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Using Census data to derive a new area-based measure of deprivation - Section 6: Indices of Deprivation

Section 6: How does our measure compare to the Indices of Deprivation?

For our measure to be valuable and useful to end users, it should also ideally be able to overcome some of the known limitations of the Indices of Deprivation. The aim of this section is to therefore explore whether this is the case across the various nations of the UK.

As we have income estimates at the MSOA level in England, one of our first lines of analysis in this country was to look at the average net equivalised weekly household income (after accounting for housing costs) of those living in areas that fall into the bottom quintile of the English Index of Multiple Deprivation (IMD). The median value was found to be £350, which is only slightly lower than the figure one obtains if they consider the lowest quintile of SEISA when applied in England only (£360). Here, SEISA is formulated by splitting English output areas only into five equal quintiles (hence the output/small areas of all other nations were excluded when creating this categorical variable). Similar averages were also found if focus was placed on particular domains of IMD, such as income and education, as well as for IDACI.

34,274 output areas were located within the bottom quintile of SEISA when applied to England only, with 12,063 of these not being found in the corresponding quintile of IMD – representing just over a third of the total. When looking at where those output areas only found in the bottom quintile of our composite measure were located (and hence were situated within a higher quintile of IMD), we observed that almost 30% were in central England, with just over a quarter found in East of England or Yorkshire and The Humber.

Furthermore, when examining the types of areas that the bottom quintile of IMD tends to capture, only 3% are classified as rural areas. Rather, IMD appears particularly effective in catching localities in major urban areas, such as London and Birmingham. Indeed, one of the key differences we find is that 12% of output areas within the bottom quintile of IMD are in London, with the equivalent figure being 3% for SEISA. In contrast, 7% of areas in the lowest quintile of our measure are rural locations, with our measure tending to pick up a greater proportion of medium and large towns in England. Table 4 illustrates the urban/rural classification of the output areas that fall into the bottom quintile of IMD/SEISA.

Table 4: Urban/Rural classification of areas that fall into the bottom quintile of IMD and SEISA (when applied to England only)

Urban/rural classification IMD (%) SEISA (%)
Rural hamlets and isolated dwellings 0.3 0.3
Rural hamlets and isolated dwellings in a sparse setting 0.0 0.0
Rural town and fringe  2.4 5.6
Rural town and fringe in a sparse setting 0.1 0.4
Rural village 0.3 1.0
Rural village in a sparse setting 0.0 0.1
Urban city and town in a sparse setting 0.2 0.4
Urban city and town   40.5 48.7
Urban major conurbation  49.7 36.4
Urban minor conurbation 6.4 7.1
Total number of output areas 34,229 34,274

When assessing how our measure compared to some of the individual domains of IMD/IDACI, we found that similar overall conclusions were reached when considering IDACI, as well as the income and employment domains. That is, around one-third to two-fifths of output areas in the bottom quintile of our measure did not appear in the equivalent quintile of these variables. Typically, IDACI and these components of IMD were again found to be picking up predominantly major urban conurbations and very few rural areas. The indicator that showed greatest similarity with our own measure with regards to the urban/rural distribution was the education domain. However, even in this instance, approximately 30% of the output areas that emerged in the bottom quintile of our measure were located in a higher quintile of the education domain, with these localities typically found in northern and central England.

In Scotland, modelled estimates of income and poverty relating to the period 2008/09 have been published by the Scottish Government (2014). We utilise the weekly net equivalent household income after housing costs below to assist us in contextualising our findings. Please note that these estimates could not be directly incorporated into our dataset as the geography codes utilised are based on the 2001 Census. As has been highlighted in statistics released on SIMD, not all council areas are covered in the bottom quintile of this index, despite these areas being known to have deprivation. For example, Na h-Eileanan Siar is a place that does not feature in the bottom quintile of SIMD, despite Scottish Government (2014) estimates indicating that it has a median weekly income of £334, which is below the national average of £349. Applying SEISA in Scotland only (so that each Scottish SEISA quintile contains the same number of Scottish output areas), we find that 3,629 of the 9,270 Scottish output areas that fall within the bottom quintile of our composite measure are located in a higher quintile of SIMD, which represents almost 40% of the total. One of the key differences between our measure and SIMD is that all council areas of Scotland are covered through the bottom quintile of our index.

