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The impacts of social determinants of health and cardiometabolic factors on cognitive and functional aging in Colombian underserved populations

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dc.contributor.authorSantamaria, Hernando
dc.contributor.authorMoguilner, Sebastian
dc.contributor.authorRodriguez, Odir
dc.contributor.authorBotero, Felipe
dc.contributor.authorPina, Stefanie
dc.contributor.authorO’Donovan, Gary
dc.contributor.authorAlbala, Cecilia
dc.contributor.authorMatallana, Diana
dc.contributor.authorSchulte, Michael
dc.contributor.authorSlachevsky Conchol, Andrea
dc.contributor.authorYokoyama, Jennifer
dc.contributor.authorPossin, Katherine
dc.contributor.authorNdhlovu, Lishomwa
dc.contributor.authorAl‑Rousan, Tala
dc.contributor.authorCorley, Michael
dc.contributor.authorKosik, Kenneth
dc.contributor.authorMuniz, Graciela
dc.contributor.authorMiranda, J. Jaime
dc.contributor.authorIbanez, Agustin
dc.date.accessioned2024-04-22T21:11:28Z
dc.date.available2024-04-22T21:11:28Z
dc.date.issued2023
dc.description.abstractGlobal initiatives call for further understanding of the impact of inequity on aging across underserved populations. Previous research in low- and middle-income countries (LMICs) presents limitations in assessing combined sources of inequity and outcomes (i.e., cognition and functionality). In this study, we assessed how social determinants of health (SDH), cardiometabolic factors (CMFs), and other medical/social factors predict cognition and functionality in an aging Colombian population. We ran a cross-sectional study that combined theory- (structural equation models) and data-driven (machine learning) approaches in a population-based study (N = 23,694; M = 69.8 years) to assess the best predictors of cognition and functionality. We found that a combination of SDH and CMF accurately predicted cognition and functionality, although SDH was the stronger predictor. Cognition was predicted with the highest accuracy by SDH, followed by demographics, CMF, and other factors. A combination of SDH, age, CMF, and additional physical/psychological factors were the best predictors of functional status. Results highlight the role of inequity in predicting brain health and advancing solutions to reduce the cognitive and functional decline in LMICs.
dc.description.versionPublicada
dc.identifier.citationSantamaria-Garcia H, Moguilner S, Rodriguez-Villagra OA, Botero-Rodriguez F, Pina-Escudero SD, O'Donovan G, Albala C, Matallana D, Schulte M, Slachevsky A, Yokoyama JS, Possin K, Ndhlovu LC, Al-Rousan T, Corley MJ, Kosik KS, Muniz-Terrera G, Miranda JJ, Ibanez A. The impacts of social determinants of health and cardiometabolic factors on cognitive and functional aging in Colombian underserved populations. Geroscience. 2023 Aug;45(4):2405-2423. doi: 10.1007/s11357-023-00755-z
dc.identifier.doihttps://doi.org/10.1007/s11357-023-00755-z
dc.identifier.urihttps://hdl.handle.net/11447/8666
dc.language.isoen
dc.subjectCardiometabolic factors
dc.subjectCognition
dc.subjectFunctionality
dc.subjectNational Aging Population Survey
dc.subjectSocial determinants of Health.
dc.titleThe impacts of social determinants of health and cardiometabolic factors on cognitive and functional aging in Colombian underserved populations
dc.typeArticle
dcterms.accessRightsAcceso Abierto
dcterms.sourceGeroScience
dspace.entity.typePublication
relation.isAuthorOfPublicatione25c3d3e-63b5-4e04-951a-12a4989aa772
relation.isAuthorOfPublication.latestForDiscoverye25c3d3e-63b5-4e04-951a-12a4989aa772

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