Content uploaded by Jay Saha
Author content
All content in this area was uploaded by Jay Saha on Sep 01, 2022
Content may be subject to copyright.
Citation: Saha, J.; Chouhan, P.;
Ahmed, F.; Ghosh, T.; Mondal, S.;
Shahid, M.; Fatima, S.; Tang, K.
Overweight/Obesity Prevalence
among Under-Five Children and Risk
Factors in India: A Cross-Sectional
Study Using the National Family
Health Survey (2015–2016). Nutrients
2022,14, 3621. https://doi.org/
10.3390/nu14173621
Academic Editor: Sara Baldassano
Received: 31 July 2022
Accepted: 30 August 2022
Published: 1 September 2022
Publisher’s Note: MDPI stays neutral
with regard to jurisdictional claims in
published maps and institutional affil-
iations.
Copyright: © 2022 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
nutrients
Article
Overweight/Obesity Prevalence among Under-Five Children
and Risk Factors in India: A Cross-Sectional Study Using the
National Family Health Survey (2015–2016)
Jay Saha 1, Pradip Chouhan 1, Farooq Ahmed 2,3,* , Tanmoy Ghosh 1, Sabbir Mondal 1, Muhammad Shahid 2,4 ,
Saireen Fatima 5and Kun Tang 2,*
1Department of Geography, University of Gour Banga (UGB), Malda 732103, West Bengal, India
2Vanke School of Public Health, Tsinghua University, Beijing 100029, China
3Department of Anthropology, Quaid-i-Azam University, Islamabad 44000, Pakistan
4School of Insurance and Economics, University of International Business and Economics (UIBE),
Beijing 100029, China
5Fazaia Medical College, Air University, Islamabad 44000, Pakistan
*Correspondence: jam007@uw.edu (F.A.); tangk@tsinghua.edu.cn (K.T.); Tel.: +86-13671129425 (K.T.)
Abstract:
The occurrence of overweight and obesity has increased in recent years in India. In this
study, we investigate the prevalence and associated risk factors of overweight/obesity among chil-
dren aged 0–59 months in India. Using data from the 2015–2016 National Family Health
Survey-4
(NFHS-4),
the research sample included 176,255 children aged 0 to 59 months. Bivariate and multi-
variate techniques were used to analyze children’s risk factors for overweight/obesity. We identified
that the prevalence of overweight/obesity among children aged 0–59 was 2.6% in India. The study
findings reveal that factors such as child sex, age, birth weight, birth rank, maternal education,
number of children, age at marriage, mother’s BMI, media exposure, social group, and dietary
diversity score were most significantly correlated with childhood overweight and obesity in India.
Furthermore, we found that male children (ARR: 1.08) aged between 0 and 11 months (ARR: 3.77)
with low birth rank (ARR: 1.24), obese (ARR: 1.81) children whose mothers married after the age
of 18 (ARR: 1.15), children who belong to a scheduled tribe family (ARR: 1.46), and children who
consumed 7–9 food items (ARR: 1.22) were at highest risk of being overweight and obese. However,
breastfeeding (ARR: 0.85) and Muslim families (ARR: 0.87) appeared to be protective factors with
respect to childhood overweight and obesity in India. Pertinent public health programs, clinical
follow-up, and awareness about sedentary lifestyles can help to reduce overweight/obesity risks
in children.
Keywords: overweight/obesity risk; under-five children; dietary diversity; NFHS; India
1. Introduction
Childhood obesity and overweight were initially considered a disease in developed
countries with higher per capita income [
1
]. Overweight is defined as excess body weight
relative to height, whereas obesity refers to surplus body fat [
2
]. According to the World
Health Organization (WHO), when body mass index (BMI) is more than 25, the situation is
denoted as overweight, and a BMI of more than 30 is considered an obesity condition [
3
].
The burden of overweight and obesity among children has increased, becoming a global
public health concern [
4
,
5
]. In developing countries with emerging economies, the in-
creasing trend of overweight and obesity among children poses a significant challenge
to the healthcare system [
6
]. The occurrence of overweight and obesity is higher in de-
veloped countries than in developing countries [
7
]. The prevalence of childhood obesity
has increased in developed countries. However, obesity prevalence is also increasing in
developing countries [
8
]. The conditions of overweight and obesity primarily occur due to
Nutrients 2022,14, 3621. https://doi.org/10.3390/nu14173621 https://www.mdpi.com/journal/nutrients
Nutrients 2022,14, 3621 2 of 18
energy imbalances between calories consumed, calories exhausted, and excessive calorie
intake or insufficient physical activity. Childhood overweight/obesity is a precursor to
metabolic syndrome, poor physical health, mental disorders, respiratory problems, and
glucose intolerance, which can continue into adulthood [
9
]. Childhood overweight and
obesity are determined mainly by insufficient nutrition, physical inactivity, high socioe-
conomic status, urban residency, traditional beliefs, and marketing of transitional food
companies [7,10].
Childhood overweight/obesity is a significant public health concern in the 21st cen-
tury. At the global level, many middle- and low-income countries are affected by over-
weight/obesity, particularly in urban areas [
8
]. According to the WHO, approximately
39 million under-five-year-old children are overweight or obese [
3
]. Globally, childhood
overweight and obesity are associated with more deaths than childhood underweight
conditions. Worldwide, overweight/obesity is considered the fifth leading mortality risk
factor, now representing a global epidemic. According to Global Burden of Disease 2017,
more than four million people die annually as a result of being overweight or obese [4].
On average, 60% of children suffering from overweight/obesity have at least one
additional risk factor for cardiovascular diseases, such as hypertension, hyperlipidemia,
or hyperinsulinemia [
11
]. The risk factor for developing abnormal lipid profiles is high
among children with overweight/obesity [
12
,
13
]. In obese children, high blood pressure
is three times greater than in non-obese or normal children [
14
–
16
]. A cluster of non-
communicable diseases and unhealthy lifestyles described as “lifestyle syndrome” or “new
world syndrome” has been observed due to the rapid advancement of urbanization and
expanding demographic trends [10].
In India, a dual burden has been observed whereby children and adolescents suffer
from obesity or overweight on the one hand and malnourishment or underweight on
the other hand [
17
]. The Global Burden of Disease (GBD) report shows that in India, the
predominance of overweight children aged 2 to 4 years was 11.5% in 2017 [
4
]. The tendency
of children to be overweight in India increased significantly between 2010 and 2017 and is
projected to increase to 17.5% by 2030 [
4
]. The occurrence of overweight among children in
India has increased from 1.6% (2006) to 3.8% (2020) [
18
]. According to the NFHS report,
the prevalence of overweight children under five years of age has increased from 2.1%
(2015–2016) to 3.4% (2019–2021).
More than 14.4 million children are obese in India, the second-highest rate globally,
behind China [
4
]. Various studies have suggested possible reasons for the increasing
trends of overweight/obesity among children in India. Possible explanations include
insufficient physical activity, increased television screen time, urban residency, and family
social status [
19
–
24
]. Further research is required to examine global health issues, such as
child obesity/overweight, among young children to protect them from future consequences.
Significant differences in overweight/obesity prevalence can be observed according to
various factors among under-five children in India. Significant differences have been
reported in countrywide representative studies on nutritional status in India according
to sociodemographic and household characteristics, as well as dietary characteristics.
Therefore, the present research aims to investigate and identify the prevalence of overweight
or obesity among Indian children under five years of age, as well as sociodemographic and
household risk factors.
