[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-seo-424360-105":3,"detail-sidebar-cat-0-en-105":81,"doc-detail-424360-en":130},{"code":4,"msg":5,"data":6},0,"ok",{"site_id":7,"language":8,"slug":9,"title":10,"keywords":11,"description":12,"schema_data":13,"social_meta":74,"head_meta":76,"extra_data":78,"updated_unix":80},105,"en","gait-speed-and-mortality-risk-among-community-dwelling-older-adults-with-heart-disease-evidence-from-the-rand-hrs","Gait Speed and Mortality Risk Among Community-Dwelling Older Adults with Heart Disease - Evidence from the RAND HRS","","Study analyzes how heart disease and gait speed relate to all-cause mortality during 11 years of follow-up in community-dwelling older adults. Data come from the RAND Health and Retirement Study Longitudinal 2020 (v2), including socio-demographics, multi-morbidity status, depressive symptoms, cognitive function, and mortality outcomes. Cox proportional hazards models estimate hazard ratios and 95% confidence intervals, using nonlinear cut-off values to improve clinical relevance. Slower gait speed shows higher mortality risk, supporting gait speed as a prognostic marker.",{"@graph":14,"@context":73},[15,34,56],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/healthcare/","Healthcare",3,{"item":32,"name":10,"@type":21,"position":33},"https://docshare.wps.com/document/gait-speed-and-mortality-risk-among-community-dwelling-older-adults-with-heart-disease-evidence-from-the-rand-hrs/424360/",4,{"url":32,"name":10,"@type":35,"image":36,"author":41,"headline":10,"publisher":44,"fileFormat":47,"inLanguage":8,"description":12,"dateModified":48,"datePublished":49,"encodingFormat":47,"isAccessibleForFree":50,"interactionStatistic":51},"DigitalDocument",{"url":37,"@type":38,"width":39,"height":40},"https://docshare.wps.com/thumbnails/gait-speed-and-mortality-risk-among-community-dwelling-older-adults-with-heart-disease-evidence-from-the-rand-hrs/424360.png","ImageObject",300,407,{"name":42,"@type":43},"Jasmine","Person",{"url":19,"name":45,"@type":46},"DocShare","Organization","application/pdf","2026-11-04","2026-09-28",true,{"@type":52,"interactionType":53,"userInteractionCount":55},"InteractionCounter",{"@type":54},"ViewAction",10,{"@type":57,"mainEntity":58},"FAQPage",[59,65,69],{"name":60,"@type":61,"acceptedAnswer":62},"Which dataset and study timeframe were used?","Question",{"text":63,"@type":64},"The analysis used the RAND Health and Retirement Study Longitudinal 2020 (v2) dataset, a longitudinal study that began in 1992, with 11 years of follow-up for mortality outcomes.","Answer",{"name":66,"@type":61,"acceptedAnswer":67},"How was mortality risk estimated in relation to gait speed?",{"text":68,"@type":64},"The study used Cox proportional hazards models to estimate hazard ratios and 95% confidence intervals, assessing mortality as a function of gait speed and using a nonlinear form to derive clinically applicable cut-offs.",{"name":70,"@type":61,"acceptedAnswer":71},"What gait-speed categories were compared, and what was the overall trend?",{"text":72,"@type":64},"Participants were grouped by gait speed cut-offs (≤0.5 m/s, 0.5–≤0.75 m/s, 0.75–≤1.0 m/s, and >1.0 m/s). Slower gait speed groups showed higher mortality risk than the >1.0 m/s group, with the highest risk in the ≤0.5 m/s category.","https://schema.org",{"og:url":32,"og:type":75,"og:title":10,"og:site_name":45,"og:description":12},"article",{"robots":77,"canonical":32},"index,follow",{"doc_id":79,"site_id":7},424360,1791100349,{"code":4,"msg":82,"data":83},"success",[84,88,92,96,101,106,110,115,120,123,126],{"id":22,"doc_module":4,"doc_module_name":25,"category_name":85,"show_sort_weight":86,"slug":87},"Story & Novel",90,"story-novel",{"id":26,"doc_module":4,"doc_module_name":25,"category_name":89,"show_sort_weight":90,"slug":91},"Literature",80,"literature",{"id":33,"doc_module":4,"doc_module_name":25,"category_name":93,"show_sort_weight":94,"slug":95},"Exam",70,"exam",{"id":97,"doc_module":4,"doc_module_name":25,"category_name":98,"show_sort_weight":99,"slug":100},5,"Comic",60,"comic",{"id":102,"doc_module":4,"doc_module_name":25,"category_name":103,"show_sort_weight":104,"slug":105},6,"Technology",50,"technology",{"id":107,"doc_module":4,"doc_module_name":25,"category_name":29,"show_sort_weight":108,"slug":109},7,40,"healthcare",{"id":111,"doc_module":4,"doc_module_name":25,"category_name":112,"show_sort_weight":113,"slug":114},8,"Research & Report",30,"research-report",{"id":116,"doc_module":4,"doc_module_name":25,"category_name":117,"show_sort_weight":118,"slug":119},9,"Religion & Spirituality",20,"religion-spirituality",{"id":118,"doc_module":4,"doc_module_name":25,"category_name":121,"show_sort_weight":118,"slug":122},"World Cup","world-cup",{"id":55,"doc_module":4,"doc_module_name":25,"category_name":124,"show_sort_weight":55,"slug":125},"Lifestyle","lifestyle",{"id":127,"doc_module":4,"doc_module_name":25,"category_name":128,"show_sort_weight":97,"slug":129},19,"General","general",{"code":4,"msg":82,"data":131},{"doc_id":79,"user_id":132,"nickname":42,"user_avatar":133,"doc_module":4,"category_id":107,"category_name":29,"doc_title":10,"doc_description":12,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":55,"is_deleted":4,"is_public":22,"is_downloadable":22,"audit_status":22,"page_count":22,"language":139,"language_code":8,"site_id":7,"html_lang":8,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":12,"update_tm":143,"read_time":30,"preview_page_count":4},2336478487870,"https://ap-avatar.wpscdn.com/davatar_085a072bc5b1113ac321206ff7593b45","Innovation in Aging, 2025, Vol. 9, No. S2 1069  \nfrom the RAND Health and Retirement Study Longitudinal 2020 (v2) dataset, a nationally-representative longitudinal study that began in 1992. Measures included socio-demographics, multi-morbidity status, depressive symptoms, cognitive function, and all-cause mortality. We used Cox-Proportional Hazards to estimate the hazard ratio (HR) and 95% confidence interval (CI) of all-cause mortality as a function of gait speed. We also examined the nonlinear form of gait speed to obtain the best cut-off points for predicting mortality that are more applicable in the clinical setting than its linear form. Participants were categorized into four groups based on gait speed cut-off (≤0.5 m/s, 0.5-≤0.75 m/s, 0 .75-≤1 .0 m/s, >1m/s) . Older adults with heart disease and slower gait speed of ≤ 0.5m/sec are more at higher risk for mortality (HR = 3.02, 95% CI = 2.18-3.06), while, those with gait speed 0.5-≤0.75 m/s are at moderately elevated risk for mortality (HR = 2.25, 95% CI 1.61-3.16), and those with gait speed 0.75-≤1.0 m/s are at lower risk than the slow walking groups (HR = 1.85, 95% CI 1.38-2.47), compared to those with gait speed >1m/sec after controlling for all covariates. These findings underscore the value of gait speed as a prognostic marker and highlight the need for targeted interventions such as lower-extremity strengthening and endurance training to preserve mobility and reduce mortality risk in this vulnerable population.  \nAbstract citation ID: igaf122.3596  \nGAIT SPEED AND MORTALITY RISK AMONG  \nCOMMUNITY-DWELLING OLDER ADULTS WITH  \nHEART DISEASE: EVIDENCE FROM THE RAND HRS  \nMelanie Navos1, and Yong-Fang Kuo2, 1. University of Texas Medical Branch, Galveston, Texas, United States, 2. University of Texas Medical Branch, Galveston, Galveston, Texas, United States  \nWe examined the relationship of heart disease and gait speed with all-cause mortality over 11 years of follow-up among community-dwelling older adults. Participants (N = 1153) were","cbCaio54X3fNk3Zr","https://ap.wps.com/l/cbCaio54X3fNk3Zr","pdf",945393,"English","# Abstract\n## Study design and dataset\n## Methods and modeling\n## Gait-speed cutoffs and findings\n## Clinical implications","[{\"question\":\"Which dataset and study timeframe were used?\",\"answer\":\"The analysis used the RAND Health and Retirement Study Longitudinal 2020 (v2) dataset, a longitudinal study that began in 1992, with 11 years of follow-up for mortality outcomes.\"},{\"question\":\"How was mortality risk estimated in relation to gait speed?\",\"answer\":\"The study used Cox proportional hazards models to estimate hazard ratios and 95% confidence intervals, assessing mortality as a function of gait speed and using a nonlinear form to derive clinically applicable cut-offs.\"},{\"question\":\"What gait-speed categories were compared, and what was the overall trend?\",\"answer\":\"Participants were grouped by gait speed cut-offs (≤0.5 m/s, 0.5–≤0.75 m/s, 0.75–≤1.0 m/s, and \\u003e1.0 m/s). Slower gait speed groups showed higher mortality risk than the \\u003e1.0 m/s group, with the highest risk in the ≤0.5 m/s category.\"}]","Gait Speed and Mortality Risk Among Community-Dwelling Older Adults with Heart Disease - Evidence from the RAND HRS | PDF",1790633916]