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. Author manuscript; available in PMC: 2025 Oct 1.
Published in final edited form as: J Racial Ethn Health Disparities. 2023 Aug 9;11(5):2756–2765. doi: 10.1007/s40615-023-01738-8

Self-Reported Racial Discrimination and Healthy Behaviors in Black Adults Residing in Rural Persistent Poverty Areas

Karen H Kim Yeary (1), Don E Willis (2), Han Yu (1), Beverly Johnson (2), Pearl Mcelfish (2)
PMCID: PMC11331421  NIHMSID: NIHMS2013950  PMID: 37555914

Abstract

Background:

Racism is a social determinant of health inequities and associated with poorer health and health behaviors. As a domain of racism, self-reported racial discrimination affects health through unhealthy behaviors (e.g. smoking) but the understudied impact of self-reported racial discrimination’s relationship with healthy behaviors (e.g. cancer screening) precludes a comprehensive understanding of racism’s impact on health inequities. Understanding how self-reported racial discrimination impacts healthy behaviors is even more important for those living in rural persistent poverty areas (poverty rates of 20% or more of a population since 1980), who have a higher disease burden due to poverty’s interaction with racism. The distinct sociocultural context of rural persistent poverty areas may result in differential responses to self-reported racial discrimination compared to those in non-persistent poverty areas.

Methods:

A community-engaged process was used to administer a survey to a convenience sample of 251 Black adults residing in 11 rural persistent poverty counties in the state of Arkansas. Self-reported racial discrimination, fruit and vegetable intake, colorectal cancer screening, cervical cancer screening, and screening mammography were assessed. Stress and religion/spirituality were also assessed as potential mediators or moderators in the relationship between self-reported racial discrimination and healthy behaviors.

Results:

In adjusted models, those reporting more self-reported racial discrimination had a higher probability of having had a test to check for cervical cancer (situation discrimination: OR=1.23, 95% CI: 1.04-1.5; frequency discrimination: OR=1.06, 95% CI: 1.02-1.12). Stress and religion/spirituality were not significant mediators/moderators.

Discussion:

Greater self-reported racial discrimination was associated with a higher odds of cervical cancer screening. Black adults residing in rural persistent poverty areas may have greater self-reported racial discrimination-specific coping and racial identity attitudes.

Keywords: Self-reported racial discrimination, health behaviors, poverty, cancer, diet

Background

In a racialized society, racial identities tell us something about the social classification of individuals. Race is not a biological construct reflecting innate differences; rather, it is a social construct that is a proxy for capturing the impacts of racism [1-3]. As a system of oppression that operates at the institutional, personally mediated, and internalized levels[1, 4, 5], racism is a social determinant of health inequities, with several reviews documenting racism’s association with poorer physical and mental health[4, 5].

Self-reported racial discrimination is a domain of racism that focuses on personally mediated racism, whereby racial minorities receive differential treatment and access to goods because of their race[4, 5]. Self-reported racial discrimination is believed to impact health through acting as a unique stressor that takes away the reserves needed to consistently practice healthy behaviors[4, 5]. Examples of self-reported racial discrimination include: not being approved for a mortgage loan based on race, appraisers devaluing a Black family’s home, etc. Several unhealthy behaviors (e.g. alcohol use, smoking, drug use) are established pathways through which self-reported racial discrimination affects health[4, 5]. However, the role of healthy behaviors—such as healthy dietary intake and cancer preventative behaviors—is not clear, leaving an incomplete understanding of the intersection between self-reported racial discrimination and health.

Self-reported racial discrimination, diet, and cancer preventative behaviors

The literature on self-reported racial discrimination’s relationship with diet has reported mixed results. One study reported that greater self-reported racial discrimination was associated with a less healthy diet (Est=1.372, SE=0.372) in Black adults[6]. Self-reported racial discrimination was also associated with greater percent energy intake from fat in a prospective study of Black adults with cardiovascular disease (Jackson Heart Study)[7]. The authors posited that among some Black populations, the chronic stress of self-reported racial discrimination may deplete the energy needed to self-regulate one’s eating[8, 9], resulting in the consumption of higher fat and sugary foods; studies have reported that in general, chronic stress is associated with a poorer diet[8, 10-12]. One study with Black adults reported no relationship between self-reported racial discrimination and fruit and vegetable intake[13]. However, self-reported racial discrimination was associated with increased fruit and vegetable intake in a sample of adolescent Black females[14]; the authors speculated that some Black people may respond to self-reported racial discrimination through working harder to better oneself, which could include consumption of a healthier diet[15, 16]. This is consistent with literature that the stress Black people feel from having to work twice as hard as others because of their race is associated with poorer health over time, with the strongest relationship among those with higher SES, i.e. high achievers[17, 18]. In addition, Black adults with optimism may respond to self-reported racial discrimination through practicing proactive coping over a sustained period of time. Eating a healthy diet could be considered a form of proactive coping that would enable Black adults to manage experiences of self-reported racial discrimination while simultaneously improving oneself[14].

