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. Author manuscript; available in PMC: 2021 Dec 1.
Published in final edited form as: J Behav Med. 2020 Mar 16;43(6):932–942. doi: 10.1007/s10865-020-00146-1

Perceived racism, affectivity, and C-reactive protein in healthy African Americans: Do religiosity and racial identity provide complementary protection?

Caroline E Drolet a, Todd Lucas a,b,c,d
PMCID: PMC7492374  NIHMSID: NIHMS1576746  PMID: 32173787

Abstract

Perceived racism contributes to cardiovascular disease (CVD) disparities among African Americans. Psychosocial factors that protect against the effects of perceived racism therefore may be reflected by indicators of CVD risk, including C-reactive protein (CRP). The current cross-sectional study examined whether CRP is linked to religiosity and racial identity – two culturally-enshrined individual differences that can protect against the harmful effects of racism. Healthy African Americans completed self-report measures of everyday racism, religious intensity (a measure of the importance of religion/spirituality), and racial centrality (a measure of racial identity strength). We measured positive and negative affectivity as outcomes (N = 534), and we collected a dried bloodspot measure of CRP (N = 118). Religious intensity and racial centrality were independently associated with greater positive affectivity, and interactively associated with negative affectivity and CRP – when perceived racism was high, strongly identified African Americans had significantly higher CRP, but lower negative affectivity, when they were also low in religious intensity. Results highlight that religiosity and racial identity may interactively protect against the effects of racism and may play a role in CVD disparities.

Keywords: racism, African American, religiosity, racial identity, C-reactive protein

1. Introduction

In the United States, African Americans have the highest rates of cardiovascular disease (CVD) of any racial group (American Heart Association, 2015). Although links to socioeconomic status are well supported, CVD disparities are additionally linked to psychosocial variables, especially perceived racism – feelings of discrimination attributed to one’s race or ethnicity (Krieger & Sidney, 1996; Pascoe & Smart Richman, 2009). To better understand the role of perceived racism in the development of racial CVD disparities, researchers can examine how perceived racism is associated with CVD risk indicators.

One important CVD risk indicator is C-reactive protein (CRP; (Clearfield, 2005; Danesh et al., 2004). In addition to providing a biological indicator of CVD risk, perpetually elevated levels of CRP can indicate exposure to chronic psychological stressors (Johnson et al., 2013). Given that perceived racism is a chronic stressor for African Americans, racism-based stress may result in elevated levels of CRP, thereby partly explaining why African Americans are at greater risk for CVD. Indeed, evidence suggests that CRP levels are often higher among African Americans than non-African Americans (Lewis et al., 2010; Sims et al., 2020), though evidence is mixed (e.g., Cunningham et al., 2012). Importantly, CRP has clinical significance in that it is potentially modifiable and could be targeted by interventions to lower CVD risk (Mora et al., 2009). In turn, it is critical to understand factors that protect against racism, including whether this protective function also extends to CVD risk indicators, such as CRP.

One way of buffering against stressors like racism is through identifying with social groups. Social identity can protect against psychological and physiological effects of stress (Contrada & Ashmore, 1999; Linville, 1985). People’s positive self-concept (i.e., sense of self) partly reflects their group identities (Ellemers & Haslam, 2012; Tajfel & Turner, 1986) and identifying with these groups can help buffer the negative effects of stressors by providing social support, resources (e.g., financial aid), and information for navigating stressful life events (House, 1981), in addition to contributing to a positive self-concept. Importantly, social identities can also promote a sense of social belonging, which can confer health (Contrada & Ashmore, 1999). Although potentially protecting against stress, social identity can also negatively impact stress and health, particularly among racial minorities who belong to marginalized social groups (e.g., Romero & Roberts, 1998). In tandem, social identities are multi-faceted, as individuals simultaneously belong to and identify with more than one social group. Understanding connections to CVD disparities thus requires explicating how multiple social identities operate in concert to impact CVD, and CVD risk factors. This especially includes understanding social identities that are culturally-enshrined among racial minorities.

