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Contributed by James W. 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 ificance 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 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 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.

This pervasive inequality has intrigued researchers for decades 4. The cumulative corpus of research supports the conclusion that the gap has biological underpinnings modulated by social and environmental conditions. Deeper understanding could benefit from biodemographic research 5.

Here we present some of such research. Support for a biological root of the gender gap in survival stems from studies of groups in which men and women have more similar lifestyles than in the general population, such as among nonsmokers 67 or within religious groups such as active Mormons 8 or cloistered monks and nuns 9. Findings indicate that, even though men and women in these groups have more similar lifestyles and men are exposed to fewer risk factors than men in the general population, a gender gap in life expectancy still persists.

An untapped source of information is the reverse situation, when both men and women experience high, perhaps extreme, levels of mortality risk. A finding that men and women have similar life expectancies under these conditions would challenge the notion that the survival advantage of women is fundamentally biologically determined in all environments.

Therefore, we study here the survival of both sexes in populations enduring mortality crises. While women have lower mortality than men in modern populations, evidence for a female survival advantage under crisis conditions is sparse. A well-known story concerns the Donner Party, a group of settlers that lost twice as many men as women when stranded for 6 mo in the extreme winter in the Sierra Nevada mountains Additional support for female hardiness comes from the fact that, in most countries, the sex difference in remaining healthy life expectancy is smaller than the difference in total life expectancy.

The difference becomes even smaller later in life: For example, the gender gap in life expectancy at age 65 y for France and Sweden in was 4. Thus women live more years than men and are able to do so even though they are in bad health for a substantial part of those extra years of life. We investigate whether the ability of women to survive better under difficult circumstances extends to crises such as famines, epidemics, or slavery. We analyzed seven documented populations with extremely low life expectancies 20 y or less for at least one of the sexes, due to extreme conditions such as famines, epidemics, or slavery.

Even though a life expectancy of 20 y might seem unrealistically low, some populations in temporarily extreme conditions had a life expectancy below this value Historical demographic data can be often problematic. However, the cases used in this study have all been ly published in a respected peer-reviewed journal. This, by itself, should ensure data quality and reliability. Nevertheless, for each case we discuss potential problems and biases that can affect the gender difference in survival.

Between andfreed American slaves were encouraged to migrate back to Africa. Many undertook the risky trip and went to Liberia, where they encountered a very different disease environment than the one in which they grew up. McDaniel 24 used data collected by the American Colonization Society from to and estimated life tables for the former slaves. The data show the highest mortality ever registered in recorded human history. The arrival in Liberia was a mortality shock. McDaniel and Preston 23 and McDaniel 24 performed multiple data checks, matching them with other administrative sources, and concluded that the emigrant population was monitored carefully.

That is, the data show a pattern of mortality over age that corresponds with that of other human populations. This might have caused some bias in the sex-specific death rates, but the percentage is small enough to conclude that any bias would be weak. At the beginning of the 19th century pro- and antislavery forces clashed about the emancipation of the slaves in the British Caribbean. The antislavery campaign obtained an annual registration of the slaves in the colony of Trinidad, the only colony controlled directly from London.

Since unregistered slaves were confiscated by the Crown, owners had a strong incentive to comply with the order. The register contains the age of slaves in and in and records how many deaths and births occurred during the period.

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John 25 analyzed the data in the register. She concluded the data were complete for all age groups except for infants age category 0—1 ywho were underreported, and that the data were affected by age heaping on multiples of five. Unfortunately, this could not be smoothed because the age and sex composition of the population was shaped by the slave trade, but she limited its interference by estimating life tables by 5-y age groups. She then produced period life tables for the male and female slaves in the plantations of Trinidad, which showed that life expectancy could have been as low as Most of the variation derived from uncertainty about the level of infant mortality, and this uncertainty could be a source of bias in the computation of the gender survival gap.

However, the author notes that most of this uncertainty can be ruled out by conditioning the survival curves to having survived up to age 1 y and that the conditional survival functions for the upper and lower bounds of the life table are virtually identical The conditional survival curves, obtained by dividing each value of the survival curves by the survival value at age 1 y as reported in ref. Most importantly, they show the same age and gender pattern as the unconditional survival curves. In the twentieth century, the Ukraine experienced particularly turbulent demographic trends that mirror a history of major crises.

They estimated that period life expectancy during the crisis dropped to 7. The authors used census data and vital registrations available before and after the crisis in andbetween which they applied a series of methods such as interpolation, forward and backward projections, assumptions for fertility and migration during the period, and correction coefficients for the underreported deaths during the crisis.

The basic idea was to compare the actual population reported in the census with a hypothetical population that would have existed without the crisis, to obtain the effect of the crisis corrected for fertility loss and migration flows produced by the famine. These could be estimated only by applying some assumptions. If the assumption of constant total fertility rate at the level of is not likely to affect the estimates by gender, the assumption related to migration could introduce a bias in the estimated gender patterns of survival, e.

