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. Author manuscript; available in PMC: 2017 Nov 1.
Published in final edited form as: Sociol Inq. 2017 Feb 16;87(2):233–255. doi: 10.1111/soin.12168

Microaggressions, Discrimination, and Phenotype among African Americans: A Latent Class Analysis of the Impact of Skin Tone and BMI

Verna M Keith 1,✉, Ann W Nguyen 2, Robert Joseph Taylor 3, Dawne M Mouzon 4, Linda M Chatters 5
PMCID: PMC5464745  NIHMSID: NIHMS833039  PMID: 28603300

Abstract

Data from the 2001–2003National Survey of American Life are used to investigate the effects of phenotype on everyday experiences with discrimination among African Americans (N=3343). Latent class analysis is used to identify four classes of discriminatory treatment: 1) low levels of discrimination, 2) disrespect and condescension, 3) character-based discrimination, and 4) high levels of discrimination. We then employ latent class multinomial logistic regression to evaluate the association between skin tone and body weight and these four classes of discrimination. Designating the low level discrimination class as the reference group, findings revealed that respondents with darker skin were more likely to be classified into the disrespect/condescension and the high level microaggression types. BMI was unrelated to the discrimination type, although there was a significant interaction effect between gender and BMI. BMI was strongly and positively associated with membership in the disrespect and condescension type among men but not among women. These findings indicate that skin tone and body weight are two phenotypic characteristics that influence the type and frequency of discrimination experienced by African Americans.

Microaggressions are verbal and behavioral exchanges, sometimes subtle and covert, that send denigrating messages to people of color (Sue et al. 2007). These raced-based interactions, including slights, exclusions, avoidance, and unfair treatment (Smith, Allen, and Danley 2007), can be stressful, demoralizing and, more importantly, threaten mental and physical health (Monk 2015; Sue et al. 2009; Williams and Mohammed 2009). Microaggressions are used to “…keep those at the racial margins in their place” (Pérez Huber and Sol rzano 2015:298), constitute chronic sources of stress (Smith et al. 2007; Williams and Mohammed 2009), and are embedded in larger institutional arrangements and ideologies that reinforce white privilege and white superiority (see Bonilla-Silva 2013:8–11). Investigations of microaggressions range from smaller in-depth qualitative studies to understand the nature of microaggressions (e.g., McCabe 2009) to large scale surveys that employ measures of “everyday discrimination” to evaluate the impact of routine discriminatory experiences on physical and mental health (e.g. Kessler, Mickelson, and Williams 1999; Pérez, Fortuna, and Alegría 2008). While each methodological approach documents the widespread prevalence of race-based interpersonal interactions and their consequences for racial/ethnic minorities, far less attention is given to the issue of differential exposure to these micro stressors within ethnoracial groups.

Other systems of oppression (e.g., gender) intersect with race to influence the life chances of people of color. A long tradition of research, for example, finds that African Americans with darker skin tones are more negatively impacted by racism than those with lighter skin tones. Darker skin tone is associated with fewer opportunities for socioeconomic achievement and other socially desirable outcomes such as marriage (Hunter 2005; Hughes and Hertel 1990; Monk 2014). Other phenotypic characteristics, such as excess body weight, are also stigmatized in U.S. society (Saguy and Gruys 2010), such that overweight individuals are frequently subjected to discriminatory treatment (Carr and Friedman 2005). Finally, other social characteristics (e.g., gender) potentially combine with race and phenotype features to expose racial group members to different combinations of microaggressions. This is an important question given that recent research suggests that specific permutations of microaggressions are more detrimental for emotional well-being than others (Clark et al. 2015).

The goal of this paper is to investigate correlates of everyday discrimination—microaggressions that reflect personal rejection, disrespect, and unfair treatment among a national sample of African Americans. We use latent class analysis to identify four classes of everyday discrimination and investigate whether patterns of discrimination vary by skin tone and body weight. The literature review begins with a discussion of research on race, microaggressions, and discrimination. This is followed by a discussion that bridges the constructs of microaggressions and everyday discrimination as interactional vs. structural approaches to racialized social interactions. We next explore microaggressions, discrimination, and phenotype (i.e., skin color and body weight), followed by a focused discussion employing an intersectionality framework in relation to phenotype and discrimination. In particular, we explore how the intersection of gender and aspects of phenotype (skin color and weight) may be associated with higher levels of discrimination. We end the literature review by describing the focus of the present study.

