ArticlePDF Available

The Association between Home Environment and Quality of Life in Children and Adolescents in Hangzhou City, China

Springer Nature
Journal of Child and Family Studies
Authors:

Abstract and Figures

To investigate the influence of the home environment, defined as family socioeconomic status (SES) (parent education level, household income), student resource-mediated SES (access to nutritional resources and cognitively stimulating experiences), reading ability, and difficulty with homework on quality of life in children and adolescents residing in urban and suburban areas in Hangzhou City, Zhejiang Province, China. This study included 3200 Grade 3–6 students from 8 elementary schools in Hangzhou City. Assessments included questionnaires that evaluated student quality of life, family SES, resource-mediated SES (dietary behavior and the home literacy environment), reading ability, and difficulty with homework. The effects of the home environment on student quality of life were analyzed by univariate analysis, multiple linear regression analysis, and structural equation modeling. Overall, 80.6% of students had a medium or better quality of life. Young age (Grade 3 or 4), female sex, household income of 10000–15000 RMB, high breakfast consumption, daily intake of fruit, a balanced diet, and good reading habits were positively correlated with student quality of life ( P < 0.05), while overuse of electronic devices was negatively correlated with quality of life ( P < 0.05). Dietary behaviors, home literacy environment, and student reading ability and difficulty with homework directly affected quality of life. Family SES indirectly affected student quality of life. Children and adolescents in China should have access to good nutrition and cognitively stimulating experiences to enhance their well-being and provide them with social and academic advantages.
This content is subject to copyright. Terms and conditions apply.
Journal of Child and Family Studies (2021) 30:14161427
https://doi.org/10.1007/s10826-021-01951-1
ORIGINAL PAPER
The Association between Home Environment and Quality of Life in
Children and Adolescents in Hangzhou City, China
Xianhong Huang1Le Hua2Xueyang Zhou3Hao Zhang1Meng Zhang1Sheng Wang1Shangren Qin1
Jie Chen3XiaoHe Wang1
Accepted: 26 March 2021 / Published online: 14 April 2021
© The Author(s) 2021
Abstract
To investigate the inuence of the home environment, dened as family socioeconomic status (SES) (parent education level,
household income), student resource-mediated SES (access to nutritional resources and cognitively stimulating experiences),
reading ability, and difculty with homework on quality of life in children and adolescents residing in urban and suburban
areas in Hangzhou City, Zhejiang Province, China. This study included 3200 Grade 36 students from 8 elementary schools
in Hangzhou City. Assessments included questionnaires that evaluated student quality of life, family SES, resource-mediated
SES (dietary behavior and the home literacy environment), reading ability, and difculty with homework. The effects of the
home environment on student quality of life were analyzed by univariate analysis, multiple linear regression analysis, and
structural equation modeling. Overall, 80.6% of students had a medium or better quality of life. Young age (Grade 3 or 4),
female sex, household income of 1000015000 RMB, high breakfast consumption, daily intake of fruit, a balanced diet, and
good reading habits were positively correlated with student quality of life (P< 0.05), while overuse of electronic devices was
negatively correlated with quality of life (P< 0.05). Dietary behaviors, home literacy environment, and student reading
ability and difculty with homework directly affected quality of life. Family SES indirectly affected student quality of life.
Children and adolescents in China should have access to good nutrition and cognitively stimulating experiences to enhance
their well-being and provide them with social and academic advantages.
Keywords Quality of life Home literacy environment Dietary behavior Social economic status Structural equation
model
Highlights
The inuence of the home environment on quality of life in students in China was explored with structural equation
modeling.
Student quality of life was directly affected by diet, the literacy environment, reading ability and difculty with
homework.
Student quality of life was indirectly affected by family socioeconomic status.
These ndings will inform the development of programs that promote improved quality of life in Chinese children.
Childhood and adolescence represent crucial phases in the
development of physical, psychological, behavioral, and
social maturity (Hosokawa and Katsura, 2017; Lee &
Jackson, 2017; Rashid et al., 2018; Zou et al., 2018). During
*XiaoHe Wang
xhewang@163.com
1Department of Health Service Management, School of Medicine
Hangzhou Normal University, Hangzhou, China
2Afliated Xixi Hospital, College of Medicine, Zhejiang
University, Hangzhou, China
3The First Afliated hospital, College of Medicine, Zhejiang
University, Hangzhou, China
Supplementary information The online version contains
supplementary material available at https://doi.org/10.1007/s10826-
021-01951-1.
1234567890();,:
1234567890();,:
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
these phases, family socioeconomic status (SES) and the
home environment inuence child and adolescent quality of
life (QOL), dened as their physical, emotional, and social
well-being (Maatta et al., 2017).
Widely used markers of SES include social indicators,
such as occupation and educational level, and economic
indicators that are material and resource related (Roubinov
& Boyce, 2017), such as income. The link between SES and
QOL in children and adolescents is mediated by accessi-
bility to resources, including nutrition and cognitively sti-
mulating experiences. Nutritional intake inuences child
and adolescent growth and development, cognitive ability,
immunity, morbidity, and mortality, with poor nutrition a
key component of poor health (Boe et al., 2018; Bradley &
Corwyn, 2002; Hong, 2007). Access to cognitively stimu-
lating experiences provides children and adolescents direct
and peer or adult-mediated learning opportunities that
impact their cognitive ability and potential for beneting
from school (Bradley & Corwyn, 2002; Rowland et al.,
2018; Russell et al., 2018). The connection between SES,
access to cognitively stimulating experiences, and QOL in
children and adolescents is related to parental behavior (Jin
& Lu, 2017). High-SES parents, dened as those with better
education and an economic advantage, typically spend more
time reading and communicating with their children and
adolescents than low-SES parents (Sun et al., 2013). This
might be because higher-SES parents have the time and
income to make better interpersonal and material invest-
ments in their childrens development than lower-SES
parents, who must focus on more basic needs (Sohr-Preston
et al., 2013). A good home literacy environment is posi-
tively related to child and adolescent language and literacy
development and might improve child and adolescent
reading ability (He et al., 2014; Noble et al., 2006; Sun
et al., 2013). Children and adolescents with reading dif-
culties might experience concomitant psychosocial pro-
blems in three dimensions, including self-belief, social
cognitive ability, and interpersonal ability (Nathan, 2006).
In Hungary, children <18 years with a reading disability had
a lower QOL than controls without a reading disability
(Balazs et al., 2016).
Studies that investigated the inuence of the home
environment on QOL in children and adolescents focused on
children and adolescents with chronic disease or those who
were obese. Research that investigated the QOL in children
and adolescents in the general population is limited and
mainly explored associations between family economic sta-
tus, parenteral education level, family structure, number of
siblings, household crowding, and parenting style (Hosokawa
& Katsura, 2017; Lee & Jackson, 2017; Ran et al., 2018;
Rashid et al., 2018; Zou et al., 2018). In the United States,
socioeconomic disadvantages were associated with a sig-
nicant negative impact on the cognitive achievement of
children aged 19 years (Lee & Jackson, 2017). In Japan,
family income was related to social skills in preschoolers
aged 5 years, and maternal and paternal education levels were
related to internalizing and externalizing problems in rst
graders aged 6 years (Hosokawa & Katsura, 2017) In Brazil
(Paula et al., 2012), clinical, socioeconomic and home
environment (family structure; number of siblings; use of
cigarettes, alcohol and drugs in the family; household over-
crowding) factors exerted a negative impact on the oral
health-related QOL of schoolchildren aged 12 years. In
Wuhan, China, youth optimism was a mechanism by which
family SES was associated with life satisfaction in children
and adolescents from primary and high schools (Zou et al.,
2018). In Shapingba district, Chongqing, China, inadequate
health literacy might have contributed to poor QOL among
junior middle school students.
Reports on the inuence of other factors on the QOL in
children and adolescents in China are limited. Compared
with adults, QOL research studies in children and adoles-
cents in China are scarce, possibly because of the relatively
stronger emphasis on parent-centeredness than child-
centeredness in Chinese culture (Daniel & Britta, 2007).
Previous studies that investigated related topics used tradi-
tional statistical methodologies, such as single factor and
multiple linear regression analysis (Matthews et al., 2014;
Paula et al., 2012; Wang et al., 2007). However, when
applying traditional multiple linear regression analysis, the
dependent variable and independent variables were dened
and only the direct effect between variables was determined.
The effect of latent variables, such as factors in the home
environment, can only be inferred from other variables that
are observed. Structural equation modeling uses a combi-
nation of factor and multiple regression analysis that indi-
cates measurement errors, and represents, estimates, and
tests a theoretical network between variables (Joreskog &
Sorbom, 1979; Meuleners et al., 2003). Therefore, structural
equation modeling evaluates the relationship between latent
constructs and observed variables. This study investigated
the QOL in children and adolescents residing in urban and
suburban areas in Hangzhou City, Zhejiang Province, China
using structural equation modeling. Hangzhou City is an
economically developed municipality that is located on the
southeast coast of China with a per capita GDP of USD
20,419 2017. This study explored how the home environ-
ment, dened as family SES (parent education level,
household income), resource-mediated SES (access to
nutritional resources and cognitively stimulating experi-
ences), reading ability, and difculty with homework
directly and indirectly inuenced the QOL in children and
adolescents in Hangzhou City. SES, reading ability and
difculty with homework were chosen as the variables
measured in this study because evidence suggests (Bradley
& Corwyn, 2002) that the effect of SES on child health is
Journal of Child and Family Studies (2021) 30:14161427 1417
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
mediated by the availability of environmental (reading and
nutritional) resources and psychological factors, which
inuence reading ability and difculty with homework.
Cognitive stimulation is a particularly important con-
sideration. Low-SES children lack resources and experi-
ence, which limits the development of their cognitive
abilities, reected by their reading skills, and their potential
to benet from school. In addition, exposure to resources
and culture is a mediating variable between SES and child
intelligence or academic performance and behavioral pro-
blems (Poulain et al., 2020). Understanding how inequal-
ities in the home environment effect children and
adolescents informs the development of programs that
promote improved QOL in Chinese children.
Methods
Participants
The sample include 3200 students with a mean age of 11.19
years (standard deviation [SD] =1.96, range 914 years).
