Socioeconomic inequalities in tobacco, alcohol and illicit drug use: evidence from Iranian Kurds
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: The associations between socioeconomic status (SES) and tobacco use, alcohol consumption and drug use are poorly understood in the Islamic Republic of Iran. AIMS: To measure education- and wealth-related inequalities in cigarette smoking, hookah smoking, illicit drug use and alcohol consumption in Kermanshah Province, Islamic Republic of Iran. METHODS: We used baseline data from the Ravansar Noncommunicable Disease (RaNCD) study. The study collected information on socioeconomic and demographic characteristics, cigarette and hookah smoking, alcohol consumption and illicit drug use of 10 015 adults aged ≥ 35 years between 2014 and 2016. The relative concentration index and absolute concentration index were used to measure education- and wealth-related inequalities in cigarette smoking, hookah smoking, illicit drug use and alcohol consumption. RESULTS: Cigarette smoking was concentrated among less-educated and less-wealthy men and women. Similarly, illicit drug use was concentrated among lower-SES men. In contrast, hookah smoking and alcohol consumption were more prevalent among higher-SES men. CONCLUSIONS: There were education- and wealth-related inequalities in tobacco, alcohol and illicit drug use in the west of the Republic of Iran. Future studies should aim to identify the main socioeconomic determinants of these inequalities in Kermanshah Province and generally in the Islamic Republic of Iran.
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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 | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it