2. Materials and Methods
2.1. Study Design and Sampling Weights
Data were taken from the fourth round of the NFHS conducted in 2015–2016, a cross-
sectional national representative survey to estimate overweight/obesity and its associated
factors among children under five years of age. The NFHS 2015–2016 was conducted under
the stewardship of India’s Ministry of Health and Family Welfare (MoHFW), with coordi-
nation and technical guidance provided by the International Institute of Population Science
(IIPS), Mumbai. The countrywide representative sample survey provides comprehensive
Nutrients 2022,14, 3621 3 of 18
data on women’s health, child health, and family planning. The NFHS-4 includes data from
a population-representative sample of 699,686 women aged 15–49 years and
112,122 men
aged 15–54 from 601,509 households. The response rates for women and men were 97%
and 92%, respectively. Municipal corporation offices provided a list of 28,586 clusters
for this stratified sample (20,509 clusters in rural areas, 8397 clusters in urban areas, and
130 clusters
in slums). Sampling weights are necessary for any analysis using the NFHS-4
data to ensure the representativeness of the survey results at the national and domain levels
due to the non-proportional allocation of the sample to the different survey domains and
urban and rural areas [
25
]. Because the NFHS-4 sample is a two-stage stratified cluster
sample, sampling weights were determined using independent sampling probabilities for
each stage and each cluster. The NFHS-4 report of India includes further information on
the sampling technique.
2.2. Study Participants
In the study sample, a total of 259,627 under-five children were born in the last
five years
(n= 259,627), of which 83,372 children were excluded: 11,884 due to death;
children of multiparous mothers (n= 3393); children whose weight/height data were not
recorded
(n= 11,138);
those whose height/age were outside of reasonable limits
(n= 1185);
flagged cases (n= 10,071); children whose/height data were <2SD (n= 45,598) from the
median of the reference population, considered acutely malnourished; and children who
lived elsewhere without their mother (n= 103) (Figure 1). The height and weight of children
between the ages of 0 and 59 months were assessed. The weight of children was determined
using a Seca 874 digital scale. A Seca 213 stadiometer was used to measure children’s
height between the ages of 24 and 59 months [
25
]. The recumbent length of children
younger than two years old or with a height of less than 85 cm was measured with a Seca
417 infantometer.
Children with height-for-age Z scores <
−
6 SD or >+6 SD, weight-for-age
Z scores <
−
6 SD or >+5 SD, or weight-for-height Z scores <
−
5 SD or >+5 SD were flagged
as having invalid data [
25
]. Ultimately, 176,255 children aged younger than 59 months were
selected for this study (Figure 1). A total of 5130 children were found to be overweight
or obese, and these children were included in the study analysis. The remainder of the
children (n= 171,125) were considered normal-weight children.
2.3. Outcome Characteristics
The study’s outcome variable, child overweight or obesity between 0 and 59 months,
assessed sociodemographic and household characteristics based on children’s body mass
index Z scores. According to the WHO, a child with a BMI Z score >2SD is considered
overweight and obese with a BMI Z score >3 SD [
26
,
27
]. In our study, children with a BMI
Z score of more than 2 (>2SD) were considered overweight/obese, and those with a BMI Z
score in the range of
−
2 to +2 were classified as normal-weight children. In this study, we
dichotomized the binary variable into two categories: normal children, coded as “0”; and
overweight/obese children, coded as “1”.
2.4. Explanatory Characteristics
We considered independent variables of sociodemographic and household character-
istics (child, maternal, and household-level factors). Child-level factors included child sex
(male and female), child’s age in months (0–11, 12–23, 24–35, 36–47, and 48–59 months),
birth weight (<2.5 kg = low and
≥
2.5 kg = normal), currently breastfeeding (no and yes),
and birth rank (1, 2, 3, and 4+). Maternal factors included maternal education, comprising
four categories (illiterate, primary, secondary, and higher), age at marriage (<18 years
and
≥
18 years), and the number of children (
≥
4 and <4). Maternal BMI was categorized
into three classes (thin (<18.5 kg/m
2
), normal (18.5–24.9 kg/m
2
), and overweight/obese
(>25 kg/m2)).
Maternal BMI is determined by dividing a woman’s weight in kilograms
by their height in square meters (kg/m
2
) [
25
]. Finally, the household- or community-
level factors were divided into the following categories: place of residence (rural and
Nutrients 2022,14, 3621 4 of 18
urban), region (categorized into six subdivisions: North: Punjab, Himachal Pradesh, Ut-
tarakhand, Haryana, Chandigarh, Rajasthan, Jammu and Kashmir, and Delhi; Central:
Madhya Pradesh, Chhattisgarh, and Uttar Pradesh; East: West Bengal, Bihar, Jharkhand,
and Odisha; Northeast: Nagaland, Assam, Manipur, Mizoram, Meghalaya, Tripura, and
Sikkim; West: Goa, Dadra and Nagar Haveli, Maharashtra, Daman and Diu, and Gujrat;
and South: Andhra Pradesh, Karnataka, Kerala, Telangana, Tamil Nadu, Lakshadweep,
and Puducherry) [
25
], social groups (Scheduled Caste, Scheduled Tribe, Other Backward
Classes, and other), religious belief (Hindu, Muslim, and other), and wealth quintile
(poorest, poorer, middle, richer, and richest).
Nutrients 2022, 14, x FOR PEER REVIEW 4 of 19
Figure 1. Flow diagram showing children aged 0 to 59 months included in the study for analyses
from the 2015–16 NFHS-4, India.
2.3. Outcome Characteristics
The study’s outcome variable, child overweight or obesity between 0 and 59 months,
assessed sociodemographic and household characteristics based on children’s body mass
index Z scores. According to the WHO, a child with a BMI Z score >2SD is considered
overweight and obese with a BMI Z score > 3 SD [26,27]. In our study, children with a BMI
Z score of more than 2 (>2SD) were considered overweight/obese, and those with a BMI
Z score in the range of −2 to +2 were classified as normal-weight children. In this study,
we dichotomized the binary variable into two categories: normal children, coded as “0”;
and overweight/obese children, coded as “1”.
2.4. Explanatory Characteristics
We considered independent variables of sociodemographic and household
characteristics (child, maternal, and household-level factors). Child-level factors included
child sex (male and female), child’s age in months (0–11, 12–23, 24–35, 36–47, and 48–59
months), birth weight (<2.5 kg = low and ≥2.5 kg = normal), currently breastfeeding (no
Figure 1.
Flow diagram showing children aged 0 to 59 months included in the study for analyses
from the 2015–2016 NFHS-4, India.
Nutrients 2022,14, 3621 5 of 18
Explanation of Explanatory Variables
Dietary Diversity Score (DDS): In the NFHS-4, dietary diversity was assessed immedi-
ately based on the number of food groups consumed within the last 24 h [
25
]. Expenditure
information was collected on 21 different types of food eaten by children the day before
data collection. These foods were initially divided into nine categories: milk or curd, pulses
or beans, fruits, eggs, fish, chicken or meat, fried food, dark-green leafy vegetables, and
aerated drinks [
25
]. Based on the data on food consumption (never/rarely, daily, and
weekly), a dietary diversity score was calculated and divided into three categories: 3 food
items (children who consumed 3 of 9 foods), 4–6 food items (children who consumed 4–6
of 9 foods), and 7–9 food items.
Exposure to media: The frequency of reading newspapers and magazines, watching
television, and listening to the radio each week was used as a proxy for media exposure.
Based on these three media categories, mothers were classified into three groups: low
exposure (uses at least one of these media at least once a week), medium exposure (uses
any two of these media at least once a week), and high exposure (uses at least three of these
media at least once a week).
Wealth quintile: The household wealth quintile is a score of economic well-being
based on housing properties and sustainable product ownership [
28
]. Based on these
scores measured by principal component analysis, household wealth is categorized into
five levels: poorest, poorer, middle, richer, and richest. Each level corresponds to 20% of
the respondents, ranging from 1 (poorest) to 5 (richest).
2.5. Statistical Analyses
Bivariate and multivariate techniques were used to analyze the association between
childhood overweight/obesity and sociodemographic, household, and dietary character-
istics. The data were also examined using descriptive statistics. We first calculated the
proportion of overweight/obese children and that of normal children. The frequency
and percentage of the study variable were determined using descriptive statistics as the
next step. Pearson’s chi-square tests were used in bivariate analysis to determine the
sociodemographic and household characteristics associated with the prevalence of over-
weight/obesity and the significant level across the independent variables. Binary logistic
regression models were used to assess the unadjusted risk ratio (URR) and adjusted risk
ratio (ARR) with 95% confidence intervals (C.I.s) between childhood overweight/obesity
and sociodemographic and household characteristics. The ARR was controlled for the sex
of the child, the child’s age, currently breastfeeding, birth rank, mother’s educational level,
age at marriage, mother’s BMI, place of residence, region, social group, religious beliefs,
wealth quintile, and dietary diversity score. Data analyses were executed with STATA 12.1
version (StataCorp L.P., Lakeway Drive, College Station, TX, USA).
