Dose–response effects of aerobic exercise on energy compensation in postmenopausal women: combined results from two randomized controlled trials
Bibliographic record
Abstract
Despite the clear health benefits of exercise, exercised-induced weight loss is often less than expected. The term ‘exercise energy compensation’ is used to define the amount of weight loss below what is expected for the amount of exercise energy expenditure. We examined the dose–response effects of exercise volume on energy compensation in postmenopausal women. Data from Alberta Physical Activity and Breast Cancer Prevention (ALPHA) and Breast Cancer and Exercise Trial in Alberta (BETA) were combined for the present analysis. The ALPHA and BETA trials were two-centred, two-armed, 12-month randomized controlled trials. The ALPHA trial included 160 participants randomized to 225 min per week of aerobic exercise, and the BETA trial randomized 200 participants to each 150 and 300 min per week of aerobic exercise. All participants were aged 50–74 years, moderately inactive (<90 min per week of exercise), had no previous cancer diagnosis and a body mass index between 22 and 40 kg m −2 . Energy compensation was based on changes in body composition (dual-energy X-ray absorptiometry scan) and estimated exercise energy expenditure from completed exercise volume. Associations between Δenergy intake, ΔVO 2peak and Δphysical activity time with energy compensation were assessed. No differences in energy compensation were noted between interventions. However, there were large inter-individual differences in energy compensation between participants; 9.4% experienced body composition changes that were greater than expected based on exercise energy expenditure, 64% experienced some degree of energy compensation and 26.6% experienced weight gain based on exercise energy expenditure. Increases in VO 2peak were associated with reductions in energy compensation ( β =−3.44 ml kg −1 min −1 , 95% confidence interval for β =−4.71 to −2.17 ml kg −1 min −1 ; P =0.0001). Large inter-individual differences in energy compensation were noted, despite no differences between activity doses. In addition, increases in VO 2peak were associated with lower energy compensation. Future studies are needed to identify behavioral and metabolic factors that may contribute to this large inter-individual variability in energy compensation.
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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 | 0.013 | 0.019 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.012 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".