Analysis of US Pediatric Pharmacists Incomes: A Gender Comparison Survey Study by the Pediatric Pharmacy Association, Practice-Based Research Network

Abstract

OBJECTIVES

While gender disparities in the US workforce have received substantial attention, income inequalities among subspecialty pharmacists remain understudied. This study aimed to develop a professional profile of pediatric pharmacists in the United States, construct and test gender-specific income-determination models, and identify and compare factors influencing income among male and female pediatric pharmacists.

METHODS

Data were collected via a national survey targeting pediatric pharmacists. The survey included human-capital, job-related, and demographic variables. Separate income-determination models were estimated between genders, using ordinary least-squares with logged annual income as the dependent variable. Key covariates included hours worked, years of experience, administrative role, salary negotiation history, and work location.

RESULTS

A total of 285 responses were analyzed from a 29.3% response rate. Women outnumbered men 3:1. The average annual income difference between male and female pharmacists was $10,294 (6.4%, not significant); however, regression estimates showed significant differences in annual income determinants by gender (p ≤ 0.05). Work input and experience positively influenced income for both genders, but job-related covariates were significant only for women. Working more hours and having more years of experience led to bigger pay increases for men than for women. Projected annual earnings based on model estimates revealed a statistically significant gender income gap of $10,745.

CONCLUSIONS

The study highlights a nuanced gender disparity in income among pediatric pharmacists, with income determinants functioning differently across genders. Although the average gender pay gap was not statistically significant, regression-based projections suggest potential underlying inequities. These findings call for further research and institutional dialogue to address gender-based income disparities in specialized pharmacy fields.

Introduction

Gender disparities in the US workforce have been the subject of long-standing debate. Within pharmacy, several articles have focused recently on gender equity in academia and leadership.^1–6 In academia, between 52% and 72% of pharmacy faculty at all ranks report experiences and perceptions of gender inequity.^5,6 A study by White et al⁷ reveals a male predominance within US Boards of Pharmacy members and highlights the need for increased women’s representation. The study finds that although women make up nearly 60% of US pharmacists, they hold only 38.8% of state Board of Pharmacy positions, highlighting a need to increase women’s representation to promote gender equity and leverage associated benefits such as stronger leadership, improved performance, and reduced bias in regulatory decision-making.

Inequities in pharmacy academia and leadership are not the only concern. Various research endeavors have been conducted that compare gender disparities in pharmacists’ incomes and advancement opportunities. A study by Carvajal et al⁸ shows the existence of pockets of income inequality within the profession. The authors find that male pharmacists generally earn more than female pharmacists, but the wage gap is concentrated among those who are older, married, more experienced, primarily dispensing medications, and working in hospital settings. Along these lines, Popovici and Carvajal⁹ estimate an overall gender earnings gap of up to 18.6%. Mott et al,¹⁰ in the 2022 National Pharmacist Workforce Study (NPWS), report that fewer than one-half of practitioners agree that people from all backgrounds and identities have equitable opportunities to advance in their careers. Using the NPWS as a representation of the overall pharmacist workforce, it was shown that female respondents represented a 59.7% majority of the population, enhancing the noted gender disparities.¹⁰ Within this framework of apparent gender disparities, the idea emerged to probe the nature and composition of the pediatric pharmacist workforce, as well as possible income differences between male and female practitioners. Specifically, this study aimed to 1) develop a professional profile of pediatric pharmacists working in the United States; 2) formulate and test an income-determination model for men and women of this pharmacist workforce segment; and 3) identify similarities and differences between male and female pharmacists in relevant variables identified in the income-determination process.

Materials and Methods

Data Source.

This study was based on survey data gathered via a 22-element REDCap (Research Electronic Data Capture; Vanderbilt University, Nashville, TN) electronic questionnaire hosted by the University of Oklahoma between January 28 and February 28, 2025, from pediatric pharmacists working in the United States.¹¹

The survey was validated by a group of 42 pediatric pharmacists prior to distribution. Following validation, the electronic survey was distributed via email to the pharmacist membership of the Pediatric Pharmacy Association (PPA) as a representative sample of pediatric pharmacists (974 members). The true number of pediatric pharmacists practicing in the United States is difficult to ascertain; however, the Board of Pharmacy Specialties credentials pharmacists in 14 specialties, including pediatrics, though certification is not required to practice in the field. There are currently over 1970 board-certified Pediatric Pharmacotherapy Specialists in the United States.

