Prevalence of Overweight and Obesity Among Children Younger Than 5 Years in India

Key Points

Question

To what extent does the prevalence of overweight and obesity among children younger than 5 years vary across India’s 36 states and union territories (2006-2024), and are these regions on track to meet the Global Nutrition Target of 5% or less overweight by 2030?

Findings

This cross-sectional study of 467 995 children in India aged 0 to 59 months found that overweight prevalence increased from 1.55% to 3.42% (2006-2021), whereas obesity increased from 0.50% to 1.30%. Despite a decrease of overweight prevalence to 1.3% in 2024, 9 states and union territories remained at low to moderate probability of meeting the 2030 target.

Meaning

These findings suggest that designing multisectoral and context-specific interventions is essential to curb high overweight and obesity.

This cross-sectional study assesses trends in overweight and obesity among Indian children younger than 5 years across 28 states and 8 union territories.

Abstract

Importance

Evidence is lacking on long-term trends across Indian states and union territories (UTs) and on the attainability of the 2030 Global Nutrition Target (GNT) goals within these specific regions.

Objectives

To estimate the trends in overweight and obesity among children younger than 5 years across 36 states and UTs in India between 2006 and 2024 and to assess the feasibility of achieving the GNT of restricting the overweight burden to 5% or less by 2030.

Design, Setting, and Participants

For this cross-sectional study, microdata and aggregate data were used from the 4 most recent waves of the National Family Health Survey (repeated cross-sectional surveys conducted between January 1, 2006, and December 31, 2024). The analysis included individual-level samples of 41 306 children in 2006, 225 002 in 2016, and 201 687 in 2021, alongside aggregate estimates of overweight from the 2024 wave. Data were analyzed in January and updated in July 2026.

Main Outcomes and Measures

Following World Health Organization definitions of overweight and obesity in children younger than 5 years (overweight is defined as weight for height >2 SDs above the World Health Organization median and obesity as >3 SDs), their prevalence and standardized annualized changes for 5 timeframes (2006-2016, 2016-2021, 2021-2024, 2006-2021, and 2006-2024) were computed. Additionally, the fractional logistic regression was used to model national and state-level overweight trajectories, forecasting probability of achieving the 5% or less 2030 GNT threshold.

Results

The final sample included 467 995 children (241 645 [51.6%] male, 226 350 [48.4%] female) aged 0 to 59 months from NFHSs conducted between 2006 and 2021. Mean (SD) child age remained consistent from 2006 to 2021: 30.1 (17.1) months in 2006, 30.1 (17.0) months in 2016, and 29.9 (17.2) months in 2021. Between 2006 and 2021, the prevalence of overweight increased from 1.55% to 3.42%, whereas obesity prevalence increased from 0.50% to 1.30% before overweight prevalence decreased to 1.3% in 2024. Although India was projected to sustain the 2030 overweight target nationally, 9 states and UTs (Arunachal Pradesh, Assam, Himachal Pradesh, Jammu and Kashmir, Kerala, Mizoram, Nagaland, Sikkim, and Tripura) maintained a low to moderate probability of adherence.

Conclusions and Relevance

In this cross-sectional study of Indian children younger than 5 years from 2006 to 2024, a historical overweight increase reversed in 2024. However, profound subnational disparities remained, suggesting that targeted regional interventions are needed to achieve the 2030 GNT.

Introduction

Globally, the increasing burden of overweight and obesity, whether measured as a combined prevalence or as obesity alone, among children younger than 5 years, particularly in low- and middle-income countries, poses a substantial public health challenge.^1,2,3,4 Children with overweight are at a higher risk of developing chronic conditions, including type 2 diabetes, hypertension, and respiratory or liver diseases, during adulthood.^5,6 Beyond physical health, the condition often leads to social and psychological hurdles, including lower self-esteem and diminished academic performance, which are frequently intensified by the weight-related stigma and bullying they encounter.¹ Compounding these human costs is a staggering financial burden; the World Obesity Federation projects that by 2035, the global economic cost of overweight and obesity (across all age groups) will increase to US $4.32 trillion annually.⁷ To combat both these health and economic effects, the Sustainable Development Goal 2.2 aims to end all forms of malnutrition, including childhood overweight and obesity, by 2030. To support this, the renewed 2025 Global Nutrition Target (GNT) update set a clear goal: by 2030, the prevalence of overweight among children younger than 5 years should be reduced to and kept below 5%.¹

India, home to the world’s largest population, contended with an increasing prevalence of overweight among those younger than 5 years between 2006 (1.6%) and 2021 (3.4%).^8,9,10 However, a recent national estimate from 2024 showing a reduction in prevalence to 1.3% has drawn global attention.¹¹ Despite this overall decrease, substantial subnational variation remains, highlighting the need for targeted public health policies in heavily impacted regions. Although the Ministry of Women and Child Development has promoted holistic nourishment through the National Nutrition Mission (or POSHAN Abhiyaan),¹² these efforts have been deemed insufficient to address the adverse effects of childhood overweight and obesity currently witnessed in India.^13,14,15,16 According to the Indian Academy of Pediatrics, childhood overweight and obesity in India are linked to maternal factors (eg, weight issues, excessive gestational gain, tobacco, and hypertension or diabetes), nutritional factors (eg, overfeeding, formula with added sugars, junk food consumption by both children and parents, and suboptimal breastfeeding), and genetic predisposition.¹⁷ Therefore, to move beyond broad national overweight and obesity prevention strategies, India needs sustained, context-sensitive interventions driven by multisectoral collaboration and active public engagement.¹²

However, health is a state subject under the Indian Constitution; consequently, the responsibility for program and policy implementation is shared between the state governments and the Union Government.¹⁸ Although the Union Ministry establishes national standards for the prevention and control of childhood obesity, individual states and union territories (UTs) must adapt and execute them, making the long-term evaluation of their performance critical to ensuring national progress. To determine whether such data were available, we performed a 2-stage PubMed search (search terms and evidence gaps provided in eBox 1 in Supplement 1). Stage 1 reviewed the availability of literature on long-term overweight and obesity prevalence, whereas stage 2 assessed the feasibility of attaining the 2030 GNT for overweight among children younger than 5 years. Our review revealed a paucity of evidence regarding long-term trends across Indian states and UTs as well as an absence of studies assessing the attainability of the 2030 GNT goals within these specific regions. To address this evidence gap, we assessed trends in overweight and obesity among Indian children younger than 5 years across 28 states and 8 UTs. Furthermore, we evaluated the feasibility of attaining the 2030 GNT for overweight in these regions.

Methods

Dataset and Sampling Strategy

For this cross-sectional study, we used microdata and aggregate data from the 4 most recent waves of the National Family Health Survey (NFHS) (repeated cross-sectional surveys conducted between January 1, 2005, and December 31, 2024): NFHS-3 (2005-2006),⁸ NFHS-4 (2015-2016),⁹ NFHS-5 (2019-2021),¹⁰ and NFHS-6 (2023-2024).¹¹ Data from NFHS-1 (1992-1993)¹⁹ and NFHS-2 (1998-1999)²⁰ were excluded from this study because they restricted information to children aged 0 to 47 and 0 to 35 months, respectively, whereas our analysis required a sample of children aged 0 to 59 months (children aged <5 years). Although individual-level microdata were accessible for the analysis of NFHS-3 through NFHS-5, only aggregate state- and UT-level estimates of overweight prevalence were available for NFHS-6 during this study. In line with previous work,²¹ we consistently used the concluding survey years (2006, 2016, 2021, and 2024) for our analysis of childhood overweight and obesity trends. The NFHS estimates are comparable across survey rounds due to their consistent sampling design. The NFHS achieved a household response rate exceeding 95% across all survey iterations, whereas the response rate for women fluctuated between 94.5% and 96.9% across NFHS-3 to NFHS-5. Detailed accounts of the sampling design, instrument development, data collection protocols, weighting methods, SE estimations, and quality assurance measures are documented in the respective NFHS reports.^8,9,10,11 All NFHS procedures were approved by the institutional ethics review board of the nodal agency—the International Institute for Population Sciences. The NFHS obtained written informed consent from all participants or their guardians prior to interviews and anthropometric measurements. As the datasets are fully anonymized and available for public use by researchers, this study was exempted from additional ethics review in accordance with the Harvard Longwood Campus Institutional Review Board’s self-determination guidelines. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline for cross-sectional studies.

