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Longitudinal data for interdisciplinary ageing research. Design of the Linnaeus Database

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To allow for interdisciplinary research on the relations between socioeconomic conditions and health in the ageing population, a new anonymized longitudinal database - the Linnaeus Database - has been developed at the Centre for Population Studies at Umeå University. This paper presents the database and its research potential. Using the Swedish personal numbers the researchers have, in collaboration with Statistics Sweden and the National Board for Health and Welfare, linked individual records from Swedish register data on death causes, hospitalization and various socioeconomic conditions with two databases - Betula and VIP (Västerbottens Intervention Programme) - previously developed by the researchers at Umeå University. Whereas Betula includes rich information about e.g. cognitive functions, VIP contains information about e.g. lifestyle and health indicators. POPULATION AND SAMPLE SIZE: The Linnaeus Database includes annually updated socioeconomic information from Statistics Sweden registers for all registered residents of Sweden for the period 1990 to 2006, in total 12,066,478. The information from the Betula includes 4,500 participants from the city of Umeå and VIP includes data for almost 90,000 participants. Both datasets include cross-sectional as well as longitudinal information. POTENTIAL: Due to the coverage and rich information, the Linnaeus Database allows for a variety of longitudinal studies on the relations between, for instance, socioeconomic conditions, health, lifestyle, cognition, family networks, migration and working conditions in ageing cohorts. By joining various datasets developed in different disciplinary traditions new possibilities for interdisciplinary research on ageing emerge.
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Gunnar Malmberg
Ageing and Living Conditions Programme/ Centre for Population Studies
Umeå University, Sweden
Presentation SIMSAM Umeå, October 19th 2011
Longitudinal Data for Interdisciplinary Ageing Research
- the Design of the Linnaeus Database
Ageing and Living Conditions Programme
Today
Ageing and Living Conditions Programme (ALC)
Linnaeus Database
Research on the Linnaeus Database
Ageing and Living Conditions Programme
Ageing and Living Conditions Programme
Interdisciplinary Research programme, started in 2007
Financed through a ”Linnaeus Grant”
Psychology, Epidemiology, Demography, Geography, Economics,
Statistics, History, Ethnology
Within the Centre for Population Studies (CPS),
Umeå University
Carl Linnaeus
Ageing and Living Conditions Programme
Psychology
Betula
Cognition
Successful
Ageing
Epidemiology
Västerbotten
Intervention
Programme
Death,
hospitalisation
Health
Life style
Social Sciences
Register
data (SCB)
Population
dynamics
Socio-economic
conditions
Historical
demography
Historical
demographic
database (DDB)
Long-term
trends of
demographic
behaviuor
Humanities
Qualitative
methods
Images and
positions of the
elderly people
in different
contexts
Ageing and Living Condition (ALC)
Ageing and Living Conditions Programme
Three Themes
Population Ageing
Mortality
Fertility
Migration
Participation of the Elderly
Labour Market
Leisure
Social relations
Society
Living conditions
Successful Ageing
Health
Cognition
Economy
Network
Care
Ageing and Living Conditions Programme
Living conditions of elderly people
Ageing and Living Conditions Programme
Economic
conditions
Health Cognitive functions Social networks
Living conditions
of elderly people
Living conditions of elderly people
Ageing and Living Conditions Programme
Current living conditions
Trends in living conditions of the elderly
Social gap (Cumulative Advantage/Disadvantage)
Living conditions of elderly people
Ageing and Living Conditions Programme
Living conditions
of elderly people
The Life Course
Cognitive functions
Health
Economic conditions
Social networks
Working life
Mobility
Neighbourhood/ Regions
Betula
Cognitive functions
Health
Socio-economic
Daily living
Leisure activities
Critical life events
4,500
Västerbotten
Intervention
Programme (VIP)
Self reported health
Life style
Living conditions
Quality of life
Socio-economic variables
Network, Social support
89,000
Register data from
National Board
of Health and Welfare
Hospitalisation
Death Causes
The Linnaeus Database
Links on individual level
Anonymized data
Register data from
Statistics Sweden
Demographic data
Socio-economic data
Family data
Work data
Geographical information
Grades
Total population
12,066,478
Ageing and Living Conditions Programme
Betula
Examine changes in cognition and health across the adult age span
(25 100 yrs)
Identify early cognitive predictors of dementia and risk factors of
dementia
Characterize successful aging
Ageing and Living Conditions Programme
Betula
Developed by Lars-Göran
Nilsson, Department of
Psychology, Umeå University
Include about 4500
participants from the city of
Umeå and its surroundings
Longitudinal data, five years
update
Health examination
current & past health
self-reported measures
social variables
critical life events
Cognitive testing
Ageing and Living Conditions Programme
Betula, samples and waves
T1 (1988-90) S1
T2 (1993-95) S1 S2 S3
(86%)
T3 (1998-00) S1 S2 S3 S4
(85%) (86%) (83%)
T4 (2003-05) S1 S3 S5
(84%) (84%)
T5 (2008-10) S1 S3 S6
Ageing and Living Conditions Programme
Västerbotten Intervention Program
Västerbotten county
CVD and diabetes
Since 1985
89,000 participants
All 40, 50, 60- y.o.
