Predicting accelerated and delayed aging in global settings: biobehavioral age gaps and the role of global exposomes

Hernandez, H., Santamaria‐Garcia, H., Moguilner, S., Legaz, A., Prado, P., Cuadros, J., Gonzalez, L., Gonzalez‐Gomez, R., Migeot, J., Coronel‐Oliveros, C., +31 more...Tagliazucchi, E., Maito, M. A., Godoy, M. E., Cruzat, J., Shaheen, A., Farombi, T. H., Salazar, D., Ros, L. U. D., Borelli, W. V., Zimmer, E. R., NJAMNSHI, A. K., Bajpai, S., Dey, A., Mostert, C. M., Merali, Z., Salama, M., Moustafa, S. A., Farina, F. R., Fittipaldi, S., Altschuler, F., Medel, V., Huepe, D., Yaffe, K., Udeh‐Momoh, C. T., Eyre, H. A., Swieboda, P., Lawlor, B., Miranda, J., Duran‐Aniotz, C., Baez, S. & Ibanez, A. (2025). Predicting accelerated and delayed aging in global settings: biobehavioral age gaps and the role of global exposomes. Alzheimer's and Dementia, 21(S6). https://doi.org/10.1002/alz70860_099534
Copy

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.

picture_as_pdf

subject
Published Version
Creative Commons: Attribution 4.0

Download

Export as

EndNote BibTeX Reference Manager Refer Atom Dublin Core JSON Multiline CSV
Export