Study Population

Table 1 presents the total NFHS sample size (2006-2024) for children aged 0 to 59 months alongside the derivation of the final analytical sample. Observations were excluded if (1) measured height or length was outside plausible limits, (2) age was outside the valid range, or (3) z scores were invalid or biologically implausible,^8,9,10 resulting in a final analytical sample of 41 306 (NFHS-3), 225 002 (NFHS-4), and 201 687 (NFHS-5) children. Information on the sample derivation for NFHS-6 was unavailable at the time of this study due to the absence of individual-level microdata. Readers may refer to the respective NFHS reports^8,9,10 for details regarding the sample selection for measuring child anthropometry.

Table 1. Construction of the Analytical Sample, NFHS, 2006-2024^a.

Variable	NFHS wave
	2006	2016	2021
No. of children aged 0-59 mo regardless of survival status	51 555	259 627	232 920
No. of children aged 0-59 mo reported to be alive	48 679	247 743	224 218
No. of children whose weight and height divided by length were measured	48 084	236 455	214 531
No. of children with height and length outside plausible limits	490	1197	5183
Age outside plausible limits	6	21	0
No. of flagged cases for out-of-range or invalid z scores	1935	10 235	7661
No. of children with missing values	4347	0	0
Total analytical sample	41 306	225 002	201 687

Abbreviation: NFHS, National Family Health Survey.

^a Although the 2023 to 2024 NFHS fact sheets provided aggregate estimates of overweight prevalence, the corresponding microdata required for advanced analysis (2024) were unavailable at the time of this study.

Overweight and Obesity Among Children Younger Than 5 Years

In accordance with World Health Organization (WHO) standards,²² NFHSs provided the measurements required to calculate the prevalence of overweight and obesity among children younger than 5 years. As a condition characterized by excessive adiposity, children are classified as overweight if their weight for length divided by height is more than 2 SDs above the WHO Child Growth Standards median, whereas obesity is defined as a weight for length divided by height exceeding 3 SDs.^1,22 For the purposes of this study, we generated a binary variable for childhood overweight and obesity: cases were coded as 1 if the child had overweight or obesity and 0 otherwise. Further details regarding the protocols for measuring child anthropometry, including the globally standardized instruments used to measure weight, height, and length for different age groups, are provided in the respective NFHS manuals.^8,9,10

States and UTs of India

India’s administrative structure comprises states and UTs, which are further subdivided into districts. India’s administrative boundaries underwent substantial reorganization between 2006 and 2024. Notable changes include the formation of Telangana from Andhra Pradesh in 2014 and the 2019 reorganization of Jammu and Kashmir into the UTs of Jammu and Kashmir as well as Ladakh. Additionally, Dadra and Nagar Haveli as well as Daman and Diu were merged into a single UT in 2020. To maintain temporal consistency across the 28 states and 8 UTs that comprise India’s current structure, we harmonized administrative boundaries (wherever applicable) for the 2006 to 2024 analysis by strategically merging or realigning units based on established methods²³ and standardized geographic identifiers. Only the 3 most recent rounds provided additional district-level representative data. Consequently, we restricted this analysis to state- and UT-level data to maintain consistency across all NFHS waves (2006-2024).^8,9,10,11

Statistical Analysis

Data were analyzed in January and updated in July 2026. The prevalence of overweight and obesity in children younger than 5 years was estimated, followed by the calculation of the standardized annualized change (SAC)²¹ to determine the annual change between survey waves. SAC was calculated using the following formula:

SAC = ([P_t − P_t − n]/n)

where P_t is the prevalence of overweight or obesity at time t, and P_t − n denotes the coverage of overweight or obesity in years before time t, with n representing the intersurvey gap in years between 2 consecutive NFHSs. Positive SAC values indicate an increase in the prevalence of overweight or obesity, representing a deteriorating trend over time. Annualized changes were calculated for 5 time frames: 2006 to 2016, 2016 to 2021, 2021 to 2024, 2006 to 2021, and the full 2006 to 2024 study period, corresponding to 10, 5, 3, 15, and 18 years, respectively.²¹ SAC was interpreted as annual percentage point changes.

