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Clustering of energy balance-related behaviors in 5-year-old children: Lifestyle patterns and their longitudinal association with weight status development in early childhood

Jessica S Gubbels12, Stef PJ Kremers12*, Annette Stafleu3, R Alexandra Goldbohm4, Nanne K de Vries125 and Carel Thijs56

Author Affiliations

1 Department of Health Promotion, Maastricht University, PO Box 616, 6200 MD, Maastricht, the Netherlands

2 NUTRIM School for Nutrition, Toxicology and Metabolism, Maastricht University, PO Box 616, 6200 MD, Maastricht, the Netherlands

3 TNO, PO Box 360, 3700 AJ, Zeist, the Netherlands

4 TNO, PO Box 2215, 2301 CE, Leiden, the Netherlands

5 School for Public Health and Primary Care (CAPHRI), Maastricht University, PO Box 616, 6200 MD, Maastricht, the Netherlands

6 Department of Epidemiology, Maastricht University, PO Box 616, 6200 MD, Maastricht, the Netherlands

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International Journal of Behavioral Nutrition and Physical Activity 2012, 9:77  doi:10.1186/1479-5868-9-77

Published: 21 June 2012

Abstract

Background

This study identified lifestyle patterns by examining the clustering of eating routines (e.g. eating together as a family, having the television on during meals, duration of meals) and various activity-related behaviors (i.e. physical activity (PA) and sedentary screen-based behavior) in 5-year-old children, as well as the longitudinal association of these patterns with weight status (BMI and overweight) development up to age 8.

Methods

Data originated from the KOALA Birth Cohort Study (N = 2074 at age 5). Principal component analysis (PCA) was used to identify lifestyle patterns. Backward regression analyses were used to examine the association of lifestyle patterns with parent and child background characteristics, as well as the longitudinal associations between the patterns and weight status development.

Results

Four lifestyle patterns emerged from the PCA: a ‘Television–Snacking’ pattern, a ‘Sports–Computer’ pattern, a ‘Traditional Family’ pattern, and a “Fast’ Food’ pattern. Child gender and parental educational level, working hours and body mass index were significantly associated with the scores for the patterns. The Television–Snacking pattern was positively associated with BMI (standardized regression coefficient β = 0.05; p < 0.05), and children with this pattern showed a positive tendency toward being overweight at age 8 (Odds ratio (OR) = 1.27, p = 0.06). In addition, the Sports–Computer pattern was significantly positively associated with an increased risk of becoming overweight at age 7 (OR = 1.28, p < 0.05).

Conclusions

The current study showed the added value of including eating routines in cross-behavioral clustering analyses. The findings indicate that future interventions to prevent childhood overweight should address eating routines and activity/inactivity simultaneously, using the synergy between clustered behaviors (e.g. between television viewing and snacking).

Keywords:
BMI; Diet; Eating pattern; Factor analysis; Overweight; Physical activity; Principal component analysis; Screen-based behavior; Sedentary behavior