A few studies have examined self-reported racial discrimination’s relationship with cancer screening among Black adults, also reporting mixed results. Among Black adults, self-reported racial discrimination was associated with lower colorectal cancer screening in a diverse sample from the California Health Interview Survey[19]; the authors speculated that self-reported racial discrimination experienced in medical settings may have deterred Black adults from getting screened. Similarly, another study reported a significant relationship between medical self-reported racial discrimination and lower mammography in Black women[19] (68.4% of Black women who did not report medical self-reported racial discrimination were screened compared to 49.3% who reported medical self-reported racial discrimination). However, self-reported racial discrimination was not associated with mammography in Black urban women (n=484)[20], or in a sample of diverse urban women in the context of a longitudinal cohort study (n=3258)[21]. Another study that examined Papanicolaou/Pap testing reported no relationship with self-reported racial discrimination in a diverse urban sample[21]. In contrast, one study in low-income Black women reported that self-reported racial discrimination was associated with an increased likelihood of receiving any type of cancer screening (colorectal cancer screening, mammography, pap test) (OR=2.56, CI=1.31-4.97)[22]; the authors speculated that Black women who live in more integrated neighborhoods (vs. segregated) may have greater opportunities to be racially discriminated against and thus be more comfortable going to racially diverse healthcare facilities. The authors also proposed that Black women residing in diverse communities may be more race conscious and subsequently more health conscious. In addition to residential segregation, self-reported racial discrimination’s association with cancer screening may depend on population density; among the studies described above, Black adults residing in urban areas reported null associations between self-reported racial discrimination and cancer screening, in contrast to Black adults residing in non-urban areas. The mixed results in the literature may also be due to the inconsistent use of self-reported racial discrimination measurements.

The potential moderating role of social support and religion/spirituality

Black individuals and other minorities may cope with self-reported racial discrimination through social support and religion/spirituality[23]. A New York City sample of diverse adults (n= 2335) reported that social support moderated the relationship between self-reported racial discrimination and mental health, although not between self-reported racial discrimination and physical health[24]. Social support moderated the association between self-reported ethnic discrimination and nicotine dependence, with self-reported ethnic discrimination being associated with greater nicotine dependence among men with low social support[25]. In a nationally representative sample of Black men, church-based emotional support moderated the association between self-reported racial discrimination and serious psychological distress, where with high levels of religion/spirituality, self-reported racial discrimination and serious psychological distress was correlated[26].

The need to examine the relationship between self-reported racial discrimination and health behaviors in rural, persistent poverty areas

Those in rural persistent poverty areas bear a disproportionate burden of disease[27]. Rural Black individuals, in particular, are more likely to live in persistent poverty[28] (poverty rates of at least 20% since 1980)[29] and experience poverty’s adverse effects, including poor educational attainment and fewer economic opportunities[30, 31]. Self-reported racial discrimination is a fundamental cause of adverse health outcomes in racial/ethnic minorities[5, 32], and in conjunction with poverty, have caused racial and regional inequities in health outcomes and behaviors[33-36]. Understanding how self-reported racial discrimination impacts healthy behaviors among those who bear a disproportionate burden of poor health outcomes is important to inform interventions in these populations, as the sociocultural context of behaviors need to be considered to effectively advance behavioral science[37]. The majority of studies in self-reported racial discrimination and health behaviors have focused on unhealthy behaviors in urban populations; fewer studies have examined self-reported racial discrimination’s relationship with healthy behaviors, particularly in rural populations.

Thus, utilizing a community-based sample of Black adults who reside in rural persistent poverty areas, we examined associations between self-reported racial discrimination and the following healthy behaviors: fruit and vegetable intake, colorectal cancer screening, cervical cancer screening, and screening mammography. We hypothesized that self-reported racial discrimination would be negatively associated with fruit and vegetable intake, colorectal cancer screening, cervical cancer screening, and screening mammography. We hypothesized that social support and religion/spirituality would moderate the relationship between self-reported racial discrimination and healthy behaviors. We also hypothesized that stress would mediate the relationship between self-reported racial discrimination and healthy behaviors.

Methods

Community-engaged process

Our team consisted of academic researchers and community leaders representing 12 rural[38] persistent poverty counties in the state of Arkansas. A community leader from each county was selected to form a 12-member Community Advisory Board. As a team, we constructed a survey to assess the health needs of Black adults and constructed a systematic plan for survey delivery, data collection, data analysis, and data dissemination.

Participants and Procedures

We took a convenience sample of Black adults residing in 11 rural[38] persistent poverty counties in the state of Arkansas (we did not sample all 12 counties because one county was predominately White with very few Black residents). Community health workers with extensive research training administered the survey to participants. Participant requirements to complete the survey included self-identifying as Black/African American, being age 18 and older, and residing in an Arkansas rural persistent poverty county. Participants were enrolled from May to June 2022 and received $20 for their study participation. A total of 251 participants were recruited. The study was approved by the University of Arkansas for Medical Sciences and Roswell Park Comprehensive Cancer Center’s Institutional Review Boards.

Assessment

Self-reported racial discrimination

was assessed through the 9-item Experiences of Discrimination (EOD) instrument[39]. The instrument conceptualizes exposure to self-reported racial discrimination as a combination of situation self-reported racial discrimination and frequency self-reported racial discrimination. Situation self-reported racial discrimination refers to the different situations in one’s day-to-day experience where self-reported racial discrimination is experienced, whereas frequency self-reported racial discrimination refers to the number of occurrences of self-reported racial discrimination across all situations. To assess situation self-reported racial discrimination, the EOD measure asks whether one had ever experienced discrimination because of their race, ethnicity, or color at different places or situations (i.e. at work; getting medical care; getting service in a store or restaurant; at school; getting hired or getting a job; getting housing; getting credit, bank loans, or a mortgage; on the street or in a public setting; from the police or in the courts), with response options ranging from ‘never’ to ‘4 or more times’. The total number of situations where self-reported racial discrimination was experienced were then added, with scores ranging from 0-9. The EOD assesses frequency self-reported racial discrimination through adding the total number of occurrences of self-reported racial discrimination across all nine situations and scores ranged from 0-45. The Cronbach’s alpha for the EOD is 0.74 or greater.

