TY - JOUR
T1 - The impacts of social determinants of health and cardiometabolic factors on cognitive and functional aging in Colombian underserved populations
AU - Santamaria-Garcia, Hernando
AU - Moguilner, Sebastian
AU - Rodriguez-Villagra, Odir Antonio
AU - Botero-Rodriguez, Felipe
AU - Pina-Escudero, Stefanie Danielle
AU - O’Donovan, Gary
AU - Albala, Cecilia
AU - Matallana, Diana
AU - Schulte, Michael
AU - Slachevsky, Andrea
AU - Yokoyama, Jennifer S.
AU - Possin, Katherine
AU - Ndhlovu, Lishomwa C.
AU - Al-Rousan, Tala
AU - Corley, Michael J.
AU - Kosik, Kenneth S.
AU - Muniz-Terrera, Graciela
AU - Miranda, J. Jaime
AU - Ibanez, Agustin
N1 - Funding Information:
Open Access funding provided by the IReL Consortium Multi-partner consortium to expand dementia research in Latin America (ReDLat, supported by National Institutes of Health, National Institutes of Aging [R01 AG057234] Alzheimer’s Association [SG-20–725707] Tau Consortium, and Global Brain Health Institute) and Alzheimer’s Association GBHI ALZ UK-20–639295 (AI, JY, KP, VV); ANID/FONDAP/15150012 (AS, AI); ANID/FONDEF/18I10113 and 20I10152 (AS, AI); ANID/Fondecyt/1191726, 1210176, 1210195 (AS, AI); ANID/PIA/ANILLOS ACT210096 (AI); Sistema General de Regalías (BPIN2018000100059), Universidad del Valle CI 5316 (AI); Alliance for Health Policy and Systems Research (HQHSR1206660) (JM); Bloomberg Philanthropies (grant 46129, via University of North Carolina at Chapel Hill School of Public Health) (JM); FONDECYT via CIENCIACTIVA/CONCYTEC, British Council, British Embassy and the Newton-Paulet Fund (223–2018, 224–2018) (JM); DFID/MRC/Wellcome Global Health Trials (MR/M007405/1) (JM); Fogarty International Center (R21TW009982, D71TW010877, R21TW011740)(JM); Grand Challenges Canada (0335–04)(JM); International Development Research Center Canada (IDRC 106887, 108167) (JM); Inter-American Institute for Global Change Research (IAI CRN3036) (JM); National Cancer Institute (1P20CA217231) (JM); National Heart, Lung and Blood Institute (HHSN268200900033C, 5U01HL114180, 1UM1HL134590) (JM); National Institute of Mental Health (1U19MH098780) (JM); Swiss National Science Foundation (40P740-160366), UKRI BBSRC (BB/T009004/1) (JM); UKRI EPSRC (EP/V043102/1) (JM); UKRI MRC (MR/P008984/1, MR/P024408/1, MR/P02386X/1) (JM); Welcome (074833/Z/04/Z, 093541/Z/10/Z, 103994/Z/14/Z, 107435/Z/15/Z, 205177/Z/16/Z, 214185/Z/18/Z, 218743/Z/19/Z) (JM); World Diabetes Foundation (WDF15-1224) (JM). The contents of this publication are solely the responsibility of the authors and do not represent the official views of these institutions.
Publisher Copyright:
© 2023, The Author(s).
PY - 2023
Y1 - 2023
N2 - Global 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.
AB - Global 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.
KW - Cardiometabolic factors
KW - Cognition
KW - Functionality
KW - National Aging Population Survey
KW - Social determinants of Health
UR - http://www.scopus.com/inward/record.url?scp=85149029365&partnerID=8YFLogxK
U2 - 10.1007/s11357-023-00755-z
DO - 10.1007/s11357-023-00755-z
M3 - Article
C2 - 36849677
AN - SCOPUS:85149029365
SN - 2509-2715
JO - GeroScience
JF - GeroScience
ER -