As we pointed out earlier, one of the main criticisms of SIMD is its inability to capture more rural parts of the country. Table 5 demonstrates that only 3% of areas in the bottom quintile of SIMD are listed as rural areas. In contrast, of the localities in the lowest 20% of our measure, 7% are categorised as accessible/remote rural vicinities.

Even if one were to compare our measure with the income, employment and education domains of SIMD, the overall conclusions we report here do not change. That is, around 40% of output areas that are in the bottom quintile of our measure are in a higher quintile of the SIMD domain being considered, with our measure able to capture a larger proportion of rural areas.

Table 5: Urban/Rural classification of areas that fall into the bottom quintile of SIMD and SEISA (when applied to Scotland only)

Urban/rural classification SIMD (%) SEISA (%)
Large urban areas 52.5 39.8
Other urban areas 37.6 41.9
Accessible small towns 5.2 8.5
Remote small towns 1.6 2.7
Accessible rural 2.2 5.1
Remote rural 1.0 2.0
Total number of output areas 10,025 9,270

A similar approach to that taken for England was applied for our analysis in Wales. That is, we began by utilising the MSOA income estimates to understand how the net weekly household income levels (equivalised and after housing costs) compared between the bottom quintile of our composite measure (when applied to Welsh output areas only) and WIMD. We found the median value for WIMD to be £330, with an equivalent estimate emerging if one were to concentrate on the income, employment or education domains of WIMD. The same median figure was found for SEISA when applied to Wales only.

2,007 output areas fall into the bottom quintile of our composite measure, with 763 (38%) of these being based in a higher quintile of WIMD. While these 763 output areas are spread across all parts of Wales, we do find that almost a quarter of these are found in two local authorities in south Wales (Rhondda and Caerphilly).

As in the other nations assessed so far, we find that the bottom quintile of our composite measure comprises of a larger proportion of rural areas than WIMD. One-fifth of areas in the bottom quintile of our measure are categorised as rural compared with approximately 14% for WIMD. Table 6 illustrates this. Similar findings emerge for Wales if we were to compare our measure with the income, employment or education domains of WIMD.

Table 6: Urban/Rural classification of areas that fall into the bottom quintile of WIMD and SEISA (when applied to Wales only)

Urban/rural classification WIMD (%) SEISA (%)
Rural hamlets and isolated dwellings 0.4 0.3
Rural hamlets and isolated dwellings in a sparse setting 0.1 0.1
Rural town and fringe  11.8 15.4
Rural town and fringe in a sparse setting 1.0 2.4
Rural village 0.6 1.5
Rural village in a sparse setting 0.1 0.7
Urban city and town in a sparse setting 2.2 1.8
Urban city and town   84.0 77.9
Urban major conurbation 0.0 0.0
Urban minor conurbation 0.0 0.0
Total number of output areas 1,988 2,007

Within Northern Ireland, 907 small areas fall into the bottom quintile of our composite measure (when applied in Northern Ireland only), with nearly 42% (380) of these localities found in a higher quintile of NIMDM. Those places that emerge in the bottom quintile of our measure only are generally found in north and/or eastern parts of Northern Ireland (e.g. Belfast, Mid and East Antrim, Antrim and Newtownabbey, as well as Armagh City, Banbridge and Craigavon).

Table 7 highlights the urban/rural classification of areas that fall into the bottom quintile of our measure and the equivalent figures for NIMDM. In contrast to what we observe in other nations, we do not see a great deal of difference by urban/rural classification. 85% of output areas in the bottom quintile of our measure are classified as urban, with the figure being marginally lower (84%) for the lowest 20% of areas according to NIMDM. So far, when we have extended our work to include comparisons between individual domains and our measure, the conclusions we have drawn have not been altered. In Northern Ireland, however, an assessment of our measure against the income or IDAC domains does lead to different results to what we see for the overall index. In particular, around 30% of output areas in the bottom quintile of either domain are classified as rural, which bucks the general trend we have seen across nations (i.e. that our measure captures a greater proportion of rural spots).

Table 7: Urban/Rural classification of areas that fall into the bottom quintile of NIMDM and SEISA (when applied to Northern Ireland only)

Urban/rural classification NIMDM (%) SEISA (%)
Mixed urban/rural 2.6 3.5
Rural 13.2 11.5
Urban 84.2 85.0
Total number of small areas 930 907

Next: Section 7: Discussion and concluding remarks

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Tej Nathwani

Tej Nathwani

Principal Researcher (Economist)
Siobhan Donnelly

Siobhan Donnelly

Lead Statistical Analyst

 

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