Tobacco use and its determinants in the 2015 Kenya WHO STEPS survey
Bibliographic record
Abstract
BACKGROUND: According to the World Health Organization (WHO), in 2015, over 1.1 billion people smoked tobacco, which represents around 15% of the global population. In Africa, around one in five adults smoke tobacco. The 2014 Kenya Global Adult Tobacco Survey reported that 2.5 million adults use tobacco products. The objective of our study was to describe patterns and determinants of tobacco use from the 2015 Kenya STEPS survey, including use of "smokeless" tobacco products and the more novel e-cigarettes. METHODS: The WHO STEPwise approach to surveillance (STEPS) was completed in Kenya between April and June 2015. Logistic regression analyses was used to assess factors affecting prevalence and frequency of tobacco use. Sociodemographic variables associated with tobacco use were considered: age, sex, level of education, wealth quintile, and residence. The relationship with alcohol as an intervening risk factor was also assessed. Our main outcomes of interest were current tobacco use, daily tobacco use and use of smokeless tobacco products. RESULTS: Of 4484 respondents, 605 (13.5%) reported being current tobacco users. Most active tobacco users were male (n = 507/605, 83.8%). Three out of four tobacco users (n = 468/605, 77.4%) reported being less than 50 years old, with the average start age being 21 (20.6, 95% CI 19.3-21.8) and the average quit age 27 (27.2, 95% CI 25.8-28.6). Most tobacco users had only ever attended up to primary school (n = 434/605, 71.7%). Men had nearly seven times higher odds of being tobacco users as compared to women (OR 7.63, 95% CI 5.63-10.33). Alcohol use had a positive effect on tobacco use. Finally, less than ten respondents reported having used e-cigarettes. CONCLUSION: The 2015 Kenya WHO STEPS provided primary data on the status of tobacco use in the country and other leading NCD risk factors, such as alcohol, and associated diseases. Our findings highlight key target populations for tobacco cessation efforts: young people, men, those with lower levels of education, and alcohol consumers. Further data is needed on the use of smokeless tobacco, and its impact on smoked tobacco products, as well as on the novel use of e-cigarettes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".