Mark A Espeland, Yitbarek N Demesie, Kay Loni Olson, Samuel N Lockhart, Sarah E Tomaszewski Farias, Maryjo L Cleveland, Christy C Tangney, Lucia Crivelli, Heather M Snyder, Michele K York, Laura D Baker, Rachel A Whitmer, Rena R Wing, Katelyn R Garcia, Kathryn E Callahan
{"title":"Associations Between Deficit Accumulation Frailty and Baseline Markers of Lifestyle in the US POINTER Trial.","authors":"Mark A Espeland, Yitbarek N Demesie, Kay Loni Olson, Samuel N Lockhart, Sarah E Tomaszewski Farias, Maryjo L Cleveland, Christy C Tangney, Lucia Crivelli, Heather M Snyder, Michele K York, Laura D Baker, Rachel A Whitmer, Rena R Wing, Katelyn R Garcia, Kathryn E Callahan","doi":"10.1093/gerona/glae279","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Multidomain lifestyle interventions may have the potential to slow biological aging as captured by deficit accumulation frailty indices. We describe the distribution and composition of the 49-component frailty index (FI) developed by the U.S. POINTER clinical trial team of investigators and assess its cross-sectional associations with sociodemographic factors and markers chosen to be representative of behaviors targeted by the trial's multidomain interventions.</p><p><strong>Methods: </strong>We draw baseline data from the 2111 volunteers enrolled in U.S. POINTER who were ages 60-79 years and at increased risk for cognitive decline. Frailty components were grouped into nine domains. Associations that FI scores and their domains had with behavioral markers were described with correlations and canonical correlation.</p><p><strong>Results: </strong>The 25th, 50th, and 75th percentiles of the frailty index score distribution were 0.153, 0.189, and 0.235. Higher frailty scores tended to occur among individuals who were older, male, and living in areas of greater deprivation (all p<0.001). They were also associated with poorer self-reported diet, less physical activity, and higher Framingham risk scores (all p<0.001). Associations were diffusely distributed among the frailty component domains, indicating that no individual domain was dominating associations.</p><p><strong>Conclusions: </strong>The U.S. POINTER deficit accumulation frailty index had expected relationships with sociodemographic factors and sensitivity to the behaviors targeted by the trial's interventions. Our analysis supports its use as a secondary outcome to assess whether the multidomain interventions differentially impact an established marker of biological aging.</p>","PeriodicalId":94243,"journal":{"name":"The journals of gerontology. Series A, Biological sciences and medical sciences","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The journals of gerontology. Series A, Biological sciences and medical sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/gerona/glae279","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Multidomain lifestyle interventions may have the potential to slow biological aging as captured by deficit accumulation frailty indices. We describe the distribution and composition of the 49-component frailty index (FI) developed by the U.S. POINTER clinical trial team of investigators and assess its cross-sectional associations with sociodemographic factors and markers chosen to be representative of behaviors targeted by the trial's multidomain interventions.
Methods: We draw baseline data from the 2111 volunteers enrolled in U.S. POINTER who were ages 60-79 years and at increased risk for cognitive decline. Frailty components were grouped into nine domains. Associations that FI scores and their domains had with behavioral markers were described with correlations and canonical correlation.
Results: The 25th, 50th, and 75th percentiles of the frailty index score distribution were 0.153, 0.189, and 0.235. Higher frailty scores tended to occur among individuals who were older, male, and living in areas of greater deprivation (all p<0.001). They were also associated with poorer self-reported diet, less physical activity, and higher Framingham risk scores (all p<0.001). Associations were diffusely distributed among the frailty component domains, indicating that no individual domain was dominating associations.
Conclusions: The U.S. POINTER deficit accumulation frailty index had expected relationships with sociodemographic factors and sensitivity to the behaviors targeted by the trial's interventions. Our analysis supports its use as a secondary outcome to assess whether the multidomain interventions differentially impact an established marker of biological aging.