Light physical activity is a better determinant of lower adiposity during the menopausal transition
Bibliographic record
Abstract
OBJECTIVE: To investigate the relationship between time spent performing physical activity (PA) and adiposity across the menopausal transition. METHODS: Body weight and body composition were analyzed in 65 women (47-54 years old; body mass index 23.2 ± 2.4 kg/m(2)) in a 5-year prospective study. Time spent in PA of varying intensities (sedentary, light, moderate and vigorous) was determined from 7-day accelerometer measurement and energy intake with a 7-day food diary. RESULTS: Significant negative correlations were observed between the time spent in light-intensity PA and fat mass (FM) (r = -0.38, p < 0.005), central FM (r = -0.36, p < 0.005), peripheral FM (r = -0.33, p < 0.01), and percent body fat (r = -0.42, p < 0.001) at year 1, respectively. No significant correlations were noted between measures of adiposity and time spent performing either moderate or vigorous PA. Analyses using tertiles of time spent in light PA at year 1 showed that FM (20.7 ± 4.0 vs. 20.3 ± 6.6 vs. 16.6 ± 4.6 kg, p < 0.05), central FM (10.1 ± 2.6 vs. 10.0 ± 3.8 vs. 7.8 ± 2.4 kg; p < 0.05) and percent body fat (34.5 ± 5.1 vs. 32.2 ± 7.7 vs. 28.1 ± 6.2%, p < 0.01) were all significantly lower in women in the highest tertile. These differences remained significant after covariate analyses using time spent in moderate- and high-intensity PA and total energy intake. Finally, lower levels of FM, percent body fat, central and peripheral FM persisted in women who spent more time in light PA (highest tertiles) over the 5-year follow-up. CONCLUSION: Our results suggest that the time spent performing light PA may have a greater impact on adiposity than moderate and/or vigorous PA, an observation independent of the menopausal status.
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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 | 0.000 | 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 | 0.001 | 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".