Association of Socioeconomic Status and CKD among African Americans: The Jackson Heart Study

Abstract

Background

Socioeconomic status (SES) is recognized as a key social environmental factor because it has implications for access to resources that help individuals care for themselves and others. Few studies have examined the association of SES with CKD in high-risk populations.

Study Design

Single-site longitudinal population-based cohort

Setting and Participants

The data for this study were drawn from the baseline examination of the Jackson Heart Study. The analytic cohort consisted of 3,430 African American men and women living in the tri-county area of the Jackson, Mississippi metropolitan areas with complete data to determine CKD status.

Predictor

High SES (defined as having a family income at least 3.5 times the poverty level or having at least one undergraduate degree)

Outcomes and Measurements

CKD (defined as the presence of albuminuria or reduced estimated glomerular filtration rate (eGFR) <60 ml/min/1.73m2). Associations were explored through bivariable analyses and multivariable logistic regression analyses adjusting for CKD and cardiovascular disease risk factors as well as demographic factors.

Results

The prevalence of CKD in the Jackson Heart Study was 20% (865/3430 participants). The proportion of the Jackson Heart Study cohort with albuminuria and decreased eGFR was 12.5% (429/3430 participants) and 10.1% (347/3430 participants) respectively. High SES was inversely associated with CKD. The odds of having CKD were 41% lower for affluent participants than their less affluent counterparts. There were no statistically significant interactions between sex and education or income although subgroup analysis showed that high income was associated with CKD among male (OR 0.47, CI 0.23–0.97) but not female (OR 0.64, CI 0.40–1.03) participants.

Limitations

Models were estimated using cross-sectional data.

Conclusion

CKD is associated with SES. Additional research is needed to elucidate the impact of wealth and social contexts in which individuals are embedded, and the mediating effects of sociocultural factors.

INTRODUCTION

Kidney disease is one of the most pressing issues in health disparities research. African Americans require dialysis or transplant at younger ages and have greater incidence rates of end stage renal disease (ESRD) at each decade of life as compared to any other racial/ethnic group.^{1, 2} These disparities have been generally thought to be a function of disproportionately high levels of chronic kidney disease (CKD) risk factors (i.e., diabetes, hypertension, and obesity). However, the presence of these co-morbidities does not fully explain the excess risks for CKD among African Americans. The evolving science in CKD research indicates that novel, non-biomedical factors can also have implications for CKD progression and complications.^3–6 Social science and social epidemiologic research have established that social environments may have important consequences for health outcomes, especially among at-risk populations such as African Americans. The accumulation of economic or social resources in an environment, referred to here as socioeconomic status (SES), is a key factor because it has implications for accessing the resources that can help individuals care for themselves and others. An emerging body of research has begun to consider the relationship between SES and CKD-related outcomes. Results from this line of work suggest that economic factors at the individual and community levels have implications for kidney disease.^{5, 7–11}

Deprivation and disadvantage are often part of the social landscape for African Americans. Little research has examined the social patterning of CKD within high-risk populations such as African Americans. Analyses of the prevalence and awareness of CKD in the Jackson Heart Study suggested the social patterning of CKD.¹² This purpose of this study is to examine further the nuanced associations of individual SES and CKD in this cohort with high CKD prevalence comprised of African Americans of all SES strata. High SES participants are expected to be less likely to have CKD than their lower income and less educated counterparts. We further tested the hypothesis that the patterning of the association between high SES and CKD varies by sex.

METHODS

Study Population and Measurements

The data for this study were drawn from the baseline examination of the Jackson Heart Study -- a single-site, longitudinal population-based cohort study prospectively investigating the determinants of cardiovascular disease (CVD) among African Americans living in the tri-county area (Hinds, Madison, and Rankin counties) of the Jackson, MS metropolitan areas. Baseline data collection occurred between September 2000 and March 2004. Recruitment, sampling, and data collection methods have been described previously.^13–16 Recruitment limited the age range to 35 to 84 but allowed relatives <35 years and >84 years to enroll in order to increase the sample power of the family component of the study.¹⁷ The total cohort consists of 5,301 African-American men and women between the ages of 21 and 94. The institutional review boards of the following participating institutions approved the study: the University of Mississippi Medical Center, Jackson State University, and Tougaloo College. All of the participants provided written informed consent.

