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Risk factors of obesity among infants and young children below 2 years of age: A case control study
For correspondence: Dr Priya Sreenivasan, Department of Pediatrics, Government Medical College Thiruvananthapuram, Thiruvananthapuram 695 588, Kerala, India e-mail: priyavineed16@gmail.com
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Received: ,
Accepted: ,
How to cite this article: Pushparajan RRM, Sreenivasan P, Sarasam AA. Risk factors of obesity among infants and young children below 2 years of age: A case control study. Indian J Med Res. 2026;163:450-5. doi: 10.25259/IJMR_2621_2025
Abstract
Background and objectives
Obesity is a chronic disease with its onset as early as infancy. This study was conducted to determine risk factors of obesity in infants and young children below 2 years of age.
Methods
For this case-control study, obese children aged 1 month to 2 years were enrolled as cases. Controls were age, sex and calendar matched non-obese children from the same setting (1:1). Sociodemographic characteristics, clinical features and potential risk factors (parental obesity, maternal weight gain during pregnancy, low birth weight, cessation of exclusive breastfeeding before 6 months of age, introduction of semisolid feeds before 6 months of age, formula feeding at enrolment, bottle feeding at enrolment, junk food consumption, and lifestyle diseases in family) were noted. Obesity was defined as weight-for-length or BMI-for-age more than 3 standard deviations above median as per World Health Organization 2006 growth charts.
Results
Univariate analysis on 52 pairs (22 male pairs) showed maternal pre-conceptional BMI>25 kg/m2, maternal BMI>25 kg/m2 paternal BMI>23 kg/m2, bottle feeding and/or formula feeding at enrolment, cessation of exclusive breastfeeding before 6 months, junk food consumption, and lifestyle diseases in family as risk factors. With multivariable logistic regression, maternal BMI>25 kg/m2 at enrolment [Adjusted odds ratio (aOR) 11.25, 95% confidence interval (CI) 3.66-34.49, P<0.001], formula feeding (aOR 6.13, 95% CI 1.33-28.17, P=0.020) and lifestyle diseases in family (aOR 6.88, 95% CI 1.83-25.88, P=0.004) were identified as significant risk factors.
Interpretations and conclusions
Risk factors of obesity in children below 2 years of age were included maternal pre-conceptional BMI>25 kg/m2, maternal BMI>25 kg/m2 at enrolment, formula feeding at enrolment, and lifestyle diseases in family.
Keywords
Formula feeding
Infantile obesity
Maternal obesity
Parental obesity
Globally, under-fives who were overweight/obese were estimated to be 35 million in 2024. Almost half of these children were Asians.1 According to National Family Health Survey (NFHS) data, overweight among under-fives has increased from 2.1% (2015-16) to 3.4% (2020-21) in India and 3.5% (2015-16) to 4% (2020-21) in the state of Kerala.2,3 A cross-sectional study using NFHS 2015-16 data showed a prevalence of overweight and obesity as 5.8% among infants aged 0-11 months (n=29,822) and 2.4% among babies aged 12-23 months (n=35,174).4
Obesity has its onset in infancy, tracks through childhood, adolescence and to adulthood. During this course, obesity paves way to premature onset of type 2 diabetes, hypertension, dyslipidaemia, coronary vascular disease and metabolic syndrome. Hence, obesity is linked to more deaths than underweight.5
Parental pre-conception nutrition, lifestyle, and exercise habits, through epigenetic mechanisms and metabolic programming, have trans-generational effects like obesity on the offspring.6 Moreover, the first 1000 days, the period from conception to second birthday, encompass several determinants of infantile and young child obesity. Early identification of these modifiable risk factors and timely intervention may prevent childhood obesity and its adverse consequences.
Studies on childhood obesity are focused more on older children. Risk factors of obesity among infants and young children below 2 years are different from those identified in older children. Parental pre-conceptional, pregnancy-related, and foetal risk factors play a major role in infantile obesity. Children below 2 years are mostly fed on human milk and complementary feeds, the practices of which differ socio-culturally and regionally. Physical activities and sedentary behaviours differ in infants and young children below 2 years of age.7 Hence, we aimed to determine the risk factors of obesity in infants and young children below 2 years of age.