One culturally-relevant identity among African Americans is religiosity, encompassing adherence to the beliefs and practices of a religion (Mattis & Jagers, 2001). Research indicates that religiosity is often and generally positively related to indicators of health (e.g., Hill et al., 2014; Suh et al., 2019). For African Americans, religious beliefs can additionally reflect a culturally-based response to oppressive social and political contexts (see Mattis & Jagers, 2001). In turn, religious beliefs can offer a unique means for buffering the effects of racism (Long, 1997), and there is evidence that African Americans may be particularly likely to experience associated health benefits (e.g., Ferraro & Kim, 2014; Krause, 2002). For example, Ferraro and Kim (2014) found that for African Americans, but not Whites, religious service attendance was related to overall lower levels of CRP, and reduced CRP over time. Taken with evidence that African Americans use some religious coping strategies in response to perceived racism (Lewis-Coles & Constantine, 2006), religiosity might protect against the deleterious health effects of perceived racism.

Another culturally-relevant social identity for African Americans is racial identity strength, encompassing the extent to which one’s race is important to one’s self-concept (Sellers & Shelton, 2003; Sellers et al., 1998). Strongly identifying as a member of one’s racial group can protect against the negative effects of racism and discrimination (Mossakowski, 2003; Sellers et al., 2006; Wong et al., 2003), thereby offering some health benefits (Smith & Silva, 2011). However, findings in this area have been mixed in that racial identity can either protect against or create additional vulnerability to racism-related stress and associated health consequences (McKoy & Major, 2003; Mossakowski et al., 2019; Sellers & Shelton, 2003). Notably, among marginalized minorities, a strong racial identity may make experiences of racism more salient, thereby exacerbating stress and negative health consequences (Romero & Roberts, 1998). Although there is evidence of links between racism and CRP (Lewis et al., 2010), connections from racial identity to CRP have not been as well attended to (though see Lucas et al., 2017).

Although both religiosity and racial identity can protect against the effects of racism, and in doing so carry implications for CVD disparities, these protective factors have not, to our knowledge, been examined simultaneously. This includes evaluating links from religiosity and racial identity to CVD risk factors, such as CRP. Simultaneously evaluating these protective factors is critical in two ways. First, given a common origin in social identity, evidence is needed to decipher whether religiosity and racial identity confer unique health benefits to African Americans, and perhaps to consider their relative importance. Second, religiosity and racial identity could work synergistically to provide health and wellness benefits to African Americans, above and beyond the independent contribution of each identity. For example, religiosity and racial identity could augment the protective benefits that each independently provides. Alternatively, religiosity and racial identity might attenuate the protective health benefits of one another in ways that are presently unknown.

Using convenience community samples of healthy African Americans, the current cross-sectional provides a critical starting point in examining associations between religiosity, racial identity, and perceived racism on CRP. We specifically examined racial centrality and religious intensity, as both constructs encompass the strength of one’s racial and religious identity. Racial centrality is the extent to which one’s racial identity is an important part of their self-concept (Sellers et al., 1997), and religious intensity, similarly, is the extent to which individuals see themselves as spiritual or religious (Fetzer Institute & National Institute on Aging Working Group, 1999). Moreover, these aspects of racial and religious identity are analogous and core components of lining these identities to well-being (e.g., Dilmaghani, 2018; Sellers et al., 2003). As additional outcomes, we also considered links to individual differences in positive and negative affect (i.e., affectivity). Past research has also linked affectivity to CVD (see Diener & Chan, 2011), with negative affectivity especially predicting CVD (see Suls & Bunde, 2005), similar to CRP. We expected that racial centrality and religious intensity would both be associated with lower CRP. In addition, we considered whether religious intensity and racial centrality would interactively attenuate the deleterious association between perceived racism and CRP, especially when participants were high on both constructs. We expected that a similar pattern of effects would emerge for negative affectivity. Although links from positive emotions to cardiovascular disease are less established, we explored whether links from positive affectivity to CRP would mirror those obtained for negative affectivity.

