RESULTS: K-means clustering was employed to identify clusters based on four markers of metabolic health (triacylglycerols, total cholesterol, direct HDL cholesterol and glucose) (n = 896) using data from the National Adult Nutrition Survey. A decision tree approach was developed for the delivery of targeted dietary advice per cluster based on biochemical characteristics, anthropometry and blood pressure. The appropriateness of the advice was tested by comparison with individualised dietary advice manually compiled (n = 99). A mean match of 89.1% between the methods was demonstrated with a 100% match for two-thirds of participants.
CONCLUSIONS: Good agreement was found between the individualised and targeted methods demonstrating the ability of this framework to deliver targeted dietary advice. This approach has the potential to be a fast and novel method for the delivery of targeted nutrition in clinical settings.