Publications by authors named "V Medel"
Structural inequality, the uneven distribution of resources and opportunities, influences health outcomes. However, the biological embedding of structural inequality in aging and dementia, especially among underrepresented populations, is unclear. We examined the association between structural inequality (country-level and state-level Gini indices) and brain volume and connectivity in 2,135 healthy controls, and individuals with Alzheimer's disease and frontotemporal lobe degeneration from Latin America and the United States.
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- Structural income inequality, defined as the uneven distribution of income across regions, affects brain dynamics and functions more significantly than individual factors like age or education.
- This study used EEG signals from 1,394 healthy participants across 10 countries to explore how structural inequality predicts various brain activity metrics, revealing a connection between socioeconomic conditions and neural functioning.
- Results show that higher structural income inequality is associated with lower brain signal complexity, increased random neural activity, and reduced power in certain brain wave frequencies, suggesting the need for a broader understanding of how social factors influence brain health.
Background: Previous studies have shown that major surgical and medical hospital admissions are associated with cognitive decline in older people (aged 40-69 years at recruitment), which is concerning for patients and caregivers. We aimed to validate these findings in a large cohort and investigate associations with neurodegeneration using MRI.
Methods: For this population-based study, we analysed data from the UK Biobank collected from March 13, 2006, to July 16, 2023, linked to the National Health Service Hospital Episode Statistics database, excluding participants with dementia diagnoses.
Brain clocks, which quantify discrepancies between brain age and chronological age, hold promise for understanding brain health and disease. However, the impact of diversity (including geographical, socioeconomic, sociodemographic, sex and neurodegeneration) on the brain-age gap is unknown. We analyzed datasets from 5,306 participants across 15 countries (7 Latin American and Caribbean countries (LAC) and 8 non-LAC countries).
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