Abstract

Objectives

In Brazil, cases of Alzheimer's disease (AD) are particularly prevalent in the southeastern region, including Minas Gerais, the largest state in the area. This study aimed to estimate the disease burden and healthcare costs from 2018 to 2022.

Methods

Data on life expectancy, human development index, population size, and gross domestic product per capita were extracted to calculate disability-adjusted life-years (DALYs). Hospital admission data for AD were obtained from the Brazilian Unified Health System Department of Informatics (DATASUS) database, including the number of cases, deaths, age-specific data, and treatment costs. These variables, along with health, social, and environmental data, were processed to create risk factor layers, and the mean cost per DALY was calculated. Generalized estimating equation models were used to analyze the relationship between DALYs and various predictors, controlling for spatial autocorrelation. Maps were created to visualize the distribution of DALYs and cost per DALY.

Results

There were 323 221 deaths from AD in Brazil, with cities averaging 3.61 deaths (range 1-73) and 5.43 hospitalizations (range 1-91) annually. The mean cost per city over these years was $9935.87 (range $44.22 to $787 307.93). In Minas Gerais, significant predictors of the estimated burden of AD include the percentage of the population aged 65 years and older, the human development index, and the prevalence of cardiovascular diseases. DALYs were higher than observed, indicating potential underreporting and insufficient resource allocation for AD treatment and prevention.

Conclusions

These results emphasize the need for region-specific policies and strategies to address the AD burden effectively. Policy makers should use this information to improve planning and allocate resources appropriately for treatment and prevention.