Furthermore, to evaluate the geographic feasibility and mathematical probability of India and its constituent states and UTs achieving a maximum childhood overweight prevalence ceiling of 5.0% by the year 2030, we implemented a fractional logistic regression framework using a quasi-maximum likelihood estimation (QMLE) approach,^24,25 with pooled data from 4 waves of the NFHS spanning 2006 to 2024. This method is specifically engineered to model bounded fractional responses, rates, and proportions natively (0 ≤ y_i ≤ 1; y_i indicates overweight in states or UTs) without requiring individual-level microdata denominators, such as those unavailable for NFHS-6. Additional details are provided in eBox 2 in Supplement 1 regarding (1) the methodologic framework and model specification; (2) the statistical notation and mathematical formulation of the QMLE-based fractional logistic regression; (3) the forecasting, uncertainty, and probabilistic estimation frameworks used to derive the 2030 overweight target from regression postestimations; and (4) the probability-based policy recommendations and their 3 typologies (sustained compliance, volatile or stalled margin, and critical intervention zones). As a supplementary analysis, we also estimated the prevalence of overweight and obesity disaggregated by sex across states and UTs using data from NFHS-4 and NFHS-5. Findings from this additional analysis may assist POSHAN Abhiyaan¹² in determining whether sex-specific interventions are required to effectively combat childhood overweight at the regional level.

All analyses were performed using Stata, version 18 (StataCorp).²⁶ We used Stata’s svy suite to apply sampling weights, accounting for the complex survey design and ensuring representative estimates for states and UTs.

Results

Sample Characteristics

The final sample included 467 995 children (241 645 [51.6%] male, 226 350 [48.4%] female) aged 0 to 59 months from NFHSs conducted between 2006 and 2021. The mean (SD) age of the children remained stable across the study period: 30.1 (17.1) months in 2006, 30.1 (17.0) months in 2016, and 29.9 (17.2) months in 2021. For anthropometric measurements, the unweighted prevalence of flagged cases (out-of-range or invalid z scores) among children was 4.02% (1935 of 48 084) in 2006, 4.33% (10 235 of 236 455) in 2016, and 3.57% (7661 of 214 531) in 2021 (Table 1). The age-specific prevalence of overweight and obesity indicates that between 2006 and 2021 the burden of these conditions increased across nearly all ages (eTable 1 and eFigure 1 in Supplement 1). Notably, the overweight burden increased in tandem with advancing age, higher maternal educational level, and improved economic status (eTable 1 in Supplement 1). Owing to the unavailability of NFHS-6 (2024) microdata at the time of analysis, specific sample characteristics could not be presented.

Trends and SAC in Overweight and Obesity

Between 2006 and 2021, the prevalence of overweight among children younger than 5 years increased from 1.55% (95% CI, 1.39%-1.73%) to 3.42% (95% CI, 3.30%-3.54%), with a similar upward trend observed for obesity, which increased from 0.50% (95% CI, 0.41%-0.60%) to 1.30% (95% CI, 1.23%-1.38%) (eTable 2 in Supplement 1). However, a downturn in overweight prevalence to 1.3% was observed in the recent NFHS-6 (2024). Maps showing the prevalence of overweight and obesity from 2006 to 2024 across India’s states and UTs are provided in eFigures 2 and 3 in Supplement 1 to demonstrate the spatial heterogeneity. State- and UT-level data (2006-2021) revealed marked variation in the burden of overweight and obesity (Figure). The median (IQR) SD for the proportion of children with overweight increased from 1.55 (1.23-2.82) in 2006 to 2.83 (3.21-5.17) in 2021. Concurrently, the median (IQR) SD for the proportion of children with obesity increased from 0.67 (0.39-1.08) in 2006 to 1.48 (1.14-2.01) in 2021 (eTable 3 in Supplement 1). In 2024, the median (IQR) SD for the overweight proportion decreased to 2.40 (1.00-4.10). Sex-stratified data reveal a higher national burden of child overweight and obesity among males than females, with both sexes showing increasing prevalence and substantial state- and UT-level variability between 2016 and 2021 (eTables 3-4 and eFigure 4 in Supplement 1).

Figure. Box Plots Showing Distribution of Childhood Overweight and Obesity Prevalence Across Indian States and Union Territories (UTs), 2006-2024.

In line with World Health Organization standards, the prevalence of overweight is a composite metric that inherently encompasses children classified as having obesity (>3 SDs). For further details on the data points underlying this figure, refer to eTable 2 in Supplement 1. The horizontal bar inside the box indicates the median (50th percentile). The lower and upper ends of the boxes represent the 25th and 75th percentiles, respectively, defining the IQR. The bottom whisker below the box is the lower adjacent value and equals the 25th percentile minus 1.5 times the IQR. The upper whisker above the box is the upper adjacent value and equals the 75th percentile plus 1.5 times the IQR. Circles indicate outliers.

