Life expectancy and healthy life expectancy in European countries Abstract Jana Langhamrová, Lenka Vraná, Petra Dotlačilová, Tomáš Fiala University of Economics, Prague The paper will analyse and compare trends in life expectancy and healthy life expectancy in selected European countries from 15 to 20. The length of human life can be expressed by the indicator of life expectancy of an x-year old person. Life expectancy at births is understood as the average age of the deaths in a stationary population. But the healthy life expectancy can be considered as an indicator that tells us how many of these years are spent by the people in good health. In this paper data about life expectancy and healthy life expectancy at birth and of a 5-yearold person for selected European countries (Belgium, Denmark, Germany, Czech Republic, Greece,, France, Italy, Netherlands, Portugal,, Poland, Hungary, Estonia) will be compared. Data will be examined separately for men and women in the period 15-. Calculated absolute and relative changes in life expectancy and healthy life expectancy between years as well as differences between life expectancy and healthy life expectancy will be supplemented by figures and the graphical visualization of the data. Introduction In the context of increasing life expectancy there are often questions as how many years will people live or where are actually the limits of human life? There are several opinions that will not be discussed here. The aim of this paper is to highlight the fact that mortality rates are improving and life expectancy is increasing and the number of old people in the population is growing. This is associated with aging of the population in the top of the age pyramid, also called absolute aging. Scientists say that the human body can live up to 0 years. This is the age that people could reach in the second half of this century if the cure for malignant neoplasms will be found. It would be the similar situation as the discovery of penicillin which initiated the rapid increase of life expectancy. Therefore it is possible to ask whether the additional years of life will be spend in relatively good health or whether it will be the years lived in diseases. Nowadays the term life expectancy in good health or healthy life expectancy is used often in this context. The advantage and disadvantage of this indicator is its qualitative character. Unlike life expectancy, healthy life expectancy tells us more about the quality of life. Indicators of prevalence, incidence, disability and absence of disability Life expectancy at birth and its increase was in the past supposed to be an indicator of improving health. But when life expectancy exceeded years many scientists wondered whether that extension of the length of life would consist only of the years in disease. As the linkages between levels of mortality and morbidity in the developed countries started to weaken, three scenarios of mortality and morbidity were formulated (Rychtaříková []). 1
The first of these three is the theory of compression of morbidity, where the reduction in the mortality is associated with better health (Fries [3], [4] and [5]). The theory of compression of morbidity assumes that chronic, severe or fatal illnesses will be compressed to a short period before death. People will therefore live longer and the elderly will have fewer health problems. Another idea was the expansion of morbidity theory, which states that the extra years are mostly spent in poor health (Gruenberg [], Kamer [7], Olshansky et. al. []). And the third is the dynamic equilibrium theory, which states that the proportion of morbidity in the additional years of life wouldn t change. It means morbidity increases proportionally with the increase in life expectancy. People would live longer and the ratio between the years of life in good and poor health would remain the same. Rychtaříková [] states that after the retreat of infectious diseases many chronic diseases took an integral part of human life. They are the long-term illnesses, which may not restrict men s life and his self-sufficiency and may not even be the cause of death but they worsen health. Therefore there are new possibilities emerging, like the characteristics of disability, in addition to the analysis of the classic indicators of mortality, life tables, morbidity, prevalence rate (proportion of the population found to have a disease) and incidence rate (ratio between population newly found to have a disease and the mid-year population). Disability is an indicator of health restrictions. It is an indicator of the disease severity as well as of the quality