Gender disparities in application and admission to the medical residency program in Peru: A cross sectional study from 2016 to 2023.

OBJECTIVE

To investigate gender disparities in applications and admissions to the medical residency programs in Peru, focusing on differences in application and admission proportions between male and female.

METHODS

We conducted a cross-sectional study to assess the proportions of female applicants and admissions to medical residency programs in Peru from 2016 to 2023. Bayesian multilevel linear models were employed, incorporating random intercepts and slopes by specialty to account for variability across specialties. This approach provided initial proportions of female in 2016 (intercepts) and annual percentage changes (beta coefficients) for each specialty. A multilevel Poisson regression model with robust variance was used to determine if being female was associated with higher admission frequency.

RESULTS

Of the 48,013 applicants, 48% were considered female applicants. Most specialties exhibited an increasing trend in female applicants (+0.2% to +2% annually), except for Family Medicine, Hematology, Pediatric Neurology, and Pathological Anatomy (-0.6%, -0.6%, -0.7%, and -0.9% annually, respectively). The specialties with the highest proportions of female admissions were in Physical Medicine and Rehabilitation (71.9%), Dermatology (71.2%), and Pathological Anatomy (71.2%). In contrast, the lowest proportions were observed in Neurosurgery (18.9%), Thoracic and Cardiovascular Surgery (17.7%), and Urology (15.6%). Declining trends in female admissions were noted in Family Medicine, Hematology, and Pathological Anatomy (-0.6%, -0.6%, and -0.8% annually, respectively). In addition, being female was associated with an 18% lower probability of admission to the medical residency program (prevalence ratio: 0.82; 95% CI: 0.78-0.85; p-value: <0.001).

CONCLUSION

This study identified persistent gender disparities in medical residency programs in Peru, with female applicants facing reduced probabilities of admission and exhibiting specialty-specific trends from 2016 to 2023.