Residential proximity to major roadways and all-cause mortality among individuals with varying severity of cardiovascular disease
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Background: Proximity to major roadways is associated with morbidity and mortality. While existing studies show associations for those with cardiovascular disease (CVD), studies comparing cohorts with varying severity of CVD are missing from the literature. We use three cohorts with varying CVD severity to understand association between all-cause mortality and traffic-related air pollution.
Methods: We constructed three cohorts based on history of CVD using electronic health records from the University of North Carolina Chapel Hill Healthcare System (UNCHCS) between 2004-2016. One cohort had a previous heart failure (HF) diagnosis, one cohort had a previous myocardial infarction (MI), and one cohort was a random sample of UNCHCS patients (RS). We calculated the distance from the primary residence to the nearest major roadway based on recorded residence at time of HF diagnosis (HF), first recorded MI (MI), or first hospital visit (RS). We used Cox proportional-hazard models to associate residence within 250m of a major roadway with all-cause mortality while adjusting for age, sex, race, smoking status, urbanicity, and census block group indicators of socioeconomic status. Results are presented as hazard ratios (HR) and associated 95% confidence intervals (CI).
Results: Each cohort had a similar distribution of the exposure (residence within 250m of a major roadway) with HF = 24%, MI = 22%, and RS= 22%. Associations between proximity to major roadways and all-cause mortality were stronger among HF patients (HR = 1.13; 95% CI = 1.04, 1.23) than those with a previous MI (HR = 1.07; 95% CI = 0.96, 1.20), and were null in the RS cohort (HR = 1.03; 95% CI = 0.89, 1.20).
Conclusions: Proximity to major roadways is associated with increased all-cause mortality risk among individuals with pre-existing CVD. This study provides a better quantification of traffic exposure and mortality risk among patients with different CVD diagnoses.