[Healthy life expectancy: a critical look at the benefits and potential of the demographic health indicator]. / Gesunde Lebenserwartung: Ein kritischer Blick auf Nutzen und Potenziale des demographischen Gesundheitsindikators.

Demographic ageing yields many societal consequences that depend strongly on the health status of the population. Special indicators have been developed for tracking and assessing population health, which are referred to with the overarching term healthy life expectancy (HLE). The derivation of HLE is intuitive and easily comprehensible. However, an overly simplistic interpretation hides the extreme complexity inherent in adding the health dimension to the life table. This makes HLE compared to classic life expectancy (LE) extremely sensitive to certain conceptual and methodological features. In the article, this is presented in more detail for three aspects: the underlying definition of health, the choice of survey data as a basis for estimating health status, and the reporting behavior of survey participants. It is shown that the impact on HLE can be enormous, leading to considerable bias in the interpretation of levels and trends, but also in the analysis of differences between populations. Nevertheless, the extension of classical LE to HLE is an important achievement that must not be abandoned. Therefore, the article also discusses ways in which the HLE indicator could be made more robust and reliable. Until this is achieved, however, the high methodological sensitivity of HLE must not be ignored if it is used to assess the health status of populations and as a basis for health policy measures.

[The gender paradox in health-impaired lifetime-end of a myth?] / Das Geschlechterparadoxon in der gesundheitlich beeinträchtigten Lebenszeit ­ Ende eines Mythos?

BACKGROUND: Women live longer than men, but they spend more life years with health-impairment. This article examines the extent to which this gender paradox can be explained by two factors: the "mortality effect," which results from the higher life expectancy of women, and "differential item functioning" (DIF), which refers to gender differences in reporting behavior. METHODS: Impaired life expectancy at age 50 is calculated for the health indicators general health, limitations, and chronic morbidity using the Sullivan method. Data on health prevalence are obtained from the 2012 survey "Gesundheit in Deutschland aktuell" (GEDA), data on mortality is taken from the Human Mortality Database. The gender difference in impaired life expectancy is decomposed into the mortality effect and the health effect. The latter is finally adjusted for DIF effects on the basis of vignettes from the 2004 SHARE survey. RESULTS: The gender paradox can be resolved not only partially but completely for all three health indicators considered by the mortality effect and DIF. After taking these two factors into account, the gender difference in impaired life expectancy reverses from higher values for women to higher values for men. DISCUSSION: The causes of the gender paradox are highly complex and the differences between women and men in total and impaired life expectancy are not necessarily going into contradictory directions. The extent of women's higher impaired life expectancy depends decisively on the underlying health indicator and is largely explained by the mortality effect.

The impact of interpersonal reporting heterogeneity on cross-country differences in Healthy Life Years in Europe.

BACKGROUND: The European Union has used Healthy Life Years (HLY) as an indicator to monitor the health of its aging populations. Scholarly and popular interest in HLY across countries has grown, particularly regarding the ranking of countries. It is important to note that HLY is based on self-assessments of activity limitations, raising the possibility that it might be influenced by differences in health reporting behaviours between populations, a phenomenon known as differential item functioning (DIF). METHODS: We estimated DIF-adjusted HLY at age 50 for Belgium, France, Germany, Greece, Italy, the Netherlands, Spain, and Sweden to determine the extent to which differences in HLY might be influenced by reporting heterogeneity across countries. We used anchoring vignettes, taken from the 2004 Survey of Health, Ageing and Retirement in Europe, to estimate DIF-adjusted prevalence rates of activity limitations measured by the Global Activity Limitations Indicator (GALI). The Sullivan method was used to calculate DIF-adjusted HLY. RESULTS: Changes in HLY before and after adjustment ranged from a 1.20-year decrease for men in Italy to a 1.61-year increase for women in Spain. Adjustment for DIF produced changes in the rankings of the countries by HLY, with upward and downward movements of up to three positions. CONCLUSION: Our results show that DIF is likely to affect HLY estimates, thereby posing a challenge to the validity of comparisons of HLY across European countries. The findings suggest that HLY should be used to monitor population health status within a country, rather than to make comparisons across countries.

