linking lives through time scottish longitudinal study (sls)
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SCOTTISH LONGITUDINAL STUDY(SLS)
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Why do we need the SLS?• overall mortality rates are higher than the rest
of Britain • fertility rates are lower than the rest of Britain• population ageing is a significant problem for
the future in Scotland• specific causes of death such as lung cancer
and heart disease rank among the worst in Europe
• rates of household deprivation are higher than in the rest of Britain
• These issues, and the inter-relationships between them, are examples of what can be explored using the SLS
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Muller-Nordhorn, J. et al. Eur Heart J 2008 0:ehm604v1-11; doi:10.1093/eurheartj/ehm604
Age-standardized mortality from ischaemic heart disease in European regions (men; age group 45-74 years; year 2000)
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What is the SLS?• SLS is a replica of the LS (Longitudinal Study of
England and Wales), which started in 1971• The SLS is a large-scale, anonymised linkage study
designed to capture 5.5% of the Scottish population• Sample based on 20 semi-random birthdates• It actually contains information on a 5.3% sample• It is built using data available from…– Census data (initial sample from 1991, then 2001)– Vital Events data (births, deaths, marriages etc…)– National Health Service Central Register (NHSCR) data
(migration into or out of Scotland)– NHS data (cancer registrations, hospital episodes and
maternity data)– Education data
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Study structure
SLS database
1991 original sample:
270,385 selected from 1991 Census
plus household members Entries since 1991:
Births 53k, Immigrants 31k
Exits of sample members from SLS:
deaths 48k, emigrants 20k
Events to sample members since their entry to SLS:
Births, widow(er)hoods, marriages, stillbirths, infant mortality (139k in total)
2001 Census sample
265,104 sample members found at 2001
plus household members
Coming soon:
School Census records, inc attendance/exclusions, attainment, qualifications
ISD health data
Project specific extracts of:Hospital admissionsCancer registrationsMaternity data
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SLS is one of three UK LS
LS England and Wales (LS)• 1% sampe
Northern Ireland LS (NILS)• 28% sample
Northern Ireland mortality study (NIMS)• 100%
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SLS project examples
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SLS project - Example 1
Assessing socio-economic inequalities in mortality at the Scottish national level, incorporating a comparison between mortality in Scotland and England
Frank Popham – University of St Andrews Paul Boyle - University of St Andrews
SLS project no. 2009_004– www.lscs.ac.uk/sls/projects/2009_004.htm
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Is there a “Scottish effect” for mortality? Scottish effect = excess Scottish mortality
over England after deprivation differences
Found in unlinked ecological data but what about linked data joining SLS and ONS LS?
Popham, F and Boyle, P: Journal of Public Health doi:10.1093/pubmed/fdr023
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Source: Mark Hillary
What about those born in Scotland now living in England?
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Born Eng, live E&WBorn Eng, live Scot
Born Scot, live E&WBorn Scot, live Scot
Before adjusting for SEP differences After adjusting for SEP differences
Source: Scottish Longitudinal Study and ONS Longitudinal Study
Impact on relative mortality rate 2001-2007 of adjusting for socio-economic differences
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Is there a “Scottish effect” for mortality? Scottish effect = excess Scottish mortality over
England after deprivation differences
Found in unlinked ecological data but what about linked data joining SLS and ONS LS?
Additionally account for country of birth as Scots born have high mortality generally
Confirms there appears to be a Scottish effect associated with born Scottish• However, unmeasured confounding still possible
explanation• Socio-economic circumstances in childhood
important?
Popham, F and Boyle, P: Journal of Public Health doi:10.1093/pubmed/fdr023
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SLS project - Example 2
Does being widowed increase the risk of death?
Paul Boyle - University of St Andrews Zhiqiang Feng - University of St Andrews Gillian Raab - University of St Andrews
SLS project no. 2008_006– www.lscs.ac.uk/sls/projects/2008_006.htm
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Research OverviewBackground Does widowhood increases mortality risk? Although commonly observed, this ‘widowhood
effect’ could be due to selection effects as married couples share various characteristics related to the risk of death.
The widowhood effect by different causes of spousal death; some are correlated with these shared characteristics, while others are not.
Methods Using data from the SLS outcomes for men and
women by different causes of death of their spouse, controlling for a range of individual- and household-level characteristics were compared.
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Effect of widowhood on the mortality hazard ratio in a Cox model, compared with the effect of age at the 1991 census, with age 50 as the baseline, adjusted for socio-economic, LLTI and ethnicity.
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Results The widowhood effect is greater than has been found
from other recent studies, especially for older women. The risk is highest shortly after widowhood, but
remains significant for over ten years. These broad results hold regardless of the cause of
death of the spouse.
Conclusions The analysis of the widowhood effect used three
methods of classifying the spouse’s cause of death in an attempt to control for potential selection effects.
The results are highly consistent and suggest that this is a causal effect, rather than a result of selection.
Boyle, P, Feng, Z. & Raab, G, (2011) Does widowhood increase mortality risk? Comparing different causes of spousal death to test for selection effects. Epidemiology, 22 1-5
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SLS Future developments
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School Education data – 3 datasets:
Pilot linkage exercise carried out using 2007 & 2008 data. 2009 linkage to be carried out summer 2011.
Names not available so linkage carried out on DOB, sex and postcode only - >80% linkage success
Data to be provided annually, and successive linkages will increase proportion of linked pupils (since each has up to 13 chances of being linked)
- School Census data- SQA attainment data - Attendance/ absence & exclusions
data available
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2011 Census – Questions added
5 new questions included:• national identity • ability in spoken English • languages other than English used at home • long term health conditions • month/year of arrival into the UK (for people not
born in the UK)
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Summary: strengths of the SLS Sample size much larger than most surveys
BHPS started with ~10,000 people in GB SLS has ±270 thousand traced members + ±505 thousand
household members in Scotland (1991) This means that it’s possible to analyse relatively small sub
populations Covers several fields of interest – demography, economic
and social issues, health, housing, mortality, migration, fertility etc
Can be linked with detailed geographical information Census compulsory so attrition rates low and linkage rates
high Includes those in communal establishments Ability to link hospital episodes data to socio-economic
characteristics Potential to link to other datasets in the future – (eg 2011
Census, HESA)
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Summary: weaknesses of the SLS
Restricted range of variables • Smoking• Income
Census information only collected every decade Not possible to return to the sample to ask
extra questions The data are highly confidential Immigration and emigration data not very
reliable We rely on census data - will there be a 2021
Census? Difficult dataset to analyse, both technically,
and logistically!
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The SLS team – contact detailsBased in Edinburgh: Based in LSCS, St
Andrews:
Joan Nolan Database Administrator0131 314 [email protected]
Zengyi HuangProgrammer0131 314 4253 [email protected]
Claire BoagSLS Manager0131 314 [email protected]
Gillian RaabStatistician 0131 314 [email protected]
Christine Lamb Chris Dibben Administrator SLS Director
SLS Support Officers
Zhiqiang Feng Peteke FeijtenPlus:Frank Popham & Lee Williamson
Interested in using the SLS?Contact:[email protected]
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Information on datasets
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Publication Hub
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Downloads Page (includes relevant legislation)
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PDF Researcher packs
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Guidance
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Registration
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Living circumstances
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husband kids (parents others)
husband (parents others)
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kids (parents others)
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• Young women no births.
• Picture for young men looks very similar see next slide
• Over ages 15 to 30 gradual move away from parents to live alone or with husband or partner
• Others is an intermediate state
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Living circumstances at 2001
• Young men no births.
• Picture very similar to that for young women
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Teen mums Teen dads
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Economic position at 2001