Abstract
This study examined the association between perceived discrimination, workplace racial composition, and three outcomes--psychological distress, life dissatisfaction, and job dissatisfaction--among a sample of professional Black (n=72) and White (n=74) women. As a comparison, these relationships were analyzed to determine if they varied from those observed in more traditionally studied populations: Whites and non-professional Blacks, using data from a population of working women in the 1995 Detroit Area Study (N=533). Perceived discrimination was associated with differences in psychological distress and job dissatisfaction but not with life dissatisfaction. The correlation between perceived discrimination and psychological distress was larger for White professional women than for Black professional women (White Women odds ratio [OR]: 1.99; Black Women odds ratio [OR]: 0.80). A larger correlation between race and job dissatisfaction was observed for Black professional women than for Black non-professional women. The racial composition of the workplace was unrelated to any of the outcomes. Study results emphasized the importance of decreasing the frequency of discrimination for positive mental health and underscored the need for more systematic research on discrimination and health among Black women of higher socioeconomic status, a growing sub-population in the U.S.
Keywords: well-being, race, gender differences, mental health, psychosocial, socioeconomic status, stress
Introduction
For Blacks in the U.S., perceived discrimination is associated with adverse health and mental health outcomes and overall dissatisfaction with life (Cokley et al., 2011; Hall et al., 2012; Kessler et al., 1999). These consequences are sufficiently large that discrimination is increasingly recognized as an important contributor to racial disparities in health (Williams et al., 2010). That is, Blacks consistently exhibit lower life expectancy, earlier deterioration of health, and earlier onset, greater severity, and poorer survival from disease (Williams et al., 2010).
Greater attention is now needed to the contribution of occupational status to health disparities (Williams et al., 2010). Higher-status occupations are generally associated with better health and well-being (Schieman & Reid, 2009; Schulz et al., 2000), but this protection may not extend to women and minorities. Women who work in high-status careers face characteristically White, male-dominated, highly competitive, and disproportionately stressful occupational environments (National Academy of Sciences, 2007; Frank et al., 1998; Frank et al., 1999). While high-status occupations have been negatively associated with stress for women, scant attention has been dedicated to how occupational experiences may differentially affect the well-being of Black women (Hall et al., 2012) or how this relationship may influence racial disparities in health.
As professionals, Black women must cope with the stress of being a racial and gender minority, in addition to the demands faced by all employees and the occupational stressors associated with the job. As Blacks move up the social ladder and obtain high-status professional positions, mobility may have both positive and negative implications for their health (Forman, 2003; Jackson & Stewart, 2003). Stress from “racial stereotyping, exclusion from office networks, harassment, or assumptions of inferior cognitive ability” (Hall et al., 2012: p. 211) is a particularly frequent occurrence for minorities, especially Black women (Peterson et al., 2004; Schulz et al., 2000; Shrier et al., 2007). Accordingly, Black professional women who work in predominantly White work environments are more likely to express higher levels of psychological distress (Jackson & Stewart, 2003).
The purpose of this study was to examine racial differences in psychological distress and life and job dissatisfaction in relation to the role that discrimination and the racial composition of the workplace may play in those differences for professional women. Prior studies have measured one form of discrimination, focused on discrimination or workplace compositional influences, or focused on the impact of low socioeconomic status (SES) on health (Adler et al., 1994). This study investigated the relation of the racial composition of the workplace and two forms of discrimination -- perceived racial discrimination and acute discrimination1 (Kessler et al., 1999) - to multiple outcomes. Additionally, this study emphasized professional women given that the extensive research-to-date has focused on low-SES women (Jackson & Stewart, 2003). Few studies have investigated the mental health issues of high-SES women or how these women deal with their stress. This may be because of assumptions regarding access to resources and/or assumptions about such women being better able to cope with mental health problems than their lower SES counterparts. It is important for research to identify and characterize mental health risks at all SES levels (Jackson & Stewart, 2003) because even those with higher SES levels may experience occupational stress (Jackson et al., 2010; Williams et al., 2010).
Furthermore, the differences in well-being and job satisfaction among non-professional women and between professional and non-professional Black women indicated a SES gradient in mental health (Schieman et al., 2006). Perceived racial discrimination, acute discrimination, and the racial composition of the workplace may be more visible and influential in professional careers because women and minorities are numerical and racial minorities (Jackson et al., 1995). We hypothesized that these experiences would be more negatively related to the mental health and job satisfaction of Black professional women than of White professional women.
Background
Perceived Discrimination & Stress
The stress paradigm has helped shape research on discrimination and health. Two distinct types of stressors dominate this paradigm, acute and chronic, which originate from an intersection of a variety of social roles (i.e., race, class, age, and gender) (Lantz et al., 2005). With long-term exposure, acute and chronic stress can negatively affect physical (Schulz et al., 2000) and mental (Jones et al., 2007; Schulz et al., 2000) health. Unfair treatment, associated with discrimination, has been increasingly recognized as a stressor among socially stigmatized groups (Cokley et al., 2011) and can lead to poor mental health (Jackson et al., 1995; Kessler et al., 1999) and well-being (Cokley et al., 2011).
The acute/chronic distinction may help reveal multiple avenues by which discrimination differentially affects health outcomes by race. For instance, despite being positively associated with poor health outcomes for Blacks, the relation of discrimination to health may be smaller in comparison to Whites (Williams et al., 2008). Earlier, more frequent and elevated exposure to risk factors (chronic) may be less strongly associated with poor outcomes than more recent, less frequent, or decreased exposure (acute). Williams et al. (2010) have pointed out that persistent poverty, low birth weight births, and obesity are all more persistent in Blacks than in Whites, but all three of these indicators are associated with poorer outcomes for Whites than for Blacks (Williams et al., 2010). Under this assumption, one would expect White professional women who experience acute forms of discrimination to experience poorer outcomes than Black professional women.
Occupational Status & Health
SES, Discrimination & Health
Rosabeth Kanter’s research is central to examining the relations of workplace environments to health. Kanter’s classic 1977 work investigated the association between proportional representation (the numerical racial/sex composition of the workplace), feelings of tokenism, and stress for women. She concluded that being a token (numerical rarity) elicited two forms of stress: 1) personal self-doubt and low expectations; and 2) and a sense of rejection. In subsequent research by Jackson et al. (1995), being a numerical rarity by race was also a source of occupational stress and was significantly associated with increased token stress and symptoms of depression and anxiety among Black middle-class workers (Jackson et al., 1995).
Work regarding tokenism influenced the understanding of the relationship among racial and gender compositions and stress. Unfortunately, information is lacking about the relations to health of being a numerical rarity on those in the upper social echelons (Jackson et al., 1995; Frank et al., 1999)--for example, professionals. Black professional women often find that they are tokens forced to cope with occupational stressors associated with the job and with double the discrimination due to gender and race (National Academy of Sciences, 2007). Therefore, it is plausible that Black and White professional women would experience their work environments differently.
