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Results were compared between REGARDS (n=25,125; aged ≥45) and HRS (n=13,197; aged>50), using Cox models to predict incident stroke from 51 ACS census tract variables and to test consistency across cohorts. Stroke incidence was lower in REGARDS (5.8%) than HRS (13.9%). Twenty neighborhood variables showed meaningful cohort differences; vacancy-for-sale associations were region-specific and not replicated broadly, while other regional and Black–White disparities failed to replicate. ",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/neighborhood-characteristics-and-incident-stroke-in-us-older-adults-evaluation-in-two-nationwide-cohorts/427688/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/neighborhood-characteristics-and-incident-stroke-in-us-older-adults-evaluation-in-two-nationwide-cohorts/427688.png","ImageObject",300,407,{"name":92,"@type":93},"\tCallum ","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-16","2026-09-29",true,{"@type":102,"interactionType":103,"userInteractionCount":81},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"Which two nationwide cohort studies were compared in the analysis?","Question",{"text":112,"@type":113},"The study compared REGARDS and the Health and Retirement Study (HRS) results to evaluate incident stroke patterns across cohorts.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How were neighborhood characteristics operationalized for predicting incident stroke?",{"text":117,"@type":113},"Cox models predicted stroke using 51 American Community Survey (ACS) census tract variables, with main effects and estimates stratified by race and region.",{"name":119,"@type":110,"acceptedAnswer":120},"What neighborhood factor showed consistent associations across the two national studies?",{"text":121,"@type":113},"Inverse associations of housing vacancies for sale with stroke replicated across two national studies, suggesting potentially beneficial effects of attractive housing markets for older adult cardiovascular disease health.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},427688,1791077109,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":81,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":8,"language":139,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":67,"update_tm":143,"read_time":81},137451211410,"https://ap-avatar.wpscdn.com/avatar/2000bb0a9246f588df?x-image-process=image/resize,m_fixed,w_180,h_180&k=1786362646172706240","Innovation in Aging, 2025, Vol. 9, No. S2 803  \nAbstract citation ID: igaf122.2723  \nNEIGHBORHOOD CHARACTERISTICS AND  \nINCIDENT STROKE IN US OLDER ADULTS:  \nEVALUATION IN TWO NATIONWIDE COHORTS  \nKendra Sims1, Torsten Neilands2, Julene Johnson2, Loni Tabb3, Monika Safford4, Suzanne Judd5, Kirsten Bibbins-Domingo6, and M. Maria Glymour1, 1. Boston University, Boston, Massachusetts, United States, 2. University of California, San Francisco, San Francisco, California, United States, 3. Drexel University, Philadelphia, Pennsylvania, United States, 4. Weill Cornell Medicine, New York, New York, United States, 5. The University of Alabama at Birmingham, Birmingham, Alabama, United States, 6. Journal of the American Medical Association, Chicago, Illinois, United States  \nResearch linking adverse neighborhood context with stroke disparities may reflect publication bias for chance associations.  \nWe compared results from the REasons for Geographic and Racial Differences in Stroke (REGARDS, n = 25,125, aged ≥ 45 years, 41% Non-Hispanic Black, 55% Stroke Belt; 2003-2020) study to the Health and Retirement Study (HRS, n = 13,197, aged> 50 years, 15% Non-Hispanic Black, 18% Stroke Belt; 2004-2020). We estimated Cox models predicting stroke for 51 American Community Survey (ACS) census tract variables, evaluating inter-cohort consistency of main, race-and region-stratified estimates. Follow-up in REGARDS (median=12.1 years; IQR:  \n6.5, 14.9) was similar to HRS (median=12.3; IQR: 8.0, 15.8) .  \nCumulative stroke incidence was lower in REGARDS (5 . 8%) than HRS (13.9%). Twenty ACS variables had associations with incident stroke that differed by at least log(0.05) between cohorts.  \nThe percentage of vacant housing units for sale was associated with incident stroke among Stroke Belt participants in REGARDS (HR per SD: 0.92; 95% CI: 0.84, 1.02) and in HRS (HR per SD:  \n0. 87; 95% CI: 0.73, 1 .03); these associations were not observed among participants in the rest of the US in REGARDS (HR per SD: 1.02; 95% 0.96, 1.09, p for region interaction: 0.058) or HRS (HR per SD: 1.02; 95% 0.96, 1.09, p for region interaction: 0.078) . None of the five other regional differences or any of the  \n11 Black-White differences replicated across cohorts. Inverse associations of vacancies with stroke replicated across two national studies, potentially implicating attractive housing markets as beneficial for older adult CVD health.","cbCaigg79G5TlW3n","https://ap.wps.com/l/cbCaigg79G5TlW3n","pdf",723213,"English","# Study design and cohorts\n## Modeling approach using ACS census tract variables\n# Findings on stroke incidence across cohorts\n## Neighborhood variables with differing associations\n## Vacancy-for-sale and regional replication\n# Interpretation and implications for CVD health","[{\"question\":\"Which two nationwide cohort studies were compared in the analysis?\",\"answer\":\"The study compared REGARDS and the Health and Retirement Study (HRS) results to evaluate incident stroke patterns across cohorts.\"},{\"question\":\"How were neighborhood characteristics operationalized for predicting incident stroke?\",\"answer\":\"Cox models predicted stroke using 51 American Community Survey (ACS) census tract variables, with main effects and estimates stratified by race and region.\"},{\"question\":\"What neighborhood factor showed consistent associations across the two national studies?\",\"answer\":\"Inverse associations of housing vacancies for sale with stroke replicated across two national studies, suggesting potentially beneficial effects of attractive housing markets for older adult cardiovascular disease health.\"}]","NEIGHBORHOOD CHARACTERISTICS AND INCIDENT STROKE IN US OLDER ADULTS - EVALUATION IN TWO NATIONWIDE COHORTS | PDF",1790644570]