Foods are generally consumed in combination; therefore dietary recommendations should consider diet as a whole, rather than individual foods or nutrients. We know that dietary intake throughout the life course is involved in the development of lifestyle diseases, including cardiovascular disease (CVD) and obesity which are currently endemic in the UK. This project aims to provide an insight into nutritional life course exposures and the potential of these exposures to affect markers of CVD.

Studies have previously linked childhood obesity with CVD in adulthood (Lloyd et al., 2010) and therefore asfood behaviours established in childhood/adolescence may ultimately go on to affect adult cardiovascular health it is important to adopt a healthy lifestyle early in life in order to decrease later disease risk. Observing dietary patterns throughout the life course should be beneficial in calculating the time point at which nutritional intake may be most important and also whether tracking one type of dietary pattern over a period of time or changing to a different diet pattern renders an individual more/less likely to be at risk of disease. Dietary patterns are primarily derived via two statistical methods: cluster analysis (CA) and principal component analysis (PCA). Both of these methods have been found to give similar results in the ALSPAC study at 7 years of age (Smith et al., 2011).

Tracking over time is easier to quantify for patterns that have been derived using cluster analysis as this method assigns an individual to one category only at each timepoint. Change in category can then easily be determined. In comparison, PCA results in a score for each individual for each pattern obtained. We will therefore examined patterns obtained from CA in the first instance.Four clusters have been observed in ALSPAC using food diary data at 7, 10 and 13 years of age (Northstone et al., 2013). We will use this information to investigate whether dietary patterns and their tracking have any implication upon known risk factors for CVD (fat mass, blood pressure, CIMT and blood lipids) observed in the cohort at 15 and 17 years of age. Socioeconomic status is a major confounder for dietary intake (Northstone et al., 2012 & 2005). It is hypothesised that there will be a correlation between dietary patterns and measured risk factors for CVD, such that a more healthy pattern will infer decreased risk and that any associations may strengthen with pattern tracking (e.g. where an individual is consistently assigned to the same pattern over time).