The impact of data gaps on our understanding of obesity and its drivers in Wales: a visual essay
Nearly 1.6 million adults in Wales live with obesity or are overweight, and more children are obese by the time they start primary school in Wales than any other part of the UK.
Available statistics like these point to a problem, but recent Nesta research has identified gaps in data which prevent us from properly understanding and tackling obesity and its drivers in Wales.
The Covid pandemic highlighted the importance of reliable and transparent data. The data ecosystem that was established during the pandemic provided us with up-to-date information from multiple organisations on infections, hospitalisations, deaths, and vaccinations enabling us to respond effectively to the crisis.
Recent Nesta research has called for a similar approach to address the obesity crisis and its drivers in Wales. With good, reliable and transparent data, we would be better able to:
What happens when good data doesn’t exist? What do we miss when there are ‘data gaps’?
We don’t hear about data gaps often – they go unreported in the news due to the challenge of communicating non-existent figures.
But one way to understand their impact is through the headlines that can’t be written.
Via a series of missing statistics in fictional headlines, this visual essay demonstrates just some of the impact that data gaps have on our understanding of what is driving obesity in Wales and how it can be addressed.
Of course, an issue making the headlines doesn’t itself change policy. There are plenty of examples of good data being available, while action to tackle the issue is insufficient. But if data is unavailable in the first place, there is very little chance of positive change.
Data gaps, including those identified by this research, occur for a variety of reasons. But the consequences of not collecting and reporting data are significant: it inhibits our ability to identify areas where services are underperforming, track progress over time, and ultimately improve the wellbeing of individuals. It is also much more difficult to identify at-risk groups, target interventions to those most in need and understand what works best for different groups.
It is easy to start closing these data gaps – and we aren’t calling for a huge database or an up to the minute live dashboard. It is often smaller efforts like extending a survey to an older age group or encouraging local authorities to record the content of their free school meals. These small changes have the potential to make large impacts on our ability to understand obesity – and develop effective interventions.