Article Text
Abstract
Background Although socioeconomic mortality differences in Germany are well documented, trends in group-specific mortality and differences between the eastern and the western parts of the country remain unexplored.
Methods Population and death counts by level of lifetime earnings (1995–1996 to 2007–2008) and broad occupational groups (1995–1996 to 2003–2004) for men aged 65 years and older were obtained from the German Federal Pension Fund. Directly standardised mortality rates and life expectancy at age 65 were used as mortality measures.
Results Mortality declined in all socioeconomic groups in eastern and western Germany and these declines tended to be larger in higher status groups. Relative socioeconomic differences in age-standardised mortality rates and in life expectancy at age 65 widened over time. Absolute differences widened over the majority of time periods. The widening was more pronounced in eastern Germany.
Conclusions Widening socioeconomic mortality differences in Germany, especially in eastern Germany, show that population groups did not benefit equally from the improvements in survival. The results suggest that special efforts have to be taken in order to reduce mortality among people with lower socioeconomic status, especially in eastern Germany. Health equity should be considered a priority when planning policies, practices, and changes in the healthcare system and related sectors.
- Mortality
- Socio-economic
- Elderly
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Background
During the final decades of the 20th century, socioeconomic differences in mortality were widening both in Western1–3 and in Eastern Europe.4–6 In Eastern Europe, rising mortality inequalities were found to be connected to drastic market-oriented transformations.7
Most evidence on socioeconomic mortality inequalities stems from European countries other than Germany. A few recent studies dealt with Germany and found the expected inverse association between mortality and wealth.8–12 Among these studies, there is only one that assessed mortality gradients in eastern and western Germany.11
Although the existence of socioeconomic mortality inequalities in both parts of Germany is not under debate, evidence on their change is scarce, and (to our knowledge) there is no study that compares changes in socioeconomic mortality inequalities in eastern and western Germany over time. Eastern Germany has experienced radical political and economic transformations and an accelerated mortality decline since German reunification in 1990. However, it is important to understand whether the observed overall progress in health affected all population groups equally, or whether health inequalities increased. The distribution of health is an issue of social justice, and is an indication of the successes and failures of social and economic policies.13
The main aim of this paper is to reveal time trends in mortality by socioeconomic status (SES) among older men in Germany and its former eastern and western parts.
Methods
Data
Population and death counts for German males by SES for the years 1995–2008 were obtained from the German Federal Pension Fund.14 The systems in the German Democratic Republic (GDR) and western Germany were different, but the principle of granting pension income based on the length of time in employment and annual earnings was, however, comparable.15 ,16 The GDR pension system covered most of the population because self-employment was virtually non-existent and because, unlike in western Germany, civil servants contributed to the pension system.11 ,15 More details about the German pension system and the integration of the eastern German system are provided elsewhere.16
The data cover 86% of all men aged 65 years and older in Germany (see ref. 11 for a detailed description of the data). Women were excluded from the analyses because the low labour force participation rates among the female cohorts under study, especially in western Germany, meant that they had lower pension incomes. However, a woman's SES may not be adequately reflected in these figures as her household income may significantly exceed her own income. Men with a migration history and non-German citizenship were not included because their working histories were often incomplete.11 ,15
Two SES measures, pension income and type of former occupation, are used. The former represents lifetime earnings, which are multiplied by an annuity value in order to obtain the pension income. The total number of earning points gained during 1 year refers to the ratio between personal pensionable incomes and average pensionable income in that year. Lower and higher incomes were credited proportionally up to a certain income ceiling. Periods of unemployment or extended sick leave were credited with fewer earning points than before the non-productive period.11 ,15
The data on lifetime earnings were initially divided into 5-point categories (0–4, 5–9, …, 60–64, 65+). Individuals with the lowest lifetime earnings under 30 points (17% of all individuals) included poor people and those with additional incomes from self-employment, private business, bank capital, and so on. Additional income not derived from dependent employment is not credited in the pension insurance, and is therefore not reflected in the lifetime earnings figures.11 ,17 This heterogeneous group was excluded from our analysis. The remaining population was aggregated into six income groups ranging from lower to higher incomes. Our prior experiments with different definitions and numbers of groups showed that six broad groups are more suitable than deciles11 for the classification of lifetime earnings. This classification also ensures better comparability of mortality estimates across time and space.