2. Method

2.1. Sample and Procedure

Our sample size was based on a manipulation for a separate study on stress reactivity (see Lucas et al., 2016; 2017). The procedure for the stress reactivity study took place after the current study. We collected enough participants to have approximately 25 participants in each of four conditions (Simmons, Nelson, & Simonsohn, 2011) for the laboratory session. A community sample of 534 African American adults (404 female, 129 male, 18–69 years old, Mage = 32.15, SDage = 13.12) was recruited from the metropolitan Detroit area via posted and online advertisements. After giving informed consent, all participants completed a prescreen battery that contained the subsequently described measures of religious intensity, perceived racism, and racial centrality, and affectivity. A subset of 118 African American adults (82 female, 36 male, 18–63 years old, Mage = 31.92, SDage = 13.89) participated in an additional face-to-face laboratory session, during which the subsequently described bloodspot sample was collected. Prescreen measures were used to determine eligibility for the laboratory portion of the study: Excluded individuals reported a pre-existing mental health condition (e.g., depression or anxiety), an endocrine disorder, or were using steroid based anti-inflammatory medication or adrenergic agonists or antagonists (i.e., beta blockers). The laboratory visit took place at least one week after completing prescreen measures at a university laboratory that was centrally located in Detroit. The subset did not significantly differ from the full sample on either age, t(112) = −0.18, p = .86, or participant sex, χ2(1) = 2.56, p = .11. Table 1 reports sample characteristics for marital status, employment, education, and income. This study received ethics review board approval. All participants completed an informed consent, were fully debriefed, and received modest remuneration.

Table 1.

Sample characteristics

Demographic Characteristic Full Sample n (%) Subset n (%)
Marital Status
 Married 72 (13.5%) 12 (10.2%)
 Remarried 3 (0.6%) 0 (0%)
 Divorced 60 (11.3%) 14 (11.9%)
 Widowed 6 (1.1%) 1 (0.8%)
 Single or Never Married 391 (73.5%) 91 (77.1%)
Employment
 Employed and working full-time 126 (23.6%) 15 (12.7%)
 Employed and working part-time 142 (26.6%) 30 (25.4%)
 Self-employed 14 (2.6%) 8 (6.8%)
 Unemployed 105 (19.7%) 28 (23.7%)
 Retired 5 (0.9%) 0 (0%)
 Student 141 (26.5%) 37 (31.4%)
Education
 Less than High School 4 (0.7%) 1 (0.8%)
 High School/GED 219 (41%) 54 (45.8%)
 Apprenticeship, craft/trade or professional Certificate 16 (3%) 5 (4.2%)
 Associate degree in college (Occupational/Vocational) 14 (2.6%) 2 (1.7%)
 Associate degree in college (Academic) 107 (20%) 26 (22%)
 Bachelor’s degree (BA, AB, BS, etc.) 116 (21.7%) 19 (16.1%)
 Master’s degree (MA, MS, BS, MSW, MBA, etc.) 51 (9.6%) 11 (9.3%)
 Professional school degree (MD, DDS, JD, etc.) 1 (0.2%) 0 (0%)
 Doctorate (PhD, ED, etc.) 6 (1.1%) 0 (0%)
Income
 Less than $10, 000 107 (20.3%) 29 (24.8%)
 $10,000 to $14,999 60 (11.4%) 14 (12%)
 $15,000 to $24,999 80 (15.2%) 21 (17.9%)
 $25,000 to $34,999 76 (14.4%) 14 (12%)
 $35,000 to $49,999 76 (14.4%) 13 (11.1%)
 $50,000 to $74,999 72 (13.7%) 14 (12%)
 $75,000 to $99,999 32 (6.1%) 9 (7.7%)
 $100,000 to $149,999 19 (3.6%) 3 (2.6%)
 $150,000 to $199,999 5 (0.9%) 0 (0%)
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2.2. Measures.

Correlations, scale reliabilities, and descriptive statistics for all study measures are presented in Table 2. The internal consistencies of all measures were psychometrically adequate (e.g., Cronbach’s α > .60).

Table 2.