This study examined whether perceived discrimination and the racial composition of the workplace had different relations to the psychological well-being of Black versus White professional women. The negative relationship between perceived discrimination and the racial composition of the workplace was hypothesized to be reflected more in Black professional women than in White professional women reporting increased psychological distress, life dissatisfaction, and job dissatisfaction. The analyses also explored whether perceived discrimination and the racial composition of the workplace correlated with psychological well-being differently in Black and White professional women than among their non-professional counterparts. This comparison provided information on the external validity of research on minority health that has disproportionately examined non-professional women. Investigating mental health risks at all occupational and SES levels will provide a more comprehensive picture about the relationship between occupational characteristics, discrimination, and mental health.
Methods
Sample
Data were from the 1995 Detroit Area Study (DAS), a multistage area probability sample. The design of the 1995 Detroit Area Study (DAS) has been described more fully elsewhere (Schulz, et al., 2000). In brief, the study used the 1995 DAS, a multistage area probability sample. Eligible participants were individuals aged 18 years and older, randomly selected from households in the Michigan counties of Oakland, Macomb, and Wayne (Jackson & Williams, 2002). The response rate was 70%, which yielded a final sample of 1,138 respondents, of whom 520 were White, 586 were Black, and 33 were Asian, American Indian, or Hispanic (Schulz, et al., 2000).
The DAS was chosen over more recent surveys because it allowed for comparison across races, included a sizeable population of both professional and non-professional women, and included questions regarding past experiences of discriminatory events and the racial composition of the workplace. No other known population study combined this information with a sample of Black professional women sufficiently large enough to support reliable quantitative data analysis.
Study Subample
The present study was based on a selected subsample of individuals who participated in the 1995 DAS. The eligibility criteria for the study were being between the ages of 18 and 70 years and a woman. Respondents were excluded if they were missing data on any of these variables: psychological distress, life dissatisfaction, job dissatisfaction, discrimination scales, the racial composition of the workplace, age, occupation, or level of education (N=160). Respondents who reported their race as Asian, American Indian, Hispanic, or Other were also excluded due to their small sample sizes (n=75). This yielded an analytic sample size of 506 Black and White women, of whom 146 were Professional workers (49% Black and 51% White), and 360 were Non-Professional workers (62% Black and 38% White) (Table I). Population estimates were based on weighted analyses designed to yield estimates representative of Detroit Area adults.
Table I.
Descriptive Statistics of the DAS Sample.
| All (N=506) | Professional | Non-Professional | ||
|---|---|---|---|---|
|
| ||||
| Black (n= 72) | White (n= 74) | Black (n= 214) | White (n= 146) | |
| Socio-Demographic Characteristics | ||||
| Age (mean) (SD), years | 45 (1.5) | 44 (1.4) | 40 (0.9) | 42 (1.2) |
| 18–30 | 10% | 12% | 30% | 27% |
| 31–39 | 22% | 25% | 24% | 21% |
| 40–52 | 42% | 39% | 24% | 25% |
| 53–70 | 26% | 24% | 22% | 27% |
| Number of children (mean) (SD) | 1.9 (0.2) | 1.6 (0.2) | 2.4 (0.1) | 1.8 (0.1) |
| Organizations** (mean) (SD) | 2.2 (0.2) | 2.6 (0.3) | 1.2 (0.1) | 1.1 (0.1) |
| Education | ||||
| High School Degree or Less | 14% | 15% | 54% | 50% |
| Some College | 43% | 22% | 40% | 42% |
| College Degree or More | 43% | 63% | 6% | 8% |
| Racial Composition of the Workplace | ||||
| All Other (Omitted) | 47% | 16% | 47% | 12% |
| All or Mostly White | 27% | 65% | 10% | 54% |
| Inapplicable | 26% | 19% | 43% | 34% |
| Discrimination Measures | ||||
| Lifetime Racial Discrimination (No/Yes) | 74% | 12% | 57% | 14% |
| Acute Event Discrimination (0–3) (mean) (SD) | .90 (.11) | .54 (.09) | .86 (.06) | .45 (.06) |
| Outcome Measures | ||||
| Psychological Distress (No Distress vs. Mild Distress) | 33% | 37% | 45% | 37% |
| Life Dissatisfaction (Satisfied vs. Not Satisfied) | 60% | 26% | 63% | 34% |
| Job Dissatisfaction (Satisfied vs. Not Satisfied) | 60% | 57% | 84% | 66% |
| Total (%) | 72 (49%) | 74 (51%) | 241 (62%) | 146 (38%) |
Number of external Organizations in which women are involved
The present study protocol was reviewed and approved by the Institutional Review Board at the University of Wisconsin – Madison. All participants provided written informed consent.
Measures
Psychological Distressi
Current psychological distress was measured by the Kessler Six (K6) Psychological Distress Scale, a short version of the 10-item Kessler Psychological Distress Scale. Respondents were asked to report the frequency of six emotions (sad, nervous, restless or fidgety, hopeless, feeling that everything is an effort, and worthless) in the past 30 days (Kessler et al., 2002). Responses to these items were reverse coded (Never, Hardly Ever, Not Too Often, Fairly Often, Very Often) and summed to yield a potential score range of 0–24. Higher scores were indicative of greater psychological distress. A cutoff point of 7 or greater was used as an indicator of mild to moderate distress (Witt et al., 2009).
Life Dissatisfaction
Perceived life dissatisfaction was measured by a single item. Looking back over their entire life, respondents were asked, “How satisfied are you with it?” (Forman, 2003). Responses were reverse coded and dichotomously categorized as not satisfied versus very/completely satisfied.
Job Dissatisfaction
Perceived job dissatisfaction was measured by a single item, “How satisfied are you with your job?” (Deitch et al., 2003). Responses were reverse coded and dichotomously categorized as not satisfied versus very/completely satisfied.
Independent Variables
Lifetime Racial Discrimination
Feelings of perceived racial discrimination were measured by asking respondents if they felt they had been treated unfairly or badly as a result of their race/ethnicity in their lifetime (Brown, 2001). Responses were coded as a dummy variable indicating a positive response to the question.
Acute Discrimination Scale
The acute discrimination scale is a 3-item scale measuring respondents reports of major acute unfair treatment, following Schulz et al. (2000). The scale includes three questions regarding feeling unfairly fired, unfairly not hired, and feeling treated unfairly by the police. Response items were coded as yes/no and summed to create a potential score range of 0–3. Higher scores were indicative of a greater number of experiences of acute unfair treatment.
Workplace Racial Composition
The racial composition of the workplace was measured by asking respondents, “Is your work group all Black, mostly Black, about half Black and half White, mostly White, or all White?” Responses were dummy coded as all/mostly White, all other (half Black/White and all/mostly Black), and inapplicable.ii
Control measures
Sociodemographic Characteristics
The following sociodemographic characteristics were included: age (18–70 in years), race (White=0, Black=1), and educational status (high school graduate or less, some college, and college degree or beyond).
