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Age-at-death distributions for men in the lowest and highest income quartiles in 1997 and 2017 by country. on June 30, 2021 by guest. Protected by copyright.
Source publication
Objectives
Levels, trends or changes in socioeconomic mortality differentials are typically described in terms of means, for example, life expectancies, but studies have suggested that there also are systematic social disparities in the dispersion around those means, in other words there are inequalities in lifespan variation. This study investigat...
Contexts in source publication
Context 1
... method makes more jagged age-atdeath distributions. However, the two methods of division of the age-specific death rates by income quartiles yield similar results, as illustrated in the online supplemental figure A1, where both methods are presented for Swedish data (Sweden was chosen because the country has the largest population size and thus more stable death rates). The online supplemental table A1 and table A2 also present data on population sizes and number of deaths by country, period, gender and income quartile. ...
Context 2
... a shift to the right of the curves were much clearer for people in the highest income quartile. Differences between the highest and the lowest income quartile (quartile 4 minus quartile 1) in life expectancy, Δe, and lifespan variation, Δe † , are also presented in figures 1 and 2. Furthermore, the mortality ...
Similar publications
With historically similar patterns of high and stable cohort fertility and high levels of gender equality, the Nordic countries of Sweden, Finland, Norway, Denmark, and Iceland are seen as forerunners in demographic behavior. Furthermore, Nordic fertility trends have strongly influenced fertility theories. However, the period fertility decline that...
Citations
... Despite robust welfare systems, this pattern is also seen in the Nordic countries (Mackenbach, 2012). Lower socioeconomic groups in the Nordics have experienced little improvements in life expectancy and no reduction in lifespan inequality, suggesting Nordic societies are failing in postponing early deaths to older ages among people of low SES (Brønnum-Hansen et al., 2021). Indexing statutory retirement age to life expectancy is, therefore, potentially harmful to those of low SES. ...
... When education is used as a proxy of SES, widening mortality inequalities over time are often attributed to the selection of those who are in the most disadvantaged group, and to the difference in what it means to be less or more educated in different time periods (Brønnum-Hansen & Baadsgaard, 2012). On the other hand, when income is used as a proxy for SES, widening mortality inequalities over time are partially attributed to the change in the income distribution of a population (Brønnum-Hansen et al., 2021). In this paper, we investigated mortality and longevity developments in Denmark and Sweden by income to quantify social inequalities in mortality in two Nordic countries, and therefore, we must make the necessary considerations. ...
... However, we found that men in the lowest SES groups experienced increased lifespan inequalities over the study period. This is consistent with research that finds widening inequalities in mortality by SES in the Nordic region (Brønnum-Hansen & Baadsgaard, 2012;Brønnum-Hansen et al., 2021;Mackenbach, 2012;Strozza et al., 2022). In particular, our results are in line with those of Strozza et al. (2022) who focus on cohort survival between ages 50 and 70 by socioeconomic status. ...
In Denmark and Sweden, statutory retirement age is indexed to life expectancy to account for mortality improvements in their populations. However, mortality improvements have not been uniform across different sub-populations. Notably, in both countries, individuals of lower socioeconomic status (SES) have experienced slower mortality improvements. As a result, a uniform rise in the statutory retirement age could disproportionally affect these low-SES groups and may unintentionally lead to a reverse redistribution effect, shifting benefits from short-lived low-SES individuals to long-lived high-SES individuals. The aim of this study is twofold: to quantify and contextualise mortality inequalities by SES in Denmark and Sweden, and to assess how indexing retirement age will affect future survival to retirement age by SES in these countries. We used Danish and Swedish registry data (1988–2019), to aggregate individuals aged 50 + based on their demographic characteristics and SES. We computed period life tables by year, sex, and SES to estimate the difference in survival across different SES groups. We then forecast mortality across SES groups to assess how indexing retirement age will affect survival inequalities to retirement age, using two forecasting models—the Mode model and the Li-Lee model. Mortality inequalities are comparable in Denmark and Sweden, even though the latter generally has higher survival. We also find that indexing retirement age to life expectancy will have two main consequences: it will reduce the probability of reaching retirement for all SES groups, particularly those of low SES, and time spent in retirement will be reduced, particularly for those of high SES.
