Worldwide relative smoking prevalence among people living with and without HIV
Bibliographic record
Abstract
OBJECTIVE AND DESIGN: People living with HIV (PLH) suffer disproportionately from the chronic diseases exacerbated by smoking tobacco. We performed a systematic review and meta-analysis to establish the relative prevalence of smoking among PLH. METHODS: We included observational studies reporting current smoking rates among PLH and comparators without HIV. We searched Medline, EMBASE, LILACS and SciELO from inception to 31 August 2019. We excluded studies that recruited participants with smoking related illness. We used a random effects model to estimate the odds ratio for current smoking in PLH and people without HIV. We used the Newcastle--Ottawa scale to assess methodological bias. We performed subgroup analysis based on sex and WHO region. We quantified heterogeneity with meta-regression and predictive distributions. PROSPERO registration:CRD42016052608. RESULTS: We identified 6116 studies and included 37. Of 111 258 PLH compared with 10 961 217 HIV-negative participants pooled odds of smoking were 1.64 [(95% confidence interval, 95% CI: 1.45-1.85) (95% prediction interval: 0.66-4.10, I2 = 98.1%)]. Odds for men and women living with HIV were 1.68 [(95% CI: 1.44-1.95) (95% prediction interval: 0.71-3.98, I2 = 91.1%)] and 2.16 [(95% CI: 1.77-2.63) (95% prediction interval: 0.92-5.07, I2 = 81.7%)] respectively. CONCLUSION: PLH are more likely to be smokers than people without HIV. This finding was true in subgroup analyses of men, women and in four of five WHO regions from which data were available. Meta-regression did not explain heterogeneity, which we attribute to the diversity of PLH populations worldwide. Smoking is a barrier to PLH achieving parity in life expectancy and an important covariate in studies of HIV-associated multimorbidity.
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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) | 0.001 | 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 | 0.001 |
| 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".