 NPFTSM-Preschool MF, Flex C 304 (age 3–6) Partial and bivariate

correlation, multiple

regressions

48 Yuanchun et al. (67) 2013 TGMD-2 BMI BC C 852 (age 6–9) One-way ANOVA, Kendall’s

tau-b test

49 Zuvela and Kezic

Krstulovic (68)

2016 POLYGON standing long jump, sit and

reach, 1/4-Mile

MF, CVE, Flex C 90 (age 8) Multiple linear regressions

FMS, fundamental movement skills; TGMD, test of gross motor development; POC, get-skilled get-active process-oriented checklists; POLYGON, a new fundamental movement skills test for 8-year-old children; PE metrics, physical education metrics elementary

assessments; Move!, monitoring system for physical functional capacity; MABC, movement assessment battery for children-second edition; PDMS, peabody developmental motor scales; OSU-SIGMA, the Ohio State University scale of intra gross motor assessment;

BMI, body mass index; WC, waist circumference; PACER, progressive aerobic cardiovascular endurance run; BF%, body fat percentage; FitnessGram Assessment, Presidential Youth Fitness Program assessment; ALPHA, the health-related ﬁtness test battery for

children and adolescents; NPFTSM-Preschool, National Physical Fitness Test Standards Manual-Preschool part; AF%, abdominal fat percentage; FMI, fat mass index; FFMI, fat-free mass index; BC, body composition; CVE, cardiopulmonary function; MF, muscle

strength and endurance; Flex, ﬂexibility; C, cross-sectional study; L, longitudinal study; S, secular trend study;T1, the ﬁrst measurement; T2, the second measurement; MANCOVA, multivariate analysis of covariance; ANOVA, analysis of variance.

Moreover, health-related ﬁtness assessment can be an overall

assessment of all elements, and it can also be an assessment of only

one element. In evaluating sub-elements of health-related ﬁtness,

various tools have been used in the included studies.

The cardiopulmonary function was assessed by the PACER

(Progressive Aerobic Cardiovascular Endurance Run), 550 m

walking and running test (89) or long-distance running (68,89,90).

The musculoskeletal function was evaluated by two groups,

muscle strength and endurance, and ﬂexibility. Methods to assess

muscle strength and endurance included grip strength, curl-ups,

push-ups, plank, and standing long jump. Furthermore, methods

to assess ﬂexibility included sit and reach and trunk lifting.

Body composition assessment methods were body mass index

(BMI), waist circumference (WC), skinfold thickness, body fat

percentage (BF%), abdominal fat percentage (AF%), fat mass index

(FMI), and fat-free mass index (FFMI).

3.5. Correlation between fundamental

movement skills and cardiopulmonary

function

A total of 10 articles (19,23,24,28,29,34,39,40,53,68) have

studied the correlation between fundamental movement skills and

cardiopulmonary function, and all the ﬁndings showed a signiﬁcant

positive association between fundamental movement skills and

cardiopulmonary function.

Among the subitems of fundamental movement skills, ﬁve

studies (19,23,29,34,39) showed a signiﬁcant correlation between

locomotor skills and cardiopulmonary function, six studies (19,

23,28,29,34,39) showed a signiﬁcant correlation between

object manipulation skills and cardiopulmonary function, and

three studies (19,29,39) showed a signiﬁcant association between

balance skills and cardiopulmonary function. Thus, there is strong

evidence for a positive association between the total and subitems

of fundamental movement skills and cardiopulmonary function.

3.6. Correlation between fundamental

movement skills and muscle strength and

endurance

A total of 12 studies (23,28,29,34,36,39–41,53,64,66,68)

were included that evaluated the correlation between fundamental

movement skills and muscle strength and endurance. These studies

found a signiﬁcant positive correlation between total fundamental

movement skills and muscle strength and endurance.

Regarding the subitems of fundamental movement skills,

seven studies (23,29,34,36,39,64,66) showed a positive

correlation between locomotor skills and muscle strength and

endurance, eight studies (23,28,29,34,36,39,64,66) showed

a signiﬁcant correlation of object manipulation skills with muscle

strength and endurance, and three studies (34,40,68) showed a

signiﬁcant correlation between balance skills and muscle strength

and endurance. All studies supported the conclusion that the total

and subitems of fundamental movement skills were signiﬁcantly

positively correlated with muscle strength and endurance.

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TABLE 2 List of fundamental movement skill evaluation tools.

Evaluation tools Full name Publisher, date Applicable

age

TGMD Test of gross motor development Ulrich (69) 3–10

TGMD-2 Test of Gross Motor Development-2 Ulrich (70) 3–10

TGMD-3 Test of Gross Motor Development-3 Ulrich (71) 3–10

POC Get-skilled Get-active process-oriented checklists Bibby (72) 3–12

Fundamental motor

skills assessment

Fundamental motor skills assessment: A manual for classroom teachers Walkley et al. (73) 3–10

POLYGON A new fundamental movement skills test for 8-year-old children Zuvela et al. (74) 8

OSU-SIGMA The Ohio State University scale of intra gross motor assessment Loovis and Ersing (75) 2.5–14

MABC-2 Movement assessment battery for children-2 Henderson and Sugden (10) 3–16

PE metrics Physical education metrics elementary assessments Dyson et al. (76) 3–18

PLAYbasic The physical literacy assessment for youth Kriellaars (77) 7–12

Passport for life Passport for life assessment Physical & Health Education Canada (78) 8–12

PDMS-2 Peabody developmental motor scales 2nd edition Folio and Fewell (79) 0–6

Move! Monitoring system for physical functional capacity The Finnish National Ministry of

Education and Culture (80)

7–18

3.7. Correlation between fundamental

movement skills and ﬂexibility

Six studies examined the correlation between fundamental

movement skills and ﬂexibility. Four studies (23,28,36,66) showed

a signiﬁcant correlation between fundamental movement skills and

ﬂexibility, and 2 showed no signiﬁcant correlation (29,64).

Moreover, as to the subitems of fundamental movement skills,

one study showed that locomotor skills were signiﬁcantly associated

with ﬂexibility, but the correlations between object manipulation

skills and ﬂexibility were not signiﬁcant (66). Another study

(23) found that three subitem skills in the 9–10 age group and

the ﬂexibility association were signiﬁcant; however, in the 11–

12 age group, locomotor, and balance skills were still signiﬁcant,

while object manipulation skills were no longer signiﬁcant. These

results indicate that the evidence of the relationship between the

total and subitems of fundamental movement skills and ﬂexibility

is uncertain.

3.8. Correlation between fundamental

movement skills and body composition

Forty-three studies examined the correlation between

fundamental movement skills and body composition. Twenty-nine

studies showed a signiﬁcant association of overall fundamental

movement skills with body composition, and 14 showed no

signiﬁcant association with body composition. Of the 29

signiﬁcantly related studies, 18 studies used BMI alone as an

assessment, four studies (26,29,31,33) used BMI and BF, two

studies (24,53) used BMI and waist circumference, one study

(50) used BMI and skinfold thickness, one study (45) used BMI,

waist circumference and skinfold thickness, 1 used BF%, AF%,

BMI, and waist circumference (58), 1 used FMI and FFM (42),

and 1 used BF%, BMI, FMI, and FFMI (62). Of the 14 studies

showing no signiﬁcant association with body composition, 13

studies (19,22,27,35,37,40,47,53,55,56,59,64,67) used BMI

as a single body composition assessment method, and one article

(24) used both waist circumference and BMI. Overall, studies that

used skinfold, AF%, BF%, FM, and FFMI as evaluation methods

obtained consistently signiﬁcant negative correlation results, while

in studies that used BMI or waist circumference as evaluation

criteria, there was no consistent signiﬁcant correlation result.

Furthermore, as to the subitems of fundamental movement

skills, three studies (23,29,39) showed a consistent inverse

correlation of balance skills with body composition. Meanwhile,

locomotor skills and body composition reﬂected a more signiﬁcant

correlation than object manipulation skills. Six studies (34,35,

45,54,57,62) showed that object manipulation skills were not

associated with body composition, while locomotor skills were

signiﬁcantly associated with body composition. Therefore, there is

evidence that the relationship between locomotor skills and body

composition is closer than that of object manipulation skills.

4. Discussion

The main objective of this review was to explore the

correlation between fundamental movement skills and health-

related ﬁtness elements in children and adolescents. We found

strong evidence from cross-sectional study results that the

children’s and adolescents’ fundamental movement skills and

cardiopulmonary function, muscle strength and endurance had

a signiﬁcant positive correlation. These results complement the

need for correlation analysis between fundamental movement

skills and musculoskeletal function by Lubans et al. (8) and

also make up for the lack of speciﬁc correlation analysis

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between fundamental movement skills and health-related ﬁtness in

Cattuzzoa et al. (9).

The positive correlation between fundamental movement

skills and cardiopulmonary function may be related to the

role of fundamental movement skills in promoting physical

activity. Previous studies have proven that fundamental movement

skills are associated with moderate- to high-intensity physical

activity (4,24,25,29). Bolger et al. (24) believed that

people with higher fundamental movement skills are more

likely to participate in organized physical activities, which will

allow them to obtain more guidance on basic athletic skills

from coaches and promote the improvement of their physical

activity intensity.

As for the positive correlation between fundamental

movement skills and muscle strength and endurance, this

may be because fundamental movement skills contribute

to the maturation of skeletal and neuromuscular. Freitas

et al. (91) believed that individual diﬀerences in fundamental

movement skills interact with the habits of play and physical

activities, as well as with the maturation of children’s bones

and neuromuscular. Stodden et al. (92) also noted that

fundamental movement skills require the generation and

decay of physical strength, which is related to the strength

of the muscle itself and the neural function related to

muscle movement.

The negative correlation of fundamental movement skills with

body composition has been conﬁrmed in most studies but has yet

to obtain consistent results, which may be related to how body

composition is assessed. Using BMI and waist circumference as

evaluation criteria did not obtain consistent correlation results,

while studies with skinfold, BF%, AF%, FM, FM, and FFMI as

evaluation results showed consistent negative correlation results.

Previous studies have also found that BMI and waist circumference

are proxy measures and should not be considered accurate

measures of total body or abdominal fat (26,93,94). In assessing

body composition, it is crucial to assess weight status using more

accurate methods than BMI alone to obtain more precise evidence.

A possible reason for the negative correlation of fundamental

movement skills with body composition is that an increased

amount of body fat hinders the performance of fundamental

movement skills (9), which may aﬀect the control of posture.

Marinsek et al. (50) found that overweight boys did not lean slightly

forwards during running compared with non-overweight boys, did

not bend their hips and knees during dribbling, and did not side

to the target during single-handed hitting. From the perspective

of postural control, strengthening the proﬁciency of motor skills

or increasing the muscle strength of body control can reduce

the adverse eﬀects of body weight. Based on this, when teaching

exercises to obese students, more attention should be given to the

exercise of movement and posture control, such as strengthening

the muscles and training fundamental movements.

Most studies support a signiﬁcant positive correlation between

fundamental movement skills and ﬂexibility, but the association

of fundamental movement skills with ﬂexibility still needs

further study. Indeed, developing ﬂexibility is very important for

adolescent health, but there is insuﬃcient evidence that ﬂexibility

is directly related to individual health status (90), which could be

related to the limitations of ﬂexibility assessment. Flexibility mainly

reﬂects the stretching and elasticity of the joints, ligaments and

muscles. Excessive tension or relaxation can aﬀect the performance

of movement skills (95). Studies have found that children with low

exercise ability have heterogeneous ﬁtness characteristics, and an

extreme range of ﬂexibility and inﬂexibility can be observed in

these children (9). However, the current commonly used ﬂexibility

assessment method (sit and reach) cannot detect a lack of function

due to muscle relaxation. Of the studies on ﬂexibility assessment

included in this review, one used trunk lifting to assess ﬂexibility

(28), which showed that fundamental movement skills were

signiﬁcantly associated with ﬂexibility. However, the use of trunk

lifting has a speciﬁc need for trunk muscle strength and endurance,

and there is a lack of validated methods for evaluating the ﬂexibility

of children and the elderly (90). Overall, an appropriate level of

ﬂexibility has positive implications for motor skill development and

physical health, but exploring scientiﬁc and reasonable methods of

ﬂexibility assessment should receive more attention.

In addition, this study found some similarities and diﬀerences

in the correlations between the fundamental movement skills

sub-item (locomotor, object manipulation and balance skills) and

health-related ﬁtness elements. Locomotor, object manipulation

and balance skills with cardiopulmonary function, muscle

strength and endurance presented consistent positive correlations,

while locomotor and object manipulation skills were associated

diﬀerently with body composition. Six studies showed that object

manipulation skills were not associated with body composition,

while locomotor skills were signiﬁcantly associated with body

composition; this is quite diﬀerent from the conclusions of

some previous studies, in which object manipulation skills

were given great attention. Barnett et al. (96) noted that the

relationship between object manipulation skills and physical

activity is seen as a “positive feedback loop” and that those

with better object manipulation skills may be more willing

to participate in activities involving these skills. Vlahov et al.

(97) also found that object manipulation skills in a prospective

study of preschool children were better predictors of health-

related ﬁtness. However, the health-promoting eﬀect of object

manipulation skills on health-related ﬁtness is more of a concern

for the individual’s “willingness to participate.” There may be

great obstacles between “willingness to participate” in physical

activities and health-related ﬁtness, such as the impact of

the sports environment and atmosphere, the shift of physical

entertainment to internet entertainment, and the compromise

between students’ physical health goals and the goals of school

knowledge acquisition.

Conversely, developing individual locomotor skills is often

associated with greater body calorie expenditure, which may

contribute to maintaining a healthy body weight. Okely et al.

(98) noted that locomotor skills in overweight children tend

to be more diﬃcult to show because they need more support

and have a greater obstacle to exercise than object manipulation

skills. Locomotor skills can better promote the maintenance of

healthy body weight in the early stage of individual movement

development, which has the same positive signiﬁcance as

promoting object manipulation skills to encourage participation in

physical activity.

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4.1. Limitations and suggestions for future

research

Our study has limitations. Due to the lack of longitudinal

research literature, this study only analyzed cross-sectional

outcomes. Due to the various evaluation tools and large diﬀerences

in the outcome data types of the reviewed articles, this review

does not oﬀer a quantitative summary (i.e., meta-analysis).

With the increase in the research literature, future reviews

can analyze the impact of fundamental movement skills on

health-related ﬁtness from a longitudinal perspective, explore

scientiﬁc teaching strategies of fundamental movement skills,

and conduct quantitative research data analysis to obtain more

accurate correlations.

5. Conclusion

This systematic review found strong evidence that fundamental

movement skills correlated with health-related ﬁtness elements

(cardiopulmonary function, muscle strength and endurance, and

body composition) in children and adolescents. Most of the

studies supported the conclusion that fundamental movement

skills were also positively correlated with ﬂexibility. In the

fundamental movement skills subitems, object manipulation,

locomotor, and balance skills were signiﬁcantly and positively

correlated with cardiopulmonary function and muscle strength and

endurance, while locomotor skills were more closely related to body

composition than object manipulation skills.

Author contributions

CL and RG participated in the study design and protocol

and wrote the manuscript. GQ sorted out the research

process and retrieved literature. YC and ZZ screened the

literature and drafted the manuscript. All authors reviewed

the manuscript.

Acknowledgments

We thank the reviewers for their valuable suggestions.

Conﬂict of interest

The authors declare that the research was conducted

in the absence of any commercial or ﬁnancial relationships

that could be construed as a potential conﬂict

of interest.

Publisher’s note

All claims expressed in this article are solely those of the

authors and do not necessarily represent those of their aﬃliated

organizations, or those of the publisher, the editors and the

reviewers. Any product that may be evaluated in this article, or

claim that may be made by its manufacturer, is not guaranteed or

endorsed by the publisher.

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Frontiers in Public Health 12 frontiersin.org

EDITED BY

Leon Morales-Quezada,

Spaulding Rehabilitation Hospital, United States

REVIEWED BY

Enrico Cocchi,

Columbia University, United States

Karen Muller Smith,

University of Louisiana at Lafayette,

United States

*CORRESPONDENCE

Xiao-Dong Yang

xdyang@shutcm.edu.cn

Ke-Xing Sun

rehababy@126.com

†

These authors have contributed equally to this

work

SPECIALTY SECTION

This article was submitted to Children and

Health, a section of the journal Frontiers in

Pediatrics

RECEIVED 18 December 2022

ACCEPTED 20 March 2023

PUBLISHED 05 April 2023

CITATION

You H-z, Zhang J, Du Y, Yu P-b, Li L, Xie J, Mi Y,

Hou Z, Yang X-D and Sun K-X (2023)

Association of elevated plasma CCL5 levels with

high risk for tic disorders in children.

Front. Pediatr. 11:1126839.

doi: 10.3389/fped.2023.1126839

Yang and Sun. This is an open-access article

distributed under the terms of the Creative

Commons Attribution License (CC BY). The use,

distribution or reproduction in other forums is

permitted, provided the original author(s) and

the copyright owner(s) are credited and that the

original publication in this journal is cited, in

accordance with accepted academic practice.

No use, distribution or reproduction is

permitted which does not comply with these

terms.

Association of elevated plasma

CCL5 levels with high risk for tic

disorders in children

Hai-zhen You1†, Jie Zhang2†, Yaning Du2,3, Ping-bo Yu1, Lei Li4,

Jing Xie1, Yunhui Mi1, Zhaoyuan Hou2, Xiao-Dong Yang3,5,6*and

Ke-Xing Sun1*

Department of Traditional Chinese Medicine, Shanghai Children’s Medical Center, Shanghai Jiao Tong

University School of Medicine, Shanghai, China,

Department of Biochemistry and Molecular Cell Biology,

Shanghai Jiao Tong University School of Medicine, Shanghai, China,

Shanghai Institute of Immunology,

Department of Immunology and Microbiology, Shanghai Jiao Tong University School of Medicine,

Shanghai, China,

Clinical Research Center, Shanghai Children’s Medical Center, National Children’s

Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China,

The Research

Center for Traditional Chinese Medicine, Shanghai Institute of Infectious Diseases and Biosecurity,

Shanghai University of Traditional Chinese Medicine, Shanghai, China,

Center for Traditional Chinese

Medicine and Immunology Research, School of Basic Medical Sciences, Shanghai University of Traditional

Chinese Medicine, Shanghai, China

Abnormal levels of some peripheral cytokines have been reported in children

patients with tic disorders (TDs), but none of these cytokines can be a

biomarker for this disease. Our aim was to systemically proﬁle differentially

expressed cytokines (DECs) in the blood of TD patients, examine their

associations with TD development, and identify from them potential biomarkers

for the prediction and management of the risk for TDs. In this study, a cytokine

array capable of measuring 105 cytokines was used to screen for DECs in the

plasma from 53 comorbidity-free and drug-naïve TD patients and 37 age-

matched healthy controls. DECs were veriﬁed by ELISA and their associations

with TD development were evaluated by binary logistic regression analysis.

Elevation of a set of cytokines was observed in TD patients compared with

controls, including previously uncharacterized cytokines in tic disorders, CCL5,

Serpin E1, Thrombospondin-1, MIF, PDGF-AA, and PDGF-AB/BB. Further analysis

of DECs revealed a signiﬁcant association of elevated CCL5 with TD

development ( p= 0.005) and a signiﬁcant ROC curve for CCL5 as a risk factor

[AUC, 0.801 (95% CI: 0.707–0.895), p< 0.0001].

Conclusion: This study identiﬁes associations of a set of circulating cytokines,

particularly CCL5 with TD development, and provides evidence that high blood

CCL5 has potential to be a risk factor for TD development.

Clinical Trial Registration: identiﬁer ChiCTR-2000029616.

KEYWORDS

tic disorders, cytokine, biomarker, risk factor, inﬂammation

Introduction

Tic disorders (TDs) are childhood-onset neurodevelopmental conditions characterized

by sudden, rapid, recurrent, and nonrhythmic motor movements or vocalizations (1), and

based on the type of tics and duration of tic symptoms, they can be classiﬁed into 3

major groups: Tourette syndrome (TS), chronic tic disorder (CTD) and provisional tic

disorder (PTD). As the most common movement disorders in the pediatric population,

TDs affect up to 5% children worldwide (2). Previous literature have supported that this

disease can cause physical and mental impairments in multiple domains, such as

TYPE Original Research

PUBLISHED 05 April 2023

DOI 10.3389/fped.2023.1126839

Frontiers in Pediatrics 01 frontiersin.org

educational attainment, peer relationships, quality of life, and even

premature mortality (2,3). Tics tend to be refractory to medical

treatments and non-medical interventions, and most patients

experience relapses that often persist into adulthood. Prediction

and management of the risk for TD onset and relapse rely

largely on biomarkers which, however, are severely lacking (4).

The etiology of TDs appears to be complex and multifactorial.

Growing evidence reveals associations between TDs and various

immune disorders, including streptococcal infection-included

autoimmunity and many other autoimmune diseases, common

allergies, asthma, and maternal immune activation (2,5,6). A

recent large-scale genome-wide pathway analysis indicates an

implication of immune-related pathways in TS (7). These

ﬁndings link dysregulation of immune responses to TD

development. As critical effectors and modulators of immune

responses, hundreds of cytokines, consisting of interleukins,

chemokines and growth factors, have the potential to be involved

in TD development, which is favored by the fact that abnormal

levels of a few cytokines in the peripheral blood, like TNF-α,

IL-12 and IL-1βhave been reported in TD patients (8–10), and

the knowledge that TS-associated streptococcal infections are

certainly able to induce production of various cytokines. Previous

studies, however, were limited to a small number of cytokines,

leaving many more cytokines uncharacterized. The goal of this

study was to use a cytokine array to simultaneously proﬁle

plasma levels of over a hundred cytokines in TD patients and

controls, characterize differentially expressed cytokines (DECs),

and examine their potential associations with TDs.

Methods

Study design and participants

53 patients (median age 8, range 3–16 years) with CTD (11),

TS (12) or PTD (13) and 37 age-matched healthy children

(median age 9, 3–16 years) who passed outpatient physical

examination were recruited for this study. The patients were

diagnosed in accordance with the DSM-V criteria and evaluated

carefully to exclude those who had any known comorbidities,

including mental retardation, autism, attention deﬁcit

hyperactivity disorder, and those who received medication within

1 year before admission. The tic severity of each patient was

evaluated using the Yale Global Tic Severity Scale (YGTSS), a

gold-standard, clinician-administered, semi-structured interview

(14). A clinician rates motor and vocal tics in terms of number,

frequency, intensity, complexity and interference over the

preceding week as well as overall related impairment. Items are

rated on a scale from 0 to 5, with higher scores indicative of

higher tic severity. YGTSS shows moderate to excellent test–

retest reliability, good to excellent internal consistency, inter-rater

reliability, convergence validity and moderate to excellent

discriminant validity (12,14,15). The peripheral blood samples

were collected within 4 h of admission, and plasma was

immediately prepared, aliquoted, and stored at −80°C for analysis.

The study was approved by the Ethics Committee of Shanghai

Children’s Medical Center (SCMCIRB-K2019080-3), registered at

www.chictr.org.cn (ChiCTR-2000029616), and conducted

between July 2020 and November 2021. Informed consent and

verbal assent (as appropriate) were provided by parents or legal

guardians of all subjects. The study was carried out in

accordance with the Helsinki Declaration.

Detection of cytokines in the plasma

Plasma cytokine proﬁling was performed with a commercial

human cytokine array (R&D Systems, Cat. No.: ARY022B) to

measure the relative levels of 105 cytokines according to the

manufacturer’s instructions. Brieﬂy, equal volume of individual

plasmas had been mixed evenly for each group of patients and

controls, and the resultant 4 sets of mixed plasma samples were

subjected to the array analysis simultaneously. DECs detected in

TD patients were individually conﬁrmed by using Quantikine

enzyme-linked immunosorbent assay (ELISA) kits from R&D

Systems [CCL5(DY478), PDGF-AA(DY221), PDGF-BB(DY220)]

as described previously (11).

Statistical analysis

Data regarding subject characteristics are collected at ﬁrst visit.

Summary statistics for continuous variables are assessed by

Kolmogorov–Smirnov test and presented by mean ± standard

deviation. Unpaired t-test were used for normal distribution data,

while Wilcoxon test was used for skewed distribution data.

Correlations of DECs levels with tic severity that was scored by

following the YGTSS were tested by Pearson’s correlation test or

Spearman’s rank correlation test (depending on the distribution

of the variables). Due to the signiﬁcant differences in gender

between healthy control group and TD group, a binary logistic

regression analysis was performed to predict TD occurrence from

gender, CCL5, PDGF-AA in data collection section and results

were expressed by estimating odds ratios (OR) with their 95%

conﬁdence intervals. The predictive values of the binary logistic

regression analysis were determined using receiver operating

characteristic (ROC) curve analysis, and the area under the curve

(AUC) was calculated accordingly.

All the data were exported to Excel and SPSS statistics version 26.0.

Statistical analyses were performed using the SPSS, and GraphPad

Prism 7 was used for mapping. Two-tailed tests were conducted to

test statistical signiﬁcance, and the signiﬁcance level was set at p<0.05.

Results

Since comorbidities and prior medications are reported to

affect the blood levels of cytokines (10,16), we excluded

comorbid patients and those recently medicated when enrolling

tic disorder patients. To systemically compare the relative

expression levels of cytokines in TD patients and controls, we

You et al. 10.3389/fped.2023.1126839

Frontiers in Pediatrics 02 frontiersin.org

employed a cytokine array to proﬁle 105 cytokines

(Supplementary Table S1) in the plasma from 3 groups of TD

patients and 1 group of control (Table 1). Cytokine signals were

developed as spots on ﬁlm (Figure 1B), and pixel intensity of

each spot was quantiﬁed for an accurate comparison

(Supplementary Table S2). Consistent with previous studies that

reported elevation of proinﬂammatory cytokines, such as TNF-α,

IL-12 and IL-1β(8–10), these cytokines were also increased to

varying degrees in TD patients in our array assay (Supplementary

Table S2). A heatmap analysis of relative levels of all tested

cytokines indicated the overall similarities and differences between

controlsubjectsandthesegroupsofTDpatients(Figure 2).

