The Use of Cluster Analysis for Non-Continuous Variables in the Assessment of Dietary Behaviours and Physical Activities in Primary School Children

Physical activity, along with proper nutrition, is a very important element in child development. Lack of everyday, regular physical activity among young people is a public health problem. The aim of the study was to use cluster analysis to assess the relationship between nutrition and physical activity levels of primary school children. The study included 682 students from randomly selected elementary schools and was performed using a proprietary questionnaire during the 2013/2014 school year. The questionnaire contained questions about eating habits and physical activity, as well as the socio-economic conditions of families. Clusters of students of similar dietary habits were identified using cluster analysis and subsequently compared in terms of physical activity level. We identified four clusters, characterized by relative internal homogeneity and at the same time variability between one another in terms of number of meals throughout the day and time of their consumption. The most important characteristic of Cluster 1 was eating four meals a day including breakfast, which is the most important meal of the day. The diets of children in Cluster 2 abounded with raw vegetables and fruits. Students in Cluster 3 were characterized by a regular and varied diet. The least appropriate behaviour in the field of nutrition was observed among students belonging to Cluster 4. Cluster analysis in the studied population allowed relationships between dietary habits and physical activity to be described. By using the UIAF indicator (Moderate to Intense Physical Activity), a statistically significant association between the eating habits of the children and their physical activity levels was observed. A sufficient level of physical activity was observed in most students belonging to Cluster 3, and high levels of physical activity were observed in a small percentage of children belonging Cluster 4. An average level of physical activity was observed in a high percentage of children belonging to Cluster 4. Low levels of physical activity were most frequently observed in Clusters 4 and 1 and least frequently observed in Cluster 3. All of the identified active forms of free-time activity were most commonly acknowledged in Cluster 3. The study supports a beneficial relationship between students’ eating behaviours and physical activity.