Association between behavioral-environmental risk patterns and multimorbidity of chronic non-communicable diseases among Chinese adolescents at schools

Abstract

Objectives

Multimorbidity, though traditionally discussed in older populations, is increasingly prevalent among adolescents. However, evidence on how co-occurring behavioral and environmental risks contribute to adolescent multimorbidity remains limited. This study aimed to identify distinct patterns of behavioral-environmental risks among Chinese adolescents and to examine how these patterns are associated with multimorbidity of chronic non-communicable diseases.

Study design

This was a cross-sectional study, utilizing data from 15,082 participants enrolled in the 2022 Shanghai “Surveillance for Common Diseases and Health Risk Factors among Students” project.

Methods

Participants were selected using a cluster random sampling method. Adolescent multimorbidity was defined as the coexistence of six chronic non-communicable diseases (high blood pressure, high myopia, dental caries, abnormal spinal curvature, obesity, and depressive symptoms). Behavioral-environmental risk dimensions covered individual lifestyle behaviors (i.e., imbalanced diet, unhealthy food, smoking or drinking, excessive screen time, insufficient sleep, and physical inactivity), school-related environmental risks (untimely seat or desk adjustment, low frequency of eye exercises or physical education classes), and family environmental factors (non-nuclear family, low parental education, disadvantaged family economy, and household secondhand smoke exposure). Latent class analysis identified distinct risk patterns, and logistic regression models explored their associations with multimorbidity.

Results

The mean age of participants was 14.94 (SD = 1.75), and 47.6% were girls. Three behavioral-environmental patterns emerged: “high behavioral and family-environmental risks (Class 1, 40.9%)”, “high behavioral and school-environmental risks (Class 2, 22.3%)”, and “relatively low behavioral-environmental risks (Class 3, 36.8%)”. Compared with Class 3, adolescents in Class 1 (OR = 1.21–1.27, all p < 0.001) or Class 2 (OR = 1.20–1.28, all p < 0.001) had significantly higher odds of multimorbidity across all adjusted models.

Conclusions

School-aged adolescents exhibit distinct behavioral-environmental risk patterns, with differing associations with multimorbidity. Findings underscore the need for integrated health promotion strategies addressing individual behaviors and broader environmental influences to reduce multimorbidity among the youth.