Obviously, the major alterations in the 3 groups of TD patients

were elevations of a set of cytokines, including the chemokine

RANTES (also known as CCL5), Serpin E1, Thrombospondin-1,

MIF, PDGF-AA, and PDGF-AB/BB (a mixture of the B subunit

containing PDGF factors detected by antibody to the B subunit that

was incapable of distinguishing between AB and BB) (Figure 2),

that appeared to be the major DECs.

Among the major DECs, CCL5 that ranked in top 3 in all 3

groups of TD patients (Supplementary Table S2) and the two

related growth factors, PDGF-AA and PDGF-AB/BB, were

selected for further ELISA analysis which conﬁrmed that both

CCL5 and PDGF-AA were signiﬁcantly increased in all 3 groups

of TD patients (p< 0.02), and PDGF-BB was signiﬁcantly

augmented in TS and PTD patients (p< 0.05) but not in CTD

patients (Figure 3).

Correlation analysis of these 3 cytokines and tic severity of all

TD patients assessed with the YGTSS were revealed by Pearson’s

correlation test, no signiﬁcant correlation was found for any of

these cytokines (Figure 4). The predictive power of these three

cytokines and the gender of the subjects that also had a

signiﬁcant difference between patients and controls (Table 1)

were evaluated by using binary logistic regression analysis, and

the result revealed that both gender (p= 0.02) and CCL5

(p= 0.005) signiﬁcantly contributed to TD development (Table 2).

In the case of gender, TD incidence for boys was found to be

3.78 times higher than that for girls in this study (Table 2),

which is in line with the reported range of gender preference for

TD (17–19). Regarding CCL5, this analysis indicated that an

increase of CCL5 concentration by 100 pg/ml caused 50%

increase of risk for TD development (OR = 1.005, 95% CI: 1.001–

1.008, p= 0.005) (Table 2), suggesting a potential for CCL5 to be

a TD risk factor. Finally, we combined all TD patients and

control subjects for ROC analysis and found that CCL5 had a

signiﬁcant ROC curve [AUC: 0.801 (95% CI: 0.707–0.895), p<

0.0001] (Figure 3D). These results suggest CCL5 as a promising

predictor for the risk of developing TD.

Discussion

Aberrant levels of multiple cytokines have been observed in TD

patients in previous studies (8–10). However, to our knowledge,

TABLE 1 General clinical data of healthy control and TD patients.

Control (n= 37) TD (n= 53) p

Age (year) 8.89 ± 3.13 (4–15) 7.91 ± 2.71 (3–16) 0.12

Sex male (%) 17 (45.9%) 41 (77.36%) 0.001*

YGTSS 21.45 ± 7.60

Motor tics 9.19 ± 2.97

Vocal tics 4.53 ± 4.79

Impairment 7.74 ± 4.66

Values are shown as mean ± standard deviation (SD).

*Statistically signiﬁcant at p< 0.05.

FIGURE 1

Cytokine array analysis of plasma from patients with tic disorders and healthy controls. (A) Schematic diagram of cytokine array coordinates representing

105 different capture antibodies printed in duplicate. (B) Array results for control subjects, and TS, CTD, and PTD patients. Dots representing CCL5, PDGF-

AA, and PDGF-AB/BB are highlighted in red, blue and green, respectively.

You et al. 10.3389/fped.2023.1126839

Frontiers in Pediatrics 03 frontiersin.org

none of these cytokines have been characterized as a risk factor of

TDs. In this study we used a commercial cytokine array capable of

measuring 105 cytokines to unbiasedly proﬁle differentially

expressed cytokines in the plasma from comorbidity-free and

drug-naïve TD patients and healthy controls and evaluated their

associations with TD development. This assay provides the ﬁrst

set of large-scale cytokine proﬁling data that can be used as a

resource for future studies of TDs from the perspective of

cytokines. For the ﬁrst time, we discover CCL5 and PDGF-AA in

TDs as two major elevated cytokines in all 3 groups of TD

patients and demonstrate their association with TDs. More

importantly, we show that while having no correlation with tic

severity, peripheral CCL5 has the potential to be a risk factor for

evaluating the predisposition to TD development.

Elevation of CCL5 in the blood have been documented in

multiple central nervous system (CNS) diseases, such as

Parkinson’s disease (20), Alzheimer’s disease (21), Multiple

sclerosis (22,23), stroke (24), and Traumatic brain injury (25).

Interestingly, up-regulated blood CCL5 has also been identiﬁed

as a risk factor of ischemic stroke that could predict future stroke

events (24). These studies, together with ours, reveal a broad

association of blood CCL5 with CNS diseases and start to

unravel the emerging role of this chemokine in raising the risk

for these diseases.

CCL5 is a CC type of chemokine that is widely expressed by

many immune cells such as T lymphocytes, macrophages, and

platelets. The best known function of CCL5 is to control

activation and chemotaxis of many types of immune cells by

engaging its cognate receptors expressing on these cells, primarily

CCR5, thereby modulating immune responses (26). In the brain,

CCL5 and CCR5 are constitutively expressed in astrocytes and

microglia and regulate not only chemotaxis of immune cells but

also non-immune cell functions (13,27,28). It has long been

known that chemokines and their cognate receptors are involved

in regulation of glial and neuronal cell functions, and that the

interactions between glial cells and neurons and through CCR5

and its ligands, e.g., CCL5, are crucial for maintaining neuronal

activities, such as neurotransmitter release, ion channel gating

and long-term potentiation (27,29). For instance, after motor

neuron injury CCL5 attenuated excessive production of

neurotoxic inﬂammatory mediators in microglia via CCR5, and

CCR5 deﬁciency accelerated demise of motor neurons in mice,

suggesting that the CCL5/CCR5 pathway plays a neuroprotective

role in a manner independent of chemotaxis (30,31). A later

study with a mouse model of Parkinson’s disease further

demonstrated that CCR5 deﬁciency resulted in lower numbers of

dopamine neurons, reduced levels of striatal dopamine, and

decreased locomotor activity (29), indicating that the CCL5/

CCR5 pathway plays an important role in maintaining striatal

dopamine levels by promoting neuron survival.

The CCL5/CCR5 pathway involved in tic disorders remains

unclear so far. Pathologically, tic disorders are considered as a

disturbed interplay within and between different brain regions,

particularly the basal ganglia-cerebellar-thalamo-cortical network

FIGURE 2

Heat map of original derivation sample, comparisons calculated via

1-normal, 2-TS, 3-CTD, 4-PTD. The red, blue, and green boxes are

marked with cytokines that differ signiﬁcantly.

You et al. 10.3389/fped.2023.1126839

Frontiers in Pediatrics 04 frontiersin.org

(BGCTC) that functions to inhibit undesired actions. It has been

shown that the dysfunction of BGCTC plays a critical role in the

pathophysiology of tics (32). Moreover, excessive release of

striatal dopamine appears to be the reason for the dysfunction of

BGCTC in tic patients (33), and dopamine receptor D2

antagonists that can inhibit dopamine-induced effects represent

the most efﬁcacious pharmacotherapy of tics in clinic (34). Thus,

it is reasonable to speculate that the CCL5/CCR5 pathway may

control tic occurrence by modulating the dopamine neuron-

striatal dopamine-BGCTC axis.

Nevertheless, the origin of the elevated blood CCL5 levels is

unknown. There are at least two possibilities. One is that blood

CCL5 comes from the brain where an inﬂammatory response is

going on and a high level of CCL5 is produced to directly

disturb the dopamine neuron-striatal dopamine-BGCTC axis,

leading to tic symptoms. Meanwhile, the brain-generated CCL5

can somehow leak into the peripheral blood causing elevation of

blood CCL5. The other possibility is that the elevation of blood

CCL5 is due to diffusion from other inﬂamed organs/tissues. It

remains to be further studied how the increase of blood CCL5

leads to the risk of functional impairment of brain.

Given that chemokines in the peripheral blood by themselves

can hardly cross the blood–brain barrier (BBB) that mainly

consists of specialized brain microvascular endothelial cells to

control the entry of cells and damaging agents from the blood

to brain (35), it is unlikely that low-grade elevation of CCL5

in the blood can directly cause signiﬁcant detrimental effect to

the CNS. Interestingly, CCL5 and its cognate receptors,

including CCR5, have been shown to involve in the regulation

of BBB permeability and immune cells’entry into the brain.

By binding to proteoglycans attached to endothelial cells,

CCL5 can be immobilized on endothelial surfaces to enable a

high local concentration that facilitates its interaction with the

receptors expressed by incoming immune cells in the blood

(36). Adhesion of the immune cells to EC-immobilized CCL5

leads to signaling events triggering increase of BBB

permeability (35). Increase of BBB permeability presumably

exacerbates the access of insults that otherwise cannot

penetrate the BBB and enter the brain. In support of the

importance of CCL5 and its receptors for BBB regulation,

animal studies of epilepsy demonstrated that antagonist-based

inhibition of CCR5 on blood cells or blocking CCL5 can

reduce BBB permeability and mitigate disease severity (35). A

very recent in vivo study using highly sensitive radiochemical-

based assays showed that circulating CCL5 can be transported

across BBB in mice by binding to heparan sulfates at the

endothelial surface in a manner independent of CCR2 and

CCR5 (37). This ﬁnding raises another possibility that

FIGURE 3

Plots showing the levels of plasma CCL5, PDGF-AA, and PDGF-BB. Plots showing the levels of plasma CCL5 (A), PDGF-AA (B), and PDGF-BB (C) from

healthy controls and TD patients (TS, CTD, PTD. (D) ROC curve analysis combining CCL5 in the differential diagnosis between TD and normal. ROC,

receiver operating characteristic; AUC, area under the curve.

You et al. 10.3389/fped.2023.1126839

Frontiers in Pediatrics 05 frontiersin.org

circulating CCL5 may exert its regulatory role inside the brain. It

is interesting to explore if elevated circulating CCL5 plays a role

in reducing BBB permeability or contributing the brain level of

CCL5 in the pathogenesis of TDs.

There is evidence that in the brain increased CCL5 can cause

pathologic consequences by engaging its cognate receptors

CCR5 and CCR1 both of which are expressed on multiple

typesofcells,suchasmicroglia,astrocytesandneurons(38–

41). For example, in a mouse model of intracerebral

hemorrhage, CCR5 activation by intracerebroventricularly

administrated CCL5 promoted neuronal cell death in the form

of inﬂammatory proptosis, thereby leading to neurological

deﬁcits (38). Additionally, CCL5-CCR1-mediated microglial

activation in the brain resulted in neurologic deﬁcits and

neuroinﬂammation (42). These animal studies imply that

targeting the CCL5-CCR1/5 cascades in the brain could be a

promising therapeutic option for neurological diseases

associated with CNS.

Based on our ﬁndings, we propose that CCL5, and its cognate

receptors CCR1/5, could be potential therapeutic targets for TDs.

Given the nature of recurring of TDs, pharmaceutical lowering of

the level of blood CCL5, attenuation of expression or function of

CCR1/5, or inhibition of CCL5-CCR1/5 or CCL5-heparan

sulfates interactions, such as by CCL5 antagonist, monoclonal

antibodies to CCR1/5, or heparan sulfates competitive inhibitor

heparin (37), would hold promise for better risk management of

TD relapse.

Due to the limitations to this study that were caused by

relatively small numbers and a single cohort of patients, the

potential of CCL5 as a risk factor for TD development needs

to be validated in multicenter studies of larger cohorts in the

future.

Data availability statement

The original contributions presented in the study are included

in the article/Supplementary Material, further inquiries can be

directed to the corresponding authors.

FIGURE 4

The correlations of the levels of plasma CCL5, PDGF-AA, PDGF-BB with tic severity of all TD patients. The correlations of the levels of plasma CCL5 (A),

PDGF-AA (B), PDGF-BB (C) with tic severity of all TD patients assessed with the YGTSS.

TABLE 2 Analysis of inﬂuencing factors in children with TDs.

OR (95% CI) p

Gender 0.02*

female 1.00

male 3.79 (1.21–11.88)

CCL5 (pg/ml) 1.005 (1.001–1.008) 0.005*

PDGF-AA (pg/ml) 1.004 (0.99–1.01) 0.12

*Statistically signiﬁcant at p< 0.05.

You et al. 10.3389/fped.2023.1126839

Frontiers in Pediatrics 06 frontiersin.org

Ethics statement

The studies involving human participants were reviewed and

approved by IRB of Shanghai Children’s Medical Center Afﬂicted

to Shanghai Jiao Tong University School of Medicine. Written

informed consent to participate in this study was provided by the

participants’legal guardian/next of kin.

Author contributions

XY and KS conceived and supervised the project; HY and JZ

performed most of experiments; YD, PY, LL, and JS contributed

to the performance of the experiments; HY, YM, ZH and XY

analyzed data; HY, XY and KS wrote the manuscript. All authors

contributed to the article and approved the submitted version.

Funding

This study was supported by grants from National Key R&D

Program of China (2021YFA1301400), Shanghai Municipal

Science and Technology Major Project (ZD2021CY001),

Shanghai Science and Technology Commission (21ZR1456300),

Shanghai Children’s Medical Center (LY-SCMC2020-03), and

Shanghai Administration of Traditional Chinese Medicine

(ZHYY-ZXYJHZX-201918) [H-ZY (2021-2023)-0206-08].

Conﬂict of interest

The authors declare that the research was conducted in the

absence of any commercial or ﬁnancial relationships that could

be construed as a potential conﬂict of interest.

Publisher’s note

All claims expressed in this article are solely those of the

authors and do not necessarily represent those of their afﬁliated

organizations, or those of the publisher, the editors and the

reviewers. Any product that may be evaluated in this article, or

claim that may be made by its manufacturer, is not guaranteed

or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found

online at: https://www.frontiersin.org/articles/10.3389/fped.2023.

1126839/full#supplementary-material.

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You et al. 10.3389/fped.2023.1126839

Frontiers in Pediatrics 08 frontiersin.org

EDITED BY

Leon Morales-Quezada,

Spaulding Rehabilitation Hospital, United States

REVIEWED BY

Ancuta Lupu,

Grigore T. Popa University of Medicine and

Pharmacy, Romania

Vasile Valeriu Lupu,

Grigore T. Popa University of Medicine and

Pharmacy, Romania

*CORRESPONDENCE

Khitam Muhsen

kmuhsen@tauex.tau.ac.il

RECEIVED 02 April 2023

ACCEPTED 05 May 2023

PUBLISHED 19 May 2023

CITATION

Lapidot Y, Maya M, Reshef L, Cohen D, Ornoy A,

Gophna U and Muhsen K (2023) Relationships

of the gut microbiome with cognitive

development among healthy school-age

children.

Front. Pediatr. 11:1198792.

doi: 10.3389/fped.2023.1198792

Gophna and Muhsen. This is an open-access

article distributed under the terms of the

Creative Commons Attribution License (CC BY).

The use, distribution or reproduction in other

forums is permitted, provided the original

author(s) and the copyright owner(s) are

credited and that the original publication in this

journal is cited, in accordance with accepted

academic practice. No use, distribution or

reproduction is permitted which does not

comply with these terms.

Relationships of the gut

microbiome with cognitive

development among healthy

school-age children

Yelena Lapidot1, Maayan Maya1, Leah Reshef2, Dani Cohen1,

Asher Ornoy3,4, Uri Gophna2and Khitam Muhsen1*

Department of Epidemiology and Preventive Medicine, School of Public Health, the Sackler Faculty of

Medicine, Tel Aviv University, Tel Aviv, Israel,

The Shmunis School of Biomedicine and Cancer Research,

Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel,

Adelson School of Medicine, Ariel University,

Ariel, Israel,

Department of Medical Neurobiology, The Hebrew University Hadassah Medical School,

Jerusalem, Israel

Background: The gut microbiome might play a role in neurodevelopment,

however, evidence remains elusive. We aimed to examine the relationship

between the intestinal microbiome and cognitive development of school-age

children.

Methods: This cross-sectional study included healthy Israeli Arab children from

different socioeconomic status (SES). The microbiome was characterized in fecal

samples by implementing 16S rRNA gene sequencing. Cognitive function was

measured using Stanford-Binet test, yielding full-scale Intelligence Quotient

(FSIQ) score. Sociodemographics and anthropometric and hemoglobin

measurements were obtained. Multivariate models were implemented to assess

adjusted associations between the gut microbiome and FSIQ score, while

controlling for age, sex, SES, physical growth, and hemoglobin levels.

Results: Overall, 165 children (41.2% females) aged 6–9 years were enrolled. SES

score was strongly related to both FSIQ score and the gut microbiome. Measures

of α-diversity were signiﬁcantly associated with FSIQ score, demonstrating a more

diverse, even, and rich microbiome with increased FSIQ score. Signiﬁcant

differences in fecal bacterial composition were found; FSIQ score explained the

highest variance in bacterial β-diversity, followed by SES score. Several taxonomic

differences were signiﬁcantly associated with FSIQ score, including Prevotella,

Dialister,Sutterella,Ruminococcus callidus, and Bacteroides uniformis.

Conclusions: We demonstrated signiﬁcant independent associations between the

gut microbiome and cognitive development in school-age children.

KEYWORDS

gut microbiome, children, healthy, school age, cognitive development, socioeconomic status

1. Introduction

The gut microbiome is important in health and disease (1,2). The microbiota is

increasingly recognized for its ability to inﬂuence the nervous system and several complex

behaviors of the host, by modulation of neurodevelopment through the microbiome-gut-

brain axis (3,4).

The gut-brain axis is characterized by a bidirectional communication between the gut

and the brain, that might modify both gastrointestinal and nervous systems function,

inﬂuencing emotion and cognition (4). Preclinical and clinical studies showed that

variations in microbiota composition contribute to various cognitive states, including

TYPE Original Research

PUBLISHED 19 May 2023

DOI 10.3389/fped.2023.1198792

Frontiers in Pediatrics 01 frontiersin.org

functional brain connectivity, depression, stress, anxiety, and

autism spectrum disorder (5–12). The mechanisms underlying

these relationships are not fully understood, but a compelling

hypothesis is that gut microbiota variation during childhood with

vulnerable neurodevelopmental window, might inﬂuence both

mental and cognitive outcomes (13).

The ﬁrst years of life are characterized by intense structural and

functional changes in the brain and thus are critical for

neurodevelopmental plasticity (14). Intriguingly, these changes

occur simultaneously with dynamic intestinal microbiome

alterations, thus raising the possibility of dialogue between the

microbes that inhabit the gastrointestinal tract and the brain in

early life (15,16). Animal models demonstrated that early life

gut microbiome inﬂuences later neurodevelopment (17).

However, evidence from human populations remains limited and

focused merely on infancy, demonstrating the association between

the intestinal microbiome with both temperament (18,19)and

cognitive performance (12,20). Evidence suggests substantial

functional and taxonomic differences in the gut microbiota of

healthy children compared to those of adults, suggesting that the

development of gut microbiome may continue into school age and

more slowly than previously thought and that the gut microbiota

of children may be more malleable to environmental factors than

that of adults (21,22). Moreover, neurodevelopment remains

an ongoing critical process during the early to middle childhood

years (23), nevertheless the association between the microbiome

and cognitive development during school age remains elusive.

Environmental exposures, including socioeconomic status

(SES) play a critical role in both intestinal microbiome (24,25)

and neurologic development (26,27). Moreover, iron deﬁciency

anemia, a main risk factor for diminished neurodevelopmental

and cognitive abilities in children (28–30), was linked with the

gut microbiome, in both animal models and human studies (31–

33). However, the interconnection between the microbiome,

environmental exposures, and cognitive function in childhood is

not fully clear. To address these gaps, we examined the

association between the intestinal microbiome and cognitive

development of school-age children, with the possible

intermediating effect of environmental exposures, including

sociodemographics, physical growth, and nutritional status. Our

working hypothesis was that the gut microbiome might be

related to cognitive development of healthy school-age children,

independent of potential confounders.

2. Materials and methods

2.1. Study population and design

This cross-sectional study focused on a population under

transition, the Israeli Arab population, the main ethnic minority

in Israel. This population comprises 20% of the Israeli

population (34,35), while 75% are Jews and 5% belong to other

population groups. The Arab population has lower educational

levels and SES compared to the Jewish population (35,36), but

there is an ongoing improvement in the educational level and

health indicators among Arabs. Access to care is universal in

Israel, due to the universal health insurance law (37).

This study was conducted in 2007–2009, in three Arab villages

in Hadera sub-district. In 2007, there were about 153,000 Muslim

Arab residents living in this region, with 3,921 live births (34).

One village had approximately 14,000 residents during the study

period and the other two villages had about 10,000 residents

each. According to the Central Bureau of Statistics, one village

belonged to cluster 2 SES, one belonged to cluster 3 SES, and the

third village belonged to cluster 4 SES. The clusters are on a

scale of 1–10, the lower the index, the lower the SES (36). At the

national level, these villages are of low and intermediate SES

levels (36). Given the SES differences across the villages, they

were referred herein as village A = high SES, village B =

intermediate SES, and village C = low SES. The drinking water

supply in these villages is piped, and all households are

connected to the national electricity company similar to the rest

of the country. Connection to the internet and cable television is

also available.

In this cross-sectional study, we examined the gut microbiome

in archived stool samples obtained from healthy children who

participated in a study on gastrointestinal tract infections. Brieﬂy,

in 2003–2004, a cohort of 289 healthy children aged 3–5 years

from three villages of different SES were recruited. In 2007–2009,

a follow-up was performed among 196 children at age 6–9 years

(38,39). Overall, 176 children who provided stool samples had

sufﬁcient material for 16S rRNA sequencing. Eight children were

excluded due to medical conditions that might affect cognitive

function directly (thalassemia minor, type-1 diabetes, Glucose-6-

phosphate dehydrogenase deﬁciency with anemia, major heart

defect, panhypopituitarism, hemophilia, and signiﬁcant

developmental delay). Three additional children with missing IQ

scores were omitted from the analysis, thus leaving 165

participants in the analysis.

2.2. Data collection

Information on household and socioeconomic characteristics

was obtained via personal interviews with the mothers, by

trained Arabic-speakers interviewers. The questionnaire included

information on age, sex, the village of residence, maternal

education, maternal age, paternal education, monthly family

income, number of persons living in the household, and number

of rooms in the household. Crowding index was calculated by

dividing the number of people living in a household by the

number of rooms in a household. Data were collected on early

life determinants e.g., birth weight, breastfeeding, and daycare

center attendance.

2.3. Current hemoglobin levels

Blood collected by ﬁnger lancing was used for hemoglobin

measurement using a portable hemoglobinometer (Hemocue Hb

Lapidot et al. 10.3389/fped.2023.1198792

Frontiers in Pediatrics 02 frontiersin.org

201+, Sweden). Hemoglobin was assessed as an indicator of

nutritional status.

2.4. Anthropometric measurements

Anthropometric measurements were performed by trained

registered nurses. Body weight was measured to the nearest

0.1 kilogram using an analog scale (calibrated before use), and

height (to the nearest 0.1 centimeter) with a stadiometer.

Information on anthropometric measurements in early childhood

(ages 18–30 months) was obtained from medical records. Z

scores of height for age (HAZ), weight for height (WAZ), and

body mass index for age (BMIZ) were calculated using Epi/Info

software [Center for Disease Control and Prevention, Atlanta,

Georgia (CDC)] based on the 2,000 CDC growth reference

curves. BMI was calculated as weight (kg)/height (m)

2.5 . Socioeconomic status (SES)

Multiple SES indicators were examined: (1) community SES

rank as classiﬁed by the Israel Central Bureau of Statistics, (2)

household socioeconomic characteristics: (a) maternal education,

(b) paternal education, (c) crowding index, and (d) reported

family income. We used these variables to generate a composite

SES score, based on conﬁrmatory factor analysis. The analysis

was implemented using “Principal Axis”method, including

rotation with “varimax”(rpackage psych). Since maternal

education was signiﬁcantly correlated with parental education

(Pearson’sr= 0.46), we included only maternal education level in

the analysis. The selected variables were tested with Bartlett’s test

of homogeneity of variances (p-value <0.0001) and Kaiser–

Meyer–Olkin factor adequacy resulting in adequate scores for all

selected variables: village of residence = 0.7, crowding index = 0.7,

maternal education = 0.7, reported family income = 0.68. The

newly generated SES score was composed of a combination of

the standardized loadings, based on the correlation matrix of the

selected variables (Supplementary Figure S1).

2.6. Assessment of cognitive function

Cognitive function was measured by Intelligence Quotient (IQ)

score using Stanford-Binet-5th edition (SB5) test, performed by a

trained Arabic speaking psychologist (39). The following

parameters were assessed: full-scale IQ (FSIQ), non-verbal IQ

and verbal IQ. The test was performed at standard conditions,

lasting 45–60 min. The SB5 was scored with the SB5 Scoring Pro,

a Windows

-based software program. Since FSIQ is highly

correlated with non-verbal and verbal IQ (Pearson’s correlation

r= 0.95 and r= 0.94 respectively), FSIQ score was selected as the

main outcome variable in this study. The psychologist was

masked to background information of the participants.

