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The lower the score, the more deprived the area
This area is policed by Hertfordshire Constabulary.
Hertfordshire Constabulary split their policing area into 33 separate neighbourhoods and this area is in the St Albans Central, North and West neighbourhood.More Details
|Oct 2021||Sep 2021|
This postcode is in the St Albans parliamentary constituency.
St Albans is a constituency in the East of England region of England. The seat has been held by Daisy Cooper (Liberal Democrat) since December 2019.
|21 SANDPIT LANE
20 Aug 2010 £510,000
The Rural/Urban classification is based upon data collected during the 2011 Census and released in August 2013 and is categorised into 6 distinct classes.
[A] Urban Major conurbation: A built up area with a population of 10,000 (3,000 in Scotland) or more and is assigned to the major conurbation settlement category.
[B] Urban Minor conurbation: A built up area with a population of 10,000 (3,000 in Scotland) or more and is assigned to the minor conurbation settlement category.
[C] Urban City and town: A built up area with a population of 10,000 (3,000 in Scotland) or more and is assigned to the city and town settlement category.
[D] Rural Town and fringe
[E] Rural Village
[F] Rural Hamlet and isolated dwelling
The Index of Multiple Deprivation (IMD) is the official measure of relative deprivation.
The index is based on 39 separate indicators across seven distinct domains (Income; Employment; Health and Disability; Education, Skills and Training; Crime; Barriers to Housing and Services; Living Environment) to provide an overall measure of multiple deprivation and is calculated for every neighbourhood.
The index is relative rather than an absolute scale and so a neighbourhood with a score of 10 is more deprived than one rated 20, but this does not equate to being twice as deprived.
Please note: Different indices are used in England, Scotland, Wales and Northern Ireland and so comparison of scores from neighbourhoods in different countries should not be undertaken.
The population figure shown for your area are an estimate provided by the Office for National Statistics and is rounded to the nearest 1,000.
The estimates are dereived from the Annual Population Survey (APS) which is the Labour Force Survey (LFS) plus various sample boosts.
The Labour Force Survey (LFS) is a household survey of people in the UK. It includes those deemed resident at private addresses, so covers students in halls of residence with parents resident in the UK. However, it does not cover most communal establishments. Its purpose is to provide information on the UK labour market but it includes data on a variety of other variables such as country of birth and nationality.
The Annual Population Survey (APS) combines results from the LFS and the English, Welsh and Scottish Labour Force Survey boosts. These boosts increase the size of the sample.
Each quarter’s LFS sample of 40,000 households is made up from five “waves”, each of approximately 8,000 households. Each wave is interviewed in five successive quarters, such that in any one quarter, one wave will be receiving their first interview, one wave their second and so on, with one wave receiving their fifth and final interview. Thus there is an 80 per cent overlap in the samples for each successive quarter and the sample is completely different after six quarters.
In some areas of the UK the boost makes up the bulk of the APS dataset, with a smaller contribution from the main LFS. The boost has a four year wave structure instead of the five quarter wave structure in the main LFS; after the initial interview, sampled households are interviewed three more times on an annual basis. Therefore the boost for these areas may be slower to react to a change in migration patterns than the main LFS and the speed with which the APS sample responds to changes in the household population may vary across the UK.
More robust estimates are available by using the APS than from the main LFS. APS datasets are produced quarterly with each dataset containing 12 months of data. There are approximately 300,000 persons per dataset.