There is accumulating evidence on differences in the link between types of dairy products and cardio-metabolic health, but inconsistent findings limit the field. In my PhD project, I undertook an epidemiological investigation comprising inter-related but distinct themes evaluating aspects of nutritional, molecular and genetic epidemiology to advance scientific understanding. I undertook research to describe dairy consumption patterns over time by evaluating nationally-representative data of the United Kingdom National Diet and Nutrition Survey. I observed significant time trends for specific dairy types and groups, which were different among different groups of people e.g. adults younger than 65 years or elderly people. Using data from the large Fenland (n~12,000) and EPIC Norfolk (n~25,000) studies, I investigated associations of total and types of dairy consumption with markers of metabolic risk and adiposity as potential pathways to cardio-metabolic disease. The analyses showed differential associations of dairy types and groups mainly with markers of adiposity and lipidaemia. I explored the potential of objective markers to assess dairy consumption, by examining metabolomics profiles and blood fatty acids to identify a set of biomarkers predicting dairy consumption and prospective associations of the identified biomarkers with type 2 diabetes risk. I was able to develop and validate metabolite scores reflecting consumption of some dairy products and observed inverse associations between some of these scores and type 2 diabetes incidence. I analysed genetic determinants of dairy consumption, using a genome-wide association study in the UK Biobank (n~500,000) and identified single nucleotide polymorphisms predicting milk, cheese and total dairy consumption. Overall, this PhD work contributed towards (1) a more precise description of dairy consumption patterns in the UK, (2) hypothesis formulation for potential biological pathways linking to cardio-metabolic disease, (3) discovery of metabolite scores as potential dairy biomarkers and (4) hypothesis formulation for potential genetic predictors of dairy consumption.