Gender inequalities persist on a large scale in academic medicine. Compared with their male counterparts, female researchers generally receive lower salaries1,2 and less funding for their studies.3 They also have slower career progression.4 The representation of female and male authorship is a simple measure and is a surrogate marker that reflects the level of gender gap in research.
We selected all interventional and observational studies and all reviews published in 2016–2020 in all primary healthcare (PHC) journals with a JCR 2019–2020 impact factor >1 (N = 16 journals) and in the same number of high-impact general internal medicine (GIM) journals. We then used Gender API (https://gender-api.com/en/) to determine the gender of the first authors. Finally, we calculated the proportion of articles authored by female researchers and compared the data by year of publication and by medical discipline using logistic regression adjusted for intracluster correlations (journal).
We retrieved 13 440 articles, the names of the authors being available for 13 329 of them. First authors’ gender could be determined for 13 173 articles (98.8%). The proportion of female first authors ranged from 47.7% to 71.6% in PHC and from 24.3% to 53.3% in GIM. It was <50% in only one of 16 PHC journals and >50% in only one of 16 GIM journals. The difference between the two journal groups was statistically significant (53.7% for PHC versus 41.2% for GIM, adjusted odds ratio [AOR] = 1.66 [95% CI = 1.03 to 2.66], P-value = 0.04). The proportion of female first authors varied only slightly during the period under review (2020 compared with 2016: AOR = 0.98 [95% CI = 0.79 to 1.20], P-value = 0.81 for PHC, and AOR = 0.99 [95% CI = 0.90 to 1.09], P-value = 0.77 for GIM).
These results can be explained in part by a higher proportion of women in leadership positions in PHC compared with other medical disciplines.5 They highlight the important contribution of female scholars to scientific knowledge in PHC.
Our study has two main limitations. First, gender assignment relied on a gender detection tool and not on self-determination, and the risk of misclassification was therefore not excluded. However, Gender API was shown to be very accurate.6 Second, gender determination on the basis of first names raises ethical considerations by simplifying the concept of gender.7
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