„lidA – leben in der Arbeit“German Cohort Studyon Work, Age and Health

Groningen April 14, 2011

Angela Rauch, Anita Tisch, Silke Tophoven and Stefan Bender (IAB)

Outline

1. Motivation I and II

2. Main Questions

3. The lidA-cohorts

4. Facts about lidA (Content, Sampling Design)

5. Linkage with Administrative Data

6. Related German surveys

7. Conclusion

2

Motivation I

• Estimation of job displacement on Mortality (Sullivan/von Wachter 2010)

• Admin Data of male Pennsylvanian workers in 70s/80s matched to Social Security Administration death records 1980-2006.

• For high-seniority male workers, mortality rates in the year after displacement are 50-100% higher.

• The effect declines sharply over time, but even 20 years later still 10-15% increase in annual death hazards.

• A loss in life expectancy of 1.0-1.5 years for a worker displaced at age 40.

• Workers with larger losses in earnings tend to suffer greater increases in mortality (no causal effect).

3

Motivation II

• The working life of tomorrow will be characterised by – higher intensity of work, – much faster rate of change (technology and

organisation), – flexible working hours and arrangements, – more interpersonal work/group work, – higher proportion of immigrant workers etc.

4

Motivation II

5

• Older work force as demographic changes prohibit early labour exit possibilities and incentives.

• Effective average retirement age may rise from just under 60 (2005) to almost 65 by 2050 (Börsch-Supan 2005).

2010 2015 2020 2025 2030 2035 204010.0

12.5

15.0

17.5

20.0

22.5

25.0Labour force projection until 2040

age 20-34 age 35-49 age 50-66

pers

ons

in m

illio

n

Source: Federal Statistical Office (2009). Results of the 12th coordinated population projection. Variant: “Medium“ population, lower limit .

Main questions

• Participation in the labour force among elderly persons depends on two main factors:– Can the person work? (work ability). Functional

ability (health)– Does the person want to (continue to) work?

(motivation, willingness). Psychological factors and positive qualities of work (may connected with health)

• Work affects health and health effects work!!!

6

Main Questions

Main question:• How does work affect health and vice versa in higher working age?

Basic research models:• The influence of different work exposures on health under the

control of individual factors and socioeconomic status• The influence of socioeconomic status on health under the control of

individual and work related factors• Gender-specific aspects of the relationship between work and health

(different diseases, specific work aspects, non-work setting)

7

Main facts and ideas

• Deterioration of health begins after the age of 45 – especially among women and people with low educational levels

• The influences of age, cohort and time need to be separable in order to detect and forecast real developments.

• The application of a cohort-sequential design (known as Schaie's “Most Efficient Design”) allows for a tri-factor model isolating the impact of the factors age, cohort and time on work-related health.

8

9

German Baby Boomers1955

1959

1965

1975

1985

1995

2005

2009

0

200

400

600

800

1,000

1,200

1,400

0.0

0.4

0.8

1.2

1.6

2.0

2.4

2.8

Geburten - Deutschland (Insgesamt)Geburten - West (Früheres Bundesgebiet)Zusammengefasste Geburtenziffer OstZusammengefasste Geburtenziffer West

Nu

mb

er

of

bir

ths

(in

th

ou

san

ds)

To

tal f

ert

ility

ra

te

Quelle:

Quelle:

Source: Federal Statistical Office 2010, BiB 2010; compiled by the authors.

Total fertility rate WestTotal fertility rate East

Births – Germany (Total) Births – Germany (West)

10

Framework conditions of labour market entry – overall economic development

1959

1965

1985

1995

2005

-6

-4

-2

0

2

4

6

8

10

12

14

1975

Arbeitslosenquote bezogen auf abhängige zivile Erwerbspersonen - in Prozent

Bruttoinlandsprodukt, preisbereinigt, verkettet - Veränderung gegenüber dem Vorjahr in Prozent

pe

rce

nt

Source: Federal Statistical Office 2011, compiled by the authors.

