Transcript Residential concentration and general health in Northern

The Northern Ireland
Longitudinal Study:
data linkage, research potential
and application
Gemma Catney
Centre for Public Health,
Queen’s University Belfast
Meeting of the Royal Statistical Society
Leeds/Bradford, 26th January
Presentation outline
• Part one: The NILS – background to the data and
their linkages
• Part two: Research application – Segregation and
health in NI
– Segregation and (ill)health
• Minority/majority status
– ‘Religious’ concentration in Northern Ireland
– Hypotheses, data, methods
– Results
• Logistic regression (outcome: poor GH), pop. concentrations
• Cox proportional hazards (outcome: all-cause mortality)
• Segregation indices and poor general health
– Discussion, conclusions, future work
Part one: The NILS –
background to the data
and their linkages
Background to the NILS and NIMS
1. Research-Driven
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Cross-sectional studies: no information on change over time
Other UK LS
Other international mortality-based LS
Health and socio-demographic profile of NI
2. Legislation
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Confidentiality protected, and managed by NISRA, under
Census legislation
3. Funding
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Infrastructure funded by the Health and Social Care R&D
Division and NISRA
Research support function funded by ESRC and NI
Government (OFMDFM)
Overview of the NILS and NIMS
1.
Northern Ireland Longitudinal Study (NILS) – c. 28% representative
sample of NI population (c. 500,000), based on health card
registrations, linked to:
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2001 Census returns
vital events (births, deaths and marriages)
demographic & migration events
distinct Health & Care datasets
Northern Ireland Mortality Study (NIMS) - enumerated population at
Census Day (c.1.6 million), linked to:
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2001 Census returns
subsequently registered mortality data
Both NILS and NIMS linked to contextual and area-based data:
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capital value of houses and property attributes
geographical indicators
settlement classifications
deprivation measures
Datasets routinely linked
Census Dataset 2001
GRO Vital Events Datasets 1997-2007
Variables include:
Age, sex and marital status
Religion and community background
Family, household or communal type
Housing, including tenure, rooms and amenities
Country of birth, ethnicity
Educational qualifications
Economic activity, occupation and social class
Migration (between 2000 and 2001)
Limiting, long-term illness, self-reported general
health, caregiving
Travel to work
- New births into the sample
- Births to sample mothers and fathers
- Stillbirths to sample mothers
- Infant mortality of children of sample mothers
and fathers
- Deaths of sample members 2001-2007
- Marriages 2004-2006
- Widow(er)hoods 2004-2006
LPS Property Data 2010
Health Card Registration Datasets 20012010
Capital and rating value (based on 2005 valuation
exercise)
- Demographic data: age, status and location
Variables include:
- Household characteristics (no. of rooms,
property type, floor space, central heating) and
valuation
- Estimated capital value
- Migration events:
immigrants added to the sample
emigration of sample members
re-entry of sample members to NI
migration within NI
Research based on the NILS/NIMS
• Health and mortality
• Temperature-related mortality and housing
• Socio-demographic and area correlates of suicides
• Distribution of cancer deaths in Northern Ireland by population and household
type
• Variations in alcohol-related deaths in Northern Ireland
• Demographic trends
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Fertility in the short-run in Northern Ireland
Lone mothers at time of birth: who are they?
Fertility levels and future school populations
Describing and modelling internal migration
Deprivation & ill-health: a comparison of Scotland and NI
• Education, employment and income
• Unemployment and permanent sickness in NI
• Pervasive area poverty: modelled household income
• House value as an indicator of cumulative wealth in older people
• Area-based analyses
• Rural aspects of health
• Population movement and the spatial distribution of socio-economic and health
status
• Residential concentration/segregation and poor health
Research support
NILS Research Support Unit
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Based at the Centre for Public Health (QUB) and NISRA HQ
(McAuley House)
Support: 2 full-time and 1 half-time Research Support Officers
Established April 2009
Remit:
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raise awareness of the NILS research potential;
assist with development of research ideas and projects;
facilitate access to NILS data;
training & advice in use and analysis of NILS datasets;
promote policy relevance; and
enhance NILS research capacity
Matching process
• NIMS database based on 1.6m pop. at
2001 Census
• GRONI deaths data added to NIMS
database on a six-monthly basis
• 3-stage matching process:
• exact computer matching
• fuzzy computer matching
• detailed manual searching
Record Linkage: Issues and Biases
Linkage rates close to 100% not possible for NIMS
– why?
1. Non-enumeration at Census:
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One Number Census methodology: imputation for adjusted est. total
Imputation varies by age, gender and geographical area
In NI enumerated 2001 Census total was 1,603,641 - an additional 81,626
people were imputed = overall imputation rate of 4.6%.
