Socioeconomic and health‐related disparities associated with healthy brain aging in Latin American countries

Abstract Background Latin American Countries (LACs) have major health‐related inequities due to historical, cultural, and social aspects. These factors have been suggested as important determinants of healthy aging in LACs. Here, we evaluated classic and socioeconomic risk factors for healthy brain aging across five large cohorts of LACs. Method Risk factors for healthy aging were evaluated using machine‐learning models in 41,092 individuals across five LACs ([Brazil, n = 9,412], Colombia [n = 23,694], Chile [n = 1,301], Ecuador [n = 5,235], and Uruguay [n = 1,450] ( Fig. 1A ). Healthy brain aging was evaluated using z‐scored cognitive and functional ability data with selected risk factors (Age, Sex, Diabetes, Education, Isolation, House Condition, Hypertension, Heart Disease, Alcohol Consumption, Physical Activity, Smoking, Falls, and Mental Health Problems). The fitness of models was evaluated with Mean Standard Error (MSE) and Raw Mean Standard Error (RMSE) extracted from Ridge Regressions Models (adjusted p<0.05). Result Regarding cognition, our machine‐learning model with LACs was significant. The most important risk factors were mental health symptoms, education, country, physical activity, alcohol consumption, falls, socioeconomic status, isolation, age, and smoking status. No significant effects of heart disease, hypertension, sex, and diabetes were found ( Fig. 1B ). The model assessing functionality in LACs was also significant and presented the following order of risk factors: physical activity, mental health symptoms, falls, heart disease, alcohol consumption, diabetes, sex, hypertension, age, SES, education, education, and smoking status. Country and isolation did not reach statistical significance ( Fig. 1C ). Conclusion Our findings demonstrated that social and health disparities outweigh classic risk factors, such as age and sex, for cognitive and functional decline in LACs, highlighting the need to identify risk factors for healthy brain aging in underrepresented populations.