Occupation
Respondents’ occupations were categorized using three-digit codes from the 1980 Census occupational coding. Occupations were divided into three categories: Professional (codes 5–234), White collar (codes 235–489) and Blue collar (codes 490–889). These categories were further collapsed to reflect Professional and Non-Professional workers. iii
Data Analyses
First, descriptive statistics of the study population were computed based on unweighted data (Table I). Next, the relations of discrimination and the racial composition of the workplace with psychological distress, life dissatisfaction, and job dissatisfaction were examined for Black and White professional women and non-professional women. Data were weighted to account for the complex survey design, and logit models were used to test the study hypotheses using Stata12/MP for Windows (StataCorp, 2009). In Model 1, the log odds for each outcome were computed in relation to lifetime racial discrimination, control measures, and workplace racial composition dummy variables. Model 2 was identical to Model 1, except lifetime racial discrimination was replaced with the acute discrimination scale. Interactions were included to test whether the association between the racial composition of the workplace, discrimination, and the dependent variable differed by race or occupational status. Age and education were included in the models on theoretical grounds because psychological distress and general satisfaction are patterned by age and education (Thoits, 2010) no other variables were assessed for confounding. In most cases, model fit, as indicated with Wald test statistics, improved with the inclusion of these two variables. Given the sample size, critical values of p<0.05 and p<0.10 are both reported (Betancourt et al., 2010).
Results
The sample was made up of 146 professional women, of whom 72 were Black and 74 were White, and 360 Non-Professional workers, of whom 214 were Black and 146 were White (Table I). Very little variation was observed in the levels of psychological distress across Black professionals, White professionals, Black non-professionals, and White non-professionals (Table I). Blacks were more likely to report life and job dissatisfaction, with Black non-professionals being most likely to report job dissatisfaction (63%). Most White women reported working in all or mostly White work environments, while Black women worked in more racially mixed environments. Levels of education varied by race and occupation: having a high school degree or less was most reported by Black and White non-professionals, having some college was most reported by Black professionals, and having a college degree or more was most reported by White professionals. Women were on average between 42 and 45 years of age; Black non-professional women bore on average a greater number of children (2.4) than other women, and professional women were slightly more physically active than non-professionals in outside organizationsiv.
Among professional women, both indicators of discrimination were significantly associated with psychological distress; however, the association with acute discriminatory events was larger for White than for Black women (White Women odds ratio [OR]: 1.99; Black Women odds ratio [OR]: 1.99 × 0.40 = 0.80) (Table II). Odds ratios relating life dissatisfaction and discrimination were both above one and somewhat attenuated for Black respondents, although both the zero-order and interaction terms were imprecisely estimated and not statistically significant (Table II). Discrimination was associated with greater job dissatisfaction, but the association was statistically significant only in the case of acute discriminatory events (Table II). Also, no evidence was observed of racial differences in these associations.
Table II.
Multiple Logistic Regression results for Psychological Distress, Life Dissatisfaction and Job Dissatisfaction among Professional Women (Model A with interactions; Model B stratified for variables found to have significant interactions).
| A. | Psychological Distress | Life Dissatisfaction | Job Dissatisfaction | |||
|---|---|---|---|---|---|---|
|
| ||||||
| (1) OR |
(2) OR |
(1) OR |
(2) OR |
(1) OR |
(2) OR |
|
| Discrimination Measures | ||||||
| Lifetime Racial Discrimination | 4.79* (0.88 – 26.10) | 3.13 (0.53 – 18.63) | 2.37 (0.53 –10.69) | |||
| Acute Event Discrimination | 1.98* (0.99 – 3.97) | 1.39 (0.69 – 2.83) | 2.93*** (1.33 – 6.46) | |||
| Racial Composition | ||||||
| All Other (Omitted) | Ref | Ref | Ref | Ref | Ref | Ref |
| All or Mostly White | 0.92 (0.16 – 5.12) | 0.77 (0.15 – 4.03) | 0.50 (0.08 – 2.94) | 0.45 (0.09 – 2.17) | 1.22 (0.27 –5.46) | 1.07 (0.27 – 4.30) |
| Independent Variables | ||||||
| Black | 0.69 (0.10 – 4.66) | 0.99 (0.16 – 5.99) | 2.51 (0.28 – 22.75) | 1.43 (0.27 – 7.57) | 0.95 (0.11 –8.58) | 0.94 (0.18 – 4.94) |
| Age | 0.97* (0.93 – 1.01) | 0.97 (0.93 – 1.01) | 1.00 (0.95 – 1.05) | 1.00 (0.95 – 1.04) | 0.97 (0.94 –1.01) | 0.97* (0.94 – 1.01) |
| Education | ||||||
| High School Degree or Less (Omitted) | Ref | Ref | Ref | Ref | Ref | Ref |
| Some College | 0.11*** (0.02 – 0.54) | 0.10*** (0.02 – 0.55) | 0.36 (0.07 – 1.84) | 0.36 (0.07 – 1.82) | 0.18** (0.04 –0.98) | 0.16** (0.03 – 0.96) |
| College Degree or More | 0.11*** (0.03 – 0.43) | 0.10*** (0.02 – 0.44) | 0.28* (0.06 – 1.27) | 0.30 (0.07 – 1.42) | 0.27* (0.06 –1.25) | 0.20* (0.04 – 1.04) |
| Interactions | ||||||
| Black x All or Mostly White | 2.24 (0.26 – 19.22) | 2.69 (0.31 – 23.12) | 3.60 (0.370 –35.09) | 3.88 (0.46 – 32.92) | 0.65 (0.08 –5.10) | 0.82 (0.12 – 5.75) |
| Black x Lifetime Racial Discrimination | 0.26 (0.03 – 2.06) | 0.22 (0.02 – 2.22) | 0.55 (0.05 –5.90) | |||
| Black x Acute Event Discrimination | 0.40* (0.15 – 1.04) | 0.85 (0.32 – 2.24) | 0.59 (0.17 – 2.00) | |||
| Constant | 16.68** (1.34 – 208.27) | 19.83** (1.76 – 223.40) | 1.74 (0.12 – 24.32) | 1.99 (0.16 – 24.85) | 7.30* (0.70 –75.66) | 7.69* (0.81 – 72.80) |
| Observations | 146 | 146 | 146 | 146 | 113 | 113 |
|
| ||||||
| B. | ||||||
| Black | ||||||
| Lifetime Racial Discrimination | 1.15 (0.39 – 3.43) | 0.50 (0.17 – 1.50) | 0.93 (0.29 –3.01) | |||
| Acute Event Discrimination | 0.80* (0.47 – 1.41) | 1.20 (0.73 – 1.97) | 1.65 (0.91 – 3.00) | |||
| White | ||||||
| Lifetime Racial Discrimination | 4.87* (1.19 – 19.86) | 3.18 (0.71 – 14.23) | 2.42 (0.66 –8.89) | |||
| Acute Event Discrimination | 1.99* (1.09 – 3.62) | 1.41 (0.77 – 2.60) | 3.13*** (1.56 – 6.32) | |||
p<0.01,
p<0.05,
p<0.1
Wald X2 = 20.13** Wald X2 = 19.06** Wald X2 =16.70* Wald X2 = 13.55 Wald X2 =8.19 Wald X2 = 15.35*
Analysis for non-professional women yielded similar results, but with four differences (Table III). First, non-professional Black women who reported experiencing racial discrimination had a lower odds than White non-professional women of reporting psychological distress (Figure 1) (White Women OR 6.64; Black Women OR: 6.64 × 0.20 = 1.35). Second, Black non-professional women had a larger odds (Black Women OR: Model 1=3.41; Model 2=3.82) of reporting life dissatisfaction. A complex relationship was observed between discrimination and job satisfaction by race. Lifetime racial discrimination was significantly associated with job dissatisfaction for both Black and White non-professional women (Table III). In contrast, a higher frequency of acute discriminatory events was only associated with more job dissatisfaction for Black non-professionals.
