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.
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.
People:
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.People: