For much of the twentieth century, clinical research treated the adult male body as the default and assumed the findings would transfer. They often did not — differences in drug metabolism, symptom presentation and disease progression were missed for decades. The correction is not complicated: measure sex and gender properly, report them separately, and analyse whether they matter. The SAGER guidelines (Sex and Gender Equity in Research) are the standard that makes this concrete.
Two different variables
| Sex | Gender | |
|---|---|---|
| Refers to | Biological attributes: chromosomes, hormones, anatomy, physiology | Socially constructed roles, identities, expressions and behaviours |
| Typically reported as | Female, male, intersex | Woman, man, non-binary, other identities |
| Relevant to | Pharmacokinetics, disease risk, physiology | Access to care, health behaviours, exposure, adherence |
Both can affect a health outcome, sometimes in opposite directions — which is why collapsing them into one column labelled "gender: M/F" loses information.
What SAGER asks of authors
- Use the terms correctly and consistently throughout the paper.
- Report how they were determined — self-reported, from records, or measured — in the methods.
- Report data disaggregated by sex and, where relevant, gender, including in tables and supplementary material.
- Discuss the implications in the discussion, or state plainly that a sex/gender analysis was not possible and why.
- Justify a single-sex study rather than leaving the restriction unexplained.
Writing about participants respectfully
Describe people as people: "participants with diabetes", not "diabetics". Where gender identity is relevant, collect it with an inclusive question rather than a forced binary, and report the categories you actually used. If your sample contained too few participants in a category for separate analysis, say so — that is a limitation, not something to quietly merge away.
Why journals are adopting it
SAGER sits alongside the other reporting standards you already meet — CONSORT, PRISMA and STROBE — and for the same reason: incomplete reporting makes research harder to use and to synthesise. Studies that disaggregate their data are more reusable, more citable in evidence syntheses, and more likely to be applicable to the patients who will eventually be treated on their basis.
Applying SAGER usually takes one extra column in a table and one honest paragraph in the discussion. That is a small price for research that describes the whole population it claims to be about.