3. Results
3.1. Children in Pairs from Different Sociodemographic and Household Characteristics in India
Sociodemographic and household characteristics of children aged 0–59 months and
their mothers are depicted in Table 1. Approximately 2.6% of the total sample population
was found to have childhood overweight/obesity. The majority of children in the sample
were aged between 36 and 47 months. Approximately 85% of children had a normal
birth weight (
≥
2.5 kg), and more than two-thirds of children were currently breastfeeding.
The most common birth rank was first or second. Nearly one-third of women had no
educational attainment. More than 40% of women were married before the age of 18, and
one-third of mothers had more than four children. The body mass index (BMI) of more
than 60% of mothers was normal. Only 7% of women were fully exposed to mass media.
Most of the children were members of OBCs (46.6%), belonging to the Hindu (78.3%),
living in rural areas (71.9%), and from central (27.7%) and eastern (25.8%) regions of India.
A large portion of the children were members of the poorest (24.1%) and poorer (21.9%)
wealth quintiles.
Nutrients 2022,14, 3621 6 of 18
Table 1. Sociodemographic and household characteristics (n= 176,255).
Characteristics Frequency (n) Percentage (%)
Child’s BMI
Overweight/obesity 5130 2.6
Normal 171,125 97.4
Child characteristics
Sex of child
Male 90,091 51.4
Female 86,164 48.7
Child age in months
0–11 29,822 16.4
12–23 35,174 20.1
24–35 35,833 20.6
36–47 38,474 22.0
48–59 36,952 21.0
Birth weight
Low (<2.5 kg) 20,056 15.5
Normal (≥2.5 kg) 113,125 84.5
Currently breastfeeding
No 61,722 36.4
Yes 114,533 63.6
Birth rank
1 65,979 38.9
2 54,663 32.3
3 27,968 15.1
4+ 27,645 13.7
Mother Characteristics
Mother’s level of education
Illiterate 52,295 29
Primary 25,666 14.1
Secondary 81,248 46.1
Higher 17,046 10.8
Age at marriage
<18 years 65,608 40.7
≥18 years 107,334 59.3
Number of children
≥4 34,496 17.3
<4 141,759 82.7
Mother’s BMI
Thin 38,518 23.2
Normal 110,440 60.7
Overweight/obese 26,673 16.1
Media exposure
Low 113,679 64.5
Medium 49,609 28.4
High 12,967 7.1
Household/community-level factors
Place of residence
Rural 133,644 71.9
Urban 42,611 28.1
Region
North 33,769 13.4
Central 51,135 27.7
East 35,662 25.8
Northeast 27,462 3.8
West 11,187 11.6
South 17,040 17.7
Nutrients 2022,14, 3621 7 of 18
Table 1. Cont.
Characteristics Frequency (n) Percentage (%)
Social group
SC 32,843 22.6
ST 34,349 10.0
OBC 69,164 46.6
Other 31,782 20.8
Religious belief
Hindu 125,550 78.3
Muslim 28,333 16.9
Other 22,259 4.8
Wealth quintile
Poorest 43,257 24.1
Poorer 41,557 21.9
Middle 35,981 20.2
Richer 30,509 18.7
Richest 24,951 15.1
3.2. Dietary Characteristics of Children in India
Table 2represents the dietary characteristics of children aged 0–59 months. A sig-
nificant portion of children consumed milk or curd (42.3%), pulses or beans (44.6%), and
dark-green leafy vegetables (46.7%) every day, and nearly all of the children rarely/never
ate fruits (58.2%), eggs (59.2%), fish (66.8%), chicken or meat (67.8%), fried food (55.3%),
and aerated drinks (78.6%).
Table 2. Dietary characteristics of the sample population (n= 176,255).
Characteristics Frequency (n) Percentage (%)
Dietary characteristics of children
Food items eaten
Milk or curd
Never/rarely 68,494 34.2
Daily 66,574 42.3
Weekly 41,187 23.5
Pulses or beans
Never/rarely 22,819 10.1
Daily 73,236 44.6
Weekly 80,200 45.3
Dark-green leafy vegetables
Never/rarely 26,940 15.0
Daily 84,856 46.7
Weekly 64,459 38.3
Fruits
Never/rarely 106,496 58.2
Daily 16,516 10.5
Weekly 53,243 31.3
Eggs
Never/rarely 111,601 59.2
Daily 5774 4.0
Weekly 58,880 36.8
Fish
Never/rarely 123,552 66.8
Daily 6528 4.8
Weekly 46,175 28.4
Chicken or meat
Never/rarely 122,997 67.8
Daily 2237 1.1
Weekly 51,021 31.1
Nutrients 2022,14, 3621 8 of 18
Table 2. Cont.
Characteristics Frequency (n) Percentage (%)
Fried food
Never/rarely 97,131 55.3
Daily 19,589 8.9
Weekly 59,535 35.8
Aerated drinks
Never/rarely 139,822 78.6
Daily 7258 4.0
Weekly 29,175 17.5
3.3. Prevalence of Overweight/Obesity by Sociodemographic and Household Characteristics of
Under-Five Children in India
The prevalence of overweight/obesity relative to socioeconomic and household char-
acteristics of under-five children in India is depicted in Table 3. The prevalence of childhood
overweight/obesity was found to be significantly higher in the following groups: age of
0–11 months (5.8%), normal birth weight (2.9%), currently breastfeeding (2.7%), and lower
birth rank (3%). There was statistically significant variation in childhood overweight or
obesity with respect to sex (p= 0.006). The rate of obesity/overweight was significantly
higher in children with mothers with higher educational qualifications (4.7%), who were
married after the age of 18 (3.1%), had fewer children (2.8%), were obese (3.4%), and fully
exposed to mass media (4%). The prevalence of overweight/obesity was significantly
higher among children residing in urban areas (3.4%), southern regions (3.6%), scheduled
tribes (2.9%), belonging to other communities (3.1%), and living in households belonging
to the richest wealth quintile (4.1%).
Table 3.
Prevalence of overweight/obesity by sociodemographic and household characteristics of
under-five children in India (n= 176,255).
Characteristics Overweight/Obese
Children (Row %)
Normal Children
(Row %)
Pearson’s χ2
Value p-Value
Child characteristics
Sex of child 7.5 0.006
Male 2.7 97.3
Female 2.6 97.4
Child age in months 1900 <0.001
0–11 5.8 94.3
12–23 2.4 97.6
24–35 1.8 98.2
36–47 1.8 98.2
48–59 2 98
Birth weight 28.7 <0.001
Low (<2.5 kg) 2.3 97.7
Normal (≥2.5 kg) 2.9 97.1
Currently breastfeeding 64.5 <0.001
No 2.5 97.6
Yes 2.7 97.3
Birth rank 63.4 <0.001
1 3 97.1
2 2.7 97.4
3 2.5 97.6
4+ 1.8 98.2
Mother characteristics
Mother’s level of education 213.5 <0.001
Illiterate 2 98
Primary 2.1 97.9
Nutrients 2022,14, 3621 9 of 18
Table 3. Cont.
