Comparison of dietary and physical activity behaviors in women with and without polycystic ovary syndrome: a systematic review and meta-analysis of 39 471 women
Bibliographic record
Abstract
BACKGROUND: Lifestyle (dietary and/or physical activity [PA]) modification is recommended as first-line therapy to manage polycystic ovary syndrome (PCOS). Current recommendations are based on healthy lifestyle practices for the general public since evidence for unique lifestyle approaches in PCOS is limited and low quality. OBJECTIVE AND RATIONALE: We aimed to synthesize evidence on dietary and PA behaviors between women with PCOS and those without PCOS. Primary outcomes were overall diet quality, total energy intake and total PA, and secondary outcomes included macronutrients, micronutrients, food groups, foods, glycemic indices, sedentary time and sitting levels. We conducted this work to identify any unique lifestyle behaviors in women with PCOS that could underlie the propensity of weight gain and obesity in PCOS and be targeted for precision nutrition and PA interventions. These findings could be used to inform future practice recommendations and research that more effectively address complications (weight gain, obesity, diabetes, infertility, cardiovascular disease and mental health) in this high-risk population. SEARCH METHODS: Databases of MEDLINE, Web of Science, Scopus and CINAHL were searched until 15 February 2022 to identify observational studies documenting dietary and PA behaviors between women with PCOS and without PCOS (Controls). Studies on children, adolescents (<18 years), pregnant or menopausal-aged women (>50 years) were excluded. Data were pooled by random-effects models and expressed as (standardized) mean differences (MD) and 95% CIs. The risk of bias was assessed by the Newcastle-Ottawa scale (NOS). OUTCOMES: Fifty-four studies (N = 39 471 participants; [n = 8736 PCOS; 30 735 Controls]) were eligible (96%; [52/54] NOS scores ≥ 7). Women with PCOS had higher cholesterol (MD: 12.78, 95% CI: 1.48 to 24.08 mg/day; P = 0.03; I2 = 19%), lower magnesium (MD: -21.46, 95% CI: -41.03 to -1.91 mg/day; P = 0.03; I2 = 76%), and a tendency for lower zinc (MD: -1.08, 95% CI: -2.19 to -0.03 mg/day; P = 0.05; I2 = 96%) intake, despite lower alcohol consumption (MD: -0.95, 95% CI: -1.67 to 0.22 g/day; P = 0.02; I2 = 0%) versus Controls. Also, women with PCOS had lower total PA (standardized mean difference: -0.38, 95% CI: -0.72 to 0.03; P = 0.03; I2 = 98%). Conversely, energy, macronutrients (carbohydrate, fat, protein, fiber), micronutrients (folic acid, iron, calcium, sodium), glycemic index and glycemic load were similar (all: P ≥ 0.06). Most eligible studies reported lower total adherence to healthy eating patterns or poorer consumption of major food groups (grains, fruits, vegetables, proteins, seeds, nuts, dairy) in women with PCOS, as described narratively since variable study methodology did not permit meta-analyses. WIDER IMPLICATIONS: Collective evidence supports that women with PCOS have a lower overall diet quality, poorer dietary intakes (higher cholesterol, lower magnesium and zinc) and lower total PA, despite lower alcohol consumption versus those without PCOS. Considerable heterogeneity among studies reinforces the need for research to address any relative contributions of other factors (e.g. genetic, metabolic or sociodemographic) to the observed differences. These clarifications may contribute to future evidence-based guideline recommendations on monitoring and managing PCOS in the era of precision lifestyle medicine.
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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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.032 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".