Trends in Activity Limitations From an International Perspective: Differential Changes Between Age Groups Across 30 Countries.

Objectives: Examine trends in limitations among young (15-39), middle-aged (40-64) and older age-groups (>=65) and their socioeconomic differences. Methods: Population-based European Social Survey data (N = 396,853) were used, covering 30 mostly European countries and spanning the time-period 2002-2018. Limitations were measured using a global activity limitations indicator. Results: Age-differential trends in limitations were found. Activity limitations generally decreased in older adults, whereas trends varied among younger and middle-aged participants, with decreasing limitations in some countries but increasing limitations in others. These age-differential trends were replicated across limitation severity and socioeconomic groups; however, stronger limitation increases occurred regarding less-severe limitations. Discussion: Functional health has improved in older adults. Contrarily, the increasing limitations in younger and middle-aged individuals seem concerning, which were mostly observed in Western and Northern European countries. Given its public health importance, future studies should investigate the reasons for this declining functional health in the young and middle-aged.

Well-Being Adjusted Health Expectancy: A New Summary Measure of Population Health.

We propose a new summary measure of population health (SMPH), the well-being-adjusted health expectancy (WAHE). WAHE belongs to a subgroup of health-adjusted life expectancy indicators and gives the number of life years equivalent to full health. WAHE combines health and mortality information into a single indicator with weights that quantify the reduction in well-being associated with decreased health. WAHE's advantage over other SMPHs lies in its ability to differentiate between the consequences of health limitations at various levels of severity and its transparent, simple valuation function. Following the guidelines of a Committee on Summary Measures of Population Health, we discuss WAHE's validity, universality, feasibility sensitivity and ensure its reproducibility. We evaluate WAHE's performance compared to life expectancy, the most commonly used indicators of health expectancy (HE) and disability-adjusted life expectancy (DALE) in an empirical application for 29 European countries. Data on health and well-being are taken from the 2018 EU-SILC, and the life tables are from Eurostat. DALE is taken from the database of the Global Burden of Disease Programme. WAHE's sensitivity to univariate and multivariate state specifications is studied using the three Minimum European Health Module health dimensions: chronic morbidity, limitations in activities of daily living, and self-rated health. The empirical tests of the indicators' correspondence reveal that WAHE has the strongest correlation with the other SMPHs. Moreover, WAHE estimates are in agreement with all other SMPHs. Additionally, WAHE and all other SMPHs form a group of reliable indicators for studying population health in European countries. Finally, WAHE estimates are robust, regardless of whether health is defined across one or multiple simultaneous dimensions of health. We conclude that WAHE is a useful and reliable indicator of population health and performs at least as well as other commonly used SMPHs. Supplementary Information: The online version contains supplementary material available at 10.1007/s10680-022-09628-1.

The Gender Gap in Life Expectancy in Urban and Rural China, 2013-2018.

BACKGROUND: Gender differences in mortality are embedded within mortality transitions. Rural residents generally lag behind their urban counterparts in the transitions. The study objective is to identify major causes of death that drive gender differences in mortality in urban and rural China. METHODS: We use age-, gender-, urban-rural- and cause-specific mortality data (2013-2018) derived from the national mortality surveillance system that covered about 24% of the Chinese population. We apply Arriaga's method to decompose age- and cause-specific contributions to the gender gap in life expectancy at birth. Analyses are stratified by urban-rural residence. RESULTS: Women had a higher life expectancy at birth than men in both urban and rural areas. Cancers, cardiovascular disease, external causes, and respiratory disease accounted for more than 90% of the gender gap in both areas during 2013-2018. In urban areas, the gender gap decreased from 5.17 years in 2013-2015 to 4.98 years in 2016-2018. In rural areas, the gender gap stayed rather constant (2013-2015: 5.68 years; 2016-2018: 5.65 years). Traffic accidents, among external causes, contributed the most to decreasing the gender gap (urban: -0.07 years; rural: -0.10 years), especially in the 0-44 age group. However, the decrease in the gender gap was counteracted by an increase in the gender gap attributable to ischemic heart disease (urban: +0.05 years; rural: +0.08 years) and lung cancer (urban: +0.02 years; rural: +0.05 years) in older age groups. The gender gap attributable either to cerebrovascular disease or to chronic lower respiratory disease decreased in urban areas but increased in rural areas. CONCLUSIONS: The urban-rural variations in the cause-specific contributions to the gender gap in China suggest the necessity of implementing urban-rural-specific interventions to improve population health and health equity.

