Video Abstract
The US physician workforce includes an increasing number of women, with pediatrics having the highest percentage. In recent research on physicians, it is indicated that men earn more than women. It is unclear how this finding extends to pediatricians.
We examined cross-sectional 2016 data on earnings from the American Academy of Pediatrics Pediatrician Life and Career Experience Study, a longitudinal study of early- and midcareer pediatricians. To estimate adjusted differences in pediatrician earnings between men and women, we conducted 4 ordinary least squares regression models. Model 1 examined gender, unadjusted; model 2 controlled for labor force characteristics; model 3 controlled for both labor force and physician-specific job characteristics; and model 4 controlled for labor force, physician-specific job, and work-family characteristics.
Sixty-seven percent of Pediatrician Life and Career Experience Study participants completed the 2016 surveys (1213 out of 1801). The analytic sample was restricted to participants who completed training and worked in general pediatrics, hospitalist care, or subspecialty care (n = 998). Overall pediatrician-reported mean annual income was $189 804. Before any adjustment, women earned ∼76% of what men earned, or ∼$51 000 less. Adjusting for common labor force characteristics such as demographics, work hours, and specialty, women earned ∼87% of what men earned, or ∼$26 000 less. Adjusting for a comprehensive set of labor force, physician-specific job, and work-family characteristics, women earned ∼94% of what men earned, or ∼$8000 less.
Early- to midcareer female pediatricians earned less than male pediatricians. This difference persisted after adjustment for important labor force, physician-specific job, and work-family characteristics. In future work, researchers should use longitudinal analyses and further explore family obligations and choices.
In research among physicians, it is indicated that women earn less than men, even when adjusting for personal and professional characteristics. General pediatricians are often grouped with pediatric subspecialists, and there has not been a recent national study in which researchers have focused solely on pediatrician earnings.
Female pediatricians report earning less than male pediatricians. Before any adjustment, women earn 76% of what men earn, or ∼$51 000 less. Adjusting for a comprehensive set of characteristics, women report earning ∼94% of men’s earnings, or ∼$8000 less.
The United States physician workforce includes an increasing number of women,1 who bring substantial value to health care.2 From 2008 to 2018, women accounted for approximately half of medical school graduates.3 In 2017, at least half of physicians in several specialties were women, including child and adolescent psychiatry, geriatric medicine, internal medicine-pediatrics, obstetrics and gynecology, and pediatrics.4 Pediatrics includes the highest percentage of women, with 6 in 10 practicing pediatricians4,5 and 7 in 10 graduating pediatric residents6,7 who are women. Despite the growth of women in pediatrics and similarities in how men and women practice pediatrics,8 it is unclear whether they are paid equally.
In many US studies, researchers have examined income by gender. Specific to physician earnings, some researchers have used data from national surveys (eg, American Community Survey) and report gaps of $80 000 or more, with no adjustments for physician characteristics.9,10 Gender gaps narrow when adjusting for physician characteristics, such as age and work hours. However, studies based on national surveys are limited because they measure few characteristics important to understanding physician jobs, such as the type of specialty or practice.11
Other surveys conducted specifically among physicians also report gender gaps. For example, in a study conducted across specialties (eg, primary care, including pediatrics; obstetrics and gynecology; medical; and surgical) in 30 practices and 6 states, male physicians reported earning $90 000 more than female physicians in 2013.12 After adjustment for physician and job characteristics, the gap narrowed substantially, but male earnings remained $27 000 higher. In studies specifically conducted among pediatricians in the 1990s and early 2000s, it was found that female gender was associated with lower annual earnings among pediatricians in office-based practices13 and among primary care physicians, including pediatricians across 3 time periods.14
Limitations in existing studies on physician earnings include single institution settings,15 academic-specific focus,15–19 data collected over a decade ago,13,14 and no or limited adjustments to reported earnings.9,20 It is suggested in the research that in addition to gender, studies of physician earnings should account for specialty, work hours, years spent on the job, time out of work, other practice-specific characteristics, and geographic location.9 Work-life balance issues and choices made in careers have been less studied, particularly among physicians.
A 2017 position article of the American College of Physicians states that more research on physician compensation to examine gender disparities is needed in all practice settings.2 Limited data sources exist that allow researchers to comprehensively examine the full continuum of labor force characteristics, physician-specific job characteristics, and life factors that might modify physician wages.
