Introduction   

Despite women’s significant progress in educational and professional achievements in recent years,1 inequality in opportunities, treatment and outcomes between women and men persist in global labour markets.2 Wage disparity between men and women has been conspicuously reported worldwide, and although gender-related income differences have generally narrowed in several countries during the last decades3–7 wage gap within numerous professions is far from being eliminated.2 7 Gathering reliable information on the key determinants of such scenario, especially through analyses considering the profile, profession and comparable job standards,7 8 is crucial to the definition and implementation of sustainable policies to promote gender wage equality.

Although it may be highly variable across different countries,7 the gender wage disparity is currently estimated at 23% worldwide, meaning that women in general earn 77% of men’s income.2 Such disparities are less prominent in traditional professions such as medicine, engineering and law, but even so a significant difference is found in income values between men and women among medical professionals.8–12 Most studies13–18 tackling wage disparities between male and female physicians have considered only a limited number of variables influencing such differences. Variables such as specialty, working hours and length of time in practice have been pointed out to justify lower wages for women; however, when variables are properly controlled for these characteristics, the wage gap usually persists.13 19 While gender gap disparity has been extensively studied in recent years,13 18–22 possible interactions between variables should be further explored in order to identify cause-and-effect scenarios.

In Brazil, the medical workforce is still mostly represented by male physicians (54%), with marked over-representation of men in certain medical specialties, such as general surgery, cardiology and orthopaedics/traumatology.23 The proportion of female physicians, however, has rapidly increased during the past decades,24 and women currently represent the majority of physicians among medical students and young professionals,23 thus resonating the feminisation phenomenon widely reported in different locations.19 25–32

Despite the growing participation of women in the Brazilian medical workforce, the general gap in salary between male and female physicians is estimated at 24%.7 33 The medical profession in Brazil is marked by the coexistence of multiple job affiliations and possibilities of insertion in the health system.34 Salary is determined by multiple variables, such as professional promotions across the medical career and holding simultaneous job positions in public and private services, where they are blindly paid for the care they provide. Therefore, the drivers behind such disparities are still unclear, and the sociodemographic, professional and behavioural characteristics that might be determinant to explain wage gap differences among Brazilian physicians are yet to be determined.

In this context, we describe here the first representative cross-sectional study of gender wage disparity in the Brazilian medical workforce. By using a hierarchical multiple regression model approach, we explored work-related and sociodemographic characteristics that might explain income differences between male and female physicians. We describe the influence of 12 distinct independent variables on salary distribution to test the hypothesis that physicians’ gender is a confounding variable in relation to wage discrepancy, and that the influence of gender would disappear when adjusting for specific characteristics that relate to medical workload and other modifiable wage-related variables.

Methods

Hierarchical framework modelling

A hierarchical multiple regression model was used to investigate the factors related to wage differences between male and female physicians. This type of analysis is generally used to explain the relationship between variables in models with a set of empirical propositions that already indicate the relationship strength and direction between predictors and outcomes. Building a conceptual framework requires knowledge of the biological or social and temporal determinations that affect the outcomes,38 and the order of predictor entry in the regression equation was defined based on a pre-established conceptual framework.39 For modelling in this paper, the position of a specific set of variables regarding the outcome was based on previous bivariate analysis (online supplementary table S1), with significant association (from stronger to weaker): (1) gender was considered the proximal term; (2) medial terms included work-related variables such as weekly workload, NOWOC shifts and physician working in office; and (3) length of time in practice and medical specialty type were considered distal terms (figure 1).

Supplementary file 1

[bmjopen-2018-023811supp001.pdf]

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Figure 1

Theoretical framework used to analyse factors associated with wage differences between male and female Brazilian physicians.

Results

The profile of 2400 male and female Brazilian physicians is shown in table 1.

The more heterogeneous sociodemographic characteristics between genders were age >60 years (male 26.3% [95% CI 23.9% to 28.7%] vs female 8.5% [95% CI 7.0% to 10.3%]) and physician with an address in urban centres (male 52.6% [95% CI 50.3% to 55.3%] vs female 61.3% [95% CI 58.5% to 64.5%]).

The more heterogeneous work-related characteristics included working in public services (female 26.7% [95% CI 24.1% to 29.5%] vs male 17.8% [95% CI 15.8 to 19.9]), private hospitals (male 42.4% [95% CI 39.8% to 45.0%] vs female 32.2% [95% CI 29.4% to 35.1%]) and family health strategy [female 26.6% [95% CI 23.6% to 29.0%] vs male 21.3% [95% CI 19.2% to 23.5%]). The variables time in practice (male <10 years 25.8% [95% CI 39.8% to 45.0%] vs female 34.5% [95% CI 31.6% to 37.6%]), weekly workload (hours) (male >60 hours 36.5% [95% CI 33.9% to 39.0] vs female 26.7% [95%CI 24.0% to 29.7%]) and monthly wage (≥US$10 762; male 20.1% [95% CI 18.0% to 22.0%] vs female 4.4% [95% CI 3.2% to 5.7%]) were also significantly heterogeneous.

