An Analysis of Factors Influencing Comorbid Anxiety and Depression Among Adults in China: A Large-Scale Cross-Sectional Study.
- 1School of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, China.
- 2Guangdong Mental Health Center, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.
Abstract
Background
Comorbid anxiety and depression (CAD) are common, but the factors influencing this comorbidity have not been comprehensively studied. The aim of this study was to investigate the associations of sociodemographic and behavioral factors with CAD among residents of Guangdong Province in China.Methods
A cross-sectional study was conducted, and questionnaires, including the Depression Screening Scale (PHQ-9), the Anxiety Screening Scale (GAD-7), and the Insomnia Severity Index (ISI), were distributed among permanent residents aged 18 years and above in Guangdong Province. Logistic regression and decision tree modeling were used to construct a model to identify factors associated with CAD in adults.Results
Based on a sample of 51,774 participants from the Guangdong Provincial Mental Health Database, four groups were compared: healthy (n = 48,657), anxiety alone (n = 285), depression alone (n = 1677), and CAD (n = 1155). Factors such as sex, age, district, insomnia, BMI, education, marital status, income, smoking, drinking, dietary regularity, exercise frequency, electronic device use, daily steps, sedentary time, and physical chronic diseases were observed significant differences across four groups (p < 0.05). In univariable analyses, factors associated with CAD (vs. healthy) included female sex, younger age, urban residence, insomnia, irregular diet, prolonged electronic device use, prolonged sedentary time, and lack of exercise. Multivariable analysis revealed that insomnia (OR = 14.64, 95% CI: 12.49-17.15), irregular diet (OR = 2.96, 95% CI: 2.45-3.58), prolonged electronic device use (OR = 1.78, 95% CI: 1.51-2.11), physical chronic diseases (OR = 1.59, 95% CI: 1.38-1.82), and female (OR = 1.19, 95% CI: 1.04-1.37) were independently associated with higher risk of CAD (all p < 0.05). Older age, married/cohabiting status, higher income, occasionally regular exercise, moderate steps, and moderate sedentary time were protective factors (ORs 0.41-0.80, all p < 0.05). District, smoking, and BMI were not retained in the multivariable model. The logistic regression model showed an AUC of 0.866 (95% CI: 0.845-0.886), and the decision tree model showed an AUC of 0.839 (95% CI: 0.818-0.860). The Hosmer-Lemeshow test indicated good calibration for the logistic model (χ² = 2.09, df = 3, p = 0.553).Conclusion
This large cross-sectional study indicated that insomnia, irregular diet, prolonged device use, and physical chronic diseases were associated with an increased risk of CAD. The logistic regression model showed good discriminative ability, and the decision tree served as an exploratory tool for visualizing risk stratification. Further prospective studies are needed to assess predictive utility.
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BibTeX
@article{chen2026analysis,
title = {{An Analysis of Factors Influencing Comorbid Anxiety and Depression Among Adults in China: A Large-Scale Cross-Sectional Study.}},
author = {Zhuoqun Chen and Jiaying Huang and Yuying Wang and Jingxian Chen and Ke Zhu and Tongjie Chen and Xin-Lin Chen and Wenyan Tan},
journal = {Brain and behavior},
year = {2026},
month = oct,
doi = {10.1002/brb3.71843},
url = {https://europepmc.org/article/MED/42905896},
note = {CC BY},
}
RIS
TY - JOUR
TI - An Analysis of Factors Influencing Comorbid Anxiety and Depression Among Adults in China: A Large-Scale Cross-Sectional Study.
AU - Zhuoqun Chen
AU - Jiaying Huang
AU - Yuying Wang
AU - Jingxian Chen
AU - Ke Zhu
AU - Tongjie Chen
AU - Xin-Lin Chen
AU - Wenyan Tan
PY - 2026
DA - 2026/10/01
JO - Brain and behavior
DO - 10.1002/brb3.71843
UR - https://europepmc.org/article/MED/42905896
AB - Background Comorbid anxiety and depression (CAD) are common, but the factors influencing this comorbidity have not been comprehensively studied. The aim of this study was to investigate the associations of sociodemographic and behavioral factors with CAD among residents of Guangdong Province in China.Methods A cross-sectional study was conducted, and questionnaires, including the Depression Screening Scale (PHQ-9), the Anxiety Screening Scale (GAD-7), and the Insomnia Severity Index (ISI), were distributed among permanent residents aged 18 years and above in Guangdong Province. Logistic regression and decision tree modeling were used to construct a model to identify factors associated with CAD in adults.Results Based on a sample of 51,774 participants from the Guangdong Provincial Mental Health Database, four groups were compared: healthy (n = 48,657), anxiety alone (n = 285), depression alone (n = 1677), and CAD (n = 1155). Factors such as sex, age, district, insomnia, BMI, education, marital status, income, smoking, drinking, dietary regularity, exercise frequency, electronic device use, daily steps, sedentary time, and physical chronic diseases were observed significant differences across four groups (p < 0.05). In univariable analyses, factors associated with CAD (vs. healthy) included female sex, younger age, urban residence, insomnia, irregular diet, prolonged electronic device use, prolonged sedentary time, and lack of exercise. Multivariable analysis revealed that insomnia (OR = 14.64, 95% CI: 12.49-17.15), irregular diet (OR = 2.96, 95% CI: 2.45-3.58), prolonged electronic device use (OR = 1.78, 95% CI: 1.51-2.11), physical chronic diseases (OR = 1.59, 95% CI: 1.38-1.82), and female (OR = 1.19, 95% CI: 1.04-1.37) were independently associated with higher risk of CAD (all p < 0.05). Older age, married/cohabiting status, higher income, occasionally regular exercise, moderate steps, and moderate sedentary time were protective factors (ORs 0.41-0.80, all p < 0.05). District, smoking, and BMI were not retained in the multivariable model. The logistic regression model showed an AUC of 0.866 (95% CI: 0.845-0.886), and the decision tree model showed an AUC of 0.839 (95% CI: 0.818-0.860). The Hosmer-Lemeshow test indicated good calibration for the logistic model (χ² = 2.09, df = 3, p = 0.553).Conclusion This large cross-sectional study indicated that insomnia, irregular diet, prolonged device use, and physical chronic diseases were associated with an increased risk of CAD. The logistic regression model showed good discriminative ability, and the decision tree served as an exploratory tool for visualizing risk stratification. Further prospective studies are needed to assess predictive utility.
SN - 2162-3279
ER -