They recorded details of body mass index, family history, physical activity, high blood pressure, high cholesterol, and diabetes were recorded. They then matched the data against healthy individuals as a scientific control.

Rather then using conventional methods for analysing statistics, the researchers borrowed an approach from the computer science field of artificial intelligence, OLAP. Online analytical processing was developed in the early 1990s and was exploited primarily in industrial and commercial applications, for financial and marketing analysis.
Fundamentally, OLAP provides a multidimensional view of data that allows patterns to be discerned in even the largest datasets that remain invisible even to the most expert user of spreadsheets. In a standard model, sales, purchases, pricing, customer base, and other economic measurements are used, Kostakis' colleagues at the University of Patras have adapted this system instead to accommodate the risk factors of heart disease.

I like the visual representation of data, far more use than tabular form