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Latent subtypes and gender differences in the comorbidity of depression and sleep disturbances among adolescents: insights from network analysis and latent profile analysis
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DOI：10.1186/s12888-026-08513-z.png)
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Abstract
En 中文
This study aimed to explore potential subtypes, influencing factors, and gender differences in the associations between adolescent depression and sleep disorders. A cross-sectional study was conducted among adolescents utilizing the Center for Epidemiologic Studies Depression Scale and the Pittsburgh Sleep Quality Index. Latent profile analysis was employed to classify potential subtypes of comorbidities; multinomial logistic regression was used to explore influencing factors across genders; network analysis was conducted to identify core bridging symptoms that mediate the relationship between depression and sleep disturbances. Multi-class logistic regression identified significant gender differences in the factors influencing comorbid depression and sleep disorders. Key risk factors included alcohol use, abnormal weight, living conditions, family economic status, and parental education, with their effects varying between males and females. Higher education emerged as protective factors for adolescents experiencing high comorbidity. The low subtype exhibited the highest network density, while the moderate subtype displayed the lowest density; the high subtype demonstrated increased density alongside a negative correlation with symptoms. CESD11 (Restless sleep) functioned as a core bridging symptom for both genders and subtypes. In females, the pattern of core bridging symptoms transitioned from a mixed depression-sleep structure to polarized pathways dominated by sleep or depression as severity escalated. Conversely, males maintained a balanced combination of depressive and sleep bridging symptoms across all classes, exhibiting no structural polarization. The comorbidity of depression and sleep disorders in adolescents indicates considerable subtype heterogeneity and distinct gender-specific characteristics. Clinically, targeted stratified interventions can be developed by emphasizing core bridging symptoms, while also integrating subtype classification and gender-based features.
Keywords:
Depression
Sleep disturbances
Network analysis
Latent profile analysis
Gender differences
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