Dynamic trends, spatial clustering, and multi-model projections of the global burden of Alzheimer’s disease and other dementias: an analysis of GBD 1990–2021 data to 2050 - Xiang, Fangfang; Liu, Xiaorui; Chen, Gang (Frontiers in Aging Neuroscience, 2026)
BackgroundAlzheimer’s disease and other dementias (ADOD) are a leading causes of disability and mortality among older adults worldwide. While the rising burden is recognized, comprehensive analyses of its dynamic growth rates, spatial clustering patterns, and comparative long-term forecasts remain limited, hindering targeted policy response.MethodsUsing data from the Global Burden of Disease (GBD) 2021 study for individuals aged ≥60 years across 204 countries (1990–2021), we analyzed six burden indicators. We calculated age-standardized rates (ASR) and estimated annual percentage changes (EAPC) to quantify trends. Spatial clustering of EAPC patterns was performed using hierarchical clustering. Future burden to 2050 was projected using both exponential smoothing (ES) and autoregressive integrated moving average (ARIMA) models, with comparative analysis across sex, age, and Socio-demographic Index (SDI).ResultsFrom 1990 to 2021, global ADOD burden increased markedly in absolute terms. EAPC analysis revealed accelerated annual growth (>1%) in East Asia and Eastern Europe, surpassing the global average. Spatial clustering identified four distinct geographic archetypes, with rapid-growth clusters spanning middle-income regions in Latin America and Southeast Asia. Women and adults aged ≥80 years, especially those ≥95, bore a disproportionately high and increasing burden. Both ES and ARIMA models projected a continued rise in absolute burden to 2050, forecasting a near-doubling of the disease burden (DALYs) among women.ConclusionThe global ADOD burden is escalating with pronounced dynamic heterogeneity in growth velocity and distinct spatial patterns. Our multi-model projections warn of a mounting crisis, disproportionately impacting women, the oldest-old, and rapidly aging middle-income regions. Public health strategies must evolve from static assessments to dynamic surveillance and geographically tailored interventions, with urgent investment in prevention and care systems in high-growth clusters.