Table III.
Multiple Logistic Regression results for Psychological Distress, Life Dissatisfaction and Job Dissatisfaction among Non-Professional Women (Model A with interactions; Model B stratified for variables found to have significant interactions.
| A. | Psychological Distress | Life Dissatisfaction | Job Dissatisfaction | |||
|---|---|---|---|---|---|---|
|
| ||||||
| (1) OR |
(2) OR |
(1) OR |
(2) OR |
(1) OR |
(2) OR |
|
| Discrimination Measures | ||||||
| Lifetime Racial Discrimination | 6.61*** (1.74 – 25.13) | 1.78 (0.58 – 5.52) | 3.05* (0.89 – 10.49) | |||
| Acute Event Discrimination | 1.79* (0.99 – 3.22) | 1.59 (0.89 – 2.87) | 0.93 (0.47 – 1.85) | |||
| Racial Composition | ||||||
| All Other (Omitted) | Ref | Ref | Ref | Ref | Ref | Ref |
| All or Mostly White | 1.18 (0.39 – 3.55) | 0.84 (0.23 – 3.13) | 0.69 (0.23 – 2.11) | 0.62 (0.19 – 2.05) | 0.63 (0.18 – 2.21) | 0.55 (0.15 – 2.00) |
| Independent Variables | ||||||
| Black | 2.35 (0.72 – 7.64) | 1.61 (0.43 – 6.01) | 3.41** (1.07 – 10.89) | 3.82** (1.17 – 12.51) | 1.38 (0.35 – 5.42) | 0.94 (0.24 – 3.68) |
| Age | 1.00 (0.98 – 1.02) | 1.00 (0.98 – 1.02) | 0.97*** (0.96 – 0.99) | 0.98** (0.96 – 0.99) | 0.97** (0.94 – 0.99) | 0.97* (0.94 – 1.00) |
| Education | ||||||
| High School Degree or Less (Omitted) | Ref | Ref | Ref | Ref | Ref | Ref |
| Some College | 0.49** (0.25 – 0.95) | 0.53** (0.28 – 0.98) | 1.12 (0.60 – 2.10) | 1.08 (0.59 – 1.98) | 0.78 (0.34 – 1.77) | 0.86 (0.39 – 1.90) |
| College Degree or More | 0.76 (0.25 – 2.34) | 0.97 (0.29 – 3.23) | 1.02 (0.29 – 3.56) | 1.16 (0.35 – 3.85) | 0.81 (0.24 – 2.77) | 0.92 (0.25 – 3.38) |
| Interactions | ||||||
| Black x All or Mostly White | 0.46 (0.10 – 2.05) | 0.61 (0.12 – 3.18) | 0.68 (0.16 – 2.89) | 0.71 (0.15 – 3.28) | 2.47 (0.47 – 13.00) | 2.55 (0.44 – 14.89) |
| Black x Lifetime Racial Discrimination | 0.20** (0.05 – 0.84) | 0.97 (0.27 – 3.56) | 0.85 (0.19 – 3.88) | |||
| Black x Acute Event Discrimination | 0.68 (0.35 – 1.33) | 0.84 (0.44 – 1.63) | 2.32** (1.01 – 5.33) | |||
| Constant | 0.37 (0.10 – 1.36) | 0.46 (0.10 – 2.05) | 1.28 (0.33 – 4.97) | 1.11 (0.27 – 4.63) | 3.69 (0.59 – 23.17) | 4.74 (0.65 – 34.32) |
| Observations | 387 | 387 | 387 | 387 | 235 | 235 |
|
| ||||||
| B. | ||||||
| Black | ||||||
| Lifetime Racial Discrimination | 1.35** (0.80 – 2.27) | 1.73 (1.00 – 3.00) | 3.05 (1.48 – 6.33) | |||
| Acute Event Discrimination | 1.21 (0.92 – 1.58) | 1.34 (1.03 – 1.74) | 2.31** (1.55 – 3.46) | |||
| White | ||||||
| Lifetime Racial Discrimination | 6.64*** (2.13 – 20.73) | 1.79 (0.69 – 4.67) | 3.17* (1.09 – 9.23) | |||
| Acute Event Discrimination | 1.81* (1.09 – 3.01) | 1.60 (0.97 – 2.64) | 0.93 (0.52 – 1.66) | |||
p<0.01,
p<0.05,
p<0.1
Wald X2 =22.77** WaldX2 = 17.10** WaldX2 = 41.00*** Wald X2 =44.91*** Wald X2 =23.20*** Wald X2 =29.93***
Figure 1.
Predicted Probaility of Psychological Distress by Race Occupational Status & Lifetime Racial Discrimation
To test whether the differences in the relationships observed among professional and non-professional women were statistically meaningful, both racial groups were pooled and a three way interaction term was introduced (Table IV). Interestingly, being a professional or a Black woman who experienced acute events of discrimination was associated with increased odds of job dissatisfaction; however, the odds ratio was significantly smaller for Black professional than for Black non-professional women who experienced acute events of discrimination (Professional Black Women OR:=1.65; Non-professional Black Women OR:2.31) (Frank et al., 1999). Lastly, contrary to hypothesized relationships, the racial composition of the workplace was unrelated to any of the indicators of well-being in this population. Also, no significant racial differences were observed in racial composition and well-being outcomes, although the odds ratios for the interaction terms in relation to job dissatisfaction suggest higher levels of job dissatisfaction for Blacks who worked in all or mostly White work environments (Black Women OR: Model 1=1.42; Model 2=1.69).
Table IV.
