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Try out PMC Labs and tell us what you think. Learn More. Sex differences in mortality vary over time and place as a function of social, health, and medical circumstances. The magnitude of these variations, and their response to large socioeconomic changes, suggest that biological differences cannot fully for sex differences in survival.

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Drawing on a wide swath of mortality data across countries and over time, we develop a set of empiric observations with which any theory about excess male mortality and its correlates will have to contend.

After the onset of this transition, cross-sectional variation in excess male mortality exhibits a consistent pattern of greater female resilience to mortality under socio-economic adversity. The causal mechanisms underlying these associations merit further research. So pervasive are these observations that some demographers now equate the longevity of the human species, at any given time and place, with the highest observed LE of women Horton and Lo,Oeppen and W. Vaupel, Yet sex differences in mortality vary widely over time and place.

In this paper we explore this variation in search of insights into why women live longer. We are motivated by the hope such insights will reveal opportunities to reduce the excess mortality of men, although this paper only documents associations and stops short of examining causal pathways. The causal mechanisms underlying these associations, and appropriate interventions to address those mechanisms, fall outside the scope of this paper and merit future research. Second is the idea that socially mediated behavioral differences explain the gap—human males in virtually every society take more risks, are more violent and behave in ways that make them more prone to accidental injury, while females are more likely to be health-seeking Kalben,Case and Paxson,Cook et al.

In this paper we do not attempt to weigh the causal evidence for each of these mutually compatible pathways; rather we describe and contrast patterns of sex differences in mortality across time and place with which any theory will ultimately have to contend. We begin our investigation with the data that is of highest quality: the contemporary developed world. We then study patterns using a wide swath of available mortality data, within and between developing and developed countries and over the time periods for which reasonably reliable data are available. Of particular interest is the observed relationship between sex differences in mortality and other changes related to the demographic and epidemiologic transition Mooney,Omran,since this relationship facilitates comparison of changes in developed countries—from which almost all published work on this subject has emerged—to those presently evolving in developing countries at an earlier phase of transition.

We limit quantitative analyses to correlations and basic regressions, using markers of socioeconomic condition within and between countries based on available measures; it is not our intent to test the causal relationship between any specific factor s and sex differences in mortality, but rather to identify patterns to encourage such testing in future research. The paper is organized as follows. The final section summarizes our observations about variation over time and place, and then returns to the question of why women live longer than men and the implications for reducing excess male mortality.

We measure mortality as survival to age 70 S 70 or LE from birth e0 which we will refer to as simply LE for brevity. We prefer the former because of its reliability of estimation in small populations for which rates of mortality among older age groups are unstable.

However, for many populations and subpopulations of a priori interest, we must rely on published estimates of LE, secondarily derived. Regarding choice of data sources, we decided, for quality and practical reasons to confine most of our study to the last 5 decades, a time period for which reasonable mortality data and some relevant covariate data are available. The major exception was data from the Human Mortality Database, which enables a look back to for 18 now high-income countries.

Others have ly published the average life expectancy for countries by decade since Wang et al. We grouped these countries using data from the Global Burden of Disease project Lozano et al. Specifically, we defined five groups of countries Group 1 most developed based on the country's Human Development Index, modified to exclude LE as a core measure to avoid autocorrelation in our analyses, as discussed below.

Likewise we separated out the former Warsaw Pact countries, deated at Group 1E, because of their distinct survival and sex differences in mortality patterns. The countries classified in each of the five groups are listed in Supplementary Table 1. A third a priori decision was to exclude from detailed consideration period-place combinations where maternal mortality was or remains very high and where epidemiologic and demographic transition has not yet begun. Finally, we have largely refrained from examining cause-specific mortality data because of substantial limitations in its availability and quality going back in time, although we return to discuss this pathway for sex differences in the final section.

The specific sources of data for each section of the paper are described in Appendix A. The left panel of Fig. The means for the populations are 0. As can be seen, women enjoy a sharp advantage and a smaller variance than men. As ly noted, within-sex geographic variation in US mortality can be largely explained by a small set of social, environmental and health care-related variables, as can between-race differences Cullen et al.

Moreover, all are less than unity—there is no US county in which males have equal or better survival than females, though there are some counties for which the ratio approaches 1. More or less identical relationships emerge with respect to percent in poverty, per capita income, or low educational attainment.

OLS regressions, shown in Table 1describe the relationships quantitatively. Though each of the four variables shown is itself a potent univariate predictor of mortality, tobacco use and obesity correlate weakly with sex differences in mortality after controlling for other covariates and add little to the model's predictive power. The occupational similarity index explains substantial variation Fig. Regression table describing sex differences in survival across US Counties, — This same relationship appears to hold among geopolitical regions within Spain and Japan, selected because of the ready availability of the data Fig.

Ecologic analyses of income strata in Canada and Denmark mirror this as well Helweg-Larsen and Juel,Trovato and Lalu, ; to our knowledge there are no counter-examples among high-income countries. In Fig. Striking too, although the slope appears to remain more or less unchanged over time, the correlation strengthens over time in both plots. Comparing Group 1 countries with each other during this year period Fig. S3the same pattern is evident. Next we examine the available data from the early 20th century to observe available Group 1 countries during their epidemiologic transition Omran,Fink, Notably, however, female survival at ages over the reproductive period has been superior to that of men for as long as we have data e.