Background

Race, Microaggressions, and Discrimination

Scholars have long noted the shifting forms of racism in the United States. For example, conventional forms of racism---historically overt and deliberate in nature—have plagued this country’s not-too-distant past, dating from the endemic racialized violence of the enslavement, Reconstruction, Jim Crow and Civil Rights eras. Recent periods of American history have been characterized by more covert forms of racism (e.g., Omi and Winant 1994; Dovidio et al. 2002; Bonilla-Silva 2013). Rather than explicit acts of hatred and brutality directed toward people of color, contemporary racism is more often, although not exclusively, enacted as more subtle manifestations of disregard, disrespect, and neglect (at both the individual and institutional levels). Scholars have used both structural and social psychological approaches to better understand the new racism (Pager and Shepherd 2008). One body of research has explored the meaning of the new racial landscape at the individual level of analysis, focusing on the White majority. For example, work exploring the seeming paradox between Whites’ expressed support for racial equality and their unwillingness to support policies aimed at achieving equality, has produced a variety of richly nuanced theoretical perspectives and analyses (see Bobo and Fox 2003; Bonilla-Silva 2013; Krysan, 2000. Others scholars privilege the perspective of ethnic and racial minorities, seeking to understand their experiences with the new manifestations of racism, including the study of racial microaggressions (e.g., Smith et al. 2007; Sue et al. 2007).

The term “racial microaggressions” was originally coined by psychiatrist Chester Pierce (1995) to capture subtle, racialized insults and practices experienced by people of color. Expanding upon Pierce’s work, Sue and colleagues (2007; 2009) organized these experiences into a three-part typology---microassaults (e.g., discriminatory acts); microinsults (e.g., negative insinuations about ability or character), and microinvalidations (e.g., denial of racialized experiences). Prolific research over the past decade, largely centered on race-based interactions at predominantly white institutions (PWIs), have documented how students of color are made to feel unintelligent, exposed to stereotypic course content about their group, subjected to low faculty expectations and recounted how African American males, presumed to be criminal and dangerous, are subjected to hypervigilance by agents of law enforcement (McCabe 2009 ; Nadal Griffin, and Hamit 2014; Sol rzano, Ceja and Yasso 2000; Smith et al. 2007). Further, studies of faculty of color at PWIs indicate that they are also subject to microaggressions including being dismissed as unqualified, affirmative action hires, chided for hair and dress deemed not to conform to normative standards, questioned about the appropriateness of their research and teaching topics, and having their authority and intellectual ability challenged by students, especially White students (Griffith et al. 2011; Pittman 2012; Stanley 2006).

Microaggressions and Everyday Discrimination: Interactional and Structural Approaches

The study of racial microaggressions has strong roots in psychological literature, often implicitly locating racial prejudice within the psyche or personality traits of individuals. A main point of departure in macro-level sociological theorizing on racism is its insistence upon expanding the lens beyond the individual (micro) level. For instance, sociologists have long rejected the notion that racial prejudice is a mere property of individual expression. Instead, racism and racial discrimination (behaviors that are a product of either implicit or explicit racist thinking) reflects broader racialized social stratification systems that privilege Whites over people of color and is maintained by a collective ideology or frame that portrays minorities in narrow, negative stereotypes that devalue and marginalize them (Bonilla-Silva, 2013; Feagin 2006). The most profound effects of racism occur via macro levels processes such as segregation that shapes access to social and economic rewards. However, Essed (1991), argued for recognizing that both macro and micro processes perpetuate racism, noting that the racial hierarchy (structure) is produced in ongoing and dynamic social interactions. Essed’s concept of everyday racism was “…introduced to cross the boundaries between structural and interactional approaches to racism and to link details of micro experiences to the structural and ideological context in which they are shaped” (1991:244). Her aim was to illustrate how structural racism is produced and reproduced in routine and repetitive micro interactions. For Essed, everyday racism, involve instances where individual racial experiences intersect with and are a consequence of the racialized social system.

Drawing on Essed’s work, the construct of everyday discrimination (Williams and Mohammed 2013) has been especially prevalent in the public health and biomedical literatures. Everyday discrimination is conceptualized as chronic, recurrent experiences with discrimination that occur in commonplace social interactions. In keeping with sociological conceptualizations of racism, everyday discrimination is driven by deeply embedded institutional and cultural arrangements that devalue people of color, and portray them in negative imagery (e.g., prone to violence, lazy) that shapes their interpersonal interactions with Whites (Williams and Mohammed 2013).

