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This page explains how deprivation scores are estimated at postcode district level, and what to keep in mind when using them.
The Index of Multiple Deprivation, usually shortened to IMD, is the main measure of relative deprivation in England. It combines information across seven domains, including income, employment, health, education, crime, housing and the local environment.
IMD is calculated for small geographic areas called Lower-layer Super Output Areas, or LSOAs. Each LSOA covers around 1,500 people and is designed to be broadly similar in population size.
There is no official IMD score for postcode districts. Any district-level figure is therefore an estimate based on aggregating LSOA data.
Postcode districts are familiar and easy to recognise, but they do not align neatly with LSOA boundaries. A single district often contains many LSOAs, each with very different levels of deprivation.
To provide a useful district-level view, IMD scores must be combined in a way that reflects the people living in each area, rather than simply averaging scores.
For each postcode district, all LSOAs that fall within that district are identified. Each LSOA’s IMD score is then weighted by its population.
In simple terms, the calculation follows these steps:
This produces a single IMD score for each postcode district that reflects the average deprivation experienced by people living there.
Once district-level scores have been calculated, postcode districts are ranked relative to one another and grouped into ten equal-sized bands, known as deciles.
A district decile of 1 indicates that the district sits among the most deprived tenth of postcode districts, while a decile of 10 indicates the least deprived tenth.
These are district-level deciles. They are not the same as official IMD deciles published for LSOAs.
Aggregated deprivation measures should be used with care. Key limitations include:
Where detailed targeting or funding decisions are required, LSOA-level analysis should always be preferred.
Postcode district IMD is best used as a high-level, exploratory tool. It works well for understanding broad patterns, supporting communication, and identifying areas for further investigation.
Good practice includes being clear that these values are estimates, combining them with local knowledge, and avoiding language that labels or stereotypes communities.