Effect of a pulse-based diet and aerobic exercise on bone measures and body composition in women with polycystic ovary syndrome: A randomized controlled trial
Bibliographic record
Abstract
Polycystic ovary syndrome (PCOS) is the most common endocrine disorder in women of reproductive age, with clinical symptoms including menstrual dysfunction and hyperandrogenemia, as well as insulin resistance which is thought to be a key contributing factor to symptoms. Insulin is also thought to positively affect bone while oligo- and amenorrhea are known to negatively affect bone. Lifestyle modification is the first recommendation to treat symptoms of PCOS; however, little is known about the effect of lifestyle interventions on bone measures in this population. Pulses (e.g., chickpeas, beans, split peas, lentils) have been shown to lower fasting insulin, and the objective of this study was to determine the effect of a pulse-based diet compared to the therapeutic lifestyle changes (TLC) diet on bone measures and body composition in women with PCOS. Women aged 18-35 years with PCOS were randomized to either a pulse-based diet or the TLC diet for 16-weeks while following an aerobic exercise program. Thirty-one in the TLC group and 29 in the pulse group completed dual-energy X-ray absorptiometry analysis following the intervention. After 16-weeks, both groups had a lower BMI, whole body fat mass, and % fat (p < 0.005), with no difference in lean mass. In both groups, lumbar spine bone mineral content (BMC) and density were higher following the intervention (p < 0.05) while femoral neck bone mineral density (BMD) was lower (p < 0.05). Intertrochanteric section modulus improved in both groups while there was a group x time interaction in femoral shaft subperiosteal width which was more favorable in the pulse group (p < 0.05). This study demonstrates that the femoral neck may be compromised during a lifestyle intervention in women with PCOS. Research is warranted to preserve bone health during lifestyle change in women with PCOS.
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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) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".