Investigators should carefully consider sex and gender differences when conducting research, according to the authors of a paper recently published in Endocrine Reviews.
The review, by Janet W. Rich-Edwards, PhD, of Brigham and Women’s Hospital in Boston, et al, makes the case that sex- and gender-informed perspective “increases rigor, promotes discovery, and expands the relevance of biomedical research” and lays out considerations and best practices for researchers to achieve these goals.
Sex differences exist in every facet of medical research, from cell to population to treatment, the authors write. Gender determines health because gender can influence environment and determine access to resources. Sex differences exist in symptoms and the authors point out that there is even a “sex bias” in gene expression. “In short,” the authors write, “the rigor of research depends on researchers’ understanding of the ways in which sex and gender influence the biologic systems they study.”
But there is an apparent lack of literature regarding sex differences, or at least true sex differences. The authors argue that researchers should keep in mind the historic neglect of women in clinical studies and the sex of animals and cells in basic research. “Furthermore, as argued below, the proliferation of ill-considered and often unplanned sex difference inquiries leads to a literature of contradictions,” the authors write. “Thus, the absence of evidence for sex differences is not necessarily evidence of the absence of sex differences.”
The authors are aware that the very concept of gender is complex and shifting, and they write that new measures of gender are likely to emerge, but again, there are few studies addressing this complexity. Some researchers have proposed methods for distinguishing gender from sex but the authors point out that many of these methods are problematic. “Such measures of gender are often measures of gender inequality,” the authors write. “Many times they are based on national or state-level statistics, rather than more granular individual or household data.”
The review covers a lot – the authors address issues of motivation, subject selection, sample size, data collection, analysis, and interpretation, considering implications for basic, clinical, and population research. The authors argue that any apparent sex differences should be approached with caution, and researchers should honestly address how well their studies rule out bias, confounding, and chance. “Even statistically significant sex differences may be due to chance or bias, instead of true heterogeneity of exposure–disease associations or of treatment effects,” the authors write.
The authors conclude by writing that investigators must address collecting and analyzing data by sex adequately, otherwise the “noise” created by multiple testing across all our datasets may drown out the signal of true sex differences. “Furthermore, in human studies it is important to investigate the impact of both sex and gender to illuminate fundamental, modifiable causes of disease and avoid a reflexive attribution of seeming sex differences solely to biology,” they write. “If we address these design and analytic issues skillfully, then we have the chance for new insights for men and women that will be critical for the next generation of scientific and therapeutic discoveries in this age of precision medicine.”