Behavioral risk factors and socioeconomic inequalities in ischemic heart disease mortality in the United States: A causal mediation analysis using record linkage data
Bibliographic record
Abstract
BACKGROUND: Ischemic heart disease (IHD) is a major cause of death in the United States (US), with marked mortality inequalities. Previous studies have reported inconsistent findings regarding the contributions of behavioral risk factors (BRFs) to socioeconomic inequalities in IHD mortality. To our knowledge, no nationwide study has been conducted on this topic in the US. METHODS AND FINDINGS: In this cohort study, we obtained data from the 1997 to 2018 National Health Interview Survey with mortality follow-up until December 31, 2019 from the National Death Index. A total of 524,035 people aged 25 years and older were followed up for 10.3 years on average (SD: 6.1 years), during which 13,256 IHD deaths occurred. Counterfactual-based causal mediation analyses with Cox proportional hazards models were performed to quantify the contributions of 4 BRFs (smoking, alcohol use, physical inactivity, and BMI) to socioeconomic inequalities in IHD mortality. Education was used as the primary indicator for socioeconomic status (SES). Analyses were performed stratified by sex and adjusted for marital status, race and ethnicity, and survey year. In both males and females, clear socioeconomic gradients in IHD mortality were observed, with low- and middle-education people bearing statistically significantly higher risks compared to high-education people. We found statistically significant natural direct effects of SES (HR = 1.16, 95% CI: 1.06, 1.27 in males; HR = 1.28, 95% CI: 1.10, 1.49 in females) on IHD mortality and natural indirect effects through the causal pathways of smoking (HR = 1.18, 95% CI: 1.15, 1.20 in males; HR = 1.11, 95% CI: 1.08, 1.13 in females), physical inactivity (HR = 1.16, 95% CI: 1.14, 1.19 in males; HR = 1.18, 95% CI: 1.15, 1.20 in females), alcohol use (HR = 1.07, 95% CI: 1.06, 1.09 in males; HR = 1.09, 95% CI: 1.08, 1.11 in females), and BMI (HR = 1.03, 95% CI: 1.02, 1.04 in males; HR = 1.03, 95% CI: 1.02, 1.04 in females). Smoking, physical inactivity, alcohol use, and BMI mediated 29% (95% CI, 24%, 35%), 27% (95% CI, 22%, 33%), 12% (95% CI, 10%, 16%), and 5% (95% CI, 4%, 7%) of the inequalities in IHD mortality between low- and high-education males, respectively; the corresponding proportions mediated were 16% (95% CI, 11%, 23%), 26% (95% CI, 20%, 34%), 14% (95% CI, 11%, 19%), and 5% (95% CI, 3%, 7%) in females. Proportions mediated were slightly lower with family income used as the secondary indicator for SES. The main limitation of the methodology is that we could not rule out residual exposure-mediator, exposure-outcome, and mediator-outcome confounding. CONCLUSIONS: In this study, BRFs explained more than half of the educational differences in IHD mortality, with some variations by sex. Public health interventions to reduce intermediate risk factors are crucial to reduce the socioeconomic disparities and burden of IHD mortality in the general US population.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".