The cross-sectional average length of healthy life (HCAL): a measure that summarizes the history of cohort health and mortality.

BACKGROUND: Healthy life years have superseded life expectancy (LE) as the most important indicator for population health. The most common approach to separate the total number of life years into those spent in good and poor health is the Sullivan method which incorporates the health dimension to the classic period life table, thus transforming the LE indicator into the health expectancy (HE) indicator. However, life years derived from a period life table and health prevalence derived from survey data are based on different conceptual frameworks. METHOD: We modify the Sullivan method by combining the health prevalence data with the conceptually better fitting cross-sectional average length of life (CAL). We refer to this alternative HE indicator as the "cross-sectional average length of healthy life" (HCAL). We compare results from this alternative indicator with the conventional Sullivan approach for nine European countries. The analyses are based on EU-SILC data in three empirical applications, including the absolute and relative level of healthy life years, changes between 2008 and 2014, and the extent of the gender gap. RESULTS: HCAL and conventional HE differ in each of these empirical applications. In general, HCAL provides larger gains in healthy life years in recent years, but at the same time greater declines in the proportion of healthy life years. Regarding the gender gap, HCAL provides a more favourable picture for women compared to conventional HE. Nonetheless, the extent of these differences between the indicators is only of minor extent. CONCLUSIONS: Albeit the differences between HE and HCAL are small, we found some empirical examples in which the two indicators led to different conclusions. It is important to note, however, that the measurement of health and the data quality are much more important for the healthy life years indicator than the choice of the variant of the Sullivan method. Nonetheless, we suggest to use HCAL in addition to HE whenever possible because it widens the spectrum of empirical analyses and serves for verification of results based on the highly sensitive HE indicator.

Life Expectancy: Frequently Used, but Hardly Understood.

Period life expectancy is one of the most used summary indicators for the overall health of a population. Its levels and trends direct health policies, and researchers try to identify the determining risk factors to assess and forecast future developments. The use of period life expectancy is often based on the assumption that it directly reflects the mortality conditions of a certain year. Accordingly, the explanation for changes in life expectancy are typically sought in factors that have an immediate impact on current mortality conditions. It is frequently overlooked, however, that this indicator can also be affected by at least three kinds of effects, in particular in the situation of short-term fluctuations: cohort effects, heterogeneity effects, and tempo effects. We demonstrate their possible impact with the example of the almost Europe-wide decrease in life expectancy in 2015, which caused a series of reports about an upsurge of a health crisis, and we show that the consideration of these effects can lead to different conclusions. Therefore, we want to raise an awareness concerning the sensitivity of life expectancy to sudden changes and the menaces a misled interpretation of this indicator can cause.

Community Social Characteristics and Health at Older Ages: Evidence From 156 Religious Communities.

Objectives: Previous studies have found that individuals' health is associated with the social characteristics of their communities. However, interpreting the causality of the relationships is difficult due to a number of potential confounders on both the individual- and community-levels as well as potential selection effects. In the current article, we analyze data on health and community characteristics from Catholic order members aged 50+ living together in religious communities. We argue that the potential for confounders and selection effects is reduced in our sample. Method: We use multilevel group actor-partner interdependence models and cross-sectional questionnaire data (N = 1,041, k = 156 communities) to test whether individuals' self-rated health was associated with the level of social conflict and connectedness of their community separate from their own involvement in conflict and feelings of connectedness. Results: We find that living in communities with higher levels of conflict is associated with worse health, especially at older ages. We also find that (a) the relationship between health and own feelings of connectedness is stronger for men and (b) women report better health than men in more connected communities. Discussion: Our results offer further evidence that at least some social characteristics of the community have a causal impact on health.

