Search

Introduction: Cardiovascular disease (CVD) is the leading cause of mortality and disability in the United States. Spatiotemporal modeling of disease incidence may guide prevention efforts toward regions most at risk in the future. Methods: We examined spatiotemporal trends in composite CVD events, defined as myocardial infarction, ischemic stroke, atrial fibrillation, heart failure, coronary artery disease, or cardiovascular death, using electronic health records from 9,718,107 U.S. Veterans who used VA healthcare facilities from 2003-2018. Age-standardized annual incidence by state was modeled using the Bernardinelli model, a Bayesian Poisson regression with linear temporal trends for the US and individual states. Results: There were 626,271 CVD events over 16 years of follow up and annual incidence fell gradually from 11.5% in 2003 to 6.6% in 2018. Incidence among all US veterans decreased an estimated 3.1% [95% CI: -3.3%, -2.9%] per year (RR year = 0.969). State-level incidences also decreased monotonically over the follow-up period (Figure panel A ), ranging from an absolute decrease 5.0% (RI) to 1.7% (OR). Estimated incidence for the five states most above (RI, FL, NC, MT, LA) and most below (OR, NV, CT, OK, MI) the national trend are plotted against the US average in Figure panel B . These outlying states differed significantly from the overall trend (posterior probabilities ≥ 99.7%), and the magnitude of trend was loosely correlated with initial incidence rate (in 2003). Notably, four states crossed the national average over the study period: CT and OK started below average in 2003 but ended above in 2018, whereas RI and NC started with high incidence and ended with below average incidence in 2018. Conclusions: Among US veterans, there was significant geographic variation in the rate of decline of incident CVD from 2003-2018. Future research will investigate the mechanisms underpinning the observed trends, particularly prevalence and control of risk factors.

The prediction of myocardial infarction (MI), acute ischemic stroke (AIS), cardiovascular (CVD) death, and 3-point MACE (MI, AIS, or CVD death) in Million Veteran Program (MVP) participants over 8 years of follow up was evaluated using environmental/traditional risk factors (“E”), polygenic risk scores (“G”), and a combination of both approaches (“GxE”). Individuals free of atherosclerotic cardiovascular disease (ASCVD) at baseline were included. Risk factor levels for the participants close to the time of MVP enrollment for age, sex, systolic blood pressure, cholesterol, HDL cholesterol, smoking status, and diabetes status were analyzed. Outcomes were determined from VA electronic record data, Medicare/Medicaid data, and the National Death Index. Analyses were undertaken separately for non-Hispanic European (EUR), African American (AFR), and Hispanic (HIS) participants. There were 157,941 veterans at risk with 8,157 MI events, 2,024 AIS events, 1,778 CVD deaths, and 9,350 3-pt MACE events over 8 years of follow-up. The overall results showed good performance with the environmental model for all three racial-ethnic groups, with C-statistics ranging from 0.69 to 0.77. The G models showed very modest prediction capabilities and similarly modest improvement in the combined GxE models. In conclusion, traditional risk factor modeling has been shown to be highly effective and, in the MVP experience, the additional impact of genetic or genetic interaction information was small.