BMJ Global Health (Apr 2021)

Identification and inclusion of gender factors in retrospective cohort studies: the GOING-FWD framework

  • Karolina Kublickiene,
  • Valeria Raparelli,
  • Carole Clair,
  • Jovana Stojanovic,
  • Uri Bender,
  • Karin H Humphries,
  • Rachel P. Dryer,
  • Christina P. Tadiri,
  • Rubee Dev,
  • Pouria Alipour,
  • Sabeena Jalal,
  • Alexia Della Vecchia,
  • Salima Hemani,
  • Heather Burnside,
  • Carola Deschinger,
  • Juergen Harreiter,
  • Simon D. Lindner,
  • Teresa Gisinger,
  • Giulia Tosti,
  • Claudia Tucci,
  • Giulio Francesco Romiti,
  • Agne Laučytė-Cibulskiene,
  • Liam Ward,
  • Leah Muñoz,
  • Raquel Gomez De Leon,
  • Ana Maria Lucas,
  • Sonia Gayoso,
  • Raúl Nieto,
  • Maria Sanchez,
  • Sandra Amador,
  • Cristina Rochel,
  • Donna Hart,
  • Nicole Hartman/Nickerson,
  • Angie Fullerton/MacCaul,
  • Jeanette Smith,
  • Myra Lefkowitz,
  • Ann Keir,
  • Kyle Warkentin,
  • Rachael Manion,
  • Vera Regitz-Zagrosek,
  • Londa Schiebinger

DOI
https://doi.org/10.1136/bmjgh-2021-005413
Journal volume & issue
Vol. 6, no. 4

Abstract

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Gender refers to the socially constructed roles, behaviours, expressions and identities of girls, women, boys, men and gender diverse people. Gender-related factors are seldom assessed as determinants of health outcomes, despite their powerful contribution. The Gender Outcomes INternational Group: to Further Well-being Development (GOING-FWD) project developed a standard five-step methodology applicable to retrospectively identify gender-related factors and assess their relationship to outcomes across selected cohorts of non-communicable chronic diseases from Austria, Canada, Spain, Sweden. Step 1 (identification of gender-related variables): Based on the gender framework of the Women Health Research Network (ie, identity, role, relations and institutionalised gender), and available literature for a certain disease, an optimal ‘wish-list’ of gender-related variables was created and discussed by experts. Step 2 (definition of outcomes): Data dictionaries were screened for clinical and patient-relevant outcomes, using the International Consortium for Health Outcome Measurement framework. Step 3 (building of feasible final list): a cross-validation between variables per database and the ‘wish-list’ was performed. Step 4 (retrospective data harmonisation): The harmonisation potential of variables was evaluated. Step 5 (definition of data structure and analysis): The following analytic strategies were identified: (1) local analysis of data not transferable followed by a meta-analysis combining study-level estimates; (2) centrally performed federated analysis of data, with the individual-level participant data remaining on local servers; (3) synthesising the data locally and performing a pooled analysis on the synthetic data and (4) central analysis of pooled transferable data. The application of the GOING-FWD multistep approach can help guide investigators to analyse gender and its impact on outcomes in previously collected data.