Descriptive statistics, reliabilities, and correlations

Variable M SD N α/r 2. 3. 4. 5. 6. α/r M SD N
1. CRP -- -- -- -- .03 .13 .16 .15 −.08 -- 2.23 2.74 118
2. PA 3.95 0.65 459 .86 -- −.33** −.07 .26** .06 .86 4.05 0.65 118
3. NA 1.62 0.56 455 .82 −.27** -- .37** −.07 −.24* .66 1.66 0.74 118
4. Racism 1.71 0.67 459 .87 −.03 .23** -- −.05 −.05 .88 1.66 0.69 117
5. Centrality 4.60 0.82 459 .76 .19** −.13** −.01 -- .04 .75 4.60 0.86 118
6. Intensity 3.01 0.72 459 .36a .16** −.09 −.01 .11* -- .38a 2.94 0.76 118
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Note. Descriptive statistics and correlations for the prescreen data appear below the diagonal, and those for participants retained after the prescreen appear above the diagonal. CRP: C-reactive protein. PA: Positive Affectivity. NA: Negative Affectivity. Centrality: Racial Centrality. Intensity: Religious Intensity.

a

The two items for religiosity were significantly correlated (p < .001).

**

p < .01

*

p < .05

2.2.1. Religious Intensity.

Religious intensity was measured using the 2-item religious intensity subscale of the Multidimensional Measure of Religiousness/Spirituality-Short Form (Fetzer Institute & National Institute on Aging Working Group, 1999). The religious intensity subscale measures the extent to which participants see themselves as religious and spiritual (“To what extent do you consider yourself a religious person?”; “To what extent do you consider yourself a spiritual person?”). Responses were rated from 1 (very) to 4 (not at all). The two responses were averaged and then reverse scored, such that higher scores indicated greater religious intensity.

2.2.2. Racial Centrality.

Racial centrality was measured using the 8-item centrality subscale of the Multdimensional Inventory of Black Identity (MIBI; Sellers et al., 1997). The centrality subscale measures the extent to which race is a core component of self-concept (e.g., “Being Black is an important reflection of who I am”). Responses were rated from 1 (strongly disagree) to 7 (strongly agree). After reverse-scoring three items, an overall score was calculated by averaging all subscale items, with higher scores indicating stronger racial identity.

2.2.3. Perceived Racism.

Perceived racism was measured using the Racism and Life Experiences Scale (Harrell, 1997). Participants responded to a question that asked, ‘Overall, how much do you think that interethnic group racism has had anything to do with problems you have had related to the following in your lifetime’ (Clark, 2006). Nine assessed domains include employment, law, finances, education, community, family/social relationships, emotional well-being, physical health, and public assistance. Responses were rated from 1 (less than 25% of the time) to 4 (between 75% and 100% of the time). An overall score was calculated by averaging all items, with higher scores indicating greater perceived racism.

2.2.4. Affectivity.

Affectivity was measured using the Positive and Negative Affect Scale–Expanded Form (PANAS-X; Watson & Clark, 1994). Participants indicated how often they generally experienced seven positively valenced (excited, enthusiastic, proud, strong, alert, attentive, and determined) and eight negatively valenced feelings (afraid, scared, nervous, jittery, hostile, irritable, guilty, and ashamed) on a scale from 1 (very slightly or not at all) to 5 (extremely). Separate positive and negative affectivity scores were calculated by averaging scale items, with higher scores indicating greater positive and negative affective tendencies.

2.2.5. CRP.

High sensitivity CRP was measured using dried bloodspot samples, which were collected using an established protocol (McDade, 2014). Finger pricks entailed wiping the middle finger of the participant’s non-dominant hand with an alcohol wipe, pricking the finger with a lancet, wiping away the first drop of blood, then collecting 3 to 5 blood spots dropped onto filter paper. The blood spot collection cards were allowed to dry before being stored at - 80 until they were shipped frozen by overnight delivery to the Center for Studies in Demography & Ecology (University of Washington), where assays were performed. A microtiter plate-based sandwich enzyme immunoassay was used to measure CRP in dried blood spot specimens. The assay, described in full elsewhere (Brindle et al., 2010), uses capture (clone C5 anti-CRP MAb, cat.no. M86005M) and detection (clone C6 anti-CRP MAb, cat.no. M86284M) antibodies purchased from Meridian Life Science, Inc. and calibrators purchased from Fitzgerald Industries International, Inc. (cat.no. 30-AC10). All specimens, calibrators and controls were assayed in duplicate. Within and between assay coefficients of variation, calculated using a variance components model for in-house dried blood spot quality control specimens run on every plate used for this study, were 6.5% and 5.3% respectively for the high (0.0089mg/L) control, 2.9% and 12.0% for the medium (0.0054mg/L) control, and 2.1% and 5.3% for the low (0.0034mg/L) control (n = 15 plates).

