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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Am J Mens Health. Author manuscript; available in PMC Aug 1, 2013.
Published in final edited form as:
PMCID: PMC3632259
NIHMSID: NIHMS451985

Association between Race, Place, and Preventive Health Screenings among Men: Findings from the Exploring Health Disparities in Integrated Communities Study

Abstract

African American men consistently report poorer health and have lower participation rates in preventive screening tests than white men. This finding is generally attributed to race differences in access to care which may be a consequence of the different healthcare markets in which African American and white men typically live. This proposition is tested by assessing race differences in use of preventive screenings among African American and white men residing within the same healthcare marketplace. Logistic regression was used to examine the association between race and physical, dental, eye and foot examinations, blood pressure and cholesterol checks, and colon and prostate cancer screenings in men in the Exploring Health Disparities in Integrated Communities in Southwest Baltimore Study. After adjusting for covariates, African American men had greater odds of having had a physical, dental, and eye examination; having had their blood pressure and cholesterol checked; and having been screened for colon and prostate cancer than white men. No race differences in having a foot examination were observed. Contrary to most findings, African American men had a higher participation rate in preventive screenings than white men. This underscores the importance of accounting for social context in public health campaigns targeting preventive screenings in men.

Keywords: Men’s health, disparities, race, segregation, integration, preventive screenings, social determinants of health

INTRODUCTION

Over the last two decades there has been a growing interest in men’s health. Despite advances in diagnosis, detection and treatment of multiple chronic diseases, African American men continue to exhibit a worse health profile and experience more excess mortality and preventable morbidity than white men (Arias, 2006; Griffith, In press; LaVeist, Bowie, & Cooley-Quille, 2000; Plowden & Young, 2003; Rich, 2000; Williams, 2003; Williams & Collins, 1995). Moreover, African American men are less likely than white men to see a doctor when in poor health even after accounting for insurance status, and availability of, and access to, medical resources/services (Committee on Understanding and Eliminating Racial and Ethnic Disparities in Health Care, 2002; Williams, 2003). Previous findings suggest that change in health-promoting (or positive health) behaviors, such as preventive health screenings, may reduce disparities in men’s health (Blanchard & Lurie, 2005; Courtenay, 2000; Griffith, In press; Williams, 2003).

Preventive screening tests are the first step to successful treatment and/or management of many chronic diseases; however, national data consistently find that African American men tend to engage in fewer health-promoting practices and behaviors and consequently have a higher rate of morbidity and mortality than white men (Keppel, 2007). While racial disparities in preventive health services have been widely documented, explanations for observed race differences remain incomplete (Fiscella, Holt, 2007; Holmes, Arispe, & Moy, 2005).

There are two major problems associated with understanding racial differences in preventive health screenings in the U.S. First, since participation in health screenings among men vary by both race and socioeconomic status (SES) (Pampel, Krueger, & Denney, 2010), and African American men are more likely to have lower SES than white men, SES is a source of confounding when examining racial disparities in preventive health screenings. Moreover, race and SES are very much intertwined, thus it is difficult to determine how race and SES operate to produce racial disparities in preventive screenings in men.

Second, racial segregation facilitates the production and propagation of health disparities that may expose individuals to different levels of health promoting behaviors and resources (LaVeist, 2005; Williams & Collins, 2001). Because the US is highly racially segregated, African Americans and whites typically live in separate communities where they have different health risk exposures and availability of healthcare resources (LaVeist et al. 2008, Gaskins et al 2009; Bowie et al 2009). For instance, racial segregation has been associated with health outcomes (Cooper, 2001; Fang, Madhavan, Bosworth, & Alderman, 1998; Acevedo-Garcia 2000) and inequalities in environmental factors that determine health care access and use (Gaskin, Price, Brandon, & LaVeist, 2009). Also, racial segregation has been found to be associated with neighborhood attributes such as high crime (Lee, 2000), poor housing conditions (Black & Macinko, 2008), and decreased availability of healthy foods like fresh fruits and vegetables (Moore & Diez Roux, 2006; Powell, Slater, Chaloupka, & Harper, 2006). This differential exposure to neighborhood stressors can shape health behaviors including preventive screening practices. For example, social environments with fewer healthy food choices, parks, sidewalks, recreational spaces, medical facilities and limited health awareness messages may negatively influence the adoption of health promoting behaviors such as physical activity, nutrition, and preventive health screenings. More recently, accounting for social context in health disparities research has demonstrated substantial reduction or lack of race differences in health outcomes such as hypertension, obesity, health services use, and diabetes in a racially integrated community without race differences in income (Bleich, Thorpe, Sharif-Harris, Fesahazion, & LaVeist, 2009; Gaskin, Price, Brandon, & LaVeist, 2009; LaVeist et al., 2008; LaVeist, Thorpe, Galarraga, Bower, & Gary-Webb, 2009; Thorpe, Brandon, & LaVeist, 2008). This evidence suggests that social context is an important, yet understudied, correlate of health that may limit the ability of national survey data to produce truly similar groups appropriate for comparisons (LaVeist, Thorpe, Mance, & Jackson, 2007; LaVeist et al., 2009; Williams & Collins, 2001).

