The influence of ethnicity and gender on the association between measured obesity and cardiorespiratory fitness with self-rated overweight, physical activity and health
Bibliographic record
Abstract
BACKGROUND: Little is known about how ethnicity may influence how self-rated physical activity (PA) and obesity relates to measured obesity, cardiorespiratory fitness and self-rated health. AIMS: To examine the influence of ethnicity on the association between: (1) self-rated and measured obesity; (2) self-reported PA and cardiorespiratory fitness; and (3) obesity and PA with self-rated health. METHODS: Data from NHANES 1999-2004 (2,981 adults) was used. RESULTS: Compared to white and overweight black men, Hispanic men were less likely to consider themselves overweight (OR = 0.36-0.56). Compared to white men, black active men were more likely to report being more active than their peers (OR = 1.44) but were less likely to be fit (OR = 0.74). Black active women and non-white overweight women were less likely to self-rate as having very good or excellent health as compared to white women with similar self-reported and measured health factors. CONCLUSIONS: Ethnicity and gender influence how self-rated and measured health factors interrelate.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".