Download Drivers of inequality (full report)

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When we published our report earlier this year on Measuring Wellbeing Inequalities across Britain, the hard part wasn’t convincing people about the value of wellbeing: it was explaining the potentially pivotal idea of wellbeing inequalities.

We say ‘potentially pivotal’ because looking at inequality of wellbeing is a new and emerging approach to understanding how people and communities are thriving or struggling. But while it’s  harder to find and understand what differences exist within and between populations, and what might drive such otherwise hidden variations, we think it could lead to some insightful findings.

This kind of data is already used widely when thinking about health and income inequalities. But can insight into differences in how people experience their lives, and why, inform how we can best use local resources? Wellbeing is potentially a better and more useful overarching measure then health or income alone, because it builds on both of these and adds other measures to create a more nuanced overall picture.

Why does looking at inequality in wellbeing matter? Because averages can hide the different experiences of those within and between populations. Average wellbeing can be high in an area, and mask people left behind in economic growth.

The Measuring Wellbeing report provided data on the levels of wellbeing inequality in local authorities across the UK and posed some questions about what factors influence this. The research also went some way to helping us understand what measures and conceptualisations of wellbeing inequality are most useful.

Drivers of wellbeing inequality report: key findings

Our new exploratory research paper in this series, unearthed some interesting insights for those working in local authorities, as well as important questions.

  1. Income particularly matters. Deprivation and lower median incomes are both associated with higher wellbeing inequality at local authority level. Unemployment is also associated with inequality in life satisfaction, though the effect is less consistent.
  2. Rural areas are likely to have an average higher wellbeing, but are also associated with higher wellbeing inequality. There was some evidence to suggest this could be due to the effects of unemployment. Findings such as this provides a space to question what is really happening in peoples’ lives in a particular local area, and what think through what support people who emerge as the ‘hidden unhappy’ in a given area may need. It also offers those working in the research community guidance on where future research may best enhance existing knowledge.
  3. The lower your wellbeing, the bigger the impact access to green space and heritage makes. Greater engagement in heritage activities and the use of green space for health or exercise is associated with lower inequality in life satisfaction in local authorities. This is despite the fact that increased engagement in these activities is not associated with improved average life satisfaction.  

While the report pulls out key findings at a national level, those working in local areas can learn much more by delving into the local data, using it alongside existing local measures and insight to triangulate data to inform decision-making.