... Several international studies have reported increased mortality among people with lower socioeconomic position. This association has been demonstrated throughout Europe (eg, for northern 14,15 and southern 14 European countries), including Germany. 16 However, options for analysing socioeconomic inequalities in mortality and life expectancy are much more limited in Germany than in many other high-income countries because the German official mortality statistics do not allow for disaggregation by socio economic position. ...
... Then we used standard life-table techniques to calculate life expectancy by sex and for residents in areas of each quintile of socioeconomic deprivation. As a final step in our main analysis, we decomposed the difference in life expectancy between the most and least deprived quintiles of German districts into age-specific and cause-specific mortality contributions (further information on the demographic methods used is in the appendix [pp [15][16][17][18][19][20][21]). In a supplementary analysis, we calculated the See Online for appendix deprivation-specific age-standardised mortality rate for the different cause-of-death groups to generate a broader overview of mortality trends by socioeconomic deprivation. ...
Background:
Earlier death among people in socioeconomically deprived circumstances has been found internationally and for various causes of death, resulting in a considerable life-expectancy gap between socioeconomic groups. We examined how age-specific and cause-specific mortality contributions to the socioeconomic gap in life expectancy have changed at the area level in Germany over time.
Methods:
In this ecological study, official German population and cause-of-death statistics provided by the Federal Statistical Office of Germany for the period Jan 1, 2003, to Dec 31, 2021, were linked to district-level data of the German Index of Socioeconomic Deprivation. Life-table and decomposition methods were applied to calculate life expectancy by area-level deprivation quintile and decompose the life-expectancy gap between the most and least deprived quintiles into age-specific and cause-specific mortality contributions.
Findings:
Over the study period, population numbers varied between 80 million and 83 million people per year, with the number of deaths ranging from 818 000 to 1 024 000, covering the entire German population. Between Jan 1, 2003, and Dec 31, 2019, the gap in life expectancy between the most and least deprived quintiles of districts increased by 0·7 years among females (from 1·1 to 1·8 years) and by 0·1 years among males (from 3·0 to 3·1 years). Thereafter, during the COVID-19 pandemic, the gap increased more rapidly to 2·2 years in females and 3·5 years in males in 2021. Between 2003 and 2021, the causes of death that contributed the most to the life-expectancy gap were cardiovascular diseases and cancer, with declining contributions of cardiovascular disease deaths among those aged 70 years and older and increasing contributions of cancer deaths among those aged 40–74 years over this period. COVID-19 mortality among individuals aged 45 years and older was the strongest contributor to the increase in life-expectancy gap after 2019.
Interpretation:
To reduce the socioeconomic gap in life expectancy, effective efforts are needed to prevent early deaths from cardiovascular disease and cancer in socioeconomically deprived populations, with cancer prevention and control becoming an increasingly important field of action in this respect.
... By considering a measure of average mortality, pension indexation does not account for the inequalities in mortality that exist within the Danish population. Several studies in Denmark that focus on social inequalities in average length of life and variation in length of life find that those inequalities have been increasing over time (Brønnum-Hansen et al. 2021;Brønnum-Hansen and Baadsgaard 2012). Uniformly raising the retirement age means that all individuals from a cohort are expected to survive longer to reach retirement age. ...
... Their substantial influence on LD across subgroups within populations has been discussed before, based on the individual level data. 20,21 At the country level captured by different SDI quintiles, 15 such impact may also be relevant. As shown in our study, apart from the general population, SDI levels contribute substantially to the variation in lifespan among healthy people. ...
Background
Alongside average health measures, namely, life expectancy (LE) and healthy life expectancy (HLE), we sought to investigate the inequality in lifespan and healthy lifespan at the worldwide level with an alternative indicator.