In the broader literature on earnings, it is shown that female-dominated professions tend to have lower earnings than male-dominated ones.21 Consistent with this, in studies on income by specialty, it is suggested that pediatricians are among the lowest paid.17,22 However, primary care pediatricians are often grouped with pediatric subspecialists, and to our knowledge, there has not been a recent national study focused solely on pediatrician earnings that includes pediatricians practicing primary, hospital, and subspecialty care. Pediatrics provides a unique opportunity to take a more in-depth look at the gender earnings gap within an individual specialty because it has the highest proportion of female physicians4,23 and most female early- to midcareer pediatricians are mothers who are juggling work and home responsibilities.24
The American Academy of Pediatrics (AAP) Pediatrician Life and Career Experience Study (PLACES)25 provides a rich source of data that includes domains other studies on physician earnings have not included. PLACES is an ongoing longitudinal study in which researchers survey pediatricians across their careers on core issues, such as work-life balance, work environment, career satisfaction, daily stressors, life changes, and financial characteristics.26
In the current study, we examine cross-sectional PLACES data from early- to midcareer pediatricians on earnings by gender and explore the extent to which measured labor force (ie, key variables in the US Census Current Population Survey that are used to examine income), physician-specific job, and work-family characteristics account for observed gender differences.
Methods
Data Source and Respondents
We analyzed cross-sectional survey data collected in 2016 from PLACES.26 Participants are surveyed twice each year: a longer survey covering several domains (eg, work characteristics, satisfaction, work-life balance, life experiences) and a shorter survey with more in-depth questions about a single topic, such as earnings, which was selected by participants for the 2016 survey.
Pediatricians were recruited in 2012 to participate in PLACES. Participants were randomly selected from an AAP database that includes all pediatricians who completed US residency programs, both AAP members and nonmembers. In recruitment, 2 cohorts were targeted: those who completed residency in 2009–2011 and those who completed residency in 2002–2004. Four in 10 pediatricians (1925 out of 4677) invited to participate in PLACES initially signed up for the longitudinal study; of these, 1804 (93.7%) completed the first survey and were thereafter considered PLACES participants. Study participants are more likely to be female, AAP members, and graduates of US medical schools than target samples of pediatricians; detail has been described previously.26
The AAP Institutional Review Board approved the study.
Measures
We linked data from 2 PLACES surveys conducted in 2016 and demographic information collected during study recruitment in 2012. Questions were developed on the basis of review of other studies and input from the AAP PLACES advisory committee.
Participants answered a question on their annual income adapted from other research5,27 (“What is your estimated annual income from your professional activities before taxes? For employees, please include salary, bonus, and profit sharing contributions. For owners, please include earnings after tax-deductible business expenses but before income tax.”). Participants also answered questions about their demographic, job, and work-family characteristics, many of which were adapted from previous research.5,7,28–32 We hypothesized that these characteristics would be associated with earnings.
For analysis, we grouped the measured variables into 3 key groups: labor force, physician-specific job, and work-family characteristics, which are described in more detail below and in Table 1, with further information in Supplemental Table 3.
Pediatrician Earnings: Description of Variables That Were Examined
Labor Force . | Physician-Specific Job . | Work-Family . |
---|---|---|
Gender | Years in current position (continuous variable) | Marital status |
∙ Female | No. patients seen in a typical week (continuous variable) | ∙ Yes (married or partnered) |
∙ Male | Owner | ∙ No (never married or partnered, divorced, widowed) |
Race and ethnicity | ∙ No | Parental status: no. of own children (continuous variable) |
Years since residency graduation (continuous variable) | ∙ Yes | Choices in income for own children |
∙ White, non-Hispanic | Work area | ∙ No (reported making little or no sacrifice in income for children) |
∙ Asian | ∙ Suburban | ∙ Yes (reported the degree of sacrifice was very much or a fair amount) |
∙ Other, including minority (African American or black, Hispanic, American Indian) | ∙ Inner city | Choices in income for work environment |
Medical school location | ∙ Urban | ∙ No (reported making little or no sacrifice in income for work environment) |
∙ US | ∙ Rural | ∙ Yes (reported the degree of sacrifice was very much or a fair amount) |
∙ International | Academic setting | Work reduction |
Region of country | ∙ No | ∙ No (always reported working full-time) |
∙ Northeast | ∙ Yes | ∙ Yes (reported working part-time and/or not working on 1 or more surveys over the last 5 years) |
∙ Midwest | Compensation method | |
∙ South | ∙ Mix salary and share of billings or other measures of performance | |
∙ West | ∙ Other, including fixed salary, share of practice billings or workload, and shift or hourly | |
No. work h per wk (continuous variable) | ||
Specialty | ||
∙ General pediatrics | ||
∙ Hospitalist | ||
