Gender differences in the prevalence and determinants of tobacco use among school-aged adolescents (11 – 17 years) in Sudan and South Sudan
Bibliographic record
Abstract
INTRODUCTION: Tobacco use is one of the leading and preventable causes of global morbidities and premature mortalities. The study explores gender differences in the prevalence and determinants of tobacco use among school-aged adolescents (11-17 years) in Sudan and South Sudan. METHODS: The study utilized the national Global Youth Tobacco Survey (GYTS) data collected in 2005 for Sudan (4,277 unweighted; 131,631 weighted). Univariate and bivariate analyses were conducted to examine the associations between the dependent (tobacco use status) and independent variables. Logistic regression analyses were performed to identify the key factors which influence tobacco consumption among adolescents in the 2 Sudans for ever cigarette users, current cigarette users, and users of noncigarette tobacco products. RESULTS: There were significant gender differences in the prevalence of ever cigarette users (21.8%; male=13.1%, female=6.5%, p<0.05) and current cigarette users (6.9%; male=4.9%, female = 1.3%, p<0.05) but not among users of noncigarette tobacco products (14.7%; male=6.8%, female=6.1%). Adolescent tobacco use was significantly associated with availability of monthly income or allowance, exposure to tobacco industry promotions, and tobacco-use behavior of familial relations. Knowledge about the harmful effects of secondhand smoke was related with decreased likelihood of tobacco use. CONCLUSION: School programs that focus on health messages alone may not work for the adolescent population. Legislations that ban all types of tobacco advertisements, promotions, and sponsorships among adolescents are needed in the 2 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 | 0.001 |
| 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 | 0.000 |
| 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".