The baseline examination had three components: a home interview, self-administered questionnaires, and a clinic visit. Individuals who had taken any medications two weeks prior to the examination were asked to bring them to the clinic to be coded by a pharmacist using the Medispan dictionary with classification according to the Therapeutic Classification System.¹⁸ Participants were asked to fast overnight before their clinic visit where anthropometric and seated blood pressure measurements were to be obtained. Venipuncture/urine collections were performed according to the National Committee for Clinical Laboratory Standards.¹³

Study Variables

CKD was defined as the presence of albuminuria or reduced glomerular filtration rate (eGFR) <60 ml/min/1.73m². The presence of albuminuria was determined by urine albumin-creatinine ratio (ACR) based on spot or 24-hour urine values (ACR>30 mg/g). eGFR was estimated using the 4-variable Modification of Diet in Renal Disease (MDRD) Study equation [GFR = 186.0 · (serum creatinine) ^−1.154 · age ^−0.203 · (0.742 if female) · (1.212 if African American)]. The definition of CKD in this study was broader than other studies that defined CKD based solely on eGFR. Analyses published elsewhere indicate that characteristics of included participants were similar to those of participants with eGFR alone.¹²

SES was represented by educational attainment and annual family income. These indicators tend to have nonlinear relationships with health indices for African Americans; therefore, each of these variables was represented by a series of dummy variables.¹⁹ Educational attainment was represented by a four-category variable: whether participants did or did not graduate from high school; attended or graduated from a community, technical, or junior college; or graduated from a four-year undergraduate institution or attained a post-baccalaureate education. Participants who did not complete high school made up the reference category. Annual family income was also a four-category variable classified into: low income (< poverty level), lower-middle income (1–1.6 times the poverty level), upper-middle income (1.6–3.5 times the poverty level), and affluent income (at least 3.5 times the poverty level). Classification was based on the year of visit, family size, and the number of resident children under 18. Following Smith²⁰ and Massey and Eggers,²¹ income category boundaries were established by U. S. Census estimations. The low income classification was the reference category.

Select demographic factors including age, sex, and marital status (married/not married) were based on self-reporting during the baseline interview. Health care access was represented by a variable corresponding to a questionnaire item asking participants to rate difficulty of getting health care services as “not difficult at all” (coded 1), “not too hard” (coded 2), “fairly hard” (coded 3), or “very hard” (coded 4). CVD-related risk factors (CVD, hypertension, diabetes, hypercholesterolemia, or BMI) were also accounted for in this analysis. CVD status was defined as the presence of coronary heart disease (electrocardiogram-determined myocardial infarction or self-reported history of myocardial infarction or angioplasty) or cerebrovascular disease (self-reported history of stroke or carotid endarterectomy or angioplasty). Hypertension status was defined as a measured blood pressure ≥ 140/90 mmHg and/or use of antihypertensive medications.^{22, 23} Presence of Type 2 diabetes mellitus (diabetes) was determined by a measured fasting glucose of ≥126 mg/dl or use of insulin and/or oral hypoglycemic agents. Presence of hypercholesterolemia was defined as an elevation in measured fasting total cholesterol (≥200 mg/dl), LDL-cholesterol (≥160mg/dl) and/or use of lipid-lowering medications. Hypertriglyceridemia was defined as elevated triglyceride levels (≥150 mg/dl) or/and treatment by fenofibrate or gemfibrozil while sex-specific limits (<50 mg/dl for women and <40 mg/dl for men) were used to define low HDL cholesterol levels.²⁴ BMI was derived by dividing participant weight in kilograms by participant height in meters squared.

Statistical Analysis

Study population characteristics were described overall by education and income strata, respectively, using mean and standard deviation for continuous variables and proportions for categorical variables. One-way ANOVA and Chi-square tests were used in descriptive analyses assessing how groups varied across key indicators. Multivariable logistic regression analysis was used to evaluate the relationship between high SES, co-morbid conditions, demographic factors, and CKD. “Education only” and “income only” models were also estimated to explore how the correlations between these components have implications for their respective relationships with CKD in the fully adjusted model. It also has been suggested that the social patterning of health outcomes for African-American men and women can vary considerably.^25–27 Group-specific logistic regression models were estimated to determine if the relationship between high SES and CKD varied by sex. All statistical analyses were conducted with StataSE Version 10 (www.stata.com).

