A cross-national comparison of obesity using body mass index-for-age percentiles: results from the Canadian Longitudinal Study on Aging and the United States Health and Retirement Study
Bibliographic record
Abstract
Obesity prevalence is increasing in both the United States and Canada concurrently with demographic shifts, resulting in increasingly older populations with a high prevalence of obesity. Older adults have unique risk factors and outcomes related to obesity, such as age-related physiologic changes over time, that need to be considered when assessing obesity. In a comparison of data from the Canadian Longitudinal Study on Aging and the US Health and Retirement Study, we use BMI-for-age percentile curves to examine obesity in the United States and Canada in individuals 50+ years. Overall, BMI values were higher among individuals in the United States and declined with chronological age in both countries. BMI values were higher among women than men in both countries. BMI-for-age percentiles reached a peak at a younger age among women in Canada compared to individuals in the United States. Using a novel measurement of obesity, the present work describes differences in obesity in older adults in Canada and the United States and highlights the need for future work in obesity research in age- and sex-disaggregated contexts. This article is part of a Special Collection on Cross-National Gerontology.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".