Risk factors for chronic noncommunicable diseases in users of two Basic Health Units in the city of São Paulo, Brazil
Bibliographic record
Abstract
Introduction: The main risk factor for Chronic Noncommunicable Diseases (CNCDs) is lifestyle, which is open to prevention and health promotion interventions. Objective: to describe the risk factors associated with CNCD among individuals seen at two Basic Health Units (BHUs) in the city of São Paulo. Method: This was a cross-sectional study carried out in two BHUs in the northern and southeastern regions of São Paulo, involving 582 adult individuals. Data collection was done using the Vigitel instrument. In the inferential analyses, a logistic regression model was used. Results: Most participants were female, aged between 31 and 60 years; a quarter practiced physical activities, and most were overweight/obese. Less than a third were smokers or drinkers. The CNCDs observed were arterial hypertension, dyslipidemia and chronic obstructive pulmonary diseases (COPD). By the logistic regression analysis, the risk of presenting CNCDs was higher in patients over 60 years old (OR 11.3; 95% CI 5.6-15.5), male (OR 1.5; 95% CI 1.0-2.2), with an elementary education (OR 1.4; 95% CI 1.0-1.9), obese (OR 1.7; 95% CI 1.1-2.6) and smokers or with history of smoking. As for smoking, both consumption time (OR 2.1; 95% CI 1.4-3.0 if more than 10 years) and number of cigarettes consumed (OR 1.7; 95% CI 1.0-2.9 if more than 10 cigarettes/day) were significant. Conclusion: The most prevalent CNCDs were arterial hypertension, dyslipidemia and COPD. The main risk factors were male gender, age over 60 years, obesity and tobacco consumption.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".