Women’s Occupational Tobacco Dust Exposure in Indonesia (T-CHARM): Protocol for a Prospective Cohort Study
Bibliographic record
Abstract
BACKGROUND: The consumption of tobacco is regarded as a contributing factor to several diseases. However, the impact of tobacco dust exposure (TDE) on tobacco workers has not been extensively investigated. OBJECTIVE: This protocol introduces the design and implementation of the Tobacco Dust Cohort for Health Assessment and Risk Monitoring (T-CHARM) study, a prospective cohort study aimed at evaluating the health impacts of TDE. METHODS: This prospective cohort study will recruit women working in tobacco processing who are nonsmokers and women who do not work for the tobacco industry and are nonsmokers living in a nearby area (unexposed group), with a total of 400 expected participants. The impact of TDE on health, including metabolic syndrome parameters; complete blood count; and cardiovascular, liver, renal, and lung function, will be evaluated in relation to urine cotinine levels. Air quality and chemical substances in the air and leaves will also be analyzed. The data will be subsequently analyzed using appropriate statistical tools. RESULTS: A total of 120 respondents have participated as of August 2025. Another 80 respondents will be recruited, laboratory analysis is ongoing, and baseline results are expected by the end of 2025. CONCLUSIONS: The strength of the T-CHARM study's approach is its detailed occupational and environmental factors and longitudinal health data from the corporate clinic or the district health center, as well as links to cancer and mortality registries and self-reported health. The current phase of the study focuses on baseline data collection for long-term follow-up. The cohort will be monitored for up to 20 years, depending on sustained funding. T-CHARM offers a robust framework for understanding the chronic health effects of occupational TDE. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/84231.
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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 | 0.026 | 0.017 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.031 | 0.009 |
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".