2.3. Statistical Analysis.

Available research suggests that extreme CRP levels likely indicate an acute infection or illness, which can conflate attempts to consider links between chronic CRP and other measures (Dhingra et al., 2007). To preserve statistical power and address this potential, CRP values > 10 mg/L were winsorized to represent scores between 0 and 10 while still maintaining relative rank. Three-step hierarchical multiple regressions were then performed to assess main and interactive effects of perceived racism, religious intensity, and racial centrality on affectivity and CRP. Significance was assessed using R-squared change and the regression weights of predictors newly entered at each step. Perceived racism, religious intensity, and racial centrality were mean centered and entered in the first step, where the main effect of each was assessed. Two-way interactions were entered and assessed at the second step and included interactions between perceived racism and religious intensity, perceived racism and racial centrality, and religious intensity and racial centrality. The hypothesized three-way interaction between perceived racism, religious intensity, and racial centrality was assessed on the third and final step. Significant three-way interactions were probed using PROCESS v2.16.3 Model 3 (Hayes, 2016). High and low values for simple slopes analyses corresponded to +1SD and −1SD from the mean respectively.

We also examined whether age, sex, exercise, education, or income confounded any effects on CRP. Only participant sex significantly predicted CRP (p = .005). Results did not substantially differ when controlling for these variables, either simultaneously or separately. The three-way interaction we describe in the results section continued to be significant between p = .01 and p = .04 when controlling for each of these variables separately and simultaneously. Moreover, none of these variables significantly interacted with perceived racism, racial centrality, or religious intensity to predict CRP. There was 17% missing data for self-reported participant height and weight, so we were unable to assess how body-mass index and weight might affect our results. However, CRP did not significantly between those who did and did not report their height and weight, t(116) = 1.31, p = .19.

4. Results

4.1. Positive and Negative Affectivity.

As seen in Table 3, there were significant main effects of religious intensity and racial centrality, with each predicting greater positive and less negative affectivity. There were no other main effects on positive affectivity and none of the predictors significantly interacted to predict positive affectivity. For negative affectivity, the main effects were qualified by a significant perceived racism × religious intensity × racial centrality three-way interaction. We probed this interaction separately for high and low perceived racism. As seen in Figure 1, when perceived racism was low, there were no effects of religious intensity or racial centrality, b = 0.04, p = .45, 95% CI of b [−0.06, 0.13]. When perceived racism was high, the racism × religious intensity interaction was significant, b = 0.19, p < .001, 95% CI of b [0.09, 0.30]. Among low racial centrality participants, religious intensity was associated with less negative affectivity, b = −0.16, p = .01, 95% CI of b [−0.28, −0.03]. Among high racial centrality participants however, religious intensity was associated with greater negative affectivity, b = 0.16, p = .02, 95% CI of b [0.02, 0.29]. Overall, negative affectivity was highest when racial centrality and religious intensity were both low. However, religious intensity was associated with greater rather than less negative affectivity among high racial centrality participants.

Table 3.

