General and abdominal obesity is related to socioeconomic status and food choices: a cross-sectional study
Bibliographic record
Abstract
Purpose This paper aims to evaluate the prevalence of general obesity (GO) and abdominal obesity (AO) in the north-west of Iran and investigate the association with food choices and socioeconomic status (SES). Design/methodology/approach In this cross-sectional study, 500 subjects aged ≥ 18 years were studied. Data on their basic characteristics, anthropometric measurements, dietary habits and physical activity were collected. The authors examined the association between GO and AO with SES and food choices using multiple logistic regression analysis. Findings The prevalence of GO and AO was 26.6 and 43.4%, respectively. A positive association was observed between age and GO (pfor trend <0.001) and AO (pfor trend 0.005) in both sexes. However, a negative correlation was detected between education and income with GO and AO (pfor trend <0.001). Two or more servings of fruit consumption a day were associated with lower odds of obesity. It was observed that the odds of GO and AO decreased by three or more servings of daily fruit. The consumption of dairy products in two or more servings a day led to a reduction in odds of GO and AO. The consumption of five or more servings of legumes, beans and nuts a week was associated with lower odds of GO and AO. Originality/value Educational attainment, greater income and a higher intake of some specific food groups were associated with lower odds of obesity in the area. More population-based investigations are required to develop effective preventive strategies to control the status of being overweight and obesity in different regions.
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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 | 0.001 |
| 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 | 0.000 |
| 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".