Smokeless tobacco use: its prevalence and relationships with dental symptoms, nutritional status and blood pressure among rural women in Burkina Faso
Bibliographic record
Abstract
Abstract Background: Sub-Saharan women use smokeless tobacco (SLT) more than smoked tobacco. Among Western Africa countries, the estimated weighted prevalence of SLT use in rural women was the highest in Burkina Faso (after Sierra Leone). This study aimed to assess the prevalence of SLT use and its associated factors among rural women in Burkina Faso by using nationally representative data. Methods : We used data from the 2013 STEPwise approach to Surveillance (STEPS) study, which provided sociodemographic, clinical (anthropometric, systolic blood pressure [SBP], diastolic blood pressure [DBP], dental symptoms), biological (total and high-density lipoprotein cholesterol and fasting blood sugar), and tobacco and alcohol consumption data. Data for 1730 rural women were used, and we performed Student’s, chi-squared and logistic regression. Results : The prevalence of current SLT use was 13.8% (95% CI: 12.2-15.5). Significant risks for SLT use were the presence of dental symptoms (adjusted odds ratio [aOR] = 2.59; p<0.001), undernourishment (aOR = 1.78; p<0.01), a decrease in waist circumference (aOR = 0.98; p<0.05), a decrease in DBP (aOR = 0.97; p<0.01), increase in SBP (aOR = 1.01; p<0.05), and an increase in differential blood pressure (aOR = 1.01; p<0.05). The co-use of alcohol was also a significant risk factor (aOR = 2.80; p<0.001). Conclusion : The prevalence of current SLT use was high among rural women in Burkina Faso, and significant concerns for users included alcohol co-use, the occurrence of dental symptoms, undernourishment, and an increase in differential blood pressure. National Public Health interventions are needed to reduce SLT use and its health-related concerns.
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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 | 0.001 | 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) | 0.001 | 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".