Until 2004, the pension insurance system was divided into three branches based on the type of occupation. Since these insurance branches merged in 2005, information on pensioners’ former occupation (defined as the last job held before retirement) is no longer available. A distinction was made between white collar and blue collar jobs. Individuals who had ever worked in the mining industry (less than 10% of the pensioners) were classified as ‘miners’.
Data were obtained as count data, in which population and deaths were split according to the lifetime earnings and occupational groups, calendar years, 5-year age groups from 65–69 to 100 and older, and place of residence (eastern or western Germany), with Berlin being divided into eastern and western parts.
The final dataset excluding those individuals with the lowest lifetime earnings covered seven time periods: 1995–1996 with 6.32 million person-years at risk (of which 77.0% were in western Germany) and 0.39 million deaths; 1997–1998 with 6.37 million (75.6% in western Germany) and 0.39 million deaths; 1999–2000 with 6.68 million (75.8%) and 0.39 million deaths; 2001–2002 with 7.33 million (75.6%) and 0.40 million deaths; 2003–2004 with 8.12 million (75.5%) and 0.42 million deaths; 2005–2006 with 8.89 million (75.1%) and 0.42 million deaths; and 2007–2008 with 9.40 million (74.7%) and 0.44 million deaths. Data on occupation were unavailable for 2005–2008.
Study methodology
Two measures are used as mortality outcomes: age-standardised death rates (SDRs), with the WHO 1976 standard population, and remaining life expectancy at age 65.18 Standard errors of the group-specific mortality measures are negligible and not shown in the analysis. For each lifetime earnings group, SDR and life expectancy values are computed for the time periods from 1995–1996 to 2007–2008. The corresponding values for the occupational groups are computed for the time periods from 1995–1996 to 2003–2004. Assessment of the socioeconomic differences in mortality relies on comparisons between the two extreme income groups and the two occupational groups.1 ,6 For the pension income, the low SES group with lifetime earnings ranging from 30 to 39 points (comprising 14.5% of the study population) is compared with the high SES group with lifetime earnings of 65 or more points (14.3% of the study population). Blue collar workers are compared with white collar workers with respect to the occupational category. In all time periods, the low SES groups have the highest, whereas the high SES groups always have the lowest, mortality levels.
Results
The absolute and relative differences in SDRs and remaining life expectancies among men at age 65 tended to widen over time, and this widening was more pronounced in eastern Germany.
In the mid-1990s, mortality differences by pension income were about the same in eastern and western Germany. Over time, the differences widened but they levelled off somewhat during the 2000s (table 1). High-income pensioners in eastern Germany experienced the strongest mortality declines over time (table 2). For example, the life expectancy difference between high-income and low-income pensioners was 3.3 years in western Germany and 3.5 years in eastern Germany in 1995–1996. This difference increased to 4.8 and 5.6 years, respectively, in 2007–2008 (table 1). Due to the strong mortality decline among eastern German high-income pensioners, their mortality in 2007–2008 was less than that of their western German counterparts (table 2). Thus, in 2007–2008, the mortality gap between the highest and lowest income groups was more pronounced in eastern Germany than in western Germany (table 1).
In all time periods, the mortality differences between blue collar and white collar workers were smaller than those between the extreme income groups. The occupational differences were smaller in eastern Germany than in western Germany. Between 1995–1996 and 1997–1998, the occupational mortality differences increased in both eastern and western Germany. In subsequent years, the gap remained at almost the same elevated level (table 1).
Overall, mortality was the lowest in the high-SES groups and mortality declines were the largest in these groups (table 2). With respect to life expectancy, the differences followed the same pattern. SDRs showed partly different trends in absolute and relative measures (table 1).
Discussion
Our results present evidence of widening mortality differences by socioeconomic groups among older men, in both eastern and western Germany. We also found that the overall levels of mortality inequality across all lifetime earnings groups and all occupational groups increased in the 1990s, and remained at almost the same elevated level through the 2000s (online supplementary annex).23 The biggest increase in mortality inequalities between the lowest and highest socioeconomic groups occurred in the mid-1990s (between 1995–1996 and 1997–1998). In subsequent years, a systematic growth of the differences between two extreme socioeconomic groups was observed only in eastern Germany (until 2001–2002) and mostly concerned mortality inequalities by lifetime earnings.
