Sarcopenic Obesity in Women with Polycystic Ovary Syndrome: Effect of a Pulse Based‐Diet and Exercise Intervention
Bibliographic record
Abstract
Polycystic ovary syndrome (PCOS) is the most common endocrine disorder in women of reproductive age and leads to an increased risk of heart disease, diabetes, infertility and endometrial cancer. Sarcopenic obesity is a term used to describe low appendicular skeletal muscle mass (ASM) relative to total body mass and, although most commonly associated with the aging population, women with PCOS share many of the characteristics associated with this condition including increased visceral adiposity, chronic inflammation and insulin resistance. We hypothesized that a pulse‐based diet (e.g. beans, lentils) would have a positive effect on body composition as analyzed by dual energy X‐ray absorptiometry. Sixty‐seven women with PCOS aged 18–35y were enrolled in the study with 44 completing the randomly assigned intervention of either a pulse‐based diet (n=25) or the National Cholesterol Education Program (NCEP) therapeutic lifestyle changes (TLC) diet (n=19) for 16 wk while participating in an exercise program. At baseline, the average % ASM was 24.2 ± 3.1% and 56% of women with PCOS were classified as sarcopenic obese as defined by having a % ASM 2 standard deviations below the mean for healthy young females studied by our group (30.4 ± 3.2%; n=14). Following the intervention, BMI was lower in both groups (p<0.001; Pulse −1.0 vs TLC −0.7) as well as percent fat mass (p<0.005; Pulse −0.5 vs TLC −0.8 %). Although there were no changes in lean body mass following the intervention, % ASM was higher in both groups (p<0.005; Pulse +1.0 vs TLC +1.3 %), suggesting that a pulse based diet is equally effective as the TLC diet when combined with exercise to reduce the prevalence of sarcopenic obesity in women with PCOS. Support or Funding Information Supported by the Saskatchewan Pulse Growers, Agriculture Agri‐Food Canada (Cluster Program) and Saskatchewan Health Research Foundation
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.003 | 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".