RESULTS

As previously reported, 1,015 Jackson Heart Study participants completed 24-hour urine collections.¹² Spot urine collections were later added to the protocol (n=2,225); however, a substantial segment of the study population did not have sufficient urine data to determine CKD status (n=1,792). Other individuals were excluded if they did not have sufficient serum data to determine CKD status (n=56) or had restricted consent (n=23). The excluded participants were somewhat more likely to be older, not married, report more difficulty with healthcare access, and have lower education and income levels (data not shown). However, the analytic sample closely resembled the overall study sample.¹²

Table 1 describes the overall and SES-stratified characteristics of the sample. Most participants were female and married, and the mean age was 54. There was a high prevalence of hypertension, diabetes, dyslipidemia, and obesity. Approximately one-third of Jackson Heart Study participants had at least college degrees and one-fourth was affluent.

Table 1.

Characteristics of Jackson Heart Study Participants by SES components

	Analysis Sample	Education				p*	Income				p*
		1	2	3	4		1	2	3	4
Age (y)	54.3± 13.1	65.1 ± 10.9	56.2 ± 12.8	49.3 ± 12.1	52.5 ± 11.7	<.001	55.1 ± 15.7	57.0 ± 13.8	52.4 ± 12.4	53.4 ± 11.1	<.001
Male (%)	37.3	35.9	35.9	38.2	37.9	.7	23.8	32.1	37.6	49.0	<.001
Married (%)	54.8	42.6	49.4	56.0	62.8	<.001	27.3	39.8	59.1	72.5	<.001
Health care access**	1.4 ± 0.8	1.5 ± 0.9	1.5 ± 0.9	1.5 ± 0.9	1.3 ± 0.6	<.001	1.9 ± 1.1	1.5 ± 0.9	1.3 ± 0.7	1.2 ± 0.5	<.001
CVD (%)	10.4	21.8	12.2	7.9	6.1	<.001	17.0	13.6	8.3	6.2	<.001
Diabetes (%)	17.9	28.8	17.9	16.4	14.1	<.001	24.1	20.3	18.1	11.6	<.001
Hypertension (%)	62.6	79.2	67.2	57.1	56.9	<.001	67.6	67.4	61.5	56.7	<.001
Hypercholesterolemia (%)	30.5	36.4	33.0	28.4	28.2	.001	30.0	30.1	31.5	30.4	.9
Hypertriglyceridemia (%)	6.7	7.6	6.5	8.7	4.5	.001	7.3	6.7	6.9	6.7	.9
BMI (kg/m2)	31.7 ± 7.1	31.6 ± 7.1	31.7 ± 6.9	32.3 ± 7.5	31.3 ± 6.9	.006	32.8 ± 8.8	32.0 ± 7.4	31.9 ± 7.1	30.8 ± 6.2	<.001
Education (%)											<.001
< High School	16.1						34.1	27.0	9.0	2.8
High School	19.9						27.7	27.5	18.3	9.9
Some College	30.3						31.4	30.9	39.0	23.1
College Degree	33.5						6.8	14.7	33.8	64.2
Income (%)						<.001
Low Income	12.0	32.9	20.8	14.5	2.9
Lower Middle	19.7	42.7	22.8	23.5	10.0
Upper Middle	25.7	18.5	29.4	38.8	30.0
High Income	25.8	5.9	16.1	23.1	57.3
eGFR distribution (%)***						<.001					<.001
>90	40.5 (1384)	29.0	38.1	49.1	39.8		39.1	38.4	42.7	40.0
>60-<90	49.8 (1699)	49.8	51.5	43.8	54.1		42.9	50.3	48.8	55.0
>30-<60	8.5 (291)	17.9	9.0	6.6	5.5		14.8	9.7	7.6	4.8
<30	1.2 (41)	3.3	1.5	0.6	0.6		2.5	1.6	0.9	0.2
Albuminuria**** (%)	12.5 (429)	19.9	14.2	10.2	10.0	<.001	13.4	15.9	12.3	8.8	<.001
SCr (mg/dL)	1.1 ± 0.6	1.2 ± 0.9	1.1 ± 0.8	1.0 ± 0.5	1.1 ± 0.5	<.001	1.2 ± 1.0	1.1± 0.7	1.1 ± 0.5	1.1 ± 0.4	.02
CKD***** (%)	20.0 (685)	34.8	22.9	16.1	14.6		28.2	24.5	18.4	12.7

Notes: n=3,430. Values expressed as percent, percent (no.), or mean ± SD. Education and Income levels (1, 2, 3, and 4) are defined in the left column.