The SAC presented in Table 2 indicates that the prevalence of overweight and obesity increased in India between 2006 and 2021 by 0.12 and 0.05 percentage points, respectively. During this time frame, all states and UTs followed a similar upward trajectory, except for Goa, which showed a downward trend in both overweight (−0.08 percentage points) and obesity (−0.06 percentage points). Between 2006 and 2024, a minor national decrease was observed in the SAC for overweight (−0.01 percentage points).

Table 2. SACs in Overweight and Obesity Among Children Younger Than 5 Years by State and UT, 2006-2024.

State or UT	SAC, percentage points
	Overweighta					Obesity
	2006-2016	2016-2021	2021-2024	2006-2021	2006-2024	2006-2016	2016-2021	2006-2021
Andhra Pradesh	−0.13	0.33	−0.39	0.03	−0.04	−0.05	0.12	0.01
Arunachal Pradesh	0.14	0.96	−0.30	0.42	0.30	0.08	0.34	0.17
Assam	0.11	0.52	−0.22	0.24	0.17	0.04	0.21	0.09
Bihar	0.10	0.25	−0.54	0.15	0.03	0.04	0.10	0.06
Chhattisgarh	0.16	0.22	−1.10	0.18	−0.04	0.00	0.22	0.07
Goa	−0.03	−0.19	−0.62	−0.08	−0.17	−0.12	0.07	−0.06
Gujarat	0.09	0.41	−0.92	0.19	0.01	0.06	0.16	0.09
Haryana	0.16	0.05	−0.60	0.12	0.002	0.08	0.03	0.06
Himachal Pradesh	0.07	0.77	−0.99	0.30	0.09	0.03	0.34	0.13
Jharkhand	0.10	0.25	−0.69	0.15	0.01	0.06	0.10	0.07
Karnataka	−0.01	0.12	−0.72	0.03	−0.09	0.03	0.07	0.05
Kerala	0.23	0.10	−0.64	0.19	0.05	0.08	0.00	0.05
Madhya Pradesh	0.07	0.06	−0.47	0.07	−0.02	0.03	0.04	0.03
Maharashtra	−0.10	0.47	−0.89	0.09	−0.07	−0.05	0.24	0.05
Manipur	0.10	0.05	NA	0.09	NA	0.01	0.03	0.01
Meghalaya	0.15	0.02	−0.48	0.11	0.01	0.03	0.01	0.02
Mizoram	<0.01	1.18	−0.42	0.39	0.26	−0.03	0.47	0.14
Nagaland	−0.10	0.24	0.42	0.02	0.08	−0.04	0.20	0.04
Odisha	0.09	0.18	−0.46	0.12	0.02	0.03	0.10	0.06
Punjab	0.10	0.36	−0.79	0.18	0.02	0.03	0.18	0.08
Rajasthan	0.05	0.24	−0.69	0.11	−0.02	0.01	0.06	0.03
Sikkim	0.06	0.21	−1.00	0.11	−0.08	0.02	0.07	0.04
Tamil Nadu	0.13	−0.14	−0.69	0.04	−0.08	0.02	0.02	0.02
Telangana	−0.16	0.54	−0.74	0.08	−0.06	−0.07	0.28	0.05
Tripura	0.07	1.05	−1.78	0.40	0.03	0.06	0.46	0.19
Uttar Pradesh	0.03	0.31	−0.85	0.12	−0.04	0.01	0.12	0.05
Uttarakhand	0.11	0.12	−1.15	0.11	−0.10	0.00	0.10	0.03
West Bengal	0.02	0.43	−0.72	0.16	0.01	−0.01	0.19	0.06
Andaman and Nicobar Islands (UT)	NA	0.49	0.60	NA	NA	NA	0.16	NA
Chandigarh (UT)	NA	0.16	0.75	NA	NA	NA	−0.11	NA
Dadra and Nagar Haveli as well as Daman and Diu (UT)	NA	−0.40	−0.45	NA	NA	NA	−0.09	NA
Jammu and Kashmir (UT)	0.31	0.79	−1.75	0.47	0.10	0.06	0.52	0.21
Ladakh (UT)	NA	1.80	−2.26	NA	NA	NA	1.22	NA
Lakshadweep (UT)	NA	1.77	−3.14	NA	NA	NA	1.17	NA
NCT Delhi (UT)	−0.27	0.56	−0.78	0.005	−0.13	−0.05	0.29	0.06
Puducherry (UT)	NA	0.32	−0.54	NA	NA	NA	0.12	NA
India	0.05	0.27	−0.71	0.12	−0.01	0.02	0.13	0.05

Abbreviations: NCT, National Capital Territory; NA, not available; SAC, standardized annual change; UT, union territory.