∙ Subspecialty, larger: neonatology, pediatric cardiology, pediatric critical care, pediatric emergency medicine, pediatric gastroenterology, and pediatric hematology-oncology33 | ||
∙ Subspecialty, smaller: all other subspecialties |
Labor Force . | Physician-Specific Job . | Work-Family . |
---|---|---|
Gender | Years in current position (continuous variable) | Marital status |
∙ Female | No. patients seen in a typical week (continuous variable) | ∙ Yes (married or partnered) |
∙ Male | Owner | ∙ No (never married or partnered, divorced, widowed) |
Race and ethnicity | ∙ No | Parental status: no. of own children (continuous variable) |
Years since residency graduation (continuous variable) | ∙ Yes | Choices in income for own children |
∙ White, non-Hispanic | Work area | ∙ No (reported making little or no sacrifice in income for children) |
∙ Asian | ∙ Suburban | ∙ Yes (reported the degree of sacrifice was very much or a fair amount) |
∙ Other, including minority (African American or black, Hispanic, American Indian) | ∙ Inner city | Choices in income for work environment |
Medical school location | ∙ Urban | ∙ No (reported making little or no sacrifice in income for work environment) |
∙ US | ∙ Rural | ∙ Yes (reported the degree of sacrifice was very much or a fair amount) |
∙ International | Academic setting | Work reduction |
Region of country | ∙ No | ∙ No (always reported working full-time) |
∙ Northeast | ∙ Yes | ∙ Yes (reported working part-time and/or not working on 1 or more surveys over the last 5 years) |
∙ Midwest | Compensation method | |
∙ South | ∙ Mix salary and share of billings or other measures of performance | |
∙ West | ∙ Other, including fixed salary, share of practice billings or workload, and shift or hourly | |
No. work h per wk (continuous variable) | ||
Specialty | ||
∙ General pediatrics | ||
∙ Hospitalist | ||
∙ Subspecialty, larger: neonatology, pediatric cardiology, pediatric critical care, pediatric emergency medicine, pediatric gastroenterology, and pediatric hematology-oncology33 | ||
∙ Subspecialty, smaller: all other subspecialties |
For further justification for why these variables were examined, see Supplemental Table 3.
For labor force characteristics, we included gender, years since residency training completion (proxy for age and work experience), race and ethnicity, medical school location, region of country, hours worked per week, and primary job or specialty because these are key variables in the US Census Current Population Survey used to examine income11,34,35 and important conventional human capital characteristics.36,37 For race and ethnicity, because of small numbers, we combined Hispanic, African American or black, American Indian, and other race into one group. We included region of country because earnings and cost of living might vary across regions38 and hours worked because part-time hours are common among female pediatricians,39 and human capital models indicate work hours are a major source of gender earning gaps.40 Specialty (eg, general pediatrics, hospitalist, smaller subspecialty, and larger subspecialty, which is described in detail in Supplemental Table 3) was included as a labor force characteristic because it further defines how occupation and earnings among different pediatric subspecialties might vary.41 We categorized subspecialty as larger (neonatology, cardiology, critical care, emergency medicine, gastroenterology, and hematology-oncology) and smaller (all other subspecialties) on the basis of fellowship size reported by the American Board of Pediatrics.33
For physician-specific job characteristics, we included variables that provided more detail on the nature of the pediatrician’s current job, including number of years in current job, workload (number of patients seen per week), practice ownership, work setting (area, academic), and compensation method. In previous research, authors controlled for work load,13 practice ownership,13,42,43 work area,13,44 and academic setting45 in studies on earnings.
For work-family characteristics, we included marital status, number of children, choices made in job for their own children, choices made in job for their work environment, and periods of work reduction (reported working part-time and/or not working on one or more surveys over the last 5 years). These variables provide information often missing in analyses of income disparities: choices made for their own families (further described in Supplemental Table 3). For example, women may be seeking flexible work schedules and/or take on more responsibilities at home.46
Data Analysis
Annual earnings self-reported by pediatricians in 2016 were analyzed in several ways. First, we examined the distribution and overall mean of earnings by gender. Second, for the overall sample and separately for women and men, we used t test and 1-way analysis of variance to examine pediatrician earnings by each labor force, physician-specific job, and work-family characteristic. Third, to estimate the adjusted difference in the log of pediatrician earnings between men and women, we used ordinary least squares regression. We conducted 4 regression models. Model 1 examined gender, unadjusted; model 2 controlled for labor force characteristics; model 3 controlled for both labor force and physician-specific job characteristics; and model 4 controlled for labor force, physician-specific job, and work-family characteristics (all characteristics are described in Table 1, Supplemental Table 3). We converted the logged regression gender coefficient back to the original scale to help interpret the findings and report the geometric means. We also used the likelihood ratio test to compare the model estimates for model 1 and model 2, model 2 and model 3, and model 3 and model 4.
