Global, regional, and national burden of depression, 1990-2021: a decomposition and age-period-cohort analysis with projection to 2040.

Abstract

Background: Depression stands as one of the leading causes of disability worldwide. This study conducts a comprehensive analysis of the global burden of depression.

Methods: Based on the Global Burden of Disease (GBD), we employed Joinpoint regression to analyze trends disease burden of depression globally from 1990 to 2021. The age-period-cohort (APC) model was employed to decompose the effects of age, period, and cohort, while the Das Gupta method quantified the contributions of aging, population growth, and epidemiological changes. A Bayesian age-period-cohort (BAPC) model was further utilized to project disease burden through 2040.

Results: In 2021, the global age-standardized incidence, prevalence, and DALY rates of depression increased by 15.6 %, 11.3 %, and 13.4 %, compared to 1990, with average annual percentage changes (AAPCs) of 0.5 %, 0.4 %, and 0.4 %. APC analysis identified a peak age effect at 60-64 years, the highest period risk during 2017-2021, and a continuous rise in cohort risk after 1987. Cross-national inequality analysis revealed a higher burden in low-SDI countries (SII = -1981.7 per 100,000 in 2021), alongside widening health disparities among females. Decomposition analysis indicated that population growth accounted for 43.5 %-54.2 % of the global burden increase. BAPC projections estimated that by 2040, global age-standardized incidence, prevalence, and DALY rates would rise to 8478.2, 6927.8, and 1248.1 per 100,000.

Conclusions: The global burden of depression continues to rise with significant inequalities. Prioritizing women, high-growth regions, and low-SDI countries is essential to address the escalating burden. This study provides critical evidence for optimizing resource allocation and developing interdisciplinary intervention plans.