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The gender gap in education that has long favored men has reversed for young adults in most upper- and middle-income countries. This reversal has major implications for the composition of marriage markets, assortative mating, gender equality, and marital outcomes such as divorce and childbearing. We focus on the implications for assortative mating and, in particular, for educational hypergamy: the pattern in which husbands have more education than their wives. We present findings from an almost comprehensive world-level analysis using census and survey microdata from 420 samples and 120 countries for the period 1960-2011. The reversal of the gender gap in education is strongly associated with the end of hypergamy and increases in hypogamy (wives having more education that their husbands). We provide near universal evidence of this trend, examine whether women are more likely to be the breadwinners when they marry men with lower education than themselves, discuss recent research regarding divorce risks among hypogamous couples, and examine attitudes about women earning more than their husbands.

In addition to fundamental mortality metrics such as mortality rates and mortality rate ratios, life expectancy is also commonly used to investigate excess mortality among a group of individuals diagnosed with specific diseases or conditions. However, as an average measure, life expectancy ignores the heterogeneity in lifespan. Interestingly, the variation in lifespan–a measure commonly used in the field of demography–has not been estimated for people with a specific condition. Based on recent advances in methodology in research within epidemiology and demography, we discuss two metrics, namely, the average life disparity and average lifetable entropy after diagnosis, which estimate the variation in lifespan for time-varying conditions in both absolute and relative aspects. These metrics are further decomposed into early and late components, separated by their threshold ages. We use mortality data for women with mental disorders from Danish registers to design a population-based study and measure such metrics. Compared with women from the general population, women with a mental disorder had a shorter average remaining life expectancy after diagnosis (37.6 years vs. 44.9 years). In addition, women with mental disorders also experienced a larger average lifespan variation, illustrated by larger average life disparity (9.5 years vs 9.1 years) and larger average lifetable entropy (0.33 vs 0.27). More specifically, we found that women with a mental disorder had a larger early average life disparity but a smaller late average life disparity. Unlike the average life disparity, both early and late average lifetable entropy were higher for women with mental disorders compared to the general population. In conclusion, the metric proposed in our study complements the current research focusing merely on life expectancy and further provides a new perspective into the assessment of people’s health associated with time-varying conditions.

In this paper we describe the Subnational Human Development Database. This database contains for the period 1990-2017 for 1625 regions within 161 countries the national and subnational values of the Subnational Human Development Index (SHDI), for the three dimension indices on the basis of which the SHDI is constructed - education, health and standard of living --, and for the four indicators needed to create the dimension indices -- expected years of schooling, mean years of schooling, life expectancy and gross national income per capita. The subnational values of the four indicators were computed using data from statistical offices and from the Area Database of the Global Data Lab, which contains indicators aggregated from household surveys and census datasets. Values for missing years were estimated by interpolation and extrapolation from real data. By normalizing the population-weighted averages of the indicators to their national levels in the UNDP-HDI database, values of the SHDI and its dimension indices were obtained that at national level equal their official versions of the UNDP.

Using data from the UN World Population Prospects, we document global trends in lifespan inequality from 1950 until 2015. Our findings indicate that (i) there has been a sustained decline in overall lifespan inequality, (ii) adult lifespan variability has also declined, but some plateaus and trend reversals have been identified, (iii) lifespan inequality among the elderly has increased virtually everywhere, and (iv) most of the world variability in age-at-death can be attributed to within-country variability. Such changes have occurred against a backdrop of generalized longevity increases. Our analyses suggest that the world is facing a new challenge: the emergence of diverging trends in longevity and age-at-death inequality among the elderly around the globe-particularly in high-income areas. As larger fractions of the world population survive to more advanced ages, it will be necessary for national and international health planners to recognize the growing heterogeneity that characterizes older populations.

Background Incidence-based multistate models of population health are commonly applied to calculate state expectancies, such as a healthy life expectancy (HLE), or unhealthy life expectancy (UHE). These models also allow the computation of other summary indices, such as the distributions of healthy or unhealthy lifespans. Objective We aim to show how a multistate health model implies a multistate death distribution, giving joint information on years lived in good and poor health. We also propose three aggregate indices of joint health and mortality inequality. Methods We propose a double-accounting approach to increment-decrement life table methods to intuitively derive a multistate health distribution over age and cumulative duration spent in each state. We then define a variety of summary lifespan inequality indices based on different distance metrics, namely Euclidean, Chebyshev, and Manhattan distances. Results We apply the method to multistate transition probabilities between health states based on the activities of daily living index for Italian women from the Survey of Health, Ageing and Retirement in Europe in 2015-2017. We demonstrate the added value of accounting for joint years lived in health states in multistate models for our understanding of the period health and mortality conditions from the perspective of health-specific lifespans of individuals. Conclusions Multivariate state distributions and summary indices derived from them give a holistic representation of population health inequality. We offer selected summary indices of the multivariate distribution with different demographic interpretations from the measures derived from univariate distributions. Although more theoretical and methodological work is required to motivate a single comprehensive population health inequality index, this direction is a promising path for a better understanding of population health dynamics and relationships between univariate statistics.

