The Association of Metabolic Syndrome with Alcohol Consumption among Urban Chinese
Bibliographic record
Abstract
BACKGROUND: Along with economic improvement, China is experiencing increasing rates of non-communicable disease and a rise in alcohol consumption. While a modest intake of red wine has been shown to be health enhancing, the pathophysiology associated with excessive alcohol consumption is being increasingly recognized. The purpose of this study is to demonstrate the health consequences of alcohol consumption among middle-aged urban Chinese people. METHODS: This cross-sectional study included 793 subjects aged 44, 48 or 52 years, from urban community health centres and a local hospital, who participated in a survey, anthropometrics and blood chemistry. Multiple logistic regression analysis was used to obtain adjusted odds ratios (OR) between alcohol intake and medical history of diabetes and hypertension, metabolic syndrome and its five component variables. RESULTS: Metabolic syndrome (MetS) was detected in 53.5% and 42.8% of men and women, respectively, (p < .05), and regular alcohol consumption was found among 72.5% and 12.4% of men and women (p < .00). A weak association was found between consuming alcohol ≥ 2 times a week (or having quit) and MetS (OR = 1.7, 1.0, 2.9) and elevated blood pressure (OR = 1.8, 1.0, 3.1). CONCLUSION: Alcohol consumption is an under-appreciated risk factor found in association with increased rates of metabolic syndrome and associated non-communicable diseases among urban residents in China.
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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 | 0.002 | 0.000 |
| 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) | 0.000 | 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".