Methods
Using data from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019, we evaluated the global distribution of life disparity (LD) and healthy life disparity (HLD) for 204 countries and territories in 2019 by sex and socio-demographic index (SDI), and also explored the relationships between average and variation health indicators.
Results
Substantial gaps in all observed health indicators were found across SDI quintiles. For instance, in 2019, for low SDI, female LE and HLE were 67.3 years (95% confidence interval 66.8, 67.6) and 57.4 years (56.6, 57.9), and their LD and HLD were 16.7 years (16.5, 17.0) and 14.4 years (14.1, 14.7). For high SDI, female LE and HLE were greater [83.7 years (83.6, 83.7) and 70.2 years (69.3, 70.7)], but their LD and HLD were smaller [10.4 years (10.3, 10.4) and 7.9 years (7.7, 8.0)]. Besides, all estimates varied across populations within each SDI quintile. There were also gaps in LD and HLD between males and females, as those found in LE and HLE.
Conclusion
In addition to the disadvantaged LE and HLE, greater LD and HLD were also found in low SDI countries and territories. This reveals the serious challenge in achieving global health equality. Targeted policies are thus necessary for improving health performance among these populations.
... pandemic on Danish life expectancy differed by socioeconomic characteristics. This is important because socioeconomic inequalities in mortality have been widening for both men and women in Denmark, as well as in other Nordic and European countries with high national incomes, social transfers, and healthcare expenditures [3][4][5][6]. Moreover, improvements in life expectancy and lifespan inequality (variation in age at death) in high-income countries have differed across socioeconomic strata, with lower socioeconomic groups in Europe and the USA experiencing little improvements by either measure [3,4,[6][7][8][9][10][11]. ...
... This is important because socioeconomic inequalities in mortality have been widening for both men and women in Denmark, as well as in other Nordic and European countries with high national incomes, social transfers, and healthcare expenditures [3][4][5][6]. Moreover, improvements in life expectancy and lifespan inequality (variation in age at death) in high-income countries have differed across socioeconomic strata, with lower socioeconomic groups in Europe and the USA experiencing little improvements by either measure [3,4,[6][7][8][9][10][11]. These increasing inequalities in mortality cannot be fully explained by changes in population composition [7,12]. ...
Background
Denmark was one of the few countries that experienced an increase in life expectancy in 2020, and one of the few to see a decrease in 2021. Because COVID-19 mortality is associated with socioeconomic status (SES), we hypothesize that certain subgroups of the Danish population experienced changes in life expectancy in 2020 and 2021 that differed from the country overall. We aim to quantify life expectancy in Denmark in 2020 and 2021 by SES and compare this to recent trends in life expectancy (2014–2019).
Methods
We used Danish registry data from 2014 to 2021 for all individuals aged 30+. We classified the study population into SES groups using income quartiles and calculated life expectancy at age 30 by year, sex, and SES, and the differences in life expectancy from 2019 to 2020 and 2020 to 2021. We compared these changes to the average 1-year changes from 2014 to 2019 with 95% confidence intervals. Lastly, we decomposed these changes by age and cause of death distinguishing seven causes, including COVID-19, and a residual category.
Results
We observed a mortality gradient in life expectancy changes across SES groups in both pandemic years. Among women, those of higher SES experienced a larger increase in life expectancy in 2020 and a smaller decrease in 2021 compared to those of lower SES. Among men, those of higher SES experienced an increase in life expectancy in both 2020 and 2021, while those of lower SES experienced a decrease in 2021. The impact of COVID-19 mortality on changes in life expectancy in 2020 was counterbalanced by improvements in non-COVID-19 mortality, especially driven by cancer and cardiovascular mortality. However, in 2021, non-COVID-19 mortality contributed negatively even for causes as cardiovascular mortality that has generally a positive impact on life expectancy changes, resulting in declines for most SES groups.