Regression results predicting outcomes from perceived racism, racial centrality, religious intensity, and interactions

b β t(df) 95%CI of b p ΔR2/sr2
Outcome: Positive Affectivity (n = 459)
  Step 1 <.001 .06
    Racism −0.02 −0.03 −0.56(455) [−0.11, 0.06] .58 .001
    Centrality 0.14 0.18 3.89(455) [0.07, 0.21] <.001 .03
    Intensity 0.13 0.14 3.09(455) [0.05, 0.21] .002 .02
  Step 2 .77 .002
    Intensity x Racism −0.05 −0.04 −0.80(452) [−0.16, 0.07] .43 .001
    Intensity x Centrality −0.01 −0.01 −0.17(452) [−0.10, 0.08] .87 <.001
    Centrality x Racism 0.04 0.04 0.81(452) [−0.06, 0.15] .42 .001
  Step 3 .42 .001
    Intensity x Centrality x Racism −0.05 −0.04 −0.81(451) [−0.17, 0.07] .42 .001
Outcome: Negative Affectivity (n = 455)
  Step 1 <.001 .08
    Racism .019 0.23 5.09(451) [0.12, 0.26] <.001 .05
    Centrality −0.08 −0.12 −2.71(451) [−0.15, −0.02] .01 .01
    Intensity −0.06 −0.08 −1.64(451) [−0.13, 0.01] .10 .01
  Step 2 .003 .03
    Intensity x Racism 0.05 0.04 0.96(448) [−0.05, 0.14] .34 .002
    Intensity x Centrality 0.11 0.13 2.90(448) [0.04, 0.18] .004 .02
    Centrality x Racism −0.12 −0.12 −2.58(448) [−0.21, −0.03] .01 .01
  Step 3 .03 .01
    Intensity x Centrality x Racism 0.12 0.10 2.24(447) [0.01, 0.22] .03 .01
Outcome: CRP (n = 117)
  Step 1 .11 .05
    Racism 0.64 0.17 1.81(113) [−0.06, 1.35] .07 .03
    Centrality 0.49 0.16 1.72(113) [−0.07, 1.06] .09 .02
    Intensity −0.14 −0.04 −0.41(113) [−0.78, 0.51] .68 .001
  Step 2 .45 .02
    Intensity x Racism −0.56 −0.12 −1.29(110) [−1.41, 0.30 .20 .01
    Intensity x Centrality −0.13 −0.04 −0.43(110) [−0.73, 0.47] .67 .002
    Centrality x Racism 0.42 0.09 1.00(110) [−0.41, 1.24] .32 .01
  Step 3 .03 .04
    Intensity x Centrality x Racism −0.88 −0.23 −2.24(109) [−1.65, −0.10] .03 .04
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Note. ΔR2 refers to the overall step, while sr2 refers to the specific predictors. CRP: C-reactive protein. Centrality: Racial

Centrality. Intensity: Religious Intensity.

Figure 1.

Figure 1.

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Moderator effects of perceived racism, religious intensity and racial centrality on negative affectivity and CRP. Centrality: Racial Centrality.

4.2. CRP

As seen in Table 3, there were no significant main effects or two-way interactive effects on CRP, although the positive association between perceived racism and CRP approached significance, as did the positive association between racial identity and CRP. Once again, there was a significant perceived racism × religious intensity × racial centrality three-way interaction. As seen in Figure 1, when perceived racism was low, there were again no links from religious intensity or racial centrality to CRP, b = 0.44, p = .26, 95% CI of b [−0.33, 1.22]. When perceived racism was high, the racism × religious intensity interaction was again significant, b = −0.75, p = .07, 95% CI of b [−1.55, 0.05]. Among low racial centrality participants, religious intensity was not associated with CRP, b = 0.14, p = .81, 95% CI of b [−0.99, 1.26]. Among high racial centrality participants, religious intensity was associated with lower CRP, b = −1.15, p = .04, 95% CI of b [−2.26, −0.05]. Overall, CRP was highest when racial centrality was high and religious intensity was low. CRP was low at all other levels of religious intensity and racial centrality.