^*p trend

^**Health care access is an ordinal variable with values denoting difficulty of getting health care services (1=not difficult at all, 2=not too hard, 3=fairly hard, 4=very hard)

^***eGFR expressed in units of mL/min/1.73 m^2

^****albumin-creatinine ratio > 30

^*****eGFR<60 or ACR>30

Abbreviations: SCr, serum creatinine; CVD, cardiovascular disease; SES, socioeconomic status; CkD, chronic kidney disease; BMI, body mass index; eGFR, estimated glomerular filtration rate. Conversion factors for units: eGFR in mL/s/1.73 m^2, x0.01667; SCr in mg/dL to micromole/L, x88.4.

Higher SES participants were younger, more likely to married, and had easier access to health care services than their less educated and less affluent counterparts. The higher SES groups had substantially lower proportions of individuals with CKD and CKD risk factors than the corresponding proportions of sample members at lower levels of education and income. The patterns for education and income were strikingly similar with the notable exception of sex. The proportion of males was not statistically distinct across education levels. However, members of the higher SES groups were more likely to be male than their counterparts at lower levels of income.

Table 2 depicts the results from logistic models examining the association between the independent variables and CKD. Age, marital status, having CVD, diabetes, or hypertension, and being obese were associated with the likelihood of having CKD in each of the equations reported. In the “education only” and the “income only” models, being affluent and highly educated were inversely associated with the likelihood of having CKD. High income was the only statistically significant SES component in the fully adjusted model. The odds of having CKD were 41% lower for affluent participants than their poorer counterparts in the full model.

Table 2.

Association of SES and CKD in the Jackson Heart Study

Variable	Education Only	Income Only	Full Model
Age (/1 y)	1.03 (1.02 – 1.04)	1.03 (1.02 – 1.04)	1.03 (1.01 – 1.04)
Male	0.96 (0.64 – 1.46)	1.24 (0.69 – 2.21)	1.10 (0.88 – 1.40)
Married	0.75 (0.62 – 0.91)	0.78 (0.62 – 0.97)	0.78 (0.63 – 0.98)
Healthcare Access*	1.04 (0.93 – 1.16)	1.03 (0.91 – 1.17)	1.03 (0.91 – 1.17)
CVD	1.82 (1.41 – 2.35)	1.71 (1.28 – 2.27)	1.70 (1.28 – 2.26)
Diabetes	2.53 (2.05 – 3.11)	2.39 (1.90 – 3.02)	2.40 (1.91 – 3.03)
Hypertension	2.43 (1.88 – 3.15)	2.99 (2.23 – 4.02)	2.99 (2.23 – 4.01)
Hypercholesterolemia	1.16 (0.95 – 1.41)	1.27 (1.02 – 1.57)	1.27 (1.02 – 1.57)
Hypertriglyceridemia	1.28 (0.91 – 1.79)	1.31 (0.91 – 1.90)	1.33 (0.92 – 1.92)
BMI (/1 kg/m2)	1.03 (1.01 – 1.04)	1.02 (1.01 – 1.04)	1.02 (1.01 – 1.04)
Education
< High School	1.00 (ref)		1.00 (ref)
High School	0.88 (0.60 – 1.17)		0.93 (0.68 – 1.29)
Some College	0.77 (0.53 – 1.05)		0.84 (0.61 – 1.17)
College Degree	0.68 (0.47 – 0.94)		0.94 (0.66 – 1.32)
p trend	.05		.8
Income
Low Income		1.00 (ref)	1.00 (ref)
Lower Middle		0.88 (0.63 – 1.30)	0.88 (0.65 – 1.20)
Upper Middle		0.78 (0.52 – 1.08)	0.80 (0.57 – 1.11)
High Income		0.58 (0.41 – 0.83)	0.59 (0.40 – 0.87)
p trend		.01	.05
Education × Male p value	.9		.9
Income × Male p value		.5	.5

Note: All variables included in the analysis are listed in the table. Values shown are OR (95% CI).