Mammography compliance

was assessed by asking participants when they had their last mammogram. Both the American Cancer Society (ACS) and UP Preventive Services Task Force (USPSTF) guidelines were used to ascertain whether participants were compliant [40].

Cervical cancer screening

was assessed by asking participants if they had a test to check for cervical cancer through either a pap smear, pap test, or HPV test. Response options were ‘yes’ and ‘no’[40].

Colorectal screening compliance

was assessed by asking participants if they had a blood stool test, sigmoidoscopy or colonoscopy. Those who indicated having the blood stool test within the past year were considered compliant. Those who indicated having a sigmoidoscopy within the last five years were considered compliant, and the those who indicated having a colonoscopy within the last ten years were considered compliant[40].

Fruit and vegetable intake

was measured using a modified version of the Behavioral Risk Factor Surveillance Survey (BRFSS) measure, which asks participants how many times a week they ate six different types of fruits and vegetables[41].

Social support

was assessed through the 19-item Medical Outcomes Study (MOS) Social Support survey[42], which asks how often different kinds of support were available (e.g. someone to help you if you were confined to bed, someone to have a good time with, someone whose advice you really want), with Likert-like response options ranging from ‘none of the time’ to ‘all of the time.’ The Cronbach alphas for the MOS are greater than 0.91.

Religion/spirituality

was assessed through two items, with one measuring religious attendance, and the other, private religious activity[43].

Perceived stress

was assessed with the 10-item Perceived Stress Scale[44]. Respondents were asked a series of questions regarding feeling upset or stressed and choose from one of 5 response options: never, almost never, sometimes, fairly often, and very often. Scores range from 0-40, with higher scores indicating higher perceived stress. Cronbach alphas for the scale are 0.84 or higher.

Demographic

variables assessed age, gender, total household income, insurance coverage, education, marital status, employment, and number of individuals residing in the household[40].

Statistical Analyses

Summary statistics were provided as frequencies/percentages for categorical variables and means/standard deviations for continuous variables. Logistic regression models were used to assess the association between exposure to self-reported racial discrimination and healthy behaviors, where the continuous response variables were dichotomized at median. For analyses involving colorectal cancer screening, only data from survey participants aged 45 or older were used. For analyses involving breast cancer screening compliance by ACS guidelines, only data from female participants ages 45 and older were used. For analyses involving breast cancer screening compliance by USPSTF guidelines, only data from female survey participants ages 50 and older were used. For analyses involving cervical cancer screening, only data from female survey participants ages 25 and older were used. Potential confounding variables, including age, gender, income, education, employment status, were included as covariates. For the calculation of derived scores (self-reported racial discrimination, fruit/vegetable intake, social support) for the regression analyses, the missing values of individual items were imputed with the sample means. To investigate the moderating effect of social support and religious activities on the relationship between self-reported racial discrimination and health behaviors, the interaction effects between the potential moderator and the self-reported racial discrimination measurements were tested in the regression models. The role of stress in mediating the effect of self-reported racial discrimination on health behaviors was investigated using Imai’s model-based causal analysis framework[45]. The point estimates for average causal mediation effect (ACME) and average direct effect (ADE) were examined and the variances were estimated by nonparametric bootstrap. All tests were two sided and p<0.05 was considered statistically significant. The statistical analyses were conducted using the statistical software R 4.2.0[46] and the “mediation” package[47].

Results

Descriptive Statistics

Table 1 reports the descriptive statistics of the sample, including the sample size that responded to each variable. For categorical variables, percentages were calculated based on the sample size that responded. The majority of the sample was female (63.7%) with a mean age of 55.1 years (SD=16.2). About half of the sample completed high school (48.4%), with about one third (32.71%) completing more than high school education, and the remaining completing less than high school education (18.9%). About one third were married or living as married (29.9%), a third were single (35.1%), and the remainder were divorced, widowed, or separated (35.1%). One third (31.3%) were employed, and nearly one third (28.0%) reported a household income of less than $15,000. A little over half (61.5%) had two or fewer persons in a household.

Table 1.