Characteristics Overweight/Obese
Children (Row %)
Normal Children
(Row %)
Pearson’s χ2
Value p-Value
Secondary 2.7 97.3
Higher 4.7 95.3
Age at marriage 177.3 <0.001
<18 years 2 98.1
≥18 years 3.1 96.9
Number of children 82.3 <0.001
≥4 1.7 98.3
<4 2.8 97.2
Mother’s BMI 276.9 <0.001
Thin 1.6 98.4
Normal 2.8 97.2
Overweight/obese 3.4 96.7
Media exposure 106.2 <0.001
Low 2.3 97.7
Medium 3.1 96.9
High 4 96
Household/community-level factors
Place of residence 47.3 <0.001
Rural 2.3 97.7
Urban 3.4 96.6
Region 417 <0.001
North 3.2 96.8
Central 2.1 97.9
East 2.1 97.9
Northeast 3.3 96.8
West 2.6 97.4
South 3.6 96.4
Social group 182.6 <0.001
SC 2.4 97.7
ST 2.9 97.1
OBC 2.6 97.4
Other 2.9 97.1
Religious belief 146.9 <0.001
Hindu 2.6 97.4
Muslim 2.4 97.7
Other 3.1 96.9
Wealth quintile 106.2 <0.001
Poorest 1.9 98.1
Poorer 2.1 97.9
Middle 2.5 97.5
Richer 3.1 96.9
Richest 4.1 95.9
Note: Data from NFHS-4, India, 2015–2016. Percentages were computed by applying sample weights.
3.4. Prevalence of Overweight/Obesity According to Dietary Characteristics of Under-Five Children
in India
Table 4illustrates the analyses of the causes of overweight/obesity by dietary char-
acteristics of under-five children in India. Children who consumed milk or curd (3.1%),
pulses or beans (2.8%), dark-green leafy vegetables (3%), fruits (3.6%), eggs (3.5%), fish
(3.3%), chicken or meat (3.6%), fried food (3.3%), and aerated drinks (3.6%) daily were more
susceptible to overweight/obesity.
Nutrients 2022,14, 3621 10 of 18
Table 4.
Prevalence of overweight/obesity according to dietary characteristics of under-five children
in India (n= 176,255).
Characteristics Overweight/Obese
Children (Row %)
Normal Children
(Row %)
Pearson’s χ2
Value p-Value
Dietary characteristics of children
Food items eaten
Milk or curd 59.9 <0.001
Never/rarely 2.1 97.9
Daily 3.1 96.9
Weekly 2.5 97.5
Pulses or beans 28.7 <0.001
Never/rarely 2.8 97.2
Daily 2.8 97.2
Weekly 2.4 97.6
Dark-green leafy vegetables 72.0 <0.001
Never/rarely 2.1 98.0
Daily 3.0 97.1
Weekly 2.4 97.6
Fruits 85.3 <0.001
Never/rarely 2.4 97.7
Daily 3.6 96.4
Weekly 2.8 97.2
Eggs 76.8 <0.001
Never/rarely 2.4 97.6
Daily 3.5 96.5
Weekly 2.8 97.2
Fish 42.1 <0.001
Never/rarely 2.4 97.6
Daily 3.3 96.7
Weekly 3.0 97.0
Chicken or meat 57.6 <0.001
Never/rarely 2.5 97.5
Daily 3.6 96.4
Weekly 2.9 97.1
Fried food 29.6 <0.001
Never/rarely 2.5 97.5
Daily 3.3 96.7
Weekly 2.6 97.4
Aerated drinks 17.0 <0.001
Never/rarely 2.5 97.5
Daily 3.6 96.4
Weekly 2.8 97.3
Note: Data from NFHS-4, India, 2015–2016. Percentages were computed by applying sample weights.
3.5. Factors Associated with Childhood Overweight/Obesity in India
Table 5shows the associations between study variables and childhood overweight/
obesity among children aged 0–59 months. Male children had an increased risk of being
overweight or obese relative to female children (ARR: 1.08 and 95% CI: 1.02–1.14). Children
aged 0–11 months had a 3.7 times higher chance of being overweight/obese than children
aged 48–59 months (ARR: 3.77 and 95% CI: 3.41–4.16). Normal birth weight was associated
with 1.3 times increased probability of being overweight/obese relative to lower birth
weight (LBW) (URR: 1.30 and 95% CI: 1.18–1.43). Children who were currently breastfeed-
ing were at a lower risk of being overweight or obese than non-breastfeeding children
(ARR: 0.85 and 95% CI: 0.79–0.92). The risk of overweight or obesity was 1.2 times higher
among first-born children (ARR: 1.24 and 95% CI: 1.12–1.38). The unadjusted regression
model identified a significant relationship between the educational status of mothers and
childhood overweight or obesity. Our analysis also revealed that the likelihood of having
an overweight or obese child was increased in mothers with a higher educational level rela-
Nutrients 2022,14, 3621 11 of 18
tive to that of illiterate mothers. However, this association was not statistically significant
(p= 0.1).
Table 5. Factors associated with childhood overweight/obesity in India, NFHS, 2015–2016.
Characteristics Unadjusted Risk Ratio (URR)—
95% CI
Adjusted Risk Ratio (ARR)—
95% CI
Sex of child
Male 1.08 *** (1.02–1.14) 1.079 ** (1.02–1.14)
Female † 1 1
Child age in months
0–11 3.38 *** (3.12–3.70) 3.77 *** (3.41–4.16)
12–23 1.36 *** (1.24–1.50) 1.47 *** (1.33–1.64)
24–35 0.88 ** (0.80–0.98) 0.89 ** (0.80–0.99)
36–47 0.91 * (0.82–1.01) 0.94 (0.85–1.05)
48–59† 1 1
Birth weight
Low (<2.5 kg) † 1
Normal (≥2.5 kg) 1.30 *** (1.18–1.43)
Currently breastfeeding
No † 1 1
Yes 1.28 *** (1.21–1.36) 0.85 *** (0.79–0.92)
Birth rank
1 1.42 *** (1.30–1.56) 1.24 *** (1.12–1.38)
2 1.28 *** (1.16–1.41) 1.12 ** (1.01–1.25)
3 1.21 *** (1.09–1.34) 1.16 *** (1.04–1.30)
4+ † 1 1
Mother’s level of education
Illiterate † 1 1
Primary 1.09 * (0.99–1.20) 0.98 (0.88–1.09)
Secondary 1.29 *** (1.20–1.38) 0.93 (0.85–1.02)
Higher 1.92 *** (1.75–2.11) 1.11 * (0.98–1.26)
Number of children
≥4 † 1
<4 1.44 *** (1.33–1.55)
Age at marriage
<18 years † 1 1
≥18 years 1.52 *** (1.43–1.62) 1.15 *** (1.08–1.24)
Mother’s BMI
Thin† 1 1
Normal 1.90 *** (1.75–2.07) 1.70 *** (1.56–1.86)
Overweight/obese 2.19 *** (1.98–2.42) 1.81 *** (1.62–2.02)
Media exposure
Low † 1
Medium 1.30 *** (1.22–1.38)
High 1.46 *** (1.33–1.61)
Place of residence
Rural † 1 1
Urban 1.24 *** (1.17–1.321) 1.06 (0.98–1.14)
Region
North † 1 1
Central 0.61 *** (0.56–0.66) 0.67 *** (0.614–0.737)
East 0.60 *** (0.55–0.66) 0.69 *** (0.616–0.762)
Northeast 1.18 *** (1.09–1.29) 1.07 (0.956–1.202)
West 0.75 *** (0.65–0.84) 0.75 *** (0.649–0.857)
South 1.10 ** (1.00–1.22) 1.07 (0.956–1.194)
Social group
SC † 1 1
ST 1.66 *** (1.48–1.77) 1.46 *** (1.31–1.62)
OBC 1.04 (0.96–1.13) 1.05 (0.96–1.15)
Other 1.32 *** (1.20–1.45) 1.15 *** (1.04–1.27)
Nutrients 2022,14, 3621 12 of 18
Table 5. Cont.