The data collected were from voluntary, self-reported responses. Following the initial email request, a follow-up was sent after 2 weeks to encourage participation. The survey closed after 4 total weeks. The survey questionnaire is presented in the supplemental Table.

Survey Questionnaire.

Pediatric Pharmacy Association members and the validation group of pediatric pharmacists in the United States were asked to provide information on their human-capital, job-related, and demographic characteristics along with data on gross income and work input. The human-capital questions included academic degree (e.g., BS in Pharmacy, PharmD), whether the pharmacist ever completed a residency or fellowship program, specialty board certification, years of experience as a registered pharmacist, and years practicing pharmacy (including residency and/or fellowship). These questions aimed to measure practitioners’ investment in skills and experience, factors likely associated with higher income levels.⁹

The job-related survey questions included primary role (clinical, administration, distribution, academia), primary site (hospital, retail, ambulatory, other), work state, location (large city central, large city suburbs, small city, rural), employment type (salaried or hourly), salary negotiation history, multiple-job status, and labor union membership. A large city central was defined as a central business district of a city with a population of at least 300,000 inhabitants; a large city suburb was a residential area of a city with a population of at least 300,000 people; a small city had at least 50,000 but fewer than 300,000 inhabitants; and a rural area was defined as a concentration of fewer than 50,000 people.

The third group of survey questions consisted of demographic characteristics. These included gender (male, female, non-binary, prefer not to answer), age, race (White, non-White), ethnicity (Hispanic/Latino, non-Hispanic/Latino), marital status (never married, married/cohabitating, separated/divorced/widowed), total number of children, and number of children younger than 18 years. Several studies suggest that these variables influence work-related decisions. For example, having children negatively affects women’s labor force participation and consequently their earnings, while positively influencing men’s earnings.¹² Other studies have found that belonging to a minority group tends to be associated with negative labor outcomes.^13–15 In addition, pediatric pharmacists were asked to provide information on the average number of hours worked per week, hourly wage rate, and annual income earned in each job, plus total annual household income. The full study survey is shown in the Supplemental Table.

Configuration of the Model.

The income-determination functions were estimated by using ordinary least-squares. Two separate models with identical covariates were developed for male and female pharmacists to compare the direction, magnitude, and statistical significance of each covariate’s influence on earnings while controlling for other confounders, thus avoiding gender differences that might be due to interaction effects. An alternative pooled model, including a gender dichotomous variable, was not pursued because of its likely incorrect assumption that the income responses to covariates were equal regardless of gender. Gender-specific models sought to provide evidence that male and female pharmacist incomes responded differently to identical stimuli.

An initial equation was formulated whereby annual income appeared as a function of work input and experience. Work input is universally considered to be the most important determinant of labor-related earnings; in pharmacy, Goldin and Katz¹⁶ even suggest that it is the only relevant variable. Work input was measured by using a linear and a quadratic component to account for diminishing returns as is customary in the labor economics literature.¹⁷ In addition, experience was meant to assess the basic impact of human capital on earnings. Professional experience was included as a covariate because it is a well-established determinant of earnings in labor economics research, including studies of the pharmacist labor force, reflecting the accumulation of skills, knowledge, and productivity over time. Any of 3 variables could have been used to assess the influence of experience on income—age, number of years as a registered pharmacist, and number of years practicing pharmacy. The high correlation among these 3 variables prevented their joint inclusion in the analysis owing to multicollinearity. The number of years of experience ultimately was chosen, and its coefficients were anticipated to be positive. Then variables from the survey questionnaire were added as covariates into the equation, one at a time, to explore their effect on income (Table 1). If either or both the male- and/or female-pharmacist coefficient was/were statistically significant, the covariate was kept in the equation; otherwise, it was removed. Three job-related variables met this criterion: an administrative primary role, salary negotiation history, and working in a large city (central or suburbs).

Table 1.