2.7. Samples collection, DNA extraction and

bacterial DNA ampliﬁcation

Fresh stool samples were obtained from the children using

collection plastic cups and transferred on ice to the laboratory at

Tel Aviv University. Samples were divided stored at −80°C until

testing. All samples underwent a single thaw prior to DNA

extraction. DNA was extracted from 180 to 220 mg of fecal

material from each sample using the QIAamp

Fast DNA Stool

Mini Kit (Qiagen, Valencia, CA) following the manufacturer’s

instructions (40) and stored at −20°C until shipment to the

Sequencing Core at the University of Illinois. Genomic DNA was

prepared for sequencing using a two-stage amplicon sequencing

workﬂow (41). Initially, genomic DNA was ampliﬁed via PCR

using primers targeting the V4 region of microbial 16S ribosomal

RNA (rRNA) genes. The primers, 515F modiﬁed and 806R

modiﬁed (42), contained 5’linker sequences compatible with

Access Array primers for Illumina sequencers (Fluidigm, South

San Francisco, CA). The PCR assays were performed in a total

volume of 10 µl using MyTaq

HS 2X Mix (Bioline) with

primer concentrations at 500 nM. Thermocycling conditions

were as follows: 95°C for 5 min (initial denaturation), followed

by 28 cycles of 95°C for 30 s, 55°C for 45 s, and 72°C for 30 s.

One microliter of the PCR product from each reaction was

transferred to the second-stage PCR assay. Each second-stage

reaction was conducted in a ﬁnal volume of 10 µl using MyTaq

HS 2X mix, and each well contained a unique pair of Access

Array primers containing Illumina sequencing adapters, single

index sample-speciﬁc barcode, and linker sequences.

Thermocycling conditions were as follows: 95°C for 5 min (initial

denaturation), followed by 8 cycles of 95°C for 30 s, 60°C for

30 s, and 72°C for 30 s. Libraries were pooled and puriﬁed using

0.6× concentration of AMPure XP beads to remove short

fragments below 300 bp. Pooled libraries were loaded onto a

MiniSeq sequencer (Illumina, San Diego, CA) with 15% phiX

spike-in and paired-end 2 × 153 base sequencing reads.

2.8. Statistical analyses

Quality control analysis of demultiplexed sequences was

performed using the Deblur (43) workﬂow, following the

construction of a phylogenetic tree (mafft-fasttree) and taxonomy

assignment with QIIME2 (44). The quality process with Deblur

uses sequence error proﬁles to obtain putative error-free

sequences, referred to as “sub”operational taxonomic units

(s-OTU). Taxonomic composition was assigned to the s-OTUs

using a pre-trained Naive Bayes classiﬁer, trained on the

Greengenes (45) 13_8 99% OTUs. Downstream analysis was

conducted using R version 4.0.3. Diversity analysis was calculated

at rarefaction depth of 11,158. Bacterial α-diversity, which

quantiﬁes the intra-sample diversity, i.e., the distribution of

species abundances in a given sample, was estimated using

Shannon’s diversity and Pielou’s evenness indexes (46) and

compared across independent variables using multivariate

Lapidot et al. 10.3389/fped.2023.1198792

Frontiers in Pediatrics 03 frontiersin.org

analysis of variance (ANOVA) tests. β-diversity, which measures

dis-similarities between samples (46), was calculated using the

Bray-Curtis dissimilarity index, the Jensen-Shannon divergence

(JSD), and the phylogenetic weighted and unweighted Unifrac

distances. Permutational multivariate analysis of variance

(PERMANOVA) was used to test differences in overall

microbiome composition [vegan; Adonis (47)], implementing a

multivariate model with the covariates: age, sex, SES score,

hemoglobin levels, HAZ at age 18–30 months and current BMIZ

scores. The Analysis of Composition of Microbiomes (48)

(ANCOM) was applied for the identiﬁcation of differentially

abundant features in association with FSIQ scores, with the false

discovery rate (FDR) level set to 0.05. ANCOM uses a linear

framework to statistically detect features whose composition

varies across FSIQ scores, while controlling for other covariates

of interest (a linear model comprised of the abovementioned

covariates). A feature was considered signiﬁcantly varying in

composition across an independent variable of interest at a

detection level of ≥0.6, meaning that the feature composition

varied across the independent variable with respect to 60% of

reference features. Non-parametric Spearman’s correlation

coefﬁcient was used to evaluate the association between α-

diversity indices and FSIQ scores.

Differences in demographic characteristics across the study

villages were examined using one-way ANOVA for continuous

variables, the Kruskal–Wallis Htest for rank-based variables and

the χ

test for categorical variables. Post-hoc pairwise

comparisons were conducted using Games–Howell test, including

multiple comparisons correction with FDR.

2.9. Ethical Approval

The Institution Review Board of Hillel Yaffe Medical Center

(approval number 6/2005, year of approval 2005) and the Ethics

Committee of Tel Aviv University approved the study (approval

year 2018). Written informed consent was obtained from the

parents of the participants.

3. Results

3.1. Demographic characteristics of the

study participants

Data from 165 children (41.2% females) who provided stool

specimens and underwent a cognitive assessment were included in

the analysis. The participants’mean age was 7.8 years, [SD = 0.9],

with signiﬁcant differences between the villages (p= 0.019). The

composite SES score ranged from −2.1 to 4.6 [mean 2.1 (SD = 1.4);

Supplementary Figure S1B] and was profoundly different between

the villages (p< 0.0001; Supplementary Figure S2A). Children from

village C (low SES) had signiﬁcantly worse SES indicators than

children from villages A/B, but there were no signiﬁcant differences

between the villages in early life determinants, e.g., birth weight,

breastfeeding, and attending a daycare. HAZ scores in infancy were

signiﬁcantly lower (p= 0.026) in children from village C (low SES)

than children from villages A/B (high/intermediate SES). The mean

BMIZ score at school age was higher among children from village C

compared to villages A/B (p<0.001) (Table 1). The mean FSIQ of

TABLE 1 Characteristi cs of the participants by the village of residence (N=165).

Villages A/B

(intermediate/high SES)

Village C (low SES) pvalue

Number of participants, (%) 100 (60.6%) 65 (39.4%) –

Age, years, mean (SD) 7.9 (0.9) 7.6 (0.8) 0.019

Sex, females, N(%) 40 (40.0%) 28 (43.1%) 0.818

Household crowding index

, mean (SD) 1.4 (0.6) 2.6 (1.3) <0.001

Household monthly income

<0.001

Above average 16 (16.0%) 3 (4.6%)

Average 34 (34.0%) 8 (12.3%)

Below average 50 (50.0%) 54 (83.1%)

Father education, years, mean (SD) 11.3 (3.4) 8.3 (3.5) <0.001

Maternal education, years, mean (SD) 11.2 (3.5) 6.5 (3.7) <0.001

SES score

, mean (SD) 3.0 (0.9) 0.8 (1.0) <0.001

Birth weight (kg), mean (SD) 3.2 (0.5) 3.4 (0.5) 0.225

Breastfeeding, yes, N(%) 98 (98.0%) 57 (87.7%) 0.09

Age of introducing solid foods, months, mean (SD) 6.0 (2.9) 5.9 (2.6) 0.741

Daycare center attendance in early life, N(%) 20 (20.0%) 12 (18.8%) 0.697

Current hemoglobin level (g/dl), mean (SD) 12.6 (0.9) 12.5 (1) 0.567

Height for age z-score (age 18–30 months), mean (SD) 0.10 (0.80) −0.20 (0.80) 0.026

Weight for age z-score, (age 18–30 months), mean (SD) 0.00 (0.9) 0.20 (1.0) 0.275

BMIZ score

, mean (SD) 0.20 (1.0) 0.82 (0.9) <0.001

Full scale IQ score 105.0 (9.2) 89.2 (12.3) <0.001

BMIZ, body mass index zscore; SD, standard deviation; SES, socioeconomic status.

Household crowding: Number of people living in the household/Number of rooms in the household.

Household income: Household income as compared to the national average.

Individual level socioeconomic status score—a composite score based on conﬁrmatory factor analysis including village of residence, maternal education, household

crowding, and household income.

Lapidot et al. 10.3389/fped.2023.1198792

Frontiers in Pediatrics 04 frontiersin.org

this cohort was 98.8 [SD = 13.1] points. FSIQ score was lower among

children from village C compared to villages A/B (Supplementary

Figure S2B).

A signiﬁcant positive association was found between the

composite SES score and FSIQ scores (p< 0.0001 by ANOVA;

Supplementary Figure S3A and Spearman’sr= 0.61, p< 0.0001;

Supplementary Figure S3B). FSIQ score was not correlated with

hemoglobin level, nor with WAZ score at age 18–30 months

(Supplementary Figures S4A,B). Signiﬁcant associations were

found between HAZ at age 18–30 months with FSIQ

(Spearman’sr= 0.22, p= 0.004) and between current BMIZ

scores and with FSIQ (Spearman’sr=−0.17, p= 0.025),

Supplementary Figures S4C,D).

Based on these results and existing knowledge regarding the

environmental effects of SES on both the microbiome (2,49–51)

and FSIQ (16,52,53), we examined the association between

FSIQ score and fecal microbiome alterations, while adjusting for

covariates that were associated with microbial alterations and

FSIQ score.

3.2. The association between FSIQ score

and bacterial α-diversity

Bacterial α-diversity as estimated by the Shannon’s diversity

index followed a normal distribution (Supplementary

Figure S5). We found a signiﬁcant positive association between

Shannon’s diversity and FSIQ score (Figure 1A). A multivariate

analysis of variance model that adjusted for sex, age, SES score,

hemoglobin level, HAZ at age 18–30 months and current BMIZ

scores on bacterial diversity (Figure 1B), showed that FSIQ and

sex were signiﬁcantly associated with Shannon’s diversity index

(F= 6.16, p= 0.014 and F= 4.89 p= 0.029, respectively). A

multivariate analysis that included FSIQ score as the dependent

variable, showed a strong positive association between fecal α-

diversity and FSIQ (F= 9.73, p= 0.002; Figure 1C). In this

model, SES scores had the strongest association with FSIQ score

(F= 97.91, p< 0.0001). Hemoglobin level was signiﬁcantly

associated with FSIQ score (F= 3.94, p= 0.049; Figure 1D).

Bacterial α-diversity and FSIQ score were positively linearly

correlated (Person’sr= 0.20, p= 0.015; Figure 1E).

These associations were further strengthened by an estimation

of bacterial α-diversity with Pielou’s evenness index. There was a

strong association between FSIQ score and increased species

evenness (Supplementary Figure S6A), with FSIQ being the

strongest and the only signiﬁcant variable associated with altered

species evenness (F= 11.32, p< 0.0001; Supplementary

Table S1A). This model showed a borderline signiﬁcant

association between hemoglobin level and Pielou’s evenness

index (F=2.91, p= 0.089). A multivariate model showed a

signiﬁcant relationship between FSIQ score and species evenness

(F= 17.41, p< 0.0001), but the effect of SES (F= 91.13, p< 0.0001)

on FSIQ score was stronger (Supplementary Table S1B).

Signiﬁcant positive linear correlation between FSIQ score and

speciesevenness(Spearman’sr=0.24, p=0.002; Supplementary

Figure S6C).

3.3. The association of gut microbiome

composition and FSIQ score

We found signiﬁcant differences in fecal bacterial composition,

as measured by the Bray–Curtis dissimilarity index (F= 10.79, R

0.06, p= 0.001; Figure 2A,Supplementary Table S2A), the

phylogenetic unweighted and weighted UniFrac distance matrixes

(F= 5.04, R

= 0.03, p= 0.001, and F= 8.59, R

= 0.05, p= 0.001

relatively; Figure 2B,Supplementary Tables S2B, S2C), and by

the JSD (F= 7.40, R

= 0.04, p= 0.001; Figure 2C,

Supplementary Table S2D). All multivariate models included

the covariates age, sex, SES score, hemoglobin, HAZ and BMIZ

scores.

FSIQ score explained the highest variance in bacterial

β-diversity as measured by the Bray-Curtis dissimilarity index,

followed by the SES score (F= 10.79, R

= 0.06, p= 0.001, and

F= 5.17, R

= 0.03, p= 0.001, respectively), the phylogenetic

unweighted UniFrac distance matrix (F=5.04, R

=0.029, p=0.001,

and F=3.33, R

= 0.019, p= 0.001, respectively), the weighted

UniFracdistancematrix(F= 8.59, R

=0.048, p= 0.001, and F=

4.35, R

= 0.024, p= 0.001, respectively) and the JSD (F= 15.99,

=0.085,p=0.001, and F=7.4, R

= 0.039, p= 0.001, respectively).

We found a signiﬁcant association of weaker magnitude,

between the participant’s age, sex, and BMIZ score, and bacterial

composition, in some β-diversity measurements. Age was

signiﬁcantly associated with the Bray-Curtis dissimilarity index

(F=2.13, R

= 0.012, p= 0.014), the weighted UniFrac (F=2.82, R

= 0.016, p= 0.003) and the JSD (F=2.64, R

= 0.014, p=0.011).

BMIZ was signiﬁcantly associated with bacterial composition

when measured by the Bray-Curtis dissimilarity method (F=1.72,

=0.010, p= 0.03) and the JSD (F=1.94, R

= 0.010, p=0.046),

while sex was signiﬁcantly associated the weighted UniFrac index

(F=1.88, R

=0.011, p=0.043).

The multivariate model using the JSD method explained the

overall highest amount of variance 16.6% of the variation in

bacterial composition (Figure 2D). The remaining models

explained a smaller amount of β-diversity variation: 12.8%, 11.8%

and 8.3% for the Bray-Curtis dissimilarity, the weighted UniFrac

and the unweighted UniFrac, respectively.

3.4. Taxonomic alterations associated with

FSIQ score

In agreement with the profound differences of bacterial

composition, we found signiﬁcant associations between the

relative abundance of several bacterial genera, with adjustment

for age, sex, SES score, hemoglobin, HAZ and BMIZ scores

(Figure 3A). Genus Prevotella was detected at the highest

detection level (W

stat

= 706), followed by Dialister (W

stat

= 675),

Sutterella (W

stat

= 637), Ruminococcus callidus (W

stat

= 609),

Bacteroides uniformis (W

stat

= 605) and Lachnospiraceae (W

stat

553). At a lower detection level, there was an association with

Bacteroides,Prevotella copri,Oscillospira and Clostridium

(Supplementary Table S3). FSIQ scores were inversely associated

Lapidot et al. 10.3389/fped.2023.1198792

Frontiers in Pediatrics 05 frontiersin.org

with the relative abundance of Prevotella (including species

Prevotella copri), Dialister and Sutterella, while Ruminococcus

callidus, Bacteroides uniformis and Lachnospiraceae were

characterized by a positive association with FSIQ levels

(Figures 3B–I).

An unadjusted analysis revealed signiﬁcant correlations

between FSIQ scores and Prevotella (Spearman’sr=−0.42, p<

0.0001), Dialisted (Spearman’sr=−0.19, p= 0.012), Sutterella

(Spearman’sr=−0.2, p= 0.01), the species Ruminococcus callidus

(Spearman’sr= 0.27, p= 0.001), and Bacteroides uniformis

(Spearman’sr= 0.41, p< 0.0001; Supplementary Figures S7A–E).

Since a signiﬁcant percentage of bacterial variance was

explained by SES scores, we performed a stratiﬁed analysis by

village of residence. We found a consistent bacterial variation

associated with FSIQ score in all villages, thus independent from

SES and adjusted for the aforementioned covariates (Figures 4A,

B). Among children from village C (low SES), Bacteroides

uniformis was the most strongly associated species with FSIQ

FIGURE 1

The association between full-scale IQ scores and bacterial α-diversity. (A) Box-violin plots of microbial diversity, measured by Shannon’s diversity index,

across tertiles of FSIQ scores, showing a signiﬁcant increase in microbial α-diversity with increased FSIQ (p= 0.014). (B) Results of a multivariate analysis of

variance displaying the association between FSIQ score and covariates of interest with bacterial diversity. FSIQ score and sex were signiﬁcantly associated

Shannon’s bacterial α-diversity index (F= 6.16, p= 0.014 and F= 4.89 p= 0.029, respectively). (C) Box-violin plots of FSIQ scores across tertiles of

Shannon’s diversity index, show a signiﬁcant increase in FSIQ scores with increased bacterial diversity ( p= 0.002). (D) Results of a multivariate analysis

of variance displaying the association between the individuals’gut Shannon’s diversity and covariates of interest with FSIQ scores. Bacterial α-diversity

and SES scores were strongly associated with FSIQ score (F= 9.73, p= 0.014 and F= 97.91, p= 0.029, respectively), while hemoglobin levels had

a more delicate albeit signiﬁcant association (F= 3.94, p= 0.049). (E) The correlation between Shannon’sα-diversity index and FSIQ score; Pearson’s

r= 0.20, p= 0.015. SES, socioeconomic status; FSIQ, full-scale IQ; HAZ, height for age z-score at age 18–30 months; BMIZ, body mass index z-score

at age 6–9 years. *The xaxis in ﬁgures (A,C) represents tertiles, T1= lowest tertile, and T3 = highest tertile. **The mid line in the box plots [ﬁgures (A,C)]

represents the median, the lower bound of the box represents the 25th percentile, the upper bound of the box represents the 75th percentile, the lowest

point of the lower whisker represents the minimum and the highest point of the upper whisker represents the maximum. The violin plot implements a

rotated kernel density plot on each side, adding information regarding the full distribution of the measured data; the width of the violin indicates the frequency.

Lapidot et al. 10.3389/fped.2023.1198792

Frontiers in Pediatrics 06 frontiersin.org

score (W

stat

= 700), followed by Prevotella (W

stat

= 635), the species

Clostridioforme (W

stat

= 607), including the lower taxonomic levels

Clostridiales (W

stat

= 581) and Clostridium (W

stat

= 567), Veillonella

dispar (W

stat

= 567), Bacteroides (W

stat

= 557) and Ruminococcus

torques (W

stat

= 539). Importantly, FSIQ score was positively

associated with the relative abundance of Bacteroides, including

Bacteroides uniformis, Clostridium, including species

Clostridioforme, Ruminococcaceae including Ruminococcus

torques and Veillonella dispar, while Prevotella was inversely

associated with FSIQ score (Figure 4C).

FSIQ score of children from the higher SES villages (A/B), was

associated with altered relative abundance of Faecalibacterium

prausnitzii (W

stat

= 643), Oscillospira (W

stat

= 587), Coprococcus

stat

= 562) and Catenibacterium (W

stat

= 520). The full results

of the stratiﬁed ANCOM analysis are presented in Supplementary

Table S4.Notably,Coprococcus,Ruminococcaceae, including genus

Oscillospira were positively associated with increased FSIQ score,

while Coriobacteriaceae,Faecalibacterium prausnitzii and

Catenibacterium levels were depleted with increasing FSIQ score

(Figure 4D).

4. Discussion

We characterized the cognitive development of school-age

children, in association with intestinal microbiome diversity and

composition and environmental exposures, including SES, a

major factor that inﬂuences both cognitive development and the

gut microbiome.

We found a signiﬁcant association between microbial α-

diversity, measured by both Shannon’s diversity and Pielou’s

evenness indices and FSIQ scores. There was a progressive

FIGURE 2

The association between full-scale IQ scores and bacterial β-diversity. (A) Principal coordinate analysis (PCoA) of the Bray-Curtis dissimilarity index,

notably altered with changing FSIQ scores (F= 10.79, p= 0.001). (B) PCoA of the phylogenetic unweighted uniFrac distance matrix, signiﬁcantly

separated with altered FSIQ score (F= 5.04, p= 0.001). (C) PCoA of the Jensen-Shannon divergence (JSD), clearly separated according to FSIQ

tertiles (F= 15.90, p= 0.001). (D) Stacked (100%) bar-plots of the explained variance in microbial beta diversity by the multivariate models. The FSIQ

score explained most of the variance in all β-diversity measurements, followed by SES score. The JSD method explained the highest percentage of

variance in microbial β-diversity (16.6%). FSIQ, full-scale IQ; PCoA, principal coordinate analysis; JSD, Jensen-Shannon divergence. *FSIQ scores in

Figures (C,D) are represented as tertiles, T1 being the lowest tertile (FSIQ scores between 59 and 96), T2 the middle tertile (FSIQ scores between 97

and105), and T3 the highest tertile (FSIQ scores between 106 and 127). **The midline in the box plots [ﬁgure (D)] represents the median, the lower

bound of the box represents the 25th percentile, the upper bound of the box represents the 75th percentile, the lowest point of the lower whisker

represents the minimum and the highest point of the upper whisker represents the maximum. The violin plot implements a rotated kernel density

plot on each side, adding information regarding the full distribution of the measured data; the width of the violin indicates the frequency.

Lapidot et al. 10.3389/fped.2023.1198792

Frontiers in Pediatrics 07 frontiersin.org

increase in both diversity indices with increased FSIQ score. The

Shannon diversity index accounts for both richness and evenness

of s-OTUs and largely mirrors the evenness ﬁndings of this

cohort. In general, lower values of Shannon diversity index

indicate less diversity, thus the intestinal microbiome of children

with lower FSIQ scores was less diverse, less even, and less rich

compared to children with higher scores. Correspondingly,

Pielou’s evenness considers the number of species and the

relative abundance of species in a sample. We found a positive

relationship between evenness and FSIQ score. Lower values of

Pielou’s index represent less even distributions of species, thus

implying potential dominance of some species in the gut.

Therefore, in our study, lower FSIQ scores were associated with

less evenness of species inhabiting the human gut. We also found

signiﬁcant differences in the intestinal microbiome composition

according to FSIQ score. These associations were observed even

after adjustment for SES and nutritional status, measured by

hemoglobin levels, BMIZ and HAZ scores.

A limited number of studies examined the associations of the

gut microbiome diversity and composition with children’s

developments, mainly between ages 2 of 3 years, (20,54,55).

These ages are usually characterized by profound changes in the

gut microbiome until it stabilizes. Unlike our study, Carlson

et al. (20) in their study of 89 children aged 1–2 years

demonstrated that greater α-diversity was associated with poorer

cognitive performance. Streit et al. studied 323 children aged 45

months and showed weak negative correlations between alpha

diversity, as measured by Faith phylogenetic diversity index and

FSIQ (correlation coefﬁcient ranged between −0.10 and −0.14),

but such differences were not observed for other indices of alpha

diversity when adjusting for confounders and multiple

comparisons (54). Rorthenberg and colleagues studied 46

children from rural China, and reported no signiﬁcant

association between alpha diversity and cognitive development at

age 3 years (55). The negative associations between alpha

diversity and cognitive development in prior studies (20,54),

might be unexpected, since higher α-diversity usually indicates a

more mature, adult-like community, while reduced α-diversity is

commonly associated with poor health outcomes, including

metabolic and inﬂammatory bowel diseases (1,56). The

FIGURE 3

Differentially abundant taxa associated with full-scale IQ scores. (A) Volcano plot showing differentially abundant s-OTUs associated with FSIQ scores in

the whole cohort, as detected by ANCOM. The x-axis represents the difference in mean centered log ratio (clr)-transformed abundance between groups,

and the y-axis represents the ANCOM W Statistic. s-OTU points are colored by the level of ANCOM signiﬁcance, with 0.9 being the highest level; s-OTUs

in gray were not signiﬁcant. (B–I) Boxplots of clr-transformed abundance of s-OTUs signiﬁcantly associated with FSIQ scores, adjusted for sex, age, SES

score, hemoglobin level, HAZ and BMIZ scores. Tertiles of FSIQ were categorized as low, middle and high FSIQ score tertiles, T1 being the lowest tertile

(FSIQ scores between 59 and 96), T2 the middle tertile (FSIQ scores between 97 and105), and T3 the highest tertile (FSIQ scores between 106 and 127).

The midline in the box plots represents the median, the lower bound of the box represents the 25th percentile, the upper bound of the box represents the

75th percentile, the lowest point of the lower whisker represents the minimum and the highest point of the upper whisker represents the maximum. FSIQ,

full-scale IQ; s-OTUs, sub-operational taxonomic units; ANCOM, analysis of composition of microbiomes; SES, socioeconomic status; HAZ, height for

age z-score at infancy (18–30 months); BMIZ, body mass index z-score at age 6–9 years.

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Frontiers in Pediatrics 08 frontiersin.org

differences between our ﬁnding of a positive relationship between

alpha diversity and others (20,54) showing inverse associations

might be related to discrepancies in the study population,

speciﬁcally, our study included school-age children that likely

have adult-like stable microbiomes, while other studies mainly

included infants and pre-school children, characterized by a

microbiome that is still evolving.

Our model was adjusted for SES and we observed a strong and

signiﬁcant association between SES and cognitive performance.

These results are in line with existing evidence, demonstrating

the profound inﬂuence of SES on cognitive development, and

behavioral outcomes (57), and on the gut microbiome at school

age (25). This complex interplay between environmental

exposures, the intestinal microbiome, and individual

neurodevelopment emphasizes the need for tailored

developmental programs and policies that are designed to

alleviate SES-related disparities in cognitive performance in

children.

We found signiﬁcant associations between the intestinal

microbiome composition and FSIQ score, which were consistent

in four distance measures for quantifying β-diversity: the binary

Bray-Curtis, the JSD, and the phylogenetic weighted and

unweighted UniFrac. Cognitive performance explained the

highest percentage of variance in all methods, followed by the

SES score. Age was signiﬁcantly, yet more ﬁnely associated with

microbial composition. Overall, JSD was the most sensitive

FIGURE 4

Differentially abundant taxa by village of residence and socioeconomic status. (A,B) Volcano plots showing differentially abundant s-OTUs as detected by

ANCOM, stratiﬁed by village; A/B [high/intermediate SES] (A), and C [low SES] (B). The x-axis represents the difference in mean centered log ratio (clr)-

transformed abundance between groups, and the y-axis represents the ANCOM W Statistic. s-OTU points are colored by level of ANCOM signiﬁcance,

with 0.9 being the highest level; s-OTUs in gray were not signiﬁcant. (B,C) Boxplots of clr-transformed abundance of s-OTUs signiﬁcantly associated with

FSIQ scores in villages A/B [high/intermediate SES] (C) and in village C [low SES] (D), adjusted for sex, age, SES score, hemoglobin level (g/dl), HAZ and

BMIZ scores. Tertiles of FSIQ were categorized as low, middle and high FSIQ score tertiles, T1 being the lowest tertile (FSIQ scores between 59 and 96), T2

the middle tertile (FSIQ score between 97 and 105), and T3 the highest tertile (FSIQ scores between 106 and 127). The mid line in the box plots represents

the median, the lower bound of the box represents the 25th percentile, the upper bound of the box represents the 75th percentile, the lowest point of the

lower whisker represents the minimum and the highest point of the upper whisker represents the maximum. FSIQ, full-scale IQ; s-OTUs, sub-operational

taxonomic units; ANCOM, analysis of composition of microbiomes; SES- socioeconomic status; HAZ, height for age z-score at infancy (18–30 months);

BMIZ, body mass index z-score at age 6–9 years.

