Background/objectives: Evidence suggests diet, physical activity (PA) and sedentary behaviour cluster together in children, but research supporting an association with overweight/obesity is equivocal. Furthermore, the stability of clusters over time is unknown. The aim of this study was to examine the clustering of diet, PA and sedentary behaviour in Australian children and cross-sectional and longitudinal associations with overweight/obesity. Stability of obesity-related clusters over 3 years was also examined.
Subjects/methods: Data were drawn from the baseline (T1: 2002/2003) and follow-up waves (T2: 2005/2006) of the Health Eating and Play Study. Parents of Australian children aged 5-6 (n=87) and 10-12 years (n=123) completed questionnaires. Children wore accelerometers and height and weight were measured. Obesity-related clusters were determined using K-medians cluster analysis. Multivariate regression models assessed cross-sectional and longitudinal associations between cluster membership, and body mass index (BMI) Z-score and weight status. Kappa statistics assessed cluster stability over time.
Results: Three clusters, labelled 'most healthy', 'energy-dense (ED) consumers who watch TV' and 'high sedentary behaviour/low moderate-to-vigorous PA' were identified at baseline and at follow-up. No cross-sectional associations were found between cluster membership, and BMI Z-score or weight status at baseline. Longitudinally, children in the 'ED consumers who watch TV' cluster had a higher odds of being overweight/obese at follow-up (odds ratio=2.8; 95% confidence interval: 1.1, 6.9; P<0.05). Tracking of cluster membership was fair to moderate in younger (K=0.24; P=0.0001) and older children (K=0.46; P<0.0001).
Conclusions: This study identified an unhealthy cluster of TV viewing with ED food/drink consumption, which predicted overweight/obesity in a small longitudinal sample of Australian children. Cluster stability was fair to moderate over 3 years and is a novel finding. Prospective research in larger samples is needed to examine how obesity-related clusters track over time and influence the development of overweight and obesity.