Everyday discrimination is most often operationalized using the Everyday Discrimination Scale (EDS) (Williams et al. 1997), a short 10-item instrument developed for use in large surveys, which conceptualizes discrimination as mundane stressors that derive from status positions, including minority group status. As such everyday discrimination is distinct from occurrences that are recognized major discriminatory events such as housing discrimination, being fired or denied a bank loan. The EDS, in contrast, captures some of the day-to-day experiences that Essed (1991: Table 5) elaborated upon such as “treated with less respect,” “perceived as dishonest,” “threatened or harassed,” and “called names.” Although not an exhaustive list of the many microaggressions that people of color are exposed to, EDS items encompass events that are similar Sue et al.’s (2007) notions of microassaults and microinsults as clear examples of unfair treatment and disrespect. Microassaults are somewhat more overt and appear less often in the microaggression literature.

Everyday discrimination occurs frequently for African Americans and other people of color (Gee et al. 2009; Kessler et al 1999; Pérez et al. 2008), with some studies noting that as many 50 percent or more of African American respondents report being targets of race based discrimination (Brondolo et al. 2011). Further, these encounters, characterized as frustrating, anger provoking, and generally stressful experiences, pose significant risk to physical and mental health (Keith et al, 2010; Levine et al. 2014; Lewis, Cogburn, and Williams 2015; Nadal et al. 2014; Williams and Mohammed, 2009; Watkins et al. 2011). Although discrimination is recognized as an everyday occurrence for many people of color, there are differences in the level and intensity of exposure to these events. Research on microaggressions among African Americans indicates that exposure to such treatment is both gendered (Ifatunji and Harnois 2016) and classed (Miller, Rote, and Keith 2013), with better educated persons and men reporting more frequent events. As such, differential exposure to these incidents may be aligned and intersect with other social categories and physical traits such as skin complexion and body weight.

Microaggressions, Discrimination, and Phenotype

African Americans experience discrimination based on two interlocking systems (Hunter 2005; Weaver 2012)--- their perceived membership in an racial group (racial discrimination) as well as, a phenotype-based continuum that privileges lighter skin tones and a more Eurotypical racial appearance over darker skin tones and a more Afrotypical racial appearance (i.e., colorism). Among African Americans, lighter skin complexion is associated with higher educational attainment, occupational status, wages and income; a greater likelihood of being employed; and more positive self-evaluations (Goldsmith, Hamilton, and Darity 2007; Hughes and Hertel 1990; Keith and Herring 1991; Monk 2014; Thompson and Keith 2001). Additional evidence of light skin advantage indicates that darker skinned defendants in the criminal justice system receive longer and more severe sentences (e.g., death sentences) than their lighter hued coethnics (Blair, Judd and Chapleau 2004; Eberhardt et al 2006; Gyimah-Brempong and Price 2006). Other work documents the more positive influence of light skin complexion for perceptions and evaluations of African American political candidates (Caruso Mead, and Balcetis 2009; Weaver 2012).

The vast majority of studies of colorism lack direct measures of overt and covert racial bias. Instead, linkages between skin color with health and social outcomes are inferred with the assumption that darker African Americans are subjected to more negative stereotypes and, hence, more discrimination. The few studies that include measures of discrimination have yielded mixed findings, ranging from no color bias (Borrell et al., 2006; Keith et al. 2010), minimal color differences in unfair treatment (Hersch 2011), and significantly more discriminatory experiences for darker respondents (Klonoff and Landrine 2000). Uncovering color gradations in racially biased experiences may, however, depend on the measures of skin color used and the source of discrimination (Monk 2015; Uzogara et al. 2013). Monk (2015), for example, finds that self-rated skin tone is a more robust predictor of unfair treatment than interviewer-rated skin tone and that lighter skin Blacks perceive more bias from other Blacks, while darker Blacks perceive more bias from Whites.

Excess body weight is an additional source of social bias given the cultural valorization of thinness in the U.S. (Saguy and Gruys 2010). Similar to dark skin tone, negative stereotypes are applied to individuals who are perceived as being overweight or obese whereby they are viewed as lazy, gluttonous, lacking self-control, unconcerned about their health (Saguy and Gruys 2010; Strings 2015), and unattractive (Hersch 2011). The declaration of obesity as a major public health problem in the 1990s, increasing public awareness of the link between weight and health, and the news media’s framing of obesity as a moral problem (Barry et al 2009; Saguy and Almeling 2008) have likely exacerbated such perceptions and contributed to limited public understanding of structural determinants of excess body weight such as the availability and affordability of nutritious, non-fattening foods (Morland and Evenson 2008). While body weight norms and the thinness ideal may be applied less rigorously within communities of color (Beauboeuf-Lafontant, 2003; Granberg, Simmons, and Simmons 2009), higher rates of obesity among African Americans make them vulnerable to weight-related stigma and discrimination in the larger society. Obese individuals report more instances of everyday discrimination, both microassaults and microinsults (Carr and Friedman 2005; Schafer and Ferraro 2011), than normal weight individuals.