Sample Characteristics

Mean (SD)/% N
Demographics
Gender (female) 63.7% 248
Age 55.1 (16.2) 221
Highest education
  Less than 8 years 5.6% 248
  8 through 11 years 13.3%
  12 years or completed high school 48.4%
  Post high school training other than college (vocational or technical) 8.11%
  Some college 14.5%
  College graduate 7.3%
  Postgraduate 2.8%
Marital status
  Married 28.3% 251
  Living as married 1.6%
  Divorced 11.6%
  Widowed 17.1%
  Separated 6.4%
  Single, never been married 35.1%
Employment status
  Employed 31.3% 246
  Unemployed 17.1%
  Homemaker 4.9%
  Student 1.2%
  Retired 18.7%
  Disabled 26.4%
  Other 0.4%
Household income
  $10,000 to $14,999 28.0% 236
  $15,000 to $19,999 11.4%
  $20,000 to $34,999 11.9%
  $35,000 or more 21.6%
Number of people in household including self
  1 33.6% 244
  2 27.9%
  3 16.4%
  4 14.8%
  5 or more 7.4%
Health behaviors
Breast cancer screening compliant (ACS guidelines) (yes) 61.8% 102
Breast cancer screening compliant (USPSTF guidelines) (yes) 68.1% 94
Colorectal screening compliant 27.8% 158
Checked for cervical cancer (yes) 15.8% 133
Fruit and vegetables servings (per day) 2.4 (.8) 247
Psychosocial factors
Overall social support (1=low, 5=high) 3.6 (1.1) 208
Emotional/Informational support (1=low, 5=high) 3.6 (1.1) 229
Tangible support (1=low, 5=high) 3.6 (1.2) 245
Affectionate support (1=low, 5=high) 3.7 (1.1) 234
Positive social interaction (1=low, 5=high) 3.5 (1.2) 239
Perceived stress (0=low, 40=high) 18.3 (6.5) 230
Situation racial discrimination 4.0 (3.4) 251
Frequency racial discrimination 10.9 (12.3) 251
Religion
Religious attendance
  Never 17.9% 162
  Once a year or less 4.3%
  A few times a year 13.0%
  A few times a month 13.6%
  Once a week 40.7%
  More than once a week 10.5%
Private religious activities
  Rarely or Never 18.0% 161
  A few times a month 18.0%
  Once a week 15.5%
  Two or more times a week 6.8%
  Daily 31.1%
  More than once a day 10.6%

A total of 60%-70% of the participants that were eligible for screening were compliant with breast cancer screening guidelines, reporting slightly lower compliance to breast cancer screening guidelines compared to a national sample of Black women over 40 years old (71.1%)[48]. The disparity regarding those who were colorectal cancer screening compliant vs. not was even more marked, with only 27.8% of our screen eligible sample compliant with colorectal cancer screening guidelines, compared to 70.0% compliance among a national sample of screen eligible Black adults[49]. Similarly, a total of 15.8% of screen eligible respondents reported ever having a test to check for cervical cancer, compared to 74.8% of Black women nationally[50]. Fruit and vegetable servings averaged 2.4 servings per day, which are similar to national averages[51] [52].

Average social support was 3.6 (1.1) on a range from 1 (low) to 5 (high). Average emotional/informational support was also 3.6 (1.1), in addition to tangible support 3.6 (1.2). Average affectionate support was 3.7 (1.1), and average positive social interaction was 3.5 (1.2). The sample reported an average perceived stress of 18.3 (6.5) (or moderate stress), where the range was 0-40. The sample reported a total average of 4.0 (3.4) situations where self-reported racial discrimination was experienced, and a total average of 10.9 (12.3) occurrences of frequency self-reported racial discrimination. A little over half (51.2%) reported attending religious services once a week or more. A total of 41.7% reported practicing private religious activities daily or more.

Regression Analyses

Table 2 reports the regression analyses results. When regressing healthy behaviors against situation self-reported racial discrimination, compliance with breast cancer screening was statistically significant in the unadjusted model, with cervical cancer screening trending towards significance (p=.05). After controlling for age, income, education, and employment status, only cervical cancer screening remained significant, with situation discrimination associated with a higher odds of having been screened for cervical cancer (OR=1.23, 95% CI: 1.04-1.5).

Table 2.

Regression of Situation Racial Discrimination against Healthy Behaviors

Unadjusted OR Adjusted OR
Cervical cancer screening 1.15 (1.00, 1.34) 1.23 (1.04, 1.5)*
Compliant with breast cancer screening guidelines (ACS) 0.80 (0.68, 0.92)* 0.88 (0.74, 1.04)
Compliant with breast cancer screening guidelines (USPSTF) 0.80 (0.68, 0.92)* 0.91 (0.74, 1.11)
Compliant with colorectal cancer screening guidelines 0.94 (0.84, 1.05) 0.97 (0.85, 1.1)
Fruit and vegetable intake 0.98 (0.91, 1.06) 1.03 (0.94, 1.13)

Controlled for age, gender, income, education, and employment status

*

p<0.05

When regressing healthy behaviors against frequency discrimination, only breast cancer screening was significantly related to frequency discrimination in the unadjusted model. In the adjusted model, only cervical cancer screening remained significant, with frequency discrimination associated with a higher odds of having been screened for cervical cancer (OR=1.06, 95% CI: 1.02-1.01).

Moderation and Mediation Analyses

There were no significant moderation effects for social support or religion/spirituality. When testing stress as a mediator in relationships between self-reported racial discrimination and healthy behaviors, stress was not a mediator in any of the associations. Social support was also not a mediator in any of the associations.

Discussion

A substantial literature has established the relationships between self-reported racial discrimination and unhealthy behaviors (e.g. alcohol use, smoking, drug use)[4, 5]. However, fewer studies have examined the role of healthy behaviors (e.g. diet, cancer prevention behaviors), with the majority being conducted in urban settings. This study contributes to the scant literature on self-reported racial discrimination and healthy behaviors among Black adults residing in rural persistent poverty communities. This is also one of the few studies that have examined self-reported racial discrimination’s association with cervical cancer screening.

