Prevalence of smokeless tobacco use in India and its association with various occupations: A LASI study
Bibliographic record
Abstract
Background: More than two-thirds of deaths in developing countries are due to non-communicable diseases, and tobacco is a leading risk factor. There are numerous different socio-demographic factors that impact on the use of smokeless tobacco, of which occupation is one. The objectives of this study are to find out the overall prevalence of smokeless tobacco use (ever and current use), the pattern of association with various occupations and related variables (current and past workers), and the role of childhood adversity on initiation and use. Methods: This study used data from the Longitudinal Aging Study in India (LASI) wave 1, a nationally representative cross-sectional study collected in 2017-18. Current and previous users of smokeless tobacco are taken into consideration as the target population. For the data analysis, survey-weighted tools have been applied for descriptive statistics and multivariable logistic regression model. The weighted data analysis has been done using R studio with R version 4. Results and discussion: From the sample size of 65,561, 38% have used either smoking or smokeless tobacco. Among them, 40% use tobacco in smoke form, 51% use smokeless tobacco, and 9% take both. At the population level, 22.8 and 20.4% are previous and current users of smokeless tobacco, respectively. Type of occupation, type of employer, place of work, kind of business, and workload were found to be significantly associated with smokeless tobacco use. A deaddiction and tobacco quitting policy targeting rural male informal workers should be the focus of the Government.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".