Methods
A case control study was conducted in the outpatient division and wards of department of Pediatrics, Government Medical College, Thiruvananthapuram, Kerala, India, a tertiary care teaching institute for a period of one year from March 2020 to February 2021. Institutional Ethical Committee Clearance was obtained from Human Ethics Committee, Government Medical College, Thiruvananthapuram before initiating the study procedures. Parent information sheet was provided and informed written consent was obtained from each parent before enrolment. Cases were children aged 1 month to 2 years with weight-for-length or body mass index (BMI)-for-age >3SD above median as per World Health Organization (WHO) 2006 Child Growth Standards.8 Controls were age, sex and calendar matched non-obese children. Children on steroids and those with endocrine and genetic conditions known to be associated with obesity were excluded. Cases were enrolled consecutively. An age and sex matched non-obese child from the same setting with an out-patient/in-patient hospital number nearest to that of the case enrolled was recruited as the control (ratio 1:1). In this manner, each control was recruited within 3 days of recruiting a case. In children, definition of obesity is age and sex specific; moreover, dietary pattern varies with age of the child. Hence, matching of age and sex was done to minimise selection bias. Sample size was calculated as 52 with alpha 0.05, beta 0.2, power 0.8, P1, the prevalence of maternal obesity among cases 0.3 and P2, the prevalence of maternal obesity among controls as 0.09. As similar studies were not available from Kerala, a pilot study was conducted with 10 cases and controls. 3 mothers among cases and 1 mother among controls were obese. Considering the fact that it was difficult to obtain cases during CoViD pandemic, P1 and P2 were decided to be kept as 0.3 and 0.09.
Variables
Data on sociodemographic characteristics, clinical features and potential risk factors (maternal BMI pre-conception or at first antenatal visit, maternal and paternal BMI at enrolment, excess maternal weight gain during pregnancy (calculated from antenatal documents as over and above the Institute of Medicine 2009 weight gain during pregnancy guidelines), low birth weight, cessation of exclusive breast feeding before 6 months of age, initiation of semisolid feeds before 6 months of age, bottle feeding at enrolment, formula feeding at enrolment, junk food consumption (bakery products, foods high in sugar, salt or fat, sugar sweetened beverages), physical activity of less than 30 min per day if below 12 months of age (tummy time and floor-based play) and less than 180 min per day if aged 12-24 months (crawling, walking and running) (based on WHO guidelines on physical activity for children under 5 years of age) and family history of lifestyle diseases- type 2 diabetes, hypertension, dyslipidaemia and coronary artery diseases) was collected by a single interviewer with a structured questionnaire.9,10 Obesity was defined as weight-for-length or BMI-for-age >3 SD above median as per WHO 2006 Child Growth Standards.8 Maternal antenatal records, birth details/case sheets and growth charts/mother and child protection cards of babies were retrieved from the mother if available. If not available from the mother, details were collected from the medical records library of our hospital (in-born children) or community health worker (out-born children) to avoid recall bias.
Statistical analysis
Data were analysed with SPSS version 27 (IBM Corp, NY, USA). Unadjusted odd’s ratios with 95% confidence intervals (CI) were calculated with each proposed risk factor as independent variable and obesity as outcome. Association between various risk factors and obesity was assessed using McNemar chi-squared test. A P value <0.05 was considered statistically significant. Variables found statistically significant in univariate analysis (P<0.05) were included in the adjusted analysis with conditional logistic regression.
Results
Fifty-five obese children were identified as potentially eligible cases but 3 had to be excluded as two were on steroids for inherited bone marrow failure syndrome and congenital nephrotic syndrome; and one child had Down Syndrome. Among 52 case-control pairs who were finally included in the study, age distribution was as follows: 1-6 months- 4 pairs (7.6%) (youngest pair recruited had completed 6 months of age), 7-12 months-27 pairs (51.9%), 13-18 months- 15 pairs (28.8%) and 19-24 months- 6 pairs (11.5%). The median (IQR) age of cases and controls were 12 (9-16) months. Twenty-two pairs (42.3%) were boys and 30 pairs (57.7%) were girls. Mean (SD) weight of cases and controls was 13.2 (2.27) kg and 9.3 (1.92) kg, respectively. Mean (SD) length of cases and controls was 73.3 (5.59) and 72.6 (6.87) cm, respectively. Median weight-for-age Z score of cases and controls were +3.1 and +0.42 respectively. Median height-for-age Z score of cases and controls were -0.5 and -0.1, respectively. Mean (SD) BMI of cases and controls was 24.3 (1.84) and 17.6 (1.60) kg/m2, respectively. All cases had both weight for length and BMI for age above +3 Z scores. Cases and controls had an equal number of babies born term (48, 92.3%) and preterm (4, 7.7%). Similarly, cases and controls had an equal number of babies born small for gestational age (6, 11.5%), appropriate for gestational age (45, 86.5%) and large for gestational age (1, 1.9%). Mean maternal BMI at enrolment for cases and controls were 26.7 (2.05) kg/m2 and 23.9 (1.3) kg/m2; mean paternal BMI at enrolment for cases and controls were 24.5 (1.58) and 24.4 (2.07) kg/m2, respectively. Other baseline characteristics are detailed in Table I.