Intersectionality, Phenotype, and Discrimination

Both colorism and weight may be more consequential for African American women than African American males. Collins (2000), Crenshaw (1989), McCall (2005), and other multiracial feminist theorists have argued forcefully that race, class, gender and other social identities converge to produce interlocking systems of oppression and opportunity that condition life experiences in unique ways. While both African American men and women face racism, the particular manifestations of racism are gendered such that oppression is predicated on a unique set of controlling images (Collins 2000). Images for Black women depict them as mammies, domestic workers, promiscuous, angry, and as welfare mothers and that deem them as less attractive, unfeminine, and more distant from the European ideal. Attractiveness is more important for women than for men, and light skin Black women are deemed more beautiful than darker Black women (Hill 2002). Due to the link between skin complexion and beauty perceptions, skin tone operates as a form of social capital such that lighter skinned Black women attract males with higher socioeconomic status (Hunter 2005; Monk 2014), a phenomenon not evident among Black men.

In the African American community, women who are larger in body size are less stigmatized, feel less pressure to be thin, have more a more positive body image, and are more accepted by Black males as romantic partners (Fujioka et al. 2009; Powell and Kahn 1995; Webb, Looby, and Fults-McMurtery 2004). Yet, in the larger society overweight and obesity restrict opportunities for upward mobility as they are associated with lower grades in school (Crosnoe and Muller 2004), lower college attendance (Crosnoe 2007), and lower wages Mason (2012); effects that are significantly stronger for women than men. White gatekeepers in schools and the workplace are likely to embrace the thin ideal, placing African American women at a greater disadvantage than their male counterparts. For both males and females, the double disadvantages of being darker in skin tone and heavier are likely to result in greater exposure to discrimination.

The Present Study

This study investigates the association between phenotype and everyday discrimination, micro-level interactions that involve unfair treatment and disrespect, among African Americans. We argue that everyday discrimination captures microassaults and microinsults and represent individual-level encounters that derive from social hierarchies (e.g., race, skin color and weight, gender) that shape interactions. We analyze data from the National Survey of American Life which allows for the application of important demographic and health covariates and produces findings that are generalizable to the African American population. We use a scale developed by Williams et al. (1997) to determine differences in the frequency with which African Americans are exposed to discriminatory experiences. We use latent class analysis (LCA) to explore patterns that emerge from the type and frequency of discriminatory encounters reported by respondents. The following hypotheses are evaluated.

Hypothesis1: Both darker skin tone and larger body weight will be associated with more frequent exposure to multiple types of everyday discrimination.

Hypothesis2: The effects of darker skin tone and body weight on exposure to multiple types of discrimination will be stronger for women than for men.

Hypothesis 3: The combination of dark skin tone and larger body weight will be associated with more frequent exposure to multiple types of everyday discrimination.

Data and Methods

Data

The African American sample for the current analyses was drawn from the National Survey of American Life: Coping with Stress in the 21st Century (NSAL), which was collected by the Program for Research on Black Americans at the University of Michigan’s Institute for Social Research. The African American sample is the core sample of the NSAL. The core sample consists of 64 primary sampling units (PSUs), of which 56 of these primary areas overlap substantially with existing Survey Research Center National Sample primary areas. The remaining eight primary areas were chosen from the South in order for the sample to represent African Americans in the proportion in which they are distributed nationally. The African American sample is a nationally representative sample of households located in the 48 coterminous states with at least one Black adult 18 years or older who did not identify ancestral ties in the Caribbean. The data collection was conducted from February 2001 to June 2003. A total of 6,082 interviews were conducted with persons aged 18 or older, including 3,570 African Americans, 891 non-Hispanic whites, and 1,621 Blacks of Caribbean descent. Fourteen percent of the interviews were completed over the phone and 86% were administered face-to-face in respondents’ homes. Respondents were compensated for their time. The overall response rate was 72.3%. Final response rates for the NSAL two-phase sample designs were computed using the American Association of Public Opinion Research (AAPOR) guidelines (for Response Rate 3 samples) (AAPOR, 2006) (see Jackson et al. (2004) for a more detailed discussion of the NSAL sample). The NSAL data collection was approved by the University of Michigan Institutional Review Board.

Measures

Dependent Variable

Our dependent variable is the Everyday Discrimination Scale (Williams, et al. 1997) that was designed to assess interpersonal forms of routine discrimination. The scale is comprised of 10 items: being treated with less courtesy, treated with less respect, received poor restaurant service, being perceived as not smart, being perceived as dishonest, or being perceived as not as good as others; and being feared, insulted, harassed, and followed in stores. Response values for each item were: 5 (almost every day), 4 (at least once a week), 3 (a few times a month), 2 (a few times a year), 1 (less than once a year), and 0 (never). In order to facilitate the analysis and interpretation of the results in latent class analysis, all indicators were dichotomized using median split. A value of 1 indicates low levels of the specific class indicator, and a value of 2 indicates high levels of the specific class indicator.