of life. The definition of health in this context according to the World Health Organization (WHO) changes and health is considered as not only the absence of disease but also a state of complete physical, mental and social well-being, hence the quality of life. The number of years that a person will live with or without a disability is considered to be a suitable indicator of health status of the population. Indicator of absence of disability DFLE (Disability-free Life Expectancy) is calculated as combination of the life tables and prevalence of good health. It indicates how many years in good health remain of the life expectancy and it is calculated mostly for ages 0 and 5 years separately for men and for women. This indicator can be computed with modification of Sullivan method for calculating healthy life expectancy (Demographic information portal [1]): DFLE x 1 i x L * prev i l x i, where l x is the number of surviving to exact age of x years, L x is the number of years lived by population in exact age x years and prev x indicates the prevalence of good health at age of x. DFLE becomes a commonly used indicator and it is published by Eurostat. The indicator is sometimes called HLY as abbreviation for English term Healthy Life Years. HLY results should be used with caution. The main problem is the comparability of the input data. There is important question whether the data about health status are from registers or from surveys. In Europe there is survey called ECHP (European Community Household Panel). It is repeated every year since 14 and it includes people at age of 1 and older. Data have the same methodology. Another European health survey is SILC (Statistics on Income and Living Conditions). One of its modules focuses on the investigation of health status, the subjectively perceived health, chronic disease, and limitation of daily activities. (1.1) 2
Healthy life expectancy According to Eurostat healthy life expectancy measures the average number of years that a person born in a given year will spend in good health. Healthy life expectancy is an indicator that combines information on mortality and morbidity. To perform a calculation the proportions of the population in good and in poor health by age and specific mortality data are needed. The indicator is calculated separately for men and women. To express the life expectancy in health we theoretically use three methods of calculation. The easiest way is Sullivan's method (Sullivan []). It is used most often due to the good availability of data. e ( h) x h 1 ( ) L i x i l x, where e x (h) is an indicator of the life expectancy in the health of the person at the exact age of x, L x (h) = L x z x and expresses total number of years that the population of l x will live between exact ages x and x + 1 in health. Symbol z x indicates the proportion of the year that was spent in health by an average person at age x. Data Data were taken from the Eurostat website. Eurostat states that the figures are comparable for the period 15 2001. Then there is an extrapolation over 2002 and which ensures a similar comparability for the estimated values for these two years. Actually, the restrictions on the comparability across countries until data apply on the "level" of the Healthy Life Years but not on the evolution of the indicator. As will be seen further, between and the methodology of the calculation of the healthy life expectancy in some countries was changed. In such cases the change could lead to a sharp increase or decrease of this indicator due to its previous development. (1.2) Comparison of life expectancy and healthy life expectancy in selected European countries In this paper we compare the life expectancy and healthy life expectancy (HLE) at birth and at age of 5 years for selected European countries (Belgium, Denmark, Germany, Czech Republic, Greece,, France, Italy, Netherlands, Portugal,, Poland, Hungary and Estonia). Data are examined separately for men and women in the years 15. Figure 1 shows the life expectancy and the healthy life expectancy at birth for women in. The chart also adds a proportion of a time that a woman spends in relatively good health. The graph shows that France is the country with the highest life expectancy from the selected countries (5.7 years), however only 74 % of these years are spent in health. The largest share of life spent in relatively good health is in Greece, where the healthy life expectancy reaches 7 years out of 3 years of the total life expectancy. 3
