Data geeks have been blessed this autumn with a new iteration of the Government’s Indices of Deprivation, last updated in 2019. The Indices of Multiple Deprivation is the combined measure pooling a range of weighted domains to produce a ranked list of English neighbourhoods. It’s familiar to many as a guide to relative deprivation at a pretty granular level – each ‘neighbourhood’ or Lower Super Output Area (LSOA) has between 1,000 and 16,00 residents. Very useful for informing planning for services, strategy, fundraising, etc. Even more so if you drill down into the individual domains and sub-domains, to explore the specific indicators around education, health, skills, employment, etc.
Here’s the overall heat map for Devon (the darker the area, the more deprived):
Things look a little different if we consider the domains that are known to be more challenging in rural areas:
It’s been recognised increasingly over the past few years that the Indices of Deprivation (IoD) methodology has within it some inadvertent urban bias, which can make some aspects of rural deprivation harder to see. There are several reasons for this, all of which are exhaustively rehearsed in the 111 pages of the Ministry of Housing, Communities and Local Government’s second gift to us, Deprivation in Rural Areas: A Supplementary Report. The report includes a comprehensive literature review, which is an excellent guide to our current understanding of rural disadvantage. Informed by this, it addresses each challenge to the IoD method in turn, and either explains what this new iteration of the Indices has done to address it, or explains why that was not possible. It ain’t flashy, it certainly ain’t pretty, but it’s really good, systematic and detailed work, that significantly aids understanding and transparency around this data. Yes, I’ve read it all.
One recognised limitation is that LSOAs in rural areas tend to be larger geographical areas, owing to more dispersed populations in the countryside, and therefore more frequently encompass both more and less deprived areas. Deprivation in the countryside anyway tends to be less concentrated, with more and less deprived residents closely intermingled. This does not show up well on heat maps. A relatively even balance of more and less deprivation in a neighbourhood comes out as, well, average. So it’s not a surprise that rural LSOAs tend to be better represented in the middle deciles, as this chart shows:
There is not an easy fix for this problem. As the report explains, drilling down to even smaller population units (they are called output areas) introduces challenges with the statistical data, and might still not be a small enough unit to accommodate nuances of rural ‘nested poverty’. So this one we have to live with.
Another set of challenges are around the range of indicators chosen to inform each domain (and sub-domain), and the relative weight given to each domain. These have to be applicable across the whole country, to enable the ranking exercise, so ideally they would work equally well for rural and urban contexts.
But this is not always the case. Commentators have pointed out the ‘rural premium’, with transport challenges and lack of choice, among other factors, means affordability measures are skewed in rural cases, while housing costs can often be relatively high compared with wages. It has also been noted that seasonal employment, and relatively low take-up of welfare benefits were not well accommodated. As we saw with the Devon heat maps above, rural areas tend to score poorly on the domains associated with access to services, and indoor living environment. As we know, many people in rural areas are further from essential services, and rural housing tends to be older, and harder to heat, especially for those off the gas main.
Not all of these issues are easily resolvable owing to the limitations of the data. And some are reflected within other measures, so don’t necessarily need a dedicated indicator. But several others have been improved in the 2025 iteration: income deprivation is now considered after housing costs, ‘making the measure more reflective of real disposable income’. Access to services, previously measured solely on road distances to key services, is now accommodated by the Department for Transport’s Connectivity Tool, a composite measure that drills down into travel for a range of purposes, and at different times of day, and takes full account of the challenges for residents without access to a car. Similarly, the Living Environment domain now includes a housing quality measure, based on data from Environmental Performance Certificates.
The report rightly emphasises that no aspects of deprivation are exclusively urban, or exclusively rural. It also notes that, although very few rural LSOAs feature in the most deprived decile overall (only 1% of rural areas, compared with 11% of urban ones), this does not mean there are not significant numbers of people living in deprivation in rural areas, as this table shows.
If you want to get a general picture of levels of deprivation in rural contexts, it’s important not to consider only the most deprived end of the scale. Over ten percent of those identified as experiencing income deprivation lived in rural areas, while only 1.1% of areas in the most deprived decile are rural.
As any countryside-dweller will tell you, there are degrees of rural. Nationally, the majority of the most deprived rural areas were found within the ‘larger rural: nearer to a major town or city’ classification, rather than more remote or dispersed settlements.
This is especially pertinent for Devon, which, outside Exeter, Plymouth and Torbay, is a county characterised by its small market towns, with their relatively less deprived rural hinterlands. The IoD team began an interesting piece of analysis disaggregating rural Built Up Areas, and identifying the most deprived as being former mining towns, or Eastern coastal communities. It is a helpful reminder that a binary rural/urban understanding is unlikely to be helpful. Frustratingly, the relevant data is not helpfully organised for regional analysis, but it would definitely be worth doing.
The literature, and our experience as a community foundation in a largely rural county, points to rural deprivation being qualitatively different in several senses from urban experience (and to deprivation in different kinds of rural areas being similarly diverse). If this is the case, then a national measure that aims for uniformity and comparability across the whole country, will likely never be perfect fit for either context. The changes made to this iteration of the IoD have responded thoughtfully to the challenges, within the constraints of the model. And where more research is needed, that’s been flagged.
What’s more important for me is the attention that this very careful look under the bonnet draws to the nuances of understanding place-based deprivation. We should never (but in practice almost always) take data at face value. The review of rural representation in the IoD might sound impossibly esoteric (and, yes, geeky). But it guides us in where we might look locally for a better granular understanding of the challenges our rural communities face. Locally generated insight is essential for fleshing out these universal metrics and filling in the gaps where national data will never go. This is the role of the Devon Community Foundation Insight team. Taken together, these two elements give us a powerful tool for informing place-based social and economic action. Which is why, foibles notwithstanding, I’m still an IoD fangirl.
Nicola Frost is Head of Impact, Insight and Learning at Devon Community Foundation