For bivariate tests, continuous variables (years since residency graduation, work hours in a typical week, years in current position, number of patients seen in a typical week, number of children) were categorized for presentation purposes. For multivariable tests, these variables were included as continuous variables, centered at their means.
The number of cases in each analysis varied slightly because of missing values for specific questions. All analyses were conducted by using Stata Version 15 (Stata Corp, College Station, TX).
Results
Sixty-seven percent of PLACES participants completed both 2016 surveys (1213 out of 1801 = 67%), which was similar for women and men (P = .99). The analytic sample was restricted to participants who completed the question on income and worked in general pediatrics (n = 507), hospitalist care (n = 118), or subspecialty care (n = 373) in 2016 (total n = 998). The 215 participants who were excluded from analysis were trained in a surgical specialty or internal medicine-pediatrics, working in a nonclinical and/or non-US position, in a fellowship training position, not working in 2016, and/or had missing data on income and/or specialty. Overall, 73.5% of the analytic sample are women.
Unadjusted Earnings by Labor Force, Physician-Specific Job, and Work-Family Characteristics
Overall pediatrician-reported mean annual income in 2016 was $189 804. For women, the unadjusted mean was $176 738 (median = $170 000, minimum = $9000, maximum = $750 000, and skewness = 1.76). For men, the mean was $226 133 (median = $210 000, minimum = $80 000, maximum = $700 000, and skewness = 1.83).
Across characteristics, female pediatricians consistently reported lower mean earnings than male pediatricians (Table 2). For example, for those in general pediatrics, women reported earning $171 047 and men reported $223 472. Also, a disproportionate number of women were in the lowest-paid group of several characteristics. For example, 418 of 734 women (56.9%) and 89 of 264 men (33.7%) reported working in general pediatrics, and 271 of 727 women (37.3%) and 35 of 261 men (13.4%) reported working <40 hours per week.
Pediatrician Yearly Unadjusted Earnings by Gender and Labor Force, Physician-Specific Job, and Work-Family Characteristics
Characteristics . | Mean Unadjusted Yearly Earnings . | ||
---|---|---|---|
Female, Mean $ (n) . | Male, Mean $ (n) . | All, Mean $ (SD) . | |
Total, N = 998c | 176 738 (734) | 226 133 (264) | 189 804 (80 265) |
Labor force | |||
Years since residency training completionb,c | |||
5–9 | 172 172 (385) | 206 581 (124) | 180 555 (60 872) |
10–15 | 181 744 (349) | 243 450 (140) | 199 432 (95 513) |
Race and ethnicitya,c | |||
Asian, non-Hispanic | 162 108 (129) | 228 125 (40) | 177 734 (68 849) |
Other (includes Hispanic, African American or black, other) | 169 250 (128) | 192 643 (28) | 173 449 (66 182) |
White, non-Hispanic | 182 703 (477) | 230 510 (196) | 196 626 (84 956) |
Medical school location | |||
International | 167 500 (79) | 220 636 (33) | 183 156 (72 285) |
United States | 177 746 (653) | 226 918 (231) | 190 595 (81 282) |
Region of country | |||
Northeast | 167 433 (146) | 214 783 (46) | 178 777 (77 891) |
West | 174 283 (189) | 225 213 (61) | 186 710 (76 060) |
Midwest | 180 772 (162) | 228 985 (66) | 194 728 (82 907) |
South | 183 021 (232) | 230 418 (91) | 196 374 (82 243) |
Hours worked per wka,c | |||
