Your browser doesn't support javascript.
loading
The cross-sectional study of depressive symptoms and associated factors among adolescents by backpropagation neural network.
Lv, J; Guo, X; Meng, C; Fei, J; Ren, H; Zhang, Y; Qin, Z; Hu, Y; Yuan, T; Liang, L; Li, C; Yue, J; Gao, R; Song, Q; Zhao, X; Mei, S.
Afiliação
  • Lv J; Department of Social Medicine and Health Management, School of Public Health of Jilin University, Changchun, 130021, China. Electronic address: ljp2207166788@163.com.
  • Guo X; Department of Social Medicine and Health Management, School of Public Health of Jilin University, Changchun, 130021, China. Electronic address: 13050277638@163.com.
  • Meng C; Department of Social Medicine and Health Management, School of Public Health of Jilin University, Changchun, 130021, China. Electronic address: mengcc123456@163.com.
  • Fei J; Department of Social Medicine and Health Management, School of Public Health of Jilin University, Changchun, 130021, China. Electronic address: kurosakidomo@163.com.
  • Ren H; Nursing Department, The First Bethune Hospital of Jilin University, Changchun, Jilin, 130021, China. Electronic address: renhui18@mails.jlu.edu.cn.
  • Zhang Y; Nursing Department, The First Bethune Hospital of Jilin University, Changchun, Jilin, 130021, China. Electronic address: zyue@mail.jlu.edu.cn.
  • Qin Z; Department of Social Medicine and Health Management, School of Public Health of Jilin University, Changchun, 130021, China. Electronic address: zeyingqin@sina.com.
  • Hu Y; Department of Social Medicine and Health Management, School of Public Health of Jilin University, Changchun, 130021, China. Electronic address: 18844194244@163.com.
  • Yuan T; Department of Social Medicine and Health Management, School of Public Health of Jilin University, Changchun, 130021, China. Electronic address: yuan18844092937@163.com.
  • Liang L; Department of Social Medicine and Health Management, School of Public Health of Jilin University, Changchun, 130021, China. Electronic address: liangleileill@163.com.
  • Li C; Department of Social Medicine and Health Management, School of Public Health of Jilin University, Changchun, 130021, China. Electronic address: 18364166569@163.com.
  • Yue J; Department of Social Medicine and Health Management, School of Public Health of Jilin University, Changchun, 130021, China. Electronic address: yjy752021@163.com.
  • Gao R; Department of Social Medicine and Health Management, School of Public Health of Jilin University, Changchun, 130021, China. Electronic address: gr998777@163.com.
  • Song Q; Department of Social Medicine and Health Management, School of Public Health of Jilin University, Changchun, 130021, China. Electronic address: songqianqian129@163.com.
  • Zhao X; Department of Social Medicine and Health Management, School of Public Health of Jilin University, Changchun, 130021, China. Electronic address: zhaoxixi2021gw@163.com.
  • Mei S; Department of Social Medicine and Health Management, School of Public Health of Jilin University, Changchun, 130021, China. Electronic address: meisongli@sina.com.
Public Health ; 208: 52-58, 2022 Jul.
Article em En | MEDLINE | ID: mdl-35687956
ABSTRACT

OBJECTIVES:

This study aimed to investigate the association between depressive symptoms and diet- and lifestyle-related behaviors among adolescents. STUDY

DESIGN:

Cross-sectional study.

METHODS:

Our study used stratified random cluster sampling method to recruit 6,251 adolescents aged 11-19 years as samples for research and analysis. The Center for Epidemiological Studies Depression Scale was used to assess depressive symptoms. Chi-squared test, t test, and logistic regression were used to explore the diet and lifestyle factors of depressive symptoms. Backpropagation (BP) neural network model was used to investigate the ranking of diet and lifestyle behaviors factors of depressive symptoms.

RESULTS:

The prevalence of depressive symptoms among adolescents was 32.1%. Multivariable logistic regression was used to determine 10 important variables of depressive symptoms. After ranking the importance by BP neural network, the top three important variables were found, which were sleep duration (100%), screen time (49.1%), and breakfast (23.6%).

CONCLUSION:

Sleep duration, screen time, and breakfast were associated factors with the most significant impacts on depressive symptoms.
Assuntos
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Depressão / Estilo de Vida Tipo de estudo: Diagnostic_studies / Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Limite: Adolescent / Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Depressão / Estilo de Vida Tipo de estudo: Diagnostic_studies / Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Limite: Adolescent / Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article