Prevalence and patterns of major depressive disorder and subthreshold depressive symptoms in south China

重性抑郁障碍 心理健康 萧条(经济学) 多项式logistic回归 中国大陆 医学 人口学 横断面研究 精神科 逻辑回归 老年学 中国 心情 内科学 地理 考古 经济 宏观经济学 病理 机器学习 社会学 计算机科学
作者
Dan-Dan Liao,Min Dong,Kai‐Rong Ding,Cai‐Lan Hou,Wenyan Tan,Yun-Fei Ke,Fu‐Jun Jia,Shibin Wang
出处
期刊:Journal of Affective Disorders [Elsevier BV]
卷期号:329: 131-140 被引量:32
标识
DOI:10.1016/j.jad.2023.02.069
摘要

Information on major depressive disorder (MDD) and subthreshold depressive symptoms (SDS) is rarely reported in south China. This study examines the prevalence rates and patterns of MDD and SDS of a large representative sample of adult residents in south China. The Guangdong Mental Health Survey was conducted on adults (over 18 years) from September to December 2021. Multistage stratified cluster sampling was used and face-to-face interviews were done with a two-stage design by trained lay interviewers and psychiatrists. A total of 16,377 inhabitants were interviewed using standardized assessment tools. Data were weighted to adjust for differential probabilities of selection and differential response. The weighted prevalence rates of MDD and SDS were 2.5 % (95%CI: 2.2 %–2.9 %) and 14.7 % (95%CI: 14.0 %–15.5 %), respectively. Multinomial logistic regression analysis revealed that female, younger age, living in urban area, higher education, unmarried, irregular meal pattern, lack of physical exercise, chronic diseases, irregular napping pattern and short sleep were positively associated with SDS. Besides, female, younger age, unmarried, irregular meal pattern, lack of physical exercise, chronic diseases, short sleep and poor mental health were positively associated with MDD. The cross-sectional nature of the study limited causal inferences. The prevalence of MDD in Guangdong province in 2021 is higher than in mainland China in 2013. Given the higher prevalence of SDS, and high burden of depression, it also offers valuable opportunities for policymakers and health-care professionals to explore the factors affecting mental health in Guangdong province, especially during the COVID-19 epidemic.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
shxxy123完成签到 ,获得积分10
3秒前
8秒前
12秒前
Polar_bear完成签到,获得积分10
13秒前
nan应助Lylin采纳,获得10
13秒前
15秒前
飞羽发布了新的文献求助10
15秒前
Ava应助Emily采纳,获得10
16秒前
19秒前
yingnju发布了新的文献求助20
20秒前
坦率的邑完成签到 ,获得积分10
23秒前
zmh完成签到,获得积分10
23秒前
Xavier完成签到 ,获得积分10
24秒前
牛初辰发布了新的文献求助10
25秒前
威武馒头发布了新的文献求助10
25秒前
蓝天发布了新的文献求助10
28秒前
HH完成签到,获得积分10
30秒前
31秒前
31秒前
wentao完成签到,获得积分10
31秒前
SCINEXUS完成签到,获得积分0
31秒前
路宇鹏完成签到,获得积分10
32秒前
科研通AI2S应助野性的博采纳,获得10
32秒前
sunidea完成签到,获得积分10
32秒前
luan完成签到,获得积分10
32秒前
34秒前
萌萌完成签到,获得积分10
39秒前
机智的宛白完成签到,获得积分20
43秒前
ASHUN完成签到,获得积分10
45秒前
沉默绮烟完成签到,获得积分10
50秒前
想去玩完成签到,获得积分10
51秒前
传奇3应助郑建星采纳,获得10
52秒前
岸上芒果lucky酱应助一二采纳,获得10
53秒前
Stove完成签到,获得积分10
54秒前
ybk666完成签到,获得积分10
55秒前
怕孤单的听寒完成签到,获得积分0
55秒前
sanlang应助Lylin采纳,获得10
57秒前
59秒前
zzw发布了新的文献求助10
1分钟前
完美世界应助蓝天采纳,获得10
1分钟前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 2000
Various Faces of Animal Metaphor in English and Polish 800
Signals, Systems, and Signal Processing 610
Photodetectors: From Ultraviolet to Infrared 500
On the Dragon Seas, a sailor's adventures in the far east 500
Yangtze Reminiscences. Some Notes And Recollections Of Service With The China Navigation Company Ltd., 1925-1939 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6353596
求助须知:如何正确求助?哪些是违规求助? 8168622
关于积分的说明 17193614
捐赠科研通 5409688
什么是DOI,文献DOI怎么找? 2863781
邀请新用户注册赠送积分活动 1841151
关于科研通互助平台的介绍 1689915