BMI, body mass index; CI, confidence interval; OR, odds ratio; SES, socioeconomic status; CkD, chronic kidney disease; CVD, cardiovascular disease; ref, reference

^*Health care access is an ordinal variable with values denoting difficulty of getting health care services (1=not difficult at all, 2=not too hard, 3=fairly hard, 4=very hard)

Our tests for interactions between sex and education (p<.9) or income (p<.5) did not yield statistically significant results. However, the findings from sex-specific logistic models presented in Table 3 suggest that sex has implications for the association between SES and CKD. Being affluent and attending college was inversely associated with the likelihood of having CKD for women as shown in the “education only” and the “income only” models. However, in the full model for female participants, neither of the SES measures was found to be statistically significant. In contrast, high income was the only SES-related factor found to be associated with CKD among men. The likelihood of having CKD was approximately 53% lower for affluent male participants compared to their poor male counterparts.

Table 3.

Association of SES and CKD by Sex in the Jackson Heart Study

Variable	Education Only		Income Only		Full Model
	Men	Women	Men	Women	Men	Women
Age (/1 y)	1.03 (1.02 –1.06)	1.03 (1.02 – 1.04)	1.04 (1.02 – 1.06)	1.03 (1.02 – 1.04)	1.04 (1.02 – 1.05)	1.03 (1.01 – 1.04)
Married	0.71 (0.50 – 1.01)	0.77 (0.61 –0.97)	0.70 (0.47 –1.04)	0.81 (0.62 – 1.05)	0.70 (0.47 –1.05)	0.81 (0.62 –1.06)
Healthcare access*	1.14 (0.92 –1.40)	1.00 (0.88 –1.15)	1.08 (0.86 –1.35)	1.00 (0.85 –1.16)	1.09 (0.87 –1.36)	1.00 (0.85 –1.16)
CVD	1.84 (1.20 –2.81)	1.81 (1.31 –2.51)	1.70 (1.05 –2.75)	1.67 (1.16 –2.40)	1.71 (1.05 –2.77)	1.66 (1.16 –2.38)
Diabetes	4.37 (3.03 –6.30)	1.95 (1.51 –2.52)	4.41 (2.93 –6.64)	1.78 (1.34 –2.37)	4.40 (2.92 –6.63)	1.78 (1.34 –2.37)
Hypertension	2.06 (1.34 –3.17)	2.65 (1.92 –3.64)	2.51 (1.54 –4.10)	3.28 (2.26 –4.76)	2.49 (1.52 –4.07)	3.29 (2.26 –4.79)
Hypercholesterolemia	1.12 (0.79 –1.59)	1.18 (0.93 –1.50)	1.15 (0.78 –1.70)	1.34 (1.03 –1.74)	1.17 (0.79 –1.73)	1.34 (1.03 –1.75)
Hypertriglyceridemia	1.50 (0.92 –2.45)	1.06 (0.65 –1.72)	1.33 (0.78 –2.26)	1.23 (0.73 –2.08)	1.35 (0.79 –2.32)	1.23 (0.73 –2.08)
BMI (/1 kg/m2)	1.06 (1.03 –1.09)	1.02 (1.00 –1.03)	1.06 (1.03 –1.09)	1.01 (0.99 –1.02)	1.06 (1.03 –1.09)	1.01 (0.99 –1.03)
Education
< High School	1.00 (ref)	1.00 (ref)			1.00 (ref)	1.00 (ref)
High School	1.00 (0.60 –1.67)	0.80 (0.57 –1.12)			0.90 (0.51 –1.61)	0.90 (0.61 –1.33)
Some College	0.78 (.47 –1.30)	0.73 (0.52 –1.04)			0.81 (0.45 –1.46)	0.85 (0.57 –1.26)
College Degree	0. 78 (0.47 –1.30)	0.62 (0.44 –0.87)			1.01 (0.55 –1.89)	0.85 (0.56 –1.31)
p trend	.6	.05			.8	.9
Income
Low Income			1.00 (ref)	1.00 (ref)	1.00 (ref)	1.00 (ref)
Lower Middle			0.76 (0.39 –1.46)	0.87 (0.61 –1.24)	0.75 (0.39 –1.45)	0.88 (0.62 –1.27)
Upper Middle			0.81 (0.42 –1.55)	0.70 (0.49 –1.02)	0.80 (0.41 –1.56)	0.74 (0.50 –1.09)
High Income			0.49 (0.25 –0.96)	0.60 (0.40 –0.92)	0.47 (0.23 –0.97)	0.64 (0.40 –1.03)
p trend			.08	.08	.1	.3

Note: All variables included in the analysis are listed in the table. Values shown are OR (95% CI).

