In recent years, increasingly efficient molecular biology techniques created new opportunities to harness large-scale repositories of biological material collected in epidemiological studies; however, methods to manipulate and analyse the wealth of information thus generated have lagged behind. The introductory chapter of this thesis presents the multifaceted field of 'computational epidemiology' from the perspectives of molecular biology, measurement theory, and statistical modelling. Focusing on measurement of DNA methylation levels, the author also reviews the state of the art, proposes novel pre-processing methods and evaluation frameworks, and provides recommendations for genome-wide studies of DNA methylation levels using Illumina Infinium® HumanMethylation450 BeadChips. The remaining chapters, in the form of three self-contained scientific articles, cover applications on the following topics: (i) DNA methylation differences associated with internal migration patterns within Italy; (ii) associations of DNA methylation profiles with adiposity measures, targeted gene expression, biomarkers of lipid and glucose metabolism, and risk of developing three obesity-associated diseases; (iii) associations of a dietary score with blood pressure, and with urinary metabolites as characterised by NMR spectroscopy. The thesis is concluded with general remarks and the presentation of some open problems that offer potential for future research.