Based on a dichotomous (male/female) measure of gender,
53.8% of the students were male and 46.2% of the students
were female. There were 848 (26.5%) Grade 6 students, 768
(24.0%) Grade 5 students, 836 (26.1%) Grade 4 students, and
748 (23.4%) Grade 3 students. Most of the students (96.9%)
lived with both biological parents, who were married. In
addition, this study included 3200 parents (89.3% mothers)
that reported on their children. Parents had a mean age of
38.67 years (SD =4.21). 52.6% of parents lived in urban
areas, and 47.4% of parents lived in the suburbs. For eco-
nomic status, 1075 (33.6%), 1217 (38.0%), and 908 (28.4%)
families had an income CNY < 10000, CNY 10,00015,000,
or CNY > 15,000 per month, respectively. Regarding parents
occupation, 29.6% of fathers were professional technical
staff, and 22.9% of mothers were unemployed. For education
level, 23.9% of fathers had a college diploma or above,
45.9% of fathers reached junior college level, and 30.2% of
fathers nished senior high school or below. Between the
mothers, 22.0% were educated to junior high school or
below, and 17.0% had a college diploma or above.
Procedure
This study was conducted in Hangzhou, a city that is in the
north of Zhejiang Province on the southeast coast of China.
There are 10 districts in Hangzhou City and approximately
1015 primary schools in each district; therefore, a multistage
cluster sampling design was used to select eight primary
schools. First, four urban and four suburban primary schools
were randomly selected. Then, three to ve classes were
randomly selected from Grade 36 in each primary school.
Inclusion criteria for students were: (1) a normal intelligence
quotient, as reported by teachers; (2) no history of brain
trauma or brain disease, visual or auditory dysfunction, or
psychiatric disorders; (3) able to speak and read Chinese; and
(4) parental consent.
This cross-sectional study was conducted between Sep-
tember and December 2016 by two researchers and six
students with masters degrees who had experience in
conducting epidemiological surveys. Before data collection,
the scientic research ethics committee of Hangzhou Nor-
mal University reviewed and approved the study protocol,
the informed consent forms, and the questionnaires. Per-
mission to conduct this study in the schools was obtained
from each head teacher, and informed consent was obtained
from the students and their parents (through a letter sent
home). When consent was given, the Children and Ado-
lescentsQuality of Life Scale and instructions on its
completion were provided to the included students, who
completed the questionnaire independently. During this
process, researchers were available to answer student
questions. Then, questionnaires were retrieved. Each stu-
dent took home the Chinese Reading Ability and its Inu-
encing Factors questionnaire for their mother or father to
complete. The students returned this questionnaire to their
teacher within 1 week. Parents and students were not
obliged to complete the questionnaires, even if they had
provided informed consent. Anonymity and condentiality
were assured. Questionnaires with a response rate of 90%
were included in the analyses. Missing data were input
using medians. This study used double data entry and
validation, and the logical range of each variable was con-
sidered to minimize errors. Finally, 3391 students returned
the Children and AdolescentsQuality of Life Scale ques-
tionnaire with a 94.2% response rate, 3360 parents returned
the Chinese Reading Ability and its Inuencing Factors
questionnaire with a 93.3% response rate, and 3200 families
completed both questionnaires, for an 88.9% response rate.
Measures
Student quality of life
Students completed the Children and AdolescentsQuality
of Life Scale that consisted of 49 items (Wu et al., 2006a,c)
and measured 4 domains, and 13 dimensions. One domain
evaluated social psychological function (21 items) and
assessed ve dimensions, including teacherstudent rela-
tionship (5 items, e.g., Are you satised with the relation-
ship between you and your teacher? 1 =not at all
satised4=very satised), peer relationships (5 items,
e.g., Is your classmate friendly toward you? 1 =not
friendly4=very friendly), and parentchild relationship (4
items, e.g., Do you like staying with your parents?),
1418 Journal of Child and Family Studies (2021) 30:14161427
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
learning ability and attitude (3 items, e.g., Do you remem-
ber new things easily?), and self-concept (4 items, e.g., Do
you feel you are an important member of the team?), which
are scored as 1 =never4=always. Another domain eval-
uates physicalmental health (12 items) and assesses three
dimensions, including: physical perception (5 items, e.g.,
Do you often feel tired after getting up?), negative emotions
(4 items, e.g., Do you often feel regretful for what you have
done?), and attitude toward homework (3 items, e.g., Do
you need a lot of time to nish homework?), which are
scored as 1 =never4=always. A third domain evaluates
living environment (8 items) and assesses three dimensions,
including: convenience (2 items, e.g., Is there convenient
transportation near your home? 1 =not at all4=very
convenient), opportunities for activity (3 items, e.g., Can
you participate in your favorite extracurricular activities? 1
=rarely4=too many opportunities), and athletic ability (3
items, e.g., Are you satised with your ability to participate
in sports? 1 =not at all4=very satised). Finally, there is
a life satisfaction domain that assesses a self-satisfaction
dimension (8 items, e.g., Are you satised with your sleep?
1=not at all satised4=very satised). Total, domain,
and dimension scores were calculated, with higher scores
indicating better QOL. Scores lower than two SDs below
the mean were considered very poor QOL. Scores between
one and two SDs below the mean were considered poor
QOL. Scores that were one SD above or below the mean
were considered moderate QOL. Scores that were between
one and two SDs above the mean were considered better
QOL. Scores that were two SDs above the mean were
considered excellent (Wu et al., 2006a,c) QOL.
Total scores were transformed to a T score metric,
which was referenced to means and SD stratied by gen-
der, age, and region of residency for the Chinese general
population. A lower T score represented a poorer QOL
according to the following categorization: T < 30 =worst
QOL; 30 T<40=bad QOL; 40 T<60=medium
QOL; 60 T<70=good QOL; and T 70 =best QOL.
During development and validation of the Children and
AdolescentsQuality of Life Scale, internal consistency and
reliability for the entire questionnaire, each domain, and
each dimension were evaluated as acceptable (Tavakol &
Dennick, 2011) using Cronbachs alpha (between 0.73 and
0.95). Content validity of the scale was assessed as good
using a correlation coefcient between each dimension and
the overall score (0.560.89), and the four domains and the
overall score (0.520.83) (Wu et al., 2006b). The Children
and AdolescentsQuality of Life Scale is widely used in
China to assess children and adolescents aged 718 years.
In previous studies (Peng et al., 2005a; Wu et al., 2006b),
Cronbachs alpha was reported at 0.8550.872, and content
validity was reported at 0.6610.866. The cumulative var-
iance contribution rate was 75.44% and the factor loading
was between 0.71 and 0.89, which indicated good construct
validity. In this study, conrmatory factor analysis was used
to assess the factorial structure of the Children and Ado-
lescentsQuality of Life Scale. Findings conrmed the 13-
factor structure (Lance et al., 2006), because the goodness
of t index (GFI) was 0.972, the adjusted goodness of t
index (AGFI) was 0.954, the comparative t index (CFI)
was 0.948, the Tucker-Lewis index (TLI) was 0.945, the
Chi-squared (χ2/df) was 2.273, and the root mean square
error of approximation (RMSEA) was 0.045. The cumula-
tive percent variance was 75.44%. Factor loading was used
to identify whether items loaded strongly onto their hypo-
thesized latent variable. Factor loading was from 0.48 to
0.89, which indicated good construct validity.
Student home environment
Student home environment was dened by family SES,
resource-mediated SES, reading ability, and difculty with
homework. Family SES was dened by parent education
level and household income. Resource-mediated SES was
dened by child and adolescent access to nutritional
resources and cognitively stimulating experiences, such as
reading materials and electronic devices. These variables
were measured using the Chinese Reading Ability and its
Inuencing Factors questionnaire, which was completed by
one parent from each family. Internal consistency and
reliability for the entire questionnaire and each domain were
evaluated using Cronbachs alpha, with values between
0.76 and 0.94 considered acceptable. Content validity of the
scale was assessed as good using the correlation coefcient
between each dimension and the overall score (0.67 to 0.91)
(p< 0.05). The cumulative percent variance was 72.37%
and factor loading was from 0.52 to 0.87, which indicated
good construct validity.
Family SES and resource-mediated SES
In Part 1 of the Chinese Reading Ability and its Inuencing
Factors questionnaire, parents reported on items that assessed
the general home environment, including student gender and
date of birth, parent educational level, family SES (household
income, annual cost of extracurricular books: CNY < 300 =
1, CNY 300500 =2, 500800 =3, CNY > 8000 =4), stu-
dent dietary behavior (frequency of breakfast intake, fre-
quency of fruit intake, and balanced diet), and the home
literacy environment (student reading-related behavior,
weekly use of electronic devices, and rules for use of elec-
tronic devices). Variables were dened based on previously
published studies (He et al., 2014;Wangetal.,2013).
Reading-related behavior was scored based on the time
spent reading each day (none =0, 00.5 h =1, 0.51h=2,
>1 h =3) plus the frequency of participation in extracurricular
Journal of Child and Family Studies (2021) 30:14161427 1419
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
activities such as reading (23 times per week =1, >3 times
per week =2, every day =3). Weekly use of electronic
devices was scored according to the time spent watching
television each day (<1 h =0.5, 12h=1.5, 23h=2.5,
>3 h =3) multiplied by 7 days plus the frequency of com-
puter use per week (1 day/week =1, approximately 3 days/
week =3, approximately 6 days per week =6, every day =
7) multiplied by the time spent using the computer (<1 h =
0.5, 12h=1.5, 24h=3, >4 h =4). Rules for use of
electronic devices were dened according to the parental
attitude concerning student television and computer use and
were scored from 1 to 6. Total scores for reading-related
behavior, weekly use of electronic devices, and rules for use
of electronic devices was from 0 to 27.
Student reading ability
In Part 2 of the Chinese Reading Ability and its Inuencing
Factors questionnaire, parents reported on student reading
ability using the Dyslexia Checklist for Chinese Children
(Wu et al., 2006a,c), which consists of 57 items and 8
dimensions, including barriers to spoken language (six
items, e.g., lack of competence in oral communication and
not good at oral communication); problems with written
expression (seven items, e.g., writing very slowly and n-
ishing homework very late); bad reading habits (six items,
e.g., reading the same sentence over again or skipping
sections); attention decit disorder (7 items, e.g., cannot
concentrate during class or doing homework); visual dis-
turbance (seven items, e.g., confuses the letters d and b);
disturbance in auditory perception (seven items, e.g., writ-
ing very slowly and nishing homework very late); dys-
graphia (six items, e.g., does not understand normal speech,
only understands when speech is slow or repeated); and
difculty understanding (nine items, e.g., often does not
understand the meaning of words in sentences). The
responses to each item were scored as 1 =never5=
always. Higher scores represented a lower reading ability.