life expectancy 7 % in good health 1 % 3 % 3 % 7 % 1 % 2 % 74 % 5 % 0 % 2 % 2 % 1 % 7 % life expectancy 75 % in good health 7 % 7 % 71 % 73 % 1 % 71 % 7 % 7 % 71 % % 74 % 77 % 74 % Figure 2 shows the same chart for men. From the values of the life expectancy spent in relatively good health and the life expectancy it is clear that men have the proportion of these two indicators generally higher than women. The highest ratio is in Greece as well. Figure 1 - Comparison of the life expectancy and the healthy life expectancy of women at birth in selected European countries in 0 50 40 30 20 0 Life expectancy at birth, own calculations Figure 2 - Comparison of the life expectancy and the healthy life expectancy of men at birth in selected European countries in 0 50 40 30 20 0 Helthy life expectancy at birth Life expectancy at birth, own calculations 4
life expectancy 42 % 3 % 4 % 54 % 72 % in good health 54 % 57 % 44 % 37 % 4 % % 52 % 43 % 50 % life expectancy 33 % 45 % 42 % 2 % 5 % in good health 3 % 34 % 47 % 5 % 47 % 2 % 31 % 40 % 42 % Figures 3 and 4 show the life expectancy and HLE for 5-year-old women and men in. It is apparent that in older ages there is a decline in the proportion of time spent in relatively good health. For both sexes the highest ratio of years spent without health restrictions occurs in Denmark (5 % for women, 72 % men). The lowest ratio of time spent in good health for women is in Estonia and Portugal (2 %) and for men in Germany (37 %) and Estonia (3 %). Figure 3 - Comparison of the life expectancy and the healthy life expectancy of women at age 5 in selected European countries in 20 15 5 0 Healthy life expectancy at age 5 Life expectancy at age 5, own calculations Figure 4 - Comparison of the life expectancy and the healthy life expectancy of men at age 5 in selected European countries in 20 15 5 0 Healthy life expectancy at age 5 Life expectancy at age 5, own calculations 5
healthy life expectancy healthy life expectancy In figures 5 and is obvious the development of healthy life expectancy at birth for women and men in selected European countries in the period 15-. There is a clear change in the methodology, which took place between and. Data are not always available at all the countries for the entire period. And it is also important to say that in some years are estimates, as reported by Eurostat. Figure 5 Development of the healthy life expectancy at birth for women in selected countries in period 15 75 5 55 50 45 15 1 17 1 1 2000 2001 2002 2005 200 2007 200 200 20 Figure - Development of the healthy life expectancy at birth for men in selected countries in period 15 75 5 55 50 45 15 1 17 1 1 2000 2001 2002 2005 200 2007 200 200 20
healthy life expectancy healthy life expectancy The charts with the development of the healthy life expectancy for women and men at age 5 (figures 7 and ) look similarly. There is also a noticeable effect caused by the change of the methodology between and ; however the decrease or increase of indicators of HLE for 5 old between these years isn t as strong (in absolute terms) as it was for the HLE at birth. Figure 7 - Development of the healthy life expectancy at age 5 for women in selected countries in period 15 15 3 0 15 1 17 1 1 2000 2001 2002 2005 200 2007 200 200 20 Figure - Development of the healthy life expectancy at age 5 for men in selected countries in period 15 15 3 0 15 1 17 1 1 2000 2001 2002 2005 200 2007 200 200 20 7
life expectancy life expectancy The indicator of life expectancy at birth for women and men has generally increased during the period. Also it is clear that the distances between the selected countries narrow. Figure - Development of the life expectancy at birth for women in selected countries in period 15-0 5 0 75 5 15 1 17 1 1 2000 2001 2002 2005 200 2007 200 200 20 Figure - Development of the life expectancy at birth for men in selected countries in period 15-0 5 0 75 5 15 1 17 1 1 2000 2001 2002 2005 200 2007 200 200 20
life expectancy life expectancy The life expectancy for 5-year-old women and men also tends to increase during the period. Figure - Development of the life expectancy at age 5 for women in selected countries in period 15-24 22 20 1 1 14 15 1 17 1 1 2000 2001 2002 2005 200 2007 200 200 20 Figure - Development of the life expectancy at age 5 for men in selected countries in period 15-24 22 20 1 1 14 15 1 17 1 1 2000 2001 2002 2005 200 2007 200 200 20