However, the authors based their work upon a solid base of historical and statistical references that represents the most reliable source of available knowledge about that period. This is described as the last major famine that caused starvation across most of Sweden. Abnormal weather conditions in the summer offollowed by widespread crop failures, caused a sudden and sharp increase in food prices. Consequently, mortality due to starvation increased. When the difficult crop conditions continued throughoutmortality increased even further in Since the famine affected most of the Swedish population, we used male and female life tables from the Human Mortality Database www.

The Human Mortality Database is the best source of historical and current death rates for national populations. The very high quality of its data is ensured by the database being limited to populations for which death registration and census data are virtually complete, since this type of information is necessary for the uniform method used to reconstruct the data series.

Among the countries included in the dataset, Sweden has the longest time series. The vital registration system in this country was established in the 17th century and was serviceably accurate by the midth century. Because the population of Iceland was small, measles was not endemic and was devastating when epidemics struck. In and Iceland experienced its two major measles epidemics of the 19th century. The disease spread rapidly through most of southern Iceland, the most populated area of the country.

Even though official registration of deaths by measles started only inthe two epidemics were documented in parish registries and reports from physicians. Both epidemics spread from Danish boats landing in the late spring of the respective year. Severe weather and unsanitary wet conditions facilitated the spread of the disease by causing many complications such as diarrhea and chronic bronchitis We used life tables from the Human Mortality Database that show a sudden drop in life expectancy of both sexes in from By potatoes were the staple food for the majority of the Irish.

When the mold Phytophthora infestans infected the plants and caused nearly total crop failures over three consecutive years, the Irish population starved. The population shrank due to extremely high mortality, emigration, and fewer births. Life tables for the famine years were constructed by combining various data sources Life expectancy dropped from about 38 y for both sexes in the prefamine years to The history of the Irish population was shaped by extensive migration during both nonfamine and famine years.

The two major destinations were North America and Britain. Controlling for migration, therefore, became a crucial aspect of the reconstruction of the toll of the famine, to reduce the impact of a potentially severe bias. Fortunately, the authors had available several analyses of the migration flows, mostly based on ship passenger lists and on British censuses which recorded the Irish-born population resident in Britainwhich allowed them to estimate quite precisely the age and sex profile of the migrants for example, the male:female ratio was about for emigrants to North America and for emigrants to Britain.

We took these measures from the life tables, when available, and otherwise applied standard demographic methods to compute the life tables For comparing mortality between the sexes, we further computed male:female mortality ratios and differences for each population and decomposed the sex differences in life expectancy by age Data for pre- and postcrisis times were available only for the Ukraine inSweden inIceland inand Iceland in In these cases, during normal years, women had higher life expectancy than men Table 1.

The female—male difference for each population was remarkably stable between the precrisis and the postcrisis years Table 1a that the epidemics or the famines affected the gender difference in survival only temporarily. Absolute and relative differences in male and female life expectancy for seven high-mortality populations during and, when available, before and after extreme mortality conditions. For the other populations analyzed in this study only partial information about mortality in normal conditions was available.

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For the freed Liberian slaves, a life table for those who survived the critical first year of arrival shows that women had 1. The estimated life expectancy in Ireland before the famine was No information pertaining to a condition of freedom was available for the slave population in Trinidad. Life expectancy was higher for women than for men for all populations, with the partial exception of the Trinidad slaves for whom, according to the lower-bound life table, males lived slightly longer than females Fig. In the lower-bound life table, female slaves suffered from higher mortality than male slaves from birth until age 25 y, while in the upper-bound life table women had lower mortality than men at birth, experienced higher mortality until age 15 y, and afterward experienced lower mortality again.

The general survival advantage of women is also reflected in the fact that the extreme age was higher for females than for males for all populations Fig. For Trinidad, dashed survival curves and vertical lines with asterisks represent estimated upper bounds. Source: authors' calculations based on published data from ref. For five populations—the two Icelandic populations and the Swedish, Irish, and Ukrainian populations—life expectancy estimates were available before and after the crisis, thus permitting evaluation of the absolute and relative impact of the crises for men and women Table 2.

The absolute reduction in life expectancy was higher for males than for females in Ireland; for the other four populations the absolute reduction was greater for females who had higher life expectancies than males in these populations both before and during the crisis. The relative decrease in life expectancy was higher for males in the Ukraine and Ireland, higher for females in Iceland, and roughly the same in Sweden. Male and female decrease in life expectancy for five high-mortality populations during extreme mortality conditions.

The sex difference in life expectancy varied among the populations Table 1. Women among the freed slaves migrating back to Liberia had the smallest absolute advantage over men 0. In Trinidad, as mentioned above, males lived longer than females 1. A decomposition of the difference in life expectancy by age shows that the biggest contribution to these differentials comes from strikingly large mortality differences between male and female infants Fig.

After age 1 y, mortality differences between the sexes contributed less and less to the total gap in life expectancy.

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Table 3 reports the share of the contribution of the 0—1-y age group and all other ages together with the total sex difference in life expectancy. Age decomposition of the differences in life expectancies between males and females for the eight high-mortality populations. Light blue bars for Trinidad represent the decomposition of the upper-bound life expectancy values.

See Table S1.

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Population structure and ageing