Exploring Prevalence and Sociodemographic Factors Associated With Smoking Among Malaysian Adults: A Cross‐ Sectional Study
Bibliographic record
Abstract
Background and Aims: The Malaysian government has implemented various antismoking measures to reduce the incidence of unhealthy lifestyles within the population. This study analyzes the baseline data of the Prospective Urban Rural Epidemiology (PURE) study to establish the prevalence of sociodemographic factors that are associated with smoking habits among Malaysian adults. Methods: This study was carried out in urban and rural communities with adults aged between 35 and 70 years using purposive sampling. Standardized questionnaires were used to assess the smoking status and sociodemographic data of the participants. Bivariate analysis and multiple logistic regression were done to determine the association between smoking status and demographic characteristics among Malaysian adults. Results: The prevalence of smoking among adults is 23.2%. The sociodemographic factors significantly associated with active smoking status were being a younger adult (adjusted odds ratio [AOR] = 1.26, 95% CI: 1.06-1.50), being male (AOR = 24.16, 95% CI: 20.58-28.36), being Malay (AOR = 1.72, 95% CI: 1.49-1.98), being a blue-collar worker (AOR = 1.75, 95% CI: 1.48-2.06), having no formal education (AOR = 1.99, 95% CI: 1.56-2.53), being unmarried (AOR = 1.22, 95% CI: 1.02-1.48) and being of low socioeconomic status (AOR = 1.45, 95% CI: 1.14-1.84). Conclusion: Public health policies and actions on smoking reduction should emphasize those identified as high-risk sub-populations, particularly younger adults, males and those who are not yet married, have no formal education and are of low socioeconomic status.
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 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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".