Most studies (Collins CA & Williams, 1999; Fang, Madhavan, Bosworth, & Alderman, 1998; LaVeist, 1989; LaVeist, 1993) of race and preventive health screenings have attempted to account for confounding of race and SES factors by adjusting for individual-level measures such as education, family or individual income. However, this approach is inadequate to account for the different environments in which whites and African Americans live, because there remains unmeasured heterogeneity associated with extreme differences in the historical and social contexts of various race groups in the United States (LaVeist et al., 2007). Failing to account for racial segregation may lead to a spurious conclusion that race, rather than social environment, may be responsible for the association.

Data sources available to disentangle race, SES, and segregation simultaneously are rare. The purpose of this study was to examine race disparities across a variety of preventive health screenings within a sample of white and African American men living in the same social context with similar healthcare resources.

METHODS

Study Population

Exploring Health Disparities in Integrated Communities (EHDIC) is an ongoing multi-site study of race disparities within communities where African Americans and whites live together and where there are no race differences in socioeconomic status (SES), as measured by median income. This analysis is based on data from the first EHDIC study site in Southwest Baltimore, Maryland (EHDIC-SWB), a low-income urban area.

EHDIC-SWB was a cross-sectional face-to-face survey of the adult population (aged 18 and older) of two contiguous census tracts collected between June and September 2003. In addition to being economically homogenous, the study site was also racially balanced and well integrated, with almost equal proportions of African American and white residents. In the two census tracts, the racial distribution was 51% African American and 44% white, and the median income for the study area was $24,002 and did not differ by race. The census tracts were block listed to identify every occupied dwelling in the study area. During block listing, 2,618 structures were identified. Of those, 1636 structures were determined to be occupied residential housing units (excluding commercial and vacant residential structures). Up to five attempts were made to contact an eligible adult in 1244 occupied residential housing units. A total of 65.8% of the occupied housing units were enrolled in the study. This resulted in 1489 study participants (41.9% of the 3555 adults living in these two census tracts recorded in the 2000 Census). Because our survey had similar coverage across each census block group included the study area, the bias to geographic locale and its relationship with SES should be minimal (LaVeist et al., 2009).

Comparisons to the 2000 Census for the study area indicated that the EHDIC-SWB sample included a higher proportion of African Americans and women, but was otherwise similar on other demographic and socioeconomic indicators (LaVeist et al., 2009). Specifically, our sample was 59.3% African American and 44.4% male, whereas the 2000 Census data showed the population was 51% African American and 49.7% male. Age distributions in our sample and 2000 Census data were similar with a median age range of 35–44 years for both samples. The lack of race difference in median income in the census, $23,500 (African American) vs. $24,100 (white) was replicated in EHDIC $23,400 (African American) vs. $24,900 (white).

The survey was administered in person by a trained interviewer and consisted of a structured questionnaire, which included demographic and socioeconomic information, self-reported height and weight, self-reported health behaviors and chronic conditions, and three blood pressure (BP) measurements. The EHDIC study has been described in greater detail elsewhere (LaVeist et al., 2009). The study was approved by the Committee on Human Research at the Johns Hopkins Bloomberg School of Public Health. These analyses are based on the 628 African American and white men in the EHDIC-SWB sample.

Measures

Outcomes measures included eight preventive health screenings reported by men in the last two years: physical, dental, eye, and foot examination, blood pressure and cholesterol checks, and colon and prostate cancer screenings. A binary variable was created for each screening test to indicate whether the men had a particular preventive service within the last two years. Race was based on participant self-identification as African American or white. Demographic variables included age (years), education level (1=high school graduate/GED; 0=less than high school graduate), and income category (<$10,000, $10,000–19,999, $20,000–34,999, $35,000–54,999, ≥$55,000).

