• Melinda C Aldrich, Anne E Cust, Camille Raynes-Greenow, and International Network for Epidemiology in Policy.
• Department of Thoracic Surgery, Vanderbilt University Medical Center, Nashville, TN; Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN. Electronic address: melinda.aldrich@vumc.org.
• Ann Epidemiol. 2019 Jul 1; 35: 1-3.

AbstractThe under-representation of women in leadership in scientific fields presents a serious problem. Gender diversity is integral to innovation and productivity, and inequality leads to loss of gender talent in science including epidemiology. This policy brief summarizes some of the key dimensions and determinants contributing to gender-equity gaps in epidemiology and other scientific fields, relevant to developed countries where there is more published evidence. Women in scientific fields hold fewer positions on editorial boards, lack equal representation in speaking engagements at conferences, and are less likely to publish or receive top tier grant funding. Reasons for these inequities range from unconscious bias, biased promotion systems, and traditional norms in the division of family life and labor in our society leading to the attrition of women in academia. Addressing the problem of gender inequity, as a component of gender inequality, will provide an ethical basis to advance innovation. Data on gender equity in the field of epidemiology are sparse. We call on academic institutions, professional societies and associations, and editorial boards relevant to epidemiology (as well as other academic disciplines more broadly) to take meaningful action to build an evidence base as to the extent of gender inequities in epidemiologic research, teaching, policy, and practice. We outline some of the necessary steps required to achieve gender equity, such as career development and mentoring programs, institutional support, and programs to address bias.Copyright © 2019 Elsevier Inc. All rights reserved.

12 keywords...

hide…