Variables in the Model

Variable	Explanation
i = 1	Male pharmacists
i = 2	Female pharmacists
j = 1 …, ni; and ni	Number of pharmacists in the i th gender
ln Eij	Vector of the natural logarithm of income earned by the j th pharmacist of the i th gender
Whij	Matrix of work-input values, including average number of hours worked per week (h = 1) and average number of hours worked per week squared (h = 2), reported by the j th pharmacist of the i th gender
Xij	Vector of human-capital characteristics, measured by number of years of experience, reported by the j th pharmacist of the i th gender
Zhij	Matrix of 3 sets of job-related characteristics, including an administrative position (h = 1), salary negotiation history (h = 2), and working in a large city (h = 3), reported by the j th pharmacist of the i th gender
uij	Vector of normally and independently distributed stochastic terms, with mean zero and variance σi2, pertaining to the j th pharmacist of the i th gender
αi	The least-squares constant term for the i th gender
λhi	Vector of 2 parameters estimated for the i th gender
γi	Scalar estimated for the i th gender
θhi	Vector of 3 parameters estimated for the i th gender

The matrix of job-related characteristics consisted of 3 dichotomous covariates. The first identified pharmacists whose primary role was administrative; holding a management position usually requires skills and quality of work commensurate with greater pay, so the coefficients of this covariate were expected to be positive.¹⁸ The second job-related covariate indicated pharmacists who had negotiated their salary in their careers; its estimated coefficients also were expected to be positive; and the third covariate indicated pharmacists working in large cities, including the central part and suburbs. As a rule, the costs of living and commuting in large cities are substantially greater than in smaller cities and rural areas, so incomes were expected to be higher, along with positive estimated coefficients.¹⁹

The dependent variable, defined as annual, pre-tax income earned for working as a pharmacist, was logged to mitigate the influence of outliers; thus, the estimated coefficients depicted relative differences rather than absolute amounts. The results show relative changes in earnings rather than exact dollar amounts.

Results

A total of 299 participants responded to the survey. Nine surveys were excluded owing to the respondents stating they were not currently working and 5 were excluded owing to not completing the survey. A total of 285 survey questionnaires (29.3%) were used in computing results and estimating parameters. Only respondents who provided complete information for all variables used in the regression analysis were included; surveys with missing data on any of these key variables were excluded from the sample. Two responses were excluded owing to non-binary and preferred-not-to-answer gender responses. The response rate was adequate for statistical inference in cross-sectional studies such as this one.^20,21 Responses from men were outnumbered by women 3:1.

Gender Composition.

The means and SDs of annual pharmacy-related income earned by survey participants, as well as variables potentially hypothesized to affect it, are presented in Table 2. Male respondents earned $10,294 more annually than female respondents, but the difference was not statistically significant. Similarly, male respondents’ annual household income exceeded female respondents’ household income by $20,450; the difference lacked significance as well. The average number of hours worked per week was similar across genders.

Table 2.

Means (SDs) of Variables Considered for the Income Determination Model of US Pediatric Pharmacists

Variable	Means ± SD
	Both Genders	Men	Women
Number of observations	285	73	212
Income
Annual income as a pharmacist, $	154,272 ± 32,120	161,847 ± 43,723	151,553 ± 26,646
Annual household income, $	244,264 ± 110,829	259,648 ± 140,173	239,198 ± 97,834
Work input, hr/wk	41.5 ± 8.4	41.2 ± 11.1	41.5 ± 7.3
Human-capital variables
Experience/practicing pharmacy, yr	13.5 ± 9.0	15.5† ± 9.4	12.8† ± 8.7
Experience/registered pharmacist, yr	13.0 ± 9.0	14.9 ± 9.4	12.4 ± 8.7
PharmD degree	97.2%	95.9%	97.6%
Specialty board certification	70.2%	67.1%	71.2%
Residency/fellowship program	84.2%	78.1%	86.3%
Job-related variables
Primary role	100%	100%	100%
Clinical	77.2%	65.8%†	81.6%†
Administration	9.5%	17.8%†	6.1%†
Distribution	4.2%	4.1%	4.3%
Academia	9.1%	12.3%	8.0%
Primary site	100%	100%	100%
Hospital	88.1%	89.0%	87.7%
Ambulatory	7.7%	8.2%	7.6%
Other	4.2%	2.8%	4.7%
Type of job	100%	100%	100%
Salaried employee	79.4%	82.4%	78.0%
Hourly employee	20.6%	17.6%	22.0%
Multiple jobs	3.9%	9.6%†	1.9%†
Ever negotiated salary	24.2%	28.8%	22.6%
Location	100%	100%	100%
Large city central	59.0%	60.3%	58.0%
Large city suburbs	15.4%	21.9%	13.7%
Small city	23.5%	13.7%†	26.9%†
Rural	2.1%	4.1%	1.4%
Union member	6.7%	8.2%	6.6%
Demographic variables
Age, yr	38.7 ± 8.9	41.2* ± 8.9	37.8* ± 8.7
Marital status	100%	100%	100%
Never married	22.4%	16.4%	24.5%
Married	73.0%	78.1%	71.7%
Separated/divorced/widowed	4.6%	5.5%	3.8%
With children younger than 18 years	46.7%	56.2%	43.4%
Non-White	9.1%	16.4%	7.1%
Hispanic	1.8%	2.8%	1.4%

* Statistically significant gender differences (p ≤ 0.01).

† Statistically significant gender differences (p ≤ 0.05).

The typical pediatric pharmacist in this sample possessed more than 13 years of experience, whether measured by total years practicing pharmacy or by years since becoming a registered pharmacist; on average, men had more years of professional practice than women. Almost everyone (97.2%) had earned a Doctor of Pharmacy degree, 70.2% held a specialty board certification, and 84.2% had completed postgraduate training (i.e., residency, fellowship). For analytical purposes, the 1- and 2-year residency responses were collapsed into a single variable, because the key factor affecting income is completion of residency, not the exact length, allowing for more robust estimation in the regression model. The sex differences in these 3 variables lacked statistical significance.

With respect to job-related variables, the results show that 77.2% of pediatric pharmacists did mostly clinical work and 9.5% held a primary administrative role, although there were marked gender disparities. Proportionately, women worked in clinical jobs more frequently than men. Conversely, proportionately more men than women held administrative positions. The other 2 roles, distribution and academia, depicted no proportional gender differences.

No gender differences were detected either in practice sites or types of job; 79.4% of practitioners worked in hospitals as salaried (exempt) employees. Only a few (3.9%) had more than 1 job, men proportionately more so than women, and 24.2% ever had negotiated salary. About 59.4% and 15.4% worked either in the central part or the suburbs of a large city, respectively and, on average, only 6.7% were members of a labor union. It is important to point out that, proportionately, more female respondents reported working in small cities than their male counterparts.

The empirical evidence also revealed that pediatric pharmacists in this sample were predominantly White and non-Hispanic. About three-quarters were married and one-half had children younger than 18 years.

Estimated Equations.

The estimated least-squares coefficients, their SDs, and (2-tailed) levels of significance for the 2 gender-specific models are presented in Table 3. The F ratios of both equations were statistically significant and the moderate to relatively high adjusted R² values suggested that the results were robust. Both covariates for work input were highly significant (p ≤ 0.01) for both genders. At the means of the covariate, an additional hour of work per week yielded an income increase of 2.6% for male respondents and 1.2% for female respondents. The percentage changes in income (2.6% for men, 1.2% for women) represent the semi-elasticities derived from these coefficients, calculated at the mean values of the covariates in each model. These effects are interpreted as the expected percentage change in annual income associated with working 1 additional hour per week, holding all other variables constant. Experience also was statistically significant for both men and women (p ≤ 0.01). The estimated parameters showed that every additional year of experience resulted in annual income going up by 1.0% for men and 0.7% for women. A quadratic component for experience was not significant for either gender. The nonsignificant quadratic term indicates that the association between experience and income is approximately linear, with earnings increasing at a constant rate as experience accumulates, without evidence of acceleration or deceleration at higher levels of experience.

Table 3.