Health-related characteristics included: health insurance (1=yes; 0=no), physical inactivity (1=yes; 0=no), regular doctor (1=yes; 0=no), smoking and drinking status (0=never; 1=former; 2=current), obesity, and any chronic condition. Using self-reported height and weight, body mass index (BMI) was calculated by dividing weight in kilograms by height in meters squared (kg/m2). Men whose BMI ≥ 30 kg/m2 were considered obese (1=yes; 0=no). Men reported whether they received a physician diagnosis of: diabetes, heart attack, hypertension, or a stroke. A variable labeled “any chronic condition” was constructed to classify men who reported having at least one of the aforementioned health conditions.

Statistical Analyses

The Student’s t and Chi-square tests were used to assess the mean and proportional differences between African American and white men for demographic and health-related factors by race. Age adjusted proportions were calculated by specifying a generalized linear model with the logit link and binomial distribution that included each health-related factor or preventive screening behavior as a function of race and age. Logistic regression models were specified to examine the association between race and each preventive health screening outcome adjusting for demographic and health characteristics described above. P-values < 0.05 were considered statistically significant and all tests were two-sided. Analyses were conducted using SAS, version 9.1.3, software.

RESULTS

The distribution of demographic variables of male participants in EHDIC-SWB by race is presented in Table 1. Of the 628 men, African Americans (60.6%) were on average four years younger and less likely to be married compared to whites. Although African American men were more likely to be a high school graduate relative to white men, there was no difference in income level between the groups of men.

Table 1
Distribution of Select Characteristics of the Men in EHDIC-SWB by Race

The age-adjusted proportions for health characteristics and preventive health screenings of the men in EHDIC-SWB are displayed in Table 2. African American men were more likely to have insurance and to be a former or never smoker than white men. There was no difference between African American and white men with respect to having a regular doctor, being physically inactive, being a current smoker, being a never, former or current drinker, being obese, or having any chronic condition. With the exception of having a foot examination, African American men were more likely than white men to participate in physical, dental, and eye examinations, blood pressure and cholesterol checks, and colon and prostate cancer screenings.

Table 2
Age-Adjusted Distribution of Health-Related Factors And Preventive Health Screenings Among Men in EHDIC-SWB by Race

The association between race and each preventive health screening outcome is presented in Table 3. Adjusting for age, marital status, education, income, insurance, having a regular doctor, physical inactivity, smoking and drinking status, obesity and any chronic condition, African American men had greater odds of having had a physical (odds ratio [OR] =1.99, 95% confidence interval [CI] 1.33, 2.98), dental (OR =1.57, 95% CI 1.09, 2.26), and eye examination (OR =1.60, 95% CI 1.11, 2.31) within the last two years than white men. African American men had similar odds of having had a foot examination in the last two years compared to white men. With respect to cardiovascular screening tests, African American men had greater odds of having had their blood pressure (OR =2.52, 95% CI 1.51, 4.21), and cholesterol checked (OR =2.13, 95% CI 1.47, 3.08) relative to white men. Regarding cancer screenings, African American men had nearly twice the odds of having been screened for colon (OR =1.86, 95% CI 1.26, 2.74) and prostate cancer (OR =1.75, 95% CI 1.19, 2.56) than white men.

Table 3
Association between Race and Preventive Health Screenings among Men in EHDIC-SWB

Discussion

This study addressed race differences in preventive health screenings among African American and white men living in the same social environment who therefore can access the same healthcare facilities. Findings indicate that African American men had greater odds of participating in physical, dental, and eye examinations, blood pressure and cholesterol checks, and colon and prostate screenings within the last two years compared to white men. There was no race difference in men participating in foot examinations. These findings underscore the importance of understanding and ameliorating the social and structural inequalities that vary between African American and white men (Blankenship, Bray, & Merson, 2000; Committee on Understanding and Eliminating Racial and Ethnic Disparities in Health Care, 2002; Williams, 2003) because it is these race differences that accelerate the manifestation of poor health in all men.

Previous national data has yield mixed results regarding whether blacks have higher or similar rates of utilization of preventive health services compared to whites (Bolen, Rhodes, Powell-Griner, Bland, & Holtzman, 2000; Centers for Disease Control and Prevention (CDC), 1999; Martin, Parker, Wingo, & Heath, 1996; Ross, Berkowitz, & Ekwume, 2008). However, national data appears to be suboptimal in conducting some research in race disparities (LaVeist et al 2011). National samples do not account for the effects of racial segregation, which places people of different race groups in very different health risk environments (Morello-Frosch & Lopez 2006). As a result some race disparities research using national samples may over estimate race differences and under estimate the consequences of segregation (LaVeist et al. 2011). Much of the work examining race differences in preventive health screenings has focused on cancer screenings or adult immunization (Alexander & Brawley, 1998; Palmer & Schneider, 2005), and did not account for segregation. The work presented herein extends to other health screenings and found that African American males report higher rates for all of the preventive screenings included in this analysis except for foot examinations. This work also makes comparisons between white and African American men living in the same social context with similar access and availability to health services. Perhaps when it is possible to design comparisons of similarly situated white and African American men, African American men may be more vigilant in seeking preventive health care. However, additional work (including a mixed methods approach) is needed to further understand the utilization of preventive health screenings of African American men particularly in integrated settings.