| Baseline characteristics | Cases (N=52), n (%) | Controls (N=52), n (%) | P value | |
|---|---|---|---|---|
|
Socioeconomic status |
Lower middle | 3 (5.8) | 2 (3.8) | 0.538 |
| Upper middle | 48 (92.3) | 50 (9) | ||
| Upper | 1 (1.9) | 0 | ||
|
Maternal education |
Matriculation and below | 11 (21.2) | 7 (13.4) | 0.364 |
| High school | 37 (71.2) | 43 (82.7) | ||
| Degree and above | 4 (7.6) | 2 (3.8) | ||
|
Paternal education |
Matriculation and below | 6 (11.5) | 7 (13.4) | 0.075 |
| High school | 41 (78.8) | 43 (82.7) | ||
| Degree and above | 5 (9.6) | 2 (3.8) | ||
|
Maternal occupation |
Yes | 24 (46.2) | 27 (51.9) | 0.348 |
| No | 28 (53.8) | 25 (48.1) | ||
Table II shows results of univariate analysis with proposed antenatal and infant risk factors for obesity. Five (9.61%) cases had junk food consumption; no controls took junk foods. Fisher Exact test was applied and showed a statistically significant difference in junk food consumption among cases and controls (P=0.028). Physical activity was found adequate in 48 (92.3%) cases and 48 (92.3%) controls. Results of adjusted analysis with multivariate logistic regression is shown in Table III.
| Antenatal and infant risk factor | Cases (N=52), n (%) | Controls (N=52), n (%) | OR (95% CI), P value with (Mc Nemar–hi squared test) | |
|---|---|---|---|---|
| Excess antenatal weight gain | 4 (7.6) | 2 (3.8) | 0.48 (0.84-2.74), 0.409 | |
| Low birth weight (Kg) | <2.5 | 9 (17.3) | 4 (7.6) | 0.39 (0.11-1.38), 0.148 |
| Cessation of exclusive breastfeeding before 6 month of age | Yes | 17 (32.6) | 6 (11.5) | 3.72 (1.33-10.42), 0.025 |
| Introducing semi-solid feeds before 6 month of age | Yes | 17 (32.6) | 12 (23) | 1.61 (0.68-3.85), 0.276 |
| Proposed risk factor | Case (N=52); n (%) | Control (N=52); n (%) | Unadjusted OR (95% CI); P value | Adjusted OR (95% CI); P value |
|---|---|---|---|---|
| Maternal pre-pregnant BMI > 25 kg/m2 | 17 (32.6) | 6 (11.5) |
3.72 (1.33-10.42); P=0.025 |
4.28 (0.89-20.61); P=0.068 |
| Maternal BMI at enrolment >25 kg/m2 | 41 (78.8) | 10 (19.2) |
15.65 (6.00-40.81); P<0.001 |
10.42 (3.37-32.25); P<0.001 |
| Paternal BMI at enrolment >23 kg/m2) | 42 (80.7) | 30 (57.6) |
3.08 (1.27-7.44); P=0.012 |
2.44 (0.69-8.61); P=0.166 |
| Cessation of exclusive breastfeeding before 6 month of age | 17 (32.6) | 6 (11.5) |
3.72 (1.33-10.42); P=0.025 |
2.18 (0.52-9.11); P=0.286 |
| Bottle feeding at enrolment | 48 (92.3) | 39 (75) |
5.50 (1.21-24.81); P=0.027 |
2.17 (0.39-12.11); P=0.374 |
| Formula feeding at enrolment | 46 (88.4) | 35 (67.3) |
3.75 (1.24-11.29); P=0.019 |
6.14 (1.33-28.33); P=0.020 |
| Lifestyle diseases in family | 46 (88.4) | 28 (53.8) |
5.50 (1.89-15.96); P=0.002 |
6.05 (1.57-23.24); P=0.009 |
OR, odd’s ratio; CI, confidence interval; BMI, body mass index
Discussion
Maternal BMI>25 kg/m2 at enrolment, formula feeding, and lifestyle diseases in family were identified as the risk factors of obesity in infants and young children below 2 years.
