Factors That Explain Differences in Abstinence Between Black and White Smokers: A Prospective Intervention Study
Bibliographic record
Abstract
BACKGROUND: Black-white differences in smoking abstinence are not well understood. This trial sought to confirm previously reported differences in quitting between blacks and whites and to identify factors underlying this difference. METHODS: During enrollment, 224 black and 225 white low-income smokers were stratified on race and within race on age and sex to ensure balance on these factors known to impact abstinence. The intervention included varenicline for 12 weeks and six guideline-based smoking cessation counseling sessions. The primary endpoint was cotinine-verified 7-day point prevalence smoking abstinence at week 26. A priori socioeconomic, smoking, treatment process (eg, treatment utilization, side effects, withdrawal relief), psychosocial, and biological factors were assessed to investigate race differences in abstinence. Unadjusted odds ratios (OR) were used to compare abstinence between blacks and whites. Adjusted odds ratios from logistic regression models were used to examine predictors of abstinence. All statistical tests were two-sided. RESULTS: Blacks were less likely to achieve abstinence at week 26 (14.3% vs 24.4%, OR = 0.51, 95% confidence interval [CI] = 0.32 to 0.83, P = .007). Utilizing best subsets logistic regression, five factors associated with race jointly predicted abstinence: home ownership (yes/no, OR = 3.03, 95% CI = 1.72 to 5.35, P < .001), study visits completed (range = 0-6, OR = 2.81, 95% CI = 1.88 to 4.20, P < .001), income (household member/$1000, OR = 1.03, 95% CI = 1.01 to 1.06, P = .02), plasma cotinine (per 1 ng/mL, OR = 0.997, 95% CI = 0.994 to 0.999, P = .002), and neighborhood problems (range = 10-30, OR = 0.88, 95% CI = 0.81 to 0.96, P = .003). CONCLUSIONS: The race difference in abstinence was fully explained by lack of home ownership, lower income, greater neighborhood problems, higher baseline cotinine, and higher visit completion, which were disproportionately represented among blacks. Findings illuminate factors that make it harder for blacks in the United States to quit smoking relative to whites and provide important areas for future studies to reduce tobacco-related health disparities.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".