Logistic Regression results for Psychological Distress, Life Dissatisfaction and Job Dissatisfaction among All Working Women (Model A with interactions; Model B stratified for variables found to have significant interactions).
| Psychological Distress | Life Dissatisfaction | Job Dissatisfaction | ||||
|---|---|---|---|---|---|---|
|
| ||||||
| A. | (1) OR |
(2) OR |
(1) OR |
(2) OR |
(1) OR |
(2) OR |
| Interactions | ||||||
| Black x Professional | 0.54 (0.14 – 2.04) | 0.87 (0.27 – 2.86) | 2.50 (0.54 – 11.58) | 1.02 (0.29 – 3.61) | 0.33 (0.06 – 1.82) | 0.43 (0.10 – 1.82) |
| Professional x Life Racial Discrimination | 0.90 (0.12 – 7.05) | 1.54 (0.23 – 10.48) | 0.61 (0.08 – 4.57) | |||
| Professional x Acute Event Discrimination | 0.98 (0.40 – 2.46) | 0.79 (0.32 – 1.97) | 2.82** (1.01 – 7.85) | |||
| Black x Lifetime Racial Discrimination | 0.21** (0.05 – 0.93) | 0.97 (0.27 – 3.47) | 0.74 (0.16 – 3.46) | |||
| Black x Acute Event Discrimination | 0.71 (0.37 – 1.38) | 0.84 (0.44 – 1.62) | 2.28* (1.00 – 5.22) | |||
| Black x Professional x Lifetime Racial Discrimination | 1.14 (0.10 – 13.23) | 0.19 (0.02 – 2.18) | 0.70 (0.05 – 10.27) | |||
| Black x Professional x Acute Event Discrimination | 0.72 (0.23 – 2.21) | 1.09 (0.35 – 3.46) | 0.27* (0.07 – 1.05) | |||
| Black x All or Mostly White | 1.13 (0.33 – 3.87) | 1.43 (0.41 – 5.02) | 1.17 (0.34 – 3.99) | 1.23 (0.36 – 4.23) | 1.42 (0.41 – 4.90) | 1.69 (0.47 – 6.13) |
| Constant | 0.78 (0.25 – 2.48) | 0.96 (0.30 – 3.12) | 1.26 (0.39 – 4.05) | 1.13 (0.35 – 3.68) | 2.96 (0.76 – 11.51) | 4.21* (0.97 – 18.32) |
| Observations | 533 | 533 | 533 | 533 | 348 | 348 |
|
| ||||||
| B. | ||||||
| Black Non-Professional | ||||||
| Lifetime Racial Discrimination | 1.35 (0.80 – 2.27) | 1.73 (1.00 – 3.00) | 3.06** (1.48 – 6.33) | |||
| Acute Event Discrimination | 1.21 (0.92 – 1.58) | 1.34 (1.03 – 1.74) | 2.31*** (1.55 – 3.46) | |||
| White Non-Professional | ||||||
| Lifetime Racial Discrimination | 6.24*** (2.13 – 20.73) | 1.80 (0.69 – 4.67) | 3.17* (1.09 – 9.23) | |||
| Acute Event Discrimination | 1.81* (1.09 – 3.01) | 1.60 (0.97 – 2.64 | 0.93 (0.52 – 1.66) | |||
| Black Professional | ||||||
| Lifetime Racial Discrimination | 1.15 (0.39 – 3.43) | 0.50 (0.30 – 0.17) | 0.93 (0.29 – 3.01) | |||
| Acute Event Discrimination | 0.81 (0.47 – 1.41) | 1.20 (0.56 – 0.73) | 1.65 (0.91 – 3.00) | |||
| White Professional | ||||||
| Lifetime Racial Discrimination | 4.82* (1.19 – 19.86) | 3.18 (0.71 – 14.23) | 2.43 (0.66 – 8.89) | |||
| Acute Event Discrimination | 1.99* (1.09 – 3.62) | 1.41 (.77 – 2.59) | 3.14*** (1.56 – 6.34) | |||
p<0.01,
p<0.05,
p<0.1
Wald X2 =23.72* Wald X2 =17.65 Wald X2 =49.32*** Wald X2 =53.16*** Wald X2 =29.38*** Wald X2 =38.32***
Discussion and Conclusion
The aim of the study was to explore the relations of two forms of discrimination and the racial composition of the workplace to racial differences in well-being among professional women. The hypothesis was that because discrimination and the racial composition of the workplace may be more visible and influential in the professional careers of Black women, their well-being would be negatively related to well-being due to the saliency of their minority status (Frank et al., 1999). Results pointed to four key findings: (1) Discrimination was associated with greater psychological distress; (2) In the presence of discrimination, White professional women reported more psychological distress than Black professional women; (3) Black professional women reported greater job satisfaction than White professional and Black non-professional women; and (4) Workplace racial composition was unrelated to the measures of well-being captured in this study. Racial differences in health were thus related to a complex intersection of social roles, including race and professional status.
The findings here make four key contributions to the literature on the relation of discrimination and occupational environments to women’s health. First, these findings support previous research on discrimination’s harmful relation to mental health: they reproduce the positive association found by others between perceived discrimination and poor mental health in a population of working women (Brown, 2000; Pamela B. Jackson & Stewart, 2003). It is important to highlight that, for professional women who generally work in gender incongruent occupations dominated by men, the experience of discrimination has a more negative association with their psychological well-being than it does for non-professional women, although the odds ratios are not statistically significantly different. More importantly, perceiving discrimination presents a challenge to all women, regardless of their occupational status.
Second, in the DAS, White women were more likely to report gender-based discrimination, while Black women were more likely to report race-based discrimination (Box 1), as found in other studies (Pavalko et al., 2003). Additionally, the correlation between experiencing acute discrimination and psychological distress was significantly larger for White women than it was for Black women, whereas in other studies White women were more likely to report greater psychological distress after experiencing race-based discrimination (Clark et al., 1999; Williams et al., 1997).
Box 1.
Main reason for Unfair or Poor Treatment
| Professional | Non-Professional | |||
|---|---|---|---|---|
| Black % | White % | Black % | White % | |
| Inapplicable | 61% | 84% | 56% | 84% |
| Ethnicity | 0% | 0% | 0% | 1% |
| Race | 14% | 0% | 9% | 2% |
| Gender | 0% | 3% | 1% | 2% |
| Age | 4% | 1% | 3% | 1% |
| Physical Appearance | 1% | 0% | 1% | 1% |
| Sexual Orientation | 0% | 0% | 0% | 0% |
| Social Class | 1% | 0% | 5% | 1% |
| Combination | 8% | 5% | 7% | 2% |
| Other | 4% | 5% | 13% | 4% |
| Don’t Know | 1% | 1% | 2% | 1% |
|
| ||||
| Unknown | 4% | 0% | 3% | 1% |
|
| ||||
| Total | 100% | 100% | 100% | 100% |
The larger correlation between acute discrimination and psychological distress is contrary to what was hypothesized but could be interpreted in a number of ways. One interpretation is that Black professional women may be adapting to the stress. They may have experienced multiple forms of discrimination earlier in life and for longer spans of time and may therefore be better able than White professional women to adapt as discriminatory experiences accumulate. Consequently, one would expect to see fewer negative health consequences for Black professional women. A second interpretation is that the exhibited association between discrimination and psychological distress for White professional women can be attributed to how Blacks and Whites tend to report their mental health issues. Other research has shown that Blacks report more somatic symptoms (physical complaints) while Whites report more psychological symptoms (emotional and cognitive complaints) (Ayalon & Young, 2003). This could cause real and significant differences in whether the psychological distress scale actually reflects the true amount of distress that exists for Black women.
