Unlocking meaning from private data… Visualising lifestyles that lead to poor coronary health
March 15, 2012
Having recently completed some work for the NHS (more on that soon), we’re on a bit of a health kick here at BD. Today I decided to use the TGI, our people classification P2 and some work we did with the NWPHO to try and visualise the link between healthy eating and heart disease.
Consider the below maps. They show the frequency of people that eat pizza more than once per week, the number of people that think eating their ‘five-a-day’ is very important and the density of lifestyles likely to lead to coronary disease.
Note: The darker the red, the higher the reading / frequency. The maps display anonymised and aggregated data and not real cases.
- Map A – People that believe in eating fruit and veg 5 times a day
- Map B – Lifestyles that may lead to coronary disease
- Map C – People that eat pizza more than once a week.
It’s not hard to see that maps B and C show a similar pattern.
The conclusion that people who eat pizza frequently are more prone to heart disease is no surprise nor is the conclusion that people who get their ‘five-a-day’ are likely to have healthier hearts.
What is interesting is that a source of data which is rightly very private has been compared with another data set. As this is modelled data, it is important to note that it does not reveal any individual patient records.
My question is: Is this a useful technique?
These are no surprises. We have made the hole and dug up what was expected but we have joined very private health data with another dataset. Should we keep digging?
Posted by Geoff Beacon, Chairman at Beacon Dodsworth
 As described in An inverse correlation between coronary disease and skin cancer.