The impact of smoking on gender differences in life expectancy: more heterogeneous than often stated.

BACKGROUND: Throughout industrialized countries, tobacco consumption is seen as the predominant driver of both the trend and the extent of gender differences in life expectancy. However, several factors raise doubts to this generalization. We hypothesize that the impact of smoking on the gender gap is context-specific and differs between populations. METHODS: We decompose the gender differences in life expectancy into fractions caused by smoking and other non-biological factors for 53 industrialized countries and the period 1955-2009 to assess the significance of smoking among the causes that can be influenced by direct or indirect interference. RESULTS: The trend of the gender gap can indeed be attributed to smoking in most populations of the western world. However, with regard to the overall extent of male excess mortality, smoking is the main driver only in the minority of the studied populations. While the impact of smoking to gender differences in life expectancy declines in all populations, the contribution of other non-biological factors is in most cases higher at the end than at the beginning of the observation period. CONCLUSIONS: Over-generalized statements suggesting that smoking is the main driver of the gender gap in all populations can be misleading. The results of this study demonstrate that-regardless of the prevailing effect of smoking-many populations have still remarkable potentials to further narrow their gender gaps in life expectancy. Although measures to further reduce the prevalence of tobacco consumption must be continued, more attention should be directed to the growing importance of other non-biological factors.

Gender gaps--Life expectancy and proportion of life in poor health.

BACKGROUND: The literature suggests that women report worse health but live longer than men--a phenomenon known as the gender paradox in health and mortality. Although studies examining the paradox abound, relatively little is known about mechanisms underlying the gap. DATA AND METHODS: With data on healthy life expectancy from the Global Burden of Disease Study 2010, this article analyses the relationship between length of life and health among men and women in 45 more-developed countries. The proportion of life spent in poor health is used as an indicator of health. This approach accounts for gender differences in longevity and illustrates the female health disadvantage pattern more clearly. RESULTS: Life expectancy at birth and the proportion of life in poor health are closely related for both genders. Furthermore, the larger the female excess in longevity, the larger the female excess in the proportion of life in poor health. INTERPRETATION: By focusing on the proportion of life in poor health, this analysis suggests that women's longevity advantage translates into a health disadvantages relative to men. The results indicate that women suffer from poor health not in spite of living longer, but because they live longer.

Do women live longer or do men die earlier? Reflections on the causes of sex differences in life expectancy.

BACKGROUND: Although many different factors have been identified to contribute to excess male mortality, it is still unclear which path of the complex cause-effect chain is the decisive driver of the life expectancy gap between women and men. OBJECTIVE: The question behind this study is whether these sex differences are caused primarily by factors leading to low female mortality or rather by factors causing high male mortality. We hypothesise that they are to a large extent caused by specific subpopulations of men with particularly high mortality levels that decrease the average life expectancy of men. METHODS: To test this hypothesis, we investigate in a meta-analysis the variability in mortality (VM) in women and men - defined as the range of death rates prevailing among subpopulations - in empirical studies analysing specific phenomena of mortality differentials. We used the data of 72 empirical studies, including 146 total effects (TE) and 1,718 single effects (SE) for 21 different risk factors. RESULTS: In 85% of TE and three quarters of SE the VM was higher in men than in women, taking into account men's higher overall mortality. The corresponding figures for the direct differences in the VM between women and men are 92 and 82%, respectively. Cases with higher female VM are rare exceptions and appear in particular in the highest age groups. CONCLUSIONS: We find support for our hypothesis that the disproportionate high mortality levels of specific male subpopulations are the central cause of the current extent of sex differences in life expectancy. Thus, public health programmes should be targeted toward these disadvantaged subpopulations among men which seem to be related primarily to socioeconomic characteristics.

Estimating mortality differences in developed countries from survey information on maternal and paternal orphanhood.