Third, professional women and Black women who reported higher frequencies of acute discrimination experienced greater job dissatisfaction, but Black professional women were less likely to report job dissatisfaction than White professionals and Black non-professionals. Professional working women reported more discrimination than non-professional working women and those with lower levels of education, which is consistent with other studies that have found that middle-class Blacks are more likely to report perceiving discrimination (Peterson et al., 2004) and unfair treatment (Schulz et al., 2000) than low-SES Blacks while continuing to benefit from greater well-being (Kessler et al., 1999). Additionally, Black professional women who experienced acute discriminatory events did not report being as adversely affected by these experiences as earlier research might suggest. What remains less clear is whether Black professional women, who combat multiple stressors, are more highly motivated and if this motivation subsequently leads to lower rates of job dissatisfaction (Forman, 2003).
Lastly, the racial composition of the workplace was unrelated to any of the global indicators of well-being. The hypothesis was that the racial composition of the workplace would affect Black and White women in different and opposite directions. In the analyses, all/mostly White racial compositions and all other occupational racial compositions were compared. Early research on proportional representation and tokenism suggests that those who are a numerical rarity in their occupational environment, especially on multiple social identities, experience greater amounts of stress and poor health (Frank et al., 1999; Jackson et al., 1995). Although the racial composition variable was an imperfect estimate of women’s proportional representation or feelings of tokenism, the expectation still would have been that Black women working in all or mostly White work environments would experience greater stress than their White counterparts. This hypothesis was not supported, although the odds ratio was suggestive of higher levels of job dissatisfaction for Black professional women in all or mostly White occupational environments. Further disaggregation of the racial compositions of the workplace was not possible due to the small sample size, but it is worth pursuing in future research.
Several potential limitations of the present study are worth noting. First, the cross-sectional design of this study did not allow for the establishment of a temporal causal relationship between discrimination and health. It was not possible to test whether previous health status shaped the perception of discrimination or the influence that perception could have had on subsequent health outcomes. Although this temporal ordering could not be tested, previous research on discrimination and health has suggested that prior health does not affect later perceptions of discrimination, such that the relation of discrimination to current health is independent of previous health status (Pavalko et al., 2003). Second, the discrimination measures were both self-reported and could have been subject to social acceptability bias. This is a universal problem with research using self-reports (Gee, 2008). In this study, the self-reported nature of this measure was important for capturing the experience of stress (Williams et al., 1997), especially because the perception of stress was what was important for reporting stress and well-being (Cohen et al., 1997).
Third, the sample size of professional women was small, thus inhibiting the assessment of other potentially important explanatory variables and resulting in low statistical power to detect some potentially meaningful differences as statistically significant. For example, an important mechanism affecting the expression of physical health is the response to discriminatory events. Including measures of coping would more fully elucidate the relationship found between discrimination and health. Additionally, the sample size precluded further disaggregation of the racial composition of the workplace and may have accounted for a lack of significance for the racial composition variable simply due to a lack of statistical power. Most problematic was the small number of White women in racially mixed occupational environments. The past four decades have witnessed an out-migration into suburbs of both White residents and employers from Detroit’s urban industrial areas (Schulz et al., 2000). This has led to inequality in the racial distribution of employees in companies that moved, resulting in a greater proportion of White women (Schulz et al., 2000), as was reflected in the data.
Fourth, the data and results may not be generalizable to the entire U.S. population. Detroit is one of the most racially segregated cities in the U.S. (Zenk et al., 2005; Farley et al. 1993). Although this might not be representative of all U.S. cities, Black professional women are more likely to be underrepresented in their occupations, as evidenced by the women in the Detroit Area Study. Despite this study representing a particular region of the country, these results still provide valuable insight into professional Black women’s occupational and discriminatory experiences.
One final feature of the data—namely, that they are over a decade old—might appear a significant limitation but actually is not. Between 1995 and 2010, women’s labor force participation rates stayed roughly the same at 58.9% and 58.6%, respectively (U.S. Department of Labor, 2011); also, women’s labor force participation in professional and managerial occupations increased from 48% to 52%, respectively (U.S. Department of Labor, 2011; Bureau of Labor Statistics, 1997). Furthermore, there has been a concurrent significant rise in women’s educational attainment (National Academy of Sciences 2007; U.S. Department of Labor, 2011). Despite the increased participation in professional and managerial occupations, Black women continue to be overrepresented in non-professional careers and both Black and White women continue to be underrepresented in male dominated professional careers (e.g., architects, physicians, and engineers) (Department of Labor, 2011).
Given higher levels of participation, one might expect discrimination in professional careers to have decreased. A priori, it is unclear whether this would have shifted the relationship between discrimination and indicators of psychological distress and general life satisfaction. If anything, a wider gap between women’s expectations about professional opportunities and the realization of limited professional mobility (i.e., the “glass ceiling” (National Acadamey of Sciences, 2007; Cook et al., 2002)) may have increased, worsening the potential costs of discriminatory experiences.
On balance, the Detroit Area Study has proved an appropriate dataset for this study. Finding data for a comparative study of psychological well-being among Black and White professional women was difficult. Datasets are plagued with challenges, including sample size, comparability across races, and poor data quality. Combining the Midlife in the United States (MIDUS) 1 & 2 surveys could provide an opportunity for a longitudinal study of midlife patterns, predictors, and consequences in multiple health areas. Unfortunately, this study did not adequately sample professional women, especially Black professional women. Additionally, the MIDUS survey has a Minority sub-survey which oversampled four minority populations: Dominicans, Puerto Ricans, Blacks, and Mexicans. Unfortunately, the data from the Minority sub-survey cannot be combined with populations from other MIDUS Surveys, and lacked measures of occupation. Future studies may want to explore the Coronary Artery Risk Development in Young Adults (CARDIA) Study, a longitudinal prospective cohort study that began in 1985–86, to examine the determinants and risk factors of cardiovascular disease in Black and White men and women, aged 18–30 years at enrollment, who were followed up for 25 years (Hughes et al., 1987). CARDIA’s design allows for fewer sources of bias and confounding because both measured and self-reported measures were included of physical and mental health and discrimination, although it did not include measures of occupational characteristics.
