Disentangling Race and Social Context in Understanding Disparities in Chronic Conditions among Men

Abstract

Disparities in men’s health research may inaccurately attribute differences in chronic conditions to race rather than the different health risk exposures in which men live. This study sought to determine whether living in the same social environment attenuates race disparities in chronic conditions among men. This study compared survey data collected in 2003 from black and white men with similar incomes living in a racially integrated neighborhood of Baltimore to data from the 2003 National Health Interview Survey. Multivariable logistic regression models estimated to determine whether race disparities in chronic conditions were attenuated among men living in the same social environment. In the national sample, black men exhibited greater odds of having hypertension (odds ratio [OR] = 1.58, 95 % confidence interval [CI] 1.34, 1.86) and diabetes (OR = 1.62, 95 % CI 1.27–2.08) than white men. In the sample of men living in the same social context, black and white respondents had similar odds of having hypertension (OR = 1.05, 95 % CI 0.70, 1.59) and diabetes (OR = 1.12, 95 % CI 0.57–2.22). There are no race disparities in chronic conditions among low-income, urban men living in the same social environment. Policies and interventions aiming to reduce disparities in chronic conditions should focus on modifying social aspects of the environment.

Introduction

The elimination of health disparities and the improvement of overall population health are among the top public health priorities identified in Healthy People 2020. However, over the past three decades, minimal progress has been achieved in reducing racial inequalities in men’s health. African-American men experience greater morbidity, premature mortality, and earlier onset of disease and present at later stages of disease progression than white men.^1–8 While these disparities are well established, explanations for observed race differences remain.

The majority of research attempting to explain these race differences in men’s health has focused on individual-level factors such as socioeconomic status (SES), access to care, masculinity, health behaviors and practices, stress, and psychosocial factors.^4,6,9,10 One plausible explanation that has received little attention is the distinct social and environmental conditions in which men of differing racial and ethnic backgrounds live. These differences produce varying levels of exposure to health risks and are largely a function of racial residential segregation.^11,12 In the USA, racial segregation facilitates the production and propagation of health disparities by exposing individuals differentially to health-promoting resources.^8,9,12–14 Thus, the social and environmental setting in which one lives may be an important determinant of men’s health. Yet much of the information on racial disparities in men’s health is based on national data, making it difficult to parse out the potential impact of segregation.⁹

Another problem associated with examining race differences in men’s health indicators using national data is that race and SES are almost always confounded. For example, in national data, minority men often belong to the low SES group and minority men typically have the worse health profile relative to white men. Therefore, it is difficult to determine how these two measures function separately or together to produce disparities.^9,15 Indeed, the most familiar approach to account for this confounding is to adjust for individual-level measures such as education, family, or individual income. Because there is unmeasured heterogeneity associated with substantial differences in the historical and sociopolitical contexts of race groups in the USA, this technique is inadequate to account for the distinct environments in which white and African-American men live.^16,17 Failing to account for the race differences in social and environmental risk exposures may lead researchers to conclude erroneously that race, rather than place, may be responsible for observed racial disparities in chronic conditions.

The Exploring Health Disparities in Integrated Communities (EHDIC) study was designed to address the confounding of race, segregation, and SES. EHDIC’s design is a unique approach that takes into account the social and environmental conditions that men live. This has been largely missing in previous men’s health literature yet an important determinant of men’s health disparities.^4,7,8,12 The objectives of this study were to examine race disparities in chronic conditions among a sample of white and African-American men living in similar social and environmental conditions and compare these findings to a national sample.

Methods

Study Population

EHDIC is an ongoing multisite 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 the data from the first EHDIC study site in Southwest Baltimore, MD (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 US$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, 1,636 structures were determined to be occupied residential housing units (excluding commercial and vacant residential structures). At most five attempts were made to contact an eligible adult in 1,244 occupied residential housing units. A total of 65.8 % of the occupied housing units were enrolled in the study. This resulted in 1,489 study participants (41.9 % of the 3,555 adults living in these two census tracts recorded in the 2000 Census). Because our survey had similar coverage across each census block group including the study area, the bias to geographic locale and its relationship with SES should be minimal.¹⁵

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.¹⁵ 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, US$23,500 (African-American) vs. US$24,100 (white), was replicated in EHDIC with US$23,400 (African-American) vs. US$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.¹⁵ 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.