It is also plausible that healthcare providers practicing in low income urban communities may be more vigilant in recommending preventive screening among African American men due to increased awareness of health disparities and earlier disease onset. (Murray et al., 2006; National Center for Health Statistics, 2011). This may also be the result of health education campaigns designed to make African Americans aware of the well-documented health risks resulting from undetected health conditions in African American men.

African American males in our study were more likely to be high school graduates than white males, and educational attainment has been found to be associated with greater uptake of preventive screenings even after controlling for income (Culter & Lleras-Muney, 2010). In analysis of the EHDIC-SWB data (not presented), education was associated with eye, dental, and physical examinations as well as prostate cancer screening. Another key variable that might influence preventive screenings is marital status. However, race differences in education and marital status are unlikely explanations of these findings as the odds ratios presented in Table 3 adjust for both variables.

In the United States, segregation and race are strongly linked together and greatly influence health status, behaviors, and screenings (LaVeist, 2005; Williams, 2003; Williams & Collins, 1995; Williams & Collins, 2001). Given high levels of residential segregation, examining the influence of social environment on uptake of preventive screenings is an important contribution of this study, because it is a factor that is not accounted for in most national samples (LaVeist et al., 2007; Williams & Collins, 2001). Using the same data from this study, Bowie and colleagues found that whites in the EHDIC-SWB study reported lower rates of several health behaviors and cancer screenings compared to a nationally representative sample of low-income whites (Bowie et al., 2009). Residential segregation concentrates, as in this case, poor African American and poor white men in areas where there may be less access to health care facilities or resources (Gaskin et al., 2009; Williams & Collins, 2001). Previous work on racial residential segregation have found that approximately 60% of African Americans would need to move to another census tract to achieve complete integration between African Americans and non-Hispanic white Americans (Iceland, Weinberg, Steinmetz, & United States Bureau of the Census, 2002). The fact that African American and white men most often live in vastly different social environments facilitates differences in the quality of care they can access or have available to them (Gaskin et al., 2009; Landrine & Corral, 2009; Williams & Collins, 2001).

The interpretation of these results should be considered in the following context. The external validity of our results may be limited because EHDIC-SWB was conducted in a low-income urban population. Results may differ in a higher SES group or in non-urban environments. Our analyses only included African American and white men, and are not generalizable to men in other racial and ethnic groups. Furthermore, preventive screenings were based on self-report and there is the possibility of differential reporting by race (Fiscella, Holt, Meldrum, & Franks, 2006); however, studies that have validated self-report of preventive health utilization with administrative claims or other gold standards have found that males and healthier individuals tend to report their health care utilization more accurately (Newell, Girgis, Sanson-Fisher, & Savolainen, 1999; Short et al., 2009).

Despite these limitations, this study contributes to our understanding of race disparities in preventive screenings by using a study design that minimizes the confounding of race, and SES, with residential segregation that is present in national data. The EHDIC study represents a new direction in health disparities research, one which accounts for unmeasured environmental heterogeneity that is associated with race but not accounted for in most analyses. This approach moves health disparities research toward targeting socio-environmental factors as the etiology of race disparities. Given the shorter life expectancy of men compared to women, it is important to ensure that public health interventions reach those less able to access care. This requires a sophisticated understanding of the etiology of health disparities to reach potential hidden populations, such as the low income urban white males in the EHDIC-SWB study. Therefore, future research efforts should focus not only on individual-level factors that influence one’s likelihood of using preventive health services, but also consider one’s social context and healthcare resources that may contribute to race differences in preventive health screenings. Clinicians and practitioners should consider obtaining information on men’s social and environmental conditions where they work and live. These social determinants of health will have an impact on men’s preventive health practices, health behaviors and subsequent health outcomes. Men’s health policies and interventions designed to reduce racial and socio-economic disparities in health screenings require an integrative approach that focuses on both structural and individual factors.

Acknowledgments

This research was supported by grant# P60MD000214-01 from the National Center on Minority Health and Health Disparities (NCMHD) of the National Institutes of Health (NIH), and a grant from Pfizer, Inc.

Footnotes

Conflicts of Interest

None of the authors have any conflicts of interest.

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