Gender Disparity in the Funding of Diseases by the U.S. National Institutes of Health

Abstract

Background: Gender bias has been an ongoing issue in health care, examples being underrepresentation of women in health studies, trivialization of women's physical complaints, and discrimination in the awarding of research grants. We examine here a different issue-gender disparity when it comes to the allocation of research funding among diseases. Materials and Methods: We perform an analysis of funding by the U.S. National Institutes of Health (NIH) to ascertain possible gender disparity in its allocation of funds across diseases. We normalize funding level to disease burden, as measured by the Disability Adjusted Life Year, and we specifically consider diseases for which both disease burden and funding level are provided. We apply a power-law regression analysis to model funding commensurate with disease burden. Results: We find that in nearly three-quarters of the cases where a disease afflicts primarily one gender, the funding pattern favors males, in that either the disease affects more women and is underfunded (with respect to burden), or the disease affects more men and is overfunded. Moreover, the disparity between actual funding and that which is commensurate with burden is nearly twice as large for diseases that favor males versus those that favor females. A chi-square test yields a p-value of 0.015, suggesting that our conclusions are representative of the full NIH disease portfolio. Conclusions: NIH applies a disproportionate share of its resources to diseases that affect primarily men, at the expense of those that affect primarily women.

Keywords: National Institutes of Health; gender disparity; research funding for diseases.

FIG. 1.

National Institutes of Health funding (2017) versus U.S. burden of disease (2015, normalized to 2017 population). The green line, produced using a power law regression analysis, represents funding commensurate with disease burden. (Figure adapted from Figure 2 of Mirin et al. Reprinted with permission from IOS Press.)