^a In line with World Health Organization standards, the prevalence of overweight is a composite metric that inherently encompasses children classified having obesity (>3 SDs).

Projecting the 2030 GNT for Overweight

Fractional logistic regression modeling (Table 3) found that national overweight prevalence was projected to reach 2.53% (95% CI, 0.23%-4.84%) by 2030, placing India in the sustained compliance category with a 98.2% probability of meeting the global target. Subnationally, 20 states and UTs fell under the sustained compliance category, 5 of which (Andhra Pradesh, Goa, Karnataka, Madhya Pradesh, and National Capital Territory of Delhi) exhibit a 100% success probability, led by Goa. Conversely, 3 states occupied a volatile or stalled margin with moderate success probabilities: Kerala (68.7% probability; 4.20% projected prevalence), Himachal Pradesh (32.6% probability), and Tripura (32.1% probability). Crucially, 6 states and UTs (Arunachal Pradesh, Assam, Jammu and Kashmir, Mizoram, Nagaland, and Sikkim) were classified into critical intervention zones, driven by low target probabilities and steep historical increases.

Table 3. Historical (2006-2024) and Projected Overweight Prevalence (Target ≤5.0% by 2030).

State or UTb	Prevalence of overweight, %a				Projected 2030 prevalence of overweight, % (95% CI)	Probability of target success, %	Policy recommendation (typologic category)
	2006	2016	2021	2024
Arunachal Pradesh	3.47	4.90	9.70	8.8	13.42 (10.21 to 16.63)	<0.01	Critical intervention zone (low probability)
Mizoram	4.27	4.27	10.17	8.9	12.74 (9.15 to 16.32)	<0.01	Critical intervention zone (low probability)
Sikkim	7.97	8.57	9.61	6.6	7.95 (5.23 to 10.66)	1.7	Critical intervention zone (low probability)
Assam	1.21	2.27	4.85	4.2	7.53 (5.01 to 10.04)	2.4	Critical intervention zone (low probability)
Nagaland	4.69	3.74	4.93	6.2	5.88 (4.27 to 7.49)	14.1	Critical intervention zone (low probability)
Jammu and Kashmir (UT)	2.48	5.60	9.55	4.3	9.39 (1.26 to 17.52)	14.5	Critical intervention zone (low probability)
Tripura	2.23	2.92	8.15	2.8	6.75 (−0.62 to 14.13)	32.1	Volatile or stalled margin (moderate probability)
Himachal Pradesh	1.13	1.83	5.66	2.7	6.28 (0.72 to 11.83)	32.6	Volatile or stalled margin (moderate probability)
Kerala	1.23	3.50	4.01	2.1	4.20 (0.98 to 7.42)	68.7	Volatile or stalled margin (moderate probability)
Punjab	1.43	2.38	4.16	1.8	3.65 (0.50 to 6.79)	80.0	Sustained compliance (high probability)
Gujarat	1.04	1.91	3.95	1.2	3.21 (−0.54 to 6.96)	82.5	Sustained compliance (high probability)
West Bengal	1.90	2.08	4.25	2.1	3.53 (0.97 to 6.10)	86.9	Sustained compliance (high probability)
Chhattisgarh	1.33	2.89	3.99	0.7	2.66 (−1.01 to 6.33)	89.4	Sustained compliance (high probability)
Bihar	0.22	1.17	2.41	0.8	2.68 (−0.75 to 6.11)	90.8	Sustained compliance (high probability)
Meghalaya	2.46	3.91	4.03	2.6	3.76 (1.97 to 5.54)	91.4	Sustained compliance (high probability)
Jharkhand	0.54	1.50	2.77	0.7	2.33 (−0.76 to 5.42)	95.5	Sustained compliance (high probability)
Haryana	1.46	3.07	3.30	1.5	2.88 (0.58 to 5.18)	96.5	Sustained compliance (high probability)
Odisha	1.67	2.60	3.49	2.1	3.31 (1.49 to 5.13)	96.6	Sustained compliance (high probability)
Tamil Nadu	3.65	4.96	4.28	2.2	3.20 (1.26 to 5.13)	96.6	Sustained compliance (high probability)
Uttarakhand	2.44	3.53	4.14	0.7	2.30 (−0.62 to 5.21)	96.6	Sustained compliance (high probability)
Maharashtra	2.82	1.84	4.17	1.5	2.37 (0.16 to 4.59)	99.0	Sustained compliance (high probability)
Rajasthan	1.61	2.07	3.26	1.2	2.32 (0.20 to 4.43)	99.4	Sustained compliance (high probability)
Uttar Pradesh	1.23	1.51	3.04	0.5	1.73 (−0.76 to 4.23)	99.5	Sustained compliance (high probability)
Telangana	2.27	0.71	3.43	1.2	1.79 (−0.17 to 3.74)	99.9	Sustained compliance (high probability)
Andhra Pradesh	2.27	1.02	2.66	1.5	1.66 (0.64 to 2.69)	100.0	Sustained compliance (high probability)
Goa	3.96	3.70	2.76	0.9	1.41 (0.30 to 2.53)	100.0	Sustained compliance (high probability)
Karnataka	2.65	2.55	3.17	1.0	1.75 (0.18 to 3.32)	100.0	Sustained compliance (high probability)
Madhya Pradesh	1.01	1.70	2.01	0.6	1.39 (−0.04 to 2.81)	100.0	Sustained compliance (high probability)
NCT Delhi (UT)	3.97	1.25	4.04	1.7	1.90 (0.20 to 3.59)	100.0	Sustained compliance (high probability)
India	1.55	2.05	3.42	1.3	2.53 (0.23 to 4.84)	98.2	Sustained compliance (high probability)