2. People who came to NI after 2001 and
subsequently died: selective unrecorded migration
3. Differences between the info collected on census
form and death certificate
Record Linkage: Issues and Biases
Study on potential biases:
O’ Reilly, D., Rosato, M. & Connolly, S. (2008) Unlinked vital
events in census-based longitudinal studies can bias
subsequent analysis.
Journal of Clin. Epid. 61: 380-385.
What are the characteristics of people whose
events are not linked into the LS datasets?
What does this mean for analyses using the
LS?
Record Linkage Rates 2001-2005
• 59,396 deaths available to be linked from 2001-2005
• 6% deaths (3,392) could not be matched
Process
Number (%)
All death records NI 59,396
Exact matches
45,496 (80.6)
Fuzzy matches
4,491 (8.0)
Manual matches
2,093 (3.7)
Linkage through
HCR
Unlinked
951 (1.7)
3,392 (6.0)
Characteristics of matched and non-matched deaths
Based on data from death records (multivariate log reg):
• Year of registration
• Socio-demographic details
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age, sex, marital status, social class (NS-SEC)
• Place of death
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home, hospital, nursing/residential home
• Area in which they lived (SOA)
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Deprivation (income domain)
Urban/rural
Population density
Imputation
• Cause of death
Variation according to demographic characteristics
(Outcome: unmatched death, 2001-2006)
Aged less than 65
Aged more than 65
Deaths
OR
Deaths
OR
1.00
25,443
1.00
0.63 ***
31,775
0.92*
1.00
19,450
1.00
1.57 ***
8,873
2.83 ***
1.40 ***
27,758
1.97 ***
2.52 ***
1,137
3.30 ***
Home 6,066
1.00
13,378
1.00
N/R home 1,009
1.05
12,771
2.00 ***
0.80 ***
31,069
1.28 ***
Sex
Male 8,130
Female 4,941
Marital status
Married 7,398
Single 3,549
Widowed 776
Sep/Divorced 1,348
Place of death
Hospital 5,996
*** P<0.001; ** P< 0.01; * P<0.05
Variation according to relative deprivation (Outcome:
unmatched death, 2001-2006)
Aged less than 65
Aged more than 65
Deaths
Odds ratios Deaths
Odds ratios
Least
Deprived
1,831
(6.8%)
1.00
10,543
(5.7%)
1.00
2nd
2,137
(8.8%)
1.19
11,103
(5.4%)
0.90
3rd
2,554
(9.5%)
1.20
11,933
(6.0%)
0.93
4th
2,901
(10.4%)
1.20
11,534
(5.2%)
0.84 *
Most
Deprived
3,530
(16.0%)
1.78 ***
11,374
(7.2%)
1.23 **
*** P<0.001; ** P< 0.01; * P<0.05
Variation by cause of death (Outcome: unmatched
death, 2001-2006)
All ages
Deaths (%unmatched)
Under 65 years old
Deaths (%unmatched)
All causes
70,289 (6.9%)
13,071 (11.1%)
I.H.D
13,970 (5.6%)
2,064 (9.4%)
Stroke
7,211 (6.8%)
542 (8.9%)
Respiratory Disease
9,722 (7.0%)
802 (9.9%)
Cancer
18,572 (5.6%)
4,846 (8.1%)
All External causes
2,634 (15.2%)
1,648 (20.3%)
Accidents
1,719 (12.3%)
830 (18.2%)
Suicides
702 (19.9%)
649 (21.4%)
Other Causes
12,840 (8.9%)
2,579 (13.6%)
Record linkage: issues and biases
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Research conclusions: small proportion of events are not
linked – biases:
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increase in months immediately after Census Day 2001
increase with ‘distance’ from the Census
are non-random and more frequent in …
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younger males, older females
people who are perhaps more socially isolated
amongst residents of nursing/residential homes
deprived areas
where enumeration is low
Non-linkage may limit the ability to study some causes of
death and potentially lead to an underestimation of
social gradients
So there are potential biases, however...
Statutory obligation to record death events. Complete &
good quality data:
long experience of use for mortality analyses and
there will be biases in every linkage study ≠100%:
this research shows that biases can be quantified
Small number problems i.e., falling death rates,
population sub-groups (minority ethnics), cause-specific
mortality (suicides, trauma & specific cancers)
yet: can increase length of follow-up study, aggregate subpopulations & increase cohort size
Part two: Research
application – segregation
and health in NI
Acknowledgements
The help provided by the staff of the Northern Ireland Longitudinal
Study and Northern Ireland Mortality Study (NILS and NIMS)
and the NILS Research Support Unit is acknowledged. The NILS
and NIMS are 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.
Corresponding author: [email protected]
More information on NILS/NIMS data:
www.nils-rsu.census.ac.uk