Prevalence of Alcohol and Tobacco Use among Men and Women in Namibia
Bibliographic record
Abstract
Namibia is known to have a high prevalence of tobacco smoking and alcohol consumption. Individuals who smoke are more likely to drink, and vice versa. It was reported that the individual rewarding effect of drinking and smoking were reported to be higher than when they are used at the same time. In this study our objective was to examine the individual and combined prevalence of drinking and smoking and investigate their sociodemographic correlates among adolescent and adult men and women in Namibia. This study was based on data from Namibia Demographic and Health Survey (NDHS 2013). Sample population were 14,185 men and women aged between 15 and 64 years. Self-reported tobacco smoking and alcohol consumption patterns were the outcome variables. Data were analysed using complex sampling techniques to account for survey design. Bivariate and multivariate techniques were used to measure the association between drinking and smoking with the sociodemographic factors. The prevalence of alcohol and tobacco use was, respectively, 53.1% (51.5⁻54.6) and 8.8% (8.1⁻9.5), and that of both drinking and smoking was 6.9% (6.3⁻7.6). In the regression analysis, several sociodemographic factors were found to be significantly associated with alcohol and tobacco use including age, area of residence, religion and educational status. Overall, women had higher rates of drinking alcohol; however, men had higher rates of engaging in high risk drinking. Men and women who reported drinking alcohol had, respectively, 2.57 and 4.60 times higher odds of smoking. Findings suggest that the prevalence of drinking was higher than that of smoking, with men having higher prevalence of high risk drinking. Men and women who drink alcohol were more likely to be smokers. The prevalence of both alcohol and tobacco use showed important sociodemographic patterns which need to be taken into consideration in designing prevention and intervention programs. Strategic tobacco control and smoking cessation approaches should pay particular attention to alcohol users.
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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".