Use of Cigarettes, Cannabis, and Alcohol Among Asian American, Native Hawaiian, and Pacific Islander Adults: Community-Based National Survey Analysis
Bibliographic record
Abstract
Background: Asian American, Native Hawaiian, and Pacific Islander (AANHPI) populations have diverse cultural, immigration, and sociodemographic characteristics. Aggregated data could mask substantial differences in substance use between cultural subgroups in this population. Yet, studies examining substance use among the AANHPI population are limited. Objective: This study aimed to describe cigarette, cannabis, and alcohol use among AANHPI adults by cultural subgroup and sex. Methods: We analyzed data from 3411 AANHPI respondents of a multilingual national survey "COMPASS" during December 2021-May 2022. Primary outcomes were self-report current (every day or some days) use of cigarettes, cannabis, and alcohol. Cultural subgroups included Asian Indian, Ethnic Chinese, Filipino, Japanese, Korean, Native Hawaiian and Pacific Islander, Vietnamese, other cultural groups, and multicultural groups. Other covariates include sex, other sociodemographics, experiences of discrimination (Everyday Discrimination Scale), and mental health (Patient Health Questionnaire 4). Multivariable logistic regressions were used to examine correlates of each substance use among AANHPI adults. Results: The prevalence of current cigarette, cannabis, and alcohol use was 4.2% (142/3359), 5.5% (184/3235) and 37.6% (1265/3361), respectively. Cigarette use ranged from 1.0% (1/100) in Asian Indian females to 14.8% (10/71) in multicultural males. Cannabis use ranged from 1.9% among Asian Indian (1/53) and Vietnamese males (4/211) to 15.7% (11/70) in multicultural females. Alcohol use varied from 6.6% (4/61) in Native Hawaiian and Pacific Islander females to 56.3% (40/71) among multicultural males. Male participants with elevated depression and anxiety symptoms were more likely to report using all 3 substances than males with minimal symptoms. However, depression and anxiety symptoms were only associated with cannabis and alcohol use among female participants. US-born female participants were more likely to report using all 3 substances compared to foreign-born females, while being US-born was only associated with higher odds of alcohol use among males. Perceived discriminatory experience was associated with higher odds of smoking in both sexes and alcohol drinking in males. Conclusions: Cigarette smoking, cannabis, and alcohol use varied widely across AANHPI cultural groups, between and within each sex. These findings underscore the necessity to disaggregate data for substance use behaviors to guide health policy and intervention programs for AANHPI adults.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.001 | 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 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".