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. 2024 Dec 23;24(1):943.
doi: 10.1186/s12888-024-06419-2.

Global trends in depressive disorder prevalence and DALYs among young populations: a comprehensive analysis from 1990 to 2021

Enhui Yang #  1 , Feng Chen #  2   3 , Yang Yang #  4 , Yuansi Zhang #  5 , Hao Lin #  6 , Yu Zhang #  7 , Maoping Chu  8   9
Affiliations

Global trends in depressive disorder prevalence and DALYs among young populations: a comprehensive analysis from 1990 to 2021

Enhui Yang et al. BMC Psychiatry. .

Abstract

To analyze the trend changes in the disease burden of depressive disorder (DD) among youth and adolescents aged 10 to 29 years globally from 1990 to 2021 to provide a theoretical basis for the prevention and treatment of DD in young populations. Utilizing data from the Global Burden of Disease Study 2021, prevalence rates and disability-adjusted life years (DALYs) were employed as indicators. Trends in the disease burden of DD among global youth aged 10 to 29 years from 1990 to 2021 were analyzed with joinpoint regression models. The analysis incorporated major risk factors. Concurrently, an age-period-cohort model was used to provide a more comprehensive assessment of the prevalence and burden of DD. Over the past 30 years, the prevalence rates of DD and DALYs rate among the 10-29-year-old age group generally showed an increasing trend, with values for females being consistently higher than values for males. Notably, compared with the other age groups, the 10- to 14- year-old age group presented more significant increases in both prevalence and DALYs. Regional disparity analysis revealed that while high-sociodemographic index (SDI) regions showed an increasing trend in DD prevalence and DALYs, middle- to low-SDI regions showed some decline. This study highlights the global disease burden of depressive disorder among young populations. The significant increase in both prevalence and DALYs in the 10- to 14-year-old age group emphasizes the trend toward an earlier onset of depressive disorder, also underlining the disparities in depressive disorder management between high-SDI and low-SDI regions. Clinical trial number: not applicable.

Keywords: Age-period-cohort analysis; Depressive disorder; Disease burden; Youth and adolescents.

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Conflict of interest statement

Declarations. Ethics approval and consent to participate: This study was based on publicly available data from the Global Burden of Disease (GBD) study provided by the Institute for Health Metrics and Evaluation ( https://vizhub.healthdata.org/gbd-results/ ). As the study utilized secondary data without directly involving human participants, no specific institutional ethics approval was required. Additionally, the study complies with the principles of the Declaration of Helsinki ( http://www.wma.net/en/30publications/10policies/b3/index.html ). Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Estimated Annual Percentage Change (EAPC) in the prevalence and Disability-Adjusted Life Years (DALYs) rates of depressive disorder 10–29 years Between 1990 and 2021 at the Global and Regional Level A represents EAPC in Prevalence rate, B represents EAPC in DALYs rate. Abbreviations: SDI, Sociodemographic Index((five categories; countries with a high, high-middle, middle, low-middle, or low sociodemographic index); UI, uncertainty interval
Fig. 2
Fig. 2
Average Annual Percent Change (AAPC) of the prevalence and DALYs of DD among the global population aged 10–29 from 1990 to 2021. A represents the AAPC in prevalence, and B represents the AAPC in DALY rates
Fig. 3
Fig. 3
Regional differences in the distribution of major risk factors for depressive disorder DALYs across different age groups A represents 10-14years old, B represents15-19years old, C represents 20-24years old, D represents 25–29 years old
Fig. 4
Fig. 4
Age-Period-Cohort (APC) Analysis on the prevalence of depressive disorder among different age groups (10–14, 15–19, 20–24, 25–29 years old) across global Socio-demographic Index quintiles. The age distribution of prevalence illustrates the temporal changes in the relative proportions of prevalence among different age groups from 1990 to 2021. Local drift indicates the annual percentage change (percentage per year) in specific prevalence for each age group from 1990 to 2021. The age effect is represented by the fitted longitudinal age-specific prevalence after adjusting for period bias for a specific number of birth cohorts. The period effect is illustrated by the period relative risk of prevalence (prevalence ratio), calculated as the ratio of age-specific prevalence from the period 1992–1996 to that of 2017–2021. The birth cohort effect is indicated by the cohort relative risk of prevalence (prevalence ratio), calculated as the ratio of age-specific prevalence from the 1967 cohort to that of the 2007 cohort. Points and shaded areas represent the prevalence or ratios and their corresponding 95% confidence intervals. A represents global, B represents High-SDI, C represents High-middle SDI, D represents Middle- SDI, E represents Low-middle SDI, F represents Low-SDI
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