Cluster analysis and food group consumption in a national sample of Australian girls.
ABSTRACT Food preferences develop early in life and track into later life. There is limited information on food consumption and dietary patterns in Australian girls. The present study aimed to: (i) determine the frequency of food groups consumed over 1day; (ii) identify dietary clusters based on food group consumption; and (iii) compare dietary intakes and activity variables between clusters.
A cross-sectional analysis of 9-16-year-old girls (n=1114) from the 2007 Australian National Children's Nutrition and Physical Activity Survey was performed.
Over the whole day, 30% of all girls consumed carbonated sugar drinks, 46% consumed take-away food, 56% consumed fruit, 70% consumed at least one vegetable, and 19% and 30% consumed white and/or red meat, respectively. K-means cluster analysis derived four clusters. Approximately one-third of girls were identified in a Meat and vegetable cluster; these girls had the highest intakes of red meat and vegetables, and tended to have higher intakes of fruit, whole grain breads, low fat yoghurt, and lower intakes of take-away foods and soft drinks. They also had the highest intakes of protein, fibre and micronutrients; and tended to perform more physical activity, compared to girls in the remaining clusters.
Girls identified in the Meat and vegetable cluster, on average, consumed more lean red meat, vegetables, fruits, and low-fat dairy products, and had a higher intakes of many nutrients. The high percentage of girls not identified in this cluster suggests the need to inform them on how to make healthy, nutrient dense food choices, and why they require increased nutrient intakes at this time.
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ABSTRACT: Developing nutrition education interventions based on clusters of dietary patterns can only be done adequately when it is clear if distinctive clusters of dietary patterns can be derived and reproduced over time, if cluster membership is stable, and if it is predictable which type of people belong to a certain cluster. Hence, this study aimed to: (1) identify clusters of dietary patterns among Dutch adults, (2) test the reproducibility of these clusters and stability of cluster membership over time, and (3) identify sociodemographic predictors of cluster membership and cluster transition.Appetite 07/2014; · 2.54 Impact Factor