The Social and Economic Correlates of Tobacco Consumption in Developing Countries Compared to Developed Countries: Evidence from Burkina Faso and Canada
Bibliographic record
Abstract
This paper examines the socio-demographic and economic factors affecting tobacco consumption in a developing country like Burkina Faso compared to a developed country like Canada. Using nationally representative data from the 2016 round of Burkina Faso’s Demographic and Health Survey (DHS) and the Canadian Community Health Survey (CCHS) 2015-2016, we estimated multivariate fixed effects models to identify the social and economic factors associated with tobacco consumption in these countries. We find evidence that age has an inverted U-shaped positive effect on cigarettes consumption in both countries with a peak at 24-35 years old in Burkina Faso and a peak at 40-54 years old in Canada. Second, being single increases the consumption of cigarettes while education and employment reduce cigarettes consumption in both countries. The gender gap in tobacco consumption between men and women is larger in Burkina Faso (5.021 cigarettes) compared to Canada (1.45 cigarettes). Third, while income have a negative impact on cigarettes consumption in Canada, it displays a U-shape effect in Burkina Faso. Hence, the social and economic context should be considered by the international organization while addressing the issue of smoking in developed and developing countries.
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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 | 0.003 | 0.006 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".