Behavioral Predictors of Weight Regain in Postmenopausal Women: Exploratory Results From the Breast Cancer and Exercise Trial in Alberta
Bibliographic record
Abstract
OBJECTIVE: This secondary analysis assessed associations between changes in energy balance and sleep behaviors and the risk of weight regain following exercise-induced weight loss. METHODS: Of 400 participants initially randomized in the Breast Cancer and Exercise Trial in Alberta (BETA), 227 lost weight following the moderate- to vigorous-intensity exercise intervention (-4.2 ± 3.6 kg) and were included in this analysis. Self-reported energy intake (EI), sleep duration, quality and timing, and objective measurements of physical activity (PA) and sedentary time were collected at the end of the intervention and the end of follow-up. Linear regression models assessed associations between changes in these behaviors and risk of weight regain during follow-up. RESULTS: Participants regained 43% of the weight lost during follow-up. Reductions in moderate to vigorous PA (β = -1.00; 95% CI = -1.74 to -0.25 h/d; P = 0.01) and steps per day (β = -0.0003; 95% CI = -0.0005 to -0.0001 steps/d; P = 0.004); increases in sedentary time (β = 0.54; 95% CI = 0.67 to 1.02 h/d; P = 0.03), EI (β = 0.001; 95% CI = 0.0003 to 0.002 kcal; P = 0.01), and fat intake (β = 0.004; 95% CI = 0.001 to 0.006 kcal; P = 0.002); and delayed sleep timing midpoint (β = 0.02; 95% CI = 0.004 to 0.03 min; P = 0.01) were associated with weight regain during follow-up. CONCLUSIONS: These exploratory results suggest that reductions in moderate to vigorous PA; increases in EI, fat intake, and sedentary time; and delayed sleep timing midpoint were significantly associated with risk of weight regain.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".