Global and National Socioeconomic Disparities in Obesity, Overweight, and Underweight Status
Bibliographic record
Abstract
Objective. To examine the association between socioeconomic factors and weight status across 53 countries. Methods. Data are cross-sectional and from the long version of the World Health Survey (WHS). There were 172,625 WHS participants who provided self-reported height and weight measures and sociodemographic information. The International Classification of adult weight status was used to classify participants by body mass index (BMI): (1) underweight (<18.5), (2) normal weight (18.5-24.9), (3) overweight (25.0-29.9), and (4) obese (>30.0). Multinomial regression was used in the analyses. Results. Globally, 6.7% was underweight, 25.7% overweight, and 8.9% obese. Underweight status was least (5.8%) and obesity (9.3%) most prevalent in the richest quintile. There was variability between countries, with a tendency for lower-income quintiles to be at increased risk for underweight and reduced risk for obesity. Conclusion. International policies may require flexibility in addressing cross-national differences in the socio-economic covariates of BMI status.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".