TY - JOUR
T1 - Public Health
AU - Hernandez, Hernan
AU - Santamaria-Garcia, Hernando
AU - Moguilner, Sebastian
AU - Legaz, Agustina
AU - Prado, Pavel
AU - Cuadros, Jhosmary
AU - Gonzalez, Liset
AU - Gonzalez-Gomez, Raul
AU - Migeot, Joaquín
AU - Coronel-Oliveros, Carlos
AU - Tagliazucchi, Enzo
AU - Maito, Marcelo Adrian
AU - Godoy, Maria Eugenia
AU - Cruzat, Josephine
AU - Shaheen, Ahmed
AU - Farombi, Temitope Hannah
AU - Salazar, Daniel
AU - Ros, Lucas Uglione Da
AU - Borelli, Wyllians Vendramini
AU - Zimmer, Eduardo R.
AU - Njamnshi, Alfred Kongnyu
AU - Bajpai, Swati
AU - Dey, A. B.
AU - Mostert, Cyprian M.
AU - Merali, Zul
AU - Salama, Mohamed
AU - Moustafa, Sara Ayman
AU - Farina, Francesca R.
AU - Fittipaldi, Sol
AU - Altschuler, Florencia
AU - Medel, Vicente
AU - Huepe, David
AU - Yaffe, Kristine
AU - Udeh-Momoh, Chinedu T.
AU - Eyre, Harris A.
AU - Swieboda, Pawel
AU - Lawlor, Brian
AU - Miranda, Jaime
AU - Duran-Aniotz, Claudia
AU - Baez, Sandra
AU - Ibanez, Agustin
N1 - Publisher Copyright:
© 2025 The Alzheimer's Association. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.
PY - 2025/12/1
Y1 - 2025/12/1
N2 - BACKGROUND: Global health challenges like aging and dementia are shaped by socioeconomic disparities, environmental factors, and social determinants of health. We developed a behavioral age gap (BAG), measuring the difference between expected behavioral age and chronological age METHOD: We utilized a cross-sectional sample (n = 161,981) comprising countries from Latin America, Europe, Asia, and Africa. Behavioral age was estimated using a Gradient Boosting Regressor with 10-fold cross-validation, incorporating multiple risk factors (hypertension, diabetes, heart disease, female sex, visual impairment and hearing impairment) and protective factors (cognition, functional ability, education) associated with healthy aging. BAG was calculated as the difference between predicted and chronological age, and adjusted gaps were derived from the residuals of regressing BAG on chronological age. RESULT: Chronological age was accurately estimated using biobehavioral predictors. Key protective predictors were functional ability, education, and cognition, while main risks were hearing impairment, heart disease, and hypertension. Participants were categorized into delayed or accelerated aging groups to explore biobehavioral factors in aging. Both models demonstrated high predictive accuracy, especially for accelerated aging. BAGs varied significantly across regions and income levels, increasing from Europe to Asia, LA, and Africa. Participants from LIC displayed accelerated aging compared to HIC. Adverse exposomes were linked to accelerated aging with large effect sizes. CONCLUSION: This work positions BAGs as markers of aging disparities, emphasizing the influence of inequalities and exposomes, while providing measures for targeted interventions and research.
AB - BACKGROUND: Global health challenges like aging and dementia are shaped by socioeconomic disparities, environmental factors, and social determinants of health. We developed a behavioral age gap (BAG), measuring the difference between expected behavioral age and chronological age METHOD: We utilized a cross-sectional sample (n = 161,981) comprising countries from Latin America, Europe, Asia, and Africa. Behavioral age was estimated using a Gradient Boosting Regressor with 10-fold cross-validation, incorporating multiple risk factors (hypertension, diabetes, heart disease, female sex, visual impairment and hearing impairment) and protective factors (cognition, functional ability, education) associated with healthy aging. BAG was calculated as the difference between predicted and chronological age, and adjusted gaps were derived from the residuals of regressing BAG on chronological age. RESULT: Chronological age was accurately estimated using biobehavioral predictors. Key protective predictors were functional ability, education, and cognition, while main risks were hearing impairment, heart disease, and hypertension. Participants were categorized into delayed or accelerated aging groups to explore biobehavioral factors in aging. Both models demonstrated high predictive accuracy, especially for accelerated aging. BAGs varied significantly across regions and income levels, increasing from Europe to Asia, LA, and Africa. Participants from LIC displayed accelerated aging compared to HIC. Adverse exposomes were linked to accelerated aging with large effect sizes. CONCLUSION: This work positions BAGs as markers of aging disparities, emphasizing the influence of inequalities and exposomes, while providing measures for targeted interventions and research.
UR - https://www.scopus.com/pages/publications/105025738686
U2 - 10.1002/alz70860_099534
DO - 10.1002/alz70860_099534
M3 - Article
C2 - 41435196
AN - SCOPUS:105025738686
SN - 1552-5260
VL - 21
SP - e099534
JO - Alzheimer's and Dementia
JF - Alzheimer's and Dementia
ER -