In middle age, stroke incidence is higher among black than white Americans. For unknown reasons, this inequality decreases and reverses with age. We conducted simulations to evaluate whether selective survival could account for observed age patterning of black–white stroke inequalities.
We simulated birth cohorts of 20,000 blacks and 20,000 whites with survival distributions based on US life tables for the 1919–1921 birth cohort. We generated stroke incidence rates for ages 45–94 years using Reasons for Geographic and Racial Disparities in Stroke (REGARDS) study rates for whites and setting the effect of black race on stroke to incidence rate difference (IRD) = 20/10,000 person-years at all ages, the inequality observed at younger ages in REGARDS. We compared observed age-specific stroke incidence across scenarios, varying effects of U, representing unobserved factors influencing mortality and stroke risk.
Despite a constant adverse effect of black race on stroke risk, the observed black–white inequality in stroke incidence attenuated at older age. When the hazard ratio for U on stroke was 1.5 for both blacks and whites, but U only directly influenced mortality for blacks (hazard ratio for U on mortality =1.5 for blacks; 1.0 for whites), stroke incidence rates in late life were lower among blacks (average observed IRD = −43/10,000 person-years at ages 85–94 years versus causal IRD = 20/10,000 person-years) and mirrored patterns observed in REGARDS.
A relatively moderate unmeasured common cause of stroke and survival could fully account for observed age attenuation of racial inequalities in stroke.
From the aDepartment of Epidemiology, University of California, Los Angeles Fielding School of Public Health, Los Angeles, CA
bDepartment of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA
cDepartment of Epidemiology and Environmental Health, State University of New York at Buffalo, Buffalo, NY
dDepartment of Medicine, University of California, San Francisco, San Francisco CA
eDivision of Epidemiology and Population Health, Department of Public Health Sciences, Miller School of Medicine, University of Miami, Miami, MI
fDepartment of Epidemiology, Harvard School of Public Health, Boston, MA
gKaiser Permanente Division of Research, Oakland, CA.
Submitted March 7, 2017; accepted March 28, 2018.
This work was supported by grants U54NS081760 from the National Institute of Neurological Disorders and Stroke, 15POST25090083 from the American Heart Association, K99AG053410, RF1AG052132, RF1AG050782, and K01AG047273 from the National Institute on Aging, K24DK103992 from the National Institute of Diabetes and Digestive and Kidney Diseases, T32 MH017119 from the National Institute on Mental Health, and a Banting Postdoctoral Fellowship from Canadian Institute for Health Research.
Description of the process by which someone else could obtain the data and computing code required to replicate the results reported: Computing code for generating and analyzing simulation data are available online: https://github.com/ermayeda/stroke_inequalities_simulation.
The authors report no conflicts of interest.
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Correspondence: Elizabeth Rose Mayeda, Department of Epidemiology, University of California, Los Angeles Fielding School of Public Health, BOX 951772, 46-070B CHS, Los Angeles, CA 90095. E-mail: firstname.lastname@example.org