Patterns and predictors of cigarette smoking among HIV-infected patients in northern Nigeria
Bibliographic record
Abstract
The smoking behaviour of persons living with HIV/AIDS in sub-Saharan Africa is poorly documented. We employed a cross-sectional study design to assess the prevalence and predictors of tobacco smoking among HIV-infected patients in northern Nigeria (n = 296). Approximately one quarter of respondents were either current (7.8%) or ex-smokers (17.9%). Smoking rates among HIV-infected women were extremely low. HIV-infected men were at least three times as likely to smoke as their female counterparts living with HIV: adjusted odds ratio (AOR) 3.16, 95% confidence interval (95% CI) 2.17-7.32. Patients with tertiary education were at least twice as likely to smoke compared with their counterparts without formal education (AOR 2.63, 95% CI 1.08-6.67). The preponderance of cigarette smoking among educated HIV-infected men in northern Nigeria offers a unique opportunity for targeted smoking cessation programmes.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".