To our surprise, greater self-reported racial discrimination was associated with a higher odds of cervical cancer screening. This is consistent with significant results reported in a low-income, medically underserved longitudinal sample of Black women, whereby self-reported racial discrimination was associated with a higher odds of receiving any cancer screening (pap test, mammogram, colorectal) at follow-up[22]. In contrast, there was a lack of significant relationships between self-reported racial discrimination and cervical cancer screening in a diverse urban sample[21]. Rural impoverished regions may offer a unique context that affects racial discrimination’s relationship with cervical cancer screening in Black adults. Living in a rural impoverished community may strengthen Black community residents’ racial identity attitudes, which have been associated with positive psychosocial variables (e.g. internal locus of control) that could increase commitment to adhering to healthy behaviors, such as cervical cancer screening[53, 54]. Similarly, Black individuals who have a higher race consciousness may have a greater health consciousness, leading to the increased practice of self-protecting behaviors[55, 56]. The implications of this finding are unclear. If racial identity attitudes and higher race consciousness contributed to self-reported racial discrimination’s positive association with cervical cancer screening, future studies may consider building upon racial identity and race consciousness in cervical cancer interventions for Black adults residing in rural persistent poverty communities. Given the cross-sectional nature of this study and lack of national representativeness however, any statements regarding study implications are purely speculative.

If self-reported racial discrimination galvanized our participants’ efforts to practice healthy behaviors, it is not clear why there were no significant relationships between self-reported racial discrimination and other healthy behaviors (i.e., breast cancer screening, colorectal cancer screening, dietary intake). Our study’s null associations between self-reported racial discrimination and other positive health behaviors are in contrast to much of the current literature reporting significant associations between self-reported racial discrimination, cancer screening[19, 22], and diet[6, 7]. These prior studies utilized predominately urban samples; none exclusively focused on Black rural impoverished communities. Self-reported racial discrimination’s relationship with healthy behaviors other than cervical cancer screening may be significant in some urban areas only, and not in rural persistent poverty areas specifically. Institutional racism may also have a greater impact than personally mediated racism on some healthy behaviors and not others. For instance, there is more limited health care access in rural communities due to provider shortages in rural areas[57-60] and rural Black adults are more likely to live in persistent poverty and experience its adverse effects, including poor educational attainment and fewer economic opportunities[30, 31]. These disparities translate into rural racial and ethnic minorities being less likely to receive preventive care to practice healthy behaviors [61-64]. Thus, any associations between self-reported racial discrimination and healthy behaviors may be tangential compared to institutional racism’s impact. Our lack of results in other healthy behaviors other than cervical cancer screening may also be due to measurement differences and/or a lack of statistical power.

Also contrary to our hypothesis, social support and religion/spirituality were not moderators in the relationship between self-reported racial discrimination’s association with health behaviors, nor were social support and stress mediators in the relationship. Social support is a well-documented pathway for behavior change that can both facilitate and inhibit certain health behaviors[65, 66]. Given that our study assessed general social support and did not specify support specific to positive health behaviors, the lack of significant results may have been due to a mixture of opposite associations between social support and health behaviors that nullified each other. Religion/spirituality has also been linked to some positive health behaviors, including smoking, physical activity, and diet[67, 68]. However, there is not an evidence base for religion/spirituality’s association with cancer screening behavior[68]. Given that only cervical cancer screening was related to self-reported racial discrimination, religion/spirituality may have lacked a moderating effect because of the lack of a significant relationship with that particular health behavior. Religion/spirituality, particularly negative religious coping[69, 70] and negative social support[71, 72] have also been found to have deleterious associations with health; thus like social support, various aspects within religion/spirituality may have worked against each other, nullifying moderating effects.

Our measure of cervical cancer screening asked participants if they had been screened for cervical cancer and did not assess whether participants were compliant with cervical cancer screening guidelines. Only 15.8% reported ever having a test to check for cervical cancer, compared to 74.8% of Black women nationally reporting compliance with cervical cancer screening guidelines[50], which include regular pap smears or tests[50]. Likely, an even smaller percentage of our participants were compliant with cervical cancer screening guidelines. A similar pattern was seen in the sample’s compliance to colorectal cancer screening guidelines, where only 27.8% were compliant with colorectal cancer screening guidelines, compared to 70.0% compliance among a national sample of screen eligible Black adults[49]. Future studies may consider confirming and addressing these marked inequities in cervical cancer and colorectal cancer screening in rural persistent poverty communities.

Study limitations include the inability of our cross-sectional data to produce causal conclusions and potential measurement error inherent in self-reported data (e.g., recall bias, social desirability bias). Despite these limitations, this study contributes to the literature by examining self-reported racial discrimination’s relationship with healthy behaviors in a sample of Black residents in rural persistent poverty areas, and by examining self-reported racial discrimination’s association with cervical cancer screening, which has not been thoroughly examined in prior work. Future studies that examine self-reported racial discrimination’s relationship in larger samples over time, utilizing multiple measures of self-reported racial discrimination and more rigorous health behavior measures (e.g., 24-dietary recalls in measuring dietary intake) are needed to advance the field. Assessing self-reported racial discrimination’s impact on health behaviors in conjunction with measures of institutional and internalized racism would further illuminate the complex mechanisms through which racism impacts health.

Table 3.

Regression of Frequency Racial Discrimination against Healthy Behaviors

Unadjusted OR Adjusted OR
Cervical cancer screening 1.04 (1.00., 1.07) 1.06 (1.02. 1.12)*
Compliant with breast cancer screening guidelines (ACS) 0.96 (0.92, 0.99)* 0.96 (0.92, 1.01)
Compliant with breast cancer screening guidelines (USPSTF) 0.96 (0.93, 1.00)* 0.99 (0.95, 1.04)
Compliant with colorectal cancer screening guidelines 1.0 (0.97, 1.03) 1.00 (0.97, 1.03)
Fruit and vegetable intake 1.00 (0.98, 1.02) 1.01 (0.98, 1.03)

Controlled for age, gender, income, education, and employment status

*

p<0.05

Acknowledgements:

Funding was provided by Roswell Park Comprehensive Cancer Center Grant P30CA016056 from the National Cancer Institute, and NIH:NCI 3P30CA016056-44S2.

Footnotes

Competing Interests: The authors have no relevant financial or non-financial interests to disclose.

Ethics Approval: The study was approved by the University of Arkansas for Medical Sciences (UAMS) and Roswell Park Comprehensive Cancer Center IRBs.

Consent to Participate: Informed consent was obtained from all individual participants included in the study.

