1. Age, wellbeing and inequality Evidence from the English Longitudinal Study of Ageing James Nazroo, Stephen Jivraj, Tarani Chandola and Bram Vanhoutte Sociology, Social Statistics and Cathie Marsh Centre james.nazroo@manchester.ac.uk

2. An ageing world [Nothing] is more likely to shape economic, social, and political developments in the early twenty-first century than the simultaneous aging of Japan, Europe, and the United States … The human life cycle is undergoing unprecedented change. To preserve economic security, we must adapt the social institutions built around it to these new realities. Demographic aging brings with it a systematic transformation of all spheres of social life … beneath even the daunting fiscal projections, lies a longer-term economic, social and cultural dynamic … What will it be like to live in societies that are much older than any we have ever known or imagined? The Commission on Global Aging (1999)

3. Changing images of ageing The title means ‘my mother, poor thing’ Contemporary critics found this image shocking at a time when it was thought that the elderly should be represented with respect or with sentiment. Sickert instead treads a fine line between complete honesty and brutality applying the paint in small dabs and touches so that the face has the crumbling texture of great age. Mamma Mia Poveretta (1901-04) Walter Richard Sickert

4. A Third Age? Healthy, wealthy and engaged in society  Post-retirement, post-parenting, but pre-dependency.  Contributing to society:  Voluntary/community activities;  Political/civic engagement.  Consuming and enjoying life, leisure and pleasure – cultural mainstream.  Self-fulfilment:  Having a role;  Having status;  Having fun.  More generally an ‘active ageing’ policy agenda is being promoted.  But active ageing, and the resources to enjoy a ‘third’ age, are strongly related to socioeconomic position – in what ways do class inequalities persist post-retirement.

5. The English Longitudinal Study of Ageing (www.ifs.org.uk/elsa)  Sample at wave 1 (2002) was approximately 11,400 people born before 1 st March 1952 who were in the private household sector. Refreshed with younger people (50-54) at both waves 3 and 6, and boosted with a cross-section (50-74) at wave 4.  Drawn from Health Survey for England (wave 0).  Includes spouses outside the age range and ‘new’ partners who joined the household since wave 0.  Face to face interview every two years since 2002, with a biomedical assessment carried out by a nurse every four years.  Those incapable of doing the interview have a proxy interview.  End of life interviews are carried out with the partners or carers of people who died after wave 1. A panel study of people aged 50 and older, just begun our sixth wave of data collection, with additional wave 0 data available.

6. ELSA: broad questionnaire coverage  Demographics  Administrative data  Self-assessed and oral health  Diagnosed disease & symptoms  Quality of received medical care  Activities of daily living and Instrumental ADLS  Eyesight, hearing, pain, falls  Mental health  Health behaviours  Cognitive function measures  Physical performance measures  Biomedical measures  Housing (tenure, quality, value)  Household wealth and income  Relative deprivation  Pensions and retirement  Employment status, earnings and job characteristics  Consumption/spending  Psychosocial factors & well-being  Social, cultural and civic activities  Expectations for the future  Life history: childhood, education, work, marriage/family, migration, health, trauma

7. Wellbeing measures in ELSA  Evaluative, hedonic and eudaimonic measures included.  General Health Questionnaire (12 item version), every second wave  Center for Epidemiological Studies Depression scale (8 item dichotomous version)  Life satisfaction (Diener)  Quality of Life (CASP – Control, Autonomy, Self-Realisation and Pleasure – 19 item version)  Largely cover negative dimensions, but not entirely  Experienced wellbeing is included in wave six (just in the field)

8. Analytical methods  Longitudinal multilevel models, observations nested within individuals, to give overlapping cohorts.  Model the association between wellbeing and age, with adjustment for a range of covariates:  Demographic factors (gender and ethnicity)  Marital status  Socioeconomic factors (occupational class, economic activity and education)  Health (limiting longterm illness, ADLs, chronic conditions)  Social support (close contacts, support from contacts, caring and volunteering activities)  Followed up for eight years (six years for some of the analyses).  Some analyses stratified by population group (wealth quintiles).

