Prevalence and correlates of weight gain attempts across five countries
Bibliographic record
Abstract
OBJECTIVE: To determine the prevalence and correlates of weight gain attempts in a pooled sample of adults aged 18 and older from Canada, Australia, the United Kingdom, the United States, and Mexico. METHOD: ), weight perception, country, survey year, and sex. Logistic regression analyses were estimated to determine the sociodemographic correlates (age, race/ethnicity, education, BMI, weight perception, weight perception accuracy, and self-rated mental health) of weight gain attempts among the pooled sample stratified by sex. RESULTS: Men (10.4%) were significantly more likely than women (5.4%) to report weight gain attempts (p < .001). Nearly one in five (17.1%) men with a BMI in the "normal" range (≥18.5 to <25.0) reported weight gain attempts. Among both men and women, minority group identity was associated with higher odds, while older age and higher BMI category were associated with lower odds, of reporting weight gain attempts. Country differences over the two survey years showed the prevalence of weight gain attempts in 2019 (vs. 2018) was higher among women in Australia (p < .05) and men in the United States (p < .01). DISCUSSION: Weight gain attempts are more common among men, compared to women, across five countries, potentially reflecting the global salience of the pursuit of a muscular body.
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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 | 0.001 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".