Limitations of the data, derived from administrative databases of the German Federal Pension Fund, have to be taken into account when interpreting the results.11 ,15 ,17 First, the dataset was restricted to male German pensioners. The exclusion of foreigners may have led to some overestimation of mortality in lower socioeconomic groups due to ‘healthy migrant’ or ‘unhealthy re-migration’ effects.19 ,20 Second, the data do not cover civil servants and self-employed people with lower mortality and are restricted to pensioners with long-term pension fund contributions. As these two restrictions may exclude pensioners with very high and very low mortality, there may be some underestimation of the mortality gap between the low and high SES groups. The increase in this gap over time may also be slightly underestimated as higher SES groups experienced faster mortality declines. However, the excluded population groups are fairly small, and therefore would not greatly influence the results. Furthermore, the overall mortality of the men included in the database is almost the same as the mortality of the male population aged 65 and older, according to official statistics. Third, the occupational categories in our dataset are very broad and are not strictly hierarchical, which may also lead to an underestimation of the “real” extent of mortality inequalities. Although some skilled blue collar workers may earn more than their white collar counterparts, we believe that the division between manual and non-manual labour is properly captured. Finally, the recorded lifetime earnings may somewhat understate the real levels of income and wealth of some pensioners. In particular, some pensioners in the lowest recorded income group probably have additional financial resources—which is why this group has been excluded from the analysis on pension income. This phenomenon is more common among western Germans. Thus, some differences in the meaning of SES at the same pension income level in eastern and western Germany have to be assumed. All of these limitations are related to the nature of the dataset, which is not designed for the monitoring of mortality changes by SES. However, this unique dataset is almost the only reliable data source for the assessment of socioeconomic mortality differences in Germany. Despite numerous data limitations, we believe that the analysis yields reliable quantitative results and provides meaningful insights into socioeconomic mortality differences in the largest country of the European Union.
The results throw light on trends in socioeconomic mortality differences in Europe and differing trends in Eastern and Western Europe.1–7 A recent study by Majer et al21 provides estimates of life expectancy at age 65 according to three educational levels in 1995–2001 for 10 Western European countries excluding Germany. In this respect, one can note that occupational differences in our study are comparable (or slightly smaller) with the differences between lower and tertiary education in other Western European countries. Differences between the extreme income groups in Germany are much higher than educational differences.
Our results show that older, better-off eastern Germans benefited most from the overall socioeconomic improvement after reunification and in this way have significantly contributed to the East–West mortality convergence. This must be taken into account in discussions on factors behind the reduction of the East–West mortality gap.22
The findings of the persisting and even widening socioeconomic mortality differences over the 1990s and 2000s in Germany, especially in its eastern part, are worrying. Our study suggests that the social and economic policies implemented after reunification did not ensure social equity or equal health improvements across socioeconomic groups. The persisting or increasing health disadvantages of lower socioeconomic groups can threaten the sustainability of health improvements at the country level. Thus, intersectoral policies tackling both inequities in medical care and social determinants outside the healthcare system should be substantially strengthened.13 However, more detailed epidemiological investigations are needed in order to identify factors underlying the different progress made by people with different levels of SES in achieving longevity.
What is already known on this subject
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Prior studies have documented socioeconomic mortality disparities in Germany, but changes in these disparities remain unexplored, especially differential trends in the eastern and western parts of the country. Despite well-documented health progress in eastern Germany after reunification, it is not known how these improvements differed depending on the level of wealth.
What this study adds
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Changes in socioeconomic inequalities in mortality were documented in eastern and western Germany from 1995–1996 to 2007–2008. Relative inequalities increased over this time period, particularly in eastern Germany, suggesting slower progress in health improvement after reunification among lower socioeconomic groups.
Acknowledgments
This study is part of the Vanguard project at the Max Planck Institute for Demographic Research.
References
Supplementary materials
Supplementary Data
This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.
Files in this Data Supplement:
- Data supplement 1 - Online annex
Footnotes
Contributors EUBK had the initial idea for the study, analysed the data and outlined the paper. DJ and VMS discussed core ideas, performed data analysis and commented on all drafts.
Competing interests None.
Provenance and peer review Not commissioned; externally peer reviewed.