Independent Variables

Self-rated skin tone is measured by the question: “Compared to most Black people, what shade of skin color do you have? Would you say very dark brown (5), dark brown (4) medium brown (3), light brown (2), or very light brown (1).” Body weight is measured using the body mass index (BMI), a continuous measure calculated as: (BMI= 703 x weight (lbs.)/ height (ins.)2.

Control Variables

Gender is a dummy variable (0=male, 1=female) and age is coded in years. Employment status differentiates respondents who are employed (the reference category), unemployed, and out of the labor force, while occupation differentiates those who are employed in white collar (reference category), service, blue collar, and other. Marital status is coded into five categories---married or partnered (reference category), separated, divorced, widowed, and never married. Region differentiates respondents residing in the Northeast, North Central, West and South (reference category). Indicators of socioeconomic status are education, coded in years, and logged annual household income coded in dollars. Missing data for education and income were imputed using an iterative regression-based multiple imputation approach incorporating information about age, sex, region, race, employment status, marital status, home ownership, and nativity of household residents. Income was coded in dollars, and the log of income is used in order to minimize variance and account for its skewed distribution.

Analysis Strategy

Latent class analysis (LCA) was used to identify discrimination typologies. LCA uses a person-centered approach to classify respondents into subgroups (i.e., latent classes) based on their patterns of response across a set of dichotomous class indicators. The latent classes identified from this procedure represent discrimination types. Latent class multinomial logistic regression analysis was used to determine correlates of discrimination types. This was conducted using the 3-step LCA approach in order to avoid the inclusion of the independent variables in the class extraction process (Asparouhov and Muthén 2014). All analyses used analytic weights. Statistical analyses accounted for the complex multistage clustered design of the NSAL sample, unequal probabilities of selection, nonresponse, and poststratification to calculate weighted, nationally representative population estimates and standard errors.

Results

Table 1 presents the sociodemographic description of the sample and study variables. The sample was 44% male, the mean age was 43 years, average education was 12 years, and the mean household income was $32,037. About 42% of the sample was married or partnered, 56% resided in the South, and 67% of respondents were employed. One in four respondents was employed in the white collar sector. The average BMI was 28.93, which exceeds the BMI cut point of 25.0 that is indicative of an overweight status. One in two respondents considered themselves to have medium brown skin, and 25% of respondents reported that they had dark skin. Overall, respondents reported relatively low levels of discrimination. However, it is important to note that even low levels of discrimination have a major impact on physical and mental health (Levine et al 2014).

Table 1.

Demographic Characteristics of the Sample and Distribution of Study Variables

% (Mean) N (S.D.) Range
Gender
    Male 44.03 1271
    Female 55.97 2299
Age 43.15 16.32 18 – 93
Education 12.30 2.58 0 – 17
Income 32037.15 32687.94 0 – 520000
Marital
    Married/Partnered 41.65 1220
    Separated 7.16 286
    Divorced 11.75 524
    Widowed 7.89 353
    Never married 31.55 1170
Region
    Northeast 15.69 411
    North Central 18.81 595
    South 56.24 2330
    West 9.25 234
Employment Status
    Employed 66.83 2334
    Unemployed 10.07 366
    Not In Labor Force 23.10 861
Occupation
    White Collar 25.00 868
    Service 23.12 791
    Blue Collar 46.87 1713
    Other 5.01 197
BMI 28.93 6.56 15.41 – 66.08
Skin Tone
    Very light brown 4.85 163
    Light brown 15.48 560
    Medium brown 49.02 1695
    Dark brown 24.83 906
    Very dark brown 5.81 192
Treated with Less Courtesy
    Low 54.49 1984
    High 45.51 1533
Treated with Less Respect
    Low 58.59 2096
    High 41.41 1422
Received Poor Service
    Low 59.72 2164
    High 40.28 1356
Not Smart
    Low 56.00 1984
    High 44.00 1528
Afraid of You
    Low 43.53 1603
    High 56.47 1913
Dishonest
    Low 43.11 1585
    High 56.89 1932
Better Than You
    Low 44.25 1581
    High 55.75 1923
Called Names/Insulted
    Low 49.37 1795
    High 50.63 1723
Threatened/Harassed
    Low 57.36 2078
    High 42.64 1445
Followed in Stores
    Low 42.28 1558
    High 57.72 1945
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Note: Percentages and N are presented for categorical variables and Means and Standard Deviations are presented for continuous variables. Percentages are weighted and frequencies are un-weighted.

