The Most Important Predictors of Metabolic Syndrome Persistence after 10-year Follow-Up: YHHP Study
Bibliographic record
Abstract
Background: Metabolic syndrome (MetS) is one of the world's largest health epidemics, and its management is a major challenge worldwide. The aim of this 10-year follow-up study was to assess the most important predictors of MetS persistence among an Iranian adult population. Methods: In this cohort study, 887 out of 2000 participants with MetS aged 20–74 years in the central part of Iran were followed-up for about 10 years from 2005–2006 to 2015–2016. MetS was defined based on the criteria of NCEP-ATP III adopted for the Iranian population. Cox proportional hazards regression was conducted to evaluate the predictors of MetS persistence in crude- and multivariate-adjusted models. Results: Our analyses showed that 648 out of 887 participants (73%) completed the follow-up and 565 (87.2%) of them had persistence of MetS after 10-year follow-up. There was a significant association between age, weight, body mass index, triglyceride, and waist circumference in participants who had MetS compared to those without MetS after 10-year follow-up ( P < 0.05). There was a direct association between increases in the mean changes of systolic/diastolic blood pressure, waist circumference, and low HDL-C and risk of MetS persistence after adjusting the model for sex and age in the total population ( P trend < 0.05). The trends were the same for women except in diastolic blood pressure. After adjustment for potential confounders, the risk of MetS persistence in men was significantly higher than women (HR = 1.98, 95% CI: 1.38–2.85, Ptrend = 0.001). Conclusions: Most of the risk factors of MetS were positively associated with persistence of MetS. Therefore, modification of lifestyle is recommended to reduce MetS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".