The National Health Interview Survey (NHIS) is an annual, cross-sectional, nationally representative health survey of the civilian, non-institutionalized, households of the USA conducted by the National Center for Health Statistics.¹⁸ Administered by U.S. Census Bureau interviewers, individuals aged 18 and over are eligible to participate in the sample adult survey which takes place in their home. Participants respond to questions regarding their demographic characteristics, health behaviors and conditions, functional limitations, cancer screening, and health care access and utilization. Detailed information regarding NHIS can be found elsewhere.¹⁸ Data from the 2003 NHIS was used to correspond with the year in which data was collected in the EHDIC-SWB study. Men who reported their race to be either black only or white only, who responded no to the question regarding Hispanic ethnicity, and who were 18 years of age and older were included in our analyses. Thus, the analytic sample consisted of 10,455 men, of which 1,551 were black and 8,904 were white.

Measures

Questions from the NHIS were replicated in the EHDIC-SWB study to facilitate comparison across studies. Each measure included in these analyses was coded similarly in both datasets. The outcome measures included three health conditions that were based on report of physician diagnoses: hypertension, diabetes, and heart disease. A binary variable was created for each health condition to indicate whether the men had been diagnosed by a physician with that particular health problem.

The primary independent variable was race. Men self-identified as black/African-American or white. Covariates included demographic and health-related characteristics known to be associated with race or the health outcome(s). Demographic variables included age (years), married (1 = yes; 0 = no), education level (0 = less than high school graduate; 1 = high school graduate/GED; 2 = more than high school graduate), and income category (<US$35,000, US$35,000–75,000, ≥US$75,000).

Health-related variables included the following: health insurance (1 = yes; 0 = no), physical inactivity (1 = yes; 0 = no), smoking and drinking status (0 = never; 1 = former; 2 = current), obesity, and self-reported health status. 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 was ≥30 kg/m² were considered obese (1 = yes; 0 = no). Men reported whether their health was excellent, very good, good, fair, or poor. A binary variable was constructed to classify men who reported their health as fair or poor.

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 across a range of demographic and health-related factors. Generalized linear models that specified the logit link and binomial distribution were used to calculate age-adjusted proportions. Each chronic condition was modeled as a function of race and age. Logistic regression models were specified to examine the association between race and each health condition adjusting for the demographic and health characteristics described above. Survey procedures were used when specifying the statistical models to account for the complex survey sampling design of the NHIS. P values <0.05 were considered statistically significant, and all tests were two-sided. All analyses were conducted in 2014 using STATA 11.¹⁹

Results

The distribution of demographic variables of male participants in NHIS and EHDIC-SWB by race is presented in Table 1. Of the 10,455 men in NHIS, African-American men (14.8 %) were, on average, about 4 years younger. In comparison to white men, smaller proportions of African-American in the NHIS sample were married or had incomes exceeding US$75,000. A larger proportion of African-American men had less than a high school education in comparison to white men. Of the 628 men in EHDIC-SWB, African-Americans (60.6 %) were, on average, 4 years younger, and a smaller proportion was married compared to whites. There were no differences in income level between the groups of men. However, a larger proportion of African-American men had a high school education or GED equivalent relative to white men, while a smaller proportion of African-American men had less than a high school education relative to the white men in this sample.

TABLE 1.

Distribution of select demographics and health-related characteristics in the black and white men in NHIS and EHDIC-SWB, 2003

Variable	NHIS			EHDIC-SWB
	White (n = 8,904)	Black (n = 1,551)	P value	White (n = 247)	Black (n = 381)	P value
Age, mean SE	46.2 ± 0.2	41.9 ± 0.5	<0.001	43.3 ± 0.9	39.4 ± 0.6	<0.001
Married (%)	68.0	53.6	<0.001	25.1	16.3	0.007
Income (%)
<US$35,000	22.7	33.0	<0.001	72.5	74.5	0.565
US$35,000–75,00	28.2	27.5	0.621	20.2	21.0	0.820
>US$75,000	24.4	12.8	<0.001	7.3	4.5	0.132
Did not respond	24.7	26.7	0.227
Education level (%)
Less than high school graduate	11.8	20.1	<0.001	44.5	34.9	0.016
High school graduate/GED	30.1	32.5	0.119	36.8	45.4	0.034
More than high school graduate	58.1	46.5	<0.001	18.6	19.7	0.742

