{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,11]],"date-time":"2026-05-11T19:48:39Z","timestamp":1778528919749,"version":"3.51.4"},"reference-count":35,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"6","content-domain":{"domain":["www.ahajournals.org"],"crossmark-restriction":true},"short-container-title":["Stroke"],"published-print":{"date-parts":[[2020,6]]},"abstract":"<jats:sec>\n            <jats:title>Background and Purpose\u2014<\/jats:title>\n            <jats:p>Cross sectional analyses have found large race differences in poststroke disability, yet these analyses do not account for prestroke disability, hospitalization factors, postacute care, transitions, or mortality. In this context, we explore mortality, nursing home placement, and disability in a longitudinal analysis of older stroke survivors who survived at least 90 days poststroke.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Methods\u2014<\/jats:title>\n            <jats:p>A prospective cohort of black or white stroke survivors from the National Health and Aging Trends Study (2009\u20132016) linked to Medicare were used. Disability was assessed during in-person interviews with validated scales (0\u20137). We used cox proportional hazards models to separately assess mortality and nursing home admission adjusting for age, sex, sociodemographics (marital status, education, income, insurance status, social network size), comorbidities, hospitalization factors, postacute care, and 90-day readmissions. To estimate racial differences in disability, we used a multilevel linear regression model initially adjusting for age and sex and then compared with a model adjusted for sociodemographics, comorbidities, hospitalization factors, postacute care, and 90-day readmissions.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results\u2014<\/jats:title>\n            <jats:p>\n              There were 282 stroke survivors, of which 76 (12.6%) were black. There were no race differences in long-term mortality (hazard ratio for black, 1.2 [95% CI, 0.7\u20132.2];\n              <jats:italic>P<\/jats:italic>\n              =0.5) or nursing home placement (hazard ratio for black, 0.7 [95% CI, 0.2\u20132.4];\n              <jats:italic>P<\/jats:italic>\n              =0.5). The largest race differences in disability were observed immediately prestroke, estimated age- and sex-adjusted activity limitations were (2.6 [2.0\u20133.2] in blacks versus 1.4 [1.0\u20131.8] in whites, mean difference, 1.2 [0.5\u20131.9],\n              <jats:italic>P<\/jats:italic>\n              &lt;0.001) and immediately poststroke (2.6 [2.0\u20133.3] in blacks versus 1.7 [1.2\u20132.1] in whites, mean difference, 1.0 [0.2\u20131.7],\n              <jats:italic>P<\/jats:italic>\n              &lt;0.01). Full adjustment did not substantially change the associations between race and disability.\n            <\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusions\u2014<\/jats:title>\n            <jats:p>Race differences in nursing home placement, long-term mortality, sociodemographics, comorbidities, hospitalization factors, postacute care, and readmissions are unlikely to be large contributors to race differences in poststroke disability. Further research is needed to understand the drivers of race differences in poststroke disability.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1161\/strokeaha.119.027700","type":"journal-article","created":{"date-parts":[[2020,5,14]],"date-time":"2020-05-14T09:00:47Z","timestamp":1589446847000},"page":"1813-1819","update-policy":"https:\/\/doi.org\/10.1161\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":10,"title":["Exploring Factors Contributing to Race Differences in Poststroke Disability"],"prefix":"10.1161","volume":"51","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3088-9838","authenticated-orcid":false,"given":"Lesli E.","family":"Skolarus","sequence":"first","affiliation":[{"name":"From the Department of Neurology, University of Michigan, Ann Arbor (L.E.S., C.F., J.F.B.)"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chunyang","family":"Feng","sequence":"additional","affiliation":[{"name":"From the Department of Neurology, University of Michigan, Ann Arbor (L.E.S., C.F., J.F.B.)"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"James F.","family":"Burke","sequence":"additional","affiliation":[{"name":"From the Department of Neurology, University of Michigan, Ann Arbor (L.E.S., C.F., J.F.B.)"},{"name":"Department of Neurology, Ann Arbor VA, MI (J.F.B.)."}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"276","reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"publisher","DOI":"10.1161\/STR.0b013e31829734f2"},{"key":"e_1_3_3_3_2","first-page":"379","article-title":"Prevalence of stroke\u2013United States, 2006-2010.","volume":"61","author":"Centers for Disease Control and Prevention (CDC)","year":"2012","unstructured":"Centers for Disease Control and Prevention (CDC). 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