LCA yielded a four-class/typology solution. Model fit was determined by the Akaike information criterion, Bayes information criterion, and adjusted Bayes information criterion. The item response probabilities are depicted in Figure 1. The four derived discrimination types are low discrimination, disrespect and condescension, character-based discrimination and hostility, and high discrimination. The low discrimination type, the most prevalent type (32.95% of the sample), is characterized by low levels of disrespect, condescension, character-based discrimination and hostility. The second most prevalent type is disrespect and condescension (26.32%). This type is characterized by high levels of disrespect and condescension, moderate levels of character-based discrimination, and low levels of hostility. The character-based discrimination and hostility type is the least prevalent type (14.95%) and is distinguished by high levels of character-based discrimination and hostility but low levels of disrespect and condescension. Finally, respondents in the high discrimination type (24.79%) report high levels of disrespect, condescension, hostility, and character-based discrimination.

Figure 1.

Figure 1

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Conditional item probability profile. Discrimination typology size information presented in the legend.

Results for the latent class multinomial logistic regression analysis are presented in Table 2. The low discrimination type is set as the comparison category. Consistent with hypothesis one, respondents with darker skin were more likely to belong to the high discrimination and disrespect and condescension types, although BMI was unrelated to discrimination. With respect to occupation, respondents who worked in the service and blue collar industries were less likely to belong to the high discrimination or character-based discrimination and hostility types than their counterparts employed in the white collar sector. Regarding sociodemographic differences, older respondents were less likely to belong to the high discrimination, disrespect and condescension, and character-based discrimination and hostility types compared to younger respondents. Divorced respondents, relative to respondents who were married or partnered, had a greater probability of being a member of the high discrimination type. The probability of belonging to the disrespect and condescension or the high discrimination type was greater for individuals who lived in the Northeast and North Central regions of the U.S. compared to those who lived in the South. Additionally, respondents who lived in the North Central region were more likely than those who lived in the South to be a member of the character-based discrimination and hostility type.

Table 2.

Latent Class Multinomial Logisitc Regression Analysis of Discrimination Typologies on Independent Variables among African Americans (N = 3343)

Disrespect and Condescension
vs. Low Discrimination		 High Discrimination vs. Low
Discrimination		 Character-Based
Discrimination and Hostility
vs. Low Discrimination
Logit SE Logit SE Logit SE
Gender
    Female 0.96 0.71 −0.88 0.55 0.48 0.81
Age −0.03 0.01*** −0.05 0.01*** −0.03 0.01***
Education −.00 0.02 0.03 0.04 0.04 0.04
Income 0.01 0.01 0.01 0.01 −0.01 0.01
Marital Status
    Separated 0.33 0.23 0.39 0.25 −0.20 0.34
    Divorced 0.27 0.17 0.47 0.23* −0.00 0.23
    Widowed 0.13 0.29 −0.13 0.30 0.11 0.27
    Never Married −0.11 0.14 0.04 0.16 0.06 0.19
Region
    Northeast 0.46 0.22* 0.52 0.22* 0.31 0.19
    North Central 0.40 0.16* 0.67 0.24** 0.60 0.16***
    West 0.41 0.39 0.73 0.43 0.33 0.30
Employment Status
      Unemployed 0.07 0.22 0.26 0.21 0.27 0.29
      Not In Labor Force −0.20 0.19 0.01 0.14 −0.13 0.15
Occupation
    Service −0.25 0.17 −0.47 0.14** −0.55 0.22*
    Blue Collar −0.19 0.18 −0.53 0.14*** −0.73 0.20***
    Other −0.55 0.31 −0.39 0.30 −0.67 0.45
BMI 0.01 0.01 0.02 0.01 0.01 0.01
Skin Tone 0.17 0.06** 0.21 0.06** 0.09 0.08
Female*BMI 0.05 0.02* −0.01 0.02 0.03 0.03
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Reference category for gender = male, marital status = married/partnered, region = South, employment status = employed, occupation = white collar.

*

p < .05;

**

p < .01;

***

p < .001

Guided by previous findings that exposure to discrimination is influenced by the intersection of multiple statuses, interaction terms representing gender by skin tone (H2), gender by BMI (H2), and skin tone by BMI (H3), were constructed and tested in latent class multinomial logistic regression models. The gender by skin tone and skin tone by BMI interactions were not statistically significant, so they were not included in the final model. Although there are no significant main effects for gender and BMI, there is a significant interaction effect between gender and BMI (Table 2). This interaction effect indicates that while higher BMI is associated with a nominal increase in the probability of belonging to the disrespect and condescension type for women, BMI is strongly and positively associated with membership in the disrespect and condescension type among men (Figure 2). That is, as African American men’s BMI increases, their probability of belonging to the disrespect and condescension type, as compared to the low discrimination type, increases substantially. Body weight matters for men, but not for women.