5. Discussion

The current research evaluated main and moderating effects of perceived racism, religiosity, and racial identity on affectivity and CRP in a community sample of African Americans. We found that religious intensity and racial centrality, which reflect the strength of religiosity and racial identity respectively, were each associated with higher positive and lower negative affectivity. In addition, results for negative affectivity were qualified by a significant three-way interaction – when perceived racism was high, religious intensity was associated with less negative affectivity among low racial centrality African Americans, but greater negative affectivity among high racial centrality African Americans. Overall, negative affectivity was highest when religious intensity and racial centrality were both low. We also found a significant three-way interaction on CRP – when perceived racism was high, religious intensity was associated with lower CRP among high racial centrality African Americans, whereas CRP levels were low among low racial centrality African Americans regardless of religious intensity. Overall, CRP was highest among high racial centrality and low religious intensity African Americans. Taken together, the current findings add to the available literature on social determinants of CVD, stress buffering, and CVD among racial minorities.

For both positive and negative affectivity, we found main effects of religious intensity and racial centrality, supporting that each individual difference may provide protection that independently contributes to greater positive emotion, and less negative emotion. In the context of chronic stressors such as racism, protective constructs can indeed foster affective resilience and adaptive coping (Folkman & Moskowitz, 2000). Thus, associations of religiosity and racial identity with affectivity could indicate that emotional resilience in the face of chronic stressors, like racism, can emerge when psychological resources are adequate. Interestingly however, we found no links between perceived racism and positive affectivity, perhaps suggesting that healthful associations with religiosity and racial identity are unrelated to perceptions of racism.

Interactive results for negative affectivity and CRP support that religiosity and racial identity may indeed aid in protecting against perceived racism among African Americans. Among African Americans high in perceived racism, negative affectivity and CRP were not affected by racial centrality when religious intensity was high. These findings may indicate a general utility of religiosity for African Americans in protecting against harmful effects of perceived racism. Aspects of religiosity in the African American community have developed to directly oppose racism and oppression (Mattis & Jagers, 2001), and offer unique means for combatting the harmful effects of racism (Long, 1997). Thus, aspects of religiosity like religious intensity might be useful for protecting against perceived racism, irrespective of one’s racial identity.

Interestingly, interactive associations of racial centrality and religious intensity emerged only when perceived racism was high. Among African Americans high in perceived racism, CRP was highest, but negative affectivity was lowest when racial centrality was high and religious intensity was low. One potential explanation for this seemingly contradictory result is provided by the literature on repressive coping – an emotional coping style characterized by suppression rather than expression of negative feelings and emotion (Newton & Contrada, 1992; Weinberger et al., 1979). When perceived racism is high, high racial centrality African Americans – who may be especially attuned and vulnerable to deleterious consequences of racism – may opt to suppress negative emotion, especially when lacking additional protection provided by high religious intensity that might permit affective expression. We also found that among African Americans high in perceived racism, CRP was lowest, but negative affectivity was highest when both racial centrality and religious intensity were high, further suggesting that the protective benefits of religious intensity might permit expression rather than suppression of negative emotion. Moreover, among those who were low in both religious intensity and racial centrality, CRP was low negative affectivity was high, potentially because lacking a strong racial identity would make suppressing negative emotions in response to racism less crucial. Although more research is needed to consider repressive coping in this context, this pattern and interpretation is consistent with some available research that has shown emotional suppression is indeed associated with higher CRP (Appleton et al., 2013).

5.2. Limitations and Future Directions

Several limitations suggest both a cautious interpretation and future directions. First, this study only included African Americans. This group has a unique and long-lasting experience of injustice in the United States, and it is unclear whether our results would generalize to other racial minorities or marginalized groups, who possess their own unique cultural histories. Second, we focused on CRP as an indicator of cardiovascular health (Casas et al., 2008). Future research should examine whether our results are reflected by other indicators of CVD risk. This includes additional markers of inflammation, as well as risk factors for other conditions for which there are disparities between African Americans and other ethnic groups (e.g., diabetes; Centers for Disease Control and Prevention, 2005). Third, the present study is limited by a cross-sectional design. Although we provide a needed initial contribution in showing that individual differences in perceived racism, religiosity, and racial identity may be linked to CRP, future intervention or longitudinal studies will be needed to decipher whether these links are causal. It is also noteworthy that our observed effects on CRP were quite small. This is not particularly surprising, given that the majority of our sample included healthy young people and that the harmful effects of discrimination on CRP emerge over time (e.g., Sims et al., 2020). However, future research ought to examine the potential clinical significance of our findings on CVD risk. Another limitation is that we were unable to fully control for a number of known predictors of CRP (e.g., statin drug use and viral infections), most notably including BMI (Visser et al., 1999). Additional research will be needed to better incorporate this and other covarying factors. Finally, although we used a validated measure of religious intensity, there are alternative methods for conceptualizing religiosity. For example, some researchers have suggested that there might be advantages to examining spirituality as a distinct construct from religiosity (see King & Crowther, 2004). Moreover, we focused on the intensity of one’s religious beliefs, rather than the type of religious affiliation or another facet of religiosity (e.g., religious attendance, beliefs and values). Especially given that African American religious traditions are uniquely oriented toward opposing oppression (see Mattis & Jagers, 2001), these religious affiliations might be more adept at helping to cope with racism than others. Thus, future research could examine different conceptualizations of religiosity and specific religious affiliations.