Plus-minus values are means ± SD

The age-adjusted proportions for health characteristics and chronic conditions of the men in NHIS and EHDIC-SWB are displayed in Table 2. Among men in NHIS, smaller proportions of African-American men had health insurance and were former smokers or current drinkers relative to white men. However, larger proportions of African-American men were physically inactive, never smokers, never or former drinkers, and obese and reported fair/poor health, hypertension, or diabetes, in comparison to white men. There were no differences between African-American and white men with regard to current smokers or reporting heart disease. Among men in the EHDIC-SWB, a larger proportion of African-Americans had health insurance compared to white men. A larger proportion of African-American men also reported never smoking, while a smaller portion of them reported being a former smoker compared to white men. There were no differences between African-American and white men with respect to being physically inactive; being a current smoker; being a never, former, or current drinker; being obese; or reporting fair/poor health, hypertension, diabetes, or heart disease.

TABLE 2.

Age-adjusted distribution of health-related characteristics among black and white men in NHIS and EHDIC-SWB, 2003

Variable	NHIS			EHDIC-SWB
	White (n = 8,904)	Black (n = 1,551)	P value	White (n = 247)	Black (n = 381)	P value
Health insurance (%)	89.7	84.3	<0.001	50.3	58.9	0.039
Physical inactivity (%)	29.9	43.8	<0.001	18.6	14.6	0.182
Smoking status (%)
Never	47.0	53.4	<0.001	18.6	27.3	0.014
Former	25.9	19.3	<0.001	12.1	7.3	0.039
Current	23.4	22.9	0.735	65.4	62.4	0.453
Drinking status (%)
Never	14.3	26.1	<0.001	11.9	15.3	0.240
Former	13.6	18.0	<0.001	34.4	31.4	0.443
Current	70.7	53.9	<0.001	53.4	53.1	0.926
Obese (%)	24.7	31.4	<0.001	21.9	23.5	0.648
Fair/poor health (%)	8.7	16.7	<0.001	32.4	27.5	0.204
Health outcomes (%)
Hypertension	23.3	33.1	<0.001	26.2	26.1	0.967
Diabetes	4.9	8.6	<0.001	5.7	5.9	0.920
Heart disease	6.1	5.1	0.168	12.6	8.7	0.103

The association between race and each of the chronic conditions is presented in Table 3 for NHIS and EHDIC-SWB. After adjusting for age, marital status, insurance, education, income, fair/poor health, physical inactivity, obesity, and smoking and drinking status, African-American men in NHIS had higher odds of having hypertension (odds ratio [OR] = 1.58, 95 % confidence interval [CI] 1.34, 1.86) and diabetes (OR = 1.62, 95 % CI 1.27, 2.08), but lower odds of heart disease (OR = 0.71, 95 % CI 0.55, 0.91) compared to white men. In our EHDIC-SWB sample that also accounts for the social and environmental condition in which these men live, African-American men had similar odds of having hypertension (OR = 1.05, 95 % CI 0.70, 1.59), diabetes (OR = 1.12, 95 % CI 0.57, 2.22), and heart disease (OR = 0.71, 95 % CI 0.41, 1.22) compared to white men.

TABLE 3.

Association between race and chronic conditions among men in the NHIS and EHDIC-SWB, 2003

	NHISa	EHDIC-SWB
	OR (95 % CI)	OR (95 % CI)
Hypertension	1.58 (1.34–1.86)	1.05 (0.70–1.59)
Diabetes	1.62 (1.27–2.08)	1.12 (0.57–2.22)
Heart disease	0.71 (0.55–0.91)	0.71 (0.41–1.22)

White adults are the reference category. Models included race, age, marital status, insurance status, household income, education level, fair/poor health, physical inactivity, obesity, and smoking and drinking status

OR odds ratio, CI confidence interval

^aOnly models that contained variables in both EHDIC and NHIS 2003 datasets were conducted. All estimates using NHIS data account for the stratified, multistage probability sampling design by applying the appropriate weights and strata variables

Discussion

Research on men’s health disparities requires innovative approaches to understanding the etiology of observed differences in health outcomes. This study sought to examine differences in physician-diagnosed chronic conditions between African-American and white men who live in similar social and environmental conditions and who have access to the same health care facilities. More specifically, this study tested the proposition that failing to account for race differences in social and environmental conditions facilitated by segregation can lead to erroneous conclusions regarding the race differences in chronic conditions in men. Within this low-income urban sample, compared to white men, African-American men had similar odds of having hypertension, diabetes, or heart disease—chronic conditions that are typically more prevalent and deadly among African-American men. Yet, in the national sample, African-American men had greater odds of having two of these chronic conditions (apart from heart disease) relative to white men. The implications of these are that social context should be considered a key determinant of men’s health as well as major contributor to men’s health disparities.

