Posted on: 14 November 2024

Deprivation is often associated with a wide range of health and social issues within the communities it impacts.

Whether it’s the increased incidence of certain medical conditions, or higher crime and anti-social behaviour rates, understanding how issues interact with and are caused by deprivation is an important component in developing policy led solutions.

For this reason, data on the geographical patterns of deprivation is exceptionally useful for cross referencing with and analysing data on other issues.

Within the UK, each country independently collects and publishes its own deprivation index. In this blog we’ll take a closer look at them and provide some practical applications for use.

 

England: Indices of Multiple Deprivation

Government departments have been measuring deprivation in England since the 1970s. The latest Indices of Multiple Deprivation were published in 2019, and are due to be updated next year.

Deprivation is measured at Lower Super Output Area level (32,844 small neighbourhoods of between 1,000 and 3,000 people), from where it can be aggregated at larger boundary sizes such as local authorities and parliamentary constituencies.

Deprivation scores are calculated across seven domains of deprivation, using 39 separate indicators. The domains of deprivation are as follows:

  • Income (22.5%)
  • Employment (22.5%)
  • Health Deprivation and Disability (13.5%)
  • Education, Skills Training (13.5%)
  • Crime (9.3%)
  • Barriers to Housing and Services (9.3%)
  • Living Environment (9.3%)

For each deprivation domain, areas are split into deciles according to their score and ranked from 1 to 10 where 1 is the most deprived decile and 10 the least. The scores are also compiled to give an overall IMD rank.

It is important to note that there is no definitive threshold below which an area can be described as deprived. The rankings enable ‘relative’ deprivation to be evaluated, and also provide consistency for analysing change over time e.g. since the previous IMD ranks were calculated in 2015.

As of 2019, the local authorities containing the highest proportion of neighbourhoods in the most deprived 10 per cent of neighbourhoods nationally are as follows: 

  1. Middlesbrough (48.8% of LSOAs in most deprived 10%)
  2. Liverpool (48.7%)
  3. Knowsley (46.9%)
  4. Kingston-upon-Hull (45.2%)
  5. Manchester (43.3%)

The results of the English Deprivation Measures 2019 can be found here

 

Scottish Index of Multiple Deprivation

The Scottish Index of Multiple Deprivation operates across 6,976 areas in Scotland called data zones. 

Each data zone contains 700-800 people, compared to 1,500 in England.

Last published in 2020, one year after the English data, the SIMD similarly uses seven domains of deprivation to rank each area, but they differ slightly from England. They are:

  • Income
  • Employment
  • Education
  • Health
  • Access to services
  • Crime
  • Housing

In Scotland, the five local authorities with the largest share of the most deprived 20% of areas are:

  • Inverclyde (45%)
  • Glasgow City (44%)
  • North Ayrshire (40%)
  • West Dunbartonshire (40%)
  • Dundee City (38%)

The results of the Scottish Deprivation Measures 2020 can be found here

 

Welsh Index of Multiple Deprivation

The Welsh Index of Multiple Deprivation is measured, like England, across LSOAs – 1,909 areas with an average population of 1,600.

It utilises 8 domains, calculated using 47 underlying indicators. The domains are:

  • Income (22%)
  • Employment (22%)
  • Health (15%)
  • Education (14%) 
  • Access to Services (10%)
  • Housing (7%)
  • Community Safety (5%)
  • Physical Environment (5%)

A number of new indicators were added for the 2019 interaction over the previous 2015 IMD rankings, so comparisons over time need to be treated with caution.

In Wales the local authorities with the highest proportion of LSOA’s in the most deprived 10% were as follows:

  • Newport (24.2%)
  • Methryr Tydfil (22.2%)
  • Cardiff (18.2%)
  • Rhondda Cynon Taf (17.5%)
  • Neath  Port Talbot (15.4%)

The results of the Welsh Deprivation Measures 2019 can be found here

 

Northern Ireland Deprivation Measure

Published in 2017, the Northern Ireland Multiple Deprivation Measure is the oldest among the four nations. 

It ranks 890 super output areas across seven domains of deprivation. These are:

  • Income (25%)
  • Employment (25%)
  • Health and Disability (15%)
  • Education, Skills and Training (15%)
  • Access to Services (10%)
  • Living Environment (5%)
  • Crime and Disorder (5%)

Of the 100 most deprived super output areas in Northern, half are in Belfast. The local authorities with highest number of SOAs in the 100 most deprived areas are as follows:

  • Belfast (50)
  • Derry City and Strabane (20)
  • Armagh City, Banbridge and Craigavon (8)
  • Newry, Mourne and Down (8)
  • Ards and North Down (3)
  • Causeway Coast and Glens (3)
  • Mid and East Antrim (3)

The results of the Northern Ireland Deprivation Measures 2017 can be found here

 

What this data can be used for

Deprivation data is made available by the statistical agencies in the respective UK countries under an open government licence. This means it’s free to use as part of other data projects and research so long as it’s accurately cited.

In the first instance, the data can simply be used to add some additional context about an area. For example, within Polimapper deprivation data can be added to any constituency or local authority profile as an additional data point.

However, the real value is derived from analysing the existence of potential links between deprivation and other datasets.

As an example, we could take data on the prevalence of a health condition across the UK and try to understand whether there is a correlation between the incidence of it and either the overall deprivation score, or the individual domains of deprivation.

From a commercial angle, we could look at the contribution of a business or industry to supporting jobs in an area of deprivation, or help a business to understand the backgrounds of its employees and what kinds of help and support it could provide to its workforce.

Such analyses can be carried out using statistical software such as R and SPSS, and then visualised using Polimapper to understand where and how the issues interact with on the ground.

 

Working with deprivation data

As you may gather from the differences outlined above, the first rule of working with deprivation data is that the measures of deprivation in each UK country are different and are therefore not directly comparable.

Therefore for any analysis of how deprivation correlates with other other data points must be carried out on a country-by-country basis.

There are other general rules for using the data such as, they cannot be used for identifying deprived individuals or groups of people as they provide area based values.

Equally they cannot be used to measure affluence, as lower relative deprivation does not denote affluence. They cannot be used to quantify the deprivation of an area, or the extent to which one area is more deprived than another. They also cannot assess how deprivation in an area has changed over time.

However, they are an extremely useful barometer for showing which small geographical areas are the most or least deprived, and how these are distributed spatially. While direct comparisons on deprivation in an area cannot be made, the indices can be used to show the change in relative position of an area over time. 

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Overall the respective deprivation measures provide a useful publicly available resource for studying links between deprivation and other spatial datasets.

If reading this has piqued your interest and you want to find out more about how you own proprietary datasets or other publicly available datasets can be analysed alongside deprivation data, feel free to drop us a message here.