Estimated Least-Squares Coefficients, Their Standard Errors (in Parentheses), and (2-Tailed) Levels of Significance in the Income-Determination Model for US Pediatric Pharmacists

Covariate	Term	Pediatric Pharmacists
		Men (i = 1)	Women (i = 2)
Constant term	αi	8.141501	10.580560
Work input	λ1i	0.149126* (0.009120)	0.045815* (0.007663)
Work input squared	λ2i	−0.001502* (0.000122)	−0.000411* (0.000080)
Experience	γi	0.010046* (0.003434)	0.006982* (0.001118)
Administrative role	θ1i	0.097258 (0.085255)	0.141297* (0.040262)
Ever negotiated salary	θ2i	0.063805 (0.074071)	0.047072† (0.022602)
Location large city	θ3i	0.128254 (0.087530)	0.065545* (0.021027)
F statistic		62.2*	23.0*
Adjusted R2		0.844	0.395

* Statistically significant (p ≤ 0.01).

† Statistically significant (p ≤ 0.05).

The coefficients of the other 3 covariates in the model, all job related, were statistically significant for female but not for male respondents (p ≤ 0.05). Female respondents in administrative roles earned, on average, 15.2% more than those primarily in clinical, distribution, or academic roles. Female respondents who had negotiated salary in their careers earned 4.8% higher income levels than the rest of the women in the sample. Finally, female respondents who worked in large cities reported 6.8% higher earnings than female respondents working in small cities or rural areas.

Discussion

A professional profile of the respondents to this survey was determined. The US PPA member pediatric pharmacists who responded to this survey consisted predominantly of a non-Hispanic White woman aged 38 to 43 years (see Table 2). She was married with an equal likelihood of having children younger than 18 years. She held a PharmD degree and a specialty board certification, had completed a residency and/or fellowship program, and had been a registered pharmacist and practicing pharmacy for the past 12 to 17 years. She worked 38 to 43 hours per week primarily in a large-city hospital, as a salaried (exempt) employee, doing clinical work, and had only 1 job. She never negotiated salary and was not a member of a labor union. The second generalization that may be made here is that the compositions of male and female ­practitioners were similar. Men were older and, consequently, possessed more professional experience, had more administrative and less clinical roles, lived more often in large cities, and were more prone to have more than 1 job. No other variables showed significant differences between genders.

Notwithstanding these similarities, male and female pharmacists responded differently to identical predictors in the income-determination model, which accords with the findings by Popovici and Carvajal.⁹ The least-squares coefficients for holding a management position, negotiating salary, and working in a large city were statistically significant for women but not for men (see Table 3); it is interesting to observe that the percentages of respondents working in an administrative role and in a large city were among the few variables for which male respondents scored higher than female respondents. This pattern may suggest that female practitioners earned higher levels of income when they worked in environments in which male respondents prevailed. Job-related information also offered insights into potential tradeoffs pharmacists make between income and other desirable job features. Ample evidence in the literature indicates that, even when earning less, female practitioners often report greater levels of both career and job satisfaction than male practitioners.^21–23–14 This is consistent with women trading off income for satisfaction at work more often than men, thus earning lower levels of income, as previously reported by Carvajal and Popovici²⁴ and Carvajal et al.²⁵

When work input and experience responses were compared across genders, the income yield to 1 more hour of work per week (2.6% for men and 1.2% for women) and 1 more year of pharmacy practice (1.0% for men and 0.7% for women) were more favorable for male than female respondents. The larger return to hours worked for men (2.6% vs 1.2% for women) may reflect differences in the types of roles or settings where extra hours are worked, or in how additional time is compensated. Experience increased income for both genders, but the smaller effect for women (0.7% vs 1.0%) may relate to career interruptions or slower promotion. Furthermore, judging by the small sizes of the standard errors in relation to the values of the estimated coefficients, the relative importance of the work-input covariates was much greater for men than for women (see Table 3). For women only, administrative roles and salary negotiation were associated with higher pay, possibly indicating that these factors are particularly important for women’s earnings progression. The higher salaries observed for administrative roles are consistent with prior research in pharmacy and other health care professions, where leadership positions command additional compensation owing to expanded responsibilities for management, budgeting, and organizational oversight. Working in large cities likely reflects higher cost of living and greater access to higher-paying positions. Factors other than work input had little influence on male practitioners’ income variability. This conclusion is supported by the higher F ratio and adjusted R² values, as well as the smaller constant-term value, found in the male vs the female estimated equations (see Table 3). That these job-related covariates were statistically significant only for women (p ≤ 0.05) suggests gender differences in role distribution, labor market dynamics, or the factors that most influence pay.