Figure 2.

Figure 2

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Predicted probability of membership in the disrespect and condescension type by gender and BMI among African Americans.

Discussion and Conclusions

Essed (1991) argued that structural racism is produced and reproduced through routine and repetitive everyday interactions or what she labeled as everyday racism. This study builds on her concept of everyday racism as one that bridges macro and micro racial processes. Our primary goals were to use the 10-item Everyday Discrimination Scale to identify patterns of everyday discrimination with special consideration to variations based on darker skin tone and heavier body size, phenotypic characteristics that are heavily stigmatized in the U. S. Using latent class analysis, we identified four classes or types of discriminatory experiences that African Americans are exposed to, ranging from low to high levels across all 10 items. The four classes represented varying combinations and frequencies of disrespectful, demeaning, harassing, and insulting micro interactions—interactions that Sue et. al. (2007) termed microassaults and microinsults—that have received less attention in research on microaggressions. Although somewhat more overt than interactions typically addressed in the microaggression literature, they represent a key dimension in that they also occur in individual-level encounters and are structured by racialized and other socially based hierarchies.

Our results make three significant contributions to the literature on race and microaggressions. First, we find that skin complexion has a significant effect on the type and degree to which African Americans are exposed to routine race-related experiences. Second, results indicate that body weight is positively associated with discrimination for males, but not females, and may indeed contribute to previous findings that African American men report more unfair treatment than women (Ifatunji and Harnois 2016). Third, we demonstrate the utility of examining patterns of discrimination that encompass variations in the types and frequency of events as reported by respondents. We discuss these contributions in turn.

Our results show that skin tone continues to shape the life experiences of African Americans in the contemporary U.S. Designating the low level discrimination class as the reference group, we found significant skin tone gradations associated with membership in two of the four latent class subgroups identified in this study. Darker respondents were more likely to be classified in the disrespect/condescension group. This classification reflects high to moderate scores on items such as being treated with less courtesy and respect and somewhat lower scores on items such as being thought of as dishonest and followed in stores. Darker respondents were also more likely to belong to the high discrimination group characterized by frequent experiences with all ten microaggressions. While much of the previous literature on colorism infers differential racial experiences based on skin color (e.g., Hughes and Hertel, 1990; Monk, 2014), the findings from this study add to a limited, but growing, literature that directly assesses the impact of skin complexion on discrimination (see Monk 2015; Uzogara et al. 2014). As other work on complexion has documented, skin tone gradations are linked to positive and negative characteristics and stereotypes (Anderson and Cromwell 1977; Maddox 2004). Maddox notes (see also Monk 2015) that phenotypic variations influence the degree to which one is perceived as being more or less African American. Thus, our finding indicates that how black one is perceived to be along the color continuum carries with it greater or lesser risk for undesirable treatment. Thus, the racialized social system does not impact all African Americans equally.

In contrast to findings for the disrespect/condescension and high discrimination subgroups, skin tone was unrelated to the character-based/hostility subgroup. These results suggest that, regardless of complexion, a subsample of African Americans are exposed to interactions that convey negative assessment of their integrity and/or have downright hostile encounters, but few other problematic interactions. This finding may demarcate a set of racialized experiences whereby racial group membership overrides intra-group racial skin tone variations because such experiences are so prevalent. That is, for the 16% of respondents represented by this pattern, being black determines exposure to certain types of discrimination rather than how black one is perceived to be along the color continuum.

Our analysis found a significant interaction between gender and BMI which indicated that BMI was strongly and positively associated with membership in the disrespect and condescension type among men, but not among women. This finding is inconsistent with our expectation, but mirrors those of studies suggesting that heavier weight matters less for African American women. African American adolescent girls and young women tend to report heavier ideal body types, less body dissatisfaction, and more positive body images than their white counterparts (Franko and Striegel-Moore 2002, Grandberg , Simmons, and Simmons2009; Molloy and Herzberger 1998). Further, African American women are less likely to desire thinness (Fujioka et al. 2009) than their white counterparts. Research by Powell and Kahn (1995) also found African American men more willing to date women with larger body size. Some scholars attribute less emphasis on weight to entrenched cultural values, perhaps even having African influences (see Webb et al. 2004). Dutton et al. (2014) also found that African American women reported less weight discrimination than white women even at the highest levels of BMI (i.e., class I and class II obesity; BMI cut points of 30.00–34.99 and 35.00–39.99, respectively). However, it is unclear whether Dutton et al.’s (2014) is due to differences in exposure to discrimination, to less awareness of discrimination, or, given the prominence of racial discrimination, attributing discrimination to racism rather than weight (Lewis et al. 2015).

