Estimating the Effects of Fine Particulate Matter on 432 Cardiovascular Diseases Using Multi-Outcome Regression With Tree-Structured Shrinkage

The positive relationship between airborne fine particulate matter (PM2.5) and cardiovascular disease (CVD) is established. Little is known about effect size heterogeneity across distinct CVD outcomes. We conducted a multi-outcome case-crossover study of Medicare beneficiaries aged >65 years residing in the mainland USA from 2000 through 2012. The exposure was two-day average PM2.5 in each individual’s residential zipcode. The outcomes were hospitalization for 432 distinct CVDs defined by the International Classification of Diseases, Revision 9. Our dataset included almost 24 million CVD hospitalizations. We analyzed the data using multi-outcome regression with tree-structured shrinkage (MOReTreeS), a novel method that enables: (1) borrowing of strength across outcomes; (2) data-driven discovery of outcome groups that are similarly affected by the exposure; (3) estimation of a single effect for each group. MOReTreeS grouped 420 outcomes together; for this group, the odds ratio [OR] for hospitalization associated with a 10 μg m− 3 increase in PM2.5 was 1.011 (95% credible interval [CI] = 1.011–1.012). The model identified congestive heart failure as having the strongest positive association with PM2.5 (OR = 1.019; 95%CI = 1.017–1.022). Some outcomes exhibited negative associations with PM2.5, including aortic dissection, subarachnoid and intracerebral hemorrhage, abdominal aneurysm, and essential hypertension; further research is needed to understand these counterintuitive findings. Supplementary materials for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement.