Bibliographic record
Abstract
BACKGROUND: To date, there is no country-representative study on tobacco and alcohol use in Zambia and Zimbabwe despite the fact that these two countries rank among the top producers of tobacco worldwide. To fill this research gap, we conducted this study to measure the prevalence of tobacco and alcohol consumption among adolescent and adult men in Zambia and Zimbabwe. Special attention was given to the age differential in the prevalence of smoking and drinking. METHODS: Country-representative data on alcohol and tobacco use along with relevant sociodemographic parameters were collected from Demographic and Health Surveys. Sample population were 23,169 men (14,773 from Zambia and 8,396 from Zimbabwe) aged 15-54 years. Data were analysed using multivariate regression techniques. RESULTS: Prevalence of tobacco use was 19.9% (19.0-20.9) in Zambia and 18.4% (17.4-19.5) in Zimbabwe, and that of alcohol was 37.6% (36.4-38.9) in Zambia and 50.5 (48.9-52.1) in Zimbabwe. In both of the countries, the majority of the tobacco and alcohol users were aged between 24-39 years. Results of multivariate regression analysis showed a significant positive association between tobacco and alcohol use with age, place of residence, religious affiliation, marital status, education and wealth quintile. CONCLUSION: Nearly one-fifth of all men in the age group of 15-54 years smoke tobacco in Zambia and Zimbabwe, with the prevalence being most pronounced among those aged between 25-39 years. The predominantly young age structure of alcohol and tobacco users warrant demographically tailored anti-tobacco and alcohol controlling programmes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".