Lapidot et al. 10.3389/fped.2023.1198792

Frontiers in Pediatrics 09 frontiersin.org

method capturing 16.6% of the variance. While the FSIQ score

explained the most variance, SES score was an important

determinant of β-diversity, suggesting that these factors

independently inﬂuence both the intestinal microbiome and

cognitive performance. The composition of the gut microbiome

is a complex trait, with the quantitative variation in the

microbiome affected by a large number of host and

environmental factors, each of which may have only a small

additive effect, making it difﬁcult to identify the association for

each separate item (58,59). Falony et al. reported signiﬁcant

relationships between previously unidentiﬁed factors such as red

blood cell count and hemoglobin levels and fecal bacterial

composition (58), while in our study the association between

hemoglobin level and beta diversity was not statistically

signiﬁcant, possibly due to the smaller sample size. Our model

explained 16% of the variance in microbial composition, a

relatively high percentage, nonetheless indicating the need to

explore additional contributions for example from dietary habits,

stochastic effects, and/or biotic interactions.

While alpha and beta diversity capture complex variation

across the community, we observed signiﬁcant differences in the

relative abundance of speciﬁc genera and species in association

with FSIQ score. High relative abundance of the genera

Prevotella, Dialister and Sutterella was associated with the lower

cognitive performance tertiles, while Bacteroides were positively

correlated with elevated FSIQ score. Interestingly, Carlson et al.

(20) described a strong association between high levels of

Bacteroides with the highest level of cognitive performance at 2

years old. Similarly, Tamana et al. (60) showed that

Bacteroidetes-dominant gut microbiome and higher relative

abundance of genus Bacteroides in late infancy were associated

with enhanced neurodevelopment by the age of 2 years among

Canadian children, mainly among males (60). It was also found

that Bacteroidetes-dominant microbiome was enriched with

numerous metabolic functions including sphingolipid metabolism

and glycosphingolipid biosynthesis. Furthermore, genes involved

in metabolism of folate, biotin, pyruvate, vitamin B6, lipoic acid

and fatty acid biosynthesis were enriched in Bacteroidetes-

dominant microbial composition (60). The intestinal microbiome

at 6–9 years is substantially different and more diverse compared

to age two years, thus our study adds new knowledge regarding

potential involvement of the gut microbiome with cognitive

function at school age and not only in early life, when the gut

microbiome is less mature, and still affected by early life factors,

such as delivery mode (61). Collectively these ﬁndings support

the idea of microbiota gut-brain-axis during childhood.

Nutrition and dietary patterns are considered major

determinants of cognitive performance in children and adolescents

(62,63). For example, iron deﬁciency anemia is linked to lower

neurodevelopmental achievements (28). We measured hemoglobin

levels as a proxy for iron deﬁciency anemia, and included this

parameter in all multivariable models, suggesting that the gut

microbiome was associated with cognitive function regardless of

hemoglobin levels. Additional nutritional factors might inﬂuence

cognitive performance and academic achievements, including B

vitamins, e.g., folate, vitamin B12 (64–66), and overall dietary

patterns (63). Diet in turn affects the development of the intestinal

microbiome in early life (67). We also found altered composition

of the gut microbiome in relation to dietary intake of

polyunsaturated fatty acids in a different cohort of Arab children

aged 10–12 years (68). Our study lacks information on dietary

intake of this cohort. Therefore, the associations between intestinal

microbiomeandcognitivefunctioninchildrenshouldbefurther

explored in large-scale prospective studies, while deciphering

potential mechanistic role of dietary intake and nutritional status in

such associations and possibly intervention studies including

probiotic or prebiotic supplementation to assess the association

with the microbiome and cognitive performance.

Our study has some limitations. First, this is a cross-sectional

study design, thus the directionality of the observed association

between the gut microbiome and cognitive development remains

to be determined in prospective studies. Second, diet is one of

the main determinants of the gut microbiome and affects the

(development) of cognitive (dys)function (24), and we did not

obtain detailed dietary questionnaires for the participants. In the

current cohort, early life dietary exposures were relatively similar

and characterized by a high prevalence of breastfeeding, a similar

age of ﬁrst exposure to solid foods, and a late entrance to a

daycare. Moreover, since all participants belong to the same

ethnic group, they share common dietary practices, mainly a

high prevalence of home-cooked, traditional meals and a diet

rich in fruit, vegetables, and legumes. Nevertheless, at school-age,

there are uncontrolled dietary exposures, that might have an

important association with the child’s microbiome and cognitive

function.

We used archived stool samples that were collected during

2007–2009. There might have been changes over time, that might

affect both cognitive development and the gut microbiome. The

SES rank of the study villages remained stable during over one

decade (69). Conversely, changes in diet and nutritional status

were documented (70,71), which might inﬂuence both the gut

microbiome and cognitive development. Although, these changes

should not affect the observed association between the gut

microbiome and cognitive development in our study, future

studies using specimens reﬂecting an up-to-date host-

microbiome-environment interaction are needed.

The strengths of the current study include a relatively large

cohort of healthy school-age children, with a deﬁned geographic,

ethnic, and cultural background, yet divergent SES. Geographic

residency and ethnicity are strong modulators of the intestinal

microbiome (72), thus the associations demonstrated in the

current study are independent from these important

confounders. Moreover, our results were adjusted for potential

confounders that affect both the microbiome and FSIQ score.

5. Conclusions

We demonstrated signiﬁcant associations between the gut

microbiome and cognitive development in healthy school age

children, independent of SES. Future longitudinal studies are

Lapidot et al. 10.3389/fped.2023.1198792

Frontiers in Pediatrics 10 frontiersin.org

needed to understand the directionality of the associations and

mechanisms that might explain these relationships.

Data availability statement

Data generated in the framework of the study cannot be made

publicly available due to legal and ethical restrictions. Aggregate

anonymized data might be available upon request from the

corresponding author.

Ethics statement

The studies involving human participants were reviewed and

approved by the Institution Review Board of Hillel Yaffe Medical

Center and the ethics committee of Tel Aviv University. Written

informed consent was obtained from the parents of the

participants.

Author contributions

The authors contributed to the study as follows: YL, study

concept, analysis and interpretation of data, drafting of the

manuscript, and statistical analysis. LR study design, laboratory

methods, data analysis, critical revision of the manuscript for

important intellectual content. MM study concept, acquisition of

data and data management. DC study design, supervision,

acquisition of data and samples, critical revision of the

manuscript for important intellectual content. UG study design,

critical revision of the manuscript for important intellectual

content. AO study design, critical revision of the manuscript for

important intellectual content and acquisition of funding. KM

study concept and design, acquisition of data and samples, study

supervision, contributed to writing of the manuscript, and

acquisition of funding. All authors had access to the study data,

reviewed, and approved the ﬁnal version of the manuscript. All

authors contributed to the article and approved the submitted

version.

Funding

This study was partially funded by internal funds from Tel Aviv

University (KM-PI) and the Israel Science Foundation (ISF) grant

number 2614/19 (KM, AO-PIs).

Acknowledgments

We thank the research assistants who took part in data and

sample collection.

Conﬂict of interest

The authors declare that the research was conducted in the

absence of any commercial or ﬁnancial relationships that could

be construed as a potential conﬂict of interest.

Publisher’s note

All claims expressed in this article are solely those of the

authors and do not necessarily represent those of their afﬁliated

organizations, or those of the publisher, the editors and the

reviewers. Any product that may be evaluated in this article, or

claim that may be made by its manufacturer, is not guaranteed

or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found

online at: https://www.frontiersin.org/articles/10.3389/fped.2023.

1198792/full#supplementary-material.

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Frontiers in Pediatrics 13 frontiersin.org

TYPE Mini Review

PUBLISHED 15 June 2023

DOI 10.3389/fpubh.2023.1199571

OPEN ACCESS

EDITED BY

Raed Mualem,

Oranim Academic College, Israel

REVIEWED BY

Sandrine Rossi,

Université de Caen Normandie, France

*CORRESPONDENCE

Michael I. Posner

mposner@uoregon.edu

RECEIVED 03 April 2023

ACCEPTED 17 May 2023

PUBLISHED 15 June 2023

CITATION

Posner MI and Rothbart MK (2023) How

understanding and strengthening brain

networks can contribute to elementary

education. Front. Public Health 11:1199571.

doi: 10.3389/fpubh.2023.1199571

open-access article distributed under the terms

of the Creative Commons Attribution License

(CC BY). The use, distribution or reproduction

in other forums is permitted, provided the

original author(s) and the copyright owner(s)

are credited and that the original publication in

this journal is cited, in accordance with

accepted academic practice. No use,

distribution or reproduction is permitted which

does not comply with these terms.

How understanding and

strengthening brain networks can

contribute to elementary

education

Michael I. Posner*and Mary K. Rothbart

Department of Psychology, University of Oregon, Eugene, OR, United States

Imaging the human brain during the last 35 years oers potential for improving

education. What is needed is knowledge on the part of educators of all types of

how this potential can be realized in practical terms. This paper brieﬂy reviews

the current level of understanding of brain networks that underlie aspects of

elementary education and its preparation for later learning. This includes the

acquisition of reading, writing and number processing, improving attention and

increasing the motivation to learn. This knowledge can enhance assessment

devices, improve child behavior and motivation and lead to immediate and lasting

improvements in educational systems.

KEYWORDS

attention, memory, elementary education, number, reading, mindset

1. Introduction

In the late 20th century, it became possible to examine the living human brain during

the performance of cognitive tasks, including those normally taught in school [see (1) for

a review]. The main method of doing this is to place the person in a magnetic resonance

imager. The signal detected in functional magnetic resonance imaging (fMRI) reﬂects

changes driven by localized brain blood ﬂow and blood oxygenation, which are coupled to

the level of neuronal activity. This allows construction of an image of the brain marked with

the areas of increased neural activity.

From the earliest studies of brain imaging it was clear that even very simple tasks, like

retrieving the use of a “hammer”, activated neurons in several widely separated cortical and

subcortical brain areas related to diﬀerent aspects of language. During the last 35 years new

methods of imaging the brain have also been developed. One of these, Diﬀusion Tensor

Imaging (DTI) allows connections between active areas of the brain to be imaged.

Many of the brain networks imaged in adults performing tasks like reading are also active

when the person is not performing a task, but is in a resting state (2). The ability to image

networks in the resting brain allows them to be studied even in infancy, when the baby is not

able to perform a task. Language networks have been imaged from birth using this resting

state method (3). Thus, during the early years of this century a tool kit of methods to study

brain networks related to cognitive tasks and the resting state has been developed.

While books (4), scholarly articles and even podcasts have attempted to inform teachers

and others involved in education about the relevance of brain developments, recent articles

have noted widespread failure of current methods to reﬂect the relevance of brain imaging

ﬁndings to education (5,6). The implication of brain research for teaching in elementary

schools has either not been understood or failed to be applied for other reasons.

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Posner and Rothbart 10.3389/fpubh.2023.1199571

FIGURE 1

Application of imaging to reading acquisition reveals two posterior

brain areas (phonological and visual word form areas), both of

which can access word meaning via the ventral frontal lobe. The

phonological pathway is related to word sound and the visual word

form area is related to the rules for visual words (orthography). The

left frontal lobe serves as a means to access semantic information

stored in various brain areas.

The goal of this paper is to make clear ﬁndings in the human

brain that could inﬂuence elementary school education, improving

learning by students and increasing their understanding of why

the eﬀort required of them is worthwhile. We attempt to outline

in a non-technical way the speciﬁc brain networks related to

instruction in reading and number that are critical for elementary

school subjects. In addition we discuss attention and motivation

as important tools for learning. Finally, we discuss concrete steps

that teachers may consider taking to assist brain changes that occur

while students carry out the tasks of elementary school.

2. Reading and writing

Reading curricula in elementary school either involve phonics

instruction, the whole word method or more recently a “balanced”

curriculum that places emphasis on reading for meaning and is

based to a large degree on whole words. Brain research has been

helpful in resolving the dispute between the phonics and whole

word forms of training. In literate adults two diﬀerent networks

connect areas in the posterior part of the brain to attention and

brain areas related to meaning (see Figure 1).

One pathway involves obtaining the word name (phonological

code) through blending letter sounds into words. For most readers

phonics training allows them to handle either unfamiliar or familiar

words by blending letter sounds to pronounce them. Words that

are familiar from speaking can then be connected to the word

meaning. This pathway is based on phonics training and the child’s

vocabulary from exposure to spoken words (7).

This form of reading is not ﬂuent and does not by itself produce

a child likely to read on their own or to enjoy reading (8). The

extreme diﬃculty of reading without a visual word form area is

illustrated by adult patients with disconnection of the visual word

form area from the primary visual cortex of one hemisphere or both

hemispheres. Words presented to the disconnected hemisphere are

painfully sounded out letter by letter (9) rather than read ﬂuently

(9). Practice in reading induced by assignments and/or reading

for pleasure builds the visual word form area. This visual word

form area chunks letters into a unit and connects to word meaning

(semantics). There is some evidence that the visual word form area

is also developed by early reading in the ﬁrst year of schooling.

Thus, phonics reading instruction not only provides a basis for

decoding but also helps to develop the visual word form area

(10). Reading instruction encroaches on parts of the brain that are

initially weakly specialized for tools and close to but distinct from

those responsive to faces (10).

The visual word form area may also involve subareas of

increasing sensitivity to whole words as one moves from the more

early visual with area to later (more anterior) parts of the visual

word form area (11). There is also evidence that the development

of the visual word form area and its connections to other parts

of the brain (connectivity) continues long after decoding has been

developed. The time course of connectivity and function of these

subareas is under active investigation (12). Exercises that expose

children to materials of interest to them help to ensure that

they become ﬂuent readers as adults. Individual diﬀerences in the

reliance on phonology vs. visual word form can be achieved by

measuring the accuracy of sounding out nonwords in comparison

to the skill of pronouncing exception words, that do not follow the

common rules of orthography (13,14). These measures could be

useful to teachers to adapt their methods to ensure that each child

reaches reading ﬂuency, but may not be useful in some languages.

Children who are diagnosed as dyslexic, that is who fail to learn

to read despite having the apparent ability to do so, show reduced

activation of both phonological and visual word form areas (15). As

expected, a computerized program to teach phonics improved the

ability of the dyslexic children to sound out words and increased

activation in phonological brain areas (16). In addition, emphasis

on letters by spacing of the visual text can also provide help for some

dyslexic children (17).

It is likely that writing may also help to develop the visual

word form area. Cursive writing requires the child to develop

speciﬁc movements for each letter. The emphasis on the letter as

a constituent of the word may help develop both the phonological

and the teaching visual word form area. In addition, there is some

evidence that teach cursive writing may provide better overall

memory for the material than would be the case with typing (18).

This may support the idea of teaching cursive to foster development

of reading skill as well as improved memory.

3. Number

The number sense allows animals and human infants to come

into the world with a primitive understanding of small numbers.

Babies can even perform simple calculation. For example, infants

look longer when adding a puppet to the display of one puppet

produces a single puppet than when it correctly reveals two puppets

(19). Thus babies, like adults, can be puzzled by an error in the

visual display of small quantities and this detection activates part

of the executive attention network [(20) described in the attention

section of this paper].

When adults are asked to determine which of two digits is

larger they are faster the larger the distance between the two. We

believe this result arises from representation of quantity within

the brain’s parietal cortex that is called the number line. It is a

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Posner and Rothbart 10.3389/fpubh.2023.1199571

FIGURE 2

Two pathways between attention nodes (circles) and memory

(rectangles), anterior pathway between attention and memory

(hexagon). Reprinted with permission from Frontier Neuroscience

(24).

goal of speciﬁc training to develop and expand this representation

of quantity. Wilson et al. (21) used a race game which required

number comparison. Performance on number comparison did

improve, but a subsequent study showed that it did not improve

more than a control condition and did not generalize to other math

skills (22).

A four-week training program using several games, including

the race game used in the Wilson et al. study, produced improved

appreciation of quantity and strengthened connections in a brain

pathway between the parietal lobe and hippocampus (23). This

pathway also plays a role in retrieval of newly learned associations

(see Figure 2).

Although much research remains it does seem possible to

aid in the development of the number line that forms a basic

understanding of quantity and serves as a framework for early

arithmetic. Another important step for the teacher is to ensure that

the concept of quantity is connected to the language network to

allow exact calculation (25). This eﬀort could involve discussion

of sample problems designed to have the student articulate their

concept of quantity in their own language and thus help in the

development of the connections between the number line and

language that is needed for exact calculation (25).

4. Attention and learning

Most of school learning depends on paying attention. Viewing

attention as having a single uniﬁed function creates confusion in

applying it to classroom learning. There is no single brain network

of attention, and so far, three mainly diﬀerent brain networks

are related to (1) obtaining and maintaining the alert state, (2)

orienting to sensory information, and (3) executive control of

voluntary behavior, thoughts and feelings. Each of these functions

involves largely separate networks of attention (26,27).

Both the orienting and the executive attention networks have

connections with memory formation and retrieval involving the

hippocampus, a central node in consolidating and retrieving

long term memories. Figure 2 indicates two somewhat separate

pathways between attention and memory networks.

The executive attention network connects the Anterior

Cingulate Cortex (ACC) through the thalamus to exert control

of the anterior hippocampus during storage of information (28).

A posterior route between the parietal orienting network and the

hippocampus is largely involved in navigation in rodents and more

general retrieval from long-term memory in humans (24).

Two forms of training have been found to improve attention

networks. One involves young children and is a 5-day adaptation

of training used to send chimpanzees to perform work in space

(29). It began by teaching 4–6-year-olds to use a joystick and ended

with practice in resolving conﬂict (30,31). It has been shown

to improve the network underlying self regulation and control

of cognition and to allow more behavioral control over delay of

gratiﬁcation. A second method involves training the control of

attention through forms of mindfulness meditation. Five days of

meditation training improved executive attention (32) and two

weeks of training produced a strong 4–8 Hz (theta) rhythm over

the frontal cortex even when the person is at rest (33). In mice, 4

weeks of near theta stimulation in the ACC changes connectivity

near to the site of stimulation (34).

The ability to train attention in childhood through network

training and meditation shows promise as a way of helping children

to learn. Attention training was used in central Europe to reduce

the gap between high-and-low income families and increase school

success (1). Training attention either directly through cognitive

exercises or through meditation could be used for the same

purpose in the US schools where inequality in pre-school education

remains high.

5. Training mindset and improving

function

There is substantial evidence that the beliefs students have

about their brain can greatly inﬂuence their behavior (35,36).

For example, those with a growth mindset, who believe that

intelligence can be changed by eﬀort, show greater ability to attend

and learn new material than those with a ﬁxed mindset, who

believe intelligence is ﬁxed and eﬀort has little inﬂuence (37).

In one study, children with ﬁxed mindset show larger frontal

activity to negative feedback but sustained their attention less and

learned less than those with a growth mindset, who use negative

information to sustain learning. In a national sample of 6,320

American adolescents a one-hour mindset intervention delivered

on-line in two sessions not only improved their growth mindset

but also improved school achievement for low and medium level

students. High level achievers showed reduced variability in their

already strong grades (38).

Afour-week growth mindset training program was designed

to enhance foundational, school related, cognitive skills in 7–

10-year-old children (39). The training included a one-on-one

tutoring program in number skills and on-line games related to

the number sense. In comparison with a non-contact control group

the trained children not only improved in growth mindset but the

improvement in mindset predicted the improvement in later math

skills. Prior to and after training an fMRI was given while children

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performed a math problem solving (addition) task. The gains in

growth mindset were strongly associated with increased activation

of the dorsal ACC and to a lesser extent the hippocampus. There

were also signiﬁcant connectivity increases between the ACC and

the hippocampus.

Thus, change in mindset from a strong intervention

strengthened the pathways between attention and memory

during mathematics problem solving. These results show that

growth mindset not only provides information on the child’s

attitude but also serves as a possible proxy for the strength of

pathways between attention and memory and provides evidence

that intervention can be eﬀective in improving their strength.

6. Lessons for elementary teachers

Neuroscience does not dictate the correct curriculum for

teaching reading, writing or arithmetic.

What it does do is equip the designers of these curricula

and those responsible for their execution with a view of the

underlying brain structures and changes that are involved when

learning this material. These principles can be associated with

assessments that reveal how the aﬀected brain structures are

working. These assessments do not require the use of brain scans

or other neuroscience methods that are critical for knowledge about

the brain.

What might teachers do to achieve the needed background for

applying neuroscience ﬁndings to their work? Jolles and Jolles (5)

argue that four themes in neuroscience are critical for obtaining

such knowledge. These are:

Theme 1. The nervous system controls and responds to body

functions and directs behavior.

Theme 2. Nervous system structure and function are

determined throughout life by genes and environment, including

the person’s own actions.

Theme 3 The brain is the foundation of the mind.

Theme 4: Research leads to understanding that is essential for

development of therapies for nervous system dysfunction and helps

improve the circumstances under which people learn.

For more general principles of classroom mangement based on

psychological research the reader could turn to https://www.apa.

org/ed/schools/teaching-learning.

It may be necessary that every school granting credentials to

teachers make sure that at least this level of knowledge is available,

and every school board might seek to hire and reward teachers with

this relevant knowledge.

Author contributions

Both authors listed have made a substantial, direct,

and intellectual contribution to the work and approved it

for publication.

Funding

This study was funded by Oﬃce of Naval Research grant

N00014-22-1-2118 to the University of Oregon and Gift Account

University of Oregon BJXGFT (Gift funds).

Conﬂict of interest

The authors declare that the research was conducted in the

absence of any commercial or ﬁnancial relationships that could be

construed as a potential conﬂict of interest.

Publisher’s note

All claims expressed in this article are solely those

of the authors and do not necessarily represent those of

their aﬃliated organizations, or those of the publisher,

the editors and the reviewers. Any product that may be

evaluated in this article, or claim that may be made by

its manufacturer, is not guaranteed or endorsed by the

publisher.

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Frontiers in Public Health 05 frontiersin.org

Frontiers in Neuroscience 01 frontiersin.org

Positive or negative environmental

modulations on human brain

development: the

morpho-functional outcomes

of music training or stress

CarlaMucignat-Caretta

* and GiuliaSoravia

1 Department of Molecular Medicine, University of Padova, Padova, Italy, 2 Department of Mother and

Child Health, University of Padova, Padova, Italy

In the last couple of decades, the study of human living brain has beneﬁtted

of neuroimaging and non-invasive electrophysiological techniques, which are

particularly valuable during development. A number of studies allowed to trace the

usual stages leading from pregnancy to adult age, and relate them to functional

and behavioral measurements. It was also possible to explore the eects of

some interventions, behavioral or not, showing that the commonly followed

pathway to adulthood may be steered by external interventions. These events

may result in behavioral modiﬁcations but also in structural changes, in some

cases limiting plasticity or extending/modifying critical periods. In this review,

weoutline the healthy human brain development in the absence of major issues

or diseases. Then, the eects of negative (dierent stressors) and positive (music

training) environmental stimuli on brain and behavioral development is depicted.

Hence, it may be concluded that the typical development follows a course

strictly dependent from environmental inputs, and that external intervention can

be designed to positively counteract negative inﬂuences, particularly at young

ages. Wealso focus on the social aspect of development, which starts in utero

and continues after birth by building social relationships. This poses a great

responsibility in handling children education and healthcare politics, pointing to

social accountability for the responsible development of each child.

KEYWORDS

development, brain, behavior, childhood, environment, music, stress

1. Introduction

e study of brain development from pregnancy to adult age has been devoted for years to

establishing a x sequence of events in the morpho-functional development. is vision was the

consequence of two concurrent causes, in dierent elds of knowledge. First, the development

of theories of cognitive development in the eld of child psychology, during the last century, that

described a rather xed sequence of functional acquisitions from birth onwards, during typical

development. is brought forward the underlying idea that both the sequence and timing of

acquisition were rather stable and culture-independent, at least in the rst phases of development.

A revision of the literature on these topics is outside the scope of this review: the readers can

refer to the seminal works of leaders in the eld, like Jean Piaget and Lev Semënovič Vygotskij.

Second, in the emerging eld of neuroscience, most data on brain development were from

OPEN ACCESS

EDITED BY

Raed Mualem,

Oranim Academic College, Israel

REVIEWED BY

Xueyun Shao,

Shenzhen University, China

Ciro De Luca,

University of Campania Luigi Vanvitelli, Italy

*CORRESPONDENCE

Carla Mucignat-Caretta

carla.mucignat@unipd.it

RECEIVED 27 July 2023

ACCEPTED 18 October 2023

PUBLISHED 03 November 2023

CITATION

Mucignat-Caretta C And Soravia G (2023)

Positive or negative environmental modulations

on human brain development: the morpho-

functional outcomes of music training or

stress.

Front. Neurosci. 17:1266766.

doi: 10.3389/fnins.2023.1266766

an open-access article distributed under the

terms of the Creative Commons Attribution

License (CC BY). The use, distribution or

reproduction in other forums is permitted,

provided the original author(s) and the

original publication in this journal is cited, in

accordance with accepted academic practice.

No use, distribution or reproduction is

permitted which does not comply with these

terms.

