Examining the Role of Race/Ethnicity and Sex in Modifying the Association Between Early Smoking Initiation and Mortality: A 20-Year NHANES Analysis
Bibliographic record
Abstract
Introduction: The authors aim to examine the modifications of the relationship between early smoking initiation and overall mortality by race/ethnicity and sex using data from U.S. adults in the 1999-2018 National Health and Nutrition Examination Surveys. Methods: The authors analyzed data from 10 aggregated National Health and Nutrition Examination Surveys cycles focusing on noninstitutionalized U.S. civilian population aged 20-79 years. Smoking initiation was categorized by age, and the study's primary outcome was all-cause mortality. The authors employed Kaplan-Meier curves and Cox proportional hazards models to investigate the associations and adjusted for race/ethnicity, sex, and survey cycle. The authors also explored effect modification by race/ethnicity and sex. Results: The analysis included 50,549 participants. The authors found that early smoking initiation was significantly associated with increased all-cause mortality across all age categories, with higher hazard ratios for earlier initiation ages. The relationship exhibited variations by race/ethnicity and sex. Non-Hispanic White population showing the highest risk, followed by non-Hispanic Black subpopulation, but race/ethnicity interaction terms was not significant. Significant interaction by sex was observed. Conclusions: Early smoking initiation is significantly associated with increased risk of mortality, with noticeable differences by race/ethnicity and sex. These findings emphasize the need for prevention measures that are sensitive to demographic variations.
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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 | 0.001 | 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 | 0.000 | 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".