The fourth and last finding pertains to whether the initially computed annual income difference of $10,294 (gender gap of 6.4%) between men and women, which was not statistically significant, might have been underrepresented. If one uses the coefficients reported in Table 3 to project the income earned by a pediatric pharmacist with 14 years of practicing experience, who works in a role other than administration, in a large city, an average of 41 hours per week, and who never has negotiated salary (i.e., the typical values of the covariates in the equation), the projected annual income would be $162,706 if he were a man and $151,961 if she were a woman, a difference of $10,745 (i.e., a gender gap of 6.7%), which meets statistical significance (p ≤ 0.05) using the SDs reported in Table 2. In other words, the evidence is inconclusive, and subject to different interpretations. One less hour of work per week or 1 less year of professional experience and the difference is not significant, while 1 more unit of either covariate would increase the t ratio of significance. To illustrate the borderline nature of our projection, if instead of 14 years one considers 13 years of practicing experience or if instead of an average of 41 hours one considers 40 hours of work per week, the projected gender difference in income would no longer be statistically significant (p > 0.05); conversely, if one considers 15 years of practicing experience or an average of 42 hours of work per year (i.e., 1 unit above the means of the variables), the strength of the statistical significance increases (p ≤ 0.05).

Limitations

Perhaps the most stringent limitation pertaining to this study was the number of observations. Although adequate, more degrees of freedom, especially of male respondents, might have allowed greater latitude when testing the statistical significance of the covariates. The probe focused on 1 subset of the profession, pediatric pharmacists, so the empirical findings may not be fully generalizable to other pharmacists experiencing somewhat different conditions, relationships, and experiences. Specifically, in the general population of US pharmacists, the percentage of men is higher, though women still predominate, and the income levels are lower for each gender, as is the fraction of participants working in hospitals.⁹ Based on the emphasis on the acute care of pediatric patients, it can be assumed that this survey’s findings represent a higher proportion of pediatric pharmacists practicing in the hospital setting as compared with the general population of pharmacists.

One also should consider that the study used self-reported data, which are inherently biased and invariably raise potential validity and reliability issues. While the questionnaire was tested prior to being available to participants, the answers were influenced by respondents’ perceptions and emotions at the times the questionnaires were filled, including the decision not to respond made by those who opted not to participate. In inferring the sample results to the population of pediatric pharmacists, an assumption was made that the distribution of nonrespondents’ human-capital, job-related, and demographic characteristics was approximately the same as the distribution of survey participants, which may not be true. Furthermore, the implicit assumption that the survey questionnaires returned were filled out by the intended respondents and that their responses were accurate might not always hold true.

Moreover, survey participation may be subject to bias, as previous research indicates that women and non-Hispanic individuals tend to have higher response rates in professional surveys. Additionally, there is a lack of understanding of the gender makeup of the pediatric pharmacist population as a whole. Neither Board of Pharmacy Specialties nor PPA collect gender information from their membership, so this also may skew the population represented in this study. These factors introduce potential misrepresentation, which may limit the generalizability of the findings.

Another limitation is that pharmacists’ reported income levels were not adjusted for spatial variations in taxes and costs of living. Thus, earnings might have been overreported by some and underreported by others. A given level of nominal income in one location with lower taxes and/or costs of living might have been equivalent, in terms of real income, to another level in a location in which higher taxes and/or cost of living prevail; yet, they appeared in the data as different amounts. Finally, data on the length of employment with the current employer were not collected, which may influence salary through factors such as salary compression or retention incentives.

Conclusion

Despite the limitations stated above, this research has been successful in developing a professional profile of US pediatric pharmacists and identifying similarities and differences between its male and female practitioners. The estimated gender differences in income, which were borderline statistically significant and subject to interpretation, provide an incentive to conduct further research, hopefully with more observation units, to obtain a more definitive answer. In the meantime, these findings should be regarded as preliminary and be used to increase awareness of gender-disparity issues and encourage conversations within the pediatric pharmacist workforce at the institutional level.

ABBREVIATIONS

NPWS

National Pharmacist Workforce Study;

PPA

Pediatric Pharmacy Association