TYPE Review

PUBLISHED 03 November 2023

DOI 10.3389/fnins.2023.1266766

Mucignat-Caretta and Soravia 10.3389/fnins.2023.1266766

Frontiers in Neuroscience 02 frontiersin.org

histology, while physiological recordings were limited to certain ages

and were mostly not intended to detect lifelong changes. is had the

consequence of transmitting the idea that xed steps of structural and

functional development are reached at precise times, with an invariant

sequence and limited variability in timing. Some notable exceptions

included the studies on plasticity of the visual cortex, that led David

Hubel and Torsten Wiesel to share the Nobel prize in 1991. However,

technical advances like functional neuroimaging and powerful

electrophysiological registration, coupled to the enhanced information

processing and miniaturization of devices, led in the last three decades

to a paradigm shi in neurosciences. is happened for the inspiring

works of Peneld on cortical registrations (Peneld and Boldrey, 1937;

Peneld and Jasper, 1954), leading to the denition of brain functional

maps (the so-called ‘homunculus’), that now appear more and more

plastic even in adults. It is becoming increasingly clear that any

function of the brain emerges from a complex network of interactions

between gene expression and environmental inputs, at the micro- and

macro-scale. Under usual circumstances, moving from one step to the

other occurs along a phylogenetically dened best-t pathway,

common to most mammals, that goes from sensory-motor to social

and cognitive development, linked to the maturation of specic brain

areas and networks. As such, any anomaly may hamper the typical

developmental scheme (see Figure 1) and triggers a wealth of

downstream eects aimed at xing the path, with outcomes that may

betting or not.

However, during the developmental path (summarized in Table1)

some critical periods of particular sensitivity and plasticity may

bedelimited, which span through infancy (for example: language

acquisition) and extend to adolescence, in particular for some

functions like memory and social stress management (Fuhrmann

etal., 2015). Actually, time is a critical factor in development, since the

susceptibility to some inuences may dramatically vary, as well as the

consequences at dierent time frames, including biochemical,

electrical, genomic and epigenetic mechanisms, up to the eects at the

level of development of the organism, which may belifelong (Boyce

etal., 2020).

Here wereview the recent literature on the development of the

human brain and its susceptibility to both negative and positive

environmental inuences. A search on PubMed was done on March

24, 2023 with the following terms: BRAIN and PLASTICITY and

CHILD and DEVELOPMENT, in any eld, with no lters for

language or year of publication: 1705 papers were retrieved. By

applying the lters: Meta-Analysis, Review and Systematic Review

573 papers were excluded to give 1,132 papers. e goal was to focus

on healthy brain development, hence abstracts were read and

evaluated to exclude papers exclusively or mainly related to Autism

(n = 75), other diseases (n = 376) or out of focus, including studies

done on cells or animals, or retracted studies (n = 311). e resulting

370 articles were evaluated, sorting out those describing studies on

the morphological and functional normal development of the brain,

stress eects on the brain and music training eects on the brain.

Articles related to second language learning or other manipulations

were excluded, as well as comment articles or introduction to issues,

or duplicate publications (same authors, title or content, also in

dierent languages). e 125 resulting relevant articles are

reviewed here.

2. Morphological and functional

development of the brain

2.1. Structural changes across development

A large longitudinal study addressed the question of whether

cognitive improvement preceded, accompanied or followed the

changes in the thickness and surface area of the cortex from infancy

to adulthood, when an association between cortical measurements

and cognitive performance is apparent: being the rate of change at

each measurement predictive of subsequent changes, it was concluded

that structural changes in the cortex are related to cognitive

performance and vice-versa, without a clear sequence in any measure

(Estrada etal., 2019). Cortical thickness has been also specically

FIGURE1

The timeline shows some acquisitions during typical development. EEG, electroencephalographic; EM, embryonic month; EW, embryonic week; PM,

postnatal month; Yrs, years.

Mucignat-Caretta and Soravia 10.3389/fnins.2023.1266766

Frontiers in Neuroscience 03 frontiersin.org

linked to dierent neurodevelopmental and psychiatric disorders

(Patel etal., 2021).

Normative structural data in the rst 6 years of life highlight a

generalized thinning of cortex, with the exception of the occipital

areas, which rst decrease and then become thicker (Remer etal.,

2017). Cortical thinning is mostly related to pyramidal neurons,

astrocyte and microglia marker genes (Shin etal., 2018). Also, during

the rst 5 years of life, genes in cortical neurons change dramatically

their methylation status, while later changes are much reduced (Price

etal., 2019).

Structural maturation of the frontal cortex, crucial for executive

functions, requires a prolonged postnatal development, which involves

TABLE1 Summary of the main developmental steps during infancy.

Age Stage of

development

Main changes Developmental abilities

Prenatal

period

Fetal development Structural features of the brain

Neurons and synapses start to mature from the spinal cord

Gyri and sulci formation

First synapses and myelination

- First movement of the fetus

- Sensory development of the fetus

First two

years

Sensory-motor

stage

Gradual development of prefrontal cortex and cerebellum

Fusiform gyrus (visual attention)

Myelination increase

Visual/auditory cortex

Increased brain connectivity

Experience dependent synapse formation

0–3 months

- Development of visual and sound perception: turns head toward

speakers and follows face

- Emerging head control

- More controlled movements (hands in the middle line)

- Looks at adult face/Respond to facial expression

- Smile at response

Continue development of motor cortex

Visual/auditory cortex

Experience-dependent synapse formation

3–6 months

- When pulled to sitting, holds head in line with body

- Reaches side position

- Mouths toys

- Reaches and grasps toys

- Looks toward noises

- Smiles in response to speakers

Connectivity between the amygdala and bilateral anterior

insula (fear expression); experience dependent synapse

formation

6–9 months

- Sits alone and extends arm if falling to the side

- Crawls forward on belly

- Picks up object easily and transfers them from hand to hand

- Expresses emotional states

- Responds dierently to caregivers and strangers

- Looks at objects and family members when named

- Imitates facial expressions, actions and sounds

- Angular Gyrus/Broca area maturation 9–12 months

- Cruises holding on the furniture

- Stands alone momentarily

- Imitates actions (claps hands and waves on command)

- Turns when called by name

- Gives objects by request

- Expresses emotions and aections

- Articulates most speech sounds

- Angular Gyrus/Broca area renement (receptive language

and speech production)

12–24 months

- Walks forward and backwards

- Walks up and down stairs with assistance

- Demonstrates use of everyday items

- Language fast development

- Plays alone and with peers

2–7 years Pre-operational

stage

- Synaptic density in the prefrontal cortex reaches its peak

- Frontal and temporal lobes (executive function and

emotional regulation)

- Language improvement

- Increased cognitive abilities

- Uses symbols in play and pretending

- Executive functions (attention control, memory self-regulation,

emotional regulation)

Mucignat-Caretta and Soravia 10.3389/fnins.2023.1266766

Frontiers in Neuroscience 04 frontiersin.org

also the migration and integration of newly formed inhibitory

interneurons (Paredes etal., 2016). Interestingly, inhibitory control

training in children shows larger eects that in adolescent, both on the

eciency of behavioral control and in the structure of some

subdivisions of the inferior frontal gyrus in the prefrontal cortex

(Delalande etal., 2020). Maturation of cortical circuits are also echoed

by biochemical ngerprinting in specic cell types. Neural cell

adhesion molecule (NCAM) isoforms are implicated in cell migration,

axonal growth and synaptic plasticity, besides schizophrenia. As

determined in post-mortem samples, they peak at dierent times

during development in the various areas, from fetal/early infancy to

late adolescence, supporting specic roles in neural circuitry

formation, emerging at precise developmental timepoints (Cox etal.,

2009). Also, connections between areas mature with time: for example,

at 9 months the connections over longer distance are emerging, while

local network connectivity decreases (Damaraju et al., 2014).

roughout development, structural and functional connectivity

develop with non-linear trajectories, which also dier for the various

areas, starting in utero and extending to late adolescence (Van de wouw

etal., 2021). Increased connectivity boosts the emergence of executive

and cognitive functions, with a dierential contribution of the

striatum, which improves cognitive functions in childhood through

increase in the cortico-cortical connections, while its eects on the

executive functions appear less age-related (Darki etal., 2020). During

adolescence, myelin microstructure renes to increase the speed of

electrical signal transmission, at the expenses of diminished plasticity,

and mature rst in sensorimotor areas and then in associative areas

(Baum etal., 2022).

2.2. Development of sensory-motor

functions

In the striate cortex, functional plasticity mirrors the number of

synapses that peaks in the rst year of age and is rapidly rened and

reduced in the subsequent pre-school years (Huttenlocher and de

Courten, 1987). Early imaging studies reported a decrease in grey

matter of frontal and parietal cortices during adolescence (Jernigan

etal., 1991), while enzymes related to cholinergic and glutamatergic

neurotransmission vary across the entire lifespan, in specic areas

(Court etal., 1993). Notably GABA-ergic neurotransmission show a

protracted period of postnatal renement, spanning the rst years of

life and possibly accounting for the protracted plasticity of visual

areas, which allows therapeutic interventions (Murphy etal., 2005).

Also, in the primary motor cortex GABAergic interneurons

mature aer childhood, fostering plasticity and motor learning

(Walther etal., 2009). Contrary to ndings in monkeys, in humans the

corticospinal projections start connecting with spinal cord at 24 post-

conception weeks, between 2 and 4 postnatal months the spontaneous

activity becomes more coordinated between limbs, yet functional

control of distal eectors is reached much later, between 6 and

12 months of age, to support goal-directed movements (Eyre etal.,

2000; Kanemaru etal., 2012).

Movement of the hand requires the identication of targets, which

is usually based on vision: already 2 days aer birth, newborns may

betrained to discriminate kinematic patterns of biological movement,

characterized by subsequent acceleration/deceleration, even if they

spontaneously do not (Craighero etal., 2020). Already at 5–6 months,

the movement of the hand is typically directed to a person or to an

object: this specicity is missing in children not sharing typical

developmental paths (Ouss etal., 2018). Sensorimotor coordination

accuracy improves in primary school children while sensorimotor

integration relies on subcortical circuits maturing at a later stage,

towards adulthood (Savion-Lemieux etal., 2009). On the other hand,

in children and adults, observation of an action activates the same

mirror-neurons system (premotor cortex-inferior frontal gyrus and

posterior parietal lobe), but with a more widespread and more

bilateral activation in children than in adults (Biagi et al., 2016).

Human movement develops through the progressive control of tools

use, which requires a complex dynamic between body size

representation and sensory inputs, so that only in late puberty the

body representation acquires adult features and may rely on

proprioception instead of visual perception (Martel etal., 2021). Of

note, children do not adapt as adults to tactile stimuli, until 8–10 years

of age, suggesting a dierent sensory experience in addition to a

dierent stimulus processing (Domenici etal., 2022).

Expert visual processing of face is lateralized to the right

hemisphere and requires visual input during infancy to become

fully operational, suggesting protracted need for stimulation (Le

Grand etal., 2003), yet face specialization starts before reading

acquisition an impinges on the decreased cortical responses to the

other stimuli (Cantlon etal., 2011), as well as on higher glutamate

relative to GABA levels in the inferior frontal gyrus (Cohen Kadosh

etal., 2015). Similarly, movement-directed visual attentional shis

for actions appears already at 7 months, suggesting concomitant

maturation of visual and attentional systems (Daum etal., 2016).

Later on, during school-age period, the increase in activity of the

adrenal gland with dehydroepiandrosterone (DHEA) surge,

promotes the concomitant maturation of amygdala with occipital

lobe, related to visual awareness, parietal lobe, related to visuomotor

abilities, and frontal lobe, related to attention (Nguyen etal., 2016).

Apparently, DHEA in childhood helps optimization of attentional

and working memory functions but may impair the processing of

spatial cues by reducing the connections from hippocampus to

cortex (Nguyen etal., 2017).

Functional lateralization requires the maturation of corpus

callosum, which has a critical renement period aer 6 years of age,

thus aecting language transfer between the two hemispheres

(Westerhausen etal., 2011). Myelinization is indeed critical for full

functional maturation, but while myelin turnover is fast, the number

of oligodendrocytes in the corpus callosum is stable from childhood,

with a yearly exchange rate of only 1 out of 300 (Yeung etal., 2014).

Prolonged maturation and myelin plasticity appear related also to

increased functional cognitive ability already by 3 years of age (Deoni

etal., 2016). In the rst 2 years of life myelination and microstructural

properties of glia appear related to cognitive abilities, with protracted

development associated to better performance in cognitive and

language tasks (Girault etal., 2019). Also, cortical thickness in the rst

2 years appears related to cognitive abilities, yet the contribution of

gestational age and maternal education may overcome structural

dierences (Girault etal., 2020).

More complex sensory functions, including multisensory

integration, appear subsequently aer middle childhood (Ernst, 2008),

and their ne-tuning appears complete by 14 years (Brandwein etal.,

2011). Cognitive mathematical abilities may berelated to white matter

in the le parietal lobe (Matejko etal., 2013) and better outcomes of

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Frontiers in Neuroscience 05 frontiersin.org

intense math training rely on le perisylvian tracts plasticity (Jolles

etal., 2016a), with a specic eect on connectivity of the intraparietal

sulcus, but not of the angular gyrus, with hippocampus, lateral

prefrontal and ventral temporo-occipital cortex (Jolles etal., 2016b).

e intraparietal sulcus content in glutamate and GABA appears

developmentally linked to math abilities (Zacharopoulos etal., 2021).

Similarly, abacus training in primary school children improves

performance and executive functions by modulating frontoparietal

activation (Wang etal., 2017), and appears linked to the volume of

fusiform gray matter (Zhou etal., 2022). In the rst 2 years of primary

school, better outcomes in mathematical abilities are associated with

specic changes in some cortical areas, in detail: arithmetic abilities

are linked to folding change in the right intraparietal sulcus, and

thickness changes in right temporal lobe and le middle occipital

gyrus, while visuospatial abilities are linked to right superior parietal

thickness, and other frontal areas in the right hemisphere (Kuhl etal.,

2020). However, complex visuospatial tasks elicit strong bilateral

parietal activation in both adults and children from age 5 onwards

(Ferrara etal., 2021).

Quantitative dierences in cognitive abilities, operationally

dened as a higher IQ, appear linked to a prolonged sensitivity to

environmental inuences (Brant etal., 2013) while its relationships to

cortical thinning and surface area in late childhood appears

controversial (Burgaleta etal., 2014; Schnack etal., 2015). Functional

control for cognitive functions emerges at a later time, for example

executive attention is linked to planning and inhibitory control, and

allows the development of self-regulation (Rueda et al., 2005).

Functional plasticity appears high in late childhood also for memory

function (Brehmer et al., 2007). Emotional regulation steers

impulsivity in the context of prospective thinking: it appears in late

childhood and is related to insula thickness (Churchwell and

Yurgelun-Todd, 2013). As outlined above, amygdala development is

crucial in managing the emotional reactivity: it is noteworthy that the

paralaminar nuclei of amygdala host a population of immature cells

that slowly develops through childhood and adolescence into

excitatory neurons but still persists even in old age, suggesting a

protracted plasticity in this area (Sorrells etal., 2019).

e developmental trajectory goes through a reduction in

modularity and local eciency of brain processing, while increasing

global eciency. is increase in the eciency of global processing,

linked to functional maturation, initially aects sensorimotor areas.

At variance, associative and paralimbic areas show a protracted

plasticity during late childhood, which may account for peripubertal

behavioral modulation (Khundrakpam etal., 2013). In school-age

children, enhanced brain modularity may also prepare for disclosing

eects of physical activity on cognitive and executive functions

(Chaddock-Heyman etal., 2020).

2.3. Sleep to grow

Already during the rst year of life, the pattern of night sleep and

awakening may predict typical and atypical cognitive trajectories

(Pisch etal., 2019), while slow waves propagation during the night,

which depends on brain connectivity, is reduced in toddlers

compared to older children (Schoch etal., 2018). Also, the decline in

slow-wave non-REM sleep activity is steeper during adolescence, in

caudal-rostral direction, suggesting late functional reorganization

following structural synaptic pruning (Feinberg et al., 2011). At

variance, local increase in slow-wave activity over the right parietal

areas, related to visuomotor-dependent plasticity, is higher in

children (Wilhelm etal., 2014), as it is the slow-wave increase in le

frontoparietal areas aer working memory training (Pugin etal.,

2015). Around 1 year of age, sleep spindles appear to berelated to

semantic generalization of words (Friedrich etal., 2015), while in

school-age children the learning-dependent hippocampal activity

and sleep-related frontal activity do change at a faster rate than in

adults (Urbain etal., 2016). Children also show the largest overnight

slope change in slow waves, which may berelated to the increased

plasticity of children brain (Jaramillo etal., 2020). Slow waves are

generated by corticocortical connections while spindles results from

thalamocortical activity and in adolescents appear modulated by

genetic background in posterior areas, while spindles in anterior

areas are more sensitive to environmental factors (Rusterholz etal.,

2018). Interestingly, the larger modulation of slow-wave activity

during night in children is not accompanied by the change in

glutamate/glutamine which is apparent in adults, pointing to dierent

biochemical pathways in children (Volk etal., 2019). Another feature

of human EEG activity is the alpha oscillation, which shows a

maturation during childhood, most apparent for the aperiodic

component: this is related to increased thalamocortical connections

and attentional performance (Tröndle etal., 2022).

3. How environment may interact with

developmental trajectories

e eect of environment on development can bepositive or

negative from the very beginning of pregnancy throughout postnatal

life. Among negative environmental regulations with a heavy societal

impact, the eect of pre-natal alcohol exposure has long been studied

in both animals and humans. Several studies have documented the

long-lasting eects of maternal alcohol consumption on both the

structure and functions of the developing brain and ultimately child

tness. Despite the detailed discussion of this topic is outside the

scope of this Review, wehighlight that early longitudinal studies

proved the adverse eects of heavy drinking during pregnancy on the

morpho-functional development, in particular in the parietal cortex

(Lebel etal., 2012) and in the development of white matter in relation

to executive functions (Gautam etal., 2014).

Also, other environmental stimuli or their absence may interfere

with the development of structural features and functional

acquisitions during postnatal development. In order to develop

harmonic abilities, the interaction with environment may foster or

hinder functions aer their appearance. As an example, children with

blind parents normally show the eye contact from birth, which

usually is a common means of communication, but by age 6 months

onwards they display progressively less attention to gaze processing,

even if this is not related to impairments in social or cognitive

abilities, suggesting that even ‘obvious’ abilities require a strong

social/environmental input and practice to be fully operational

(Senju etal., 2015). Hence, the neuroscientic literature provides

several lines of evidence that support the steering role of

environmental stimuli in early development, with durable eects in

dierent areas, both anatomical and functional, including cognitive,

emotional, and social abilities.

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Frontiers in Neuroscience 06 frontiersin.org

3.1. Case studies

Here webriey introduce two examples, one of negative (stress)

and one of positive (music training) environmental inuences on the

development of the brain and its functions, to highlight how much

weas adults are responsible for the life paths of future generations. In

order to include articles from dierent countries, socioeconomical

status and cultures, wefocused on two modulators that were less likely

linked to these factors. Stressful environmental conditions like low

socioeconomical status, trauma or neglect share similar characteristics

among dierent cultures. Also, music and music training are

widespread in all cultures, and include learning sensory-motor

abilities which makes them less dependent on overall cognitive

abilities or higher socioeconomical status than, for example second

language training. us, music training appears a robust example to

explore in this review.

3.2. The role of stress

Stress may profoundly impact on neurodevelopmental trajectories,

at dierent ages, by means of the dierent neural, endocrine,

neuroendocrine, metabolic and immune responses. Notably, the brain

itself is the target of stress hormones, that shape the brain stress

response, tuned to plasticity, a double-edged sword that may either

blunt or enhance adaptive responses, modifying the vulnerability to

early life stressors. Under this respect, the concept of resilience

includes the processes leading to positive adaptation to relevant

traumas or adverse challenges. Early rehabilitation and care, including

proprioceptive stimulation as sensory-tonic stimulation and kangaroo

care, coupled to parenting support may inuence the development of

very preterm infants (Guittard etal., 2023), while severe maltreatment

or abuse impairs functional and structural brain development, thus

representing a relevant threat for the single person and a signicant

cost for society. Hence, boosting resilient responses in high-risk

persons may promote neural and neuroendocrine plasticity to

decrease maladaptive or even psychopathological responses (Cicchetti,

2010). In the rst 2 years of life, elicited imitation task as a tool to

investigate declarative memory, reveals that neglected children do not

receive maternal feedback while abused children do, leading to a loss

of plasticity in neglected children, while increased imitation in abused

infants possibly leads them to increased cognitive but decreased social

competence (Cheatham etal., 2010). e brain-derived neurotrophic

factor (BDNF) is involved in synaptic plasticity and is dierentially

expressed in childhood (Sterner et al., 2012). Interestingly, the

exposure to unfavorable environment leads to depression in persons

carrying the Val66Met BDNF polymorphism (Comasco etal., 2013),

with Val carriers of the same polymorphism more prone to self-

injurious behavior (Bresin etal., 2013), while childhood abuse in Met

carriers results in poorer cognitive performance and brain anomalies,

including larger lateral ventricles and reduced right hippocampus

(Aas etal., 2013). e same polymorphism appears to impact stress

experience more at late stages (Lehto etal., 2016). BDNF methylation

in adolescent brain is related to neighborhood disadvantage and

thinner lateral orbitofrontal cortex (Wrigglesworth et al., 2019).

Children outcome on dierent measures was linked to parenting

quality, but also to BDNF status and genes involved in dopamine and

serotonin neurotransmission, that appear to convey some vulnerability

to environmental stress, fostering the vision of a continuum of general

traits to describe the responses to stress, instead of two susceptibility

traits (e.g., the orchid/dandelion duality) leading to dierent responses

(Zhang etal., 2021). By widening the analysis to the BDNF gene

network, it appeared that this network interacted with adverse

prenatal conditions to aect later cognitive development, so that a

high BDNF network score coupled to high prenatal adversity resulted

in slower cognitive development and grey matter density in associative

cortical areas (de Mendonça Filho etal., 2021).

Material hardship linked to poverty may lead to dierent

amygdala-prefrontal cortex connectivity in late infancy, and leads to

reduced amygdala-orbitofrontal cortex connections in adolescents,

also related to anxiety and depression, indicating some preferential

windows of plasticity for targeted supporting interventions (Hardi

etal., 2022).

Low socioeconomic resources may impair visual working

memory, as a proxy for cognitive abilities, and related brain activity in

the le frontal cortex of children up to 4 years old (Wijeakumar etal.,

2019). e socioeconomical status may result in dierential exposure

to language or stress, which may bethe bases for the dierences in

hippocampus and amygdala seen in socioeconomically disadvantaged

children, with an additional contribution of age, inducing additional

dierences in the le superior temporal and inferior frontal gyri

(Noble etal., 2012). Similar reductions in amygdala and hippocampus

were detected in children experiencing early life stress in the form of

physical abuse, early neglect or low socioeconomic status (Hanson

etal., 2015). Child abuse appears also to aect the morphological

complexity of the prefrontal cortex and to increase recruitment of

perineuronal networks, mediated by oligodendrocyte precursors, that

lead to decreased plasticity (Tanti etal., 2022).

A large study conrmed that trauma exposure resulted in

adolescent thinner superior frontal gyri and right amygdala and larger

cingulate cortices (Jeong etal., 2021). Child maltreatment results in

increased Cornu Ammonis (CA) 4 subeld of hippocampus, most

apparent in males, while larger CA1 is associated with late-onset

psychopathology, suggesting that maltreatment dierentially aects

hippocampal subelds, which may precede the appearance of

psychopathology (Whittle etal., 2016). e level of self-perceived

stress is also associated with smaller hippocampal volume in

adolescents (Piccolo et al., 2018), and in a longitudinal study,

attachment dimensions like anxiety and avoidance were linked to

larger decreases in prefrontal and anterior temporal cortices in

adolescent brain (Puhlmann etal., 2023).

In adolescents, post-traumatic stress disorder, as a result of altered

fear regulation, is linked to decreased grey matter volume in the

centromedial and basolateral amygdala, whose connectivity with le

orbitofrontal and subcallosal cortices is increased, while connections

to the right cingulate and prefrontal cortices appear less strong

(Aghajani etal., 2016).

Volumetric correlations among dierent areas indicate that

prenatal stress but not childhood trauma may de-couple amygdala

growth from the development of other regions involved in emotional

processing (Mareckova et al., 2022). Early childhood deprivation

induces long-term modications, apparent in adult white matter

tracts, in particular of the limbic circuits and long-ranging association

bers, while the microstructural organization appears not altered

(Mackes et al., 2022). Also, epigenetic changes in some genes

associated to child abuse may enhance the risk of child depression

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Frontiers in Neuroscience 07 frontiersin.org

(Weder etal., 2014), and regions of low methylation dierentiated

children receiving less tactile contact (Moore etal., 2017). Lastly,

genome-wide mapping shed out some loci linked to postnatal stress

and subcortical structures like caudate and accumbens nuclei, which

have a role in neuronal plasticity and neurodevelopmental disorders,

however causality remains to beascertained (Bolhuis etal., 2022).

3.3. Music training – positively steering

development

Highlights for positive experience-related brain plasticity stem

from the eects of music training in infancy, because of the worldwide

diusion of music across all human cultures, paralleled by a

widespread training at young age, which is however not diuse to all

persons. Because of the multimodal nature and prolonged practice of

instrument or voice, music training appears well suited to exploit

plastic capabilities of the brain.

Adult musicians show increased sound discrimination, as a result

of training. Early music training enhances children performance in

specic musical skills like melody discrimination (Ireland etal., 2019).

Aer 2 years of training in school age children, an improvement in

tonal discrimination and increased maturity of auditory processing

are apparent (Habibi etal., 2016). In 9 to 15 years old trained or

untrained subjects, cognitive exibility was linked to sound

discrimination performance, which was more apparent in music-

trained group (Saarikivi etal., 2016).

