GEOG3025 Multivariate neighbourhood indicators

GEOG3025 Multivariate neighbourhood indicators Lecture overview: Objectives of lecture Introductory questions Multivariate deprivation Deprivation indicators Calculation of indicators Lecture summary

GEOG3025 Objectives Understand the concept of multiple material deprivation Understand the principle of multivariate deprivation indicators Be able to calculate and interpret general-purpose indicators

GEOG3025 Introductory questions… What makes an area “deprived”? How might you measure social deprivation?

GEOG3025 Multiple deprivation Recognition that deprivation is a multifaceted phenomenon (Black Report, 1980) Particular focus on health care applications Measurement requires combination of multiple variables – multivariate indicators

GEOG3025 Research areas Material deprivation as cause of health inequality Deprivation and mortality Deprivation and educational achievement Use in resourcing public services (e.g. standard spending assessment)

GEOG3025 Deprivaton or exclusion? Multiple deprivation –Derived directly from census data –Derived from census and administrative data Social exclusion –Incorporating concepts of exclusion from normal activities of citizens e.g. consumption, savings, production, political social (Burchardt et al. 2002)

GEOG3025 Multivariate deprivation… Remoteness, elderly population? Photo: Dave Martin Poor transportation, unemployment, lone parents? Overcrowding, unskilled jobs?

GEOG3025 Census-based deprivation indicators Jarman –Deprviation payments to GPs 1980s, 90s Carstairs –Health-related, esp. Scotland Townsend –Health-based, widely used Department of the Environment

GEOG3025 Census deprivation index construction: issues Data source choice Variable choice To combine or not? To standardise or not? To transform or not? To weight or not?

GEOG3025 Two distributions… Number of areas Percentage Not owner occupied Unemployed

GEOG3025 Transform and/or standardise? Standardise:adjust for spread Transform: adjust for shape

GEOG3025 Example: Townsend score Input variables –No car –More than one person per room –Not owner occupied –Unemployed

GEOG3025 Townsend calculation Express variables as percentages Log transformation of unemployment and overcrowding values (+ 1) Z score standardisation of all variables Sum the standardised scores with equal weighting

GEOG3025 Townsend score for single area VariablePercentLogZ No car Overcr. Not own Unemp. Score

GEOG3025 Townsend score for single area VariablePercentLogScore No car17 Overcr.6 Not own45 Unemp.9

GEOG3025 Townsend score for single area VariablePercentLogZ No car17- Overcr Not own45- Unemp.91

GEOG3025 Townsend score for single area VariablePercentLogZ No car Overcr Not own Unemp.911.1

GEOG3025 Townsend score for single area VariablePercentLogZ No car Overcr Not own Unemp Score5.8

GEOG3025 Deprivation mapping Source: devon.gov.uk

GEOG3025 Non-census/hybrid indicators Index of local conditions Welsh Jarman Index of local deprivation Index of multiple deprivation Combining census and non-census variables: –House condition, income support, derelict land, low GCSE grades, house insurance weights, etc.

GEOG3025 IMD 2000 Index of multiple deprivation 6 ‘domains’: –Income –Employment –Health and disablity –Education, skills and training –Housing –Geographical access to services

GEOG3025 MAUP/ecological fallacy Levels of measured deprivation dependent on area boundaries Large areas can conceal small areas (‘pockets’ of deprivation) Area-level deprivation indicators will misrepresent many individuals and households within the areas

GEOG3025 Structural problems… Different regions have different deprivation structures Claims of London-bias may just represent population figures Urban-rural deprivation differences Welsh Jarman – additional variables

GEOG3025 Assignment Select variable set and study region CASWEB retrieval (including denominators) Run Geodep spreadsheet Import dataset Define denominators Design indicator Run/re-run Interpret scores

GEOG3025 Lecture summary Problems with specification and design Data limitations – especially early versions Particularly relevant to general-purpose indicators Best to use purpose-specific indicators Key review reference: Senior (2002) in Census Data System