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The Census Area Statistics
Myles Gould
Understanding area-level inequality & change
Presentation Content
Nature of Census & CAS data Data Tools Research Uses Analysis Issues Examples: Health Variations
– CAS, SARS & combining with other data
Nature
What is the Census? Cross-sectional snapshot of population on
single date Source of secondary data Can be examined at many geographical
levels Total (nearly!) enumeration (count) &
coverage of national population Coverage is consistent (all households asked
same questions)
Source: Press Association
What is the CHCC?
Collection of Historical & Contemporary Censuses
Census Area StatisticsSample of
Anonymised Records (SARs)• aggregated to zones
• 1971, 1981, 1991, 2001 • representative sample of individuals• 1991 and 2001
Historical Censuses Collection• 1851 & 1881
All datasets are available in UK HE & FE sectors
Census Statistics A range of products are available
Source: Rees et al (2002)
CAS Complex data structure Data aggregated for different geographical units 1991 LBS contain 99 tables for GB, & approx.
20,000 statistical count A relatively simple table…
Census Geography Rich source of local statistics for a range of
hierarchical geographical units
Source: adapted from Martin (1991)
1991 Eng & Wales
2001
2001Outputs
Headcounts: counts males, females, households for unit postcodes upwards (eg LS2 9JT)
Profiles: counts & %s for OAs upwards, but confidentiality protected
Key statistics: 50 variables, mainly %s for OAs upwards, LA data already available
CAS: 7000 counts in cross-tabulations for OAs upwards:
Standard tables: 25,000 counts in more detailed tables for Wards/LAs
Tools
Casweb
Available at http://census.ac.uk/casweb/
CommonGIS
Uses & Examples
Research Uses Describing demographic & socio-economic profiles
of areas– EDA & mapping
Selecting & identifying areas for further study Exploring patterns &/or relationships for
variables/processes– typically generalized linear modelling
Looking at change over time Using as a denominator for calculating other
statistics Combining with other secondary data sources in
multivariate analysis Identifying & classifying areas with similar
characteristics– factor/cluster analysis, composite deprivation indices
Census change over time atlas CommonGIS also used to visualise change over time
Analysis Issues Ecological fallacy MAUP scale aggregation problem &
different results Confounders & ecological analyses Decennial snapshot & out of date quickly Need for standardisation & understanding
underlying composition Dealing with unstable population
denominators (shrunken estimates) Cross-tabulations of a small number of
variables in any one CAS table
Some Research Questions Are there variations between different types of people? Are there variations between places? Are there absolute or relative differences? How does place matter? Is it composition (who’s in a
place) or context that matters? Are variations explained solely by poverty? Do variations vary over time? Is there a widening gap?
Are variations becoming more polarized Are there groups & places we should target with policy
responses? What aspects of place matter?
Health Variations
NB not all these questions can be answered with census data
Health Variations
LTLIHealth
GoodHealth
Fair
30
20
10
Per
cent
age
English Local Authorities, 2001Variations in self-reported heath, amongst
Source: 2001 Census Area Statistics, Crown Copright
Kensington & Chelsea
Easington
Easington
Barnsley
Health Variations
combi.30-5950-5940-4930-39
50
40
30
20
10
0
Per
cent
age
amongst English Local Authorities, 2001Variations in self-reported heath by age,
Source: 2001 Census Area Statistics, Crown Copright
Age category
Liverpool
Easington
EasingtonTow er HamletsManchesterLiverpool
Liverpool
Easington
Easington
Know sleyLiverpool, ManchesterTow er Hamlets
Local Health Variations
Gould & Jones (1996) - Self-reported
Limiting Long-Term Illness Analysis National & sub-regional comparisons Consider compositional vs context debate 2% Individual SARs Use multilevel analysis
– Individual & area variations at same time
419,550 individuals, 42,073 reported illness 278 SAR Areas - combinations of Local
Authority districts (protecting confidentiality of individuals)
Health Variations
Health Variations
Results Marked relationship illness & age but differences between the sexes are not
particularly marked until the older age group there is a 'multiplicative' relationship so that the
worst health of all is experienced by partly skilled/unskilled, local-authority rent, with no car
geographical variation remain after allowing for individual characteristics – area composition (who lives in a place)
Place does make some difference
Health Variations
Health VariationsHealth & Deprivation: Exploratory Survival Analysis Jones, Gould & Duncan (2000) Combine HALS & Census CAS
Health Variations
Results Deprivation little effects on mortality when
in wards where deprivation <0 (mean)– little difference between social classes
in areas of relative affluence Marked differences between classes in
areas of increasing deprivation
Further work SARs, LTLI & Cambridge scores New unpublished work with Kelvyn Jones Looking at absolute & relative variations in morbidity
and social advantage Model interaction quartile Cambridge scores
(individuals), with area means, & with area Gini coefficients
Health Variations
Further work SARs, LTLI & Cambridge scores Min 2.13 ≈driver mate; Ql= 19 ≈security officer Md=36 ≈stores controller Qu=46 ≈ Farmers; Max=94 ≈ General Medical
Practitioner In areas with more equality, individual class effects are
small
Q1Q2
Q1
Q2Q3
Q3Q4 Q4
Low status
High status
Q1Q2
Q1
Q2Q3
Q3Q4 Q4
Health Variations
Self-critique Ethnicity in effect treated chaotic conceptions (Sayer 1992)
– ‘lumping everything together’ MAUP, SAR areas big and crude, what do they mean? Some purchase on modelling complex relationships, but
still only suggesting reasons for variations ML Point us in right direction for other survey work or some
qualitative
Caveats