Lifestyle Interventions Targeting Body Weight Changes during the Menopause Transition: A Systematic Review
Bibliographic record
Abstract
OBJECTIVE: To determine the effectiveness of exercise and/or nutrition interventions and to address body weight changes during the menopause transition. METHODS: A systematic review of the literature was conducted using electronic databases, grey literature, and hand searching. Two independent researchers screened for studies using experimental designs to evaluate the impact of exercise and/or nutrition interventions on body weight and/or central weight gain performed during the menopausal transition. Studies were quality appraised using Cochrane risk of bias. Included studies were analyzed descriptively. RESULTS: Of 3,564 unique citations screened, 3 studies were eligible (2 randomized controlled trials, and 1 pre/post study). Study quality ranged from low to high risk of bias. One randomized controlled trial with lower risk of bias concluded that participation in an exercise program combined with dietary interventions might mitigate body adiposity increases, which is normally observed during the menopause transition. The other two studies with higher risk of bias suggested that exercise might attenuate weight loss or weight gain and change abdominal adiposity patterns. CONCLUSIONS: High quality studies evaluating the effectiveness of interventions targeting body weight changes in women during their menopause transition are needed. Evidence from one higher quality study indicates an effective multifaceted intervention for women to minimize changes in body adiposity.
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 | 0.007 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".