References

  • 1.Jones CP, Levels of racism: a theoretic framework and a gardener's tale. American Journal of Public Health, 2000. 90(8): p. 1212–5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Goodman AH, Why genes don't count (for racial differences in health). Am J Public Health, 2000. 90(11): p. 1699–702. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Graves JL Jr. and Goodman AH, Racism, Not Race: Answers to Frequently Asked Questions. 2021: Columbia University Press. [Google Scholar]
  • 4.Williams DR, et al. , Understanding how discrimination can affect health. Health Serv Res, 2019. 54 Suppl 2: p. 1374–1388. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Williams DR, Lawrence JA, and Davis BA, Racism and Health: Evidence and Needed Research. Annu Rev Public Health, 2019. 40: p. 105–125. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Forsyth JM, et al. , Perceived racial discrimination and adoption of health behaviors in hypertensive Black Americans: the CAATCH trial. J Health Care Poor Underserved, 2014. 25(1): p. 276–91. [DOI] [PubMed] [Google Scholar]
  • 7.Sims M, et al. , Perceived discrimination is associated with health behaviours among African-Americans in the Jackson Heart Study. J Epidemiol Community Health, 2016. 70(2): p. 187–94. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Jackson JS, Knight KM, and Rafferty JA, Race and unhealthy behaviors: chronic stress, the HPA axis, and physical and mental health disparities over the life course. Am J Public Health, 2010. 100(5): p. 933–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Brondolo E, et al. , Racism and hypertension: a review of the empirical evidence and implications for clinical practice. Am J Hypertens, 2011. 24(5): p. 518–29. [DOI] [PubMed] [Google Scholar]
  • 10.Mezuk B, et al. , Reconsidering the role of social disadvantage in physical and mental health: stressful life events, health behaviors, race, and depression. Am J Epidemiol, 2010. 172(11): p. 1238–49. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Oliver G and Wardle J, Perceived effects of stress on food choice. Physiol Behav, 1999. 66(3): p. 511–5. [DOI] [PubMed] [Google Scholar]
  • 12.Oliver G, Wardle J, and Gibson EL, Stress and food choice: a laboratory study. Psychosom Med, 2000. 62(6): p. 853–65. [DOI] [PubMed] [Google Scholar]
  • 13.Corral I and Landrine H, Racial discrimination and health-promoting vs damaging behaviors among African-American adults. J Health Psychol, 2012. 17(8): p. 1176–82. [DOI] [PubMed] [Google Scholar]
  • 14.Gibbons FX, et al. , Perceived racial discrimination and healthy behavior among African Americans. Health Psychol, 2021. 40(3): p. 155–165. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Sanders MG, Overcoming Obstacles: Academic Achievement as a Response to Racism and Discrimination. Journal of Negro Education, 1998. 66(1): p. 83–93. [Google Scholar]
  • 16.Lalonde R and Cameron JE, Behavioral responses to discrimination: A focus on action., in The Psychology of Prejudice: The Ontario Symposium Zanna M and Olson J, Editors. 1994, Lawrence Erlbaum Associates: New York. p. 257–288. [Google Scholar]
  • 17.DeAngelis RT, Striving While Black: Race and the Psychophysiology of Goal Pursuit. J Health Soc Behav, 2020. 61(1): p. 24–42. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Assari S, et al. , Subjective Socioeconomic Status Moderates the Association between Discrimination and Depression in African American Youth. Brain Sci, 2018. 8(4). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Crawley LM, Ahn DK, and Winkleby MA, Perceived medical discrimination and cancer screening behaviors of racial and ethnic minority adults. Cancer Epidemiol Biomarkers Prev, 2008. 17(8): p. 1937–44. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Dailey AB, et al. , Perceived racial discrimination and nonadherence to screening mammography guidelines: results from the race differences in the screening mammography process study. Am J Epidemiol, 2007. 165(11): p. 1287–95. [DOI] [PubMed] [Google Scholar]
  • 21.Jacobs EA, et al. , Perceived discrimination is associated with reduced breast and cervical cancer screening: the Study of Women's Health Across the Nation (SWAN). J Womens Health (Larchmt), 2014. 23(2): p. 138–45. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Ibekwe LN, et al. , Racism and Cancer Screening among Low-Income, African American Women: A Multilevel, Longitudinal Analysis of 2-1-1 Texas Callers. Int J Environ Res Public Health, 2021. 18(21). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Jacob G, et al. , A Systematic Review of Black People Coping With Racism: Approaches, Analysis, and Empowerment. Perspect Psychol Sci, 2022: p. 17456916221100509. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Bergeron G, et al. , Association between racial discrimination and health-related quality of life and the impact of social relationships. Qual Life Res, 2020. 29(10): p. 2793–2805. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Osman A, et al. , Ethnic Discrimination and Smoking-Related Outcomes among Former and Current Arab Male Smokers in Israel: The Buffering Effects of Social Support. J Immigr Minor Health, 2018. 20(5): p. 1094–1102. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Nguyen AW, et al. , Discrimination, Serious Psychological Distress, and Church-Based Emotional Support Among African American Men Across the Life Span. J Gerontol B Psychol Sci Soc Sci, 2018. 73(2): p. 198–207. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Beech BM, et al. , Poverty, Racism, and the Public Health Crisis in America. Front Public Health, 2021. 9: p. 699049. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Harris RP and Worthen D, African Americans in Rural America. Challenges for rural America in the twenty-first century, 2003: p. 32–42. [Google Scholar]
  • 29.Service, U.S.D.o.A.E.R., Rural Poverty and Well-Being: Geography of Poverty. 2013-2014. [Google Scholar]
  • 30.Fitchen JM, On the Edge of Homelessness: Rural Poverty and Housing Insecurity. Rural Sociology 1992. 57: p. 173–193. [Google Scholar]
  • 31.Kusmin L, Rural America at a glance. USDA-ERS Economic Brief, 2012. [Google Scholar]
  • 32.Phelan JC and Link BG, Is racism a fundamental cause of inequalities in health? Annual Review of Sociology, 2015. 41(1): p. 311–330. [Google Scholar]
  • 33.Mays VM, Cochran SD, and Barnes NW, Race, race-based discrimination, and health outcomes among African Americans. Annu Rev Psychol, 2007. 58: p. 201–25. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Torpy JM, Lynm C, and Glass RM, JAMA patient page. Poverty and health. Jama, 2007. 298(16): p. 1968. [DOI] [PubMed] [Google Scholar]
  • 35.Mansfield C and Novick LF, Poverty and Health. NC Med J, 2012. 73: p. 366–373. [PubMed] [Google Scholar]
  • 36.Hales CM, et al. , Trends in Obesity and Severe Obesity Prevalence in US Youth and Adults by Sex and Age, 2007-2008 to 2015-2016. Jama, 2018. 319(16): p. 1723–1725. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Klein WMP, et al. , Behavioral Research in Cancer Prevention and Control: Emerging Challenges and Opportunities. J Natl Cancer Inst, 2022. 114(2): p. 179–186. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Bureau, U.S.C., Urban and Rural. https://data.census.gov/cedsci/table?q=rural&tid=DECENNIALCD1132010.H2&hidePreview=true, 2010. Accessed May 10, 2021.