Instrument practice allows a regional-specic increase in the

organization of the pyramidal tract already in childhood (Bengtsson

et al., 2005) and extend to cognitive abilities underlying musical

training, initially on more closely related elds (Schlaug etal., 2005).

Long lasting eects on motor performance appear stronger if the

music practice starts before age seven, even if the amount of training

was similar, pointing to the existence of a sensitive period in infancy

(Penhune etal., 2005).

Interestingly, even relatively a short period (9 months) of music

training may produce benets for pitch processing in music but also

in language, showing that cognitive benets extend over dierent

cognitive domains, by modifying their neural substrates and related

pattern of brain activity (Moreno etal., 2009). Musical and linguistic

syntactic abilities may belearned through similar processes in early

infancy and about age 4–5, music training aects timbre identication

and improve language abilities, like morphologic rule formation and

memory for words, showing that training eects extend beyond the

music domain (Marin, 2009). Notably, increased right brain activity

due to human voice processing is related to intelligence in toddlers

and school-age children (An etal., 2020).

Preschool children benet even from short (20 days) music

training, whose eects spill over to verbal intelligence and executive

function tasks (Moreno etal., 2011). Over 2 years of training around

8 years old, speech segmentation skills improve more than in

untrained children suggesting therapeutic strategies for children with

language impairments and related learning diculties (François

etal., 2013).

In preschool children, music or second language training induce

long-lasting improvement in processing of the trained sounds and

increase suppression of untrained, non-relevant sounds, as shown by

event-related potentials (Moreno etal., 2015).

By exploring the brain structure, aptitude to music in

school-age children is related to pre-training structural

organization of the right corticospinal tract while the corpus

callosum structure appears more linked to tonal ability (Zuk

etal., 2022).

Increased pitch discrimination is related to larger auditory regions

in both untrained and music-trained adults and children, while in

musicians it is also associated to larger inferior frontal gyrus (Palomar-

García etal., 2020).

Aer only 15 months of practice, music training may induce

structural changes in the brain, directly related to improvements in

auditory and motor skills (Hyde etal., 2009). Apparently, starting

musical training before age 7 changes white matter connectivity, more

robustly in the isthmus of corpus callosum: therein, fractional

anisotropy, related to myelinization, is linked to both age of starting

the training and sensorimotor synchronization performance (Steele

etal., 2013). On the other hand, the benets of music appear to extend

also to prenatal age, since in preterm infants exposed to musicotherapy,

the maturation of white matter improved in acoustic radiations,

claustrum and uncinate fasciculum, and also amygdala volumes

increased, suggesting improved acoustic and emotional processing,

compared to non-exposed preterm and full-term babies (Sa de

Almeida etal., 2020). e age of onset is critical for structural changes

to appear: focusing on exposure to a second language and music, it

emerged that the arcuate fasciculus, which participates in both music

and language activities by linking areas of the dorsal auditory pathway,

is sensitive to second language in the le hemisphere, while in the

right one it changes according to music exposure (Vaquero etal.,

2020). Hence, the structure of dierent areas is selectively modied

according to the type of experience mostly in early infancy.

4. Development is socially modulated

A relevant, yet underappreciated, issue in developmental

neuroscience is the social nature of our species. In a study involving

both parents and children, focused on the intergenerational

transmission of sociality, the parents’ limbic, embodied simulation

and mentalizing networks appeared linked to the use of strategies for

children’s emotion regulation, suggesting a strong link between

parent–child interactions and later child social life (Abraham etal.,

2016). However maternal inuence starts prenatally, since maternal

stress (e.g., pandemic-related) aects 3 months infants’ regulatory

capacity (Provenzi etal., 2021), and also extends to calibration of

growth rate and timing of sexual development, by aecting postnatal

testosterone levels in infants (Corpuz, 2021). Maternal depression

during pregnancy appears to inuence the development of amygdala,

by interacting with the canonical transforming growth factor-beta

(TGF-β) signaling pathway (Qiu etal., 2021).

In school-age children, parental praise as a positive parenting style

may result in increased openness to experiences and carefulness,

together with increase in gray matter in the posterior insula, which is

involved in empathy modulation due to the connections with

amygdala (Matsudaira et al., 2016). By using fMRI-based

neurofeedback, it was possible to demonstrate that both children and

adolescents can learn to upregulate amygdala function, suggesting a

possible tool to act on regulation of emotional reactivity (Cohen

Kadosh etal., 2016).

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5. Conclusion

e possibility of non-invasive exploration of the living brain also

in children, emerged in the last years, led to a dramatic increase in our

understanding of development of the brain and its functions, in the

context of the growing body. e development of cognitive,

emotional, and social behaviors appears more along a continuum

than limited to narrow developmental windows, while certain

attainments may bespecic to some developmental periods (Guyer

etal., 2018). Out of the laboratory, the increasing knowledge of the

developmental processes led to a paradigm shi in the approach to

children, in the context of parental relationships and pedagogical

approaches, up to inform the political processes. Actually, sharing

knowledge accumulating through dedicated studies on brain

development and the increasing evidence about the long-lasting

functional outcome of environmental modications, may serve to

raise consciousness about the actions to undertake to provide support

and care to fragile children. While awareness of environmental risks

for development and overall health is increasing (Chesney and

Duderstadt, 2022), a widespread knowledge of the risks and

possibilities for external actions to drive children development is still

on the way. e possibility of early detection of child needs even with

primary pediatric care and support to the family increases the chances

of steering cognitive, emotional and social development towards

positive outcomes (Williams and Lerner, 2019). Addressing adverse

childhood experiences requires fostering health and educational

services to promote the foundation of lifelong health, with the

necessary inclusion of family (Bethell etal., 2017). Assistance for

families, starting from maternal health, and for communities will

provide supporting relationships to lay the foundation of resilience

throughout life (Traub and Boynton-Jarrett, 2017). is should

bedeclined across dierent cultures and is particularly relevant for

children with additional requirements, like neurodevelopmental

disorders (Bannink Mbazzi and Kawesa, 2022). Including constructs

like ‘neuroplasticity’ in the educational trajectories led to an

empowerment of the main actors, children, parents and teachers by

fostering executive functions (Choudhury and Wannyn, 2022). e

contribution of widespread schooling on the social construction of

cognition and neurocognitive development has long been appreciated

(Baker etal., 2012). In these last years, programs have been designed

to support selective attention in children from low socioeconomic

status with some genotypes which may represent a risk factor (Isbell

etal., 2017). However, cognitive development is only one side of the

coin: the role of social regulation of development, starting from

parents to the group of peers needs to berecognized and actively

included in political long-sighted plans. More can bedone on the

bases of the recent data on the involvement of social processes in the

development of self-regulatory processes, to improve both personal

development and society.

Author contributions

CM-C: Conceptualization, Data curation, Funding acquisition,

Investigation, Writing – original dra. GS: Writing – review & editing.

Funding

e author(s) declare nancial support was received for the

research, authorship, and/or publication of this article. is work was

supported by a grant from the University of Padova (DOR2021)

to CM-C.

Acknowledgments

We thank Luisa Canella for pushing us over the years to maintain

our experimental (CM-C) and clinical (GS) focus on child

development, and Antonio Caretta for fostering CM-C interest in

brain development.

Conﬂict of interest

e authors declare that the research was conducted in the

absence of any commercial or nancial relationships that could

beconstrued as a potential conict of interest.

e author(s) declared that they were an editorial board member

of Frontiers, at the time of submission. is had no impact on the peer

review process and the nal decision.

Publisher’s note

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and do not necessarily represent those of their aliated organizations,

or those of the publisher, the editors and the reviewers. Any product

that may be evaluated in this article, or claim that may be made by its

manufacturer, is not guaranteed or endorsed by the publisher.

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Frontiers in Public Health 01 frontiersin.org

Econeurobiology and brain

development in children: key

factors aecting development,

behavioral outcomes, and school

interventions

RaedMualem

1,2,3,4*, LeonMorales-Quezada

RaniaHusseinFarraj

3, ShirShance

2,3, DanaHodayaBernshtein

SapirCohen

3, LoayMualem

6, NivenSalem

2, RivkaRikiYehuda

YusraZbedat

4, IgorWaksman

7 and SeemaBiswas

1 Department of Natural and Environmental Sciences, Faculty of Education, Oranim Academic

College, Kiryat Tiv'on, Israel, 2 The Institute for Brain and Rehabilitation Sciences, Nazareth, Israel,

3 Econeurobiology Research Group, Research Authority, Oranim Academic College, Kiryat Tiv'on,

Israel, 4 Ramat Zevulun High School, Ibtin, Israel, 5 Department of Physical Medicine and Rehabilitation,

Harvard Medical School and Spaulding Rehabilitation Hospital, Boston, MA, United States,

6 Department of Computer Science, Haifa University, Haifa, Israel, 7 Bar Ilan University Medical School,

Tzfat, Israel, 8 Global Health Research Laboratory, Department of Surgery B, Galilee Medical Center,

Nahariya, Israel

The Econeurobiology of the brain describes the environment in which an

individual’s brain develops. This paper explores the complex neural mechanisms

that support and evaluate enrichment at various stages of development,

providing an overview of how they contribute to plasticity and enhancement

of both achievement and health. It explores the deep beneﬁts of enrichment

and contrasts them with the negative eects of trauma and stress on brain

development. In addition, the paper strongly emphasizes the integration

of Gardner’s intelligence types into the school curriculum environment. It

emphasizes the importance of linking various intelligence traits to educational

strategies to ensure a holistic approach to cognitive development. In the ﬁeld

of Econeurobiology, this work explains the central role of the environment in

shaping the development of the brain. It examines brain connections and plasticity

and reveals the impact of certain environmental factors on brain development

in early and mid-childhood. In particular, the six key factors highlighted are an

environment of support, nutrition, physical activity, music, sleep, and cognitive

strategies, highlighting their potential to improve cognitive abilities, memory,

learning, self-regulation, and social and emotional development. This paper

also investigates the social determinants of health and education in the context

of Econeurobiology. It emphasizes the transformative power of education

in society, especially in vulnerable communities facing global challenges in

accessing quality education.

KEYWORDS

public health, brain development, brain connectivity, plasticity, learning, education,

self-regulation, social determinants of health

OPEN ACCESS

EDITED BY

Sarah C. Hellewell,

Curtin University, Australia

REVIEWED BY

Toshiki Iwabuchi,

Hamamatsu University School of Medicine,

Japan

Carla Mucignat,

University of Padua, Italy

*CORRESPONDENCE

Raed Mualem

raed.mualem@oranim.ac.il

RECEIVED 24 January 2024

ACCEPTED 29 July 2024

PUBLISHED 26 September 2024

CITATION

Mualem R, Morales-Quezada L, Farraj RH,

Shance S, Bernshtein DH, Cohen S, Mualem L,

Salem N, Yehuda RR, Zbedat Y,

Waksman I and Biswas S (2024)

Econeurobiology and brain development in

children: key factors aecting development,

behavioral outcomes, and school

interventions.

Front. Public Health 12:1376075.

doi: 10.3389/fpubh.2024.1376075

Shance, Bernshtein, Cohen, Mualem, Salem,

Yehuda, Zbedat, Waksman and Biswas. This is

an open-access article distributed under the

terms of the Creative Commons Attribution

License (CC BY). The use, distribution or

reproduction in other forums is permitted,

provided the original author(s) and the

original publication in this journal is cited, in

accordance with accepted academic

practice. No use, distribution or reproduction

is permitted which does not comply with

these terms.

TYPE Review

PUBLISHED 26 September 2024

DOI 10.3389/fpubh.2024.1376075

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1 Introduction

e human mind is capable of astonishing function. Weare still

understanding how the brain develops and adapts to life experiences

and the environment in which a child grows. A glance at the United

Nations Sustainable Development Goals (1), shows the importance of

a child’s environment in maximizing educational opportunity and

attainment. e rst 3 years of life are when the brain is most plastic

(capable to change and adapt through life experiences). Research has

shown that early environmental inuences signicantly shape brain

architecture. For example, studies have demonstrated how

socioeconomic factors can aect brain development, linking poverty

to alterations in brain structure and function (2, 3).

is article focuses on brain research related to child development

and learning in early and middle childhood (2–5 years and 6–11 years,

respectively), examining how environmental and epigenetic factors

– collectively referred to as the econeurobiology of the brain – interact

to inuence brain development. Wepresent an econeurobiological

model that integrates these factors and oers educational and policy

proposals inspired by Gardner’s model of intelligence. is model is

rst introduced here to provide a framework for understanding the

subsequent sections of the manuscript. Additionally, a detailed outline

of the manuscript is provided to help readers grasp the overall picture

and navigate the complex interactions discussed in the

following sections.

Econeurobiology is dened as the study of how environmental

and epigenetic factors inuence neurobiological developmental

processes in the brain, particularly during early childhood. is

multidisciplinary eld examines the intricate interactions between the

environment, genetic predispositions, and brain development.

In order to understand how to optimize learning inside and

outside the classroom, an appreciation of how the human brain

develops and functions, and how cognition, concentration, learning

and memory are enhanced through brain connectivity and plasticity

is important. e context in which a child grows is crucial, especially

when environmental exposure can aect – positively or negatively –

the dynamics behind neural functional connectivity throughout

development. e context can enhance learning, well-being, and

resilience when environmental conditions are optimized, but can

substantially disadvantage a child who is subjected to environments

of continuous stress and privation (2–4). ese factors exert their

eects into adulthood, with implications for individuals, families,

communities, and societies. ese factors are both the social

determinants of learning and the social determinants of health. eir

interaction is at multiple levels and is cumulative. us, positive

interventions that aect health and education in early childhood have

potentially profound and far-reaching impacts on individuals,

families, and their communities (5–8).

Drawing on a wide range of literature from neurodevelopmental

biology to pedagogy, this paper introduces the econeurobiological

model, which examines how environmental and epigenetic factors

inuence neurodevelopmental processes in the brain. Our model

integrates these factors to understand their impact on brain

development, especially in children. In addition to detailing the

neurobiological mechanisms involved, the paper presents educational

and policy proposals inspired by Gardner’s model of intelligence,

aiming to enhance cognitive development through tailored

educational strategies.

1.1 Evolution of the human brain

Research into the evolution of primates has revealed that the

uniqueness of the human brain is not determined by its volume but

by the number of neurons within the brain and the network of

connections between them (9). Human brain volume as a ratio to

body mass is larger than that of other mammals. For example, the

adult elephant brain weighs 4–5 kg, while the human brain weighs

1.5 kg (1.5 liters by volume). e human brain’s 86 billion neurons

contrast with a gorilla’s 30 billion. A gorilla needs to eat for about

8 h a day in order to meet the energy requirements of its brain.

Humans need to eat substantially less (9, 10). e evolution of

human brain size is probably a function of evolutionary changes in

diet, foraging for food, and optimizing energy metabolism. One

explanation is the invention of re and the consumption of cooked

food – food eciency (10). Homo erectus (the upright man) rst

began using re in areas of SouthAfrica and present-day Kenya

about 1.5 million years ago (11). Beyond the impact of cooking on

brain architecture, it is likely that environmental pressures and

social competition have played a signicant role in brain volume

development and an increase in the number of neurons (12).

Cooked food is more easily digested and yields more calories than

raw food (13). e human brain makes up2% of body mass, but it

consumes about 20% of daily energy, which is linearly related to the

number of neurons and the quality of neural connections. e

energy consumption of a neuron is constant and does not depend

on the size of the brain (14). Figure1 illustrates the evolutionary

increase in brain volume.

e expansion of the neocortex through primate evolution

parallels the greater cognitive capacity of the human brain (Figure2).

Neuroanatomical experiments have shown that exercise can increase

dendrites, spines, and other structures, indicating that functional

activity drives the anatomical reshuing of neurons and areas. For

example, motor training induces experience-specic patterns of

plasticity across the motor cortex and spinal cord (16). Humans have

the largest frontal cortex of all primates and the entire cerebral cortex

of humans in proportion to body size is larger than in other primates

(9, 10, 13, 16). It is human fetal development of the neocortex and

subsequent cellular organization and connectivity between brain areas

that distinguishes it from the brains of other primates in terms of

intellectual capacity (17).

1.2 Building brain architecture

During the rst years of our lives, over a million new neural

connections are formed every second. is rapid rate of synapse

formation highlights the high brain plasticity during early childhood,

which is crucial for signicant learning potential. e rate of

connection formation and brain plasticity decreases with age (18).

e stages of brain development include neurogenesis, cell

migration, dierentiation, maturation, synaptogenesis, cell death and

pruning, and myelogenesis. Neurogenesis begins in the early

embryonic stage and is usually completed 5 months aer birth.

Neurogenesis in the hippocampus, however, continues through life,

not only in the hippocampus but also in the subventricular zones,

rostral migratory stream, and olfactory bulb network, playing a crucial

role in learning and memory (19).

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Each of the stages of development is aected by neurohormonal

and environmental factors. Dendrites in babies protrude from the cell

body and extend dynamically over the rst 2 years of life. Axons grow

much faster than dendrites and, therefore, through contact with the

dendrites of other neurons, inuence dendrite dierentiation and

neuronal connectivity. An increased and redundant number of

neurons and connections are formed in the rst 2 years – more than

needed; thus, cell death and synaptic pruning take place. Aer a

FIGURE1

The increase in brain volume among primates.

FIGURE2

Overview of brain functions. This simpliﬁed summary highlights major brain regions and their primary functions. Note that many functions involve

interactions across multiple areas. Key regions include the hypothalamus, which has a major role in reactions to stress (15), brainstem (pain modulation

and sympathetic outﬂow), and the reward system (VTA, nucleus accumbens, prefrontal cortex) (ﬁgure drawn by Sally Saadi).

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period of rapid proliferation and the construction of neural pathways

and networks, neural connections are reduced through pruning so

that electrical circuits in the brain can operate more eciently (19).

Experiences in early childhood- the critical period – determine

the process of neurological development and the architecture of neural

networks – the wiring in the brain (6, 20, 21). Networks that are

continuously used are strengthened while unused networks are

pruned (22, 23). Every active thought, feeling, or behavior leads to the

activation of thousands of neurons that connect together. Repetitive

patterns of behavior or thought result in automatic neural activation.

On the other hand, patterns of behavior and thought that are

suppressed or interfere with established network formation disappear.

e creation of environments that stimulate neural networks that

support learning is crucial. Equally, shielding children from negative

environmental factors substantially impacts cerebral plasticity (24).

us, a child’s rst years signicantly aect the architecture of the

continually developing and changing brain as the child’s experiences

shape the formation and pruning of connections through the process

of developmental synaptogenesis (6, 25, 26). A key neurotransmitter

implicated in embryonic development is gamma-aminobutyric acid

(GABA), controlling cell migration. Glutamate and glycine receptors

appear from the rst phases of cortical development, and while a

detailed study of neurotransmitters is beyond the scope of this article,

interference with neurotransmitter signaling has been implicated in

several neurodevelopmental disorders (27–29). Dysregulation in

neuronal dierentiation and signaling with abnormal synaptic

function are similarly associated with dopaminergic (and other

neurotransmitter) pathways in early brain development implicated in

cognitive, behavioral, and psychiatric disorders.

Impaired connectivity between neurons has an immediate eect

on cognitive, behavioral, and emotional function, which, in turn,

aect learning (5, 6), and emotional regulation (30). When an

individual vocalizes a word aer reading, distinct neural networks

are activated compared to when the word is spoken aer being

heard. is dierence is highlighted in studies utilizing functional

MRI (fMRI) and electrophysiological measurements, which show

that reading and auditory processing engage dierent cortical areas,

reecting the various pathways involved in language processing and

cognitive functions (6, 31, 32). e stimulus and subsequent

processing of information are dierent. us, several stimuli modify

cortical organization and connectivity in specic and dierent

ways. Understanding which parts of the cortex are involved in a

process is complex but functional MRI (fMRI) and

electrophysiological measurements of cortical oscillations are of

value. Electrophysiological analysis involves the study of types of

brain electrical activity and their intensity and distribution over the

cortical surface. In fact, EEG has been used to evaluate brain

maturity from newborns to infants, where specic patterns of

activity such as the occurrence of posterior rhythm, sleep spindles,

and vertex waves represent markers of adequate electrographical

development (especially when these events occur between 6 and

8 weeks aer birth) (31). Some neural correlates of behavior and

cognition can beassociated with EEG activity. EEG activity across

dierent frequency bands is associated with a variety of cognitive

and physiological states, but these associations are complex and

multifaceted. For instance, gamma waves are oen linked to

cognitive processing and problem-solving activities. Beta waves are

associated with active thinking and focus, while alpha waves are

related to relaxation and calm states. eta waves are typically

observed during meditative, drowsy, or creative states, and delta

waves, while prominently associated with deep sleep, can also

appear during focused attention and certain cognitive tasks

(Figure3) (5–8, 33, 34). us, it should bepossible to see whether

a child is calmly learning by monitoring electroencephalography

(EEG) activity. In contrast, previous studies of children exposed to

toxic stress showed patterns of neural activity that reect cortical

hypoactivation, including reduced alpha power with increase power

of the theta band (35). erefore, EEG can bea valuable tool in

evaluating neurophysiological markers of brain maturity in the

context of cognitive and behavioral function. Recent advances in

signal analysis methods have been used to generate predictive

models, where cognitive processing, emotional states, or behavioral

performance are correlated with biological markers of EEG activity,

to monitor cognitive behavioral development in children or to

assess responses to therapeutic interventions.

1.3 Developmental plasticity

Most of the human behavior result from social interactions and

exposure to the environment. Some, however, are found to beprewired

into the brain, such as the capacity to develop language. Similarly, the

brain’s ability to process and integrate visual stimuli exist almost

immediately aer birth (36). Nevertheless, the expansion of brain

development is further boosted as the newborn is exposed to new

sensorial and emotional experiences. It is during this developmental

stage that neural networks, primed to receive new stimuli, compete for

survival by becoming more ecient and precise in response to

environmental demands. e neuronal mechanisms supporting the

formation of new memories and learning consist of use-dependent

long-term modications of synaptic transmission. Moreover, this

synaptic connectivity must bestrengthened by repeated temporal

ring to promote long-term potentiation (LTP) (37). It has been

conrmed that tetanic stimulation of excitatory pathways led to long-

lasting enhancement of the ecacy of the synapses between the

activated bers and the respective postsynaptic neurons (38), this

increase in synaptic ecacy occurs only if the postsynaptic neurons

respond by generating action potentials to the ongoing tetanic stimuli,

thus fullling the criterion of contingent pre and post synaptic

activation (39). When postsynaptic neurons are prevented to respond

to the stimuli, synaptic strengthening is void, leading to a decrease in

synaptic ecacy, this phenomenon is known as long-term depression

(LTD). e molecular basis supporting the generation of LTP and

LTD are beyond the scope of this chapter, yet, it has been shown these

synaptic modications are calcium dependent and that the polarity of

the modications depends on the rate of rise, and the amplitude of this

calcium increase (40). us, fast, and strong intracellular increase of

calcium lead to LTP, while slow and smaller increases trigger LTD

(41). erefore, stimulus-induced, and self-generated neuronal

synchronized activity, plays a crucial role in the activity-dependent

shaping of the neuronal architecture during development. is has a

direct impact in the formation of cognitive skills in humans, as LTP/

LTD activity must benely tuned to promote synaptic strengthening

and synaptic consolidation during learning experiences.

Hence, endogenous and exogenous factors inuence how

neuronal circuits develop early in life. Exposure to a nurturing

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environment can further facilitate neuronal growth and renement,

while exposure to adverse conditions will have a detrimental eect.

Consequently, families must besupported by their societies to

provide the most favorable – econeurobiology – environment for

development, so children can have the opportunity to achieve their

physical and intellectual potential.

1.4 The capacity for learning

Understanding an individual’s cognitive abilities, temperament and

behavior depends on an understanding of neuroscience and

neurological function (33). e brain contains about 86 billion neurons,

16 billion of which are in the cerebral cortex. is number of neurons

is unique to humans and explains the high-energy requirements of the

human brain compared to other living creatures. e human brain

constantly changes and renews itself in response to new experiences,

knowledge, and information from the environment – brain plasticity (7,

8, 10). Neurons are the basic units of information processing and

decision-making. e large number of neurons in the human cerebral

cortex and neural networks are responsible for brain connectivity and

higher functioning (10, 13). Neurons connect with each other through

a process called synaptogenesis, with electrical transmission resulting

in the secretion of neurotransmitters. One neuron may form as many

as 10,000 new connections (8, 10, 13). It is the formation of these

connections that is crucial to the process of learning. Plasticity allows

people to learn and adapt. us, while at birth, all individuals have

approximately 86 billion neurons, the environment and an individual’s

social interactions shape the structure and architecture of the brain and

facilitate cognitive and learning processes. ese processes include the

formation of ideas, the solution of multivariate problems, strategies to

navigate daily activities, contingency planning, and the expression of

character, emotion, and behavior. e capacity for learning and self-

regulation (moderation of one’s behavior) are essential to resilience in

childhood and adult life. It is the processing of information in the

cerebral cortex and connectivity, especially with the limbic system, that

makes it possible for an individual to weigh information, draw

conclusions, judge good and evil, remember events and their

signicance, learn from mistakes, plan ahead and change these plans as

circumstances change, and form patterns of behavior and personality.

e organization of the cerebral cortex is dependent on the individual’s

exposure to environmental factors and personal life experiences that

aect gene expression; thus, the environment of a child at home and in

school inuences the creation of neuroproteins and transmitters that

promote brain connectivity (42). e more frequently a process of

experience takes place, the stronger the connections between neurons.

