Moderate to high levels of exercise are associated with higher resting energy expenditure in community-dwelling postmenopausal women
Bibliographic record
Abstract
Postmenopausal women experience an age-related decline in resting energy expenditure (REE), which is a risk factor for energy imbalance and metabolic disease. Exercise, because of its association with greater lean tissue mass and other factors, has the potential to mediate REE decline, but the relation between exercise and REE in postmenopausal women is not well characterized. This study tests the hypothesis that exercise energy expenditure (EEE) is positively associated with REE and can counter the effects of age and menopause. It involves a cross-sectional sample of 31 healthy postmenopausal women (aged 49-72 years) with habitual exercise volumes at or above levels consistent with current clinical recommendations. Subjects kept exercise diaries for 4 weeks that quantified exercise activity and were measured for body composition, maximal oxygen uptake, and REE. Multiple regression analysis was used to test for associations between EEE, age, body composition, and REE. There was a significant positive relation between EEE and lean tissue mass (fat-free mass and fat-free mass index). The relation between REE and EEE remained significant even after controlling for lean tissue mass. These results support the hypothesis that exercise is positively associated with REE and can counter the negative effects of age and menopause. They also indicate a continuous relation between exercise and REE across ranges of exercise, from moderate to high. Exercise at levels that are at or above current clinical guidelines might, in part, ameliorate the risk for energy imbalance and metabolic disease because of its positive relation with REE.
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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 | 0.000 | 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 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".