Trend of disease burden and risk factors of depressive disorder disease in Zhejiang Province from 1990 to 2019
Objective To understand the trend of disease burden and risk factors of depressive disorders in Zhejiang Province from 1990 to 2019,and provide the scientific basis for the prevention and control of depressive disorders in Zhejiang Province.Methods The data were from 2019 Global Burden of Disease Study(GBD2019);trends in the incidence,prevalence,and disability-adjusted life years(DALY)rates and major risk factors attributed to the DALY rate in Zhejiang Province from 1990 to 2019 were calculated;and those were compared to the regions with different socio-demographic index(SDI)of China and the world.Joinpoint Regression Program 5.0.1 software was used to calculate the average annual percent change(AAPC).Results In 2019,incidence,morbidity and DALY rate were 3 726.65/105,4 253.14/105 and 664.38/105,respectively;in which,those of ≥70 years old group were the highest,those of 0-14 years old group were the lowest.In 2019,incidence,morbidity and DALY rate of females were higher than those of males.From 1990 to 2019,the incidence,morbidity and DALY rate of depressive disorders in Zhejiang Province showed the upward trend(AAPC values were 0.32％,0.69％and 0.49％,respectively);which were higher than mean levels in China and the levels in middle SDI regions.From 1990 to 2019,the order of top 3 risk factors were intimate partner violence,bullying victimization and childhood sexual abuse;the standardized DALY rates of three risk factors showed downward trend(AAPC values were-0.77％,-1.13％and-0.42％,respectively,P＜0.05).Conclusion From 1990 to 2019,the disease burden of depressive disorders in Zhejiang Province showed upward trend.It should formulate the differentiated and refined prevention and control measures to reduce the burden of depression disorder in Zhejiang Province,according to the current disease burden characteristics of depressive disorder.
Depressive disordersDisease burdenDisability-adjusted life yearsRisk factors
NETL
NSTL
万方数据