ObjectiveTo estimate smoking-related mortality and its contribution to educational inequalities in life expectancy in Spain.DesignNationwide, observational study from 2016 to 2019. Population-attributable fractions were used to estimate age, sex and education-specific cause-of-death smoking-attributable mortality. Life table techniques and decomposition methods were used to estimate potential gains in life expectancy at age 35 and the cause-specific contributions of smoking-related mortality to life expectancy differences across educational groups.SettingSpain.ParticipantsWe use cause-specific mortality data from population registers and smoking prevalence from the National and the European Health Survey for Spain from 2017 and 2019/2020, respectively.ResultsWe estimated 219 086 smoking-related deaths during 2016–2019, equalling 13% of all deaths, 83.7% of those in men. In the absence of smoking, potential gains in male life expectancy were higher among the low-educated than the high-educated (3.1 vs 2.1 years). For women, educational differences were less and also in the opposite direction (0.6 vs 0.9 years). The contribution of smoking to life expectancy differences between high-educated and low-educated groups accounted for 1.5 years among men, and −0.2 years among women. For men, the contribution of smoking to these differences was mostly driven by cancer in middle age, cardiometabolic diseases at younger ages and respiratory diseases at older ages. For women, the contribution to this gap, although negligible, was driven by cancer at older ages among the higher educated.ConclusionsSmoking remains a relevant preventable risk factor of premature mortality in Spain, disproportionately affecting life expectancy of low-educated men.

The Human Development Index is the world's most famous indicator of the level of development of societies. A disadvantage of this index is however that only national values are available, whereas within many countries huge subnational variation in development exists. We therefore have developed the Subnational Human Development Index (SHDI), which shows within-country variation in human development aaoss the globe. Covering more than 1,600 regions within 161 countries, the SHDI and its underlying dimension indices provide a 10 times higher resolution picture of human development than previously available. The newly observed within-country variation is particularly strong in low- and middle-developed countries. Education disparities explain most SHDI inequality within low-developed countries, and standard of living differences are most important within the more highly developed ones. Strong convergence forces operating both across and within countries have compensated the inequality enhancing force of population growth. These changes will shape the twenty-first century agenda of scientists and policy-makers concerned with global distributive justice.

Based on harmonized census data from 81 countries, we estimate how age and coresidence patterns shape the vulnerability of countries’ populations to outbreaks of coronavirus disease 2019 (COVID-19). We estimate variation in deaths arising due to a simulated random infection of 10% of the population living in private households and subsequent within-household transmission of the virus. The age structures of European and North American countries increase their vulnerability to COVID-related deaths in general. The coresidence patterns of elderly persons in Africa and parts of Asia increase these countries’ vulnerability to deaths induced by within-household transmission of COVID-19. Southern European countries, which have aged populations and relatively high levels of intergenerational coresidence, are, all else equal, the most vulnerable to outbreaks of COVID-19. In a second step, we estimate to what extent avoiding primary infections for specific age groups would prevent subsequent deaths due to within-household transmission of the virus. Preventing primary infections among the elderly is the most effective in countries with small households and little intergenerational coresidence, such as France, whereas confining younger age groups can have a greater impact in countries with large and intergenerational households, such as Bangladesh.

For a long time, studies of socioeconomic gradients in health have limited their attention to between-group comparisons. Yet, ignoring the differences that might exist within groups and focusing on group-specific life expectancy levels and trends alone, one might arrive at overly simplistic conclusions. Using data from the Spanish Encuesta Sociodemográfica and recently released mortality files by the Spanish Statistical Office (INE), this is the first study to simultaneously document (1) the gradient in life expectancy by educational attainment groups, and (2) the inequality in age-at-death distributions within and across those groups for the period between 1960 and 2015 in Spain. Our findings suggest that life expectancy has been increasing for all education groups but particularly among the highly educated. We observe diverging trends in life expectancy, with the differences between the low- and highly educated becoming increasingly large, particularly among men. Concomitantly with increasing disparities across groups, length-of-life inequality has decreased for the population as a whole and for most education groups, and the contribution of the between-group component of inequality to overall inequality has been extremely small. Even if between-group inequality has increased over time, its contribution has been too small to have sizable effects on overall inequality. In addition, our results suggest that education expansion and declining within-group variability might have been the main drivers of overall lifespan inequality reductions. Nevertheless, the diverging trends in longevity and lifespan inequality across education groups represent an important phenomenon whose underlying causes and potential implications should be investigated in detail.

Despite the intuitive notion that educational homogamy matters for the distribution of economic resources across households, existing research finds that changes in educational homogamy have had little impact on inequality between households. In this article, we document whether this conclusion generalizes to 21 countries and aim to understand the reasons why. We use data from the Luxembourg Income Studies to simulate the impact of both observed and hypothetical changes in educational homogamy on inequality. If educational homogamy had remained stable over time, the estimated difference between observed and simulated inequality would have been below 1 per cent in most countries. Extreme hypothetical changes from maximum hypergamy and hypogamy to maximum educational homogamy were simulated to increase inequality between 7 and 41 per cent, depending on the country. Hence, even though changes in educational homogamy have the potential to affect inequality, actual changes observed in this study were not strong enough to have a major impact. Additional analysis revealed that the potential impact of educational homogamy was systematically lower in countries with high levels of female labor force participation. Future changes in educational homogamy might therefore have an even smaller impact on inequality as ever more countries attain high levels of female employment.