Global and National Socioeconomic Disparities in Obesity, Overweight, and Underweight Status
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it