The eight dimensions were clustered into two categories
using principal component analysis: dyslexia (dened as a
specic and signicant impairment in reading ability that
cannot be explained by decits in intelligence, learning
opportunity, motivation, or sensory acuity (Fisher et al.,
2002), and included the rst six dimensions) and bad
reading habits (dened as reading habits that impede read-
ing speed or are harmful to health).
Internal consistency and reliability for the total score and
the factors that composed the Dyslexia Checklist for Chi-
nese Children were evaluated using Cronbachs alpha, with
values of 0.974 and 0.7520.901, respectively. Factor
loadings for all items were satisfactory, from 0.383 to 0.856
(Hou et al., 2018). In this study, conrmatory factor ana-
lysis was used to assess the factorial structure of the
Dyslexia Checklist for Chinese Children. Findings con-
rmed the eight factor structure (Lance et al., 2006),
because the GFI was 0.943, the AGFI was 0.931, the CFI
was 0.927, the TLI was 0.925, the χ2/df was 2.863, and the
RMSEA was 0.051. The cumulative variance contribution
rate was 75.68%. Factor loading was used to identify
whether items loaded strongly onto their hypothesized latent
variable. Factor loading was between 0.41 and 0.91, which
indicated good construct validity.
Student difculty with homework
Difculty with homework was scored based on the need for
parental pressure to ensure the homework was nished
(seldom =1, sometime s =2, always =3) plus the time
each day required to nish the homework (<1 h =1, 12h
=2, 23h=3>3h=4) according to a previously pub-
lished report (He et al., 2014).
Statistical Analysis
Initially, normality, outliers, and multicollinearity were
evaluated. Normality was assessed using coefcients of
skewness (sk) and kurtosis (ku). Values fell within the
acceptable ranges of 0.581.54 for sk and 2.152.63 for
ku. The multivariate normality test gave a value of 8.45,
which indicated that the data followed a multivariate normal
distribution, because this value was <10. The existence of
outliers were identied by Cooks distance. The maximum
Cooks distance was <0.5 (0.028), which indicated there
were no outliers in these data. Multicollinearity was tested
by the tolerance rate and variance ination factor (VIF). The
ndings showed no tolerance rate <0.10 or VIF > 10. All the
tolerance values were >0.78 and the VIF was <3.9, which
indicated no multicollinearity.
Statistical analysis was performed using SPSS16.0 and
AMOS22.0. A descriptive analysis was conducted using
mean ± SD for quantitative variables and frequencies ±
percentages for qualitative variables. Reliability was
examined with Cronbachs alpha and content validity was
measured using Pearsons correlation coefcient. Differ-
ences in QOL scores based on gender, student grade,
parent education level, annual cost of extracurricular
books, and student dietary habits were analyzed using a
Students t-test or analysis of variance (ANOVA) with
Bonferroni post-hoc analysis. The factors that affected
QOL were identied using multiple regression analysis
with the four domains and total scores for QOL as
dependent variables, and student gender and grade, parent
education level, home literacy environment, and student
reading ability as independent variables. Factors with p<
0.1 in the univariate analysis were included in the multiple
regression analysis.
1420 Journal of Child and Family Studies (2021) 30:14161427
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Based on the data from the multiple regression analysis
and previously published literature, factors in the home
environment, including family SES, resource-mediated
SES, student reading ability, and difculty with home-
work were included in structural equation modeling to
analyze their effect on student QOL. The costs of extra-
curricular books and monthly household income were used
to adjust family SES. Student reading ability, which is
affected by the home literacy environment, and difculty
with homework were included in the model. Structural
equation modeling was performed using AMOS24.0. A
Chi-squared χ2test was used to assess model t. In addition,
the CFI, TLI, RMSEA, and the standardized root mean
square residual (SRMR) were used to assess goodness of
t of models. Acceptable criteria were set according to
guidelines reported in literature: CFI > 0.93, TLI > 0.90,
RMSEA < 0.08, and SRMR < 0.08. Full information max-
imum likelihood with robust standard errors (MLR) was
adopted to deal with missing data and non-normality. The
level of signicance in the analyses was set to 0.05.
Results
Student Quality of Life
Overall, 15.1% of students had the worst QOL, 4.3% had a
bad QOL, 62.5% had a medium QOL, 14.4% had a good
QOL, and 3.7% of had the best QOL. 80.6% of students had
a medium or better QOL.
Between the four domains assessed by the QOL measure,
scores for psychosocial function, physicalmental health,
and life satisfaction were signicantly higher among female
students compared with male students (p< 0.001). Scores
for psychosocial function, physicalmental health, living
environment, and life satisfaction were signicantly higher
among younger students (Grade 3 or 4) compared with
older students (Grade 5 or 6) (p< 0.001). Scores for psy-
chosocial function and living environment were sig-
nicantly higher among students residing in urban regions
compared to students residing in suburban regions (p<
0.01), and scores for life satisfaction was signicantly
higher among students residing in suburban regions (p<
0.01) (Table S1).
Inuence of Parents Educational Level and Family
SES on Student Quality of Life
Scores for all four domains assessed by the QOL measure
(psychosocial function, physicalmental health, living
environment, life satisfaction) signicantly increased with
increases in parent educational level and family SES (p<
0.05) (Table S2).
Inuence of Student Eating Habits on their Quality
of Life
Scores for psychosocial function, physicalmental health,
and life satisfaction were signicantly increased in students
who ate breakfast every day compared with those who ate
breakfast less frequently (p< 0.05). Scores for psychosocial
function, physicalmental health, living environment, and
life satisfaction were signicantly increased in students who
ate fruit everyday compared with those who ate fruit often
or seldom and in those who ate fruit often compared with
those who ate fruit seldom (p< 0.05). Scores for psycho-
social function, physicalmental health, living environment,
and life satisfaction were signicantly increased in students
who ate a balanced diet compared with those who ate pre-
dominantly meat or vegetables, and scores for psychosocial
function, physicalmental health, and living environment
were signicantly increased in students who ate pre-
dominantly meat compared with predominantly vegetables
(p< 0.05) (Table S3).
Multiple Linear Regression Analysis
Univariate analysis and multiple linear regression analysis
were performed using the four domains assessed by the
QOL measure (psychosocial function, physicalmental
health, living environment, life satisfaction) as dependent
variables and student gender, age, region of residence,
family SES (parent education level, household income),
dietary behavior (breakfast intake, fruit intake, balanced
diet), and home literacy environment (reading-related
behavior, weekly use of electronic devices, rules for use of
electronic devices at home), as independent variables.
Factors with p< 0.1 on univariate analysis were included in
multiple regression analysis. The ndings revealed eight
factors were associated with higher psychosocial function,
including young age (junior grades), having a father with a
college level or above of education, household income
CNY 10,00015,000, frequent breakfast consumption, daily
intake of fruit, good reading-related behavior, and limited
time spent using electronic devices; the most inuential
factor was reading-related behavior. Eight factors were
associated with higher physicalmental health, including
young age (Grade 3 or 4), household income CNY
10,00015,000, frequent breakfast consumption, balanced
diet, daily intake of fruit, good reading-related behavior,
limited time spent using electronic devices, and lenient rules
for use of electronic devices. The most inuential factor was
reading-related behavior. Eight factors were associated with
a better living environment, including living in an urban
area, having a father with college level or above of educa-
tion, having a mother with a junior college level of edu-
cation, frequent breakfast consumption, daily intake of fruit,
Journal of Child and Family Studies (2021) 30:14161427 1421
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
good reading-related behavior, and strict rules for use of
electronic devices. The most inuential factor was reading-
related behavior. Eight factors were associated with better
life satisfaction, including living in a rural area, young age
(Grade 3 or 4), frequent breakfast consumption, balanced
diet, daily intake of fruit, good reading-related behavior,
limited time spent using electronic devices, and lenient rules
for use of electronic devices. The most inuential factor was
reading-related behavior (Table 1).
Structural Equation Modeling
Structural equation modeling was used to describe the
inuence of the home environment on student QOL
(Fig. 1). Dietary behavior, difculty with homework,
reading ability, home reading environment and other
inuencing factors were identied using univariate analysis,
multiple linear regression analysis, and exploratory factor
analysis. Measurement and structural models were con-
structed. The measurement model was tested with con-
rmatory factor analysis. The strength of relationships in the
structural model were estimated using correlation coef-
cients generated by AMOS24.0. Model t was assessed,
and the model was respecied. The nal model had good t,
because χ2/df, GFI, AGFI, NFI, IFI, and CFI were >0.9, and
the RMSEA was <0.05 (Table 2).
The estimated path coefcients from one independent
latent variable to the dependent latent variable are
Table 1 Multivariate linear regression for students quality of life scores (standardized coefcients)
Independent variables Categories Quality of life
Psychological
function
Physical
mental health
Living
environment
Life
satisfaction
Total
score of QOL
Residence (suburb =0) Urban 0.021 0.027 0.118* 0.057** 0.017
Grade (three, four =0) Five and six 0.097** 0.103 0.018 0.136 0.11*
Gender (boys =0) Girls 0.086** 0.022 0.012 0.028 0.056**
Students reading
behavior
0.23* 0.16* 0.19* 0.18* 0.24*
Students time using
electronic devices
0.062** 0.078** 0.011 0.065** 0.069**
Rules for using
electronic devices
at home
0.013 0.051** 0.054** 0.039** 0.003
Students
breakfast intake
0.092** 0.084** 0.052** 0.087** 0.095**
Monthly household income (<5000 =0)
50011000 yuan 0.014 0.014 0.009 0.016 0.012
10001150000 yuan 0.073** 0.058** 0.032 0.025 0.070
>15000 yuan 0.020 0.008 0.054** 0.006 0.021
Fathers education (junior high and below =0)
Senior high school 0.019 0.008 0.022 0.003 0.022
Associate degree 0.025 0.021 0.027 0.011 0.030
Bachelors degree
and above
0.045** 0.005 0.056** 0.003 0.027
Mothers education (junior high and below =0)
Senior high school 0.015 0.014 0.021 0.018 0.023
Associate degree 0.011 0.006 0.061** 0.002 0.019
Bachelors degree
and above
0.012 0.003 0.054** 0.002 0.017
Students balanced diet intake (more vegetables =0)
More meat 0.020 0.045** 0.053** 0.002 0.014
Balanced diet 0.018 0.046** 0.072** 0.076** 0.064**
Students vegetable and fruit intake (never =0)
Often 0.021 0.013 0.012 0.004 0.022
Everyday 0.068* 0.061** 0.087* 0.065** 0.089**
* < 0.01; ** < 0.05
1422 Journal of Child and Family Studies (2021) 30:14161427
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
summarized in Table 3. The direct effect of parent educa-
tional level on family SES was positive and signicant. The
direct effect of family SES on dietary behavior and the
home literacy environment was positive and signicant.