<30 | 107 706 (126) | 173 333 (3) | 109 233 (52 530) |
30–39 | 185 172 (145) | 226 406 (32) | 192 627 (90 159) |
40–49 | 189 633 (211) | 231 243 (70) | 199 998 (69 819) |
50–59 | 193 630 (150) | 215 899 (89) | 201 922 (64 124) |
≥60 | 200 868 (95) | 239 433 (67) | 216 818 (88 128) |
Specialtya,b,c | |||
General pediatrics | 171 047 (418) | 223 472 (89) | 180 250 (83 815) |
Hospitalist | 173 651 (86) | 204 031 (32) | 181 890 (55 195) |
Subspecialty, smaller | 163 669 (108) | 178 542 (48) | 168 245 (68 913) |
Subspecialty, larger | 209 982 (122) | 260 116 (95) | 231 930 (76 520) |
Physician-specific job | |||
Years at current joba,b,c | |||
<3 | 164 838 (187) | 201 500 (70) | 174 824 (62 826) |
3–5 | 164 616 (229) | 231 791 (86) | 182 956 (76 649) |
>5 | 192 465 (318) | 237 593 (108) | 203 905 (89 584) |
No. patients per wka,b,c | |||
<60 | 159 339 (357) | 211 550 (140) | 174 046 (70 985) |
60 or more | 194 432 (367) | 243 225 (120) | 206 455 (85 721) |
Ownera,b,c | |||
No, employee or contractor | 168 393 (610) | 220 479 (217) | 182 060 (71 005) |
Yes | 219 857 (122) | 252 234 (47) | 228 861 (107 192) |
Work area | |||
Inner city | 164 447 (152) | 213 197 (66) | 179 206 (63 259) |
Suburban | 178 790 (296) | 240 654 (78) | 191 692 (90 622) |
Urban | 177 130 (221) | 226 520 (100) | 192 516 (71 757) |
Rural | 194 259 (58) | 210 250 (20) | 198 359 (91 299) |
Academic work settinga,b,c | |||
Yes | 169 087 (257) | 207 255 (106) | 180 233 (65 468) |
No | 181 034 (475) | 238 797 (158) | 195 452 (87 261) |
Compensation methoda,b,c | |||
Fixed salary, share of practice billings and/or workload, or shift or hourly | 165 569 (525) | 216 216 (185) | 178 765 (73 659) |
Mix of salary and billings or other measures of performance | 204 913 (206) | 249 354 (79) | 217 232 (89 376) |
Work-family | |||
Married or partnered | |||
No | 171 701 (93) | 210 185 (27) | 180 360 (65 274) |
Yes | 177 649 (638) | 228 123 (235) | 191 236 (82 208) |
No. childrenb,c | |||
0 | 178 941 (124) | 201 947 (38) | 184 338 (59 151) |
1 | 169 043 (121) | 191 029 (35) | 173 976 (62 343) |
2 | 180 974 (316) | 232 353 (102) | 193 512 (80 750) |
≥3 | 172 801 (173) | 244 701 (87) | 196 860 (97 760) |
Choices in income for own childrena,c | |||
Yes | 158 493 (336) | 210 527 (74) | 167 884 (77 331) |
No | 192 215 (396) | 232 211 (190) | 205 183 (78 837) |
Choices in income for work environmenta,b,c | |||
Yes | 162 670 (261) | 206 767 (90) | 173 977 (73 591) |
No | 184 378 (469) | 235 930 (172) | 198 211 (82 633) |
Work reduction: reported working part-time and/or not working on ≥1 surveys over the last 5 ya,c | |||
Yes | 149 711 (325) | 207 129 (31) | 154 711 (75 003) |
No | 198 214 (409) | 228 661 (233) | 209 264 (76 431) |
Characteristics . | Mean Unadjusted Yearly Earnings . | ||
---|---|---|---|
Female, Mean $ (n) . | Male, Mean $ (n) . | All, Mean $ (SD) . | |
Total, N = 998c | 176 738 (734) | 226 133 (264) | 189 804 (80 265) |
Labor force | |||
Years since residency training completionb,c | |||
5–9 | 172 172 (385) | 206 581 (124) | 180 555 (60 872) |
10–15 | 181 744 (349) | 243 450 (140) | 199 432 (95 513) |
Race and ethnicitya,c | |||
Asian, non-Hispanic | 162 108 (129) | 228 125 (40) | 177 734 (68 849) |
Other (includes Hispanic, African American or black, other) | 169 250 (128) | 192 643 (28) | 173 449 (66 182) |
White, non-Hispanic | 182 703 (477) | 230 510 (196) | 196 626 (84 956) |
Medical school location | |||
