The difference between sex and gender, and why both matter in health research
August 17, 2021 By Jacqueline (Jacquie) Gahagan, Dalhousie University
The term sex is generally used to refer to a binary of being either female or male as denoted by attributes that comprise biological sex. Gender, on the other hand, is meant to refer to the various socially constructed roles, behaviours, expressions and identities of girls, women, boys, men and gender-diverse people.
For example: Do you want to know if a new drug was tested and approved for safe and effective use with women? That is a “sex” question. Do you want to know why women make up the majority of long-term care workers and how this impacts their lives? That is a “gender” question.
Canada is seen as a world leader in sex- and gender-based analysis. However, there are still a variety of challenges in the actual application of this approach in health research. In practical terms, when health research does not include sex- and gender-based analysis, it can result in a lack of access to appropriate health information, diagnoses or care for all populations.
Canada’s longstanding commitment to sex- and gender-based analysis is noteworthy. However, this approach has yet to achieve widespread integration across federal departments and agencies.
Improving health programs for everyone
If sex- and gender-based analysis is truly aimed at advancing our understanding of the ways in which, for example, federal policies and programs are improving the health of women, men, boys, girls and gender-diverse populations, we need all federal departments and agencies to use this approach. However, as indicated by the Office of the Auditor General of Canada, only a fraction of federal departments and agencies that committed to measures such as the Action Plan on Gender-based Analysis have actually conducted gender-based analysis.
This lack of uptake matters because a sex- and gender-based analytical process can be used to determine how diverse groups of women, men, girls, boys and gender-diverse people are being differentially affected by federal initiatives.
It can be challenging to address or correct poorly developed policies after the fact by applying sex- and gender-based analysis after they’ve been rolled out or applied. The point is to ensure that inequalities are addressed at the outset of our health policy development processes, and not as an afterthought or add-on to satisfy departmental reporting requirements.
One of the stated goals of sex- and gender-based analysis is to help government decision-makers — including those in the health sector — identify sex and gender considerations, such as the participation and inclusion of diverse populations. To achieve that, these issues need to be incorporated from the very beginning, while programs and policies are in the developmental phase.
Implementing sex- and gender-based analysis
Tensions in implementing a sex- and gender-based analysis approach have been evident for a long time in the health sector. For example, in relation to “women’s” cancer screening and cancer registries, the ongoing invisibility of lesbian, bisexual and transgender populations overlooks the unique cancer diagnosis, treatment and care needs of gender-diverse populations.
In addition, cancer registries can benefit from sex- and gender-based analysis. These registries collect, store, manage and analyze data on people with cancer to help with cancer surveillance, as a resource for cancer researchers and to serve as the evidence base to inform public health programs and policies.
If cancer data are collected using a gender binary of male or female patient populations, for example, this information is then fed into the cancer registry that in turn renders invisible those who identify as gender non-binary, transgender or other gender identity. How then can we inform gender- and sex-appropriate cancer prevention, care, treatment and support programs or policies in such instances?
Sex is NOT gender but we continue to treat these as the same concept. We use them interchangeably. We use them in health research, health policies and health programs with dire consequences. After decades of trying, we should be able to get this right.
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