To conclude, research examining the relationship between race and health for high SES Blacks is extremely limited (Forman, 2003; Williams & Mohammed, 2009; Williams et al., 2010), despite the Bureau of Labor Statistics (2010) showing that 33.7 percent of Black women and 41.4 percent of White women are in professional careers and that, overall, women constituted 51 percent of professional and managerial workers in 2009. One study (Forman, 2003) found that racial segmentation in the workplace negatively affected the psychological well-being of middle class Blacks, but unfortunately this study did not directly examine the consequences of perceived discrimination. Despite the aforementioned limitations, the present study provides an opportunity to investigate the mental health issues of professional women and challenges the assumption that those with higher SES levels have perfect health. As Black women continue to enter the ranks of professional careers, more systematic research on discrimination and health is seriously needed, in order to expand our knowledge of the relation of discrimination and other stressors to multiple measures of health at the upper socioeconomic echelons.
Acknowledgments
Preparation of this paper was supported in part by National Institute of Health (R24 HD047873- 07, P30 AG17266) and the National Institute on Aging (T32 AG00129). I would like to give a special thank you to Dr. Jenna Nobles, Dr. Mustafa Emirbayer, Dr. Robert Hauser, and Dr. Whitney Witt.
Footnotes
Acute discrimination refers to the experience of severe negative life events that result from unfair treatment.
Different parameterizations of psychological distress were explored, all of which produced substantively identical results.
Women reporting inapplicable on job satisfaction were not currently employed and were therefore omitted from analysis of job satisfaction.
Professional careers include occupations such as computer specialist, engineer, lawyer, teacher, and social worker, while non-professional careers include occupations such as sales worker, clerical and kindred worker, office operator, service worker, and precision machine operatives, to name a few.
Outside organizations include: neighborhood, professional, religious, political, fraternal, or social organizations.
Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
References
- Adler NE, Boyce T, Chesney MA. Socioeconomic status and health: The challenge of the gradient. American Psychologist. 1994;49(1):15–24. doi: 10.1037//0003-066x.49.1.15. [DOI] [PubMed] [Google Scholar]
- Ayalon L, Young MA. A Comparison Of Depressive Symptons In African Americans And Caucasian Americans. Journal of Cross-Cultural Psychology. 2003;34(1):111–124. Retrieved from http://jcc.sagepub.com/cgi/reprint/34/1/111. [Google Scholar]
- Betancourt TS, Agnew-Blais J, Gilman SE, Williams DR, Ellis BH. Past horrors, present struggles: the role of stigma in the association between war experiences and psychosocial adjustment among former child soldiers in Sierra Leone. Social science & medicine (1982) 2010;70(1):17–26. doi: 10.1016/j.socscimed.2009.09.038. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Brown TN. “Being Black and Feeling Blue”: the Mental Health Consequences of Racial Discrimination. Race and Society. 2000;2(2):117–131. doi: 10.1016/S1090-9524(00)00010-3. [DOI] [Google Scholar]
- Brown TN. Measuring Self-Perceived Racial And Ethnic Discrimination In Social Surveys. Sociological Spectrum. 2001;21(3):377–392. doi: 10.1080/027321701300202046. [DOI] [Google Scholar]
- Clark R, Anderson NB, Clark VR, Williams DR. Racism as a stressor for African Americans. A biopsychosocial model. The American psychologist. 1999;54(10):805–16. doi: 10.1037//0003-066x.54.10.805. [DOI] [PubMed] [Google Scholar]
- Cohen S, Kessler RC, Gordon LU. Measuring Stress: A Guide for Health and Social Scientists. New York: Oxford University Press; 1997. Strategies for measuring stress in studies of psychiatric and physical disorders.pdf; pp. 3–26. [Google Scholar]
- Cokley K, Hall-Clark B, Hicks D. Ethnic Minority-Majority Status and Mental Health: The Mediating Role of Perceived Discrimination. Journal of Mental Health Counseling. 2011;33(3):243–263. [Google Scholar]
- Committee on Maximizing the Potential of Women in Academic Science and Engineering, National Academy of Sciences, National Academy of Engineering, & Institute of Medicine. Beyond Bias and Barriers: Fulfilling the Potential of Women in Academic Science and Engineering. Washington, D.C: National Academies Press; 2007. p. 307. Retrieved from http://www.nap.edu/openbook.php?record_id=11741&page=1. [PubMed] [Google Scholar]
- Cook EP, Heppner MJ, O’Brien KM. Career Development of Women of Color and White Women: Assumptions, Conceptualization, and Interventions From an Ecological Perspective. The Career Development Quarterly. 2002;50(4):291–305. doi: 10.1002/j.2161-0045.2002.tb00574.x. [DOI] [Google Scholar]
- Deitch EA, Barsky A, Butz RM, Chan S, Brief AP, Bradley JC. Subtle Yet Significant: The Existence and Impact of Everyday Racial Discrimination in the Workplace. Human Relations. 2003;56(11):1299–1324. doi: 10.1177/00187267035611002. [DOI] [Google Scholar]
- Forman TA. The Social Psychological Costs of Racial Segmentation in the Workplace: A Study of African Americans’ Well-Being. Journal of Health and Social Behavior. 2003;44(3):332– 352. Retrieved from http://www.jstor.org/stable/1519783. [PubMed] [Google Scholar]
- Frank E. Prevalence and Correlates of Harassment Among US Women Physicians. Archives of Internal Medicine. 1998;158(4):352–358. doi: 10.1001/archinte.158.4.352. [DOI] [PubMed] [Google Scholar]
- Frank E. Career Satisfaction of US Women Physicians: Results From the Women Physicians’ Health Study. Archives of Internal Medicine. 1999;159(13):1417–1426. doi: 10.1001/archinte.159.13.1417. [DOI] [PubMed] [Google Scholar]
- Gee GC. A multilevel analysis of the relationship between institutional and individual racial discrimination and health status. American Journal of Public Health. 2008;98(Supplement 1):S48–S56. doi: 10.2105/ajph.98.supplement_1.s48. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Hall JC, Everett JE, Hamilton-Mason J. Black Women Talk About Workplace Stress and How They Cope. Journal of Black Studies. 2012;43(2):207–226. doi: 10.1177/0021934711413272. [DOI] [PubMed] [Google Scholar]
- Hughes GH, Cutter G, Donahue R, Friedman GD, Hulley S, Hunkeler E, Jacobs DR, Jr, et al. Recruitment in the coronary artery disease risk development in young adults (CARDIA) study. Controlled Clinical Trials. 1987;8(4):68–73. doi: 10.1016/0197-2456(87)90008-0. [DOI] [PubMed] [Google Scholar]
- Jackson J, Williams DR. Detroit Area Study, 1995: Social Influence on Health: Stress, Racism, and Health Protective Resources. 2002 Aug 16; doi: 10.3886/ICPSR03272.v1. [DOI] [Google Scholar]