Characteristics Unadjusted Risk Ratio (URR)—
95% CI
Adjusted Risk Ratio (ARR)—
95% CI
Religious belief
Hindu † 1 1
Muslim 0.99 (0.91–1.07) 0.87 *** (0.79–0.96)
Other 1.56 *** (1.45–1.68) 0.94 (0.85–1.05)
Wealth quintile
Poorest † 1 1
Poorer 1.02 (0.93–1.11) 0.84 *** (0.76–0.93)
Middle 1.29 *** (1.18–1.40) 0.98 (0.88–1.09)
Richer 1.38 *** (1.27–1.51) 0.97 (0.87–1.09)
Richest 1.72 *** (1.58–1.88) 1.07 (0.94–1.22)
Dietary diversity score
<3 food items † 1 1
4–6 food items 1.14 *** (1.07–1.22) 1.00 (0.94–1.08)
7–9 food items 1.47 *** (1.36–1.58) 1.22 *** (1.12–1.34)
Constant 0.01 ***(0.00952–0.0135)
Pseudo R2 0.05
Log-likelihood −20281.044
Probability χ2<0.001
Mean VIF for ARR model 1.74
*** if p< 0.01, ** if p< 0.05, * if p< 0.1. CI= confidence interval,
†
= reference category, VIF = variance
inflation factor.
Children from families with fewer than four siblings had 1.44 times increased chances
of being overweight or obese relative to children from families with four or more siblings.
The odds of overweight or obesity were more than one time higher among children whose
mothers were married after the age of 18 (ARR: 1.15 and 95% CI: 1.08–1.24) and obese
(ARR: 1.81 and 95% CI: 1.62–2.02). The prevalence of overweight or obesity was 1.46 times
increased among children whose mothers were fully engaged in mass media. Children
living in urban areas in the north-eastern and southern regions among those who belonged
to other communities and the richest household quintile had a higher probability of being
overweight or obese than other children. However, the adjusted table did not show that
this association was statistically significant. In terms of social category, children belonging
to a scheduled tribe had 1.4 times increased possibility of being overweight compared to
children belonging to a scheduled caste (ARR: 1.46 and 95% CI: 1.31–1.62), and children
from families with Muslim religious beliefs had a lower prevalence of overweight/obesity
than children from Hindu families (ARR: 0.87 and 95% CI: 0.79–0.96). Children who
consumed 7–9 food items had an increased chance of overweight/obesity as compared to
children who consumed <3 food items (ARR: 1.22 and 95% CI: 1.12–1.34) (Table 5).
4. Discussion
In the present study, we examined the incidence of overweight and obesity among
children in India, as well as the contributing factors. According to the survey, 2.6% of
Indian children under five years of age were obese or overweight. Compared with other
South Asian countries, childhood overweight/obesity was found to be higher in India
(2.8%) than in Bangladesh (1.6%) and Nepal (1.4%) and lower than in Maldives (5.4%)
and Pakistan (4.9%) [
26
]. Overweight/obesity among under-five children in India was
significantly associated with sex, age, birth weight, birth rank, number of children, age at
marriage, mother’s BMI, maternal education, media exposure, social groups, and dietary
diversity score.
The study results reveal that male children were more likely to be overweight or obese
than female children. This results of the present study are also compatible with evidence
from Ethiopia [
27
], Ghana [
29
], Nepal [
30
], Pakistan [
31
], Cameroon [
32
], China [
33
], and
Brazil [
34
]. However, our findings contradicts those of other research showing that female
Nutrients 2022,14, 3621 13 of 18
children were more likely to be overweight/obese than male children [
35
,
36
] or that sex had
no considerable influence on overweight or obesity in children [
37
]. These contradictory
results may be a result of genetic and environmental factors [
27
], calorie intake, physical
activity behaviors [38,39], and social and individual psychology [40].
We found that younger children had an increased probability of being overweight or
obese relative to their older counterparts. Previous studies carried out in Indonesia [
41
],
Cameroon [
32
], and Malaysia [
42
] showed similar results. This phenomenon could be
explained by the fact that young children who are fed formula instead of breast milk might
become more overweight or obese than older children [43].
A significant association was also revealed between breastfeeding and childhood
overweight in the present study. Children who were currently breastfeeding had a lower
probability of being overweight or obese than non-breastfeeding children. These findings
are consistent with those of previous research from the United States [
44
], China [
45
], and
Denmark [
46
]. It is possible that breast milk supplies a moderate amount of calories and
nutrients for children, such as sugar, water, protein, and fat [
45
,
47
], which can protect
against childhood overweight or obesity.
First-born children were more likely to be overweight or obese compared to children
with a higher birth rank (4+) in India. Few researchers have studied the link between birth
rank and childhood obesity at an early age. This result is consistent with the results of
an investigation in Ethiopia [
27
,
32
]. Children with a birth rank of 1–3 were more likely to
be overweight/obese than children with a birth rank of >3, according to a cross-sectional
examination of 4518 Cameroonian children aged 6–59 months.
A significant determinant of childhood overweight or obesity is maternal education.
In India, mothers with higher levels of education had a higher risk of having overweight or
obese children. Similar findings were reported in studies in Saudi Arabia [
48
], China [
49
],
Kazakhstan [
50
], Nepal [
30
], and Bangladesh [
31
]. The following factors may explain this
result: children from well-educated households may consume more protein, have higher
dietary diversity and increased energy and fat intake, and be more likely to have high levels
of lipoprotein in their blood, which might cause them to become overweight or obese [
35
].
Moreover, educated mothers are more likely to be employed, which could mean that they
pay less attention to or observe their children’s physical activity or sitting behavior, such
as watching television, less than unemployed mothers, which significantly increases their
BMI and obesity [
51
]. Furthermore, we found that mothers with higher levels of education
tended to feed their children different food and consume unnecessary nutrients, which
may increase the risk of their children being overweight or obese [52].
In the present study, we examined the significant impact that maternal age at marriage
had on childhood obesity/overweight in Indian children aged 0–59 months. The odds
ratios show that children whose mothers were married after the age of 18 were more likely
to be overweight or obese. Children of older mothers or those who married after the age of
18 were more likely to be obese or overweight. [
53
]. We were not able to clearly interpret
this finding; however, a possible explanation is that mothers married at an older age began
investing more in their careers, which reduced mother-child interactions and gave them
less time to monitor their children’s physical activity, which may lead to their children
being overweight or obese.
Another prominent covariate is the mother’s BMI, which has been strongly associated
with childhood overweight or obesity. In the current study, children whose mothers
were overweight/obese had a higher risk of becoming overweight or obese than those
whose mothers were underweight or thin. Numerous studies have reported maternal
BMI as a risk factor for childhood obesity [
54
,
55
]. This might be explained by the fact
that the evidence of epigenetic processes in the uterus, including DNA methylation and
changes in the intestinal microbiome, contributes to obesity in children [
56
]. Excessive
lifestyle exposure (socioeconomic status, food production, marketing, food scarcity, and
an obese environment) promote unhealthy behaviors, to which some individuals are
susceptible [
57
,
58
]. For example, it is possible that mothers were exposed to such complex
Nutrients 2022,14, 3621 14 of 18
factors, which contributed to the development of their obesity. In such a case, their children
would be more likely to be exposed to the same complex factors, increasing the growth of
the uterus and the tendency toward obesity [54].
Our findings are consistent with trends that have been identified in developing coun-
tries, but the relations did not remain significant upon multidisciplinary analysis. Children
with urban residences were more overweight than rural children in India. However, the
adjusted risk ratio was not significant. This result is consistent with those reported in a
previous study in Cameroon [
32
]. Several studies have reported a significant association
between childhood overweight and place of residence. Furthermore, overweight children
have been reported to more often live in urban areas than rural areas. This finding is in line
with those of studies conducted in Peru [59], Poland [60], China [33], and Hawaii [61].
The present study also highlights a strong association between region and childhood
overweight/obesity. The odds of being overweight were almost 1.07 times higher in north-
eastern and southern India than in northern India. However, this association was not
statistically significant. Overweight rates were two times higher in northern and eastern
India than in other regions [
17
]. Similarly, a higher prevalence of overweight was observed
in north-eastern and southern India than in other regions [
62
], which could be explained
by the higher socioeconomic status of these regions, which may be affected by rapid
urbanization and a reduction in the number of urban playgrounds, which may lead to a
sedentary lifestyle for children.
