Latent class analysis of obesity‐related characteristics and associations with body mass index among young children. (7th April 2020)

• Record Type: Journal Article
• Authors: Anderson, Laura N.; Sandhu, Ravinder; Keown‐Stoneman, Charles D.G.; De Rubeis, Vanessa; Borkhoff, Cornelia M.; Carsley, Sarah; Maguire, Jonathon L.; Birken, Catherine S.
• Is Part Of: Obesity science and practice. Volume 6:Number 4(2020)
• Page Start: 390
• Page End: 400
• Publication Date: 2020-04-07
• Subjects: child obesity -- latent class analysis -- nutrition -- physical activity; Obesity -- Periodicals; 616.398005
• DOI: 10.1002/osp4.414
• Languages: English
• ISSNs: 2055-2238

Abstract

Summary: 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.