  • 39.Krieger N, et al. , Experiences of discrimination: validity and reliability of a self-report measure for population health research on racism and health. Soc Sci Med, 2005. 61(7): p. 1576–96. [DOI] [PubMed] [Google Scholar]
  • 40.Gage-Bouchard EA and Rawl SM, Standardizing Measurement of Social and Behavioral Dimensions of Cancer Prevention and Control to Enhance Outreach and Engagement in NCI-Designated Cancer Centers. Cancer Epidemiol Biomarkers Prev, 2019. 28(3): p. 431–434. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.(CDC), C.f.D.C.a.P., Behavioral Risk Factor Surveillance System Survey Questionnaire. U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, 2021( Atlanta, Georgia: ). [Google Scholar]
  • 42.Sherbourne CD and Stewart AL, The MOS social support survey. Soc Sci Med, 1991. 32(6): p. 705–14. [DOI] [PubMed] [Google Scholar]
  • 43.Koenig H, Parkerson GR Jr., and Meador KG, Religion index for psychiatric research. Am J Psychiatry, 1997. 154(6): p. 885–6. [DOI] [PubMed] [Google Scholar]
  • 44.Cohen S, Kamarck T, and Mermelstein R, A global measure of perceived stress. Journal of Health and Social Behavior, 1983. 24(4): p. 385–96. [PubMed] [Google Scholar]
  • 45.Imai K, Keele L, and Tingley D, A general approach to causal mediation analysis. Psychol Methods, 2010. 15(4): p. 309–34. [DOI] [PubMed] [Google Scholar]
  • 46.URL RCTR, R: A language and environment for statistical computing. Foundation for Statistical Computing, Vienna, Austria, 2022. https://www.R-project.org/. [Google Scholar]
  • 47.T. D, et al. , mediation: R Package for Causal Mediation Analysis. Journal of Statistical Software, 2014. 59(5): p. 1–38.26917999 [Google Scholar]
  • 48.Control, C.f.D., Table CanBrTest. Use of mammography among women aged 40 and over, by selected characteristics: United States, selected years 1987–2019. 2019. [Google Scholar]
  • 49.Joseph DA, et al. , Vital Signs: Colorectal Cancer Screening Test Use — United States, 2018. MMWR Morb Mortal Wkly Rep, 2020. 69: p. 253–259. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50.Institute NC, Cervical Cancer Screening. Cancer Trends Progress Report, 2019. https://progressreport.cancer.gov/detection/cervical_cancer. [Google Scholar]
  • 51.Stewart H and Hyman J, Americans Still Can Meet Fruit and Vegetable Dietary Guidelines for $2.10-$2.60 per Day. United States Department of Agriculture, 2019: p. https://www.ers.usda.gov/amber-waves/2019/june/americans-still-can-meet-fruit-and-vegetable-dietary-guidelines-for-210-260-per-day/#:~:text=USDA%20food%20consumption%20surveys%20find,addition%20to%20Federal%20dietary%20recommendations. [Google Scholar]
  • 52.Prevention, C.f.D.C.a., Get the Facts: Sugar-Sweetened Beverages and Consumption. 2022: p. https://www.cdc.gov/nutrition/data-statistics/sugar-sweetened-beverages-intake.html.
  • 53.Martin JK and Hall GC, Thinking Black, thinking internal, thinking feminist. Journal of Counseling Pscyhology, 1992. 39(4): p. 509–514. [Google Scholar]
  • 54.Mahalik JR, Pierre MR, and Wan SSC, Examining racial identity and masculinity as correlates of self-esteem and psychological distress in Black men. J Multicult Couns Devel, 2006. 34(2): p. 94–104. [Google Scholar]
  • 55.Bediako SM, Kwate NO, and Rucker R, Dietary behavior among African Americans: assessing cultural identity and health consciousness. Ethn Dis, 2004. 14(4): p. 527–32. [PubMed] [Google Scholar]
  • 56.Nevarez L, et al. , Race/Ethnic Variations in Predictors of Health Consciousness Within the Cancer Prevention Context. Am J Health Promot, 2020. 34(7): p. 740–746. [DOI] [PubMed] [Google Scholar]
  • 57.Tucker-Seeley RD, Social Determinants of Health and Disparities in Cancer Care for Black People in the United States. JCO Oncol Pract, 2021. 17(5): p. 261–263. [DOI] [PubMed] [Google Scholar]
  • 58.Alcaraz KI, et al. , Understanding and addressing social determinants to advance cancer health equity in the United States: A blueprint for practice, research, and policy. CA Cancer J Clin, 2020. 70(1): p. 31–46. [DOI] [PubMed] [Google Scholar]
  • 59.Zahnd WE, et al. , The Intersection of Rural Residence and Minority Race/Ethnicity in Cancer Disparities in the United States. Int J Environ Res Public Health, 2021. 18(4). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 60.Zahnd WE, McLafferty SL, and Eberth JM, Multilevel analysis in rural cancer control: A conceptual framework and methodological implications. Prev Med, 2019. 129S: p. 105835. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 61.Eberth JM, et al. , Mortality-to-incidence ratios by US Congressional District: Implications for epidemiologic, dissemination and implementation research, and public health policy. Prev Med, 2019. 129S: p. 105849. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 62.Department, A.H., BRFSS County Estimates. https://www.healthy.arkansas.gov/programs-services/topics/brfss-county-estimates, 2019: p. Retrieved April 29, 2022.
  • 63.Safi H, Vaccination Rate per County for Children Aged 11-14 Years with 2 or More HPV Vaccine, Arkansas 2022. Arkansas Department of Health, 2022. https://www.immunizear.org/arkansas-immunization-rate-reportca. [Google Scholar]
  • 64.National Cancer Institute, C.f.D.C., State Cancer Profiles. Arkansas, 2019-2020. https://statecancerprofiles.cancer.gov/quick-profiles/index.php?statename=arkansas#t=1(Accessed May 2, 2022). [Google Scholar]
  • 65.Harvey IS and Alexander K, Perceived social support and preventive health behavioral outcomes among older women. J Cross Cult Gerontol, 2012. 27(3): p. 275–90. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 66.Vaccaro JA, Gaillard TR, and Marsilli RL, Review and Implications of Intergenerational Communication and Social Support in Chronic Disease Care and Participation in Health Research of Low-Income, Minority Older Adults in the United States. Front Public Health, 2021. 9: p. 769731. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 67.Koenig HG, King DE, and Carson VBVB, Handbook of Religion and Health. 2nd ed. 2012, New York, NY, USA: Oxford University Press. [Google Scholar]
  • 68.Koenig HG, Religion, spirituality, and health: the research and clinical implications. ISRN Psychiatry, 2012. 2012: p. 278730. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 69.Pargament KI, Koenig HG, and Perez LM, The many methods of religious coping: development and initial validation of the RCOPE. J Clin Psychol, 2000. 56(4): p. 519–43. [DOI] [PubMed] [Google Scholar]
  • 70.Pargament KI, Ano GG, and Wachholtz AB, The Religious Dimension of Coping: Advances in Theory, Research, and Practice, in Handbook of the psychology of religion and spirituality. 2005, Guilford Press: New York, NY, US. p. 479–495. [Google Scholar]
  • 71.Fiala WE, Bjorck JP, and Gorsuch R, The Religious Support Scale: construction, validation, and cross-validation. Am J Community Psychol, 2002. 30(6): p. 761–86. [DOI] [PubMed] [Google Scholar]
  • 72.Taylor RJ, et al. , Church-Based Emotional Support and Negative Interactions Among Older African Americans and Black Caribbeans. J Gerontol B Psychol Sci Soc Sci, 2022. 77(11): p. 2006–2015. [DOI] [PMC free article] [PubMed] [Google Scholar]

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