Objective: Identifying how obesity-related characteristics cluster in populations is important to understand disease risk. Objectives of this study were to identify classes of children based on obesity-related variables and to evaluate the associations between the identified classes and overweight and obesity.
Methods: A cross-sectional study was conducted among children 3-11 years of age (n = 5185) from the TARGet Kids! network (2008-2018). Latent class analysis was used to identify distinct classes of children based on 15 family, metabolic, health behaviours and school-related variables. Associations between the identified latent classes and overweight and obesity were estimated using multinomial logistic regression.
Results: Six classes were identified: Class 1: 'Family and health risk behaviours' (20%), Class 2: 'Metabolic risk' (7%), Class 3: 'High risk' (6%), Class 4: 'High triglycerides' (21%), Class 5: 'Health risk behaviours and developmental concern' (22%), and Class 6: 'Healthy' (24%). Children in Classes 1-5 had increased odds of both overweight and obesity compared with 'Healthy' class. Class 3 'High risk' was most strongly associated with child overweight (odds ratio [OR] 1.9, 95% confidence interval [CI] 1.2, 3.2) and obesity (OR 3.3, 95% CI 1.7, 6.7).
Conclusions: Distinct classes of children identified based on obesity-related characteristics were all associated with increased obesity; however, the magnitude of risk varied depending on number of at-risk characteristics. Understanding the clustering of obesity characteristics in children may inform precision public health and population prevention interventions.
Keywords: child obesity; latent class analysis; nutrition; physical activity.
© 2020 The Authors. Obesity Science & Practice published by World Obesity and The Obesity Society and John Wiley & Sons Ltd.