In general, the use of indirect methods is limited to developing countries. Developed countries are usually assumed to have no need to apply such methods because detailed demographic data exist. However, the potentialities of demographic analysis with direct methods are limited to the characteristics of available macro data on births, deaths, and migration. For instance, in many Western countries, official population statistics do not permit the estimation of mortality by socioeconomic status (SES) or migration background, or for estimating the relationship between parity and mortality. In order to overcome these shortcomings, I modify and extend the so-called orphanhood method for indirect estimation of adult mortality from survey information on maternal and paternal survival to allow its application to populations of developed countries. The method is demonstrated and tested with data from two independent Italian cross-sectional surveys by estimating overall and SES-specific life expectancy. The empirical applications reveal that the proposed method can be used successfully for estimating levels and trends of mortality differences in developed countries and thus offers new prospects for the analysis of mortality.

Differences in life expectancy by education and occupation in Italy, 1980-94: indirect estimates from maternal and paternal orphanhood.

In the present study, we use the modified orphanhood method to analyse mortality differences by socio-economic status in Italy. This technique permits the indirect estimation of adult mortality from survey-based information on parents' survival in developed populations and helps to overcome several limitations of conventional studies on mortality differences by social class. We estimate a time series of life tables by education and occupation and analyse the differences in life expectancy by socio-economic status along with their changes between 1980-84, 1985-89, and 1990-94. Whereas mortality differences between the highest social class and the other socio-economic status groups increased among men, they decreased among women. We speculate about the reasons for these sex-specific trends and evaluate the application of indirect estimation techniques to the populations of developed countries.

Unnatural deaths among nuns and monks: is there a biological force behind male external cause mortality?

It is still unclear if and how biological factors contribute to excess male mortality due to 'external causes' (accidents, injuries, homicides and suicides). Sex hormones and reproductive roles are supposed to drive sex differences in behaviours increasing the male external cause mortality risk. This study analyses the external cause mortality of Catholic nuns and monks from three Bavarian cloisters whose similar environments allow the impact of biological factors to be isolated from a number of confounding causes. Using obituaries, entries in the profession books of religious orders and cemetery registers 2533 deaths of nuns and monks could be linked to a specific cause of death for the years 1946-2005, of which 69 belong to the group of external cause deaths. External cause mortality of the Bavarian cloistered and the West German general population has been compared by means of standardized mortality rates (SMRs) for ages 45 onwards using the European age standard for the age groups 45-64, 65-74 and 75+. Whereas nuns show statistically significantly lower external cause mortality than the general female population, monks' external cause mortality parallels or even exceeds that of general population males. These findings contradict the reproductive role hypothesis and provide some evidence for the sex hormones hypothesis.

[Sex differences in mortality - time to take a second look]. / Die geschlechtsspezifischen Sterblichkeitsunterschiede -Zeit für eine Zwischenbilanz.

Ever since mortality has been measured, the existence of a female survival advantage is well known. This topic reached particular interest with the widening of the male-female survival gap during the general decline of mortality in the 20(th) century to an extent of seven years. Only in the last 20 years has a slight narrowing of this gap been observed. The numerous examinations of these sex differences in mortality can be classified into two main explanation categories: the biological and the behavioral or environmental explanations. While in the past, scientists searched for the responsible factors solely in one of these complexes, it is obvious today that the cause of this phenomenon can only be found in a multi-causal context. This article describes the current knowledge and summarizes the most important of them inside the framework of more current research which has enabled researchers to exclude the non-biological factors in comparing female and male survival patterns. Those indicate the existence of a female biological advantage, which however should not exceed a difference of 1-2 years. Consequently, the rest should be due to behavioral and environmental factors. But the additional existence of a cohort effect of people born between 1930 and the mid 1940s with a significant higher male excess mortality often remains unrecognized. This effect could lead again to a widening of this mortality gap in the near future. However, in the long term, we should expect a further decline of sex differences in mortality closer to the biological level due to the continuous approximation of female and male life styles and sex-specific mortality risks.