BMC psychiatry · 2025
The risk factors of obsessive-compulsive disorder: a cross-sectional study in Southwestern China.
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Chen Haibing, Feng Jie, Wang Mengling, Han Huifang, Deng Yue, Qin Kesu, Liao Jiangyu, Chen Chengzhi, Qiu Jingfu, Zhang Hongyang
Аннотация
BACKGROUND: In recent years, obsessive-compulsive disorder (OCD) has emerged as the fourth most prevalent mental disorder. However, the relationship between OCD and various factors, including demographic characteristics, lifestyles, and dietary habits remains uncertain. This study aims to explore the connection between various factors and OCD.
METHODS: A cross-sectional survey was conducted from January 14 to February 15, 2023, targeting the general population through an online platform. Demographic characteristics, lifestyles, dietary habits, and OCD symptoms were assessed using a validated classification scale. To identify potential risk factors for OCD, Lasso and logistic regression analyses were performed. Subsequently, the relative importance of these factors was evaluated through machine learning models, including Support Vector Machine, Random Forest, and Back Propagation Neural Network.
RESULTS: Among the 1572 participants, 30.40% were categorized as high-risk for OCD. Logistic regression analysis revealed that having a medical history (OR = 1.709, 95% CI: 1.064-2.738), sleep disorders (OR = 1.460, 95% CI: 1.005-2.137), gastrointestinal (GI) symptoms (OR = 1.562, 95% CI: 1.057-2.311), and abnormal defecation (OR = 1.431, 95% CI: 1.013-2.018) significantly increased the risk of OCD (all P < 0.05). These findings were consistent with the results from machine learning models, further supporting the critical role of these factors in OCD risk.
CONCLUSION: This study identified medical history, GI symptoms, sleep disorders and picky eating as significant risk factors for OCD. These findings offer valuable insights into the etiology of OCD and suggest potential avenues for targeted interventions and preventive strategies aimed at reducing OCD risk.
METHODS: A cross-sectional survey was conducted from January 14 to February 15, 2023, targeting the general population through an online platform. Demographic characteristics, lifestyles, dietary habits, and OCD symptoms were assessed using a validated classification scale. To identify potential risk factors for OCD, Lasso and logistic regression analyses were performed. Subsequently, the relative importance of these factors was evaluated through machine learning models, including Support Vector Machine, Random Forest, and Back Propagation Neural Network.
RESULTS: Among the 1572 participants, 30.40% were categorized as high-risk for OCD. Logistic regression analysis revealed that having a medical history (OR = 1.709, 95% CI: 1.064-2.738), sleep disorders (OR = 1.460, 95% CI: 1.005-2.137), gastrointestinal (GI) symptoms (OR = 1.562, 95% CI: 1.057-2.311), and abnormal defecation (OR = 1.431, 95% CI: 1.013-2.018) significantly increased the risk of OCD (all P < 0.05). These findings were consistent with the results from machine learning models, further supporting the critical role of these factors in OCD risk.
CONCLUSION: This study identified medical history, GI symptoms, sleep disorders and picky eating as significant risk factors for OCD. These findings offer valuable insights into the etiology of OCD and suggest potential avenues for targeted interventions and preventive strategies aimed at reducing OCD risk.