Transition and trend analysis of the burden of depression in China and different income countries: Based on GBD database and joinpoint regression model

被引:14
作者
Chen, Si [1 ,2 ]
Sun, Hongwei [1 ]
Song, Yan [2 ]
Zhang, Min [2 ]
Huang, Wei [2 ]
Zhao, Chunshan [2 ]
Wang, Yanyu [1 ]
Wang, Jihong [2 ]
Meng, HaiBo [4 ]
Zhou, Lei [3 ]
Xu, ZhengYang [2 ]
Bai, YuXin [2 ]
机构
[1] Shandong Second Med Univ, 7166 Baotong West St, Weifang 261053, Shandong, Peoples R China
[2] BeiHua Univ, Jilin 132013, Peoples R China
[3] Chinese Ctr Dis Control & Prevent CDC, Beijing 102206, Peoples R China
[4] Jilin City Med Assoc, Jilin 132011, Peoples R China
基金
中国国家自然科学基金;
关键词
Depression; Burden; Income countries; Transition analysis; Trend analysis; China; ADJUSTED LIFE-YEARS; GLOBAL BURDEN; PREVALENCE; DISEASE; DISORDERS; STRESS;
D O I
10.1016/j.jad.2024.06.067
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
Background: Depression is a leading cause of disability and poor health worldwide and is expected to rank first worldwide by 2030. The aim of this study is to analyze the transition and trend of depression burden in China and various income-level countries by utilizing the Global Burden of Disease (GBD) database and the Joinpoint regression model. This analysis seeks to comprehend the variations in the burden of depression across different income regions and evaluate their developmental patterns. Methods: Based on the GBD 2019 open dataset, this study extracted data on YLD (Years Lived with Disability), DALY (Disability-Adjusted Life Years), and incidence related to depression. The analysis focused on the period between 1990 and 2019, covering global data and distinguishing between high-income, upper-middle-income, lower-middle-income, low-income countries, and China. We utilized the Joinpoint regression model to fit the spatiotemporal trend changes among different income-level countries. Pairwise comparisons were conducted to examine the parallelism and to determine if the differences in trend changes among various regions were statistically significant. Results: From 1990 to 2019, the age-standardized YLD and DALY for depression female were higher than that in male. The YLD total change rate of depression men was higher than that of women. China exhibited the largest disparity in total YLD change rates between genders, reaching 0.08. During 1990 to 2019, the incidence of depression in 2005-2019 increased among females in middle to high-income countries, low-income countries, and China as compare to that of 1990-2005. Notably, China shown the most increase the incidence rate of females (from -0.4 % to 0.84 %). China experienced the most significant change in the YLD of depression during this period (AAPC = 0.45, 95 % CI = 0.41, 0.48, P < 0.01). China's YLD/Incidence rate was higher compared to the global, HICs, UMCs, LMCs, and LICs. In China, the YLD/incidence rate of depression began to rise in 1994, peaking around 2010, and then gradually declining. Since 2010, the growth rate of depression DALYs in China has been higher than the global average, high-income countries, upper-middle-income countries, lower-middleincome countries, and low-income countries. The DALY's AAPC value for the HLCs was the highest (AAPC = 0.24, 95 % CI = 0.22, 0.25, P < 0.01). The UMCs, in comparison to other regions, incidence rate had the highest AAPC value (AAPC = 0.48, 95 % CI = 0.46, 0.50, P < 0.01). Conclusions: Given the significant variations in the burden of depression across countries with different income levels, future strategies aimed at reducing the burden of depression should adopt tailored and differentiated approaches according to each country's specific needs and developmental stages.
引用
收藏
页码:437 / 449
页数:13
相关论文
共 42 条
[1]  
Abbafati C, 2020, LANCET, V396, P1204
[2]   Prevalence of depression among university students in low and middle income countries (LMICs): a systematic review and meta-analysis [J].
Akhtar, Parveen ;
Ma, Lu ;
Waqas, Ahmed ;
Naveed, Sadiq ;
Li, Yixuan ;
Rahman, Atif ;
Wang, Youfa .
JOURNAL OF AFFECTIVE DISORDERS, 2020, 274 :911-919
[3]  
American Psychiatric Association, 2022, Diagnostic and statistical manual of mental disorders: DSM-5TM, DOI 10.1176/appi.books.9780890425596
[4]  
[Anonymous], 2020, Population: demography, population projections, census, asylum & migrationoverview
[5]  
[Anonymous], 2018, Chinese Circ J, DOI DOI 10.3969/J.ISSN.1000-3614.2018.12.002
[6]   Trends in depression incidence in China, 1990-2019 [J].
Bai, Ruhai ;
Dong, Wanyue ;
Peng, Qiao ;
Bai, Zhenggang .
JOURNAL OF AFFECTIVE DISORDERS, 2022, 296 :291-297
[7]   Global Trends in the Incidence of Anxiety Disorders From 1990 to 2019: Joinpoint and Age-Period-Cohort Analysis Study [J].
Cao, Huiru ;
Wu, Yang ;
Yin, Hui ;
Sun, Yanqi ;
Yuan, Hui ;
Tao, Mengjun .
JMIR PUBLIC HEALTH AND SURVEILLANCE, 2024, 10
[8]  
Chen T.C., 2020, Vital Health Stat, V2, P184
[9]  
Chinese Center for Disease Control and Prevention, 2020, Institute for Health Metrics and Evaluation. Global health data ex-changeEB/OL
[10]   Global estimates of the need for rehabilitation based on the Global Burden of Disease study 2019: a systematic analysis for the Global Burden of Disease Study 2019 [J].
Cieza, Alarcos ;
Causey, Kate ;
Kamenov, Kaloyan ;
Hanson, Sarah Wulf ;
Chatterji, Somnath ;
Vos, Theo .
LANCET, 2020, 396 (10267) :2006-2017