In addition to this classical analysis of the subject, next figures show the development of the life expectancy and the healthy life expectancy in somewhat unconventional way. The charts show the development of healthy life expectancy and life expectancy for selected countries divided by gender and the dependency between these two indicators. Each point on the curve indicates one year and some of the years have been highlighted for clarity. If the life expectancy and HLE would increase at the same relative pace over the time and if the scale would be the same on both axes there would be 45-degree line in the chart. We decided for the different axis scaling to make the lines more visible. As the lines in the charts are more complex it suggests there is no dependency between the life expectancy and HLE that could be easily described. When the connecting line goes steeply upward (or even rises "back" to the left) it indicates compression of morbidity (extending the healthy life expectancy, stagnation or even decline in the life expectancy). On the other hand the horizontal trend of the connecting line (or even the decreasing trend) suggests an expansion of morbidity (overall life expectancy increases, but a healthy life expectancy is stagnating or even declining) people live longer, but the added years are spend not in the full health. Figure 13 a) - d) - Development of the healthy life expectancy and the life expectancy at birth for women in selected countries in period 15-13 a) Belgium 15 4 2 5 5 0 1 2 3 Life expectancy at birth 13 b) Denmark 4 2 15 5 77 7 7 0 1 2 Life expectancy at birth 13 c) Italy 74 72 15 4 2 1 2 3 4 5 Life expectancy at birth 13 d) Portugal 15 3 1 5 57 55 53 51 7 7 0 1 2 3 4 5 Life expectancy at birth
Figure 14 a) - d) - Development of the healthy life expectancy and the life expectancy at birth for men in selected countries in period 15-14 a) Belgium 14 b) Denmark 4 2 15 4 2 15 5 73 74 75 7 77 7 Life expectancy at birth 72 71 7 5 4 3 2 15 14 c) Italy 74 75 7 77 7 7 0 Life expectancy at birth 72 73 74 75 7 77 7 Life expectancy at birth 14 d) Portugal 1 15 5 5 57 5 55 54 71 72 73 74 75 7 77 Life expectancy at birth 7 7 Figure 15 a) - d) - Development of the healthy life expectancy and the life expectancy at age 5 for women in selected countries in period 15-15 a) Belgium 13 15 1 20 21 Life expectancy at birth 22 15 b) Denmark 15 14 13 15 17 1 1 20 Life expectancy at birth
15 14 13 7 15 c) Italy 15 1 20 21 22 23 Life expectancy at birth 7 5 4 3 15 15 d) Portugal 1 1 20 21 22 Life expectancy at birth Figure 1 a) - d) - Development of the healthy life expectancy and the life expectancy at age 5 for men in selected countries in period 15-1 a) Belgium 15 14 15 1 17 1 Life expectancy at birth 1 b) Denmark 14 13 15 7 14 15 1 17 Life expectancy at birth 15 1 c) Italy 7 15 1 d) Portugal 7 15 1 17 1 1 Life expectancy at birth 5 4 14 15 1 17 1 Life expectancy at birth 1 Acknowledgement This article has been supported by the grant IGA VSE 24/2013 "Mortality and aging of the Czech population."
References [1] Demografický informační portal. Demographic information portal. Available from WWW: <http://www.demografie.info.cz > [2] Eurostat. Available from WWW: <http://ec.europa.eu/eurostat> [3] Fries, J. F.: Aging, natural death, and the compression of morbidity. N Engl J Med 303, 10. p. 130-135. [4] Fries, J. F.: Reducing disability in older age. JAMA, 2002. p. 314-31. [5] Fries, J. F.: The compression of morbidity: Near or far?. Milbank Memorial Fund Quarterly, 1. p. 20-232. [] Gruenberg, E. M.: The failures of Access. Milbank Memorial Fund Quarterly / Health Society, 177. p. 3-24. [7] Kamer, M.: The rising pandemic of mental disorders and associated chronic diseases and disabilities. Acta Psychiatrica Scandinavica 2,10. p. 22-27. [] Langhamrová, Jitka, Miskolczi, Martina, Langhamrová, Jana. Life Expectancy Trends in CR and EU. Prague 22.0. 23.0.. In: International Days of Statistics and Economics at VŠE, Prague. Prague : VŠE,, p. 2 30. ISBN 7-0-175-77-5. [] Olshansky, S. J., Rudberg, M. A., Carnes, B. A., Cassel, C. K., Brody, J.: Trading off Langer for worsening health: the expansion of morbidity hypotesis. Journal of Aging and Health, 3, 2, p. 14-21. [] Rychtaříková, J.: Zdravá délka života v současné české populaci, Demografie, 200, roč. 4, n. 3. p. 1-17. [] Sullivan, D.: A Single Index of Mortality and Morbidity. HSMHA Health Reports,, 171. p. 347 354. Authors: Ing. Jana Langhamrová Department of Statistics and Probability, Faculty of Informatics and Statistics University of Economics, Prague xlanj1@vse.cz Ing. Petra Dotlačilová Department of Demography, Faculty of Informatics and Statistics University of Economics, Prague dotlacilova.petra@gmail.com Ing. Lenka Vraná Department of Statistics and Probability, Faculty of Informatics and Statistics University of Economics, Prague lenka.vrana@gmail.com RNDr. Tomáš Fiala, CSc. Department of Demography, Faculty of Informatics and Statistics University of Economics, Prague fiala@vse.cz 13