Role of developmental and epigenetic programming than genetic influences in maternal transmission of obesity has been highlighted by Rodgers et al11 with the evidence that obese mothers who underwent bariatric surgery after their first pregnancy gave birth to less obese babies than their siblings who were born before surgery. A child with one obese parent has 40% probability of becoming overweight and if both parents are obese, probability of overweight increases to 70%.12 The new conceptual ‘child obesity–parent (CO–Parent)’ model linked independent and interdependent contributions of both maternal and paternal weights, weight‐related behaviours and their wellbeing pre-conceptionally, antenatally and postnatally, to early years of child’s weight and weight‐related behaviours.13 Our study also established an association between pre-pregnancy BMI>25kg/m2 and obesity in offspring. Formula milk contains aromatic amino-acids, tryptophan, kynurenine and many other regulators that may theoretically trigger aberrant epigenetic programming at the level of DNA methylation. This enhances the expression of FTO gene which may theoretically explain enhanced adipogenesis.14 Our study found that 46 (88.4%) cases and 35 (67.3%) controls resorted to formula feeding. An association between formula feeding and infant obesity was noted both in univariate and adjusted analysis.
Bottle feeding tends to encourage the infant to feed until the bottle is empty. This pressuring feeding behaviour overlooks satiety cues of the infant and may be associated with obesity.15 The Rise and SHINE cohort study conducted among 308 mother- baby pairs found an association between avoidance of bottle use in bed and lower BMI Z -score (β -0.32 units; 95% CI -0.57, -0.07).16 A longitudinal birth cohort study of 1780 infants found that bottle feeding and night time formula feeding was associated with rapid weight gain in infancy as evidenced by a change >0.67 in weight SD scores.17 In our study, 48 (92.3%) cases and 39 (75%) controls were bottle fed; an association between bottle feeding and infant obesity was noted only on univariate analysis.
Strength of our study lies in its design; this age-matched case-control study eliminates confounding due to age related differences in quality, quantity, frequency and consistency of complementary feeds. Single observer took all anthropometric measurements thereby eliminating inter-observer bias. Recall bias was tackled to the maximum possible extent by relying upon documents to verify the authenticity of data through antenatal reports, birth records and immunisation cards. Our study identified certain lacunae in the existing child health practices. Growth charts available in Mother and Child Protection Cards of cases and controls, were not plotted satisfactorily. Regular plotting of growth charts ensures early identification of growth faltering.
Our study had limitations with respect to certain exposure variables. Though pre-conceptual parental obesity is a known risk factor, data on paternal weight before or at conception was not documented and hence, could not be retrieved. Though data on breastfeeding, complementary feeding, and junk food consumption were collected, a deeper interrogation on the dietary diversity was not conducted. Another exposure variable which we found difficult to measure was maternal sleep deprivation due to its subjective nature in recall. Study was conducted during the CoViD pandemic and hence, sample size was less.
Our study results may be generalised to regions which share similar socio-cultural milieu, breast feeding rates, and nutritional practices. The study results give policy/practice implications as well. Strategies should be planned to create awareness among adolescents and adults onoptimal lifestyle and desirable BMIs that benefit their offsprings. Strengthening of awareness on exclusive breastfeeding till six months followed by optimal complementary feeding practices should be done regularly.
Acknowledgment
Authors acknowledge Kerala University of Health Sciences (KUHS) for granting permission for publication of this article, prepared as part of thesis work done in partial fulfilment of the requirements for MD Pediatrics degree course.
Author contributions
RRMP: Executed the idea, data collection, manuscript writing; questions related to the accuracy or integrity of the work were appropriately investigated and resolved; PS: Conceived the idea, devised the protocol, data analysis, intellectual content, manuscript writing; AKAS: Refined the idea, approved the protocol, interpreted the data, manuscript writing. All authors have read and approve the final printed version of the manuscript.
Financial support and sponsorship
None.
Conflicts of Interest
None.
Use of Artificial Intelligence (AI)-Assisted Technology for manuscript preparation
The authors confirm that there was no use of AI-assisted technology for assisting in the writing of the manuscript and no images were manipulated using AI.
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