Intrarelationships between suboptimal health status and anxiety symptoms: A network analysis

焦虑 担心 心理干预 医学 精神科 公共卫生 临床心理学 住所 人口 横断面研究 心理学 环境卫生 人口学 病理 社会学
作者
Yangyu Liu,Pu Ge,Xiaoming Zhang,Yunchou Wu,Zhaocai Sun,Quan Bai,Jing Sun,Huali Zuo,Pingping Wang,Jinyu Cong,Bo Xu,Kunmeng Liu,Yibo Wu,Benzheng Wei
出处
期刊:Journal of Affective Disorders [Elsevier]
卷期号:354: 679-687
标识
DOI:10.1016/j.jad.2024.03.104
摘要

Suboptimal health status is a global public health concern of worldwide academic interest, which is an intermediate health status between health and illness. The purpose of the survey is to investigate the relationship between anxiety statuses and suboptimal health status and to identify the central symptoms and bridge symptoms.This study recruited 26,010 participants aged <60 from a cross-sectional study in China in 2022. General Anxiety Disorder-7 (GAD-7) and suboptimal health status short form (SHSQ-9) were used to quantify the levels of anxiety and suboptimal health symptoms, respectively. The network analysis method by the R program was used to judge the central and bridge symptoms. The Network Comparison Test (NCT) was used to investigate the network differences by gender, place of residence, and age in the population.In this survey, the prevalence of anxiety symptoms, SHS, and comorbidities was 50.7 %, 54.8 %, and 38.5 %, respectively. "Decreased responsiveness", "Shortness of breath", "Uncontrollable worry" were the nodes with the highest expected influence. "Irritable", "Exhausted" were the two symptom nodes with the highest expected bridge influence in the network. There were significant differences in network structure among different subgroup networks.Unable to study the causal relationship and dynamic changes among variables. Anxiety and sub-health were self-rated and may be limited by memory bias.Interventions targeting central symptoms and bridge nodes may be expected to improve suboptimal health status and anxiety in Chinese residents. Researchers can build symptom networks for different populations to capture symptom relationships.
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