The present study also highlights the increased risk of childhood overweight or
obesity among scheduled tribe families compared to scheduled caste families. No previous
research has examined such an association, possibly ignoring the direct influence of social
groups on the development of childhood overweight and obesity. A high accumulation of
body fat percentage was observed among Indian tribes [
63
]. Because most tribes are still
untouchable, these outcomes can be partially explained by the lack of healthcare awareness
and vaccination confidence [64].
Multivariate analysis has shown a weaker protective effect on children overweight/
obese of Muslim religion than Hindu religion in India. A previous study in Cameroon [
32
]
reported that Muslim families might protect their children against being overweight,
possibly due to parental choices with respect to a child’s diet that may be influenced by
religion. In other words, religion can affect eating habits as a result of adherence to rules
that separate religious groups [65].
With respect to the relationship between the dietary diversity score and childhood
obesity or overweight, we observed a significant gradual increase in the risk of being
overweight or obese among children who consumed 7–9 food items daily in India. This
result is similar to the results of studies on children in Iran [
66
], Saudi Arabia [
67
], and
the Dongcheng District of Beijing [
68
]. The dietary diversity score increased in tandem
with the percentage consumption of most food groups, leading to excessive energy intake
and obesity [
69
]. Higher dietary diversity scores were related to increased energy intake,
increased consumption of all three components of micronutrients (vitamin A, iodine, and
iron), and increased risk of obesity/overweight [
70
]. Higher dietary diversity scores were
also associated with daily consumption of several foods, such as curd or milk, pulses or
beans, fish, eggs, fruits, chicken or meat, vegetable, fried food, and aerated drinks, which
may lead to increased energy accretion and an increased probability of being overweight or
obese among children aged 0–59 months in India.
Strengths and Weaknesses of the Research
This study has several strengths. The nationally representative data used for respon-
dent selection and the multilevel sampling method reinforce the study results [
25
], to a
large extent, increasing the generalizability of our results for all children aged 0–59 months
in India. This study highlights the dietary intake of children and related problems. Despite
having its strengths, this study is also subject to some significant limitations. We were
unable to determine the causal relationship between the predictive variable and explana-
Nutrients 2022,14, 3621 15 of 18
tory variables due to the cross-sectional nature of the data, which may have distorted our
estimates or resulted in the absence of an association. Another limitation is that this analysis
did not include all possible sociodemographic and household variables. The present study
explains some sociodemographic and household characteristics of overweight or obesity
among Indian children under the age of under-five, but it cannot account for factors related
to physical activities or children’s lifestyles. We have superscribed this limitation to address
the corresponding bias through a verified data imputation method.
5. Conclusions
In the present study, we examined the sociodemographic and household factors as-
sociated with overweight or obesity among under-five children in India. Risk factors of
overweight include being a male child, having a high birth weight, being aged between
0–23 months,
and having a low birth rank, whereas breastfeeding protects against over-
weight or obesity among children between 0 and 59 months of age. The likelihood of being
overweight or obese, having children with more than four siblings, getting married after
turning 18, and increased media exposure were also higher in children whose mothers had
higher levels of education. This study also indicates a high prevalence of early childhood
overweight, with significant disparities between dietary diversity scores and scheduled
tribe families in India. However, Muslim families appeared to be a protective factor against
childhood overweight/obesity. In terms of preventative strategies, parents should focus on
advocacy campaigns to reduce excess weight and obesity and strengthen clinical measures,
such as antenatal weight gain monitoring, which could help to counteract overweight or
obese children in later life. Further studies, i.e., nutrition education studies on feeding
practice and physical activity, should be conducted in higher socioeconomic environments.
The government should clinically follow up with children with high birth weight in an
effort to prevent later childhood overweight. More studies are needed to investigate other
possible risk factors linked to the increase in childhood overweight or obesity in India.
Author Contributions:
Conceptualization, J.S.; methodology, J.S. and P.C.; formal analysis, J.S. and
F.A.; investigation, J.S., P.C., T.G. and S.M.; resources, F.A.; data curation, J.S.; supervision, P.C. and
F.A.; project administration, P.C.; writing—original draft preparation, J.S. and F.A.; writing—review
and editing, F.A., P.C., T.G., S.M., M.S., S.F. and K.T. All authors have read and agreed to the published
version of the manuscript.
Funding: This research received no external funding.
Institutional Review Board Statement:
The International Institute for Population Sciences (IIPS),
Mumbai, provided ethical clearance for the National Family Health Survey (NFHS-4). The Inner City
Fund (ICF) International Review Board (IRB) examined and approved this work. Respondents were
provided written permission to take part in the survey.
Informed Consent Statement:
The current investigation relied on secondary data that was freely
accessible in the public domain. There is no identifying information about the survey participants in
the dataset. As a result, no ethical clearance was necessary to perform this research.
Data Availability Statement:
The general datasets are accessible through the Demographic Health
Surveys (DHS) repository. The data used in this work are accessible upon reasonable request from
the first author.
Acknowledgments:
The authors are grateful to the International Institute for Population Sciences
(IIPS), Mumbai, for providing access to the data used in this work.
Conflicts of Interest: The authors declare no conflict of interest.
References
1.
Gupta, N.; Shah, P.; Nayyar, S.; Misra, A. Childhood obesity and the metabolic syndrome in developing countries. Indian J. Pediatr.
2013,80, 28–37. [CrossRef]
2.
National Institutes of Health, National Heart, Lung, and Blood Institute. Disease and Conditions Index: What Are Overweight and
Obesity? National Institutes of Health, National Heart, Lung, and Blood Institute: Bethesda, MD, USA, 2010.
Nutrients 2022,14, 3621 16 of 18
3. WHO. Obesity. Available online: https://www.who.int/health-topics/obesity#tab=tab_1 (accessed on 6 February 2022).
4.
GBD Obesity Collaborators. Health Effects of Overweight and Obesity in 195 Countries over 25 Years. N. Engl. J. Med.
2017
,
377, 13–27. [CrossRef] [PubMed]
5.
Shawon, M.S.R.; Hossain, F.B.; Thomson, B.; Adhikary, G.; Chowdhury, A.; Chowdhury, R.; Townsend, N. Trends in the prevalence
of overweight among Bangladeshi children aged 24–59 months (2004–2014) by sex and socioeconomic status. Int. J. Obes.
2020
,
44, 664–674. [CrossRef] [PubMed]
6.
Corvalán, C.; Garmendia, M.L.; Jones-Smith, J.; Lutter, C.K.; Miranda, J.J.; Pedraza, L.S.; Popkin, B.M.; Ramirez-Zea, M.; Salvo, D.;
Stein, A.D. Nutrition Status of Children in Latin America. Obes. Rev. 2017,18, 7–18. [CrossRef]
7. McPherson, K. Reducing the global prevalence of overweight and obesity. Lancet 2014,384, 728–730. [CrossRef]
8.
Neupane, S.; Prakash, K.C.; Doku, D.T. Overweight and Obesity among Women: Analysis of Demographic and Health Survey
Data from 32 Sub-Saharan African Countries. BMC Public Health 2016,16, 1–19. [CrossRef]
9.
May, A.L.; Freedman, D.; Sherry, B.; Blanck, H.M.; Centers for Disease Control and Prevention. Obesity—United States, 1999–2010.
MMWR Surveill Summ.
2013
,62, 120–128. Available online: https://www.cdc.gov/mmwr/pdf/other/su6203.pdf (accessed on
30 July 2022).
10.
Koirala, M.; Khatri, R.; Khanal, V.; Amatya, A. Prevalence and factors associated with childhood overweight/obesity of private
school children in Nepal. Obes. Res. Clin. Pract. 2015,9, 220–227. [CrossRef] [PubMed]
11. Dietz, W.H. Overweight in childhood and adolescence. N. Engl. J. Med. 2004,350, 855–857. [CrossRef]
12.
Ruano, C.; Lucumi, E.; Albán, J.; Arteaga, S.; Fors, M. Obesity and Cardio-Metabolic Risk Factors in Ecuadorian University
Students. First Report, 2014–2015. Diabetes Metab. Syndr. Clin. Res. Rev. 2018,12, 917–921. [CrossRef]
13.
