Activity level and body mass index: An analysis of the Canadian Forces Health and Lifestyle Information Survey
Bibliographic record
Abstract
The increasing prevalence of overweight status and obesity among the general population is a major public health concern. There is debate surrounding the role of recreational physical activity in the prevention of weight gain at the population level. This study examined the cross-sectional association between overweight status and obesity and recreational physical activity in a large representative sample of members of the Canadian Armed Forces (n = 4749) using polytomous logistic modelling. A systematic review of the literature looking at the longitudinal relationship between activity level and body mass was conducted and a health promotion intervention was developed. After adjustment for several significant covariates, recreational energy expenditure was significantly and inversely associated with the prevalence of class I obesity compared to normal weight classification (OR 0.94, 95% CI 0.90-0.97), but was not significantly associated with the odds of having a BMI classified as either overweight or obese class II/III (OR 1.01, 95% CI 0.98-1.03; OR 0.93, 95% CI 0.85-1.02) versus having a BMI classified as normal. This study suggests efforts to prevent overweight status and obesity at the population level could profitably address physical activity habits but need to consider the multi-factorial nature of the problem.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.010 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".