Conclusions
COVID-19 mortality disproportionally affected those of lower SES and exacerbated existing social inequalities in Denmark. We conclude that in health emergencies, particular attention should be paid to those who are least socially advantaged to avoid widening the already existing mortality gap with those of higher SES. This research contributes to the discussion on social inequalities in mortality in high-income countries.
... Numerous international studies have reported higher mortality among people with lower socioeconomic position (e.g. [10][11][12]), and the relationship between mortality and socioeconomic position has also been examined for Germany. However, as official German mortality statistics cannot be linked to individual socioeconomic information, these studies are based on survey data [11,13] or the administrative data of the German Pension Fund (DRV) [14,15] or health insurance data [16]. ...
Background
Earlier death among people in socioeconomically deprived circumstances has been found internationally and for various causes of death, resulting in a considerable life expectancy gap between socioeconomic groups. This study examines how age- and cause-specific mortality contributions to the socioeconomic gap in life expectancy have changed in Germany over time.
Methods
Official German population and cause-of-death statistics from 2003 to 2021 were linked to the district-level German Index of Socioeconomic Deprivation. Life-table and decomposition methods were applied to calculate life expectancy by deprivation quintile and decompose the life expectancy gap (∆LE) between the most and least deprived quintiles into age- and cause-specific mortality contributions.
Findings
From 2003 to 2019, the ∆LE between the most and least deprived quintiles of districts increased from 1.1 to 1.8 years among women and from 3.0 to 3.1 years among men. Thereafter, in the COVID-19 pandemic, it increased more rapidly to 2.2 and 3.5 years respectively in 2021. The causes of death contributing most to the ∆LE were cardiovascular diseases (CVD) and cancer, with declining contributions of CVD deaths at age 70 and above and increasing contributions of cancer deaths at ages 40-74 over time. COVID-19 mortality at ages 45+ was the strongest contributor to the increase in ∆LE after 2019.
Interpretation
To reduce the socioeconomic gap in life expectancy, effective efforts are needed to prevent early deaths from CVD and cancer in deprived populations, with cancer prevention and control becoming an increasingly important field of action in this respect.
... Note that related research on the changing relationship between income and US mortality has also documented a trend in the widening of variability in mortality among low-income persons as well. 82 However, research outside the US also suggests that increased variability at the low end of the educational (or income) distribution is not necessarily a consequence of widening inequality in mortality. 83 The growing variability in mortality for less-educated adults has been recently linked to changes in the balance of US federal and state policies and institutional factors and their growing influence in more recent decades. ...
Policy Points
We reviewed some of the recent advances in education and health, arguing that attention to social contextual factors and the dynamics of social and institutional change provide critical insights into the ways in which the association is embedded in institutional contexts.
Based on our findings, we believe incorporating this perspective is fundamentally important to ameliorate current negative trends and inequality in Americans’ health and longevity.
... In Norway, formal home care services include home help and home nursing [18], which are generally provided by the municipality [19]. Although it is confirmed that LE at older age in Norway is increasing [8,20], there is still a lack of information on time trends of expected years receiving formal home-based care services in the Norwegian older population. Therefore, the aim of the current study is to examine the trend in expected years receiving formal home help and/or home nursing services among Norwegian older adults aged 70 or older during 1995-2017 and make projections for the number of persons receiving care in the coming decades. ...
Background:
Life expectancy (LE) is increasing worldwide, while there is lack of information on how this affects older individuals' use of formal home care services.
Aim:
We aimed to decompose LE into years with and without home care services and estimate projected number of users towards 2050 in Norway for people 70 years or older.
Methods:
This study is based on a sample of 25,536 participants aged 70 years and older in the Trøndelag Health Study (HUNT) survey 2 (1995-1997), 3 (2006-2008), or 4 (2017-2019) linked with national data on mortality. Prevalence of home care services was standardised to the Norwegian population by age and sex. The Sullivan method was used to estimate expected years with and without home help services and nursing services for the years 1995, 2006 and 2016. Data from HUNT4 and Statistics Norway were used to estimate projected use of these services between 2020 and 2050.