McPhee, P.G.; Singh, S.; Morrison, K.M. Childhood Obesity and Cardiovascular Disease Risk: Working toward Solutions. Can. J.
Cardiol. 2020,36, 1352–1361. [CrossRef] [PubMed]
14.
Stabouli, S.; Kotsis, V.; Papamichael, C.; Constantopoulos, A.; Zakopoulos, N. Adolescent Obesity is Associated with High
Ambulatory Blood Pressure and Increased Carotid Intimal-Medial Thickness. J. Pediatr.
2005
,147, 651–656. [CrossRef] [PubMed]
15.
Rumi´nska, M.; Majcher, A.; Pyr´zak, B.; Czerwonogrodzka-Senczyna, A.; Brzewski, M.; Demkow, U. Cardiovascular Risk Factors
in Obese Children and Adolescents. Adv. Exp. Med. Biol. 2016,878, 39–47. [CrossRef]
16.
Maggio, A.B.R.; Aggoun, Y.; Marchand, L.M.; Martin, X.E.; Herrmann, F.; Beghetti, M.; Farpour-Lambert, N.J. Associations among
obesity, blood pressure, and left ventricular mass. J. Pediatr. 2008,152, 489–493. [CrossRef] [PubMed]
17.
Ranjani, H.; Mehreen, T.S.; Pradeepa, R.; Anjana, R.M.; Garg, R.; Anand, K.; Mohan, V. Epidemiology of childhood overweight &
obesity in India: A systematic review. Indian J. Med. Sci. 2016,143, 160–174. [CrossRef]
18.
Varghese, J.; Gupta, A.; Mehta, R.; Stein, A.; Patel, S. Changes in child undernutrition and overweight in india from 2006 to 2019:
An analysis of 22 states. Medicine, 2021; in press. [CrossRef]
19.
Thomas, U.M.; Narayanappa, D.; Sujatha, M.S. Prevalence of Overweight and Obesity among School Children in Mysuru,
Karnataka. J. Fam. Med. Prim. Care 2021,10, 2788. [CrossRef]
20.
Jain, S.; Pant, B.; Chopra, H.; Tiwari, R. Obesity among adolescents of affluent public schools in Meerut. Indian J. Public Health
2010,54, 158–160. [CrossRef]
21.
Macwana, J.I.; Mehta, K.G.; Baxi, R.K. Predictors of overweight and obesity among school going adolescents of Vadodara city in
Western India. Int. J. Adolesc. Med. Health 2017,29, 1–7. [CrossRef]
22.
Kotian, M.S.; Saya, G.K.; Kotian, S.S. Prevalence and determinants of overweight and obesity among adolescent school children
of South Karnataka, India. Indian J. Community Med. Off. Publ. Indian Assoc. Prev. Soc. Med. 2010,35, 176–178. [CrossRef]
23.
Luhar, S.; Timæus, I.M.; Jones, R.; Cunningham, S.; Patel, S.A.; Kinra, S.; Clarke, L.; Houben, R. Forecasting the Prevalence of
Overweight and Obesity in India to 2040. PLoS ONE 2020,15, e0229438. [CrossRef] [PubMed]
24.
Mistry, S.; Puthussery, S. Risk factors of overweight and obesity in childhood and adolescence in South Asian countries: A
systematic review of the evidence. Public Health 2015,129, 200–209. [CrossRef] [PubMed]
25.
IIPS & ICF National Family Health Survey (NFHS-4). Available online: http://rchiips.org/NFHS/NFHS-4Reports/UttarPradesh.
pdf%0Ahttps://dhsprogram.com/pubs/pdf/FR338/FR338.UP.pdf (accessed on 22 August 2022).
26.
Bishwajit, G.; Yaya, S. Overweight and obesity among under-five children in South Asia. Child Adolesc. Obes.
2020
,3, 105–121.
[CrossRef]
27.
Weldearegay, H.G.; Gebrehiwot, T.G.; Abrha, M.W.; Mulugeta, A. Overweight and obesity among children under five in Ethiopia:
Further analysis of 2016 national demographic health survey: A case control study. BMC Res. Notes
2019
,12, 1–6. [CrossRef]
[PubMed]
28.
Rutstein, S.O.; Johnson, K. The DHS Wealth Index. DHS Comparative Reports No. 6; ORC Macro: Calverton, MD, USA, 2004.
Available online: http://dhsprogram.com/pubs/pdf/CR6/CR6.pdf (accessed on 7 March 2022).
29.
Aryeetey, R.; Lartey, A.; Marquis, G.S.; Nti, H.; Colecraft, E.; Brown, P. Prevalence and predictors of overweight and obesity
among school-aged children in urban Ghana. BMC Obes. 2017,4, 38. [CrossRef]
30.
Karki, A.; Shrestha, A.; Subedi, N. Prevalence and associated factors of childhood overweight/obesity among primary school
children in urban Nepal. BMC Public Health 2019,19, 1055. [CrossRef]
31.
Ahmed, J.; Laghari, A.; Naseer, M.; Mehraj, V. Prevalence of and factors associated with obesity among Pakistani school children:
A school-based, cross-sectional study. Int. J. Environ. Health Res. 2013,19, 242–247.
Nutrients 2022,14, 3621 17 of 18
32.
Tchoubi, S.; Sobngwi-Tambekou, J.; Noubiap, J.J.N.; Asangbeh, S.L.; Nkoum, B.A.; Sobngwi, E. Prevalence and risk factors of
overweight and obesity among children aged 6–59 months in Cameroon: A multistage, stratified cluster sampling nationwide
survey. PLoS ONE 2015,10, e0143215. [CrossRef]
33.
Zhang, J.; Wang, H.; Wang, Z.; Du, W.; Su, C.; Zhang, J.; Jiang, H.; Jia, X.; Huang, F.; Ouyang, Y.; et al. Prevalence and stabilizing
trends in overweight and obesity among children and adolescents in China, 2011–2015. BMC Public Health
2018
,18, 571. [CrossRef]
34.
Pelegrini, A.; Bim, M.A.; de Souza, F.U.; da Silva Kilim, K.S.; de Araújo Pinto, A. Prevalence of overweight and obesity in Brazilian
children and adolescents: A systematic review. Rev. Bras. Cineantropometria Desempenho Hum. 2021,23, 1–19. [CrossRef]
35.
Shah, B.; Cost, K.T.; Fuller, A.; Birken, C.S.; Anderson, L.N. Sex and gender differences in childhood obesity: Contributing to the
research agenda. BMJ Nutr. Prev. Health 2020,3, 387–390. [CrossRef] [PubMed]
36.
Ulbricht, L.; De Campos, M.F.; Esmanhoto, E.; Ripka, W.L. Prevalence of excessive body fat among adolescents of a south Brazilian
metropolitan region and State capital, associated risk factors, and consequences. BMC Public Health 2018,18, 312. [CrossRef]
37.
Kitsantas, P.; Gaffney, K.F. Risk profiles for overweight/obesity among preschoolers. Early Hum. Dev.
2010
,86, 563–568. [CrossRef]
[PubMed]
38.
Simen-Kapeu, A.; Kuhle, S.; Veugelers, P.J. Geographic Differences in Childhood Overweight, Physical Activity, Nutrition and
Neighbourhood Facilities: Implications for Prevention. Can. J. Public Health 2010,101, 128–132. [CrossRef] [PubMed]
39.
Larson, N.I.; Story, M.T.; Nelson, M.C. Neighborhood Environments: Disparities in Access to Healthy Foods in the US. Am. J.
Prev. Med. 2009,36, 74–81.e10. [CrossRef]
40. Damaris, M.; Nguimbus, E.; Bikono, F. Prevalence of overweight and obesity among rural preschool school children Cameroon.
Int. J. Adv. Res. 2017,5, 673–678. [CrossRef]
41.
Rachmi, C.N.; Li, M.; Baur, L.A. Overweight and Obesity in Indonesia: Prevalence and Risk Factors—a Literature Review. Public
Health 2017,147, 20–29. [CrossRef]
42.
