A Data-Based Approach to Evaluating Representation by Gender and Affiliation in Key Presentation Formats at the Annual Meeting of the Society for Epidemiologic Research

Am J Epidemiol. 2021 Sep 1;190(9):1710-1720. doi: 10.1093/aje/kwab080.

Abstract

The annual meeting of the Society for Epidemiologic Research (SER) is a major forum for sharing new research and promoting the career development of participants. Because of this, evaluating representation in key presentation formats is critical. For the 3,257 presentations identified at the 2015-2017 SER annual meetings, we evaluated presenter characteristics, including gender, affiliation, subject area, and h-index, and representation in 3 highlighted presentation formats: platform talks (n = 382), invited symposium talks (n = 273), and chairing a concurrent contributed session or symposium (n = 188). Data were abstracted from SER records, abstract booklets, and programs. Gender was assessed using GenderChecker software, and h-index was determined using the Scopus application programming interface. Log-binomial models were adjusted for participant characteristics and conference year. In adjusted models, women were less likely than men to present an invited symposium talk (relative risk = 0.60, 95% confidence interval: 0.45, 0.81) compared with all participants with accepted abstracts. Researchers from US public universities, US government institutions, and international institutions were less likely to present a symposium talk or to chair a concurrent contributed session or symposium than were researchers from US private institutions. The research areas that were most represented in platform talks were epidemiologic methods, social epidemiology, and cardiovascular epidemiology. Our findings suggest differences in representation by gender, affiliation, and subject area after accounting for h-index.

Keywords: bibliometric data; professional society; representation.

Publication types

  • Research Support, N.I.H., Intramural

MeSH terms

  • Bibliometrics*
  • Congresses as Topic / statistics & numerical data*
  • Epidemiologic Methods*
  • Epidemiology / statistics & numerical data*
  • Female
  • Gender Equity
  • Humans
  • Male
  • Societies, Medical / statistics & numerical data*