Integrated in primary care routines
Ageing and Living Conditions Programme
Health examination in VIP
Measurements:
Blood lipids (s-cholesterol, triglycerides)
Blood pressure
Body Mass Index, Waist
Oral Glucose Tolerance
Questionnaire:
SES
Social network and interaction
Self-reported health
Lifestyle: physical activity,,
tobacco, alcohol
(Food habits not available )
Quality of life
Data from the National Board of Health and Welfare
Patient registry
Hospital
Diagnoses (main and bi-)
Op-codes
Length (days) of
hospitalization
Hosp. date
Cause-of-death registry
Date
Diagnoses (main and bi-)
Death place
Ageing and Living Conditions Programme
Ageing and Living Conditions Programme
Register data from Statistics Sweden
Individual data for the whole Swedish population (registered
residents)
Census data for 1960, 1970, 1980, 1990
Annual data from 1986 2009
Ageing and Living Conditions Programme
Register data from Statistics Sweden
Basic individual information
gender, age, place of birth (parish, country)
Socio-economic data
incomes, education, (un-)employment, pensions, allowances
Family data
partner, (adult) parents, children
Work place data
company id, work place id, coordinates (100m)
Place of Residence
coordinates (100m)
Grades
Linking individual data to
neighbourhood, work place and family data
Neighbourhood
data
Place of residence
100-meter coordinates
Work place
data
Family and household
data
Workplace ID
100-meter coordinates Family ID
Family Networks in the Linnaeus Database
Ageing and Living Conditions Programme
Sibling
Sibling
Sibling
Sibling
Child Child Child Child
Mother Father
Individual
Grand
child Grand
child Grand
child Grand
child
Sibling
Sibling
Sibling
Sibling
Mother Father
Partner
Child Child Child Child
Grand
child Grand
child
Grand
child Grand
child
Statistics Sweden
register data Patient and death
cause data VIP Betula
Geographical
extension Sweden Sweden Västerbotten
county Umeå
Number of
individuals Total national
population Total national
population 89 000 4500
Links on
individual level
Time coverage 1960, 1970, 1980, 1990
1990 - 2005 1980s - 2006 1985
1988-
Time resolution 10 years (60 -90)
Annual (90-06) Continuous 10 year updates 5 years
Spatial
resolution 100 meter squares
Kind of
information
Socio-economic
Income
Family (links)
Work
Residence etc.
