Ian Shuttleworth David Martin and Paul Barr S tructure Introduction The data and the project The analysis Geography Individual factors Propertyhousehold factors Concluding comments questions and ways forward ID: 241803
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Slide1
Understanding address accuracy: an investigation of the social geography of mismatch between census and health service records
Ian Shuttleworth, David Martin and Paul BarrSlide2
Structure
Introduction
The data and the project
The analysis
Geography
Individual factors
Property/household factors
Concluding comments, questions and ways forwardSlide3
Introduction
Several “Beyond 2011” options include the use of administrative data
Health service register is most complete of the existing administrative population sources
Need to understand these admin data better
Extending earlier work on migrants aged 25-74, this presentation considers spatial accuracy of health card registration in April 2001 for all age groups against the 2001 CensusSlide4
The Data and the Project
The Northern Ireland Longitudinal Study (NILS) is used (c450,000 in the analysis), based on a 28% sample (104/365) of birthdates of the NI population taken from
healthcards
The analysis compares address information from the healthcard system (individual property: XUPRN) as recorded in April 2001 compared with the 2001 Census (29
th
April)Slide5
The Data and the Project
It is assumed that the 2001 address information is the ‘gold standard’ to assess spatial accuracy
These first results are a descriptive profile of matches/mismatches and will be followed by
further (multivariate) analyses of the position as of April 2001, lags post 2001, and the position in 2011Slide6
The Analysis: Geography
Maps show: (
i
) mismatch between valid information from Census and
healthcard
system and (ii) missing information from both systems
M
ismatch higher in some rural areas – a feature that appears elsewhere in other parts of the analysis
Missing information on address higher in rural areas
Specific peaks of mismatch in some urban locations
These are a result of (
i
) types of people in different places; (ii) types of property in different places; (iii) interactions of (
i
) and (ii); and (iv) NI-specific factorsSlide7
Address mismatch levels – excluding missing information from Census and BSOSlide8
Missing XUPRNS from (a) Census and (b) BSO
Missing Census
Missing BSOSlide9
The Analysis: Individual factors
Individual social and demographic characteristics influence address matching rates
Some of these might be expected in terms of conventional ‘hard-to-enumerate’ categories (eg age, gender), others less so (eg education)
Lower rates of match of interest are marked in
red
; higher rates in
green
in the following two tables – social/demographic variables and labour market variables
The average match is 75.8%
We start with two graphs of age….and then the tablesSlide10
Percentages
Absolute numbers
Matches and mismatches by age (percentages and absolute numbers
Match
Mismatch
Both null
Null census
Null BSOSlide11
No information - Census and BSO
No information- Census
No information - BSO
Same address: yes
Same address: no
Community background
Catholic
2.44
1.88
4.09
73.31
18.29
Protestant
1.47
1.63
3.14
78.20
15.56
None
1.48
2.40
3.26
71.30
21.57
Other
1.11
1.82
2.72
75.18
19.16
Limiting long-term illness
Yes
1.94
2.04
4.06
77.91
14.06
No
1.87
1.67
3.41
75.48
17.58
Gender
Male
1.99
1.76
3.89
73.59
18.77
Female
1.81
1.75
3.25
77.91
15.28
Education
No qualification
2.00
1.57
4.07
77.63
14.73
Any qualification
1.71
1.78
3.44
72.91
20.16
Migration
Did not move pre-census
1.94
1.52
3.49
78.90
14.16
Moved pre-census
1.22
4.48
4.10
41.27
48.94
Living arrangements
couple:married
1.97
1.42
3.55
78.86
14.20
couple:remarried
0.76
1.14
2.51
81.31
14.27
couple:cohabiting
0.86
1.97
3.37
54.05
39.74
couple:no
(Single)
1.91
1.64
3.30
75.78
17.37
couple:no (married/remarried)
2.16
1.77
4.20
72.52
19.34
couple:no
(separated)
1.01
1.96
3.04
68.94
25.05
couple:no
(divorced)
1.10
1.89
3.19
73.79
20.04
couple:no
(widowed)
1.87
1.36
4.11
82.80
9.87
communal establishment
6.00
18.43
14.16
24.07
37.35Slide12
No information - Census and BSO
No information- Census
No information - BSO
Same address: yes
Same address: no
Aged 18-74
Economic activity
Employee
1.59
1.52
3.18
73.83
19.88
self-employed
3.50
2.04
6.86
67.59
20.01
Unemployed
2.02
2.24
4.14
67.73
23.86
econActive student
