Virginia Zarulli

The emergence of longevous populations

Significance Public interest in social and economic equality is burgeoning. We examine a related phenomenon, lifespan equality, using data from charismatic primate populations and diverse human populations. Our study reveals three key findings. First, lifespan equality rises in lockstep with life expectancy, across primate species separated by millions of years of evolution and over hundreds of years of human social progress. Second, industrial humans differ more from nonindustrial humans in these measures than nonindustrial humans do from other primates. Third, in spite of the astonishing progress humans have made in lengthening the lifespan, a male disadvantage in lifespan measures has remained substantial—a result that will resonate with enduring public interest in male–female differences in many facets of life. The human lifespan has traversed a long evolutionary and historical path, from short-lived primate ancestors to contemporary Japan, Sweden, and other longevity frontrunners. Analyzing this trajectory is crucial for understanding biological and sociocultural processes that determine the span of life. Here we reveal a fundamental regularity. Two straight lines describe the joint rise of life expectancy and lifespan equality: one for primates and the second one over the full range of human experience from average lifespans as low as 2 y during mortality crises to more than 87 y for Japanese women today. Across the primate order and across human populations, the lives of females tend to be longer and less variable than the lives of males, suggesting deep evolutionary roots to the male disadvantage. Our findings cast fresh light on primate evolution and human history, opening directions for research on inequality, sociality, and aging.

Women live longer than men even during severe famines and epidemics

Significance Women live longer than men in nearly all populations today. Some research focuses on the biological origins of the female advantage; other research stresses the significance of social factors. We studied male–female survival differences in populations of slaves and populations exposed to severe famines and epidemics. We find that even when mortality was very high, women lived longer on average than men. Most of the female advantage was due to differences in mortality among infants: baby girls were able to survive harsh conditions better than baby boys. These results support the view that the female survival advantage is modulated by a complex interaction of biological environmental and social factors. Women in almost all modern populations live longer than men. Research to date provides evidence for both biological and social factors influencing this gender gap. Conditions when both men and women experience extremely high levels of mortality risk are unexplored sources of information. We investigate the survival of both sexes in seven populations under extreme conditions from famines, epidemics, and slavery. Women survived better than men: In all populations, they had lower mortality across almost all ages, and, with the exception of one slave population, they lived longer on average than men. Gender differences in infant mortality contributed the most to the gender gap in life expectancy, indicating that newborn girls were able to survive extreme mortality hazards better than newborn boys. Our results confirm the ubiquity of a female survival advantage even when mortality is extraordinarily high. The hypothesis that the survival advantage of women has fundamental biological underpinnings is supported by the fact that under very harsh conditions females survive better than males even at infant ages when behavioral and social differences may be minimal or favor males. Our findings also indicate that the female advantage differs across environments and is modulated by social factors.

Mortality by education level at late-adult ages in Turin: a survival analysis using frailty models with period and cohort approaches

Objectives Neglecting the presence of unobserved heterogeneity in survival analysis models has been showed to potentially lead to underestimating the effect of the covariates included in the analysis. This study aimed to investigate the role of unobserved heterogeneity of frailty on the estimation of mortality differentials from age 50 on by education level. Design Longitudinal mortality follow-up of the census-based Turin population linked with the city registry office. Setting Italian North-Western city of Turin, observation window 1971–2007. Population 391 170 men and 456 216 women followed from age 50. Primary outcome measures Mortality rate ratios obtained from survival analysis regression. Models were estimated with and without the component of unobserved heterogeneity of frailty and controlling for mortality improvement over time from both cohort and period perspectives. Results In the majority of cases, the models without frailty estimated a smaller educational gradient than the models with frailty. Conclusions The results draw the attention of the potential underestimation of the mortality inequalities by socioeconomic levels in survival analysis models when not controlling for unobserved heterogeneity of frailty.

Unobserved Heterogeneity of Frailty in the Analysis of Socioeconomic Differences in Health and Mortality

The concepts of unobserved frailty and selection have been extensively analyzed with respect to phenomena like mortality deceleration at old ages and mortality convergence or cross overs between populations (for example American black and white populations, men and women). Despite the long-time observation of converging mortality risks in differential socioeconomic mortality research, the interest in the connection between frailty, selection, and health and mortality inequalities over a life course approach has increased only recently. This overview of the literature summarizes the main concepts of unobserved frailty and socioeconomic differences in mortality and how frailty and selection relate to these differences at old ages. It then reviews the evidence coming from the existing studies. Although the number of studies is still limited, the body of research on unobserved frailty and socioeconomic inequalities in health and mortality in a life course approach is growing. The results, however, are contradictory, and whether selection plays a major role in shaping the observed socioeconomic mortality patterns at old ages is still controversial.

