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Pour la séance d'octobre de notre club de revue d’articles, nous discuterons d’un article sur l’exécution d’analyses du genre de bases de données existantes lorsque les données autodéclarées sur le genre ne sont pas disponibles.

Paper

Conducting gender-based analysis of existing databases when self-reported gender data are unavailable: the GENDER Index in a working population

Objectives

Growing attention has been given to considering sex and gender in health research. However, this remains a challenge in the context of retrospective studies where self-reported gender measures are often unavailable. This study aimed to create and validate a composite gender index using data from the Canadian Community Health Survey (CCHS).

Methods

According to scientific literature and expert opinion, the GENDER Index was built using several variables available in the CCHS and deemed to be gender-related (e.g., occupation, receiving child support, number of working hours). Among workers aged 18–50 years who had no missing data for our variables of interest (n = 29,470 participants), propensity scores were derived from a logistic regression model that included gender-related variables as covariates and where biological sex served as the dependent variable. Construct validity of propensity scores (GENDER Index scores) were then examined.

Results

When looking at the distribution of the GENDER Index scores in males and females, they appeared related but partly independent. Differences in the proportion of females appeared between groups categorized according to the GENDER Index scores tertiles (p < 0.0001). Construct validity was also examined through associations between the GENDER Index scores and gender-related variables identified a priori such as choosing/avoiding certain foods because of weight concerns (p < 0.0001), caring for children as the most important thing contributing to stress (p = 0.0309), and ability to handle unexpected/difficult problems (p = 0.0375).

Conclusion

The GENDER Index could be useful to enhance the capacity of researchers using CCHS data to conduct gender-based analysis among populations of workers.

Presenter

Amanda DoggettAmanda Doggett, PhD Candidate
School of Public Health and Health Systems, University of Waterloo

Amanda is a PhD Candidate in the School of Public Health and Health Systems at the University of Waterloo. Amanda currently works with data from the COMPASS study – a large longitudinal cohort study of youth across Canada. Amanda’s research has mainly focused on substance use behaviours among youth, and she has a particular interest in quantitative methods. Currently, her dissertation work focuses on the impact of missing data in youth BMI research.

Author

>Anais Lacasse

Anaïs Lacasse, PhD
Associate Professor, Department of Health Sciences, University of Quebec in Abitibi-Témiscamingue

Trained in pharmacoepidemiology at the Faculty of Pharmacy of Montreal University, Anaïs Lacasse is an associate professor in the Department of Health Sciences at the University of Quebec in Abitibi-Témiscamingue (UQAT), Quebec, Canada. She is a Junior 2 scholar of the Fonds de recherche du Québec - Santé (FRQS) in partnership with the Quebec SPOR Support Unit and her research program aims to better understand the treatment of chronic pain in the real-world clinical context. Specifically, 3 complementary research axes are explored: 1) The healthcare trajectories of people living with chronic pain, 2) The use of drugs for the treatment of chronic pain, and 3) The linkage and validation of databases and measurement scales for research in this field. Anaïs Lacasse is actively involved in several FRQS research networks, especially as the Co-Director of the Quebec Pain Research Network (QPRN) and member of the Steering Committee of the Quebec Network on Drug Research (RQRM).

Quand
octobre 28th, 2020 de  1:00 PM à  2:00 PM
Lieu
Virtuel
ON
Canada
Webinar Fee(s)
Webinar Registration 12,00 $