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Developing and evaluating a frailty index for older South Africans - findings from the HAALSI study

dc.contributor.authorBarker, Fred J.
dc.contributor.authorDavies, Justine
dc.contributor.authorGomez-Olive, F. Xavier
dc.contributor.authorKahn, Kathleen
dc.contributor.authorMatthews, Gail V.
dc.contributor.authorPayne, Collin
dc.contributor.authorSalomon, Joshua A.
dc.contributor.authorTollman, Stephen M.
dc.contributor.authorWade, Alisha
dc.contributor.authorWalker, Richard W.
dc.contributor.authorWitham, Miles D.
dc.date.accessioned2022-12-05T01:22:47Z
dc.date.available2022-12-05T01:22:47Z
dc.date.issued2021-06-09
dc.date.updated2021-11-28T07:31:13Z
dc.description.abstractBackground: despite rapid population ageing, few studies have investigated frailty in older people in sub-Saharan Africa. We tested a cumulative deficit frailty index in a population of older people from rural South Africa. Methods: analysis of cross-sectional data from the Health and Ageing in Africa: Longitudinal Studies of an INDEPTH Community (HAALSI) study. We used self-reported diagnoses, symptoms, activities of daily living, objective physiological indices and blood tests to calculate a 32-variable cumulative deficit frailty index. We fitted Cox proportional hazards models to test associations between frailty category and all-cause mortality. We tested the discriminant ability of the frailty index to predict one-year mortality alone and in addition to age and sex. Results: in total 3,989 participants were included in the analysis, mean age 61 years (standard deviation 13); 2,175 (54.5%) were women. The median frailty index was 0.13 (interquartile range 0.09–0.19); Using population-specific cutoffs, 557 (14.0%) had moderate frailty and 263 (6.6%) had severe frailty. All-cause mortality risk was related to frailty severity independent of age and sex (hazard ratio per 0.01 increase in frailty index: 1.06 [95% confidence interval 1.04–1.07]). The frailty index alone showed moderate discrimination for one-year mortality: c-statistic 0.68–0.76; combining the frailty index with age and sex improved performance (c-statistic 0.77–0.81). Conclusion: frailty measured by cumulative deficits is common and predicts mortality in a rural population of older South Africans. The number of measures needed may limit utility in resource-poor settings.en_AU
dc.description.sponsorshipDr Barker and Professor Witham acknowledge support from the NIHR Newcastle Biomedical Research Centre. ANW is supported by the Fogarty International Centre of the National Institutes of Health under Award Number K43TW010698. National Institutes of Ageing (NIH) grant 1P01AG041710-01A1 National Dept of Science and Innovation (via South African Medical Research Council); Wellcome Trust (058893/Z/99/A; 069683/Z/02/Z; 085477/Z/08/Z; 085477/B/08/Z).en_AU
dc.format.mimetypeapplication/pdfen_AU
dc.identifier.issn0002-0729en_AU
dc.identifier.urihttp://hdl.handle.net/1885/281529
dc.language.isoen_AUen_AU
dc.provenanceThis is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/),which permits non-commercial re-use,distribution,and reproduction in any medium,provided the original work is properly citeden_AU
dc.publisherOxford University Pressen_AU
dc.rights© 2021 TheAuthor(s)en_AU
dc.rights.licenseCreative Commons Attribution Non-Commercial Licenseen_AU
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/en_AU
dc.sourceAge and Ageingen_AU
dc.subjectfrailty indexen_AU
dc.subjectolder peopleen_AU
dc.subjectglobal healthen_AU
dc.titleDeveloping and evaluating a frailty index for older South Africans - findings from the HAALSI studyen_AU
dc.typeJournal articleen_AU
dcterms.accessRightsOpen Accessen_AU
local.bibliographicCitation.lastpage7en_AU
local.bibliographicCitation.startpage1en_AU
local.contributor.affiliationBarker, Fred J., Newcastle Universityen_AU
local.contributor.affiliationDavies, Justine, University of the Witwatersranden_AU
local.contributor.affiliationGomez-Olive, F. Xavier, University of the Witwatersrand, Johannesburg, South Africaen_AU
local.contributor.affiliationKahn, Kathleen, University of the Witwatersranden_AU
local.contributor.affiliationMatthews, Gail V., University of New South Walesen_AU
local.contributor.affiliationPayne, Collin, College of Arts and Social Sciences, ANUen_AU
local.contributor.affiliationSalomon, Joshua A., Stanford Universityen_AU
local.contributor.affiliationTollman, Stephen M., University of the Witwatersranden_AU
local.contributor.affiliationWade, Alisha, University of the Witwatersranden_AU
local.contributor.affiliationWalker, Richard W., Newcastle Universityen_AU
local.contributor.affiliationWitham, Miles D., Newcastle Universityen_AU
local.contributor.authoruidPayne, Collin, u1057660en_AU
local.description.notesImported from ARIESen_AU
local.identifier.absfor420202 - Disease surveillanceen_AU
local.identifier.absfor420210 - Social epidemiologyen_AU
local.identifier.ariespublicationu3555277xPUB463en_AU
local.identifier.citationvolume2021en_AU
local.identifier.doi10.1093/ageing/afab111en_AU
local.publisher.urlhttps://academic.oup.com/en_AU
local.type.statusPublished Versionen_AU

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