Deprivation Scores on Plinth
What is a Deprivation Score?
The Deprivation Score shows how deprived an area is compared to other areas in England, based on official government data called the Index of Multiple Deprivation (IMD).
How the IMD works
The government divides England into roughly 33,000 small neighbourhoods called Lower-layer Super Output Areas (LSOAs), each containing around 1,500 people. Every neighbourhood is ranked from most to least deprived based on seven factors:
- Income – how many people are on low incomes
- Employment – how many people are out of work
- Education – skill levels and qualifications
- Health – rates of illness and disability
- Crime – levels of recorded crime
- Housing – barriers to housing and local services
- Living environment – quality of housing and outdoor environment
Data basis in Plinth
Reports use the English Indices of Multiple Deprivation (IMD 2019) at small-area level, aligned with 2011 LSOA boundaries — the same geography codes stored on participant records for reporting. The headline figure is the overall combined measure (not a single domain such as income or health on its own).
Reading the scores
The score runs from 0 to 100. Higher values indicate greater deprivation relative to other neighbourhoods in England — so a higher number means the area sits towards the more deprived end of the national distribution.
| Score | What it means |
|-------|---------------|
| 0–20 | Among the least deprived 20% of neighbourhoods |
| 40–60 | Around the middle of the distribution |
| 80–100 | Among the most deprived 20% of neighbourhoods |
A lower score (closer to 0) means less deprivation. A higher score (closer to 100) means greater deprivation.
Example
A score of 43 sits below the midpoint of the scale, so it indicates a neighbourhood that is less deprived than many areas in England, but not among the least deprived. A score in the 80s would sit towards the most deprived end of the range.
How we calculate scores for your reports
When we show deprivation data in your reports, we look at which neighbourhoods your participants come from and calculate a weighted average. Neighbourhoods where more of your activity is concentrated have more influence on the overall score, so the headline figure reflects the mix of areas your participants actually come from — not a simple headcount or an unweighted average.