A year ago I discussed health disparities in several posts, including one on Rates and Burden, where I noted that “rates are very useful measures, because they allow comparison across populations of different sizes. But from a population health perspective, rates alone are not enough, because large disparities in very small populations have a different impact than similar disparities in larger populations. Burden refers to the impact of a health problem in a population, combining both the rate and the number of people affected.” I went on to observe that in comparing male and female mortality, there is a surprisingly high male mortality rate, but it is the size of this population (155 million) that transforms the rate into a significant population health burden, equal or more important than those by race or socioeconomic status.
This old post came immediately to mind several months ago when I saw the New York Times headline “Male Genes May Explain Higher Health Disease Risk,” which focuses on work by Fadi Charchar and colleagues that appeared in The Lancet. Findings reveal that British men have one of two variants of a cluster of genes on their Y chromosome – one of which carries a 50% increased risk of heart disease, even after controlling for smoking, diabetes, and cholesterol.
Genetics is one of the five determinant categories in the population health model underpinning this blog; we know that our underlying genetic makeup influences both mortality and health related quality of life. In one of the most commonly cited papers on the determinants of population health, McGinnis and colleagues observed that “although only about 2 percent of deaths in the United States maybe attributed to purely genetic diseases, perhaps 60 percent of late-onset disorders—such as diabetes, cardiovascular disease, and cancer—have some genetic component.”
So why haven’t I blogged at all about genetics and population health, and why does genetics not appear in our closely related model underpinning the County Health Rankings? The reason is that we have – until recently – viewed genetics as a non-modifiable health factor. That is, genetics are closely linked to health, but not amenable to treatment or prevention.
The New York Times asserts that the findings by Charchar et. al. put "a whole different perspective on risk factors for heart disease in men.” Of course these findings need to be replicated, and the specific genes and their mechanism of action identified. Ultimately, how we view gender differences in chronic disease-related mortality will hinge on whether the Y chromosome effect can be modified genetically or therapeutically.
Disparities are only differences; inequities are those disparities that are unjust and remediable. If the Y chromosome cluster is shown to be responsible for much of the gender difference but cannot be modified or treated, it would not make sense for population health policy to target this differential health burden. So far, most complex genetic diseases have been resistant to the promise of genomic therapy and personalized medicine. In a future post I will offer a population health policy perspective on the risks and advantages of major genomic investments. For now, this study should alert us to the possibility that part of the male mortality burden may be unmodifiable and therefore a disparity but not an inequity of policy relevance.
David A. Kindig, MD, PhD is Emeritus Professor of Population Health Sciences and Emeritus Vice-Chancellor for Health Sciences at the University of Wisconsin School of Medicine and Public Health. Follow him on twitter: @DAKindig.