International | 167 500 (79) | 220 636 (33) | 183 156 (72 285) |
United States | 177 746 (653) | 226 918 (231) | 190 595 (81 282) |
Region of country | |||
Northeast | 167 433 (146) | 214 783 (46) | 178 777 (77 891) |
West | 174 283 (189) | 225 213 (61) | 186 710 (76 060) |
Midwest | 180 772 (162) | 228 985 (66) | 194 728 (82 907) |
South | 183 021 (232) | 230 418 (91) | 196 374 (82 243) |
Hours worked per wka,c | |||
<30 | 107 706 (126) | 173 333 (3) | 109 233 (52 530) |
30–39 | 185 172 (145) | 226 406 (32) | 192 627 (90 159) |
40–49 | 189 633 (211) | 231 243 (70) | 199 998 (69 819) |
50–59 | 193 630 (150) | 215 899 (89) | 201 922 (64 124) |
≥60 | 200 868 (95) | 239 433 (67) | 216 818 (88 128) |
Specialtya,b,c | |||
General pediatrics | 171 047 (418) | 223 472 (89) | 180 250 (83 815) |
Hospitalist | 173 651 (86) | 204 031 (32) | 181 890 (55 195) |
Subspecialty, smaller | 163 669 (108) | 178 542 (48) | 168 245 (68 913) |
Subspecialty, larger | 209 982 (122) | 260 116 (95) | 231 930 (76 520) |
Physician-specific job | |||
Years at current joba,b,c | |||
<3 | 164 838 (187) | 201 500 (70) | 174 824 (62 826) |
3–5 | 164 616 (229) | 231 791 (86) | 182 956 (76 649) |
>5 | 192 465 (318) | 237 593 (108) | 203 905 (89 584) |
No. patients per wka,b,c | |||
<60 | 159 339 (357) | 211 550 (140) | 174 046 (70 985) |
60 or more | 194 432 (367) | 243 225 (120) | 206 455 (85 721) |
Ownera,b,c | |||
No, employee or contractor | 168 393 (610) | 220 479 (217) | 182 060 (71 005) |
Yes | 219 857 (122) | 252 234 (47) | 228 861 (107 192) |
Work area | |||
Inner city | 164 447 (152) | 213 197 (66) | 179 206 (63 259) |
Suburban | 178 790 (296) | 240 654 (78) | 191 692 (90 622) |
Urban | 177 130 (221) | 226 520 (100) | 192 516 (71 757) |
Rural | 194 259 (58) | 210 250 (20) | 198 359 (91 299) |
Academic work settinga,b,c | |||
Yes | 169 087 (257) | 207 255 (106) | 180 233 (65 468) |
No | 181 034 (475) | 238 797 (158) | 195 452 (87 261) |
Compensation methoda,b,c | |||
Fixed salary, share of practice billings and/or workload, or shift or hourly | 165 569 (525) | 216 216 (185) | 178 765 (73 659) |
Mix of salary and billings or other measures of performance | 204 913 (206) | 249 354 (79) | 217 232 (89 376) |
Work-family | |||
Married or partnered | |||
No | 171 701 (93) | 210 185 (27) | 180 360 (65 274) |
Yes | 177 649 (638) | 228 123 (235) | 191 236 (82 208) |
No. childrenb,c | |||
0 | 178 941 (124) | 201 947 (38) | 184 338 (59 151) |
1 | 169 043 (121) | 191 029 (35) | 173 976 (62 343) |
2 | 180 974 (316) | 232 353 (102) | 193 512 (80 750) |
≥3 | 172 801 (173) | 244 701 (87) | 196 860 (97 760) |
Choices in income for own childrena,c | |||
Yes | 158 493 (336) | 210 527 (74) | 167 884 (77 331) |
No | 192 215 (396) | 232 211 (190) | 205 183 (78 837) |
Choices in income for work environmenta,b,c | |||
Yes | 162 670 (261) | 206 767 (90) | 173 977 (73 591) |
No | 184 378 (469) | 235 930 (172) | 198 211 (82 633) |
Work reduction: reported working part-time and/or not working on ≥1 surveys over the last 5 ya,c | |||
Yes | 149 711 (325) | 207 129 (31) | 154 711 (75 003) |
No | 198 214 (409) | 228 661 (233) | 209 264 (76 431) |
One-way analysis of variance, P < .05 for female (test examined bivariate associations for annual earnings and characteristics separately for female and male pediatricians).
One-way analysis of variance, P < .05 for male.
One-way analysis of variance, P < .05 for all (both female and male).