Online supplementary table S2 shows the relationships between the proportions of monthly wage and work-related characteristics, specialties and gender. Women are over-represented in the first two lower monthly wage categories (≤US$3857 and US$3587–5381) for 10–30 years of time in practice (PR 3.53 [95% CI 2.31 to 5.40] and PR 2.39 [95% CI 1.86 to 3.07]), weekly workload >60 hours (PR 2.44 [95% CI 1.74 to 3.44] and PR 2.17 [95% CI 1.57 to 2.99]), ≤2 weekly on-call shifts (PR 1.93 [95% CI 1.46 to 2.55] and PR 2.2 [95% CI 1.66 to 2.92]) and >2 weekly on-call shifts (PR 2.26 [95% CI 1.4 to 3.65] and PR 1.97 [95% CI 1.23 to 3.15]), owning a physician office (PR 2.17 [95% CI 1.52 to 3.09] and PR 2.13 [95% CI 1.64 to 2.77]), working in a physician office (PR 2.10 [95% CI 1.42 to 3.11] and PR 2.04 [95% CI 1.46 to 2.86]), working in surgery-based specialties (PR 1.71 [95% CI 1.05 to 2.78] and PR 3.03 [95% CI 1.92 to 4.78]), and surgery plus internal medicine-based specialties (PR 2.48 [95% CI 1.58 to 3.90] and PR 1.68 [95% CI 1.18 to 2.38]). Men are more prevalent in ≥US$10 762 in all the categories of all work variables, except in the <20 hours of weekly workload category.

The difference in monthly wages was also explored according to the medical specialties stratified by gender (online supplementary table S3). The highest PRs of women in the first wage group (lowest wage) occurred in anaesthesiology (PR 2.30 [95% CI 1.38 to 2.30]), gynaecology and obstetrics (PR 2.27 [95% CI 1.47 to 2.27]), general surgery (PR 2.16 [95% CI 1.5 to 2.16]), other surgery specialties (PR 2.16 [95% CI 1.05 to 2.16]) and cardiology (PR 2.06 [95% CI 1.17 to 2.06]). Only in paediatrics, orthopaedics and trauma specialties the proportion of women in the lowest wage range was not significant.

By analysing the influences of the independent factors in relation to monthly wage, the model with the lowest residual deviance was the full model (table 2). This model explained a greater amount of variance when compared with all the other models. Residual deviance decreased from 8.00649 in the empty model to 7.16805 in the full model (online supplementary figure S1). After adjustment for the work characteristics in the multinomial multiple regression model, the gender variable remained at its estimated (ß) level, with no significant change. The final effect of this full model suggests that the probability of men receiving the highest salary level (≥US$10 762 per month) is 17.1% compared with 4.1% for women (online supplementary table S4 and figure S2).

The interactions between gender and work variables were studied in all simulations (online supplementary table S5). The probability of men being in the highest monthly wage class was higher than women for all factors. The most relevant interaction effects occurred in work in a physician office (19.1% vs 3.1%), <10 years of time in practice (8.6% vs 1.7%), 40–60 hours of weekly workload (20.0% vs 4.1%) and internal medicine-based specialties (17.2% vs 3.5%). The impact of these interactions can also be verified in online supplementary supplementary figure S3.

Discussion

Our results show a high wage disparity between male and female Brazilian physicians. Almost 80% of women are concentrated in the three lowest wage categories (≤US$3857, US$3587–5381 and US$5381– 7175), while 51% of men are represented in the three highest wage categories (US$7175–8969, US$8969–10 762 and ≥US$10 762), with a male prevalence of more than 15% over female physicians in the highest category. This scenario represents a vertical segregation in which women are under-represented in higher paying positions.45 46 This situation is similar to medical practice in the USA, where women earn 63% of men’s income,47 and in the UK, where men earn approximately 10% more than women.48

To explain the gender wage differences found, we included work-related characteristics such as weekly workload, time in practice and specialty as independent variables in a hierarchical modelling approach. However, even after these adjustments, the wage difference between men and women persisted, and the variability remained unexplained. These results are similar to those found in other studies8 10 12 13 19 43–46 that also included work characteristics as adjustment factors.

Many authors have suggested that the weekly workload is a plausible explanation for wage disparity between genders, arguing that women earn less because they work fewer hours than men.49 50 Our study shows that women were more prevalent than men in the categories of weekly workload of 20–40 and 40–60 hours (table 1), while male physicians were more prevalent among physicians working more than 60 hours per week. However, even after adjusting the wage for workload, female physicians were found to earn less than their male counterparts who work the same amount of time. The present study indicates that women also earn less when the wage differences are observed in each weekly workload range (table 2), as previously suggested.51 Such disparities were also reported in a British study,52 where female physicians’ income per hour represented 89% of men’s income. Similarly, in the USA,53 54 women accounted for 83% of men’s income even when working the same number of hours per week and weeks per year as men.

