Clustering unhealthy lifestyle factors in Chinese children and adolescents with overweight or obesity.

Abstract

Background: This study used latent class analysis (LCA) to examine the potential patterns of unhealthy lifestyle factors (ULFs) and their association with overweight and obesity in children and adolescents with overweight or obesity in China.

Methods: We conducted three cross-sectional surveys, recruiting 7,927 children with obesity or overweight from September 2019 to January 2022. We used LCA to identify patterns of co-occurrence of ULFs based on seven types of behaviors. Multinomial logistic regression model was constructed to examine the association of fetal and neonatal factors with the clusters of ULFs.

Results: Of 7,927 participants, 7,627 (96.78%) had at least one ULF, and 6,942 (87.57%) had two or more ULFs concurrently. Using LCA, four distinct clusters were identified based on the elbow point of the Akaike's information criterion (AIC), that is, "unhealthy food intake but long sleeping", "relative health", "healthy food intake but unhealthy eating-sleeping-sitting habits", and "unhealthy food intake and unhealthy sitting-activity habits". Moreover, several factors including sex, age, infancy feeding, parental obesity, and parental age were significantly associated with the clusters of ULFs.

Conclusions: We provide evidence on how multiple ULFs in combination may influence health among Chinese children and adolescents with overweight or obesity, and we agree that further external validations are warranted.

Clinical trial number: Not applicable.