The direct effect of dietary behavior on reading ability was
negative and signicant. The direct effect of the home lit-
eracy environment on reading ability was negative and
signicant. The direct effect of reading ability on difculty
with homework was positive and signicant. The total
effect of parent education level on family SES, dietary
behavior, and the home literacy environment was positive
and signicant. The total effect of parent education level on
reading ability and difculty with homework was negative
and signicant. The total effect of family SES on dietary
behavior and the home literacy environment was positive
and signicant. The total effect of family SES on reading
ability and difculty with homework was negative and
signicant. The total effects of dietary behavior and the
home literacy environment on reading ability and difculty
with homework were negative and signicant. The total
effect of reading ability on difculty with homework was
positive and signicant.
The estimated path coefcients from latent variables to
QOL are summarized in Table 4. The direct effect of dietary
behavior on QOL was positive and signicant. The direct
effect of difculty with homework on QOL was negative
and signicant. The total effect of family SES (parent
education level, household income), dietary behavior, home
literacy environment, and reading ability on QOL was
positive and signicant and the total effect of difculty with
homework was negative and signicant.
Discussion
This study investigated the QOL in children and adolescents
residing in urban and suburban areas in Hangzhou City,
Zhejiang Province, China. Compared with national data
(Wu et al., 2006b), the overall QOL for primary school
students in Hangzhou City was good, because 80.6% of
students had a medium or better QOL. Compared with
children and adolescents in the general Chinese population
(Wu et al., 2006a,c), children and adolescents residing in
Hangzhou City had lower scores for psychosocial function
(3.04 ± 0.47 versus national 3.72 ± 0.71) and living envir-
onment (2.73 ± 0.54 versus national 3.67 ± 0.79) and higher
scores for physicalmental health (3.04 ± 0.49 versus
national 2.33 ± 0 .61) and life satisfaction (3.11 ± 0.44
versus national 1.52 ± 0.44). These data suggest that stra-
tegies should be implemented to improve the psychosocial
function and living environment of children and adolescents
residing in Hangzhou City. However, overall QOL and
several aspects of QOL (psychological function, physical
mental health, living environment, and life satisfaction)
were signicantly higher in children and adolescents
residing in Hangzhou City compared to primary school
students in Hubei province (Huang & Shan, 2006),
Fig. 1 Structural equation model
Table 2 Fit indices of nal model
Fit indices GFI AGFI CFI NFI IFI χ2/df RMSEA
Reference
value scale
>0.9 >0.9 >0.9 >0.9 >0.9 <5 <0.08
Fitted value 0.95 0.94 0.93 0.92 0.93 5.44 0.041
GFI goodness of t index, AGFI adjusted goodness of t index, CFI
comparative t index, NFI normed t index, IFI incremental t index,
RMSEA root mean square error of approximation
Journal of Child and Family Studies (2021) 30:14161427 1423
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Shanghai, and Suzhou (Peng et al., 2005b; Shen et al.,
2004). This might be explained by the geographical location
of the children and adolescents. Previous studies showed
that QOL scores for primary school students varied between
regions and were higher in cities than in rural areas (Chen
et al., 2007). Accordingly, evidence suggests (Fang, 2001)
that student QOL is a comprehensive indicator reecting
health and living standards, varying with socio-economic
and cultural levels.
Previous studies that investigated similar topics always
used traditional statistical methodologies (C et al., 2014;
Paula et al., 2012; Wang et al., 2007), which did not eval-
uate the effect of latent variables. In addition, variables
might be collinear by chance, which might lead to the
incorrect identication of relevant predictors in the statis-
tical model. In this study, by using structural equation
modeling, the direct (parent education level and monthly
household income) and indirect effects of family SES on
student QOL by mediating variables, such as dietary
behavior and the home literacy environment were analyzed.
Bradley et al, (Bradley & Corwyn, 2002) reported that
accessibility to resources and cultural activities was a
mediating variable between SES and child intelligence and
behavior. The home literacy environment is an important
mediating variable. A good home literacy environment
provides resources for the development of a childs reading
ability, and it is a protective factor against dyslexia (He
et al., 2014; Noble et al., 2006; Sun et al., 2013). Since
structural equation modeling investigates indirect effects,
reading ability and difculty with homework were included
as factors in the home environment and were analyzed as
mediating variables in this study.
Evidence suggests that fruit and vegetable intake and the
variety of fruit consumed are associated with some aspects
of QOL in children (Matthews et al., 2014), and an inap-
propriate diet and lack of breakfast might be important
environmental risk factors that lead to learning disorders in
children (Wang et al., 2013). In addition, it has been reported
that parent beliefs and behaviors (Davis-Kean 2005;He
et al., 2014) were indirectly related to child academic
achievement. Therefore, in this study, student eating habits
were chosen as a measure of nutritional resources, and the
home literacy environment was chosen as a measure of
student exposure to cognitively stimulating experiences. The
results showed that dietary behaviors and the home literacy
environment of students living in Hangzhou City directly
affected their QOL by inuencing their reading ability and
their ability to do homework. Family SES indirectly affected
student QOL. These data imply that a higher family SES, as
shown by well-educated parents and a high household
income, healthy dietary behaviors among children and
adolescents, and a good home literacy environment, could
improve student reading ability, decrease risks of dyslexia,
Table 4 Standardized total effect, standardized direct effect, and
standardized indirect effect of latent variables on students quality
of life
Latent variables Total effect Direct effect Indirect effect
Family
socioeconomic status
0.362* 0.000 0.362*
Students dietary
behavior
0.513* 0.430* 0.083**
Home literacy
environment
0.0575** 0.000 0.0575**
Students reading ability 0.213** 0.000 0.213**
Studentdifculty with
homework
0.260** 0.260** 0.000
** < 0.05,* < 0.01
Table 3 Standardized total effect, standardized direct effect, and standardized indirect effect between latent variables
Independent variable Dependent variable Standardized
total effect
Standardized
direct effect
Standardized
indirect effect
Family socioeconomic status Students dietary behavior 0.62* 0.62* 0.00
Home literacy environment 0.94* 0.94* 0.00
Students reading ability 0.49* 0.00 0.49*
Students difculty in nishing
homework
0.41** 0.00 0.41**
Students dietary behavior Students reading ability 0.39** 0.39** 0.00
Students difculty in nishing
homework
0.32** 0.00 0.32**
Home literacy environment Students reading ability 0.27** 0.27** 0.00
Students difculty in nishing
homework
0.22** 0.00 0.22**
Students reading ability Students difculty nishing
homework
0.82* 0.82* 0.00
* < 0.01; ** < 0.05
1424 Journal of Child and Family Studies (2021) 30:14161427
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
improve student ability to do homework, and enhance stu-
dent QOL. Similar to the results of this study, previous
research showed that SES was not related to child mental
health or psychological well-being in a sample of
19,487 schoolaged children collected from the 20132014
China Education Panel Survey; however, SES indirectly
affected child mental health and psychological well-being
through parentchild relations, peer relations, and
teacherstudent relations (Jarman et al., 2015; Ge, 2017).
Previous studies have shown that there is an association
between parental education level and nutrition in children.
In Europe, the IDEFICS (identication and prevention of
dietary- and lifestyle-induced health effects in children and
infants) cohort study (Arvidsson et al., 2017) of 16,229
children aged 29 years revealed that children of parents
with a lower level of education had a higher sugar and fat
intake than children of parents with a higher level of edu-
cation. Studies of 34,366 children in Brazil and 7474 chil-
dren in the United Kingdom found that the unhealthy
dietary habits of children were associated with a low level
of maternal education (Cribb et al., 2011; Saldiva et al.,
2014). In the United States (Shonkoff et al., 2017) a study
of 599 parentchild dyads showed that clearly explained
parent rules about the types of foods children could eat
might decrease sugar intake.
A good home literacy environment provides children and
adolescents direct and indirect learning opportunities and
encourages a culture of continuous learning. Children from
low-SES families often lack access to cognitively stimu-
lating resources, such as educational materials and outdoor
activities that enhance cognitive ability. Previous reports
(Noble et al., 2006; Park et al., 2017) show that family SES,
time parents spend reading with children, and the number of
books in a home are associated with the home literacy
environment; student weekday and weekend screen time
decrease as parental education level increases (Sharif &
Sargent, 2006); and a good home literacy environment
might improve student reading abilities (He et al., 2014;
Noble et al., 2006; Sun et al., 2013).
The precise determination of the processes how the home
environment inuences QOL in children and adolescents is
challenging; therefore, this study has several limitations.
First, it was a cross-sectional study and causality could not
be inferred. Second, factors that contribute to QOL are
complex and important indicators might not have been
considered in this model, including student to parental
exposure to stress inducing conditions and health-relevant
behaviors or lifestyle.
In conclusion, this study showed that the home envir-
onment inuenced the QOL in children and adolescents in
Hangzhou City, China. These ndings emphasize that
children and adolescents should have access to good
nutrition and cognitively stimulating experiences to
enhance their well-being and provide them with social and
academic advantages.
Acknowledgements The project was supported by Provincial Natural
Science Foundation of Zhejiang (No. LQ14H260001).
Compliance with Ethical Standards
Conict of Interest The authors declare no competing interests.
Publishers note Springer Nature remains neutral with regard to
jurisdictional claims in published maps and institutional afliations.