1959 cohort age 16

1965 cohort age 16

1965 cohort age 25

1959 cohort age 25

Unemployment rate (of dependent cilivian working population - percentage)

Gross domestic product (price adjusted, GDP - year to year percent change)

11

• German Baby Boomers1959: 1.24 million births (GDR +FRG)1965: 1.33 million births (GDR +FRG)

• Profiteers of the educational expansion in Germany

• Labour market entry during economic crises

• Now: At the threshold to older working age2008: 932,358 employees covered by social security born 1959; 1,048,788 employees covered by social security born 1965;about the same proportion of men and women

• In the future: A challenge for the social security systems

The lidA-cohortsIn general

Study DesignSequential Cohort Design

2019

2016

2013

462011

1959 cohort

1965 cohort

1971 cohort

cohort effects period effects age effects

48

51

54

45

48

52

54

57

60

12

Facts about the survey

• 6,000 randomly chosen persons in two cohorts: – approx. 2,700 of the 59-cohort– approx. 3,300 of the 65-cohort

• Duration of the questionaire: approx. 1 hour • CAPI-interviews• Follow-up after 3 years (panel design)

13

• Work: Physical exposure and psychosocial work exposure • Professional aspects: Work history, job satisfaction, work-home

interference, employment status, retirement expectations, work ability

• Subjective health and health indicators: Interviewee’s own rating of physical and psychological health, health behaviour, restrictions in activity, cognitive functioning, anxiety, depression, fatigue, addictive behaviour

• Objective health indicators: Hand grip strength test• Personal aspects: Lifestyle factors, activities of daily living, life

satisfaction, self confidence, motivation • Socio-demographic background: Age, gender, marital status,

education level, occupational position, occupational biography 14

Sampling Design

15

• sample drawn from the employment history data (BeH) of the federal employment agency

• two-stage sampling design: • first stage: 222 sample points, drawn proportionately to the

population • big cities are represented by more than one sample point• second stage: random selection of respondents within the

sample points • the same amount of interviews in each sample point• disproportional distribution of the two cohorts (oversampling

of the 1965s cohort)

Linkage with Administrative Data

Survey Data (CAPI)

Health insurance data

Administrative Datasets of the

Federal Employment Agency

16

‘Administrative data are computerized records that are gathered for some administrative purpose, but contain information that can be used for other purposes as well.’ (John Billings)‘Administrative data describes information collected by persons, organizations or departments of government for their own purposes.’ (Statistics Canada)

Health insurance data*

health insurance master data

data on inpatient care

data on outpatient care

disablement data

* Preliminary information as of September 2010

Work-Health-Matrix(aggregated data)

17

Linkage with Administrative Data IHealth Insurance Data

Establishment History Panel (BHP)

Integrated employment Biographies (IEB)

Datasets of the Federal Employment Agency

18

Linkage with Administrative Data II Administrative Datasets of the Federal Employment Agency

• total number of employees • number of full-time employees• number of female employees • employee age structure• wage structure• …

• cross sectional data (time reference 30 June)

• times of employment• times of unemployment• information on job search • participation in employment and training measures• …

• longitudinal data on a daily basis (west: 1975-2009; east: 1990-2009)

19

1975

1976

1977

1978

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49

0102030405060708090

100

full-time part-time marginal employment vocational trainingrecipient of social benefit

%

1975

1976

1977

1978

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49

0

10

20

30

40

50

60

70

80

90

100

%

MenEmployment status by age, born 1959

WomenEmployment status by age, born 1959

The lidA-cohortsEmployment Status

20

MenEmployment status by age, born 1965

WomenEmployment status by age, born 1965

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43

0

10

20

30

40

50

60

70

80

90

100

full-time part-time marginal employment vocational trainingrecipient of social benefit

%

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43

0

10

20

30

40

50

60

70

80

90

100

%The lidA-cohortsEmployment Status

• Maybe the other (short) presentation?

21

22

Linkage between survey data and administrative data:

1. Agreement rates:

Linkage with Administrative Data III First results of the pretest 2010 (n=200)

panel participation

(n=200)

linkage with datasets of the Federal Employment Agency

(n=200)

linkage with health insurance data

(n=192)

Written agreement (%) 95 83 68

Written agreement (n) 190 166 131

23

Difficulties record linkage health insurance data:

1. Individual level:

• health data = sensitive data

• written agreement necessary

• misspelling insurance number or insurance company’s name

Linkage with Administrative Data IV Health insurance data

24

Difficulties record linkage health insurance data:

1. Individual level:

Linkage with Administrative Data IV Health insurance data

25

Difficulties record linkage health insurance data:

1. Individual level:

• health data = sensitive data

• written agreement necessary

• misspelling insurance number or insurance company’s name

2. Insurance company level:

• only statutory health insurances

• large and changing number of insurances in Germany (>160)