1.21
2.58
2.84
74.63
18.74
Retired
1.69
1.33
3.57
84.38
9.04
econInactive
student
1.95
3.38
4.02
70.24
20.41
home-maker
1.70
1.58
3.09
77.55
16.07
perm sick
1.69
1.85
3.95
77.12
15.40
Other
2.15
2.09
4.11
72.75
18.90
Missing
2.69
2.84
5.51
75.27
13.69
Occupation
professional
1.55
1.58
3.49
74.46
18.91
intermediate
1.49
1.50
2.86
77.77
16.39
self-employed
3.62
2.05
6.84
68.74
18.74
lowerSupervisor
1.38
1.52
3.26
74.74
19.10
routine
1.69
1.50
3.20
76.97
16.64
not working
2.45
2.37
5.05
70.31
19.82
students
1.84
2.33
3.53
74.83
17.48
unclassified
2.02
1.91
3.22
77.90
14.95Slide13
The Analysis: Property/household factors
Property/household influence address accuracy
Some of these might be expected in terms of conventional ‘hard-to-enumerate’ categories (tenure), others less so (eg property type)
Lower rates of match of interest are marked in
red
; higher rates in
green
in the following two tables – social/demographic variables and labour market variables
20% of households have mismatch between the address information of members – problems reconstructing households?Slide14
No information - Census and BSO
No information- Census
No information - BSO
Same address: yes
Same address: no
Tenure
Owner occupier
2.10
1.41
3.47
78.31
14.72
Social rented
0.58
1.63
2.75
75.87
19.17
Private rented
2.23
3.29
4.94
55.79
33.76
Property type
detached house/bungalow
3.63
2.06
4.86
74.03
15.42
semi-detached house/bungalow
0.41
0.79
2.07
80.51
16.20
terraced (
include
end of Terrace)0.310.762.0280.1116.79flat/tenement: purposeBuilt1.225.935.8153.8233.23converted/shared house (inc bedSit)3.1510.058.2235.0643.53commercial building6.088.9815.1930.5239.23caravan/other mobile/temporary12.519.077.5545.3725.50communal establishment6.0018.4414.1624.0637.34Household compositioncouple with children2.041.523.2678.8214.36couple without children1.441.663.4171.9521.54single parent1.271.322.8674.9819.57one person family1.522.824.5158.7332.41pensioner1.721.353.9683.749.22other2.301.684.3269.7921.90Slide15
Concluding Comments
Around 17% of individuals are in the ‘wrong place’; about 20% of households with two or more NILS members have individuals in the ‘wrong place’
Is 85% as good as it gets? Or 75%? Are stocks
of ‘mismatch’
at one moment in time a balance between inflows and outflows?
In some cases,
eg
people who moved in the past year, error is most likely associated with lags in reporting information
For others, eg cohabitees, the mismatch may well be a reflection of a complex reality and complex livesSlide16
Concluding Comments
Where BSO XUPRN ≠ BSO Census, the distance of the error is small (mode, median= < 1km)
Interpretation will vary according to the intended purpose
(
eg for health screening and some statistical purposes need to know exact address, others perhaps not so critical)
These insights all raises the issue of how to cope with uncertainty and the inherent ‘fuzziness’ of
life
Mismatch is a result of property/household factors and individual factors (see overleaf)Slide17
An abstract
place typology
of types of
errorSlide18
Future analysis
To get a better grasp of these issues we need to move to multivariate modelling – perhaps in an ML framework – to look at people, properties and places to make more reliable estimates
Future work will
Look at position as of April 2001 using multivariate approaches as above
Consider changes through time from 2001 onwardsSlide19
Future analysis
Future work will
Update the analysis using 2011 data – have structural social changes 2001-2011 made the population easier or harder to capture by the healthcard system?
Seek to add information on institutional factors (eg NILS members grouping in GP practices)
Try to transfer the NI experience to England & Wales and Scotland – what might be expected given the housing and demographic profile of localities in Britain?Slide20
Acknowledgement
The
help provided by the staff of the Northern Ireland Longitudinal Study/Northern Ireland Mortality
Study
(NILS)
and
the NILS Research Support Unit is acknowledged. The
NILS is
funded by the Health and Social Care Research and Development Division of the Public
Health Agency
(HSC R&D Division) and NISRA. The NILS‐RSU is funded by the ESRC and the Northern Ireland
Government. The
authors alone are responsible for the interpretation of the data and any views or opinions presented are
solely those
of the
author(s)
and do not necessarily represent those of NISRA/NILS
.