The impact of lifestyle on the reproductive, metabolic, and psychological well-being of women with polycystic ovary syndrome (PCOS)
Bibliographic record
Abstract
Introduction: Polycystic ovary syndrome (PCOS) affects the reproductive, metabolic, and psychological health of 6 to 18% of women worldwide. The impact of lifestyle is poorly understood in research and practice. This dissertation aims to elucidate how dietary intake, physical activity, and psychological well-being relate to the array of symptoms and characteristics of PCOS. Methods: Women diagnosed with PCOS were compared to women without PCOS with subfertility in four observational studies. Data collected included: dietary intake, physical activity, psychological well-being symptoms (depression, anxiety, stress, and quality of life), anthropometrics, metabolic and reproductive hormonal assays. A protocol for a randomized controlled trial involving a lifestyle intervention is presented. Results: Women with PCOS had similar caloric intake and physical activity as women without PCOS, despite being more overweight (P < 0.001). In women with PCOS, those with insulin resistance (IR) consumed less fiber (P < 0.05), a greater glycemic load (P = 0.03) and less magnesium (P < 0.05) than without IR. Fiber intake was negatively correlated with IR (rho = -0.35, P < 0.005), fasting insulin (rho = -0.37, P < 0.005), glucose tolerance (rho = -0.23, P < 0.05), testosterone (rho = -0.35, P < 0.005), and dehydroepiandrosterone sulfate (rho = -0.27, P = 0.02). Magnesium intake was negatively correlated with IR (rho = -0.32, P < 0.01), C-reactive protein (rho = -0.47, P < 0.001), and testosterone (rho = -0.30, P < 0.01), but positively correlated with HDL cholesterol (rho = 0.29, P = 0.01). Symptoms of anxiety were significantly higher in women with PCOS, particularly those with hyperandrogenism (P < 0.01). In women with PCOS and increased depressive symptoms, vitamin D intake was significantly decreased (P < 0.02). Conclusions: While caloric intake of women with PCOS could not explain obesity, increasing fiber and magnesium intakes may reduce IR, hyperandrogenemia, and dyslipidemia. Women with PCOS, particularly hyperandrogenic phenotypes, experience increased symptoms of anxiety potentially related to hirsutism, which challenges societal expectations of women’s appearance. A lifestyle focused on a high fiber, low glycemic diet, supplementation, physical activity, and managing emotional distress may improve some symptoms of 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| 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".