Why women suffer and men die?
Women have longer life expectancy in all countries of the world (for countries with reliable data), but women tend to report poorer self-rated health, they have higher disability levels at all ages and perform more poorly on physical tests than men. This male-female health-survival paradox (M:F HSP) has fundamental societal and personal implications, perhaps best illustrated by the large population of disabled widows in high-income countries – a population that is expected to increase in absolute numbers in the coming years. Many different factors are thought to influence the M:F HSP, but there is a general agreement that cigarette smoking is the largest identifiable factor in explaining the increasing sex gap in mortality in the developed countries. With the dying out of the generations that took up smoking in high-income countries, the sex difference in life expectancy is expected to decrease.
Sex Differences in Health and Mortality by Social Status and its Changes
There is extensive literature documenting a social gradient in both health and survival for both males and females. Factors like retirement, loss of social relations and bereavement affect the social position and their effect increases with age. However, very little is known about the magnitude of sex differences in health (hospital admissions, surgeries, and services at general practitioner and mortality across social status groups and how much changes in social position over the life course explain sex differences in morbidity and mortality. Furthermore, previous studies demonstrated that lower socioeconomic status is associated with unhealthier lifestyle (e.g. smoking and alcohol consumption). The magnitude of sex differences in survival remains to be investigated when mortality due to smoking- and alcohol-related causes of death are eliminated. In collaboration with the Independent Research group: Gender Gaps in Health and Survival at Max Planck Institute of Demographic Research (MPIDR), we have built a nationwide dataset including data since 1980 for the Danish population, which has made these analyses possible. We will continue using the same data, to address the hypothesis that in females the social status and its loss is most strongly associated with health status, whereas in males we expect the association to be strongest with mortality, i.e. women’s health deteriorates during bad times, but men die.
Comparison of Utah and Denmark
The research interest is to test and compare the trends in female and male survival in 20th century societies with different behavioural patterns: On the one hand Denmark with a widespread smoking and alcohol consumption for both females and males, and on the other Utah where smoking and drinking are limited as a result of religious believes. The causes of death analysis will help us disentangle whether the explanatory factors for the persistent gap among the genders can be explained by the same chronic conditions in both societies, or if alternative explanations should be pursued. Furthermore, by using the extensive Danish and Utah population registers we will be able to identify the causes of death responsible for the differential mortality in women and men by socioeconomic stratification. Thus, we will be able to expand the results of the social gradient effect on the male-female survival paradox including causes of death information.
We are in the process of examining causes of deaths information in Denmark since 1950 and our collaborators: professor Ken Robert Smith and associate professor, Heidi A. Hanson, University of Utah, are preparing similar analyses of data from 1904 for the state of Utah. We include different perspectives on the analysis of causes of death used for the population level analysis. First, we look at a traditional decomposition technique for comparisons of life expectancy at birth (Arriaga 1984) and decompose this by causes of death between groups. Second, a description of the number of life years lost due to each of the causes of death is studied (Andersen et al 2013). Third, a comparison of the cause contribution in the survival of cohorts is assessed (Beltran-Sanchez et al 2008). All three methods complement each other by showing: the changes due to age and causes of death in two cohorts (either period or cohort life tables); the years lost or a snapshot of the current mortality in a population; and the survival experience of all the cohorts present at a given time.
Are male-female health survival differences driven by male-female differences in survival after disease onset?Women outlive men, but the ‘extra time’ is generally spent in poor health. Furthermore, women generally have better survival after disease onset than comparable male patients. We intend to use the excellent Danish register data to evaluate the extent to which the sex difference in survival is driven by male-female differences in survival after onset of heart disease and cancer - the two most frequent causes of death in Denmark. By using the unique Danish registries on cancers and heart diseases we will contribute further to the understanding of the effect of a possible better survival in two major disease categories for women on the sex difference in life expectancy. We have established databases for analysing this relationship. Our first preliminary result is that the minimum contribution (i.e. differences among those that are diagnosed and die from the same cancer) of Danish women’s better survival following a cancer diagnosis is 9.6% of the total difference in life expectancy (i.e. 0,41 years due to better survival of women out of 4,2 years in total life expectancy difference for the period 2005 to 2014). Similar analysis will be done for other major disease groups and decomposition by cause made.
The influence of smoking – end of the smoking epidemic
The generations that took up smoking in high income countries are dying out. This may have a major influence on the sex differences in life expectancy and on its forecast. We plan to examine these effects both in terms of reporting the effect and to highlight its implications. In our first analysis we first used the Preston Glei Wilmoth method to calculate smoking attributable deaths in EU and the US. Next, we will estimate remaining cohort survival for non-extinct cohorts. These studies will increase knowledge on the effect of lifestyle behaviour on the life expectancy measure and its forecast. Due to selection effects on males and the survivors having a lower mortality and the later onset of smoking in women the life expectancy may narrow substantially and perhaps in some populations become similar. Whereas the smoking epidemic has ended in high income countries, it has just begun in middle and low-income countries and we will explore this further in future studies.