Sidik, S.M.; Rampal, L. The prevalence and factors associated with obesity among adult women in Selangor, Malaysia. Asia Pac.
Fam. Med. 2009,8, 2. [CrossRef]
43.
Huang, J.; Zhang, Z.; Wu, Y.; Wang, Y.; Wang, J.; Zhou, L.; Ni, Z.; Hao, L.; Yang, N.; Yang, X. Early feeding of larger volumes of
formula milk is associated with greater body weight or overweight in later infancy. Nutr. J. 2018,17, 12. [CrossRef]
44.
Wang, L.; Collins, C.; Ratliff, M.; Xie, B.; Wang, Y. Breastfeeding Reduces Childhood Obesity Risks. Child. Obes.
2017
,13, 197–204.
[CrossRef]
45.
Yan, J.; Liu, L.; Zhu, Y.; Huang, G.; Wang, P.P. The association between breastfeeding and childhood obesity: A meta-analysis.
BMC Public Health 2014,14, 1267. [CrossRef] [PubMed]
46.
Morgen, C.S.; Larsson, M.W.; Ängquist, L.; Sørensen, T.I.A.; Michaelsen, K.F. Overweight in childhood of exclusively breastfed
infants with a high weight at 5 months. Matern. Child Nutr. 2021,17, e13057. [CrossRef] [PubMed]
47. Stolzer, J.M. Breastfeeding and obesity: A meta-analysis. Open J. Prev. Med. 2011,1, 88–93. [CrossRef]
48.
Al-Hussaini, A.; Bashir, M.S.; Khormi, M.; AlTuraiki, M.; Alkhamis, W.; Alrajhi, M.; Halal, T. Overweight and obesity among Saudi
children and adolescents: Where do we stand today? Saudi J. Gastroenterol. Off. J. Saudi Gastroenterol. Assoc.
2019
,
25, 229–235.
[CrossRef]
49.
Feng, Y.; Ding, L.; Tang, X.; Wang, Y.; Zhou, C. Association between maternal education and school-age children weight status: A
study from the China Health Nutrition Survey, 2011. Int. J. Environ. Res. Public Health 2019,16, 2543. [CrossRef]
50.
Kurmanov, B.; Pena-Boquete, Y.; Samambayeva, A.; Makhmejanov, G. Determinants of Overweight and Underweight among
Children under 5 in Kazakhstan. Open Public Health J. 2021,14, 501–508. [CrossRef]
51.
Morrissey, T.W.; Dunifon, R.E.; Kalil, A. Maternal Employment, Work Schedules, and Children’s Body Mass Index. Child Dev.
2011,82, 66–81. [CrossRef]
52.
Brandstetter, S.; Atzendorf, J.; Seelbach-Gobel, B.; Melter, M.; Kabesch, M.; Apfelbacher, C. Sociodemographic factors associated
with health literacy in a large sample of mothers of newborn children: Cross-sectional findings from the KUNO-Kids birth cohort
study. Eur. J. Pediatr. 2019,179, 165–169. [CrossRef]
53.
Barclay, K.; Myrskylä, M. Advanced maternal age and offspring outcomes: Reproductive aging and counterbalancing period
trends. Popul. Dev. Rev. 2016,42, 69–94. [CrossRef]
54.
Heslehurst, N.; Vieira, R.; Akhter, Z.; Bailey, H.; Slack, E.; Ngongalah, L.; Pemu, A.; Rankin, J. The association between maternal
body mass index and child obesity: A systematic review and meta-analysis. PLoS Med.
2019
,16, e1002817. [CrossRef] [PubMed]
55. Seth, A.; Sharma, R. Childhood obesity. Indian J. Pediatr. 2013,80, 309–317. [CrossRef] [PubMed]
56.
Godfrey, K.M.; Reynolds, R.M.; Prescott, S.L.; Nyirenda, M.; Jaddoe, V.W.V.; Eriksson, J.G.; Broekman, B.F.P. Influence of maternal
obesity on the long-term health of offspring. Lancet Diabetes Endocrinol. 2017,5, 53–64. [CrossRef]
57.
Nettle, D.; Andrews, C.; Bateson, M. Food insecurity as a driver of obesity in humans: The insurance hypothesis. Cambridge Core
2017,40, e105. [CrossRef] [PubMed]
58.
Bush, N.R.; Allison, A.L.; Miller, A.L.; Deardorff, J.; Adler, N.E.; Boyce, W.T. Socioeconomic disparities in childhood obesity risk:
Association with an oxytocin receptor polymorphism. JAMA Pediatr. 2017,171, 61–67. [CrossRef] [PubMed]
59.
Hernández-Vásquez, A.; Bendezú-Quispe, G.; Santero, M.; Azañedo, D. Prevalence of Childhood Obesity by Sex and Regions in
Peru, 2015. Rev. Esp. Salud Publica 2016,90, e1–e10.
Nutrients 2022,14, 3621 18 of 18
60.
Markowska, M.; Przychodni, A.M.; Nowak-Starz, G.; Cie´sla, E. The frequency of overweight and obesity occurrence among Polish
children (age 6–7 years) in relation to the place of residence, the education level of parents. Anthropol. Rev.
2017
,
80, 381–392.
[CrossRef]
61.
Stark, M.J.; Niederhauser, V.P.; Camacho, J.M.; Shirai, L. The prevalence of overweight and obesity in children at a Health
Maintenance Organization in Hawai’ i. Hawaii Med. J. 2011,70, 27–31.
62.
Wang, Y.; Chen, H.-J.; Shaikh, S.; Mathur, P. Is obesity becoming a public health problem in India? Examine the shift from under-to
overnutrition problems over time. Obes. Rev. 2009,10, 456–474. [CrossRef]
63.
Kshatriya, G.K.; Acharya, S.K. Triple burden of obesity, undernutrition, and cardiovascular disease risk among Indian tribes.
PLoS ONE 2016,11, e0147934. [CrossRef]
64.
Islam, T.; Mandal, S.; Chouhan, P. Influence of socio-demographic factors on coverage of full vaccination among children aged
12–23 months: A study in Indian context (2015-2016). Hum. Vaccines Immunother. 2021,17, 5226–5234. [CrossRef]
65.
Tabacchi, G.; Giammanco, S.; La Guardia, M.; Giammanco, M. A review of the literature and a new classification of the early
determinants of childhood obesity: From pregnancy to the first years of life. Nutr. Res. 2007,27, 587–604. [CrossRef]
66.
Golpour-Hamedani, S.; Rafie, N.; Pourmasoumi, M.; Saneei, P.; Safavi, S.M. The association between dietary diversity score and
general and abdominal obesity in Iranian children and adolescents. BMC Endocr. Disord. 2020,20, 181. [CrossRef] [PubMed]
67.
Amin, T.T.; Al-Sultan, A.I.; Ali, A. Overweight and obesity and their relation to dietary habits and socio-demographic char-
acteristics among male primary school children in Al-Hassa, Kingdom of Saudi. Eur. J. Nutr.
2007
,47, 310–318. [CrossRef]
[PubMed]
68.
Min, K.; Wang, J.; Liao, W.; Astell-Burt, T.; Feng, X.; Cai, S.; Liu, Y.; Zhang, P.; Su, F.; Yang, K.; et al. Dietary patterns and their
associations with overweight/obesity among preschool children in Dongcheng District of Beijing: A cross-sectional study. BMC
Public Health 2021,21, 223. [CrossRef]
69.
Jayawardena, R.; Byrne, N.M.; Soares, M.J.; Katulanda, P.; Yadav, B.; Hills, A.P. High dietary diversity is associated with obesity in
Sri Lankan adults: An evaluation of three dietary scores. BMC Public Health 2013,13, 314. [CrossRef] [PubMed]
70.
Karimbeiki, R.; Pourmasoumi, M.; Feizi, A.; Abbasi, B.; Hadi, A.; Rafie, N.; Safavi, S.M. Higher dietary diversity scoreis associated
with obesity: A case–control study. Public Health 2018,157, 127–134. [CrossRef] [PubMed]
