Ruilin Cao1, Tingting Gao2, Yueyang Hu3, Zeying Qin4, Hui Ren5, Leilei Liang6, Chuanen Li7, Songli Mei8. 1. School of Public Health, Jilin University, No. 1163 Xinmin Street, Changchun, Jilin Province, 130021, China. Electronic address: 17808062486@163.com. 2. School of Public Health, Jilin University, No. 1163 Xinmin Street, Changchun, Jilin Province, 130021, China. Electronic address: gaoting1123@sina.com. 3. School of Public Health, Jilin University, No. 1163 Xinmin Street, Changchun, Jilin Province, 130021, China. Electronic address: 1402610488@qq.com. 4. School of Public Health, Jilin University, No. 1163 Xinmin Street, Changchun, Jilin Province, 130021, China. Electronic address: zeyingqin@sina.com. 5. School of Public Health, Jilin University, No. 1163 Xinmin Street, Changchun, Jilin Province, 130021, China. Electronic address: renhui18@mails.jlu.edu.cn. 6. School of Public Health, Jilin University, No. 1163 Xinmin Street, Changchun, Jilin Province, 130021, China. Electronic address: liangleileill@163.com. 7. School of Public Health, Jilin University, No. 1163 Xinmin Street, Changchun, Jilin Province, 130021, China. Electronic address: 18364166569@163.com. 8. School of Public Health, Jilin University, No. 1163 Xinmin Street, Changchun, Jilin Province, 130021, China. Electronic address: meisongli@sina.com.
Abstract
BACKGROUND: Previous studies have showed the independent associations between screen time, physical activity (PA), sleep duration, and depressive symptoms, but little is known about the influence of lifestyles on depressive symptoms. This study aimed to identify clustering patterns of health-related behavior in Chinese adolescents and their association with depressive symptoms. METHODS: The sample consisted of 4178 adolescent students. Screen time, physical activity, and sleep time were self-reported. The level of depressive symptoms was measured using the Center for Epidemiologic Studies Depression Scale. A two-step cluster analysis was conducted to identify lifestyle patterns. Univariate and multivariate logistic regression were used to examine the associations between clusters and depressive symptoms. RESULTS: About 28.1% of participants reported depressive symptoms. Four lifestyle clusters were identified: (1) active pattern (n = 865 [20.7%]); (2) high sleep duration pattern (n = 1263 [30.2%]); (3) high screen time pattern (n = 665 [15.9%]); and (4) low physical activity-low sleep duration pattern (n = 1385[33.1%]). Cluster 1 and 2 were relatively healthy groups. Cluster 3 and 4 were at a higher risk of developing depressive symptoms than cluster 1. LIMITATIONS: This was a cross-sectional study, and causal relations could not be identified. Self-reported questionnaire instruments were used to collect data, which might have led to some recall bias. CONCLUSIONS: Clusters of lifestyle behaviors were identified, and differences in depressive symptoms were found among clusters. Public mental illness prevention strategies should expand their capacity to focus on lifestyle patterns.
BACKGROUND: Previous studies have showed the independent associations between screen time, physical activity (PA), sleep duration, and depressive symptoms, but little is known about the influence of lifestyles on depressive symptoms. This study aimed to identify clustering patterns of health-related behavior in Chinese adolescents and their association with depressive symptoms. METHODS: The sample consisted of 4178 adolescent students. Screen time, physical activity, and sleep time were self-reported. The level of depressive symptoms was measured using the Center for Epidemiologic Studies Depression Scale. A two-step cluster analysis was conducted to identify lifestyle patterns. Univariate and multivariate logistic regression were used to examine the associations between clusters and depressive symptoms. RESULTS: About 28.1% of participants reported depressive symptoms. Four lifestyle clusters were identified: (1) active pattern (n = 865 [20.7%]); (2) high sleep duration pattern (n = 1263 [30.2%]); (3) high screen time pattern (n = 665 [15.9%]); and (4) low physical activity-low sleep duration pattern (n = 1385[33.1%]). Cluster 1 and 2 were relatively healthy groups. Cluster 3 and 4 were at a higher risk of developing depressive symptoms than cluster 1. LIMITATIONS: This was a cross-sectional study, and causal relations could not be identified. Self-reported questionnaire instruments were used to collect data, which might have led to some recall bias. CONCLUSIONS: Clusters of lifestyle behaviors were identified, and differences in depressive symptoms were found among clusters. Public mental illness prevention strategies should expand their capacity to focus on lifestyle patterns.
Authors: Casey Regan; Caitlin Fehily; Elizabeth Campbell; Jenny Bowman; Jack Faulkner; Christopher Oldmeadow; Kate Bartlem Journal: Prev Med Rep Date: 2022-06-27