Grades (School)
Hospital care
Death
Death cause
Health indicators
Life style
Living conditions
Socio-economic
Cognitive
function
Health
Socio-
economic
Ageing and Living Conditions Programme
VIP
89,680
Statistics Sweden
Data
12,066,478
Patient Registry
and
Death Cause Registry
Betula
4,500
Intersections of the databases
Overlap 1,691
Ageing and Living Conditions Programme
1935 2006
Age 70
Place
of birth
Family
Socio-
economic
Indicator
1960
Age 25
Family
Socio-
economic
Work
Income
Education
1990
Family
Socio-
economic
Work
Income
Education
Residence
Health
Cognition
Life style
Age 55 Age 0
A life biography
Ageing and Living Conditions Programme
1970 1980
Advantages of the Linnaeus Database
Longitudinal analyses of the interrelations between health and socio-
economic conditions
Cognition, health and life style data in Betula and VIP
Health outcome in the Patient and Death Cause Registers
Rich socio-economic information in Statistics Sweden data
Create data of neighbourhoods and networks
Combination of individual, network, neighbourhood variables
Ageing and Living Conditions Programme
Advantages of the Linnaeus Database
Data on mobility, (residential, interregional, work places, separations etc)
Register data covers a longer period and has a higher time
resolution
Register data include the whole population
Drop out analysis
Data quality control
Ageing and Living Conditions Programme
“Family networks and retirement”
Xavier de Luna, ALC
Emma Lundholm, ALC
Gunnar Malmberg, ALC
Ingrid Svensson, ALC
Labour market mobility in late
working life”
Emma Lundholm, ALC
Gunnar Malmberg, ALC
“Health outcome of migration and
labour market mobility among
middle aged”
Emma Lundholm, ALC
Gunnar Malmberg, ALC
Yulia Blomstedt, ALC
“Family networks, life style and
health”
Gunnar Malmberg ALC
Tom Chang, University of Southern California
Heather Royer, RAND Cooperation
“Inequality as a health risk –
longitudinal and geographical
perspectives"
Sören Edvinsson, ALC
Gunnar Malmberg, ALC
Erling Lundevaller, ALC
“Network effects on timing of
retirement”
Tom Chang, University of Southern California
Heather Royer, RAND Cooperation
Olle Westerlund, ALC
Projects based on the Linnaeus Database
Network effects and the effects of
retirement on cognition”
Tom Chang, University of Southern California
Heather Royer, RAND Cooperation
Anna Sundström, ALC
“Educational attainment, grades and
health outcome”
Lauren Hersch Nicholas, University of Michigan
Yulia Blomstedt, ALC
Gunnar Malmberg, ALC
“Health, retirement and
widowhood. Using sequence
analysis to study life trajectories in
later life”
Nicola Barban, Università Bocconi, Milano
Xavier de Luna, ALC
Emma Lundholm, ALC
Ingrid Svensson, ALC
“Family networks, social support
and health”
Emma Lundholm, ALC
Yulia Blomstedt, ALC
“The agreement between dementia
diagnoses in the population based
Betula project and national register
data”
Anna Sundström, ALC
“Leisure activity and risk of cognitive
decline and dementia”
Anna Sundström, ALC
Projects based on the Linnaeus Database
“Stressful negative life events and
cognition”
Anna Sundström, ALC
“Correcting for attrition in Betula
studies “
Anna Sundström, ALC
Lars Nyberg, ALC
Xavier de Luna, ALC
“Regional differences in
intergenerational proximity and
employment transmission”
Emma Lundholm, ALC
“Social characteristics of
participants and non-participants in
VIP”
Margareta Norberg, ALC
Nawi Ng, ALC
“Participation vs non-participation in
a health intervention (VIP): Mortality
and CVD morbidity”
Margareta Norberg, ALC
Yulia Blomstedt
Nawi Ng, ALC
“Clustering of CVD riskfactors in
Västerbotten
Margareta Norberg, ALC
Nawi Ng, ALC
Projects based on the Linnaeus Database
“Physical activity and cognitive
performance across the lifespan”
Anna Sundström, ALC
“Marital status and dementia
diseases”
Anna Sundström, ALC
Lars-Göran Nilsson, ALC
“Inspection time across the life
span”
Anna Sundström, ALC
Projects based on the Linnaeus Database
Future plans
Update the Linnaeus database
Extend the database
Links to the historical database,
Data for two regions from 1600s until today
Link to internationl survey data
SHARE-data
Swedish node
Ageing and Living Conditions Programme
Preconditions for using the data
Research only within the themes of ALC programme and the
research questions approved by the ethical committee:
Population ageing: consequences for needs of care and support
in different demographic scenarios
Impacts of health, cognition and socioeconomic conditions on
participation in society and working life
Effects of socioeconomic conditions on health and cognition in
ageing populations
Preconditions for using the data
Protect the integrity of the individuals in the database
All empircal analyses of micro data has to be carried in the data-lab
at ALC
Each project has to apply from the steering group to get access to a
specific data-set
Research has to be in collaboration with ALC researchers
Looking forward collaborations
Thank you!
