Dietary diversity score is inversely related to the risk of polycystic ovary syndrome in Tehranian women: a case-control study
Bibliographic record
Abstract
Polycystic ovary syndrome (PCOS) is the most common endocrine disorder among women of reproductive age and is affected by various dietary factors. Therefore, this study aimed to investigate the relationship between dietary diversity score (DDS) and the risk of PCOS. Our case-control study was conducted in the summer and autumn of 2019 in Taleghani and Arash hospitals in Tehran, Iran. A total of 494 participants (203 cases and 291 controls) were included in the study. Thereafter, their demographic information, dietary intake, and anthropometric and physical activity assessments were gathered. A validated semi-quantitative food frequency questionnaire was then used to calculate the DDS by scoring 5 food groups. To evaluate the risk of PCOS in association with DDS, the subjects were categorized based on the quartile cut-off points of the DDS. The mean ± SD age of the participants in both the case and control groups was 28.98 ± 5.43 and 30.15 ± 6.21 years, while mean ± SD body mass index was 25.74 ± 5.44 and 23.65 ± 3.90 kg/m2, respectively. The comparison between the case and control groups indicated that total DDS was 5.19 ± 1.19 for the cases and 5.51 ± 1.19 for the controls. The comparison of DDS in the highest versus the lowest quartiles showed a decreased risk of PCOS (p < 0.05). We demonstrated an inverse association between DDS and PCOS compared with the control group. Furthermore, a higher DDS was significantly associated with a lower risk of PCOS (odds ratio = 0.40). Novelty: This is the first investigation on the relationship between DDS and PCOS. Results depicted an inverse relationship between DDS and 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".