AHEAD WP I, II Health and Morbidity

1. AHEAD WP I, IIHealth and Morbidity Brian Nolan, Richard Layte, Anne Nolan (ESRI) Stanislawa Golinowska, Agnieszka Sowa, Roman Topor-Madry (CASE)

2. AHEAD WP I • Aim is to describe and econometrically model health status and health services use by age and socio-economic circumstances • Based on data for (most) EU-15 members in the ECHP, 1995 -2001 • To inform analysis of implications of population ageing for health care resources

3. Analysing Health Status • Look at how health status measures vary by age across countries, for men and women • Multivariate analysis of determinants of health - age, gender, education, marital status, employment status and income • Focus is on age “effect” on health before and after socio-economic controls

4. Percentage Reporting Chronic illness by age, Men - 1995

5. Predicted probability of reporting a chronic illness (controlling for socio-economic characteristics) by age, Men - 1995

6. Key Messages on Age and Health • Strong observed relationship between self-reported health status and age for both men and women, but gradient varies a good deal across countries • Controlling for socio-economic characteristics substantially reduces age-health relationship • Substantial variation in degree of remaining “age effect” across countries

7. Analysis of Health Services Use • Descriptive picture of number of GP visits and hospital nights in year by age across countries, separately for men and women • Multivariate analysis of determinants of GP and hospital utilisation, incorporating age, gender, education, marital status, employment status, income and household composition • Mulivariate analysis of utilisation also controlling for health status

8. Number of GP visits by age, Men - 1995

9. Predicted number of GP visits (controlling for age and socio-economic characteristics) by age, Men - 1995

10. Predicted number of GP visits (controlling for age, socio-economic characteristics and health status) by age, Men - 1995

11. Predicted number of GP visits by age, All ECHP, Men - 1995

12. Key Messages on Age and GP Visits • Number of visits increases markedly with age in every country, but much more in some than others • Controlling for socio-economic characteristics flattens this relationship, so in some countries very modest age “effect” remains • Controlling also for self-reported health status substantially reduces age effect, not now consistently significant in most countries

13. Number of hospital nights by age, Men - 1995

14. Predicted hospital nights (controlling for age and socio-economic characteristics) by age, Men - 1995

15. Predicted hospital nights (controlling for age, socio-economic characteristics and health status) by age, Men - 1995

16. Predicted number of hospital nights by age, All ECHP, Men - 1995

17. Key Messages on Age and Hospital Nights • Number of nights increases with age but less consistent than GP visits • Controlling for socio-economic characteristics flattens this relationship – for some countries few significant age “effect” remain • Controlling also for self-reported health status nearly all the age coefficients are insignificant

18. WPI Summary • Increasing age is associated with worse self-assessed health in a cross-section; partly due to socio-economic composition • Increasing age is also associated with more use of health services, much of this is attributable to socio-economic composition • Differences in self-reported health account for most of remaining cross-sectional age-use relationship • Substantial variation across countries in age-health and age-service use relationships

19. AHEAD WP II • Aim is to analyse health status and use of health services in selected new Member States • Bulgaria, Estonia, Hungary, Poland, Slovakia • Uses survey and administrative data, estimates econometric models, and looks at trends over time

20. Share of elderly (65+) in the population

21. 2.5 2 Bulgaria Estonia 1.5 1 1970 1980 1990 2000 2010 Total fertility rate Hungary Poland Slovakia

22. Life expectancy at birth total

23. Infant mortality

24. Epidemiological development • Improving health status indicators such as life expectancy and infant mortality since mid-1990s, but significantly behind EU-15 • Disease incidence: • Increasing incidence of cancer, • rapid increase in tuberculosis early 1990s (transition crisis), esp. Estonia, Bulgaria • increasing incidence of mental disorders – alcohol-related • Health adjusted life expectancy gap vis-à-vis EU-15 8 years, life expectancy gap 5 years

25. Self-Assessed Health

26. Influences on Self-Assessed Health

27. Health status – summary • Poorer health status related to: • Old Age • Sex – being female • Labour market inactivity • Low education level • Rural population Good health status related to: • Higher education level • Higher income • Not living single

31. Medical services utilization - summary GP more frequent utilization: • Poor health status • Old Age • Sex – being female • Labour market inactivity • Higher income and education confirmed only in Poland Specialist more frequent utilization: • Sex – being female • Higher education level • Poor health status • Labour market inactivity • Higher income Hospital more frequent utilization: • Poorer health status • Higher income, higher education and inactivity confirmedonly in Poland

32. Health services utilization: Key Trends • Hospital utilisation – the biggest driver of health care costs, 40%-50% of total • Increasing hospital admissions in Hungary, Poland and Bulgaria: Per 1001990 2002 Bulgaria 19.0 16.4 Estonia 18.5 19.1 Hungary 21.8 24.6 Poland 12.1 17.5 Slovakia 16.4 19.0 • Role of primary care still being developed