Factors Associated with Smoking and Alcohol Consumption among Street Vendors in the Metropolitan Area of Bucaramanga, Colombia
Bibliographic record
Abstract
AIM: The objective of the study was to characterize, learn and establish related factors about the behavior of alcohol and tobacco consumption in a sample of street vendors in the Metropolitan Area of Bucaramanga, Colombia.METHODS: A descriptive cross-sectional study was conducted on 425 street vendors. With regard to sampling, a non-probability sampling was conducted on the streets of every city in the Metropolitan Area. Each worker was given a questionnaire that included socio-demographic and occupational variables, in addition it was applied the Fagerstrom test was applied along with the Alcohol Use Disorders Inventory Test (AUDIT).RESULTS: Twenty one percent of the workers reported being consumers of cigarettes, 57% had consumed alcohol and 17% had both habits; consuming liquor and cigarettes. As for consumption of harmful liquor, men had higher risk (OR 2.97 p =.001), the age of highest consumption was between 18-39 years (OR 1.3 p =.01) and smokers had a significant risk (OR 4.33 p=.001). According to the logistic regression model, among the main factors associated with harmful alcohol use they were: male gender, not having health insurance, smoking and living in the main city of the Metropolitan Area.CONCLUSION: Street vendors have certain socio-demographic and labor variables that lead to raising their vulnerability. As for their spending habits, they have a high consumption of cigarettes and alcohol in relation to other group of workers, however the level of dependence is not superlative. In those who had detrimental alcohol consumption, the most important related variables to intervene were insufficient health coverage and smoking.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".