Conversely, a failure to stimulate a child and the withholding of aection

diminish connectivity and result in the loss of neurons, a reduced

capacity to learn, and an inability to self-regulate emotions and

behavior. Even in childhood, provided children are loved and supported,

the brain is shaped by challenges, adversity and failures, as well as

successes. is builds resilience and the capacity to learn and adapt.

Neural pathways in cognition describe the complex interaction

between various brain regions, including the limbic system, the

prefrontal cortex, and the reward system. e limbic system,

traditionally associated with emotions and memory, plays a signicant

role in both conscious and unconscious processing, inuencing

behaviors that range from instinctive to deliberate. e prefrontal

cortex, on the other hand, is linked to reasoning and analytical thinking.

Kahneman’s dual-process theory categorizes these functions into ‘fast’

and ‘slow’ systems, but this dichotomy remains a topic of debate in

cognitive psychology and neuroscience, with emerging research

suggesting more integrated and overlapping roles of these systems (43).

Both pathways are crucial to eective learning in the classroom,

inuencing concentration, focus, memory, and the evaluation of what

is learned. Figure4 illustrates how these neural pathways inuence

classroom learning, using the example of writing a story. e optimal

development of connectivity between these systems is essential for

fostering both quick, intuitive thought and slower, more considered

analysis, contributing to what is termed the ‘optimized brain.’ Creating

conditions that support this connectivity is vital for developing

resilience and adaptive capacities in children, enabling them to

manage adversity more eectively. Furthermore, the ‘reward’ pathways

of the brain, primarily mediated by dopamine produced in the ventral

FIGURE3

Electroencephalogram (EEG) waves in the brain (ﬁgure drawn by Sally Saadi).

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tegmental area (VTA) of the midbrain, connect with the limbic

system, including the nucleus accumbens, amygdala, and

hippocampus. Engaging in pleasurable learning activities, music, and

aerobic exercise, alongside receiving positive feedback and praise,

activates these motivation and reward pathways, driving the formation

of memories, social–emotional learning, and behaviors essential for

eective learning and socialization (5, 6, 10, 44).

e interaction of these brain systems forms a complex and

integrated network essential for learning and behavior regulation. e

reward system, which includes the VTA, nucleus accumbens,

amygdala, hippocampus, hypothalamus, and striatum, plays a crucial

role in regulating motivation toward specic objects, persons, or

actions. Motivation is vital for learning and other functions, as it

drives the engagement and persistence necessary for acquiring new

skills and knowledge. e VTA connects with the limbic system and

nucleus accumbens, which are in turn connected to the amygdala,

hippocampus, hypothalamus, and striatum. ese interconnected

networks form a comprehensive system for behavior regulation,

linking dierent hubs from the prefrontal cortex to the brainstem.

is underscores the importance of a balanced and well-connected

neural network for optimal cognitive and behavioral functioning.

is article reviews the evolution of human brain development

and explains the conditions for optimal brain architecture, plasticity,

and childhood learning. e inuence of environmental factors –

econeurobiology – is discussed in the context of the social

determinants of health and their inuence on intellectual potential.

2 Environmental enrichments at

dierent developmental stages

Research has consistently shown that environmental enrichment

at dierent developmental stages positively inuences brain plasticity,

leading to improvements in health and achievement. Studies reveal

that both physical and social enrichment can cause functional,

structural, and molecular changes in the brain, such as increased

growth factor expression and neurogenesis (45, 46). is is evident in

investigations of early environmental enrichment in rats.

Environmental enrichment in these studies typically involves

providing animals with a stimulating environment that includes a

variety of objects, opportunities for physical activity, and social

interactions. Such enrichment has been shown to inuence brain

development and function by enhancing neuroplasticity and

promoting the expression of growth factors. For instance, these studies

highlight sex-specic responses in oxytocin (OT) and brain-derived

neurotrophic factor (BDNF) expression (45, 46). For instance, while

physical enrichment enhances motor and cognitive functions and

hippocampal BDNF expression in both sexes, combined physical and

social enrichment is particularly benecial for females. is suggests

an OT-based mechanism that selectively stimulates BDNF response

in a region-specic manner, depending on the type of enrichment (45).

Further studies in male mice post-weaning indicate that

environmental enrichment increases social behavior, moderates

stress-related physiological markers, and boosts BDNF levels in the

prefrontal cortex. Conversely, removing female rats from enriched

environments leads to behaviors indicative of psychiatric disorders,

such as increased passive coping and hyperphagia, along with signs of

HPA axis dysregulation (46). ese ndings underscore the potential

of environmental enrichment in early life to aect parental care and

ospring outcomes, possibly extending to transgenerational eects.

However, translating these paradigms from animal models to clinical

settings, such as in stroke patients, requires more alignment for

eective implementation. Environmental enrichment shows promise

for a wide range of neurological and psychiatric conditions (46).

In terms of aging, environmental enrichment (EE), even without

exercise, can prevent cognitive decline and reduce age-related brain

FIGURE4

Connectivity between areas of the brain during a typical classroom task (ﬁgure drawn by Sally Saadi).

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deterioration. is is particularly signicant for populations where

physical exercise is impractical. EE alone has been found to reduce

anxiety, enhance memory, and potentially bemore eective in older

animals. is suggests that EE can mitigate cognitive loss with age

independently of physical activity (47).

Moreover, EE enhances performance in various behavioral tasks,

like spatial memory and anxiety-related behaviors in adult Wistar rats

(48). While EE reduces anxiety and improves spatial memory

accuracy, its impact on attentional tasks is less pronounced. Notably,

EE also aects brain functional networks, promoting more ecient

connectivity (49).

Lastly, a comprehensive review of 375 studies, focusing on 142 of

higher quality, reveals the signicance of non-cognitive skills acquired

early in life on later outcomes. ese skills show consistent eects on

academic achievement, psychosocial, language, and cognitive

outcomes. e ndings highlight the need for better study design and

reporting, especially in randomized controlled trials and observational

studies. Interventions targeting the development of non-cognitive

skills could be particularly benecial for disadvantaged children,

suggesting a broader societal impact (49). Altogether, these ndings

show how dramatic the inuence exerted by the environment can

beon brain plasticity. Studies using the EE paradigms have indicated

several molecular mechanisms that might emerge as possible ways of

accession for a successful treatment of neuropathological conditions

aecting the juvenile and adult CNS (50). ese studies also reveal

how EE inuence cognitive development as everyday experiences can

potentially enhance or inhibit cognitive plasticity and therefore the

ability to learn (51).

In summary, environmental enrichment at various developmental

stages oers profound benets for brain plasticity, ultimately

enhancing achievement and health outcomes.

3 The negative impact of trauma and

toxic stress on plasticity

Toxic stress, as observed in children’s brains, is characterized by

an adverse response to early life challenges and can exert far-reaching

negative eects on physical, psychological, and behavioral well-being

(52). is type of stress can result in persistent alterations to the brain’s

stress response systems, which may compromise an individual’s ability

to manage stress and regulate emotions in the future (53). e

implications of toxic stress extend to epigenetic modications,

potentially leading to enduring alterations in gene expression and

subsequent child development (54). Furthermore, the family setting

plays a critical role, with the implementation of physical punishment

by parents being identied as a signicant source of toxic stress that

can impact brain architecture and function (55).

Adverse childhood experiences (ACEs) – that generate toxic stress

– are dened as traumatic events that occur before the age of 18 years

that can have major consequences for behavioral, cognitive, and

physiological development aecting one’s life-course health trajectory

(56) ACEs can include maltreatment, severe household dysfunctions,

the loss of one or both parents for any reason, and other events such

as severe bullying, natural disasters, extreme poverty, or exposure to

warfare. ese traumatic experiences elicit strong physiological stress

responses that prepare the body to face dangers or hazards,

conditioning it into a ght, ight, or freeze mode (57).

Emotional trauma can profoundly aect brain plasticity by altering

neuronal circuits and synaptic connections (58). e stress induced by

trauma typically activates the neural systems related to attention and

memory, which leads to a temporary increase in synaptic plasticity

within the hippocampus (59). Initially, this response may enhance

memory, but over time, the hippocampus oen becomes less

responsive to new excitatory plastic changes (60). e enduring nature

of traumatic memories, particularly those resistant to extinction that

are characteristic of posttraumatic stress disorder (PTSD), is likely a

consequence of these changes in plasticity (61). Moreover, chronic

exposure to ACEs have been linked to inammation in childhood,

adolescence, and across adulthood (62). Chronic inammation has

been established as an overlying mechanism in which the immune

system contributes to the development of later disease (63). Cytokines,

which coordinate inammatory processes, are oen used as biomarkers

to assess levels of inammation. Children who were exposed to toxic

stress between the ages of 6–8 years were found to have higher levels of

C-Reactive Protein (CRP) and Interleukin-6 (IL-6) at 10 years. In

addition, ACEs prior to 9 years were associated with higher levels of

CRP at age 15 (62). e negative impact that chronic inammation has

in a developing brain, particularly during the maturation of cognitive

and emotional functioning, may beconsidered an important factor for

the presentation of disease or psychopathology later in life. It has been

demonstrated that exposure to psychosocial deprivation early in

childhood, is associated with smaller gray and white matter volume

and global reductions in cortical thickness (64). Moreover, these

structural abnormalities were correlated with impaired cognitive

functioning and increased development of psychopathology (65, 66).

However, when children are removed from their adverse environment

– removed from toxic stress – by placing them in a safe and caring

environment, these changes reverse, predominantly in the lateral and

medial prefrontal cortex and white matter tracts that connect the

prefrontal and parietal cortex (67), which are cortical structures

associated with cognition and emotional regulation.

e detrimental impacts of prolonged trauma and stress on brain

plasticity are well-established (68–70). Chronic stress can lead to

reduced metabolism and synaptic density in the hippocampus and

prefrontal cortex, which then necessitates behavioral adaptations (71).

Additionally, chronic stress can lead to systemic changes that

contribute to allostatic load, but the brain retains a degree of resilience

and can react positively to interventions aimed at promoting plasticity

and thus aid recovery (72). Research also shows that acute stress can

modify inhibitory neurotransmitters, such as gamma-aminobutyric

acid (GABA), inuencing the stress axis and potentially aecting

plasticity (72).

In conclusion, understanding the eects of trauma and stress on

neural plasticity is essential for developing therapeutic strategies.

ese strategies not only aim to foster resilience but also address the

persistent adverse eects of stress, thereby contributing to healthier

brain function and mitigating the long-term consequences of stress-

related disorders.

3.1 The catastrophic eects of violent

conﬂicts on econeurobiology

War and violent conicts oen result in devastating consequences,

including loss of life, displacement of civilians, destruction of

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infrastructure, and long-lasting socio-economic impacts.

Communities endure trauma, and the conict can exacerbate existing

political, ethnic, or religious tensions, making post-war recovery

challenging. Humanitarian crises may arise with limited access to

basic necessities, hindering the overall development of the aected

regions. Regrettably, war and violent conicts disproportionally aects

the most vulnerable populations, children, women, and the older

adult, who in addition to beexposed to death, injury, disabilities,

illness, and rape, they also suer from intense and continuous

psychological suering. Children are exposed to situations of terror

and horror that have detrimental eects on neural development and

may leave enduring cognitive decits and psychopathology such as

posttraumatic stress disorder (PTSD), depression, and anxiety.

Furthermore, these negative eects may beprolonged by exposures to

further privations and violence in refugee situations (73).

Although the ideal action would be the complete removal of

children from war, and to place them in a supportive and caring

environment, the socio-political realities, frequently prevent any

moral and/or humanitarian eort to achieve this goal. erefore,

humanitarian organizations are le with limited option to mitigate the

terrible consequences of these violent conicts have on children. e

destruction of the econeurobiology must beconsidered a war crime,

as the devastating eects on neural development will adversely aect

the life trajectory of those children who survive and prevent them to

reach their full potential.

4 Education as a determinant of

health and social mobility

e adolescent brain becomes capable of performing more

complex functions but loses adaptability in terms of lifestyle change

or behavior. is decline in brain plasticity emphasizes the importance

of investment in positive learning environments in early childhood.

Risk factors for poor academic attainment accumulate well before a

child begins school (5, 7). An early nurturing environment where

children are exposed to positive interactions and encouraged to learn

determine literacy, numeracy, motor skill, cognition, and emotional

development in school (5, 7, 74). By the age of 3 years, the children of

high-income professionals have been found to have twice the

vocabulary of children from low-income families (71). One dollar

invested in early childhood yields a benet of $ 16.14 (Figure5), while

an investment of $ 1in those over 21 years of age yields only $ 4.10

(5, 8, 23).

is paper acknowledges the signicant inuence of country and

culture on educational theory and practice, particularly in the sections

on early childhood programs, elementary curriculum, and STEAM

education. e costs and benets of early childhood programs

presented in Figure5B were estimated primarily for the UnitedStates.

However, it is crucial to recognize that institutional and economic

circumstances vary widely between nations, impacting the

applicability and eectiveness of these programs.

Motivation and skill for those engaging with young learners in

school are essential. Schools require investment and teachers require

training and support. Class sizes should besmaller, and lessons should

engage each child, re the imagination, and allow them to explore

what there is to learn about the world within a safe and supportive

environment. Extracurricular education and activity are as important

as classroom learning (75). Integrating sport, music, art, and activity

into classroom lessons and eectively timing lessons, breaks and the

school day add to the quality of education, how a child learns, what

they learn, what they remember, and how they learn to learn (76–78).

While standardized tests of knowledge acquisition and critical

thinking (based on Bloom’s taxonomy of critical thinking, which

categorizes cognitive skills from basic recall of facts to higher-order

thinking skills such as analysis and evaluation) are used to assess the

attainment of educational milestones, class attendance, participation,

levels of substance abuse, crime, teenage pregnancy, and child

employment are important markers of the eects of education as a

determinant of health, future employment, economic security, and

social mobility. Bloom’s taxonomy classies educational learning

objectives into six hierarchical levels: knowledge, comprehension,

application, analysis, synthesis, and evaluation. is framework helps

educators structure and evaluate the eectiveness of their teaching by

focusing on the development of higher-order cognitive skills (77–79).

Poorly performing schools are in themselves a determinant of the

failure of a child to meet his or her educational potential and life goals.

Funding educational programs that target early school-age children is

important but, in reality, the education of the poorest children in

society remains inadequately funded and badly managed. Addressing

the determinants of poverty are a priority in improving education

from early childhood (80). Education remains the single most

important factor in liing children out of poverty (81).

5 Econeurobiology: key factors that

inﬂuence the developing brain

A child’s environment and the social determinants of health

inuence the biological mechanisms that shape an individual’s

cognitive, social, psychological and behavioral development (23).

5.1 The nurturing and loving environment

Nurturing, loving, supportive and caring environments are powerful

factors in child development and positive neuroplasticity (82–86). e

‘serve and return’ reciprocal interaction between children and their

parents has been shown to beeective in “brain building” as early as

infancy. e model, developed by Harvard University (87), uses a tennis

analogy where an infant serves (focuses his or her attention on an object),

and the parent returns the serve (sharing the child’s attention and

building on this). Learning continues in a supportive and encouraging

environment as the child plays, develops language skills, and gains an

understanding of the context and meaning of the world around them. In

the absence of responsive caregiving — or if responses are unreliable or

inappropriate — brain architecture does not develop as expected. It is

easier to form strong neural networks in early childhood than it is to

intervene or “x” them later (88, 89). Adverse Childhood Experiences

(ACE) and “toxic stress” such as exposure to domestic violence, emotional

abuse, physical abuse, sexual abuse, emotional neglect, and physical

neglect aect physical and mental health, and substantially aect the

ability to learn, school attendance, and academic attainment (83, 90, 91).

Toxic stress is cumulative and results in uncontrolled pruning processes,

especially in the hippocampus, neuron loss, impaired synapses, damage

to neural connectivity, and poor development of the prefrontal area of the

brain responsible for thinking, problem-solving, the control of behavior

(Figure6) (83, 86, 88). is is negative neuroplasticity (23, 86).

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e eects on the child increase the longer exposure to the toxic

environment is allowed to continue, and the risk of long-term health

complications increases as the ACE score increases. For example,

exposure of children to their mother’s physical abuse and their own

experience of physical and emotional abuse adds up to an ACE score

of 3. is is higher than an individual with an ACE score of 0 or 1.

ere is a direct link between the ACE score and toxic stress in

children, with a signicant increase in the risk of long-term physical

and mental health complications (93). e eects of fear and anxiety

on cognition and memory (especially declarative memory that has an

emotional impact) may bemediated through glucocorticoid eects on

the hippocampus (94). Stress hormones and catecholamines are

implicated in the consolidation of emotion-laden memories through

arousal-induced activation of noradrenergic mechanisms within the

amygdala (95). Children may display obvious signs of trauma in the

classroom such as aggression or falling asleep in class; but more subtle

signs such as the inability to concentrate or an unwillingness to learn

are less easily discerned and less oen attributed to abuse. Investment

in small class sizes and real facetime with individual pupils are

essential to identifying the problems that aect a child’s performance

in class. Tackling environments of toxic stress and child protection are

global health and education imperatives (96–98).

ere is a positive correlation between clean, well-maintained,

calm, ordered school environments and academic performance

FIGURE5

(A) Education as a sustainable development goal. Adapted with permission from the illustration: “2030 Sustainable Development Goals.” © Courtesy of

the United Nations (1). (B) The return on investment of early childhood education. Adapted with permission from the illustration: “Cost/Beneﬁt for Two

FIGURE6

The eect of toxic stress on the healthy brain. The PET scan of the brain activity of a normal, healthy brain shows regions of high activity (red) and low

activity (blue and black). In the abused brain under toxic stress, there is a signiﬁcant decrease in activity in the temporal lobes, which regulate emotions.

Adapted with permission from Chungani (92).

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(99–101). Cognitive performance is reduced in ‘busy’ (distracting)

visual environments compared to ‘non-busy’ visual environments (99).

Poor lighting in classrooms aects both children’s health and their

ability to learn (100). e availability of greenspace in the learning

environment is positively associated with cognitive performance.

Learning outdoors, and even watching nature from the classroom, are

associated with a decrease in heart rate and cortisol levels (101).

erefore, a pedagogy of love rooted in empathy for oneself, others, and

nature is essential for a child’s development, as well as for the integrity,

well-being, social harmony, and economic prosperity of society.

5.2 Nutrition and a healthy diet

The infant gut microbiome (the genetic material of gut

microorganisms) influences neurodevelopment from birth via

the gut-brain axis (Figure7). The gut-brain axis involves the

vagus nerve, immune system, hypothalamic–pituitary axis,

tryptophan metabolism, and synthesis of neuroactive peptides,

metabolites, short-chain fatty acids and neurotransmitters (102–

111). Complete bacterial colonization is achieved within the first

3 years of life and is affected by the child’s diet, the existence of

gastrointestinal disease, and exposure to antibiotics (112). A

crucial function is the homeostatic mechanism of gut

permeability and protection from enteric pathogens. Diarrheal

diseases alone result in under-5-year mortality of up20%, and

episodes of diarrhea (three or more unformed stools per day) in

the first 2 years of life may result in malnutrition-related cognitive

deficits before children begin school (113).

e eects of malnutrition on brain development are profound.

Chronic undernutrition and poverty in childhood are primarily

measured by stunting (linear growth retardation and cumulative

growth decit). Stunted children have impaired cognition, learning,

and motor function that aect school attendance, classroom

participation, and learning and educational attainment (114). Fatty

acids, choline, iron, zinc, cholesterol, phospholipids, and

sphingomyelin play essential roles in myelination – key to white

matter and cortical development (115, 116). Up to one-third of

preschool children worldwide have vitamin A deciency, 1% of whom

develop night blindness (115). Nutritional inputs from infancy to

school age (including breast-feeding, iron supplementation, iodine

fortication, zinc, micronutrient and vitamin supplementation, and

protein-energy supplementation) in community-based programs have

had some success. e role school meals play in the nutrition of school

age children is crucial to cognitive development and the quality of

learning in schools- Learning Adjusted Years of Schooling (LAYS)

(116–118). e cost of providing school meals for approximately 70

million vulnerable children is an average of $ 64 per child per

year (119).

5.3 Physical activity and socialization

Development of the brain is aected by movement and exercise

(77, 120–122). Eortless movement for only 10 min has been shown

to improve the ability to remember and concentrate at all ages- from

kindergarten to university (77). Ten minute breaks in class for gentle

exercise may signicantly improve classroom learning and

performance in examinations, and are a relatively low-cost and easy

intervention in the school timetable (77). Improvement in key

educational competencies, especially higher orders of cognition in

Bloom’s taxonomy of critical thinking, has been demonstrated aer

FIGURE7

A healthy gut and the gut-brain axis (ﬁgure drawn by Roaa Mohamed).

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small intervals of aerobic exercise (77, 120, 121). e mechanism

may be related to the relationship between movement and the

secretion of BDNF. Increased BDNF secretion increases the

production of mRNA which produces neurotropin, proteins, and

neurotransmitters, such as dopamine, which increase anterior

hippocampal volume, improve mood, motivate learning, and

improve spatial memory (122, 123).

Physical activity improves cognition, increases brain volume in

children with cerebral palsy, and improves phonemic skills (122). In

students with visual impairment, the relationship between cognitive

function and physical activity, especially in adolescents with

disabilities, suggests that moderate-intensity exercise is important for

brain plasticity at this age (122). Exercise may be important in

developing resilience and dealing with stress (124, 125). Children who

exercise as a means of coping with pressure at school should have

access to sporting facilities in school that are safe, supervised, and

accessible aer the school day.

Prolonged periods of sitting are associated with the digital age.

While unhealthy in terms of a lack of physical activity, they are also

associated with other dangers, detailed discussion of which is beyond

the scope of this article. Violent video game content has been shown

to increase aggression, violence, depression, lack of empathy and the

spectator phenomenon (126, 127). Prolonged sitting, especially in

front of LED screens, leads to fatigue, disrupts sleep, biological

rhythms, and reduces cognitive function (128–132). An over-reliance

on screen-based learning in the classroom at the expense of writing,

drawing, hands-on tasks, outdoor learning, play, and movement,

especially where there is physical and social interaction between the

teacher and pupils and among the pupils, is to bediscouraged. Screen

time is recommended to belimited to 90 min in total during the

school day (133).

5.4 Music

e positive impact of music on cognitive development,

including fetal development, has been extensively studied (78, 134).

Listening to Mozart has been found to signicantly help mothers

cope with stress and improve their temperament (134–138) which, in

turn, may positively impact the child’s home environment. Music also

encourages calm and restful sleep (134, 136, 139). Music is an

important stimulus for the growth of functional neural networks

throughout the brain in the rst 3 years of childhood (6, 134–140).

e eect on brain development remains signicant in school-age

children and is, therefore, of considerable interest in improving

learning conditions in the classroom, with evidence of improvement

in spatial intelligence of up to 43% among students learning to play

the piano versus 11% among students studying computer science

without music (136). Music also impacts intellectual development, in

particular the ability to listen to and absorb language (138). ere is

a debate as to whether these eects are only in the short term (with

no lasting eect on intelligence) but positive eects on academic

achievement associated with music may beseen in the teenage years

(134, 137, 139). Relatively short periods of music training have strong

implications on brain plasticity (141) and have strong implications

for promoting the development of music-based correction strategies

for children with language-based learning disabilities (142). Further,

training children in music leads to a long-term improvement in

visual spatial, verbal, and mathematical performance (143). Music

skills also enhance language development, literacy, literature,

intelligence metrics, creativity, ne motor coordination,

concentration, self-condence, emotional sensitivity, social skills,

teamwork, self-discipline, general achievement, and relaxation. Early

exposure to music improves personal and social development within

the context of a fun and rewarding experience (144, 145). e eects

on the limbic system of pleasure and enjoyment are important

motivators of learning. Playing music to children for 10 min has been

shown to increase gamma waves involved in thought processes and

alpha waves representing a feeling of calm (78) (Figure8). At least

6 months of musical training in primary school is required to

signicantly improve behavior and inuence the development of

neural processes reected in specic brain wave patterns (146, 147).

5.5 Sleep

Sleep cycles begin in the womb at 23 weeks of gestation. In infancy,

while the number of new neural connections formed is very high,

more hours of sleep are needed for pruning and consolidation

processes by which recent memories become crystallized into long-

term memories (148–151) (Figure9). By school age, the establishment

of a sleep schedule becomes important. Rapid eye movement (REM)

sleep is essential for the processes of short-term memory (148, 152–

154). Sleep that includes REM, as well as non-REM states, is crucial to

synaptic development, the support of cognitive functions, memory

and plasticity (memory encoding, unication and reunion) (155–157).

e process of pruning during sleep converts short-term to long-term

memories. Pruning involves the clearance of amyloid, an insoluble

protein precipitate, formed aer the development of synapses by glial

cells (148, 149). e restorative function of sleep may result from the

removal of potentially neurotoxic waste products that accumulate in

the central nervous system (158).

Non-REM sleep may beseen on electroencephalogram in the

form of sleep spindles and K-complexes. Functional magnetic

resonance imaging shows thalamic and limbic system activity during

sleep, indicating their role in memory consolidation. Variations in

brain activity during sleep are associated with uctuations in cerebral

oxygen demand and perfusion (159, 160).

Sleep deprivation reduces alertness, reduces the motivation to

learn, limits concentration and memory formation, and aects mood

(161); indeed, sometimes children fall asleep in class. Scheduled naps

during the school day in kindergarten have been shown to enhance

cognition and learning (162). Keeping children awake and attentive in

class is a teaching challenge at any age, but shorter lessons, interesting

and stimulating learning activities, inclusion and active participation,

and seating struggling children closer to the teacher (or in the teacher’s

eyeline) are key strategies to improve learning. e identication of

problems at home, anxiety or night terrors that may result in sleep

deprivation is crucial.

Melatonin is secreted by the pineal gland in the evening and night.