Overall earnings were associated with many of the characteristics (Table 2). Among labor force characteristics, pediatricians in the larger subspecialty group (eg, neonatology, cardiology, critical care, emergency medicine, gastroenterology, and hematology-oncology) and those working ≥60 hours reported the highest incomes, reporting overall mean earnings of $231 930 and $216 818, respectively. Among physician-specific characteristics, pediatricians who reported more years at their current job, more patients per week, being an owner, working in a nonacademic work setting, and being paid by a mix of salary and billings or performance measures reported higher earnings. For example, the overall mean income of owners was $228 861 and employees was $182 060, P < .001. Among work-family characteristics, large differences in mean unadjusted earnings were found. For example, the overall mean for pediatricians who reported making choices in their earned income for their children was significantly lower than those not reporting such choices ($167 884 vs $205 183, P < .001).
Independent Effect of Gender on Log of Pediatrician Earnings: Unadjusted and Adjusted Earnings
In Figure 1, we present the male gender coefficient and R2 for 4 models using the log of annual earnings. Without any adjustment, male pediatricians earned $51 319 more than female pediatricians, P < .001 (model 1). Adjusting for labor force characteristics, men earned $25 566 more than women, P < .001 (model 2). Adjusting for both labor force and physician-specific job characteristics, men earned $14 240 more than women, P < .001 (model 3). Finally, when adjusting for labor force, physician-specific job, and work-family characteristics, men earned $7997 more than women, P < .05 (model 4). The model R2 increased across the 4 models, from 0.08 in the unadjusted model 1 to 0.48 in model 4. We used likelihood ratio tests to assess whether each subsequent model led to a significant increase in model fit; across models, each increase in explained earnings variation was statistically significant (P < .001). The female-to-male earnings ratio increased across models, from 0.76 in model 1, to 0.87 in model 2, 0.91 in model 3, and 0.94 in model 4. The full model results are presented in Supplemental Table 4.
Female-male pediatrician annual earnings gap, unadjusted and adjusted by labor force, physician-specific job, and work-family characteristics determined by using ordinary least squares regression. Gender coefficient ($): male (ref = female); bars represent 95% confidence intervals. Dollar amounts are log of annual earnings (95% confidence interval) converted back to original scale ($). For full model results, see Supplemental Table 4. Labor force characteristics are as follows: gender, years since residency graduation, race and ethnicity, medical school location, region of country, number of work hours per week, and specialty. Physician-specific job characteristics are as follows: years in current position, number of patients seen in a typical week, owner, work area, academic setting, and compensation method. Work-family characteristics are as follows: marital status, parental status, choices made for own children, choices made for work environment, and work reduction over past five survey years.
Female-male pediatrician annual earnings gap, unadjusted and adjusted by labor force, physician-specific job, and work-family characteristics determined by using ordinary least squares regression. Gender coefficient ($): male (ref = female); bars represent 95% confidence intervals. Dollar amounts are log of annual earnings (95% confidence interval) converted back to original scale ($). For full model results, see Supplemental Table 4. Labor force characteristics are as follows: gender, years since residency graduation, race and ethnicity, medical school location, region of country, number of work hours per week, and specialty. Physician-specific job characteristics are as follows: years in current position, number of patients seen in a typical week, owner, work area, academic setting, and compensation method. Work-family characteristics are as follows: marital status, parental status, choices made for own children, choices made for work environment, and work reduction over past five survey years.
Discussion
We analyzed self-reported 2016 annual earnings among early- to midcareer pediatricians and found women earn less than men. Before any adjustment, female pediatricians earn 76% of what male pediatricians earn, or ∼$51 000 less. Adjusting for common labor force characteristics, such as demographics, experience, work hours, and specialty, female pediatricians earn 87% of what male pediatricians earn, or ∼$26 000 less. Adjusting for both labor force and physician-specific job characteristics, female pediatricians earn 91% of male pediatrician earnings, or ∼$14 000 less. Finally, adjusting for a comprehensive set of labor force, job-specific, and work-family variables, female pediatricians earn 94% of male pediatrician earnings, or ∼$8000 less.
