Prevalence of Obesity among School-going Children in India: A Comprehensive Systematic Review, Meta-analysis, and Spatial Analysis
Bibliographic record
Abstract
Childhood obesity is a notable public health concern in India and other developing nations. There are many published articles on the prevalence of obesity among school children in various states of India. Estimating obesity prevalence at state and national levels will help understand its distribution and guide effective prevention strategies. To estimate the pooled prevalence of obesity among school-going children in India using a systematic review and spatial analysis. This systematic review and meta-analysis include cross-sectional studies from 1995 to 2023, reporting the prevalence of obesity among school-going children in India. Two authors independently screened and extracted data from PubMed, Scopus, and the Web of Science. Study quality was assessed using the Newcastle-Ottawa Scale, and the random effect model was used as there was high heterogeneity (I 2 >50%). Spatial analysis and cumulative meta-analysis were performed using R and STATA software. A total of 125 articles were selected based on the inclusion and exclusion criteria. The overall pooled prevalence of obesity was found to be 6.97% (95% CI: 5.97, 7.97). Among the different regions of India, the highest pooled prevalence was found in the Northern region, that is, 8.58% (95% CI: 5.47, 11.69), and the lowest in the Central region, that is, 5.63% (95% CI: 3.95, 7.31). The cumulative analysis indicated a rising trend in the prevalence of obesity among school-going children over the years. This meta-analysis offers vital insights into its scope and geographical distribution, helping to develop effective strategies to prevent its persistence into adulthood. Trial registration: The PROSPERO registration number is CRD42023431574.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".