Research in the field has generally found that men report higher levels of everyday discrimination than women (Ifatunji and Harnois 2016). Such results are found in research on the general population (Kessler, Mickelson, and Williams 1999) and among Latinos (Pérez, Fortuna and Alegria 2008). It is important to note that we did not find a main effect for gender and everyday discrimination. This, however, was due to the inclusion of the gender and BMI interaction. When this interaction term was not included in the analysis, gender was significant in all three multinomial logistic regression models: African American men were more likely to belong to the disrespect and condescension, high discrimination, and character-based discrimination and hostility types compared to the low discrimination type. Consequently, the interaction between gender and obesity may account for some of the gender difference in everyday discrimination among African Americans.

This study contributes to the growing literature on discrimination by investigating everyday discrimination as a multidimensional construct. Our findings of patterns in the frequency and type of discrimination experiences mirror Essed’s research (1991) using case studies of Dutch and U.S. born Black women who reported different combinations of racist experiences. Given the effectiveness of the Everyday Discrimination Scale in uncovering these patterns, using a single scale score to represent discrimination should be viewed with caution. Specifically, single scale scores combine information from individuals with different combinations of experiences. Those differences in discrimination experiences may obscure the significance of particular types of discrimination for important outcomes. For example, in preliminary analyses we found no association between skin tone and discrimination using a summed scale score. However, using latent class analyses confirmed a relationship between skin tone and discrimination that would have remained undetected. Prior research using the Everyday Discrimination Scale (as a summed scale score) has enriched our understanding of the health threat posed by racialized stress by linking unfair treatment to a number of physical and mental health outcomes (Paradies 2006; Williams and Mohammad 2009). However, taking a more multidimensional approach as used here may be useful for better identifying individuals who are at highest risk (Ifatunji and Harnois 2016). Indeed, Clark and colleagues (2015) found that African Americans whose lives are characterized by chronic discrimination, similar to our high discrimination pattern, are more likely to meet the criteria for anxiety disorder, major depressive disorder, and illicit drug-use disorder. Future research should be mindful of how measures of discrimination are operationalized, as well as analytic methods that capture differences in types and patterns of exposure.

While this study adds to the body of work on race, phenotype, and discrimination among African Americans, it is not without limitations. The Everyday Discrimination measure used in this study includes important aspects of potentially undesirable racialized experiences, but it is limited to ten items and cannot possibly capture the entire spectrum of unfair treatment experienced by African Americans (Lewis et al 2015; Williams and Mohammed 2009). As noted previously, the scale largely reflects microassaults and microinsults rather than the more subtle microinvalidations outlined by Sue (2007). A second issue is that the items do not speak to the specific context in which the experience occurred such as the workplace or in public spaces. Where and under what circumstances African Americans are exposed to unfair treatment is important for understanding how it is subjectively experienced. For example, microaggressions experienced in the work setting where the perpetrator is known and likely to be encountered on a regular basis may be more upsetting and detrimental to health than those experienced in public spaces where the perpetrator is unknown and the interaction occurs by chance. Finally, the measure of discrimination used in this study does not take into account the source or perpetrator. Recently, Monk (2015) documented the importance of investigating who is doing the discriminating, especially as it concerns intra-racial experiences based on skin color. He found that darker skinned African Americans perceive more discrimination from whites, while lighter skinned African Americans perceive more discrimination from other African Americans. Future studies should address these limitations by exploring additional types of unfair treatment and attending to issues of context and source of discrimination.

Contributor Information

Verna M. Keith, Department of Sociology, Race and Ethnic Studies Institute, 4351 TAMU, Texas A & M University, College Station, TX 77843-4351, keithvm@tamu.edu

Ann W. Nguyen, Edward R. Roybal Institute on Aging, University of Southern California, Los Angeles, CA 90015, nguy333@usc.edu

Robert Joseph Taylor, School of Social Work, Institute for Social Research, University of Michigan, Ann Arbor, MI 48109, rjtaylor@umich.edu.

Dawne M. Mouzon, Edward J. Bloustein School of Planning and Public Policy, Institute for Health, Health Care Policy, and Aging Research Rutgers, The State University of New Jersey, New Brunswick, NJ 08901, dawne.mouzon@rutgers.edu

Linda M. Chatters, School of Public Health, School of Social Work, Institute for Social Research, University of Michigan Ann, Arbor MI 48109, chatters@umich.edu

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