Moving to the low- and middle-income countries LMICsthree different patterns are salient, depicted in Fig. The cross-sectional resilience pattern emerges about a decade thereafter, by explaining about 50 percent of the variance. S6which shows recent within-country variation in cross section for two populous countries for which reasonable quality data are available.

Sri Lanka, on the other hand, is a Group 3 country which as recently as still had sufficiently high rates of maternal mortality that national rates of mortality were higher for women ages 15—40 than for men Omran,Fink, S7 ; by contrast, maternal mortality rates are detectable but low in Group 3 countries, and much lower in Groups 1 and 2 Hogan et al.

The experience of Eastern European countries, including the former Soviet Union FSUadds a unique dimension to our understanding of sex differences in mortality. Moreover, as shown vividly in Fig. The figure illustrates another remarkable feature not evident elsewhere in the world, which is volatility of sex differences in mortalitymatched otherwise only in demographic disasters such as epidemics and wars.

This observation must be viewed in the context of the enormous political change that swept this region during the 's and 90's, namely the liberalization of state communism during the 80's consequent to Gorbachev's policies in the USSR associated with rapid and demonstrable improvement in the relative mortality of menand the subsequent demise of that system in the FSU and former Warsaw Pact countries and replacement with market systems in all. Because of the historic heavier use of alcohol in this region of the world than any other, and the plausibility of its role as mediator for mortality rate gyrations, toxic levels of alcohol consumption have been the focus of much study Gerry,Mckee and Shkolnikov,Murphy et al.

Many analysts credit reduction in excess male mortality to one specific aspect of the Gorbachev reforms—alcohol consumption taxes—in the 80's, and blame the subsequent spike in male mortality on the elimination of those alcohol taxes after see for example Bhattacharya et al. Comparative data exploring the statistical association between male survival decline and changes in the rate of mortality from acute intoxication among the Russian Oblasts over the two time periods —88 alcohol less available and —98 alcohol more available may raise the question whether alcohol was the root cause of the rapid increase in male mortality, or one of its mediators.

As shown in Fig. From the above observations we draw a series of ten inferences, presented roughly in the order of those least to most speculative; since we have offered no identification strategy in the data, none is intended to suggest causal inference. Sex differences in mortality vary over time and place as a function of socioeconomic and possibly medical conditions.

The magnitude of these variations, and their abruptness in response to large socioeconomic changes, suggest that intrinsic biological differences alone cannot fully for observed sex differences in survival. While many have ly observed the variation in sex differences in mortality over time and place, the assembled evidence suggests that such variation follows distinct and identifiable patterns of social change.

It is almost certain, though data are incomplete, that there was a time in the history of all now developed Group 1 countries, and those now developing Groups 2 and 3wherein female mortality exceeded that of men.

In developed countries the turning point likely occurred between the late 19th century for northern Europe and Switzerland, for example and see Fig. In Group 2 countries this change occurred later, most likely in the mid-twentieth century although confirmation is problematic because we do not have reliable data on these countries for this time period.

We observe this same sex differences in mortality transition, occurring between andin countries less far along in development Group 3. Omran in his seminal presentation of the epidemiologic transition in Omran, opines this was due to maternal mortality at a time when fertility rates were high and the combination of medical knowledge and resources insufficient to prevent frequent maternal deaths from bleeding and infection in poor countries.

This conclusion would appear to be reinforced by our observations of Group 2 and 3 countries as they have entered transition, and the data on maternal mortality presented in Fig. This happens because as we move our attention from regions with high indices of development to regions with lower indices of development we observe that both men and women tend to have lower survival rates, but men more strikingly so i.

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That this relationship emerges so predictably as epidemiologic transition progresses—in more or less every observable culture and society except those poorest of the Group 3 countries and the Group 4 countries which have not yet entered transition —suggests that the pattern is unlikely to be explained by any specific policy, custom, habit, medical treatment, or health behavior which vary idiosyncratically over time and place.

What might not, ex antehave seemed inevitable is observed: a decade or two after maternal mortality has declined to relatively low levels—e. We have not explored in this paper the reasons for this continued decline nor the best explanations for the timing of the turnabout described in the next point, but note here the universality of the pattern among Group 1 counties—including Japan, which may in other regards prove an outlier—and the evidence that Group 2 countries are following the same pathway.

This inflection point in the sex differences in mortality transition is evident in almost all high-income Group 1 countries, as well as most middle-income Group 2 countries. Best observed presently for the most advanced Group 1 countries Fig. It is instructive to investigate the pattern within Japan, one of the world's fastest developing countries after World War II and with a distinctive set of cultural norms. As seen in Fig. Noteworthy is the perpetuation of this resilience pattern after the tipping point where male survival improves relatively approximately for Group 1 and or so for Group 2.