BMI, body mass index; CI, confidence interval; OR, odds ratio; SES, socioeconomic status; CkD, chronic kidney disease; CVD, cardiovascular disease; ref, reference

^*Health care access is an ordinal variable with values denoting difficulty of getting health care services (1=not difficult at all, 2=not too hard, 3=fairly hard, 4=very hard)

DISCUSSION

This study extends our initial analyses of indicators of CKD prevalence and awareness¹² and prior research that focuses on economic deprivation and its implications for the excess risks for outcomes such as CKD.^{7–11, 28} Our research suggests that affluence also has implications for kidney disease among African Americans. As expected, affluent or highly educated African American participants in the Jackson Heart Study had lower risks for CKD relative to their poor or less educated counterparts. The results from this study also suggested that the patterns of association between high SES and CKD may differ by sex. Similar to other epidemiologic research showing that a lack of economic resources is associated with health outcomes such as hypertension, diabetes, and CVD,^29–38 CKD is socially patterned. Importantly, the findings from this study indicate that the relationship between SES and CKD may not be linear; while affluent and educated participants had lower risks of CKD, the likelihood of having CKD among middle-income participants was not significantly different from their poor counterparts. Similarly, high school and junior college graduates as well as college attendees did not have statistically distinct risks for CKD relative to study participants who did not graduate from high school. These results suggest that the relationship between SES and health outcomes may be complicated and require researchers to consider potential non-linear relationships between economic factors and health conditions such as CKD.

Sex-specific analyses suggested different patterns of CKD risk for men and women with varying SES. High income was associated with CKD among males but not in females although we found no statistically significant interaction between sex and SES. While speculative, high incomes may provide African American men with access to facilities (e.g., health clubs) or resources (e.g., private medical care) that substantially reduce their risk for CKD relative to low-income men. Additional research is required to determine how SES-related factors are associated with sex-related factors with regards to CKD.

The relationship between marital status and CKD was an unexpected finding worth notation. The likelihood of married participants having CKD was significantly lower than their unmarried counterparts. Classic social science asserts that social relationships affect individual well being.³⁹ The data are consistent with studies examining the impact of social relations on cardiovascular outcomes. For example, individuals who live alone or have minimal contact with friends, relatives, or acquaintances have been found to have higher rates of CVD and overall morbidity and mortality than do persons who are integrated in social networks.^40–42 The relationship between social relations and kidney disease has not been pursued extensively.⁴³ Research has not determined the degree to which factors such as marriage have implications for the development and progression of CKD. It is not clear how social relationships combine with other environmental factors to impact the health and the development and progression of CKD among individuals at risk for CKD. Further research is needed to elucidate these patterns of association.

Despite its contributions to understanding SES patterning of CKD, this study is not without limitations. Our definition of CKD included both albuminuria and low eGFR. A sensitivity analysis was performed using the IVEware software.⁴⁴ For those missing urine values, albuminuria status was imputed for those with missing urine values using the Sequential Regression Imputation Method⁴⁵ and their CKD status was then determined based on both albuminuria and eGFR. Association of SES and CKD was then assessed using logistic regression models similar to the main analyses described in the paper. The results were very similar to the results reported in Table 2. Analyses of the cohort using low eGFR only (Table S1; available as online supplementary material associated with this article at www.ajkd.org) also yielded similar results to those combining albuminuria and eGFR (Table 2). Higher income levels correlated significantly with higher eGFRs. All of the usual limitations of cross-sectional studies apply.¹² The income and education measures used in the analyses were crude measures of SES and analyses utilizing more comprehensive measures of individual (e.g., wealth-oriented measures such as home ownership, investment income, or net worth) and neighborhood SES could produce more robust findings.

Some might consider the analysis of an exclusively African American sample to be a limitation arguing diminished usefulness without a comparison group. However, there is evidence that the factors associated with African American health outcomes can differ substantially from other groups.^{25, 46–49} The results from this study provide deeper insight into CKD among a heterogeneous group of African Americans often masked in comparative studies in which race or ethnic group membership is represented by a single variable.

High SES was associated with lower risks for CKD among African Americans in the Jackson Heart Study though the results were not linear. As well, the results suggested there may be nuanced socioeconomic differences for men and women. Additional research incorporating measures of wealth and other social contextual factors may assist in developing culturally and context-specific interventions to help reduce disparities in CKD development and progression in the short term and eliminate them in the long term.

Supplementary Material

01

Table S1: Association of SES and Low eGFR in the Jackson Heart Study.