Results:
During 1995-2017, the use of home help services decreased from 22.6% to 6.2% (p < 0.001), and from 6.4% to 5.5% (p = 0.004) for home nursing services. Adjusted for age and sex, the use of home help services decreased significantly over time (p < 0.001), while home nursing services were stable (p = 0.69). LE at age 70 increased from 11.9 to 15.3 years in men (p < 0.05) during 1995-2017, and from 14.7 to 17.1 in women (p < 0.05). In the same period, the expected years receiving home help decreased from 2.6 to 1.1 in men (p < 0.05), and from 4.4 to 2.1 in women (p < 0.05). The expected years receiving home nursing increased from 0.6 to 0.9 in men (p < 0.05), and from 1.3 to 1.7 in women (p < 0.05). Projected numbers of people 70+ in Norway in need of either of these services were estimated to rise from 64,000 in 2020 to 160,000 in 2050.
Conclusion:
While overall life expectancy increased, the expected years receiving home help have decreased and home nursing slightly increased among the Norwegian population aged 70 years and older during 1995-2017. However, the substantial increase in the projected number of older adults using home care services in the future is an alert for the current health care planners.
... High life expectancy is generally associated with low lifespan variation (Németh, 2017;Shkolnikov et al., 2011;Wilmoth & Horiuchi, 1999) and is due to progress in reducing premature mortality . However, this association is not always observed Aburto et al., 2020;Brønnum-Hansen et al., 2021;. Thus, the coupling of changes in life expectancy and lifespan variation has gained increasing interest among demographers and policy makers. ...
... Various cross-country comparisons of mortality have been done between Cuba and other countries in Latin America and the Caribbean (Alvarez et al., 2020;Palloni & Pinto-Aguirre, 2011) and between Denmark and other Nordic or European countries Ballester et al., 2019;Brønnum-Hansen et al., 2021;Jørgensen et al., 2019;Leon, 2011). In this study, we were interested in comparing two countries that differ in climate, history, ethnicity, culture, and political and economic systems but have developed welfare policies including free universal access to social, educational and health benefits. ...
Cuba and Denmark represent states with different welfare models that have reached the same level of life expectancy. The purpose was to investigate and compare mortality changes in the two countries. Systematically collected information on population numbers and deaths for the entire Cuban and Danish populations was the basis of life table data used to quantify differences in the change in age-at-death distributions since 1955, age-specific contributions to differences in life expectancy, lifespan variation, and other changes in mortality patterns in Cuba and Denmark. Life expectancy in Cuba and Denmark converged until 2000, when the increase in life expectancy for Cuba slowed down. Since 1955, infant mortality has fallen in both countries but mostly in Cuba. Both populations experienced compression of mortality as lifespan variation decreased markedly, primarily due to postponement of early deaths. Given the different starting point in the mid-1900s and living conditions for Cubans and Danes, health status achieved among Cubans is striking. A rapidly ageing population is challenging both countries, but Cuban health and welfare are further burdened by a deteriorating economy in recent decades.
... By proposing action on the social determinants of health such as affordable child-care, education, living environments and income structures, they aim to facilitate a possible re-orientation of policy away from redistribution to universalism and a needsbased approach with 29 recommendations to combat social inequality of health that demand cross-sectorial actions (651). There are other important contributions on this matter from Norway (587,(652)(653)(654)(655). ...
This report of a rapid review of inequalities in health and wellbeing in Norway since 2014
was commissioned by the Norwegian Directorate of Health to inform the development
of a National Strategy to Reduce Social Inequalities in Health. It is a joint collaboration
between UCL Institute of Health Equity (IHE) and WellFare: Nordic Research Centre for
Wellbeing and Social Sustainability, Department of Education and Lifelong Learning at
the Norwegian University of Science and Technology (NTNU).
