Consumo de álcool e risco para doença coronariana na região metropolitana de São Paulo: uma análise do Projeto GENACIS
Bibliographic record
Abstract
OBJECTIVES: To examine the association between patterns of drinking and coronary heart disease (CHD) risk in a populational sample. METHODS: A population-based cross-sectional study carried out from January 2006 to June 2007, in Metropolitan São Paulo, Brazil, in conjunction with the international collaborative GENACIS project (Gender, Alcohol, and Culture: an International Study), with PAHO support. The subjects (1,501; 609 men, 892 women) of this study were residents of randomly chosen households aged 30 years and above who consented to provide information. The dependent variable was cardiac risk as assessed by the WHO Rose Angina Questionnaire. Logistic Regression analysis was used and the data were adjusted for Body Mass Index (BMI) and smoking. RESULTS: The response rate was 75%. Being female, older, African-American, a current smoker, and having a greater BMI were associated with higher risk of coronary heart disease. Lifetime abstainers (OR = 2.22) and former drinkers (OR = 2.42) had greater CHD risk than those who consumed up to 19g pure alcohol per day, with no binge. Among those who had binged weekly or more there was a tendency toward higher risk (OR = 3.95, p = .09). CONCLUSIONS: Our findings suggest a lower risk for CHD among moderate drinkers. It is important, in studies which were investigating cardiac risk, assess heavy alcohol use, since it can change that risk. Also, effective public policies are needed to reduce harmful drinking and related morbidity in Brazil.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".