Population Ageing
Focus on the family level
Malmberg G., Hjälm A. and Lundholm E.
Are the distances between adult children and elderely parents increasing?
Are three- and four-generation families more common today?
Who lives close to elderly parents and adult children?
How does geographical mobility influence the proximity between elderly
parents, adult children and grandchildren?
Does the presence of family members affect the health status of elderly
people?
Percent of 55-year olds having a living parent and/or
grandchild 1990-2005
Ageing and Living Conditions Programme
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
1990 1992 1994 1996 1998 2000 2002 2004
Parents Grandchildren Parent and grandchild Childless
Ageing and Living Conditions Programme
Percentages having adult children living within 25 km at age 60,
by municipalities
Lundholm, E.
Participation
Effects of education of older workers on timing of retirement and
earnings
De Luna X., Stenberg A. and Westerlund O.
Family Ties and Retirement in Sweden
Presence and proximity to adult children, grand-children or elderly parents:
consequences on the timing of retirement
Lundholm E. and Malmberg G.
Mobility in late working life
- consequences for retirement, income and health
Blomstedt Y., Lundholm E. and Malmberg G.
Change of workplace 2005 2006, age 20- 70
Source: linneus database
Ageing and Living Conditions Programme
Change of workplace 1991 1992 and 2005 2006, age 20- 70
Ageing and Living Conditions Programme
Successful Ageing
“Determinants of declining cognition”
Maria Johansson, Lars Nyberg, Ingrid Svensson
“Marital status and cognitive performance”
Anna Sundström and Hossein Mousavi-Nasab
“Effects of divorcing at high age on BMI”
Jenny Häggström, Olle Westerlund, Margareta Norberg
“Social networks and health”
Yulia Blomstedt, Emma Lundholm
“Tobacco consumption in ageing cohorts smoking or snuffing”
Margareta Norberg, Göran Broström, Gunnar Malmberg, Nawi Ng
Future plans, research and collaborations
Working in interdisciplinary research groups
Extending the research
More researchers within the programme, more funding
International collaborations
Extending the database
Longer time period
Links to the historical database
Ageing and Living Conditions Programme
... We used baseline mortality data of the study areas between January 1st, 1991, and December 31st, 2014, from the Linnaeus database at the Center for Demographic and Ageing Research (CEDAR), Umeå University, Sweden (Malmberg et al., 2010). The information on daily deaths was based on the place of residence and included the death date and age at death. ...
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EXECUTIVE SUMMARY Background: A regional integrated database could serve as a rich data source for in-depth analysis in research studies across key Public Health lifestyle areas in the East Midlands. This could inform Public Health policy, service delivery and commissioning decisions. Unfortunately, existing datasets are poorly aligned across the four key Public Health lifestyle areas examined in this study: physical activity, smoking cessation, reduction in alcohol consumption, and diet and weight management. This feasibility study was therefore commissioned by the East Midlands Directors of Public Health Group chaired by Professor Derek Ward, Director of Public Health in Lincolnshire, with funding from the NIHR East Midlands Clinical Research Network and the College of Social Science, University of Lincoln. Public Health researchers in the Mental Health, Health and Social Care Research Group (MH2aSC) at the University of Lincoln were invited to carry out the study to explore the feasibility of developing and implementing an integrated lifestyle database across the East Midlands Region. Methods: A scoping review for available evidence was conducted to inform decisions about feasibility of the proposed integrated lifestyle database. This was followed by a consultation exercise with 18 stakeholders, predominantly in the East Midlands, from September 2020 to February 2021. The consultation exercise sought to gather the views of stakeholders, purposively invited to take part due to their role in public health, about the potential feasibility of an integrated database. Stakeholders were identified and invited by email to participate in the consultation meetings which took place via Microsoft Teams. A topic guide, designed specifically for this study, was used to guide the discussion. The meetings were recorded, transcribed, and analysed thematically. Results: The scoping literature review revealed potential benefits but also barriers to the development of an integrated lifestyle dataset, and highlighted the need to consider local factors which need to be better understood prior to implementation. These findings from the literature were supported by rustults from the subsequent consultation exercise. Stakeholders for the most part, welcomed the idea of an integrated East Midlands lifestyle database because of its potential benefits for research and to produce evidence to inform service