Social and Economic Conditions Impact Brain Health More than Age and Sex

Latin America, a region marked by vibrant cultures, rich literature, and captivating art, also holds vast inequalities related to aging. Our study has pulled back the veil on the complex disparity-related factors influencing healthy aging, underscoring the need for tailored public policies.
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Social and Economic Conditions Impact Brain Health More than Age and Sex
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Uncovering the complexity of aging across diverse and underserved populations 

In a recent landmark study in Nature Medicine conducted by the Latin American Brain Health Institute (BrainLat), the Javeriana University in Bogota, the Global Brain Health Institute (GBHI), and other institutions, we uncover the multifaceted determinants of healthy aging in Latin American countries (LACs). In countries filled with huge diversity illustrated by writers like Gabriel García Márquez, the polyrhythmic Salsa, and cinematic masterpieces like City of God, the factors that impact aging are also full of nuances and variations but profoundly affected by disparities. 

The study (Figure 1), which incorporated the expertise of scientists from Latin America, the U.S., and Ireland, analyzed 44,394 participants from various Latin American countries. We utilized machine learning models of cross-sectional and longitudinal designs to explore the complex factors contributing to healthy aging in terms of cognitive and functional skills. Unlike high-income regions where age and sex are predominant, we found that disparity-related factors such as social determinants of health (SDH), mental health symptoms, and cardiometabolic risks play a more substantial role in Latin America. The effects were more pronounced in low-income nations within the region. This groundbreaking research provides vital insights into healthy aging in Latin America and emphasizes the urgent need for tailored interventions and policies to address unique regional risks and disparities.

a, General design of the study describing the countries included in the cross-sectional analyses (Chile, Uruguay, Colombia and Ecuador) and in the longitudinal analyses (Costa Rica and China). b, Database selection in the cross-sectional (n = 31,680 participants) and longitudinal (n = 9,258 participants) studies (total n = 40,938 participants). c, Imputation procedures. d, Risk factors, including demographics, SDH, health status (cardiometabolic factors and falls), mental health symptoms and lifestyle risk factors. e, Outcomes: cognition and functional ability. f, Multimethod approach, including different regressions (linear regression, elastic net, LASSO, ridge regression). g, Multicollinearity between risk factors that justified the selection of ridge regression as the adequate model. h, Bayesian optimization to find the best hyperparameters for ridge regression. i, Regression step used with the ridge regression. j, Regression report. k, The multimethod results revealed high consistency across methods using goodness-of-fit metrics (R2, Cohen’s F2, MSE and RMSE) and a high coherence in the weight and ranking of risk factors of healthy aging (β estimates). In k, the upper panel presents the multimethod findings related to cognitive performance. The lower panel displays the functional ability data across all countries in Latin America. Risk factors: demographics, SDH, health, lifestyle, mental health symptoms and country.

Figure 1. Methodological framework. 1. Methodological framework. a, General design of the study describing the countries included in the cross-sectional analyses (Chile, Uruguay, Colombia and Ecuador) and in the longitudinal analyses (Costa Rica and China). b, Database selection in the cross-sectional (n = 31,680 participants) and longitudinal (n = 9,258 participants) studies (total n = 40,938 participants). c, Imputation procedures. d, Risk factors, including demographics, SDH, health status (cardiometabolic factors and falls), mental health symptoms and lifestyle risk factors. e, Outcomes: cognition and functional ability. f, Multimethod approach, including different regressions (linear regression, elastic net, LASSO, ridge regression). g, Multicollinearity between risk factors that justified the selection of ridge regression as the adequate model. h, Bayesian optimization to find the best hyperparameters for ridge regression. i, Regression step used with the ridge regression. j, Regression report. k, The multimethod results revealed high consistency across methods using goodness-of-fit metrics (R2, Cohen’s F2, MSE and RMSE) and a high coherence in the weight and ranking of risk factors of healthy aging (β estimates). In k, the upper panel presents the multimethod findings related to cognitive performance. The lower panel displays the functional ability data across all countries in Latin America. Risk factors: demographics, SDH, health, lifestyle, mental health symptoms and country.

Cultural diversity, disparities, and healthy aging

The same region that gave the world magical realism in literature also shows us that aging is a multifaceted phenomenon influenced by social and health disparities. Our results, coauthored by GBHI faculty Victor Valcour and Brian Lawlor, and the Senior Atlantic fellow Sebastian Moguilner, paint a vivid picture of a region where factors related to disparities in education, cardiometabolic conditions, mental health, and social isolation impact cognition and functionality in aging, particularly in low-income nations like Colombia and Ecuador. Latin America's growing concern with dementia, predicted to increase by 150-220% by 2050, further emphasizes the need to tailor strategies to its unique social fabric. The role of socioeconomic disparities in biological models of aging and dementia has been historically overlooked. Now is the time to address such bias. 

By focusing on the region-specific needs, understanding the biology x environment interactions, and creating tailored interventions, we can drive positive change in brain health and aging across Latin America. This approach is not merely data collection and analysis; it's about raising voices against brain health inequities and providing evidence to make a healthier future. Addressing the diversity and disparities in brain health and aging is not just about scientific explorations. Our study, also coauthored by Hernan Hernandez, Marcelo Maito, Carolina Ochoa-Rosales, Michael Corley, and Jaime Miranda, evidences how poverty weaves together the threads of multimodal factors, creating a complex model of aging that reflects the contextual influences of the region.

Towards a healthier future for the region

Our study offers a roadmap for developing public health policies that resonate with people's real life and conditions. We must create multifaceted public health strategies that embrace Latin America's cultural diversity and address its unique challenges. Governments, researchers, healthcare providers, and communities must work hand in hand to:

  • Address the disparities: There will be no healthy aging in the future if the governments and stakeholders do not address the structural inequities in the area, with special focuses in brain diseases and caregivers.

By building on Latin America's vibrant diversity and addressing disparities, we can weave a future where aging is not a decline but a rich, fulfilling phase of life. 

For further insights, explore the complete study here:

Santamaria-Garcia H, Hernandez H, Moguilner S, Maito M, Ochoa-Rosales C, Corle M,  Valcour V, Miranda J, Lawlor B, Ibanez A. Factors associated with healthy aging in Latin American populations. Nature Medicine, 2023, https://doi.org/10.1038/s41591-023-02495-1

The poster image as been designed by Lucas Neufeld and Agustin Ibanez

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