Smokeless tobacco use and circulatory disease risk: a systematic review and meta-analysis
Bibliographic record
Abstract
Objective: Smokeless tobacco use is a public health issue throughout the world, but reviews and analyses of circulatory disease risks associated with smokeless tobacco use may be outdated or incomplete. This study provides a thorough and comprehensive review and meta-analysis of circulatory disease risks in high-income countries, including recently published study estimates. Methods: We conducted a systematic review of studies of circulatory disease risks associated with smokeless tobacco use in Europe and North America that were identified from electronic databases and reference lists. Study estimates were extracted by region, smokeless tobacco use status, cigarette smoking status, and circulatory condition and combined in meta-analysis using a random-effects model. We used the Newcastle-Ottawa scale to assess study quality and risk of bias. Results: We identified 17 relevant cohort studies, two pooled analyses, five case-control studies and one cross-sectional analysis. We found increased risk of heart disease (relative risk (RR) 1.17, 95% CI 1.09 to 1.27) and stroke (RR 1.28, 95% CI 1.01 to 1.62) among US smokeless tobacco users compared with non-users. Increased circulatory disease risk was not observed among Swedish smokeless tobacco users. Conclusion: US smokeless tobacco users were found to have increased risk of heart disease and stroke.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.025 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".