Measuring Disadvantage in Rural Populations - Amanda Burke - University of East Anglia

1. Measuring rural disadvantage: A Norfolk case study Amanda Burke, Andy Jones Norwich Medical School University of East Anglia 6th December 2018

2. Why? The issue: Rural areas may be under-represented in multiple deprivation indices because: • rural deprivation may occur in very small pockets and • the characteristics of rural and urban deprivation differ The task:Develop an index of rural deprivation (RDI), using Norfolk as a case study, with an emphasis on health.

3. Norfolk

4. Can we use or re-weight the IMD? Low ranks = higher ‘deprivation

5. What’s in these two domains?

6. First steps in provisional RDI • Some IMD domains generally apply to urban and rural areas; they are highly correlated to each other e.g. income and employment. Let’s group these as ‘relative household deprivation’. • Let’s create another group of indicators very specific to our area of interest – rurality. We have two dimensions for measuring rural deprivation. Relative household deprivation Locality related deprivation (Rurality)

7. What else? The IMD measures relative deprivation. Sometimes this equates to prevalence, sometimes not! • Example: IMD ‘Older people income deprived’, some LSOAs in Norfolk highly deprived on this measure have very few older people income deprived. • Example: Health measures are age-standardised. An LSOA with an older population may be ‘less health deprived’ than one with a younger population, but have more people with health problems. Rural populations in Norfolk are older. Include a further dimension for population Population characteristics

8. What about the ’pockets’? What about the potential issue of small pockets of deprivation in rural areas? We created a simple measure (variability index) for assessing the heterogeneity of deprivation within LSOAs. This is the range of scores for self-reported poor health in an LSOA using Census ‘OAs’. We included as a final possible dimension of rural deprivation in our provisional RDI Spatial scale

9. Indicators Relative deprivation IMD 2015 domains: Income, Employment, Education and Health and disability Locality related deprivation Average time to travel to eight essential services, IMD2015: Housing in poor condition Population ONS 2015 mid-year population estimates 75+ Spatial Scale Variability index

10. Testing • Using Principal component analysis (PCA), it was not clear whether, ‘spatial scale’ was a distinct, separate dimension of rural deprivation. We removed it. • We tested various weightings of the three remaining dimensions of the RDI against six comparison variables (one local). We selected the version best correlated with these which ALSO resulted in at least one additional ‘Rural village and dispersed’ LSOA in the most deprived quintile

11. IMD: LSOAs in Norfolk

12. RDI – LSOAs in Norfolk

13. Take homes • The RDI provides a structure to group discrete sets of correlated variables representing different dimensions of deprivation and to weight them. It could be used for different purposes e.g. urban deprivation. • The variability indicator developed for this research may provide a simple tool for identifying heterogeneity of deprivation. • Rural town and fringe have most heterogeneity of health deprivation, and show most change in most deprived quintile compared to the IMD. • With all indices, there is a level of subjectively and there is no ‘gold-standard’ comparison.

14. Thank you Mandy Burke A.Burke@uea.ac.uk