Objective While black-white and regional disparities in U.S. stroke mortality rates are well documented, the contribution of disparities in stroke incidence is unknown. We provide national estimates of stroke incidence by race and region, contrasting these to publicly available stroke mortality data. Methods This analysis included 27,744 men and women without prevalent stroke (40.4% black), aged ≥45 years from the REasons for Geographic And Racial Differences in Stroke (REGARDS) national cohort study, enrolled 2003–2007. Incident stroke was defined as first occurrence of stroke over 4.4 years of follow-up. Age-sex–adjusted stroke mortality rates were calculated using data from the Centers for Disease Control and Prevention (CDC) Wide-Ranging Online Data for Epidemiological Research (WONDER) System. Results There were 460 incident strokes over 113,469 person-years of follow-up. Relative to the rest of the United States, incidence rate ratios (IRRs) of stroke in the southeastern stroke belt and stroke buckle were 1.06 (95% confidence interval [CI], 0.87–1.29) and 1.19 (95% CI, 0.96–1.47), respectively. The age-sex–adjusted black/white IRRblack was 1.51 (95% CI, 1.26–1.81), but for ages 45–54 years the IRRblack was 4.02 (95% CI, 1.23–13.11) while for ages 85+ it was 0.86 (95% CI, 0.33–2.20). Generally, the IRRsblack were less than the mortality rate ratios (MRRs) across age groups; however, only in ages 55–64 years and 65–74 years did the 95% CIs of IRRsblack not include the MRRblack. The MRRs for regions were within 95% CIs for IRRs. Interpretation National patterns of black-white and regional differences in stroke incidence are similar to those for stroke mortality; however, the magnitude of differences in incidence appear smaller.

Background and Purpose Black/white disparities in stroke incidence are well-documented, but few studies have assessed the contributions to the disparity. Here we assess the contribution of “traditional” risk factors. Methods 25,714 black and white men and women, aged 45+ and stroke-free at baseline were followed for an average of 4.4 years to detect stroke. Mediation analysis employing proportional hazards analysis assessed the contribution of “traditional” risk factors to racial disparities. Results At age 45, incident stroke risk was 2.90 (95% CI: 1.72 – 4.89) times more likely in blacks than whites, and 1.66 (95% CI: 1.34 – 2.07) times at age 65. Adjustment for risk factors attenuated these excesses by 40% and 45%, respectively, resulting in relative risks of 2.14 (95% CI: 1.25 – 3.67) and 1.35 (95% CI: 1.08 – 1.71). Approximately one-half of this mediation is attributable to systolic blood pressure. Further adjustment for socioeconomic factors resulted in total mediation of 47% and 53% to relative risks of 2.01 (95% CI: 1.16 – 3.47) and 1.30 (1.03 – 1.65) respectively. Conclusions Between ages 45 to 65 years, approximately half of the racial disparity in stroke risk is attributable to traditional risk factors (primarily systolic blood pressure) and socioeconomic factors, suggesting a critical need to understand the disparity in the development of these traditional risk factors. Because half of the excess stroke risk in blacks is not attributable to traditional risk factors and socioeconomic factors, differential racial susceptibility to risk factors, residual confounding or non-traditional risk factors may also play a role.

Background The accuracy of stroke diagnosis in administrative claims for a contemporary population of Medicare enrollees has not been studied. We assessed the validity of diagnostic coding algorithms for identifying stroke in the Medicare population by linking data from the REasons for Geographic And Racial Differences in Stroke (REGARDS) Study to Medicare claims. Methods and Results The REGARDS Study enrolled 30,239 participants 45 years and older in the United States between 2003 and 2007. Stroke experts adjudicated suspected strokes using retrieved medical records. We linked data for participants enrolled in fee-for-service Medicare to claims files from 2003 through 2009. Using adjudicated strokes as the gold standard, we calculated accuracy measures for algorithms to identify incident and recurrent stroke. We linked data for 15,089 participants, among whom 422 participants had adjudicated strokes during follow-up. An algorithm using primary discharge diagnosis codes for acute ischemic or hemorrhagic stroke [ICD-9-CM codes: 430, 431, 433.x1, 434.x1, 436] had positive predictive value of 92.6% (95% Confidence Interval (CI), 88.8%-96.4%), specificity of 99.8% (99.6%-99.9%), and sensitivity of 59.5% (53.8%-65.1%). An algorithm using only acute ischemic stroke codes [433.x1, 434.x1, 436] had positive predictive value of 91.1% (95% CI, 86.6%-95.5%), specificity of 99.8% (99.7%-99.9%), and sensitivity of 58.6% (52.4%-64.7%). Conclusions Claims-based algorithms to identify stroke in a contemporary Medicare cohort had high positive predictive value and specificity, supporting their use as outcomes for etiologic and comparative effectiveness studies in similar populations. These inpatient algorithms are unsuitable for estimating stroke incidence due to low sensitivity.