Latent class analysis of sleep disturbances among children and adolescents with neurodevelopmental disorders in Tianjin
10.16835/j.cnki.1000-9817.2025052
- VernacularTitle:天津市神经发育障碍儿童青少年睡眠障碍潜在类别分析
- Author:
LI Penghong, CHE Yifan, ZHAO Ziyu, CUI Tingkai
1
Author Information
1. School of Public Health, Tianjin Medical University, Tianjin (300070) , China
- Publication Type:Journal Article
- Keywords:
Neurodevelopmental disorders;
Sleep;
Latent class analysis;
Child;
Adolescent
- From:
Chinese Journal of School Health
2025;46(2):186-190
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To understand the latent categories of sleep disturbances among children and adolescents with neurodevelopmental disorders (NDDs) in Tianjin and their relationship with behavioral and social issues, so as to provide a basis for preventing and improving sleep disturbances in the population.
Methods:From September 2021 to June 2024, 272 children and adolescents aged 2-23 years with neurodevelopmental disorders were recruited from special education schools and designated rehabilitation institutions in Tianjin. Sleep disturbances were assessed using the Children s Sleep Habits Questionnaire (CSHQ). Behavioral and social issues and severity were evaluated using the Autism Behavior Checklist (ABC) and Childhood Autism Rating Scale (CARS). Latent class analysis (LCA) was employed to categorize the subjects into different sleep disturbances categories. Cochran- Armitage test was used to analyze the trend of detection rate of sleep disturbances in different age groups. Spearman rank correlation was used to analyze the correlation between the scores of each scale. The generalized linear model was used to analyze the influence of CARS and ABC scale scores. Covariance analysis was used to examine differences in behavioral and social issues among the different categories.
Results:Among 272 survey respondents, a total of 197(72.4%) children and adolescents with NDDs were identified with sleep disturbances. The detection rates of sleep disturbances were 88.9% for those aged 2-6 years, 70.6% for aged 7-12, 66.7% for aged 13-18 and 50.0% for 19-23 years old, which was decreased across age group ( Z =3.58, P <0.01). There was a positive correlation between the total CSHQ score and the total ABC score ( r=0.16, P =0.01). The generalized linear model analysis showed that after adjusting age, gender, parents education level and family monthly income, bedtime habit ( β =3.60) and sleeping latency disorder ( β =3.36) were positively correlated with CARS scores, while the bedtime habit ( β =16.73) and waking up at night ( β =17.46) were positively correlated with ABC scores ( P <0.05). LCA revealed that sleep disturbances in children and adolescents with NDDs could be classified into four categories. The covariance analysis results showed that there were statistically significant differences in the average scores of CSHQ (70.84±9.05, 50.96±6.64, 50.33±5.82, 43.84±5.44) and ABC (49.44± 39.34 , 53.04±39.75, 63.51±40.31, 38.14±34.23) among different categories of all partipants ( F=92.09, 3.95, P <0.05).
Conclusion:Sleep disturbances in children and adolescents with NDDs are severe and exhibit distinct categorical characteristics.