In Brazil, women are generally concentrated in specialties such as general practice, paediatrics, family medicine, gynaecology and obstetrics, which pay less if compared, for example, with surgical specialties, which are mostly occupied by men.55 They also tend to be salaried employees and less likely to own medical offices.15 56–58 Even in the face of this configuration, our results indicate that vertical segregation is present among specialists and non-specialists. Women are concentrated in the categories of lower wages, while men are predominant in the higher wage categories even when there is no difference in specialty between genders, suggesting that women might be occupying lower paying positions within specialties. These findings are similar to those reported by other scholars,8 9 who found significant income gaps between men and women, even after adjusting for variables such as workload, level of productivity and years of experience. Unequal payments within specialties were also reported by Desai and colleagues,8 who found that female physicians received statistically less reimbursement than male providers irrespective of the amount worked, level of productivity or years of experience.

Most studies tackling the underlying causes surrounding wage differences, even after introducing adjusting factors in their analyses, could not determine the factors that would in fact contribute for such inequalities. In this study, there was a significantly higher proportion of male physicians working in hospitals and private services than women, which could contribute to the wage gap found in our analysis. However, a previous study from our group using the same data set34 has found a higher proportion of male doctors working as dual practitioners or exclusively in private services, with a specialist profile and many years of medical training. Men also tend to occupy leading positions more frequently, as shown elsewhere.59 Due to the collinearity effect between the variables ‘time in practice’ and ‘specialty’ with the variable and ‘place of work’, we chose to work with the former, which added greater explicability to the phenomena of gender pay gap. If the ‘place of work’ variable cannot fully explain gender pay gap, ‘time in practice’ and ‘specialty’ cannot either, as they describe the phenomena in the same way.

In Brazil, factors such as entrepreneurialism of men towards achieving higher salaries, prestige and professional status might be associated with the wage disparity reported here. Yet, similarly to those findings reported by Apaydin et al,10 which have found that 30% of payment differences found in selected US states could not be explained by any of the adjusted variables included in the study, the specific drivers behind the income differences between men and women in Brazil remain undetermined and might rely merely on gender discrimination. Our results show that when the variable ‘time in practice’ was categorically analysed, the wage differences were observed in all categories, meaning that the wage disparity is not produced throughout the medical career. Therefore, we believe that gender might explain the wage disparity found. Nevertheless, future studies should incorporate variables related to sociological and cultural issues in their analyses, or the behaviour and practices of institutions and organisations.

Overall, the situation of women in the universe of medical work in Brazil is paradoxical. The number of women in the profession has increased significantly, but inequalities in relation to men persist, emphasising the remuneration gap. Our results highlight the fact that salary discrepancies between men and women in medicine should no longer be treated with neutrality or simply explained by isolated phenomena such as workload or type of specialty.

Subliminar or explicit gender discrimination is still reported and its consequences go beyond salary inequalities. For example, discrimination and harassment committed by men against women in the workplace affect performance and lead to absenteeism, demotivation, and even depression and anxiety.53 56 Both the International Labour Organization and WHO advocate for equal payments between men and women, requiring the elimination of all forms of discrimination in jobs and occupations60 so that gender equality prevails.61 According to the 2018 Global Gender Gap Report,62 there is still a 32.0% average gender gap found worldwide. The positive average trend registered since the last report is supported by improvements in the majority of countries covered both this year and last year. However, reduction of inequality will not be solved in legal and procedural terms, or only through wage policies; it will also depend on the social processes by which acceptable commitments are negotiated in relation to the realisation of gender equality.

This study relies on a probabilistic representation of Brazilian physicians and provides a robust, comprehensive multinomial model methodology that gives a differential advantage to support the gender wage inequality discussion. The main limitation is its cross-sectional design, which makes it impossible to establish causality or to argue about the temporal effect of physicians’ income difference. Salary is a complex and multidimensional variable that groups together individual and collective elements, fixed or flexible, and different sources can present different results. Furthermore, the medical profession is widely diversified in Brazil, reflecting the very nature of the country’s highly fragmented health system, where most physicians hold multiple job positions in public and private services, implicating different configurations of contract modalities and job affiliations.

The study was based on self-reported information on income, and even though the choice of collecting income data through wage categories might have helped to increase the adhesion response for this particular variable, the refusal rate (3.8% of respondents did not want to answer about income) and the very nature of categorising continuous quantitative variables might represent the underestimation of income values.

Conclusion

A significant gender wage difference exists in Brazil, and female physicians are more frequently positioned in lower wage categories. Our data show that even after adjusting for working factors as weekly workload, NOWOC shifts, physician office work, time in practice and specialty type, the gender influence in wage remains inexplicably high.

Future studies should always include the characteristics of medical work as adjustment variables. These studies may also include other sociodemographic variables or relate to trajectories and social organisation of private life. These should be added to qualitative studies that seek to understand gender inequalities from the relationships between men and women in different spaces and aspects of society.