Study: Brain clocks capture diversity and disparities in aging and dementia across geographically diverse populations . Image Credit: Lightspring / Shutterstock In a recent study published in the journal Nature Medicine , researchers used deep learning to analyze the impact of geographical, sociodemographic, socioeconomic, neurodegeneration-related, and gender diversity on brain-age gaps across 15 countries. They found that structural socioeconomic inequality, pollution, and health disparities are key predictors of increased brain-age gaps, particularly in Latin American and Caribbean (LAC) regions, with larger gaps observed in females and individuals with cognitive impairments like Alzheimer’s disease (AD).
Background The brain undergoes dynamic changes with age, which are crucial to understanding, especially in relation to disparities and brain disorders like AD. Brain-age models, which measure brain health across various factors, have the potential to capture diversity in aging but have been underexplored in underrepresented populations like those in LAC. These populations face significant socioeconomic and health disparities, which may impact brain aging.
Research on brain aging has mainly focused on populations from the Global North and often uses structural magnetic resonance imaging (MRI), neglecting brain network dynamics captured by functional MRI (fMRI) and electroencephalograms (EEG). While EEG is a more accessible tool .