Sex Differences in the Effects of Weight Loss Diets on Bone Mineral Density and Body Composition: POUNDS LOST Trial
Bibliographic record
Abstract
CONTEXT: Weight loss is associated with reduction in bone mineral density (BMD). OBJECTIVE: The objective was to address the role of changes in fat mass (FM) and lean mass (LM) in BMD decline in both sexes. DESIGN: A 2-year randomized controlled trial, the Preventing Overweight Using Novel Dietary Strategies (POUNDS-LOST). SETTING: The setting was the general community. PATIENTS OR OTHER PARTICIPANTS: Enrolled were 424 overweight and obese participants (mean age, 52 ± 9 y; 57% females). INTERVENTION: Intervention included weight loss diets differing in fat, protein, and carbohydrates. MAIN OUTCOME MEASURES: Main outcome measures were change in spine, total hip (TH), and femoral neck (FN) BMD and sex differences after dietary intervention. RESULTS: At baseline, a stronger correlation between BMD and body composition measurements was observed in women, primarily with LM (r = 0.419, 0.507, and 0.523 for spine, FN, and TH, respectively; all P < .001). In men, only LM correlated with hip BMD (r = 0.298; P < .001). Mean weight loss at 2 years was -6.9%, without differences among diets. Two-year changes in BMD were 0.005 (P = .04), -0.014 (P < .001), and -0.014 g/cm(2) (P < .001), at the spine, TH, and FN, respectively. These changes directly correlated with changes in LM in women (r = 0.200, 0.324, and 0.260 for spine, FN, and TH, respectively), whereas FM loss correlated only with changes in TH BMD (0.274; P < .001). In men, changes in LM (-0.323; P < .001) and FM (-0.213; P = .027) negatively correlated with changes in spine BMD. CONCLUSIONS: Weight loss diets result in sex-specific effects on BMD. Although men exhibited a paradoxical increase in spine BMD, women tended to decrease in BMD at all sites.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".