Dietary patterns of 11-year-old children and associations with nutrient intakes

Abstract

Background:  The majority of studies looking at diet–disease relationships have mainly concentrated on individual nutrients or foods. Recently, the popularity of using dietary patterns, which evaluates the diet as a whole opposed to individual nutrients to assess diet–disease relationships, has increased. However, few studies have assessed the relationship between dietary patterns and nutrient intakes. In this study, the principal component analysis (PCA) method was used to determine the dietary patterns of 11-year-old children and how these were related to nutrient intakes. Methods:  Children participating in a population-based birth cohort study (n = 709; male 378) completed a food frequency questionnaire (FFQ) (adapted DietQ, Tinuviel Software, Anglesey, UK) nutrient intakes were calculated (QBuilder, Tinuviel Software, Anglesey, UK). All nutrient data were log-transformed and energy-adjusted. PCA (a quantitative method for data reduction to extract simplified patterns from correlated multi-item data) was applied to data collected by FFQ to determine dietary components. Component scores were used to test the validity of the dietary components with known predictors such as gender and socioeconomic status (SES) using analysis of variance. The relationship between these dietary components and nutrient intakes were assessed using Pearson's correlation. Results:  A total of 73 items were retained in the PCA. A three component solution was chosen. Dietary components were termed Fruit (fresh and tinned fruit), Processed food (high fat processed foods) and Traditional (mixture of meat and vegetables). Higher SES was associated with higher scores for Fruit and Traditional components (P = 0.02 and P < 0.001, respectively) and lower scores for the Processed component (P < 0.001). Girls had significantly higher scores for the Fruit component than boys and lower scores for the Processed component (P < 0.001). The intakes of fats were significantly inversely associated with the Fruit component, whereas the opposite relationship is seen for the Processed component (Table 1). Antioxidant vitamins β-carotene, vitamin C and vitamin E had a positive relationship with the Fruit and Traditional components, whereas the inverse association was seen for the Processed component. Table 1.   Correlation coefficients of dietary patterns and selected nutrients Component Total fat MUFA PUFA Saturated fat Retinol β-carotene Vitamin E MUFA, monounsaturated fat; PUFA, polyunsaturated fat; *P < 0.01, **P < 0.001. Fruit −0.35** −0.37** −0.12* −0.28** −0.11* 0.31** 0.23** Processed food 0.35** 0.44* 0.15** 0.26** −0.14** −0.35** −0.20** Traditional −0.08 −0.05 −0.01 −0.09 0.12* 0.46** 0.15** Discussion:  The dietary patterns identified in this study are similar to those identified by others (Northstone & Emmett, 2008; Craig et al., 2010). To our knowledge, this is one of the first studies to evaluate the relationship between dietary patterns and nutrient intakes in British school children. The results from this study suggest that, when dietary patterns are compared, then patterns of nutrient intakes are also being compared. This is an important consideration because nutrients are not consumed individually, yet the majority of focus of diet-disease relationships has been to evaluate the relationship between individual nutrient and disease. Conclusions:  Dietary patterns, derived using PCA, are a method for assessing patterns of dietary and nutrient intakes and may provide a useful method to evaluate diet–disease relationships.