- Jackson Pamela B, Stewart QT. A Research Agenda for the Black Middle Class: Work Stress, Survival Strategies, and Mental Health. Journal of Health and Social Behavior. 2003;44(3):442–55. [PubMed] [Google Scholar]
- Jackson Pamela B, Thoits PA, Taylor HF. Composition of the Workplace and Psychological Well-being: The effects of Tokenism on America’s Black Elite. Social Forces. 1995;74(2):543–557. [Google Scholar]
- Jackson Pamela Braboy, Williams DR, Stein DJ, Herman A, Williams SL, Redmond DL. Race and Psychological Distress: The South African Stress and Health Study. Journal of health and social behavior. 2010;51(4):458–77. doi: 10.1177/0022146510386795. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Jones HL, Cross WE, DeFour DC. Race-Related Stress, Racial Identity Attitudes, and Mental Health Among Black Women. Journal of Black Psychology. 2007;33(2):208–231. doi: 10.1177/0095798407299517. [DOI] [Google Scholar]
- Kanter RM. Men and Women of the Corporation. New York: Basic Books; 1977. [Google Scholar]
- Kessler RC, Andrews G, Colpe LJ, Hiripi E, Mroczek DK, Normand SLT, Walters EE, et al. Short screening scales to monitor population prevalences and trends in non-specific psychological distress. Psychological medicine. 2002;32(6):959–76. doi: 10.1017/s0033291702006074. [DOI] [PubMed] [Google Scholar]
- Kessler RC, Mickelson KD, Williams DR. The Prevalence, Distribution, and Mental Health Correlates of Perceived Discrimination in the United States. Journal of Health and Social Behavior. 1999;40(September):208–230. [PubMed] [Google Scholar]
- Labor, U. S. D. of. Women in the Labor Force_: A Databook. U.S. Bureau of Labor Statistics; 2011. pp. 1–98. [Google Scholar]
- Lantz PM, House JS, Mero RP, Williams DR. Stress, Life Events, and Socioeconomic Disparities in Health: Results From The Americans’ Changing Lives Study. Journal of Health and Social Behavior. 2005;46(3):274–288. doi: 10.1177/002214650504600305. [DOI] [PubMed] [Google Scholar]
- Mays VM, Coleman LM, Jackson J. Perceived Race-Based Discrimination, Employment Status, and Job Stress In a National Sample of Black Women: Implications for Health Outcomes. Journal of Occupational Health Psychology. 1996;1(3):319–329. doi: 10.1037//1076-8998.1.3.319. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Pascoe EA, Smart Richman L. Perceived discrimination and health: A meta-analytic review. Psychological Bulletin. 2009;135(4):531. doi: 10.1037/a0016059. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Pavalko EK, Mossakowski KN, Hamilton VJ. Does Perceived Discrimination Affect Health? Longitudinal Relationships between Work Discrimination and Women’s Physical and Emotional Health. Journal of Health and Social Behavior. 2003;44(1):18–33. Retrieved from http://www.jstor.org/view/00221465/ap050001/05a00030/0. [PubMed] [Google Scholar]
- Pavalko Eliza K, Mossakowski KN, Hamilton VJ. Does Perceived Discrimination Affect Health? Longitudinal Relationships between Work Discrimination and Women’s Physical and Emotional Health. Journal of Health and Social Behavior. 2003;44(1):18–33. doi: 10.2307/1519813. [DOI] [PubMed] [Google Scholar]
- Peterson NB, Friedman RH, Ash AS, Franco S, Carr PL. Faculty self-reported experience with racial and ethnic discrimination in academic medicine. Journal of General Internal Medicine. 2004;19(3):259–265. doi: 10.1111/j.1525-1497.2004.20409.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Schieman S, Reid S. Job authority and health: Unraveling the competing suppression and explanatory influences. Social Science & Medicine. 2009;69(11):1616–1624. doi: 10.1016/j.socscimed.2009.08.038. [DOI] [PubMed] [Google Scholar]
- Schieman S, Whitestone YK, Van Gundy K. The Nature of Work and the Stress of Higher Status. Journal of Health and Social Behavior. 2006;47(3):242–257. doi: 10.1177/002214650604700304. [DOI] [PubMed] [Google Scholar]
- Schulz AJ, Gravlee CC, Williams DR, Israel BA, Mentz G, Rowe Z. Discrimination, symptoms of depression, and self-rated health among African American women in Detroit: results from a longitudinal analysis. American Journal of Public Health. 2006;96(7):1265. doi: 10.2105/AJPH.2005.064543. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Schulz AJ, Israel BA, Williams DR, Parker E, Becker A, James S. Social inequalities, stressors and self-reported health status among African American and white women in the Detroit metropolitan area. Social science & medicine (1982) 2000;51(11):1639–53. doi: 10.1016/s0277-9536(00)00084-8. [DOI] [PubMed] [Google Scholar]
- Schulz AJ, Williams DR, Israel B, Becker A, Parker E, James S, Jackson J. Unfair treatment, neighborhood effects, and mental health in the Detroit metropolitan area. Journal of health and social behavior. 2000;41(3):314–32. [PubMed] [Google Scholar]
- Shrier DK, Zucker AN, Mercurio AE, Landry LJ, Rich M, Shrier LA. Generation to generation: discrimination and harassment experiences of physician mothers and their physician daughters. Journal of women’s health (2002) 2007;16(6):883–94. doi: 10.1089/jwh.2006.0127. [DOI] [PubMed] [Google Scholar]
- StataCorp, L. Stata version 11.0. College Station, TX: StataCorp LP; 2009. [Google Scholar]
- Statistics, B. of L. Gender differences in occupational employment. 1997 Apr;:15–24. [Google Scholar]
- Williams DR, Mohammed SA. Discrimination and racial disparities in health: evidence and needed research. Journal of behavioral medicine. 2009;32(1):20–47. doi: 10.1007/s10865-008-9185-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Williams DR, Mohammed SA, Leavell J, Collins C. Race, socioeconomic status, and health: complexities, ongoing challenges, and research opportunities. Annals of the New York Academy of Sciences. 2010;1186(1):69–101. doi: 10.1111/j.1749-6632.2009.05339.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Williams DR, Neighbors HW, Jackson JS. Racial/Ethnic Discrimination and Health: Findings From Community Studies. American journal of public health. 2008;98(9 Suppl):S29–37. doi: 10.2105/ajph.98.supplement_1.s29. Retrieved from -1&ver=1&vname=PQD&RQT=309&did=289036581&exp=02-24-2012&scaling=FULL&vtype=PQD&rqt=309&TS=1172436682&clientId=3751. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Williams DR, Yu Y, Jackson; JS, Anderson NB. Racial Differences in Physical and Mental Health: Socio-economic Status, Stress and Discrimination. Journal of Health Psychology. 1997;2(3):335–351. doi: 10.1177/135910539700200305. [DOI] [PubMed] [Google Scholar]
- Witt WP, Kahn R, Fortuna L, Winickoff J, Kuhlthau K, Pirraglia PA, Ferris T. Psychological distress as a barrier to preventive healthcare among U.S. women. The journal of primary prevention. 2009;30(5):531–547. doi: 10.1007/s10935-009-0190-z. [DOI] [PubMed] [Google Scholar]