Open Access This article is licensed under a Creative Commons
Attribution 4.0 International License, which permits use, sharing,
adaptation, distribution and reproduction in any medium or format, as
long as you give appropriate credit to the original author(s) and the
source, provide a link to the Creative Commons license, and indicate if
changes were made. The images or other third party material in this
article are included in the articles Creative Commons license, unless
indicated otherwise in a credit line to the material. If material is not
included in the articles Creative Commons license and your intended
use is not permitted by statutory regulation or exceeds the permitted
use, you will need to obtain permission directly from the copyright
holder. To view a copy of this license, visit http://creativecommons.
org/licenses/by/4.0/.
References
Arvidsson, L., Eiben, G., Hunsberger, M., De Bourdeaudhuij, I.,
Molnar, D., & Jilani, H. (2017). Bidirectional associations
between psychosocial well-being and adherence to healthy diet-
ary guidelines in European children: prospective ndings from
the IDEFICS study. BMC Public Health,17(1), 926. https://doi.
org/10.1186/s12889-017-4920-5
Balazs, J., Miklosi, M., Toro, K. T., & Nagy-Varga, D. (2016).
Reading disability and quality of life based on both self- and
parent-reports: importance of gender differences. Frontiers in
Psychology,7, 1942
Boe, T., Serlachius, A. S., Sivertsen, B., Petrie, K. J., & Hysing, M.
(2018). Cumulative effects of negative life events and family
stress on childrens mental health: the Bergen Child Study. Social
Psychiatry and Psychiatric Epidemiology,53(1), 19. https://doi.
org/10.1007/s00127-017-1451-4
Bradley, R., & Corwyn, R. (2002). Socioeconomic status and child
development. Annual Review of Psychology,53, 371399
Chen, L., Wu, H., & Mai, J. (2007). Comparison of quality of life
among primary and secondary school students between urban and
rural in Beijing and Guangzhou. Chinese Journal of Social
Medicine,24(4), 268270
Cribb, V. L., Jones, L. R., Rogers, I. S., Ness, A. R., & Emmett, P. M.
(2011). Is maternal education level associated with diet in 10-
year-old children? Public Health Nutrition,14(11), 20372048.
https://doi.org/10.1017/s136898001100036x
Daniel, T. L. S., & Britta, M. L. (2007). A comprehensive review of
quality of life (QOL) research in Hong Kong. Scientic World
Journal,7, 12221229
Davis-Kean, P. E. (2005). The inuence of parent education and family
income on child achievement: the indirect role of parental expec-
tations and the home environment. Journal of Family Psychology,
19(2), 294304. https://doi.org/10.1037/0893-3200.19.2.294
Fang, J. (2001). Determination of quality of life and its application,
Vol. 1. Beijing: Beijing Medical University Press
Journal of Child and Family Studies (2021) 30:14161427 1425
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Fisher, S. E., Francks, C., Marlow, A. J., MacPhie, I. L., Newbury, D. F.,
& Cardon, L. R. (2002). Independent genome-wide scans identify a
chromosome 18 quantitative-trait locus inuencing dyslexia. Nat-
ure Genetics,30(1), 8691. https://doi.org/10.1038/ng792
Ge, T. (2017). Effect of socioeconomic status on childrens psycho-
logical well-being in China: the mediating role of family social
capital. Journal of Health Psychology, 1359105317750462.
https://doi.org/10.1177/1359105317750462
He, Z., Shao, S., Zhou, J., Ke, J., Kong, R., & Guo, S. (2014). Does
long time spending on the electronic devices affect the reading
abilities? A cross-sectional study among Chinese school-aged
children. Research in Developmental Disabilities,35(12),
36453654. https://doi.org/10.1016/j.ridd.2014.08.037
Hong, R. (2007). Effect of economic inequality on chronic childhood
undernutrition in Ghana. Public Health Nutrition,10(4),
371378. https://doi.org/10.1017/s1368980007226035
Hosokawa, R., & Katsura, T. (2017). A longitudinal study of socio-
economic status, family processes, and child adjustment from
preschool until early elementary school: the role of social com-
petence. Child Adolescent Psychiatry Mental Health,11,62
https://doi.org/10.1186/s13034-017-0206-z
Hou, F., Qi, L., Liu, L., Luo, X., Gu, H., & Xie, X. (2018). Validity
and reliability of the dyslexia checklist for Chinese children.
Frontiers in Psychology,9, 1915 https://doi.org/10.3389/fpsyg.
2018.01915
Huang, Y., Han-Rong, W. U., & Shan, L. U. (2006). Comparison of
quality of life between city and countryside among primary and
secondary school students in Hubei. Chinese Journal of School
Health, 27(1), 3435.
Jarman, M., Ogden, J., Inskip, H., Lawrence, W., Baird, J., & Cooper,
C. (2015). How do mothers manage their preschool childrens
eating habits and does this change as children grow older? A
longitudinal analysis. Appetite,95, 466474. https://doi.org/10.
1016/j.appet.2015.08.008
Jin, H. H., & Lu, Y. (2017). Academic performance of Texas public
schools and its relationship with studentsphysical tness and
socioeconomic status. International Journal of Applied Geospa-
tial Research,8(3), 3752
Joreskog, K. G., & Sorbom, D. (1979). Advances in Factor Analysis
and Structural Equation Models. Cambridge, MA: Abt Books
Lance, C. E., Marcus, M. B., & Michels, L. C. (2006). The sources of
four commonly reported cutoff criteria: what did they really say?
Organ Research Methods,9, 202220.
Lee, D., & Jackson, M. (2017). The simultaneous effects of socio-
economic disadvantage and child health on childrens cognitive
development. Demography,54(5), 18451871. https://doi.org/10.
1007/s13524-017-0605-z
Maatta, S., Konttinen, H., Haukkala, A., Erkkola, M., & Roos, E.
(2017). Preschool childrens context-specic sedentary beha-
viours and parental socioeconomic status in Finland: a cross-
sectional study. BMJ Open,7(11), e016690 https://doi.org/10.
1136/bmjopen-2017-016690
Matthews, C., Milte, C. M., Ball, K., & McNaughton, S. A. (2014).
Associations between fruit and vegetable intake and quality of
life. Journal of Nutrition & Intermediary Metabolism,1,18
Meuleners, L. B., Lee, A. H., Binns, C. W., & Lower, A. (2003).
Quality of life for adolescents: assessing measurement properties
using structural equation modelling. Quality of life Research,12
(3), 283290
Nathan, K. (2006). Reading difculties and psychosocial problems:
does social information processing moderate the link? Australian
Journal of Psychology,58(4), 171
Noble, K. G., Farah, M. J., & McCandliss, B. D. (2006). Socio-
economic background modulates cognition-achievement rela-
tionships in reading. Cognitive Development,21(3), 349368.
https://doi.org/10.1016/j.cogdev.2006.01.007
Park, S., Stone, S. I., & Holloway, S. D. (2017). School-based parental
involvement as a predictor of achievement and school learning
environment: an elementary school-level analysis. Children &
Youth Services Review,82, 195206
Paula,J.S.,Leite,I.C.,Almeida,A.B.,Ambrosano,G.M.,Pereira,
A.C.,&Mialhe,F.L.(2012).Theinuence of oral health
conditions, socioeconomic status and home environment factors
on schoolchildrens self-perception of quality of life. Health
Quality Life Outcomes,10,6https://doi.org/10.1186/1477-
7525-10-6
Peng, N., Wang, L., & Wang, L. (2005a). A study of life among
primary and secondary school students in Shanghai. Chinese
Journal of School Health,26(4), 265268
Peng, N., Wang, L., & Wang, L. (2005b). A study on quality of life
among primary and secondary school students in Shanghai.
Chinese Journal of School Health,26(4), 265268
Poulain, T., Vogel, M., & Kiess, W. (2020). Review on the role of
socioeconomic status in child health and development. Current
Opinion in pediatrics,32(2), 308314
Ran, M., Peng, L., Liu, Q., Pender, M., He, F., & Wang, H. (2018).
The association between quality of life (QOL) and health literacy
among junior middle school students: a cross-sectional study.
BMC Public Health,18(1), 1183
Rashid, V., Engberink, M. F., van Eijsden, M., Nicolaou, M., Dek-
ker, L. H., & Verhoeff, A. P. (2018). Ethnicity and socio-
economic status are related to dietary patterns at age 5 in the
Amsterdam born children and their development (ABCD)
cohort. BMC Public Health,18(1), 115 https://doi.org/10.1186/
s12889-017-5014-0
Roubinov, D. S., & Boyce, W. T. (2017). Parenting and SES: relative
values or enduring principles? Current Opinion in Psychology,
15, 162167
Rowland, A. S., Skipper, B. J., Rabiner, D. L., Qeadan, F., Campbell,
R. A., & Naftel, A. J. (2018). Attention-decit/hyperactivity
disorder (ADHD): interaction between socioeconomic status and
parental history of ADHD determines prevalence. Journal Child
Psychology Psychiatry,59(3), 213222. https://doi.org/10.1111/
jcpp.12775
Russell, A. E., Ford, T., & Russell, G. (2018). The relationship
between nancial difculty and childhood symptoms of attention
decit/hyperactivity disorder: a UK longitudinal cohort study.
Social Psychiatry and Psychiatric Epidemiology,53(1), 3344.
https://doi.org/10.1007/s00127-017-1453-2
Saldiva, S.R., Venancio, S.I., de Santana, A.C., da Silva Castro, A.L.,
Escuder, M.M., & Giugliani, E.R. (2014). The consumption of
unhealthy foods by Brazilian children is inuenced by their
mothers educational level. Nutrition Journal, 13(33). https://doi.
org/10.1186/1475-2891-13-33
Sharif, I., & Sargent, J. D. (2006). Association between television,
movie, and video game exposure and school performance.
Pediatrics,118(4), e10611070. https://doi.org/10.1542/peds.
2005-2854
Shen, H., Li, H., & Xu, Y. (2004). Survey on quality of life in Suzhou.
Chinese School Medicine,18(6), 497498
Shonkoff,E.T.,Dunton,G.F.,Chou,C.P.,Leventhal,A.M.,
Bluthenthal, R., & Pentz, M. A. (2017). Direct and indirect
effects of parent stress on child obesity risk and added sugar
intake in a sample of Southern California adolescents. Public
Health Nutrition,20(18), 32853294. https://doi.org/10.1017/
s136898001700252x
Sohr-Preston, S. L., Scaramella, L. V., Martin, M. J., Neppl, T. K.,
Ontai, L., & Conger, R. (2013). Parental socioeconomic status,
communication, and childrens vocabulary development: a
third-generation test of the family investment model. Child
Development,84(3), 10461062. https://doi.org/10.1111/cdev.