development and commissioning decisions. However, concerns were expressed by some providers including anxieties around revealing their business strategies to rival organisations also involved in the provision of lifestyles services, the cost of setting up and running the proposed integrated database, and the complexities involved in information sharing and governance arrangements which would need to be established. Conclusion: In view of the findings the following options should be explored while taking into consideration the barriers and facilitators expressed by stakeholders: 1. A fully integrated individual level lifestyle dataset across the whole East Midlands covering all four lifestyle areas, with governance and access controlled by one institution (possibly a Local Authority or a university) that will house and maintain the database. 2. A fully integrated individual level dataset for all four lifestyle areas, within just one geographical area to start with, which is owned by the service provider. There is a need to consider how to make this available more widely, as the providers only report collated data back to the commissioners. 3. A fully integrated individual level dataset initially starting with one health area (possibly smoking which already has a standardised Key Performance Indicators (KPI) across the whole region, (to be rolled out later subject to success), with governance and access controlled by the institution (either a Local Authority or a local university) that will house the database. 4. An integrated aggregated level dataset covering all four lifestyle areas (reporting similar KPIs as is done currently by service providers who report back to their commissioners), across the whole East Midlands, with governance and access controlled by one institution (possibly a Local Authority or a university) that will house and maintain the database. 5. A fully integrated aggregated level dataset for all four lifestyle areas, within just one geographical area to start with, as we have in Lincolnshire, which is owned by the service provider. There is a need to consider how to make this more widely available, as the providers only report collated data back to the commissioners. This is the model already used in Lincolnshire. 6. An integrated aggregated level dataset initially starting with one health area (possibly smoking which already has a standardised KPI) across the whole region, (to be rolled out later subject to success), with governance and access controlled by the institution (either a Local Authority or a local university) that will house the database.
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Studies of memory trajectories using longitudinal data often result in highly nonrepresentative samples due to selective study enrollment and attrition. An additional bias comes from practice effects that result in improved or maintained performance due to familiarity with test content or context. These challenges may bias study findings and severely distort the ability to generalize to the target population. In this study, we propose an approach for estimating the finite population mean of a longitudinal outcome conditioning on being alive at a specific time point. We develop a flexible Bayesian semiparametric predictive estimator for population inference when longitudinal auxiliary information is known for the target population. We evaluate the sensitivity of the results to untestable assumptions and further compare our approach to other methods used for population inference in a simulation study. The proposed approach is motivated by 15-year longitudinal data from the Betula longitudinal cohort study. We apply our approach to estimate lifespan trajectories in episodic memory, with the aim to generalize findings to a target population.
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Objectives: The aim of this nationwide study was to examine the association between age at retirement and dementia risk, with a follow-up period of up to 24 years. Methods/Design: This cohort study comprised Swedish citizens born in 1930 who were alive in the year 1990 (n=63,505). The cohort was followed for incidents of dementia through data provided by the Swedish National Patient Register and the Cause of Death Register. Age at retirement and socioeconomic variables were retrieved from Statistics Sweden. Results: During the follow-up, 5,181 individuals received a dementia diagnosis. Competing risk regression models, adjusted for sex, education, marital status, occupation, and previous history of cardiovascular diseases, showed that later-than-average retirement age was associated with decreased dementia risk. Conclusions: The present results supports the idea that individuals who retired at an older age has a decrease risk of dementia. However, as this was an observation study, unmeasured factors, such as premorbid cognitive level and genetic predisposition, may have influenced our findings and remains to be elucidated in future studies.
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