9. Age and quality of life: a longitudinal analysis (CASP-19 score adjusted for gender and ethnicity)

10. Age and depression: a longitudinal analysis (CES-D score adjusted for gender and ethnicity)

11. Age and satisfaction with life: a longitudinal analysis (Diener score adjusted for gender and ethnicity)

12. Contrasting images of ageing: Reflections of class? A political storm is brewing over proposals to raise the state pension age to 67 (BBC News 2005)

13. The distribution of financial wealth, age 60-74

14. Age, quality of life and wealth: a longitudinal analysis (CASP-19 score adjusted for gender and ethnicity)

15. Age, depression and wealth: a longitudinal analysis (CES-D score adjusted for gender and ethnicity)

16. Age, satisfaction and wealth: a longitudinal analysis (Diener score adjusted for gender and ethnicity)

17. Survival rates by wealth, age 50+ Men Women

18.  Focus is on the retirement transition between waves 2 and 4 of ELSA:  Route into retirement (routine, voluntary, involuntary);  Wealth on retirement,  Respondents who were aged 70 or younger and economically active at wave 2 (n = 1,693).  Observed 573 (34%) transitions into retirement from wave 2 to wave 4.  Change models – including baseline score as an independent variable.  Models account for sample design and non-response. The impact of retirement: Sample and measures used

19. The impact of retirement on wellbeing  Model transitions into retirement compared with those still working, for those aged 70 or younger and who are economically active.  Routine retirement, because ‘reached retirement age’  Voluntary  To enjoy life  To spend time with partner or family  Fed up with job and wanted a change  To give the younger generation a chance  Offered reasonable financial terms to retire early  Involuntary  Ill health (own, or of a relative/friend)  Made redundant  Could not find another job

20. Undifferentiated modelDifferentiated model Remain working0 Start working0.02 (-0.40, 0.44) Remain not working0.44 (0.30, 0.60) Become unemployed-0.05 (-0.71, 0.62) Stop working, sick1.16 (0.66, 1.67) Start looking after the home -0.60 (-1.18, -0.03) Retire0.04 (-22, 0.31) Retire wealthy- Retire not wealthy- Retirement and depression A transition model for those ≤ state pension age Modelling depression score at wave 2: ordinal logistic regression coefficients *Models adjusted for gender, age and depression score at wave 1

21. Undifferentiated modelDifferentiated model Remain working00 Start working0.02 (-0.40, 0.44) Remain not working0.44 (0.30, 0.60)0.46 (0.30, 0.61) Become unemployed-0.05 (-0.71, 0.62)-0.04 (-0.71, 0.62) Stop working, sick1.16 (0.66, 1.67)1.17 (0.66, 1.68) Start looking after the home -0.60 (-1.18, -0.03)-0.60 (-1.17, -0.03) Retire0.04 (-22, 0.31)- Retire wealthy--0.41 (-0.82, 0.01) Retire not wealthy-0.37 (0.03, 0.70) Retirement and depression A transition model for those ≤ state pension age Modelling depression score at wave 2: ordinal logistic regression coefficients *Models adjusted for gender, age and depression score at wave 1

22. Depression and type of retirement transition

23. Age and depression: explaining the relationship (CES-D score adjusted for gender and ethnicity)

27. Age and quality of life: explaining the relationship (CASP-19 score adjusted for gender and ethnicity)

28. Age and life satisfaction: explaining the relationship (Diener score adjusted for gender and ethnicity)

29. Persisting class inequalities: improvements in men’s life expectancy at birth ONS Longitudinal Study 2007

30. Social mobility: odds to be in a professional or managerial class for four age cohorts Year of birth < 19201920-291930-391940-451946-52 Class of origin Semi/un-skilled manual 11111 Skilled manual 1.461.39*1.351.511.26 Administrative/Skilled non-manual 1.86*3.302.762.312.06 Manager/professional 2.764.944.023.403.32 Bold figures p < 0.05, *p < 0.1

31. Concluding comments: well-being in later life  Age and transitions:  Wealth  Marital status (divorce and widowhood)  Health/disability  Retirement status/route (voluntary)  Social class  Cohort and generation:  Occupational structures  Pension arrangements  Retirement choices/opportunities  Marriage choices  But persisting inequalities