This seminar first aired live on April 21st, 2022.

Moderator: Vidhi Maniar, Data for Health, Johns Hopkins Bloomberg School of Public Health Speakers: 

  • Dr. Rosemary Morgan, Associate Scientist, Johns Hopkins Bloomberg School of Public Health
  • Dr. Gayane Yenokyan, Senior Biostatistician, Johns Hopkins Bloomberg School of Public Health
  • Onikepe Owolabi, Program Director, Data Driven Policy Initiative to Improve Women’s Health, Vital Strategies 

Seminar Synopsis: This seminar provides an overview of what gender analysis in health data means and methods to apply gender analyses to large health datasets. The focus is on the differences between sex disaggregation and gender analysis using gender equity indicators. Speakers provide examples of gender analyses with country and regional datasets from Africa to showcase how this type of analysis can positively affect the health and well-being of women and girls and non-binary people. 

Methods for gender analysis described include use of proxy indicators, data triangulation, cross-examination, and cross-referencing of multiple data sources within a country or region. Comparison of data sources and gender equity indicators can complete a more representative picture of health and disease in a country or region. This type of gender analysis of population data provides critical context for the creation of gender-responsive public health policies and programs.