Effect of Diet and Exercise, Alone or Combined, on Weight and Body Composition in Overweight‐to‐Obese Postmenopausal Women
Bibliographic record
Abstract
Lifestyle interventions for weight loss are the cornerstone of obesity therapy, yet their optimal design is debated. This is particularly true for postmenopausal women; a population with a high prevalence of obesity yet toward whom fewer studies are targeted. We conducted a year-long, 4-arm randomized trial among 439 overweight-to-obese postmenopausal sedentary women to determine the effects of a calorie-reduced, low-fat diet (D), a moderate-intensity, facility-based aerobic exercise program (E), or the combination of both interventions (D+E), vs. a no-lifestyle-change control (C) on change in body weight and composition. The group-based dietary intervention had a weight-reduction goal of ≥10%, and the exercise intervention consisted of a gradual escalation to 45-min aerobic exercise 5 day/week. Participants were predominantly non-Hispanic whites (85%) with a mean age of 58.0 ± 5.0 years, a mean BMI of 30.9 ± 4.0 kg/m(2) and an average of 47.8 ± 4.4% body fat. Baseline and 12-month weight and adiposity measures were obtained by staff blinded to participants' intervention assignment. Three hundred and ninety nine women completed the trial (91% retention). Using an intention-to-treat analysis, average weight loss at 12 months was -8.5% for the D group (P < 0.0001 vs. C), -2.4% for the E group (P = 0.03 vs. C), and -10.8% for the D+E group (P < 0.0001 vs. C), whereas the C group experienced a nonsignificant -0.8% decrease. BMI, waist circumference, and % body fat were also similarly reduced. Among postmenopausal women, lifestyle-change involving diet, exercise, or both combined over 1 year improves body weight and adiposity, with the greatest change arising from the combined intervention.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".