12023
1426 Journal of Child and Family Studies (2021) 30:14161427
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Sun, Z., Zou, L., Zhang, J., Mo, S., Shao, S., & Zhong, R. (2013).
Prevalence and associated risk factors of dyslexic children in a
middle-sized city of China: a cross-sectional study. PLoS One,8
(2), e56688. https://doi.org/10.1371/journal.pone.0056688
Tavakol, M., & Dennick, R. (2011). Making sense of Cronbachs
alpha. International Journal of Medical Education,2,5355.
https://doi.org/10.5116/ijme.4dfb.8dfd
Wang, C., Wu, J., & Zhao, W. (2007). Health-related quality of life
among school-aged children and its association with family
environment. Chinese Journal of School Health,28(5), 423425
Wang, Q., Wang, X., & Peng, J. (2013). Relationship of learning
disabilities with both dietary patterns and dietary behaviors in
children. Chinese Journal of Child Health Care,21(2), 141143
Wu, H., Liu, P., & Meng, H. (2006a). Norm, reliability and validity of
children and adolescentsQOL Scale. Chinese Journal of School
Health,27(1), 1821.
Wu, H., Li, P., & Meng, H. (2006b). Norm, reliability and validity of
children and adolescentsQOL Scale. Chinese Journal of School
Health,27(1), 1021
Wu, H. R., Song, R. R., & Yao, B. (2006c). The establishment of
dyslexia checklist for Chinese children. Chinese Journal of
School Health,27(3), 189190
Zou, R., Niu, G., Chen, W., Fan, C., Tian, Y., & Sun, X. (2018).
Socioeconomic inequality and life satisfaction in late childhood
and adolescence: a moderated mediation model. Social Indicators
Research,136(9), 114
Journal of Child and Family Studies (2021) 30:14161427 1427
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
1.
2.
3.
4.
5.
6.
Terms and Conditions
Springer Nature journal content, brought to you courtesy of Springer Nature Customer Service Center GmbH (“Springer Nature”).
Springer Nature supports a reasonable amount of sharing of research papers by authors, subscribers and authorised users (“Users”), for small-
scale personal, non-commercial use provided that all copyright, trade and service marks and other proprietary notices are maintained. By
accessing, sharing, receiving or otherwise using the Springer Nature journal content you agree to these terms of use (“Terms”). For these
purposes, Springer Nature considers academic use (by researchers and students) to be non-commercial.
These Terms are supplementary and will apply in addition to any applicable website terms and conditions, a relevant site licence or a personal
subscription. These Terms will prevail over any conflict or ambiguity with regards to the relevant terms, a site licence or a personal subscription
(to the extent of the conflict or ambiguity only). For Creative Commons-licensed articles, the terms of the Creative Commons license used will
apply.
We collect and use personal data to provide access to the Springer Nature journal content. We may also use these personal data internally within
ResearchGate and Springer Nature and as agreed share it, in an anonymised way, for purposes of tracking, analysis and reporting. We will not
otherwise disclose your personal data outside the ResearchGate or the Springer Nature group of companies unless we have your permission as
detailed in the Privacy Policy.
While Users may use the Springer Nature journal content for small scale, personal non-commercial use, it is important to note that Users may
not:
use such content for the purpose of providing other users with access on a regular or large scale basis or as a means to circumvent access
control;
use such content where to do so would be considered a criminal or statutory offence in any jurisdiction, or gives rise to civil liability, or is
otherwise unlawful;
falsely or misleadingly imply or suggest endorsement, approval , sponsorship, or association unless explicitly agreed to by Springer Nature in
writing;
use bots or other automated methods to access the content or redirect messages
override any security feature or exclusionary protocol; or
share the content in order to create substitute for Springer Nature products or services or a systematic database of Springer Nature journal
content.
In line with the restriction against commercial use, Springer Nature does not permit the creation of a product or service that creates revenue,
royalties, rent or income from our content or its inclusion as part of a paid for service or for other commercial gain. Springer Nature journal
content cannot be used for inter-library loans and librarians may not upload Springer Nature journal content on a large scale into their, or any
other, institutional repository.
These terms of use are reviewed regularly and may be amended at any time. Springer Nature is not obligated to publish any information or
content on this website and may remove it or features or functionality at our sole discretion, at any time with or without notice. Springer Nature
may revoke this licence to you at any time and remove access to any copies of the Springer Nature journal content which have been saved.
To the fullest extent permitted by law, Springer Nature makes no warranties, representations or guarantees to Users, either express or implied
with respect to the Springer nature journal content and all parties disclaim and waive any implied warranties or warranties imposed by law,
including merchantability or fitness for any particular purpose.
Please note that these rights do not automatically extend to content, data or other material published by Springer Nature that may be licensed
from third parties.
If you would like to use or distribute our Springer Nature journal content to a wider audience or on a regular basis or in any other manner not
expressly permitted by these Terms, please contact Springer Nature at
onlineservice@springernature.com
... Among children, previous reports show that socio-economic inequalities in HRQoL could partially be explained by variations in parenting practices and parental mental health [24,25]. Finally, one study conducted in China found that dietary behaviours and the home literacy environment mediated the association between socio-economic conditions and quality of life among participants aged 9 to 14 years old [26]. However, to the best of our knowledge, research examining both psychosocial and behavioural mediators of socio-economic disparities in HRQoL specifically among children is lacking. ...
... We showed that psychosocial risk factors mediated about 25% of socio-economic inequalities in health-related quality of life among children, while health behaviours did not play a role. To the best of our knowledge, these are the first analyses of this kind focused specifically on children [16,26]. Our findings thus contribute to a more comprehensive understanding of health inequalities by providing empirical evidence for the pathways linking socio-economic conditions to quality of life among children [7]. ...
Article
Full-text available
Background The present analysis aimed to assess the mediating role of psychosocial and behavioural factors in socio-economic inequalities in health-related quality of life (HRQoL) among children and adolescents. Methods Cross-sectional data was drawn from the randomly selected SEROCoV-KIDS cohort study in Geneva, Switzerland. Associations of socio-economic conditions (parents’ highest education, household financial situation) with HRQoL, psychosocial (parent–child relationship, school difficulties, friends, extracurricular activities) and behavioural factors (screen time, physical activity, green spaces time, sleep duration), along with associations of psychosocial and behavioural factors with HRQoL, were evaluated with generalized estimating equations. Counterfactual mediation analyses were conducted to test pathways linking socio-economic conditions to HRQoL. Results Of 965 children and 816 adolescents, those with disadvantaged financial circumstances were more likely to have a poor HRQoL (adjusted Odds Ratio [aOR]: 3.80; 95% confidence interval [CI]: 1.96–7.36 and aOR: 3.66; 95%CI: 2.06–6.52, respectively). Psychosocial characteristics mediated 25% (95%CI: 5–70%) and 40% (95%CI: 18–63%) of financial disparities in HRQoL among children and adolescents, respectively. Health behaviours were weakly patterned by socio-economic conditions and did not contribute to financial differences in HRQoL. Conclusions These findings provide empirical evidence for mechanisms explaining socio-economic disparities in child HRQoL and could inform interventions aimed to tackle health inequalities.
... Perceiving the importance of English as a global language, nowadays parents are encouraging children's English communication skills and supporting it in various ways (Farida et al., 2024). The favourable physical and social elements of the home environment and parents support psychologically aid in the development of young students' cognitive abilities, language development (Choudhury et al., 2024;Dong & Chow, 2022;Huang et al., 2021) and literacy skills (Wahyuni & Tin, 2024;Bigozzi et al., 2023;Romero-González et al., 2023). ...
Article
Full-text available
A child’s ‘home’ is believed to be their first educational institution. The home environment is composed of both physical and psychological elements. Before going to school, children learn all of their formal, informal, and moral information at home. The child acquires languages to communicate with others in addition to a variety of other abilities. A conducive home environment not only helps students learn the English language but also improves their overall academic achievement. The present study aimed to find out the influence of the home environment on students’ achievement in English. The researcher has adopted a systematic literature review method, under which articles from the last four years (2020-2024) were reviewed and analysed. The findings of the study showed a positive impact of a favourable home environment and its various factors on students’ achievement in English. The researcher also found students’ academic achievement was negatively impacted by many factors i.e., low socio-economic status, parents’ strictness, less participation of parents, etc.
... Additionally, smoking has been found to negatively impact QOL as it adversely affects sleep quality and is associated with higher anxiety and depression levels [18,19]. Finally, family atmosphere and high family income have been found to contribute to high QOL, as families with high incomes may have the time and financial resources to provide better investments, safer homes, and greater support to their offspring than those with low incomes [20,21]. ...
Article
Full-text available
Aim: The aim of this study was to assess the quality of life (QOL) and its influencing factors among healthcare college students in Riyadh, Saudi Arabia. Methods: A cross-sectional study was conducted among healthcare students at King Saud University. A modified version of the Arabic World Health Organization Quality of Life-BREF (WHOQOL-BREF) questionnaire, including 25 questions, was used to assess students’ QOL. Data were collected through an online survey and analyzed using IBM SPSS Statistics version 26 (IBM Corp., Armonk, NY). Descriptive and regression statistics were used. Results: A total of 547 healthcare students completed the questionnaire during the data collection period. Of all the students, 39.7% were from applied medical college, 62.5% were females, 98.9% were single, and 91.8% were non-smokers. Regarding academic status, 58.3% did not participate in any extracurricular activity, 42.6% had an academic advisor, and 80.4% had a grade point average (GPA) higher than 4.1. The average QOL score across all domains was moderately good (60.30 ± 16.0), whereas the physical domain showed the poorest score (46.89 ± 14.8) while the environmental domain had the greatest score (68.04 ± 20.6). The environmental domain was the only domain that showed significant differences between healthcare colleges (p < 0.001). Moreover, students who were male (p = 0.009), non-smokers (p = 0.023), reported living with family/friends (p = 0.031), and from families with high monthly income (p < 0.001) had significantly higher environmental QOL scores than their counterparts. Conclusions: The study found that healthcare students had moderately good mean QOL scores. The environmental domain was the only QOL domain that showed significant differences between healthcare colleges with the greatest score among medical college students. Gender, smoking status, residence status, and family monthly income were found to have a strong association with students’ environmental QOL scores. Institutions need to focus on the regular measurement of students' QOL, which facilitates implementing strategies that can promote their overall QOL and subsequently positively impact their performance academically and practically.
