Evidence map›Paper›PMID 38764153›Full record

ArticleEpidemiology and psychiatric sciences2024

The long-term spatio-temporal trends in burden and attributable risk factors of major depressive disorder at global, regional and national levels during 1990-2019: a systematic analysis for GBD 2019.

Zhi-Yang Mo, Ze-Zhen Qin, Jun-Jie Ye, Xin-Xuan Hu, Rui Wang, Ya-Ye Zhao, Ping Zheng, Qiao-Shan Lu, Qiao Li, Xian-Yan Tang

Abstract read
In one paragraph

Article in Epidemiology and psychiatric sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
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29citing papers in PubMed, 1 pooled it
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

29 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Zhi-Yang MoDepartment of Epidemiology and Biostatistics, School of Public Health, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, China.
Ze-Zhen QinDepartment of Epidemiology and Biostatistics, School of Public Health, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, China.
Jun-Jie YeDepartment of Epidemiology and Biostatistics, School of Public Health, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, China.
Xin-Xuan HuDepartment of Epidemiology and Biostatistics, School of Public Health, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, China.
Rui WangDepartment of Epidemiology and Biostatistics, School of Public Health, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, China.
Ya-Ye ZhaoDepartment of Epidemiology and Biostatistics, School of Public Health, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, China.
Ping ZhengDepartment of Epidemiology and Biostatistics, School of Public Health, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, China.
Qiao-Shan LuDepartment of Epidemiology and Biostatistics, School of Public Health, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, China.
Qiao LiDepartment of Epidemiology and Biostatistics, School of Public Health, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, China.
Xian-Yan TangDepartment of Epidemiology and Biostatistics, School of Public Health, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, China.ORCID https://orcid.org/0000-0001-6448-0355

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimsCaused by multiple risk factors, heavy burden of major depressive disorder (MDD) poses serious challenges to public health worldwide over the past 30 years. Yet the burden and attributable risk factors of MDD were not systematically known. We aimed to reveal the long-term spatio-temporal trends in the burden and attributable risk factors of MDD at global, regional and national levels during 1990-2019.

methodsWe obtained MDD and attributable risk factors data from Global Burden of Disease Study 2019. We used joinpoint regression model to assess the temporal trend in MDD burden, and age-period-cohort model to measure the effects of age, period and birth cohort on MDD incidence rate. We utilized population attributable fractions (PAFs) to estimate the specific proportions of MDD burden attributed to given risk factors.

resultsDuring 1990-2019, the global number of MDD incident cases, prevalent cases and disability-adjusted life years (DALYs) increased by 59.10%, 59.57% and 58.57%, respectively. Whereas the global age-standardized incidence rate (ASIR), age-standardized prevalence rate (ASPR) and age-standardized DALYs rate (ASDR) of MDD decreased during 1990-2019. The ASIR, ASPR and ASDR in women were 1.62, 1.62 and 1.60 times as that in men in 2019, respectively. The highest age-specific incidence, prevalence and DALYs rate occurred at the age of 60-64 in women, and at the age of 75-84 in men, but the maximum increasing trends in these age-specific rates occurred at the age of 5-9. Population living during 2000-2004 had higher risk of MDD. MDD burden varied by socio-demographic index (SDI), regions and nations. In 2019, low-SDI region, Central sub-Saharan Africa and Uganda had the highest ASIR, ASPR and ASDR. The global PAFs of intimate partner violence (IPV), childhood sexual abuse (CSA) and bullying victimization (BV) were 8.43%, 5.46% and 4.86% in 2019, respectively.

conclusionsOver the past 30 years, the global ASIR, ASPR and ASDR of MDD had decreased trends, while the burden of MDD was still serious, and multiple disparities in MDD burden remarkably existed. Women, elderly and populations living during 2000-2004 and in low-SDI regions, had more severe burden of MDD. Children were more susceptible to MDD. Up to 18.75% of global MDD burden would be eliminated through early preventing against IPV, CSA and BV. Tailored strategies-and-measures in different regions and demographic groups based on findings in this studywould be urgently needed to eliminate the impacts of modifiable risk factors on MDD, and then mitigate the burden of MDD.

Indexed as

Global Burden of DiseaseGlobal HealthMajor Depressive DisorderAdolescentAdultAgedCost of IllnessDisability-Adjusted Life YearsFemaleHumansIncidenceMaleMiddle AgedPrevalenceRisk FactorsSpatio-Temporal Analysisage-period-cohort studybullying victimizationchildhood sexual abuseglobal burden of diseaseintimate partner violencejoinpoint regression analysismajor depressive disordersystematic analysis

Identifiers

PMID38764153
PMCPMC11362682

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.