What explains wage differences between male and female Brazilian physicians? A cross-sectional nationwide study.

OBJECTIVE

In many countries an increase in the number of women in medicine is accompanied by gender inequality in various aspects of professional practice. Women in medical workforce usually earn less than their male counterparts. The aim of this study was to describe the gender wage difference and analyse the associated factors in relation to Brazil's physicians.

PARTICIPANTS

2400 physicians.

SETTING

Nationwide, cross-sectional study conducted in 2014.

METHODS

Data were collected via a telephone enquiry. Sociodemographic and work characteristics were considered factors, and monthly wages (only the monthly earnings based on a medical profession) were considered as the primary outcome. A hierarchical multiple regression model was used to study the factors related to wage differences between male and female physicians. The adjustment of different models was verified by indicators of residual deviance and the Akaike information criterion. Analysis of variance was used to verify the equality hypothesis subsequently among the different models.

RESULTS

The probability of men receiving the highest monthly wage range is higher than women for all factors. Almost 80% of women are concentrated in the three lowest wage categories, while 51% of men are in the three highest categories. Among physicians working between 20 and 40 hours a week, only 2.7% of women reported receiving >US$10 762 per month, compared with 13% of men. After adjustment for work characteristics in the hierarchical multiple regression model, the gender variable estimations (ß) remained, with no significant modifications. The final effect of this full model suggests that the probability of men receiving the highest salary level (≥US$10 762) is 17.1%, and for women it is 4.1%. Results indicate that a significant gender wage difference exists in Brazil.

CONCLUSION

The inequality between sexes persisted even after adjusting for working factors such as weekly workload, number of weekly on-call shifts, physician office work, length of practice and specialisation.