Our study is comparable to gender differences found in other studies of US workers. In our unadjusted model, we found the female-to-male earnings ratio was 0.76. Among full-time US workers, the female-to-male unadjusted annual earnings ratio was 0.81 in 2016.47 A US government report by the Joint Economic Committee summarized the persistent gender earnings gap across diverse occupations and education levels, with the largest pay gap among those with professional degrees and worse for mothers and part-time workers.48
Our findings compare with studies of other physicians in which researchers found large unadjusted gender differences in income and smaller differences when adjustments are made, ranging from women earning 8% to 38% less than men.9,13,17–19,49–51 Because we controlled for labor force, job-specific, and work-family variables in our study, the findings support previous reports in which authors suggested earnings gaps may be related to mothers who might prioritize job flexibility19 and that periods of part-time work and not working are related to earnings.12
The role of employment negotiations and discrimination in the earnings gap has been discussed.44 Women and men may make different choices, negotiate differently, or experience different pressure from themselves or others regarding their own children and families. Women, including physicians, spend more time on household and child care responsibilities than men.46,52,53 They may accept lower salaries for nonmonetary benefits, such as fewer work hours,54 flexibility of work hours, and location or community of work place.44 Our study is unique because our focus is on one specialty, and we adjust for a comprehensive set of work-life characteristics that other researchers have suggested are important.12,18–20 Besides labor force variables (eg, work hours and specialty), some of the largest differences in earnings were among the work-family characteristics. Still, even when controlling for these characteristics, we found that early- to midcareer women in pediatrics earned $8000 less than men.
The gender pay gap is complex and multifaceted. Economists have discussed the issue extensively and propose explanations such as education, occupation choice, experience, work place flexibility and hours, negotiation skills, competitiveness, parenting, and time away from work.55,56 They suggest that, in part, women earn less because of long work hours and inflexible conflict with home responsibilities.55 In a study of master of business administration graduates, it was found that women and men had similar income and work hours at the start of their careers, but over time, both income and work hours increasingly diverged.55 Researchers also reported that work interruptions and differences in hours worked explained much of the gender gap in earnings and having children was related to more work interruptions, fewer hours worked, and less income for women but not men. Economist Claudia Goldin suggests that to obtain convergence of pay, changes to the structure and renumeration of jobs are needed (eg, more-flexible work schedules without reduction in opportunities and pay).57
US academic medical institutions are working toward policies to achieve pay equity.58 In a study of an academic pediatrics department, gender salary inequalities were found and an intervention strategy was designed that focused on several areas, including salary corrections and annual monitoring of salaries.15 Postintervention, gender salary differences were no longer significant. Their intervention might be helpful to other physician employers.
Our study has strengths, including a national sample, focus on a specialty with a majority of women, and examination of a comprehensive set of physician characteristics. Limitations include that data are self-reported by early- and midcareer pediatricians and many different pediatric subspecialties were combined because of insufficient numbers to examine separately. The generalizability to other specialties or career stages and whether our findings differ from studies of specialties with lower portions of women is unclear. The difference in earnings might be more substantial as pediatricians progress through their careers. Although the response among PLACES participants who completed the study surveys was high, the initial project sign-up rate was lower, at ∼40%, and women, US medical school graduates, and AAP members were more likely to sign up. We could not adjust for all possible characteristics, so it remains unclear whether it is only gender that explains the remaining income gap between men and women. Because of small numbers of Hispanic and African American pediatricians in our sample, we combined these pediatricians with those who specified “other race” and were not sufficiently powered to examine differences in earnings for specific groups. Finally, the data are cross-sectional and therefore do not explore how pediatrician earnings and the gender gap progress over time, which will be possible with future PLACES data.
Conclusions
In this study, we found gender differences in annual earnings among early- and midcareer pediatricians, with women earning less than men. This difference persists after adjustment for important labor force, physician-specific, and work-life characteristics. With more female physicians in the workforce, the findings can be important to understanding overall physician earnings. In future work, researchers should use longitudinal analysis and further explore periods of part-time work, family obligations, and work flexibility.
Acknowledgments
We thank the pediatricians participating in PLACES who are all giving generously of their time to make this project possible. This research was supported by the AAP.
Ms Frintner conceptualized and designed the study, conducted the analyses, coordinated and supervised data collection, drafted the initial manuscript, and reviewed and revised the manuscript; Dr Sisk assisted with the conception and design of the study, reviewed and helped interpret the analyses, and reviewed and revised the manuscript; Drs Olson, Byrne, Freed, and Starmer assisted with the conception and design of the study and critically reviewed the manuscript; and all authors approved the final manuscript as submitted.
The research presented in this article is that of the authors and does not reflect the official policy of the AAP.
FUNDING: This study was supported by the American Academy of Pediatrics.
References
Competing Interests
POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential conflicts of interest to disclose.
FINANCIAL DISCLOSURE: The authors have indicated they have no financial relationships relevant to this article to disclose.
Comments