Population Studies-A Journal of Demography最新文献

Chronological age, in conjunction with population life tables, is widely used for estimating future life expectancy. The aims of this study are to estimate a subjective ageing indicator, namely self-rated age, and to evaluate its concurrent validity in comparison with other age indicators: subjective survival probabilities, subjective age, and biological age. We use data from the Wave 6 of the Survey of Health, Ageing and Retirement in Europe, Wave 12 of the Health and Retirement Study in the United States, and life tables from the Human Mortality Database. For the statistical analysis we use multinomial regression models. Our results indicate that health status and frequency of physical activities imply similar patterns of self- rated age, subjective survival probabilities, subjective age, and biological age. However, the impact of cognitive function differs by geographical region. Self-rated age can be interpreted as a subjective adjustment that better reflects the ageing process.

With few exceptions, greater disparities in mortality risk by socio-economic status (SES) have been found among men than among women. Most research has also shown that the higher mortality risk after widowhood (the widowhood effect) is greater for men. However, a different picture appears when examining these associations jointly. Based on Swedish register data, this study shows that widowhood weakens, or even reverses, the sex differences in socio-economic disparities in mortality. The overall findings also indicate that higher SES elevates the widowhood effect for men but diminishes it for women, and that the widowhood effect is greater for women than men in the lowest SES categories. These results imply that men with higher SES are more vulnerable after widowhood, perhaps because of their previous relatively privileged situation. The disadvantage of widows in lower SES categories may reflect exposure to financial strains after spousal loss and inequalities in the healthcare system.

We test a conjecture to explain Turkey's decades-long 'underachievement' in early child mortality improvements. We argue that it is largely a consequence of cultural barriers to embracing available modern medical technology and healthcare practices. The empirical test rests on a reformulation of Coale's Ready-Willing-Able (RWA) framework for explaining fertility changes, which makes it suitable to understand mortality changes. We use structural equation modelling and Demographic and Health Surveys spanning 1993-2013 to estimate basic parameters of the reformulated framework. These parameters are then used to classify mothers into four groups with different configurations of RWA dimensions and different probabilities of adopting modern medical practices. We find that observed behaviours in these groups were consistent with RWA expectations. In addition, we find that an important contributor to Turkey's lagging mortality decline was a population distribution biased towards groups more reticent to adopting modern healthcare.

This paper argues that son preference resulted in gender-based discriminatory practices that unduly increased mortality rates for females at birth and throughout infancy and childhood in nineteenth- and early-twentieth-century Greece. The relative numbers of boys and girls at birth was extremely high and under-registration of females cannot on its own explain this result. The infanticide and/or mortal neglect of infant girls was therefore more common than previously acknowledged. Likewise, sex ratios increased as children grew older, thus suggesting that parents continued to treat boys and girls differently throughout childhood. A large body of qualitative evidence (contemporary accounts, folklore traditions, feminist newspapers, and anthropological studies) further supports the conclusion that girls were neglected due to their inferior status in society.

The migrant mortality advantage has been observed extensively, but its authenticity is debated. In particular, concerns persist that the advantage is an artefact of the data, generated by the problems of recording mobility among foreign-born populations. Here, we build on the intersection of two recent developments: the first showing substantial age variation in the advantage-a deep U-shaped advantage at peak migration ages-and the second showing high levels of population over-coverage, the principal source of data artefact, at the same ages. We use event history analysis of Sweden's population registers (2010-15) to test whether this over-coverage can explain age variation in the migrant mortality advantage. We document its U-shape in Sweden and, crucially, demonstrate that large mortality differentials persist after adjusting for estimated over-coverage. Our findings contribute to ongoing debate by demonstrating that the migrant mortality advantage is real and by ruling out one of its primary mechanisms.

Studies have shown that children in rural areas face excess risks of dying, but the little research on spatial inequalities in adult mortality has reached mixed conclusions. We examine rural-urban differences in mortality in 53 low- and middle-income countries. We consider how the rural-urban mortality gap evolves from birth to age 60 by estimating mortality based on birth and sibling histories from 138 Demographic and Health Surveys run between 1992 and 2018. We observe excess rural mortality until age 15, finding the largest differences between urban and rural sectors among 1-59-month-olds. While we cannot claim higher mortality among urban adults than those in rural areas, we find a reduced gap between the sectors over the life course and a diminishing urban advantage in adult mortality with age. This shift over the life course reflects a divergence in the epidemiologic transition between the rural and urban sectors.

Evidence from theories of Developmental Origins of Health and Disease (DOHaD) suggests that experiencing adverse early life conditions subsequently leads to detrimental adult health outcomes. The bulk of empirical DOHaD literature does not consider the nature and magnitude of the impact of adverse early life conditions at the population level. In particular, it ignores the distortion of age and cohort patterns of adult health and mortality and the increased load of chronic illness and disability that ensues. In this paper, we use a microsimulation model combined with empirical estimates of incidence and prevalence of obesity, type 2 diabetes, and associated disability in low- and middle-income countries to assess the magnitude of delayed effects on adult healthy life expectancy and on compression (or expansion) of morbidity at older ages. The main goal is to determine if, in what ways, and to what extent delayed effects due to early conditions can influence cohorts' chronic illness and disability profiles.

Lowering desired family size is a necessary precondition for fertility declines in high-fertility settings. Although accumulated evidence links socio-economic developments to changing fertility desires, little research has disentangled the relative importance of key socio-economic determinants. Combining individual- and community-level data from Demographic and Health Surveys in 34 sub-Saharan African (SSA) countries, we compare the relative role of different socio-economic factors on fertility desires at the individual, community, and country levels. Results show that at the individual level, women's education has a stronger effect than household wealth and area of residence. The high levels of reported desired family size in rural parts of SSA are mainly a consequence of relatively lower levels of education. The relative impact of women's education is even stronger at the community level. Our findings are robust to alternative measures of fertility preferences and strengthen previous findings regarding the relationship between fertility and women's education.

Parents with two boys or two girls are more likely to have a third child than those with a 'sex mix'. However, little is known on whether these 'mixed-sex preferences' extend beyond the nuclear family. This study leverages the random variation in sex at birth to assess whether the sex of nieces and nephews, in combination with own children, matters for fertility choices. Using three-generational data from the US Panel Study of Income Dynamics (PSID), I show that extended families (including grandparents, their children, and their grandchildren) are collectively more likely to have three or more grandchildren when lacking sex mix, whether the first two grandchildren are siblings or cousins. I explore the pathways for these offspring sex preferences, finding support for a preference for an uninterrupted line of male descendants. This multigenerational approach also contributes a new estimation strategy that causally estimates the effects of family sizes on outcomes beyond fertility.

Italy was hit harshly by the Covid-19 pandemic, registering more than 35,000 Covid-19 deaths between February and July 2020. During this first wave of the epidemic, the virus spread unequally across the country, with northern regions witnessing more cases and deaths. We investigate demographic and socio-economic factors contributing to the diverse regional impact of the virus during the first wave. Using generalized additive mixed models, we find that Covid-19 mortality at regional level is negatively associated with the degree of intergenerational co-residence, number of intensive care unit beds per capita, and delay in the outbreak of the epidemic. Conversely, we do not find strong associations for several variables highlighted in recent literature, such as population density or the share of the population who are older or have at least one chronic disease. Our results underscore the importance of context-specific analysis for the study of a pandemic.