It would appear that the patterns of sex differences in mortality observed through the epidemiologic transition for high-income Group 1 countries are being recapitulated in low- and middle-income countries Groups 2 and 3. Our observations may offer a new way of looking at the epidemiologic transition stages as originally defined in Omran,Fink, Omran was writing, as chance would have it, at a critical historic moment that he could not have foreseen, as Group 1 countries were moving from the era of ever-improving relative survival for women into the modern era in which men have begun to catch up.

At that very time, those countries we now dub Group 2 were beginning to enter transition. Moreover, we would speculate that the cresting of that advantage as development proceeds, now evident in all developed countries, may demarcate yet a further phase in the demographic transition, though it is too early to do more than prognosticate, as Group 2 countries as a group have just entered this phase, and Group 3 countries have yet to arrive. Perhaps more importantly, from the perspective of sex differences in mortality, transition appears to demonstrate an impressively consistent pattern, at least based upon the data available.

Viewing Fig. Obviously it is premature to consider this empirically proved, but we offer it as a prediction that might be verified in the future.

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From the evidence presented it is clear that some Group 1 countries as a whole, e. In point of fact a value in excess of 1 is not encountered in a single country or sub-region of a Group 1 country, nor even in a Group 2 country except perhaps a handful of Chinese counties, mostly rural in a unique setting for which there are other plausible explanations related to family planning policies, son preference, and their unintended social consequences. Risky behaviors, such as smoking or alcohol consumption, have been identified in some settings as causal or contributory to the observed variation in sex differences in mortality.

What factors underlie this phenomenon? As noted it is unlikely that maternal mortality, or other adverse health impacts associated with reproduction, play a role—even lingering—in this phenomenon that seems very robust to variation in geography, culture and ethnicity. On the one hand, women are achieving greater role parity, as legal and social barriers to their advancement are eroding in formerly male-dominated arenas such as construction, manufacturing, business management, academics, other professions, and political leadership.

At the same time men, now more often sharing many of the same needs and interests as women, are more likely in most cultures to provide child-care and other family roles formerly delegated to women. Moreover an increasing fraction of households have single or same-sex he. There are important limitations to our approach that must be considered:. First, as we conceded at the outset, our effort has required use of very diverse data sets, each with quirks and opportunities for imprecision and bias.

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In many cases we have relied on life table analyses of others to impute sex-specific S 70 or LE. We do not address over time and place the roles of sex-specific causes of death, with the exception of maternal mortality, and even for that we lack detailed data for most times and countries. There is considerable evidence that after epidemiologic transition cardiovascular disease CVD, including heart attack, stroke, heart failure is the major cause of mortality and of its change Crimmins,as well as a disease that more often prematurely kills men.

They argue p. Nothing in our analysis can, in and of itself, disprove such a reductionist assertion. However, as noted, any theory of sex differences in mortality must be able to for observations from myriad countries, cultures and ethnicities in which the distributions of many risks, and their timing in relationship to other developmental and medical changes, are variable. For example, there is compelling evidence that in south Asian countries women, more than men, are afflicted by inactivity, poor diet and obesity, even if they smoke far less Saquib et al. The limited availability and quality of disease-specific mortality data has precluded our further exploration of such considerations, which represent important directions for future research.

We lack data for numerous independent covariates of a priori interest—e. The importance of such unmeasured covariates in our analyses awaits further research. We have no way to for yet another compelling difference well documented in many societies, namely differential health seeking behavior; women utilize approximately double the healthcare services of their male counterparts in developed societies Bertakis et al. The importance of this difference as a cause rather than a result of sex differences in mortality, outside the context of improvements in obstetric care, is impossible to assess from our data.

Even for those covariates that we have investigated—per capita GDP, educational attainment, percent in poverty—we lack consistent definitions and metrics over time. We return in closing to the question with which we started: why do women live longer than men? Our study aims to better understand the underlying basis of the century-long female survival advantage in current high-income countries, and the emerging advantage in most of the rest of the world. As noted in the introduction, there are three broad theories that have received attention; we now return to each.

The first theory is that women enjoy a hard-wired, biologic advantage, conferred during human evolution. While none of the data point to a specific basis, there almost certainly is a biologic advantage that seems impervious to—indeed, becomes more evident under—environmental or socioeconomic stress. How else could we explain the universality of the female survival advantage over time, culture, religion, political regime and place, once the scourge of maternal mortality has been overcome? And as noted earlier, even in the setting of high maternal mortality rates, women over 40 had lower mortality than men Fig.

In not one single US county, nor in any single country in Groups 1—3 including 1E, do more men survive to age 70 than women do. But despite the data limitations, we can infer more. For while some sex-specific difference in either S 70 or LE appears to be constant, the magnitude is not. So if the life expectancy difference in the Group 1—3 and 1E countries averages 6—8 years currently, and the difference in survival to 70 still exceeds 10 percent in many Group 1 countries, including the US, what s for the remainder?

The second broad theory proposes that sex-differences in health behaviors deserve consideration. This theory has indeed received a great deal of attention, with special attention to tobacco and alcohol McCartney et al. Differences between the sexes in their proclivities toward violence, dangerous occupations, risky driving, and athletic behaviors no doubt play a role, especially in mortality differences among young adults.

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The weaker sex? Vulnerable men and women’s resilience to socio-economic disadvantage