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Abstract
There are many explanations for the sex-specific difference in life expectancy. An important reason for this difference can be found in the genome difference of one sex chromosome. It is obvious that testosterone, as an effective hormonal product of this genome difference, influences not only morphology, physiology and risk profiles of diseases but also social behavior and lifestyle. Statistical simulations are, for physicians, an unusual way to demonstrate differences in human mortality, but they may help to show other, and more abstract, aspects of nature. The Penna model of biological aging is a well-established model for simulating the influence of genetic factors on sex-specific mortality. In this study, the Penna model is explained and modified to take into account the potentially detrimental effects of testosterone on male mortality. This is achieved by a modification of the Verhulst factor, starting with male puberty. We demonstrated that about one-third of the sex-specific difference in life expectancy may be caused by the influence of testosterone in this mathematical aging model. These results do not show that male vices (smoking, drinking, risk-taking behavior, etc.) can be attributed only to testosterone even though it may appear so from the statistics. There are some correlations but not causal relations. It seems, even from the view of a mathematical–statistical simulation, that males are discriminated against regarding mortality and life expectancy. This underlines the need for sex-specific research, social policy and preventive programs (e.g. sports, nutrition) for minimizing the negative impact of male-specific genetic and hormonal factors.