Abbreviations: NCT, National Capital Territory of Delhi; UT, union territory.

^a In line with World Health Organization standards, the prevalence of overweight is a composite metric that inherently encompasses children classified as having obesity (>3 SDs).

^b Projections were possible for only 29 states and UTs and the national level because the 4 required historic prevalence estimates were available exclusively for those entities. Excluded states and UTs are Andaman and Nicobar Islands (UT), Chandigarh (UT), Dadra and Nagar Haveli as well as Daman and Diu (UT), Ladakh (UT), Lakshadweep (UT), Puducherry (UT), and Manipur.

Discussion

This study provides a comprehensive assessment of the trends in overweight and obesity among children younger than 5 years across Indian states and UTs from 2006 to 2024, evaluating the country’s trajectory toward the 2030 GNT of maintaining or reducing the prevalence of overweight to 5% or less. Although prevalence estimates revealed a concerning national upward trend in overweight and obesity between 2006 and 2021, a sudden decrease in overweight prevalence to 1.3% in 2024 warrants a reassessment of overweight prevention strategies across India’s states and UTs. Furthermore, fractional logistic regression analysis found that 9 states and UTs exhibited a low to moderate probability of achieving the 2030 GNT threshold.

The shift from an increasing trend in overweight between 2006 and 2021 to a sudden decrease in 2024 marks remarkable progress in India’s childhood overnutrition prevention efforts. Although the specific causes of this decrease require further in-depth research, the reduction in childhood overweight could be attributed to an aggressive restructuring of India’s flagship nutrition interventions under POSHAN Abhiyaan.¹² This initiative enabled digital tracking across millions of Anganwadi centers (synonymous to courtyard shelters), allowing for the rapid identification and community-level monitoring of growth deviations to prevent both undernutrition and overnutrition at early stages.²⁷ Mirroring India, notable reductions in overweight among children younger than 5 years have occurred in other low- and middle-income countries, such as Chile and Kenya.¹ In Chile, prevalence decreased from 9.9% in 2012 to 8.7% in 2024, driven by robust food environment reforms, including a 2014 sugar-sweetened beverage tax.¹ The decrease in Kenya reflects a sustained commitment to mitigating the double burden of malnutrition, achieved by operationalizing a double-duty actions framework that targets undernutrition and overweight simultaneously.¹

Regarding the 2030 GNT for overweight, 5 of the 6 low-probability critical intervention zones are Northeastern states: Arunachal Pradesh, Assam, Mizoram, Nagaland, and Sikkim. Within the moderate-probability volatile or stalled margin category, Tripura represents another Northeastern state struggling with adherence. Cumulatively, these 6 states form a distinct regional cluster at elevated risk of failing to achieve the 2030 overnutrition mitigation targets. The high probability of an increasing overweight burden in the Northeastern states may be driven by increasing socioeconomic status, rapid urbanization, and a concurrent depletion of urban recreational spaces, all of which promote sedentary lifestyles among young children.²⁸ Furthermore, meat consumption in the Northeast remains a documented risk factor—constrained purchasing power further restricts dietary diversity. This economic limitation forces a reliance on low-fiber, energy-dense foods, ultimately accelerating regional overnutrition trends.²⁹

Limitations

A few limitations should be considered when interpreting the findings of this study. First, select self-reported covariates, such as child age and maternal educational level, are subject to recall error and social desirability bias. Although age displacement and heaping occur in NFHS data lacking official birth records, this is unlikely to alter our findings. Because weight for height z scores evaluate weight relative to measured height rather than age, they are inherently robust against age misreporting. A minor risk of misclassification remains only if an age error causes a child to cross the 24-month threshold, where WHO growth standards transition from recumbent length to standing height tables. Second, excluding children with missing or implausible anthropometric data introduces a potential risk of selection bias if they differ systematically from the analyzed sample. To evaluate this, we conducted a sensitivity analysis comparing maternal and household characteristics between the included and excluded subsamples and found no meaningful systematic differences. Furthermore, because standard NFHS sampling weights explicitly adjust for nonresponse at both the household and individual levels,³⁰ population representativeness is maintained, and the likelihood of substantial selection bias affecting our estimates is minimized. Third, due to the absence of obesity prevalence data in the NFHS-6 fact sheets, this variable could not be analyzed or discussed. Fourth, because the fractional logistic regression model relies on only 4 time points, it is constrained to a parsimonious specification and yields correspondingly wide CIs. Consequently, readers should avoid overinterpreting the precision of individual projections. The primary value of this reanalysis lies in its bounded predictions and principled uncertainty quantification rather than in pinpoint forecasting precision.

Conclusions

India’s prevalence of overweight among children younger than 5 years decreased sharply to 1.3% in 2024, highlighting the potential success of scaled interventions, such as POSHAN Abhiyaan’s digital growth-monitoring infrastructure.²⁷ However, national averages mask a distinct high-risk cluster in the Northeast, where 6 states show low to moderate probabilities of achieving the 2030 global target, likely driven by rapid urbanization, sedentary lifestyles, and dietary transitions toward energy-dense foods.^28,29 The findings of this study are expected to inform prioritized, localized interventions to mitigate childhood overweight and obesity across Indian states and UTs. Future policies must prioritize these at-risk states through tailored subnational frameworks addressing regional drivers. Concurrently, research is urgently needed to investigate the mechanisms behind the 2024 decrease, ensuring equitable progress toward overnutrition mitigation benchmarks.

Supplement 1.

eBox 1. Literature search strategy in PubMed investigating trends in the prevalence of overweight and obesity among children under-five in India, with a focus on the 2030 Global Nutrition Targets for this age group

eBox 2. Methodology and forecasting analysis

eTable 1. Prevalence of overweight by age group, maternal education, and household wealth quintile among children under-five, National Family Health Survey, 2006-2024

eTable 2. Prevalence of overweight and obesity across states and union territories (UTs) among under-five children in India, 2006-2024

eTable 3. Measures of dispersion (SD and IQR) for the prevalence of overweight and obesity across Indian States and Union Territories, 2006–2024

eTable 4. Prevalence of overweight and obesity among male and female children by state and union territory (UT), 2016-2021

eFigure 1. Prevalence (%) of overweight and obesity by child age, 2006-2021

eFigure 2. Prevalence (%) of overweight (from 2006 to 2024) across states and union territories of India

eFigure 3. Prevalence (%) of obesity (from 2006 to 2021) across states and union territories of India

eFigure 4. Distribution of sex-stratified prevalence (%) of childhood overweight and obesity across Indian states and Union Territories (UTs), 2016–2021

Supplement 2.

Data Sharing Statement