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Clustering of Sedentary Behaviours, Physical Activity, and Energy-Dense Food Intake in Six-Year-Old Children: Associations with Family Socioeconomic Status

Junwen Yang‐Huang, Amy van Grieken, Lu Wang, Wilma Jansen, Hein Raat

2020Nutrients33 citationsDOIOpen Access PDF

Abstract

This study examined the clustering of lifestyle behaviours in children aged six years from a prospective cohort study in the Netherlands. Additionally, we analysed the associations between socioeconomic status and the lifestyle behaviour clusters that we identified. Data of 4059 children from the Generation R Study were analysed. Socioeconomic status was measured by maternal educational level and net household income. Lifestyle behaviours including screen time, physical activity, calorie-rich snack consumption and sugar-sweetened beverages consumption were measured via a parental questionnaire. Hierarchical and non-hierarchical cluster analyses were applied. The associations between socioeconomic status and lifestyle behaviour clusters were assessed using logistic regression models. Three lifestyle clusters were identified: “relatively healthy lifestyle” cluster (n = 1444), “high screen time and physically inactive” cluster (n = 1217), and “physically active, high snacks and sugary drinks” cluster (n = 1398). Children from high educated mothers or high-income households were more likely to be allocated to the “relatively healthy lifestyle” cluster, while children from low educated mothers or from low-income households were more likely to be allocated in the “high screen time and physically inactive” cluster. Intervention development and prevention strategies may use this information to further target programs promoting healthy behaviours of children and their families.

Topics & Concepts

Socioeconomic statusScreen timeCluster (spacecraft)Environmental healthLogistic regressionDemographyCohortGerontologyMultilevel modelHousehold incomeSedentary lifestyleMedicinePsychologyPhysical activityPopulationGeographyPhysical therapyInternal medicineArchaeologyProgramming languageMachine learningComputer scienceSociologyObesity, Physical Activity, DietEating Disorders and BehaviorsHealth and Lifestyle Studies
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