... Parent socio-demographic characteristics (e.g., income and educational level) may also affect adolescents' healthrelated outcomes. For example, lower family income and lower parents' education levels are associated with a higher risk of obesity, lower fitness levels, and lower quality of life among adolescents (Huang et al., 2021). In addition to socio-demographic characteristics, acculturation may also impact adolescents' health status. ...
Article
Full-text available
Previous studies have suggested the impact of intervention fidelity on the management and prevention of chronic diseases; however, little is known about the effect of the contributing determinants (at multiple levels of influence) that can impact health-related interventions intending to improve the health status of Hispanic adolescents with overweight or obesity. The current study aimed to assess whether fidelity (i.e., dosage and quality of the program delivery), acculturation (i.e., orientation to the American culture, retention of Hispanic cultural values), and individual-level socio-demographic characteristics (i.e., income, education) predict changes in family processes (e.g., parent control), which in turn may affect adolescent health-related outcomes including body mass index (BMI), physical activity, dietary intake, and adolescents' health-related quality of life. A pathway analysis model was utilized to explore the study variables among 140 Hispanic parent-adolescent dyads randomized to Familias Unidas Health and Wellness (FUHW) intervention. Results indicated that fidelity was significantly associated with changes in parent-adolescent communication, parent monitoring, limit-setting, and control. Parents' education was associated with changes in parent limit-setting, and parent Hispanicism was associated with changes in parent limit-setting and discipline. The examination between family processes and adolescent health outcomes revealed that parents' higher discipline and improved communication with their adolescents were significantly associated with improved adolescents' quality of life, and parent control was positively associated with physical activity and negatively associated with BMI in adolescents. Our findings demonstrated the significant contribution of intervention fidelity and participants' characteristics in parenting strategies leading to adolescents' health outcomes to prevent obesity-related chronic diseases. Future research is needed to investigate the effect of environmental and organizational factors on the delivery of the intervention materials.
... School life of primary and middle school students has a large impact on students' well-being. Student quality of life was directly affected by difficulty with homework (Huang et al., 2021). A survey of elementary school students found that 34.5% of students felt that the most distracting thing in their studies was the amount of homework (Li & Li, 2012). ...
Article
Full-text available
Children’s psychological well-being is critical for students’ school performance and mental health. This study developed the Chinese Children’s Subjective Well-being Scale and explored an appropriate strategy to improve children’s subjective well-being from the collaboration between school and home perspective. Based on a literature review, focus group interviews, expert validity, factor structure and confirmatory factor analysis, this study developed the Chinese Children’s Subjective Well-being Scale. We then enrolled 289 grade 3–6 students from a public primary school in southeastern China to conduct multiple linear regression analysis. The Chinese Children’s Subjective Well-being Scale had good reliability and validity. Homework anxiety was negatively associated with subjective well-being (β = -0.21. p = 0.011). Family interaction and support improved subjective well-being. Less parental supervision and family conflict could buffer the negative effect of homework anxiety on subjective well-being. The Chinese Children’s Subjective Well-being Scale can be used with primary school students in China. This study also recommended that governments and education practitioners focus on optimizing collaboration between school and home to improve children’s subjective well-being by reducing their homework anxiety and increasing the harmonious family atmosphere (more family interaction and support and less parental supervision and family conflict).
... In addition, family SES plays a part for children's physical well-being, parent relations and home life, and perceived financial resources (Von Rueden et al., 2006). What's more, empirical evidence has shown that SES can not only directly, but also indirectly influence children's well-being through parenting factors like parenting practices (Huang et al., 2021). Therefore, this study tends to analyze the relationship between child quality of life and SES. ...
Article
Full-text available
It is well-documented that child quality of life is associated with family socio-economic status (SES). However, few studies have examined the potential mediating effects of different types of parenting practices between the two variables. The current study aims to examine the influences of SES and parenting practices on child quality of life and the mediating effects of parenting practices on the relationship between SES and child quality of life in the context of China. A total of 1,401 children aged 8–14 and 1,401 parents were involved in a cross-sectional survey in Shanghai, China. Pediatric Quality of Life Generic Core Scales and Alabama parenting questionnaire were used to measure child quality of life and parenting practices. Family SES was assessed by self-reported family monthly income and parental education level. Multivariate regression analysis was conducted to examine the associations among SES, parenting practices and child quality of life. The direct and indirect relationship between SES and quality of life were examined as well. The results have shown that a higher level of SES and positive involvement are associated with better child quality of life while deficient monitoring is negatively associated. Besides, parents’ positive involvement acts as a full mediator between SES and child quality of life, while deficient monitoring acts as a partial mediator. These findings have given implications for future studies, interventions, and policy making. For social workers, education of positive parenting strategies should be provided to parents with low SES. For policy makers, programs should be designed to improve parenting skills in current China.
... Socioeconomic status (SES), which is usually measured by the family income and maternal education level, is documented to be strongly associated with children's cognitive development (Huang et al., 2021;Lambert et al., 2017;Lynn, 1990;Sheridan et al., 2017). Unfortunately, due to various reasons (e.g., language barrier and legal restrictions) many refugee families go through financial difficulties and live in poor conditions in the country of resettlement (UNHCR, 2014; UN, 2014). ...
Article
Full-text available
War trauma is often accompanied by poor living conditions in the new environment in a manner preserving or even deteriorating the negative influences of war. Several researchers have investigated the refugee experiences of displaced children. Often they have focused on the detrimental effects of war on psychological well-being, mental health, educational settings, social adaptation, quality of nutrition, financial difficulties, safety and language learning experiences. Each of these effects has been proven to negatively affect cognitive abilities; however, the current study reviews the key studies to reveal the cognitive and linguistic outcomes of holding refugee status in the early childhood period. Doing this, we aim to reveal the adverse conditions that affect refugee children’s three core abilities of executive functions, namely working memory, inhibitory control and shifting. In addition to cognitive outcomes, we present the factors that may affect these children’s mother tongue development and their experiences with the language spoken in the host country in the context of schooling. This study suggests that refugee children should be assessed for their cognitive and language abilities after arriving in the country of resettlement so that their needs can be identified and addressed effectively. Caretakers should also be given both psychological and financial support to enrich their children’s language and cognitive input. Also, the outcomes of the research in this field should be effectively shared with different stakeholders from the caregivers and teachers of the refugee children to the NGOs and policymakers responsible to take solid actions to counter the adverse effects of displacement.
Article
The present study introduces systematic data on the cognitive and linguistic abilities of refugee children. We tested 9–10 year-old Syrian refugee children (N = 25) on their cognitive abilities (i.e., working memory, shifting, inhibitory control, and fluid intelligence) and vocabulary knowledge in Arabic and Turkish. We compared their performance to two non-refugee control groups with low socioeconomic status, matched on age and mother’s education: Arabic-Turkish bilinguals (N = 29) and Turkish monolinguals (N = 19). Refugee children lagged behind both non-refugee groups in the fluid intelligence task. Compared to their bilingual peers, they showed poorer performance in working memory and shifting tasks. On the other hand, these scores matched their monolingual peers, with only slower performance in the shifting task. Greater exposure to trauma and poverty were predictors for lower scores in refugee children’s cognitive tasks. On the language tests, refugee children exhibited a smaller Turkish vocabulary size compared to both non-refugee controls. Trauma exposure, poverty and kindergarten attendance factors were significant predictors for this difference. As for the Arabic language skills, Syrian children outperformed their bilingual peers in Arabic. Although Syrian children displayed a more balanced bilingual profile, their performance in their dominant language (Arabic) was poorer than the bilingual control group’s performance in their dominant language (Turkish). Overall, the results suggest that refugee children’s working memory, shifting and fluid intelligence abilities, as well as mother tongue development, were negatively affected by forced displacement, but they were able to develop Turkish vocabulary skills and match Turkish monolinguals on both working memory and shifting abilities. This is the first piece of evidence suggesting that while being a refugee has adverse effects on children’s cognitive and linguistic development, holding bilingual status may actually create a protective shield in some cognitive abilities for disadvantaged refugee children.
Article
Full-text available
Abstract Background Lower health literacy is associated with poor quality of life (QOL) among patients with chronic disease; little is known about this relationship among the general population, especially for child and adolescent. To fill this gap, this paper aimed to investigate the association between health literacy and QOL in junior middle school students, and explore how QOL varies by health literacy. Methods An anonymous cross-sectional survey was conducted among junior middle school students (aged 12–15) from Shapingba district, Chongqing in China, and participants were recruited using stratified cluster sampling. Health literacy and QOL were measured using two validated scales, and quantified using a five-point Likert scale with health literacy classified as low, medium, or high. We used multivariable logistic regression to test adjusted association between health literacy and QOL. Results A total of 1774 junior middle school students were evaluated, with the mean age was 13.8 ± 1.0 and of whom 905 (51.0%) were male. About 25.5% of the research subjects had a low health literacy. When controlling for age, grade, family structure and other covariates, highest discrimination was found among participants with low to high health literacy. Overall, Students who equipped with higher health literacy was associated with greater QOL (P
Article
Full-text available
The study on developmental dyslexia (DD) has fairly matured in the past decades, even when there is a lack of a standardized and convenient instrument for dyslexia in the Chinese population. The purpose of this study was to assess the reliability and validity of the Dyslexia Checklist for Chinese Children (DCCC), which was administered to Chinese students in primary school. A total of 545 students from grades 2 through 6 were recruited in Wuhan to participate in this study. We used confirmatory factor analysis (CFA) to evaluate the structure validity of the DCCC. Concurrent validity was determined via correlations between the DCCC and the verbal comprehension index (VCI), and Chinese achievement. The reliability of the DCCC was assessed via test-retest reliability and internal consistency. The CFA suggested that the first order model with eight factors and 55 items fit the data well (RMSEA = 0.057, CFI = 0.930, and TLI = 0.925). The DCCC was negatively associated with VCI (r = −0.218) and Chinese achievement (r = −0.372). The test-retest reliability of the DCCC was 0.734, and the internal consistency of all subscales was above 0.752. The DCCC thus proved to have adequate validity and reliability to screen Chinese dyslexia among students in grades 2 through 6.