Beyond limitations, our findings offer several additional avenues for future research on biological stress pathways. Notably, further investigation into the biological pathways between CRP and racism, religiosity, and racial identity is warranted. Similar to what has been suggested by Lewis and colleagues (2010), both dysregulation of the hypothalamic-pituitary-adrenal axis and low heart-rate variability might be pathways through which racism affects CRP, given their relation to elevated CRP in the context of acute and chronic stressors (Horsten et al., 1999; Miller et al., 2007). Moreover, it would be advantageous to examine these relationships over time, as evidenced by recent work on racism and CRP by Sims et al. (2020). Further examining these biological pathways might further elucidate how racism, religiosity, and racial identity mechanistically influence CVD.

5.3. Conclusions

African Americans experience the highest rates of CVD (American Heart Association, 2015) due in part due in part to deleterious health effects of racism (Krieger & Sidney, 1996; Pascoe & Smart Richman, 2009). In our study, focusing on CRP as a risk factor for CVD, we found that religious intensity and racial centrality independently and interactively buffer against the harmful effects of perceived racism on CRP in an African American sample. However, alongside findings on emotional suppression from Appleton and colleagues (2013), our results could suggest that high racial identity, in the absence of religiosity, might contribute to negative affect suppression and elevated CRP. In general, our findings suggest that supportive social identities might interactively protect against perceived racism, thereby reducing subsequent risk of CVD. Affiliating with groups that offer perspectives that directly oppose racism, like those offered by African American religious groups (Long, 1997; Mattis & Jagers, 2001), might be particularly helpful for preventing elevated CRP. Our results further indicate that such affiliation might be particularly important for those with high racial centrality, but who lack other supportive group affiliations: Without an additional protective social identity, those who are highly identified with their racial group might be particularly vulnerable to the effects of racism (see also McCoy & Major, 2003), potentially putting them at greater risk for CVD. This vulnerability is reflective of the “double-edged” nature of racial identity (Yip, 2018), whereby racial identity can provide both protection and vulnerability in the face of racism. Further research is needed to understand the extent to which such affiliations might prevent CVD, but our findings offer a promising avenue for considering how individual differences that protect against racism may be implicated in CVD disparities.

Ethical Approval.

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee (Wayne State University Institutional Review Board (B3), IRB#: 023417B3E) and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Acknowledgments

This research was supported by Award Number R21HL097191 from the National Heart, Lung, and Blood Institute awarded to the second author. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Heart, Lung, And Blood Institute or the National Institutes of Health. We thank Mercedes Hendrickson, Nathan Weidner, Lenwood Hayman, Edyta Debowska, Kaitlyn Simmonds, Kevin Wynne, Stefan Goetz, Rhiana Wegner, and the Clinical Research Center at Wayne State University for assistance with data collection. We also thank Eleanor Brindle and the Center for Studies in Demography & Ecology at the University of Washington for support with dried blood-spot collection.

Footnotes

The authors declare no conflicts of interest

Publisher's Disclaimer: This Author Accepted Manuscript is a PDF file of an unedited peer-reviewed manuscript that has been accepted for publication but has not been copyedited or corrected. The official version of record that is published in the journal is kept up to date and so may therefore differ from this version.

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