In this study, there were no race differences in hypertension, diabetes, and heart disease observed between African-American men and white men who lived in a low-income, racially integrated community and had access to similar health care resources. This absence of racial disparities in these chronic conditions is consistent with the EHDIC hypothesis which suggests that race differences in health risk exposures facilitated by segregation may account for the observed race differences in health in men. These findings contradict previous work examining health disparities because those studies failed to account for social context where men live. This can pose a significant problem when relying on national data to understand and inform men’s health disparities.^17,20–22

There are three explanations for these findings. First, the EHDIC study design represents an opportunity to begin to disentangle race and residential segregation to better understand health disparities among men. In the USA, segregation and race are inextricably linked together, very much influencing health outcomes.^4,6,11,12,17 Moreover, African-Americans and whites often live in considerably different social and physical environments, which contribute to differences in their risk exposures and the quality of care they can access. Investigators have estimated that nearly 60 % of African-Americans would need to move to another census tract to achieve complete integration between African-Americans and non-Hispanic white Americans.^23–25 Yet, remarkably, national samples such as NHIS do not account for segregation.¹⁷ Consequently, national data might be overestimating race disparities in men’s health and grossly underestimating the far-reaching effects of residential segregation.

Second, it is worth noting that in the EHDIC-SWB sample, the health profile of white men closely resembled that of African-American men. On each of the three health indicators—hypertension, diabetes, and heart disease—the prevalence of these conditions were similar between white and African-American men. This was not the case when examining the NHIS data. This suggests that when African-American and white men are exposed to the same challenging health risk exposures in a low-income urban environment, their health profiles appear to be similar. Our findings emphasize the need to address social context when seeking to understand men’s health disparities.

Finally, it is likely that health care providers practicing in low-income urban communities may be more vigilant in screening and managing chronic conditions among African-American men due to increased awareness of earlier disease onset, higher prevalence of chronic conditions, shorter life expectancy, lower participation rates in screening practices, and premature mortality.^9,26,27 In the EHDIC-SWB sample, African-American and whites had similar access to health care resources which has been shown to produce similar health outcomes.^17,28 Furthermore, Thorpe and colleagues demonstrated that African-American men in EHDIC-SWB engaged in preventive health screenings more than white men.⁹ Future work using mixed methodologies should focus on understanding the facilitators and barriers of where men live and how it influences health conditions among men.

The results herein should be interpreted with the following caveats. Because EHDIC-SWB was conducted in two contiguous low-income urban census tracts, it is unknown if these results are transferable to higher SES groups, non-urban areas, or among men with other racial/ethnic backgrounds. This work was based on self-report data; however, prior work has established the accuracy of self-report of chronic conditions.^29–34 Further, this study used public-use NHIS data that precluded the ability to determine whether any of the men in NHIS lived in racially integrated communities. Because the NHIS is designed as a nationally representative sample of the USA, it is highly plausible that NHIS is as segregated as the US population. As a result, the number of men in NHIS that reside in integrated communities is likely to be small.

Notwithstanding these limitations, this study contributes to our understanding of race disparities in chronic conditions in men by using a study design that minimizes the confounding of race, SES, and residential segregation often present in national data. The EHDIC study represents an innovative approach to health disparities research, one which accounts for the social and environmental conditions that are associated with race but typically ignored by most research designs. Further, this approach moves men’s health disparities research toward targeting socio-environmental factors as the etiology of race disparities. This approach is also more amenable to intervention development and policy creation, implementation, and solutions.

Understanding men’s health disparities and the impacts that social determinants have on men’s health outcomes is the first step in designing strategies to address these inequities. Within this low-income urban sample, African-American and white men had similar odds of having physician-diagnosed hypertension, diabetes, and heart disease. This study adds to the burgeoning men’s health literature by establishing social context as a key contributor to disparities in chronic conditions between African-American and white men. Health care professionals should consider obtaining information on men’s social and environmental conditions where they live and work. Interventions designed to reduce the structural impediments on men’s health will require a multilevel approach that focuses on individual, family, community, and health system factors.