Article
Full-text available
Abstract Background Health inequalities are already present at young age and tend to vary with ethnicity and socioeconomic status (SES). Diet is a major determinant of overweight, and studying dietary patterns as a whole in relation to overweight rather than single nutrients or foods has been suggested. We derived dietary patterns at age 5 and determined whether ethnicity and SES were both related to these dietary patterns. Methods We analysed 2769 validated Food Frequency Questionnaires filled in by mothers of children (5.7 ± 0.5y) in the Amsterdam Born Children and their Development (ABCD) cohort. Food items were reduced to 41 food groups. Energy adjusted intake per food group (g/d) was used to derive dietary patterns using Principal Component Analysis and children were given a pattern score for each dietary pattern. We defined 5 ethnic groups (Dutch, Surinamese, Turkish, Moroccan, other ethnicities) and 3 SES groups (low, middle, high, based on maternal education). Multivariate ANOVA, with adjustment for age, gender and maternal age, was used to test potential associations between ethnicity or SES and dietary pattern scores. Post-hoc analyses with Bonferroni adjustment were used to examine differences between groups. Results Principal Component Analysis identified 4 dietary patterns: a snacking, full-fat, meat and healthy dietary pattern, explaining 21% of the variation in dietary intake. Ethnicity was related to the dietary pattern scores (p
Article
Full-text available
Objective Using a short-term longitudinal design, this study examined the concurrent and longitudinal relationships among familial socioeconomic status (SES; i.e., family income and maternal and paternal education levels), marital conflict (i.e., constructive and destructive marital conflict), parenting practices (i.e., positive and negative parenting practices), child social competence (i.e., social skills), and child behavioral adjustment (i.e., internalizing and externalizing problems) in a comprehensive model. Methods The sample included a total of 1604 preschoolers aged 5 years at Time 1 and first graders aged 6 years at Time 2 (51.5% male). Parents completed a self-reported questionnaire regarding their SES, marital conflict, parenting practices, and their children’s behavioral adjustment. Teachers also evaluated the children’s social competence. ResultsThe path analysis results revealed that Time 1 family income and maternal and paternal education levels were respectively related to Time 1 social skills and Time 2 internalizing and externalizing problems, both directly and indirectly, through their influence on destructive and constructive marital conflict, as well as negative and positive parenting practices. Notably, after controlling for Time 1 behavioral problems as mediating mechanisms in the link between family factors (i.e., SES, marital conflict, and parenting practices) and behavioral adjustment, Time 1 social skills significantly and inversely influenced both the internalization and externalization of problems at Time 2. Conclusions The merit of examining SES, marital conflict, and parenting practices as multidimensional constructs is discussed in relation to an understanding of processes and pathways within families that affect child mental health functioning. The results suggest social competence, which is influenced by the multidimensional constructs of family factors, may prove protective in reducing the risk of child maladjustment, especially for children who are socioeconomically disadvantaged.
Article
Full-text available
Background: In children the relationship between a healthy diet and psychosocial well-being has not been fully explored and the existing evidence is inconsistent. This study investigates the chronology of the association between children's adherence to healthy dietary guidelines and their well-being, with special attention to the influence of weight status on the association. Methods: Seven thousand six hundred seventy five children 2 to 9 years old from the eight-country cohort study IDEFICS were investigated. They were first examined between September 2007 and June 2008 and re-examined again 2 years later. Psychosocial well-being was measured using self-esteem and parent relations questions from the KINDL® and emotional and peer problems from the Strengths and Difficulties Questionnaire. A Healthy Dietary Adherence Score (HDAS) was calculated from a 43-item food frequency questionnaire as a measure of the degree to which children's dietary intake follows nutrition guidelines. The analysis employed multilevel logistic regression (country as random effect) with bidirectional modeling of dichotomous dietary and well-being variables as both exposures and outcomes while controlling for respective baseline values. Results: A higher HDAS at baseline was associated with better self-esteem (OR 1.2, 95% CI 1.0;1.4) and fewer emotional and peer problems (OR 1.2, 95% CI 1.1;1.3 and OR 1.3, 95% CI 1.2;1.4) 2 years later. For the reversed direction, better self-esteem was associated with higher HDAS 2 years later (OR 1.1 95% CI 1.0;1.29). The analysis stratified by weight status revealed that the associations between higher HDAS at baseline and better well-being at follow-up were similar in both normal weight and overweight children. Conclusion: Present findings suggest a bidirectional relation between diet quality and self-esteem. Additionally, higher adherence to healthy dietary guidelines at baseline was associated with fewer emotional and peer problems at follow-up, independent of children's weight status.
Article
Full-text available
Purpose: Attention deficit/hyperactivity disorder (ADHD) is associated with socioeconomic status (SES), in that children who grow up in low SES families are at an increased risk of ADHD symptoms and diagnosis. The current study explores whether different levels of ADHD symptoms are associated with prior changes in the SES facet of financial difficulty. Methods: Using the Avon Longitudinal Study of Parents and Children (ALSPAC), we examined symptoms of ADHD measured by the Strengths and Difficulties Questionnaire (SDQ) hyperactivity subscale in relation to parent-reported changes in financial difficulty, grouped into four repeated measures at four time points across childhood; (n = 6416). A multilevel mixed-effects linear regression model with an unstructured covariance matrix was used to test whether different patterns of financial difficulty were associated with subsequent changes in ADHD symptoms. Results: Families who had no financial difficulty had children with a lower average ADHD symptom score than groups who experienced financial difficulty. Children whose families stayed in financial difficulty had higher mean ADHD symptom scores than all other groups (No difficulty mean SDQ hyperactivity 3.14, 95% CI 3.07, 3.21, In difficulty mean SDQ hyperactivity 3.39, 95% CI 3.28, 3.45, p < 0.001). Increasing or decreasing financial difficulty predicted mean symptom scores lower than those of the in difficulty group and higher than the no difficulty group. Conclusions: Our findings contribute to the building evidence that SES may influence the severity and/or impairment associated with the symptoms of ADHD, however the effects of SES are small and have limited clinical significance.
Article
Full-text available
Objectives This study examined the associations of parental socioeconomic status (SES) with preschoolers’ objectively measured sedentary time (SED) over the course of a week and with parent-reported children’s screen and reading times at home as indicators of sedentary behaviours (SB). Design Cross-sectional. Setting In years 2015 and 2016 in Finland. Participants 864 children, aged 3–6 years, with their parents. Outcome measures Children’s accelerometer data were transformed into average SED minutes per hour in different contexts (preschool, home during preschool days, weekend and total). Parent-reported children’s screen and reading times were expressed as average daily minutes. The SES indicators (maternal and paternal education and relative household income) were grouped into three categories. Linear or logistic regression analyses were used, with municipality, season, and children’s gender and age as covariates. CIs were adjusted for clustering at the preschool group level. Results Children with low maternal (β=17.21, 95% CI: 8.71 to 25.71) and paternal (β=10.54, 95% CI: 0.77 to 20.30) education had more overall screen time at home than their more advantaged counterparts. SES differences in overall screen time were mostly explained by TV viewing. Children with low as opposed to high maternal education (β=−2.66, 95% CI: −4.95 to –0.38) had less reading time at home. Children whose fathers were on the middle (β=−1.15, 95% CI: −2.01 to –0.29) educational level had less weekend SED than those with high paternal education. Otherwise, parental SES was not related to objectively measured SED. Conclusions The results of this study highlight the fact that the associations between parental SES and preschoolers’ SB are dependent on the indicators of SES and SBs, and vary between different contexts. Generally, parental SES was not associated with SED, whereas some SES differences existed in screen time and reading time at home. Interventions aiming to diminish SES differences in children’s SB should focus on home hours. Trial registration number ISRCTN57165350.
Article
Full-text available
Purpose: Numerous studies have documented that lower socioeconomic status (SES) is associated with increased mental health problems in children. One proposed pathway for this association has been differential exposure to accumulated risk factors in children of lower SES. The aim of the current study was to investigate the socioeconomic distribution of exposure to negative life events and family stress and to examine the direct and interactive association between lower SES and exposure to life events and family stress in relation with mental health problems. Methods: Using cross-sectional data from the second wave of the Bergen Child Study (conducted in 2006), the current study investigated the association between lower SES and exposure to negative life events, family life stressors, and mental health problems in a sample of 2043 Norwegian 11-13 years and their parents. Information about mental health was self-reported by the children using the Strengths and Difficulties Questionnaire, whereas information about SES and exposure to negative life events and family stressors were provided by their parents. Results: The findings showed that lower SES was associated with more symptoms of emotional-, conduct-, hyperactivity/inattention-, and peer problems and that exposure to life events and family stress explained some of this association (10-29% of the total effects). Conclusions: Low SES and higher prevalence of negative life events and family stressors were associated with more symptoms of mental health problems. Overall, the effect sizes were smaller than previous investigations (f (2)s = 0.015-0.031), perhaps suggesting a buffering effect of the social safety net in place in Norway.
Article
Purpose of review: This review presents findings from recent studies investigating the role of socioeconomic status (SES) in child development. Studies on associations between SES and different parameters of physical and psychological health, on interventions and possible resilience factors are reviewed. Recent findings: Several cross-sectional and longitudinal studies demonstrate social disparities in child behavior and health. They underline the detrimental effects of low SES on child development. Some studies also highlight the potentially adverse effects of early diseases or vulnerabilities on later career and social position. Whereas most studies applied parent-based measures of SES, some studies emphasize the significance of child-based (e.g. perceived social position) and area-level indicators of SES (e.g. area deprivation). With respect to intervention, study findings suggest positive effects of programs aiming to improve specific neighborhood characteristics and psychosocial functioning of individuals. Summary: The relation between SES and health is bidirectional and stable, and the effects of interventions aiming at changing behaviors of children and families with low SES are small. There is a need for further center-based and area-level interventions and studies evaluating the effects of these interventions.
Article
This study aimed to examine the relationship between socioeconomic status and children’s psychological well-being and to investigate the mediating effect of family social capital. A sample of 19,487 school-aged children was collected from 2013–2014 China Education Panel Survey. Structural equation modeling was applied to test the hypothesized model. The results showed that socioeconomic status was not significantly related to the children’s psychological well-being. However, two indicators of family social capital, namely, parent involvement and parent–child relationship, played a complete mediating role in the direct mechanism. The theoretical and practical contributions were discussed.