Its secretion is stimulated by darkness and inhibited by light along the

retino-hypothalamic tract (Figure9). Infants have the highest levels,

and, as a child grows, melatonin levels reduce, and secretion becomes

delayed (163). Melatonin may promote deeper sleep, leading to better

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memory consolidation (164). Metabolites of melatonin are involved

in DNA repair and free radical scavenging (165, 166). Supplementation

may beeective for children with sleep disorders.

5.6 Brain connectivity – Gardner’s theory

of multiple intelligences

Intellectual potential is determined by the optimization of

connections in the brain and the activation of multiple areas of the

brain. Gardner’s theory of multiple intelligences sheds light on the

importance of connectivity between areas of the brain and the

importance of connectivity in learning (Figure10).

While Gardner describes the existence of multiple intelligences

which include verbal and linguistic, logical and mathematical, visual

and spatial, musical, naturalist, body kinesthetic, interpersonal, and

intrapersonal, it is crucial to understand that these diverse abilities

contribute to the creation of a unied sense of self (167, 168). Gardner

demonstrated that when one area of the brain is activated, another

area of the brain is aected. Improvement in one particular area of

the brain that expresses a particular intelligence aects the other

intelligences, i.e., logical-mathematical intelligence can beimproved

through musical intelligence (169–171). e synthesis of various

brain systems, such as the frontoparietal network, limbic system,

default mode network, and attentional networks, results in the

cohesive perception of being ‘one person.’ is unied experience is

FIGURE8

(A) Levels of cognition and academic performance with and without music (scale from 0–100) (78). (B) Changes in brain activity when listening to

music (absolute power from alpha and gamma band) (78). Adapted with permission from (78), licensed under CC BY.

FIGURE9

(A) Recommended hours of sleep based on childhood age (Data Source: 151). (B) Mechanism of inhibition of melatonin secretion from the pineal gland

(ﬁgure drawn by Razan Bakir).

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similar to how dierent chemical senses (olfaction, taste, trigeminal

sensitivity) collectively create the perception of the ‘aroma’ of food,

where the contribution of each sense is indistinguishable from the

whole percept. erefore, while Gardner’s model is useful for

organizing educational activities (e.g., music, physical education,

literature), it is essential to balance these activities to foster the

development of a harmonious and integrated individual.

6 Using econeurobiology to tackle the

social determinants of health

We propose a model that describes the impact of a child’s ecological

environment on neurological function – the ‘econeurobiology’ of brain

development – Figure 11. e model refers to the ecological

environment in which a child grows and the factors that shape cognition

FIGURE10

Neural networking (brain connectivity) illustrated by Gardner’s multiple intelligences in the classroom.

FIGURE11

The econeurobiology of the brain for healthy child development.

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and social and emotional learning in early childhood. e model should

beconsidered in tackling the social determinants of health, education,

and child development, and creating eective and supportive

environments for learning toward realization of the intellectual potential

of individuals and the human capital of communities. Education lis

children out of poverty – “e ght against poverty starts with quality

education for every child” (172). Music, exercise, rest and quality sleep,

healthy food, and calm, ordered and nurturing environments are

important in the preschool and elementary school curriculum to foster

critical thinking, socialization and behavior that builds human capital.

7 Application of Gardner’s intelligence

model, economic biology strategies,

and connection to the environment of

school curriculum

It is important to consider that the application of Gardner’s

intelligence model and economic biology strategies may vary

signicantly across dierent cultural and institutional contexts. For

example, educational policies and economic resources in the

United States dier greatly from those in developing countries.

erefore, while our model provides a general framework, educators

and policymakers should adapt these strategies to t the specic needs

and circumstances of their countries. is includes acknowledging the

diverse educational challenges and opportunities that arise from

varying economic, social, and cultural backgrounds.

Integrating Gardner’s Multiple Intelligences model into educational

curricula has been shown to eectively cater to diverse student learning

styles. By acknowledging students’ dominant intelligences, educators

can apply Gardner’s theory across all learning types, not just those

traditionally emphasized, such as verbal–linguistic and logical-

mathematical intelligences (173). is approach facilitates an

all-encompassing educational experience that acknowledges the

signicance of teachers understanding and analyzing the intelligences

their students possess. e aim is to enhance learning outcomes by

adopting a Multiple Intelligences-based approach tailored to each child’s

unique abilities, thus improving learning achievement (173).

e educational impact of Gardner’s theory is also apparent in its

ability to enrich student learning experiences at the upper elementary

level (174). Analysis of its application revealed improvements in

student capabilities, enabling deeper analysis and connection with

previous knowledge — essential for constructing meaningful learning.

By addressing the diverse learning styles and preferences, the use of

multiple intelligences in the classroom promotes a more inclusive and

productive educational environment (174).

When teaching strategies are tailored to the assessed multiple

intelligences of students, educators are better equipped to meet the diverse

needs of their classrooms, which, in turn, promotes greater academic

engagement (175). Students have shown enhanced involvement and

motivation when their intellectual strengths are the focus of instruction.

is tailored approach not only facilitates comprehension but can also

positively inuence academic performance. Further studies examining

the correlation between students’ achievements and their predominant

intelligences could lend more credibility to these ndings (175).

In summary, the integration of Gardner’s theory into educational

practices allows for a nuanced approach to teaching. By adopting

strategies sensitive to individual dierences, educators can enhance

student understanding and performance, particularly in complex

areas such as physics (176).

How can econeurobiology and what we know about the

psychology of cognition and learning beapplied in the classroom to

improve educational attainment and foster behaviors that shape

healthy communities? Addressing investment in education and

teaching is crucial. Under-resourced and overworked teachers would

struggle to motivate and stimulate children using the best of learning

and psychological strategies. Education should beseen within the

context of community building and a global strategy toward

prosperous and cohesive societies. Investment in teaching should

be commensurate with the importance of successful child

development. e importance of quality teaching and investment in

school in early and mid-childhood for all children should

beemphasized over the prevailing focus on higher education for the

select few. Education strategies must identify and prioritize the social

determinants of learning in children and optimize learning in early

childhood when brain plasticity is maximal. Creating a positive and

safe environment in school and addressing problems at home are

fundamental. Healthy, aordable school meals that address genuine

nutrition needs (vitamin A and iodine deciency, for example) should

beavailable to children who are malnourished.

Ten minutes of relaxing music or aerobic exercise before class can

prime children for their lessons (Figure12). In class, four strategies

have been found to stimulate learning and promote memory

formation (177, 178): (1) retrieval practice (questioning pupils to elicit

their recall and retrieval of information rather than lecturing to

passive listeners); (2) feedback (pupils become self-aware of what they

know and understand and the gaps in their learning). is stimulates

and focuses new learning and increases depth of understanding; (3)

spaced-practice (knowledge and understanding consolidated in stages

over time so that pupils can process, reorganize and apply what they

have learned). is facilitates the formation of lasting memories; (4)

interleaving (acquiring new information through a variety of teaching

and learning methods – a mix of skills that stimulate brain connectivity

and memory formation).

8 The importance of science,

technology, engineering, art and

mathematics

STEAM education plays a vital role in preparing students for the

future, but its implementation can be inuenced by cultural and

economic factors. For instance, the emphasis on dierent subjects

within STEAM may vary depending on national priorities and

resources. In some countries, there might be a greater focus on

technology and engineering due to industrial needs, while others

might prioritize science and mathematics based on educational

traditions. Additionally, the availability of resources for hands-on

learning and extracurricular activities can dier, aecting the overall

eectiveness of STEAM programs. By considering these cultural and

economic variations, wecan better tailor STEAM education to meet

the unique needs of students globally.

Children have fallen behind in science, technology, engineering,

art and mathematics (STEAM) education, in reading, and in literacy

(179, 180). Wenow have a reduced adult STEAM workforce, reduced

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adult literacy and reduced engagement with book reading (181).

Literacy, science, and mathematical skills are essential to

industrialization, a productive workforce, and the economic prosperity

of nations. Children from vulnerable backgrounds are particularly

disadvantaged and less likely to pursue STEAM subjects in higher

education (182). Yet, eective teaching of STEAM subjects can

stimulate and re the imagination of children. ese subjects lend

themselves to practical teaching strategies that translate theories into

tangible and real experiments, drama classes, drawing, and model-

making that are fun and engaging – enhancing brain connectivity for

optimal learning. ey introduce real-world examples into the

classroom where the relevance of STEAM concepts are obvious and

learning is translational and modular. eoretical concepts that are

time-consuming, boring, laborious and dicult to explain become

practical problem-solving exercises, explorations and analyses of

everyday (real-life) activities that interest motivate and stimulate

learning – augmenting connectivity between cortical and social and

emotional learning centers from an early age.

Scientic and technological literacy are the basic tools and

strategies employed in research and discovery. ey develop skills of

critical thinking and enable students to generate new knowledge.

Education of STEAM subjects is crucial to the overall development of

the brain architecture, specically in the prefrontal cortices and the

strengthening of top-down self-regulation pathways. rough STEAM

education, students learn how to think, rather than being taught what

to think- promoting independent and analytical thinking.

9 Conclusion

Brain connectivity is engaged at all levels of Bloom’s taxonomy of

critical thinking, both simultaneously and cumulatively. Active

inquiry-based learning strategies surpass traditional passive didactic

methods in enhancing brain connectivity, leading to more eective

educational outcomes. Contextual learning strategies, particularly

those incorporating real-world examples and outdoor experiences,

serve to bolster cognition and memory. ey add relevance and a

sense of achievement, making learning more rewarding.

Competency-based educational strategies test the application of

knowledge, skills, and attitudes, providing critical feedback for

teachers and learners. is feedback catalyzes the acquisition of new

knowledge and the reinforcement of successful behavioral models,

which then evolve into essential life skills. rough such strategies,

children learn the meta-skill of learning itself—a fundamental tool for

lifelong education.

e relevance of school curricula to the communities they serve is

paramount to ensuring that children remain engaged in their education.

Extracurricular activities should complement and extend classroom

learning, incorporating low-cost sports and team-building exercises into

a broader curriculum framework. Opportunities such as sporting events,

drama clubs, choirs, bands, debating societies, school journals, and

community service projects should not be exclusive to well-funded

schools. Instead, they should be leveraged to address educational

determinants and meet community needs, especially in underprivileged

and unstable environments (183–188).

We call upon policymakers and international institutions to

recognize the critical role of designing supportive econeurobiological

environments within communities and schools. Safe and nurturing

settings enable children to acquire skills essential for building healthy,

caring, and prosperous societies. Wealso call for the immediate action

to remove children from war and violent conicts, and to establish

eective strategies to mitigate the negative eects of war by

re-establishing healthy and functional econeurobiology.

In summary, the convergence of econeurobiology and educational

strategy presents a pivotal opportunity for transformation. By

leveraging insights into brain development within educational and

community contexts, wecan cultivate environments that not only

FIGURE12

Optimizing the elementary school schedule – a typical day for children aged 5 and 10 years (a combination of stimulation and relaxation to optimize

learning).

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Frontiers in Public Health 16 frontiersin.org

bolster learning and cognitive growth but also contribute to forging

more resilient, healthier, and united societies.

Author contributions

RM: Conceptualization, Writing – original dra. LM-Q:

Conceptualization, Writing – original dra. RF: Writing – original dra.

SS: Writing – original dra. DB: Writing – original dra. SC: Writing –

original dra. LM: Writing – original dra. NS: Writing – original dra.

RY: Writing – original dra. YZ: Writing – original dra. IW: Writing –

original dra. SB: Conceptualization, Writing – original dra.

Funding

e author(s) declare that nancial support was received for the

research, authorship, and/or publication of this article. e research

was supported by Oranim Academic College and the Ministry of

Regional Cooperation, Israel.

Acknowledgments

e authors wish to thank Sally Saadi, Razan Bakir and Roaa

Mohamed for their assistance in drawing the gures.

Conﬂict of interest

e authors declare that the research was conducted in the

absence of any commercial or nancial relationships that could

beconstrued as a potential conict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors

and do not necessarily represent those of their aliated organizations,

or those of the publisher, the editors and the reviewers. Any product

that may beevaluated in this article, or claim that may bemade by its

manufacturer, is not guaranteed or endorsed by the publisher.

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How understanding and strengthening brain networks can contribute to elementary education

Article

Full-text available

Jun 2023

Imaging the human brain during the last 35 years offers potential for improving education. What is needed is knowledge on the part of educators of all types of how this potential can be realized in practical terms. This paper briefly reviews the current level of understanding of brain networks that underlie aspects of elementary education and its preparation for later learning. This includes the acquisition of reading, writing and number processing, improving attention and increasing the motivation to learn. This knowledge can enhance assessment devices, improve child behavior and motivation and lead to immediate and lasting improvements in educational systems.

Protocol for a prospective multicenter longitudinal randomized controlled trial (CALIN) of sensory-tonic stimulation to foster parent child interactions and social cognition in very premature infants

Article

Full-text available

Jan 2023

Introduction Premature birth is associated with long-term somatic and neurological disorders, including cognitive, social and behavioral impairments. Moreover, the mothers of infants born preterm exhibit a higher prevalence of anxiety and depressive symptoms after birth. Early rehabilitation, developmental care, and parenting support have already been shown to have a positive impact on neurological outcome. However, no randomized controlled study has so far assessed the effects on parenting and long-term neurological outcomes of proprioceptive stimulation to trigger positive brain plasticity in very preterm babies. The CALIN project will therefore investigate the impact of sensory-tonic stimulation (STS) of extremely preterm infants by their parents on child parent interactions, infants' morphological and functional brain development and subsequent cognition (including social cognition), and parents' anxiety and depressive symptoms in the postpartum period. Methods and analysis Infants born between 25 and 32 weeks of gestation will be randomly assigned to the “STS + Kangaroo care” or “Kangaroo care” group. The primary endpoint, child and parent interactions, will be rated at 12 months corrected age using the Coding Interactive Behavior system. Secondary endpoints include: 1/functional and anatomical brain maturation sequentially assessed during neonatal hospitalization using electroencephalogram (EEG), amplitude-integrated EEG (aEEG), cranial ultrasound and MRI performed at term-corrected age, 2/social and cognitive outcomes assessed at 15 months, 2, 4 and 6 years, and 3/parents' anxiety and depressive symptoms assessed at 7 ± 1 weeks after birth, using dedicated questionnaires. Ethics and dissemination This study was approved by the French Ethics Committee for the Protection of Persons on 18 October 2021. It is registered with the French National Agency for the Safety of Medicines and Health Products (ANSM; no. 2020-A00382–37). The registry number on ClinicalTrials.gov is NCT04380051.

Mapping gene by early life stress interactions on child subcortical brain structures: A genome‐wide prospective study

Article

Full-text available

Nov 2022

Background: Although it is well-established that both genetics and the environment influence brain development, they are typically examined separately. Here, we aimed to prospectively investigate the interactive effects of genetic variants-from a genome-wide approach-and early life stress (ELS) on child subcortical brain structures, and their association with subsequent mental health problems. Method: Primary analyses were conducted using data from the Generation R Study (N = 2257), including genotype and cumulative prenatal and postnatal ELS scores (encompassing life events, contextual risk, parental risk, interpersonal risk, direct victimisation). Neuroimaging data were collected at age 10 years, including intracranial and subcortical brain volumes (accumbens, amygdala, caudate, hippocampus, pallidum, putamen, thalamus). Genome-wide association and genome-wide-by-environment interaction analyses (GWEIS, run separately for prenatal/postnatal ELS) were conducted for eight brain outcomes (i.e., 24 genome-wide analyses) in the Generation R Study (discovery). Polygenic scores (PGS) using the resulting weights were calculated in an independent (target) cohort (adolescent brain cognitive development Study; N = 10,751), to validate associations with corresponding subcortical volumes and examine links to later mother-reported internalising and externalising problems. Results: One GWEIS-prenatal stress locus was associated with caudate volume (rs139505895, mapping onto PRSS12 and NDST3) and two GWEIS-postnatal stress loci with the accumbens (rs2397823 and rs3130008, mapping onto CUTA, SYNGAP1, and TABP). Functional annotation revealed that these genes play a role in neuronal plasticity and synaptic function, and have been implicated in neuro-developmental phenotypes, for example, intellectual disability, autism, and schizophrenia. None of these associations survived a more stringent correction for multiple testing across all analysis sets. In the validation sample, all PGSgenotype were associated with their respective brain volumes, but no PGSGxE associated with any subcortical volume. None of the PGS associated with internalising or externalising problems. Conclusions: This study lends novel suggestive insights into gene-environment interplay on the developing brain as well as pointing to promising candidate loci for future replication and mechanistic studies.

Multiple intelligences and its pedagogical impact on the teaching-learning process

Article

Full-text available

Feb 2021

Currently, society is in constant change, education must move to this innovative model and the educational community must be part of it, taking into account the diversity of learning that they can exist within a classroom. This research seeks to analyze the pedagogical impact of Gardner's theory of multiple intelligences, in the teaching and learning process of students of the upper elementary school sublevel. The exploratory and bibliographic method was used, which allowed to obtain results from its application, managing to enhance the abilities and skills of the students, in order to be able to carry out an analysis and associate previous knowledge, for the construction of meaningful learning.

Decomposing the role of alpha oscillations during brain maturation

Article

Full-text available

Aug 2022
eLife

Childhood and adolescence are critical stages of the human lifespan, in which fundamental neural reorganizational processes take place. A substantial body of literature investigated accompanying neurophysiological changes, focusing on the most dominant feature of the human EEG signal: the alpha oscillation. Recent developments in EEG signal-processing show that conventional measures of alpha power are confounded by various factors and need to be decomposed into periodic and aperiodic components, which represent distinct underlying brain mechanisms. It is therefore unclear how each part of the signal changes during brain maturation. Using multivariate Bayesian generalized linear models, we examined aperiodic and periodic parameters of alpha activity in the largest openly available pediatric dataset (N=2529, age 5-22 years) and replicated these findings in a preregistered analysis of an independent validation sample (N=369, age 6-22 years). First, the welldocumented age-related decrease in total alpha power was replicated. However, when controlling for the aperiodic signal component, our findings provided strong evidence for an age-related increase in the aperiodic-adjusted alpha power. As reported in previous studies, also relative alpha power revealed a maturational increase, yet indicating an underestimation of the underlying relationship between periodic alpha power and brain maturation. The aperiodic intercept and slope decreased with increasing age and were highly correlated with total alpha power. Consequently, earlier interpretations on age-related changes of total alpha power need to be reconsidered, as elimination of active synapses rather links to decreases in the aperiodic intercept. Instead, analyses of diffusion tensor imaging data indicate that the maturational increase in aperiodic-adjusted alpha power is related to increased thalamocortical connectivity. Functionally, our results suggest that increased thalamic control of cortical alpha power is linked to improved attentional performance during brain maturation.

A Prospective Study of the Impact of Severe Childhood Deprivation on Brain White Matter in Adult Adoptees: Widespread Localized Reductions in Volume But Unaffected Microstructural Organization

Article

Full-text available

Jul 2022

Background: Early childhood neglect can impact brain development across the lifespan. Using voxel-based approaches we recently reported that severe and time-limited institutional deprivation in early childhood was linked to substantial reductions in total brain volume in adulthood, more than twenty years later. Here we extend this analysis to explore deprivation-related regional white matter volume and microstructural organization using diffusion-based techniques. Methods: A combination of tensor-based morphometry analysis and tractography was conducted on diffusion weighted imaging data from 59 young adults who spent between 3 and 41 months in the severely depriving Romanian institutions of the 1980’s before being adopted into UK families, and 20 non-deprived age-matched UK controls. Results: Independent of total volume, institutional deprivation was associated with smaller volumes in localized regions across a range of white matter tracts including (1) long-ranging association fibers such as bilateral inferior longitudinal fasciculus, bilateral inferior fronto-occipital fasciculus, left superior longitudinal fasciculi, and left arcuate fasciculus; (2) tracts of the limbic circuitry including fornix and cingulum; and (3) projection fibers with the corticospinal tract particularly affected. Tractographic analysis found no evidence of altered microstructural organization of any tract in terms of hindrance modulated orientational anisotropy (HMOA), fractional anisotropy (FA) or mean diffusivity (MD). Discussion: We provide further evidence for the effects of early neglect on brain development and their persistence in adulthood despite many years of environmental enrichment associated with successful adoption. Localized white matter effects appear limited to volumetric changes with microstructural organization unaffected.<br/

Sleep disturbances and sleep patterns in children with tic disorder: A case-control study

Article

Full-text available

Aug 2022

Study objectives To characterize sleep disturbances and sleep patterns in children with Tic disorder (TD), and explore their association with TD severity and types. Methods A case-control study was conducted in 271 children with TD recruited from a clinical setting and 271 non-TD children recruited from a primary school, matched by age (mean = 8.47 years, SD = 1.53 years) and gender (15.1% female). The Children's Sleep Habits Questionnaire (CSHQ) was used to assess sleep patterns and sleep disturbances. The TD types and severity were assessed with the Yale Global Tic Severity Scale (YGTSS). Results The TD children scored higher on CSHQ total score than non-TD group ( t = 29.50, p < 0.001) and demonstrated severer global sleep disturbance. Compared to non-TD children, TD children presented with increased risks for global sleep disturbance (aOR: 1.95; 95% CI = 1.20–3.06), and most specific sleep disturbances, including bedtime resistance (aOR: 3.15; 95% CI = 1.96–5.06), sleep onset delay (aOR: 3.43; 95% CI = 1.58–7.46), sleep anxiety (aOR: 2.83; 95%CI = 1.83–4.38), parasomnias (aOR: 3.68; 95% CI = 2.02–6.62), night waking (aOR: 9.29; 95% CI = 2.64–32.65), sleep disordered breathing (aOR: 1.72; 95% CI = 1.03-2.90) and daytime sleepiness (aOR: 1.72; 95% CI = 1.09–2.74). Children with mild and moderate tics, Provisional Tic Disorder (PTD), Chronic Tic Disorder (CTD) and Tourette Syndrome (TS) presented with more global and more specific sleep disturbances. In addition, combined ADHD, etc. Conclusion Children with TD are major risks for increased sleep disturbances, especially for those with severe and chronic symptoms. Furthermore, comorbid ADHD increases risk in certain areas of sleep. These findings highlight the importance to consider sleep outcomes in the assessment and treatment for children with TD.

Neuropsychology of Anxiety: An enquiry into the functions of the septo-hippocampal system (3rd edition)

Book

Feb 2024

https://global.oup.com/academic/product/the-neuropsychology-of-anxiety-9780198843313?cc=es&lang=en&# The Neuropsychology of Anxiety first appeared in 1982 as the first volume in the Oxford Psychology Series, and it quickly established itself as a classic work in the psychology and neuroscience literature. It presented an innovative, and at times controversial, theory of anxiety and the brain systems, especially the septo-hippocampal system, that subserve it. This completely updated and revised third edition provides a further updated theory of septo hippocampal function combined with an improved understanding of anxiety. The book includes a new chapter on prefrontal cortex integrating frontal and hippocampal views of anxiety, as well as an extensively modified chapter on personality providing a new basis for further developments of Reinforcement Sensitivity Theory. In addition, numerous figures have been fully updated and converted to colour to support the text. This book is essential for postgraduate students and researchers in experimental psychology and neuroscience, as well as for all clinical psychologists and psychiatrists.

Neurobiological predispositions for musicality: White matter in infancy predicts school-age music aptitude

Article

Dec 2022
DEVELOPMENTAL SCI

Musical training has long been viewed as a model for experience‐dependent brain plasticity. Reports of musical training‐induced brain plasticity are largely based on cross‐sectional studies comparing musicians to non‐musicians, which cannot address whether musical training itself is sufficient to induce these neurobiological changes or whether pre‐existing neuroarchitecture before training predisposes children to succeed in music. Here, in a longitudinal investigation of children from infancy to school age ( n = 25), we find brain structure in infancy that predicts subsequent music aptitude skills at school‐age. Building on prior evidence implicating white matter organization of the corticospinal tract as a neural predisposition for musical training in adults, here we find that structural organization of the right corticospinal tract in infancy is associated with school‐age tonal and rhythmic musical aptitude skills. Moreover, within the corpus callosum, an inter‐hemispheric white matter pathway traditionally linked with musical training, we find that structural organization of this pathway in infancy is associated with subsequent tonal music aptitude. Our findings suggest predispositions prior to the onset of musical training from as early as infancy may serve as a scaffold upon which ongoing musical experience can build. Research Highlights Structural organization of the right corticospinal tract in infancy is associated with school‐age musical aptitude skills. Longitudinal associations between the right corticospinal tract in infancy and school‐age rhythmic music aptitude skills remain significant even when controlling for language ability. Findings support the notion of predispositions for success in music, and suggest that musical predispositions likely build upon a neural structural scaffold established in infancy. Findings support the working hypothesis that a dynamic interaction between predisposition and experience established in infancy shape the trajectory of long‐term musical development.

Right Fusiform Gray Matter Volume in Children with Long-Term Abacus Training Positively Correlates with Arithmetic Ability

Article

Nov 2022
NEUROSCIENCE

Abacus-based mental calculation (AMC) training has a positive effect on number-related cognitive abilities. While visuospatial strategy may distinguish AMC from conventional calculation method, the underlying neural mechanism is still elusive. The current study aimed to address this question by examining the plasticity of fusiform induced by AMC training and whether this training affects the association between the volume of fusiform and behavioral performance in numerical cognitive tasks using voxel-based morphometry analysis. The results showed that gray matter volumes of bilateral fusiform were significantly smaller in the AMC group relative to the control group. In addition, the volume of right fusiform was positively correlated with digit memory span and negatively correlated with reaction time of an arithmetic operation task only within the AMC group. These results indicate that bilateral fusiform may be the essential neural substrate for AMC experts to recognize and reconstruct abacus-based representations for numbers. These results may advance our understanding of the neural mechanisms of AMC and shield some lights to potential interactions between brain development and cognitive training in children.

Education and Health as Social Determinants: The Econeurobiology of Brain Development

Abstract

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