• many small and regional insurances

Linkage with Administrative Data IV Health insurance data

26

Difficulties record linkage health insurance data:

Pretest 2010:

• 131 persons in 34 different insurance companies

Linkage with Administrative Data IV Health insurance data

Number persons(n=131)

Number insurance companies

Status of agreement on the insurance company’s level

75 (57 %) 11 data available4 (3 %) 2 no answer (Jan. 2011)

19 (15 %) 14 insurance company too small

32 (24 %) 7 refusal

1(<1 %) - linkage impossible

Outlook for the survey

• contact to health insurance companies (ongoing)

• February to summer 2011: data collection first wave

• September 2011: linkage to health insurance data and employment histories

• August/September 2013: start of the second wave of the survey

27

SHARE - Survey of Health, Ageing and Retirement in Europe

• SHARE is a multidisciplinary and cross-national panel database of micro data on health, socio-economic status and social and family networks of more than 45,000 individuals aged 50 or over.

• In 2008 was selected as one of the projects to be implemented in the European Strategy Forum on Research Infrastructures (ESFRI).

• Eleven countries contributed data to the 2004 SHARE baseline study (Denmark, Sweden, Austria, France, Germany, Switzerland, Belgium, the Netherlands, Spain, Italy and Greece). After 2005: Israel, Czech Republic, Poland and Ireland.

28

SHARE - content

• health variables• bio-markers (e.g. grip strength, body-mass index, peak flow), • psychological variables (e.g. well-being, life satisfaction),• economic variables • social support variables (e.g. assistance within families, transfers

of income and assets, social networks, volunteer activities).

• For Germany: link between SHARE and administrative data from the German Pension System

29

Future data: The National Cohort

• The National Cohort will be an intensive investigation of the health, lifestyle and genetics of 200,000 people over 10 years.

• One hour survey and one additional our medical examination (for example biomarkers), follow-up after 5 years (plan: lifelong study).

• 40,000 participants will be scanned with advanced magnetic resonance imaging (early signs of common diseases).

• Main question: how chronic diseases are conditioned by lifestyle and environmental issues, as well as by genetic.

• Plan: Linkage to administrative data (agreement of the individuals).

30

Conclusion

• Labour market and health will be a key topic for research in the next years

• Linkage of surveys, medical test data and administrated data (agreement of the individuals)

• lidA will help to unterstand the relation between health and work (hope you agree!)

• Same design for the National Cohort• Need for cross-national comparison (Share)

31

Universität UlmRichard Peter (Projektleiter) Jean-Baptist du Prel

infas Helmut Schröder (Projektleiter) Jacob SteinwedeAnne Kersting

Universität Magdeburg Enno Swart (Projektleiter) Stefanie MarchDorothea Thomas

Bergische Universität Wuppertal Bernd Hans Müller (Projektleiter)Juliane HardtMelanie EbenerMario Iskenius Martin Willner

Töres Theorell

associated partner: Hans Martin Hasselhorn, Uwe Rose (BAuA)

Institut für Arbeitsmarkt- und Berufsforschung Angela Rauch (Projektleiterin) Stefan Bender Markus PrombergerPatrycja SciochAnita TischSilke Tophoven Mark Trappmann

lidA - Konsortium

32

stefan.bender@iab.de

www.iab.dewww.lida-studie.de

33

34

Backup

Employment status by age, born 1959

35

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43

0100,000200,000300,000400,000500,000600,000700,000800,000900,000

1,000,0001,100,000

1975

1976

1977

1978

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49

0100,000200,000300,000400,000500,000600,000700,000800,000900,000

1,000,0001,100,000

full-time part-time marginal employment vocational trainingrecipient of social benefit

Employment status by age, born 1965

The lidA-cohortsEmployment Status

36

4 3 4 4 4

5041 35

29 25

10

1414

1413

1617

2124

25

20 23 25 28 33

0

10

20

30

40

50

60

70

80

90

100

Geburtskohorte1947

Geburtskohorte 1953

Geburtskohorte 1959

Geburtskohorte1965

Geburtskohorte1971

in P

roze

nt

Höchster allgemeiner Schulabschluss 2008

ohne allgemeinen Schulabschluss Haupt-/Volksschulabschluss

Abschluss der polytechnischen Oberschule Realschul- oder gleichwertiger Abschluss

Fachhochschul- oder Hochschulreife

Quelle: Statistisches Bundesamt 2009. Eigene Darstellung.

The lidA-cohortsEducation