Why did Danish women's life expectancy stagnate? The influence of interwar generations' smoking behaviour.

The general health status of a population changes over time, generally in a positive direction. Some generations experience more unfavourable conditions than others. The health of Danish women in the interwar generations is an example of such a phenomenon. The stagnation in their life expectancy between 1977 and 1995 is thought to be related to their smoking behaviour. So far, no study has measured the absolute effect of smoking on the mortality of the interwar generations of Danish women and thus the stagnation in Danish women’s life expectancy. We applied a method to estimate age-specific smoking-attributable number of deaths to examine the effect of smoking on the trends in partial life expectancy of Danish women between age 50 and 85 from 1950 to 2012. We compared these trends to those for women in Sweden, where there was no similar stagnation in life expectancy. When smoking-attributable mortality was excluded, the gap in partial life expectancy at age 50 between Swedish and Danish women diminished substantially. The effect was most pronounced in the interwar generations. The major reason for the stagnation in Danish women’s partial life expectancy at age 50 was found to be smoking-related mortality in the interwar generations.

Reply to Delanghe et al.: Iron status is not likely to play a key role in the gender survival gap under extreme conditions

Females survive better than males in populations under stressful conditions, such as famines, epidemics, and slavery (1). Delanghe et al. (2) identify a biological mechanism that might partly explain this finding. They emphasize that women generally have smaller body iron stores than men, and therefore are less prone to develop conditions such as scurvy or siderophilic infections. This could … [↵][1]1To whom correspondence should be addressed. Email: jwv{at}demogr.mpg.de. [1]: #xref-corresp-1-1

Matrix methods in health demography: a new approach to the stochastic analysis of healthy longevity and DALYs

BackgroundIncreases in human longevity have made it critical to distinguish healthy longevity from longevity without regard to health. Current methods focus on expectations of healthy longevity, and are often limited to binary health outcomes (e.g., disabled vs. not disabled). We present a new matrix formulation for the statistics of healthy longevity, based on health prevalence data and Markov chain theory, applicable to any kind of health outcome and which provides variances and higher moments as well as expectations of healthy life.MethodThe model is based on a Markov chain description of the life course coupled with the moments of health outcomes (“rewards”) at each age or stage. As an example, we apply the method to nine European countries using the SHARE survey data on the binary outcome of disability as measured by activities of daily living, and the continuous health outcome of hand grip strength.ResultsWe provide analytical formulas for the mean, variance, coefficient of variation, skewness and other statistical properties of healthy longevity. The analysis is applicable to binary, categorical, ordinal, or interval scale health outcomes. The results are easily evaluated in any matrix-oriented software. The SHARE results reveal familiar patterns for the expectation of life and of healthy life: women live longer than men but spend less time in a healthy condition. New results on the variance shows that the standard deviation of remaining healthy life declines with age, but the coefficient of variation is nearly constant. Remaining grip strength years decrease with age more dramatically than healthy years but their variability pattern is similar to the pattern of healthy years. Patterns are similar across nine European countries.ConclusionsThe method extends, in several directions, current calculations of health expectancy (HE) and disability-adjusted life years (DALYs). It applies to both categorical and continuous health outcomes, to combinations of multiple outcomes (e.g., death and disability in the formulation of DALYs) and to age- or stage-classified models. It reveals previously unreported patterns of variation among individuals in the outcomes of healthy longevity.

Am I Halfway? Life Lived = Expected Life

We have reached halfway in life when our age equals our remaining life expectancy at that age. This relationship in stable population models between life lived and life left has captured the attention of mathematical demographers since Lotka. Our paper aims to contribute to the halfway-age debate by showing its time trends under mortality models and with current data from high longevity countries. We further contrast the halfway-age results by sex, and between period and cohort perspectives. We find that in 1850 life expectancy at birth was higher than halfway-age by around 10 years (HMD-mean halfway-age of 33.3 and 32.2 against HMD-mean life expectancy of 44.3 and 41.4 for women and men respectively). Nevertheless, declines in mortality at young ages radically changed life expectancy and it is found today at the same level as the double of halfway-age. While the period perspective puts halfway-age for females and males at 41.8 and 39.5 in 2010, for cohorts born in 2010 this might be as high as 10 years more. The stage of midlife has always been considered an important step in the life of human beings. However, there is no agreement on which is the age or age-range that represents the middle phase. Here we have further added the notion that halfway-age is not a static index but a moving age. Current and future progress in reducing mortality at older ages will require redefining our notion of midlife.