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Epidemiology and health-related services: Edited by Dan Solomon

Disparities in lupus care and outcomes

Demas, Kristina L; Costenbader, Karen H

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Current Opinion in Rheumatology: March 2009 - Volume 21 - Issue 2 - p 102-109
doi: 10.1097/BOR.0b013e328323daad
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Health disparities, according to the National Institutes of Health (NIH) Working Group on Health Disparities, have been defined as ‘differences in the incidence, prevalence, mortality and burden of diseases and other adverse health conditions that exist among specific population groups in the US’ [1]. The study of disparities in health outcomes and their causes is now a national priority. Sociodemographic disparities in the incidence and severity of many chronic diseases, including obesity, hypertension, diabetes mellitus and chronic renal disease, have been observed [1–3]. Vulnerable populations may be defined by age, race/ethnicity, sex, sexual orientation, socioeconomic status, geographic residence or other characteristics [1].

Of the numerous conceptual frameworks describing determinants of health outcomes disparities, a conceptual model articulated by House includes sociodemographic factors that are relatively fixed such as age, sex, race, ethnicity and geographic location and those that are potentially modifiable [4,5] (Fig. 1). The NIH Strategic Plan on Health Disparities focuses on differences in healthcare delivery [6], an important potentially modifiable factor in the pathway between belonging to a specific sociodemographic group and ultimate healthcare outcomes. Healthcare system factors, medical insurance and psychosocial factors, including adherence, education and social support are also potentially modifiable factors that may interact with fixed sociodemographic factors or act independently and influence long-term outcomes, creating health outcomes disparities.

Figure 1
Figure 1:
Conceptual framework for understanding sociodemographic differences and disparities in systemic lupus erythematosus

Health disparities in systemic lupus erythematosus

Among the rheumatic diseases, SLE is the most strongly associated with disparities in its incidence, prevalence and long-term outcomes [7,8]. SLE incidence appears to have increased in the general United States population over the past four decades [9], and SLE has one of the highest mortality rates of the rheumatic diseases [9,10]. Prognosis is improved by prolonged, complex and potentially toxic therapies. For unknown reasons, SLE is most prevalent among women and those of nonwhite descent; those of African heritage are the most affected population. Lupus incidence rates among black women, for example, are 3–4 times those of white women. Mean age at onset of lupus is younger among black people [11,12], and disease damage accrues more quickly [13]. Nonwhite people with lupus have mortality rates at least more than three times as high as white people [10,14–17]. The Centers of Disease Control and Prevention documented that lupus mortality rates from 1979 to 1998 were more than five times higher for women than for men [10]. The highest and fastest increasing SLE mortality rates in the United States from 1979 to 1998 were observed among African–American women aged 45–64 years [10]. In this population, a 69.7% increase in mortality was seen (Fig. 2). Other racial and ethnic minorities, including Hispanics, Asians and Native Americans, the poor, and those lacking medical insurance and education are also at increased risk of developing SLE and poor outcomes from the disease.

Figure 2
Figure 2:
Systemic lupus erythematosus death rates* among women by age group and race– United States, 1979–1998

The root causes of these disparities and the potentially remediable factors contributing to them remain poorly understood. The disparities observed in SLE are likely to be explained only partially by genetic, hormonal and biologic factors. Genetic and biologic differences between racial and ethnic groups and between men and women cannot explain the socioeconomic ‘gap’ in SLE incidence, severity and outcomes or the widening of this gap over time.

Several research groups are investigating the underlying causes of disparities in the incidence, prevalence and health outcomes among individuals with SLE. In particular, we reviewed those that have focused on healthcare system factors. The studies reviewed herein have significantly contributed to our growing understanding of the multiple causes of SLE disparities and have helped to identify potentially correctable contributory factors. Although lupus does affect some men, it is predominantly a disease of women. Before puberty, lupus is approximately twice as common in girls. At the onset of puberty, the rate in women begins to climb, reaching a peak ratio of 8–9: 1 from ages 15–45 years. After menopause, the disproportionate incidence rates in women decline to approximately twice those in men [18,19]. Rates of lupus nephritis and lupus nephritis end-stage renal disease, necessitating renal dialysis or transplantation, are also much higher among women compared with men [20]. Genetic or hormonal differences or both may underlie much of the female predominance in SLE, but have yet to be well quantified [21].

By most measures, including income, educational level, wealth, medical insurance, occupation and area-based socioeconomic measures, individuals with lower socioeconomic status (SES) have higher rates of incidence, severity and mortality from SLE than do those of higher SES [16,22–32,33•]. SLE mortality is highest in the United States South and associated with poverty and Hispanic ethnicity [34,35]. Women also earn substantially less income than men and more women than men live below the Federal poverty level in the United States (22.5% of women versus 18.3% of men in 2004) [36]. SES may thus be contributing to observed disparities in SLE incidence and outcomes with regard to sex.

SLE incidence, morbidity and mortality are all much higher among nonwhite than white racial and ethnic groups in the United States [10,37]. Started in 1994, LUpus in MInorities: NAture vs. nurture (LUMINA) is a multiethnic (Hispanic, African–American and white), longitudinal SLE cohort study based in Alabama, Texas and Puerto Rico [28–32,33•]. It currently has 636 participants who meet the American College of Rheumatology (ACR) criteria for the classification of SLE [38,39], have disease duration of at least 5 years and are at least 16 years of age [40]. The relationship of race/ethnicity and SES to the increased SLE incidence and poorer survival in African and Hispanic–American patients have been studied in LUMINA [28–32,33•]. An early analysis followed 288 SLE patients for 5 years from study onset. During this time, 34 (11.8%) patients died and LUMINA investigators have attempted to disentangle race/ethnicity from SES as predictors of SLE mortality [28]. Those with incomes below the Federal poverty level were four times more likely to die than were those with higher incomes [28,41•]. After adjustment for poverty and medical insurance, the risk of SLE progression was greatly reduced among both African–American and Hispanic participants [24]. Significant predictors of poor outcomes and disease progression in this cohort have included Hispanic and African–American ancestry, as well as poverty, lack of education and lack of social support (not married or living together) [33•].

The LUMINA cohort has also allowed the investigation of racial and ethnic disparities in specific SLE manifestations and outcomes, including renal disease, myocarditis, hypertension and work disability [31,42–45]. LUMINA participants who developed renal disease were younger, had more hypertension and were more African–American or Texan–Hispanic [31,42,43]. African–American and Texan–Hispanic ethnicity and obesity were also risk factors for developing hypertension in LUMINA [46]. Abrupt SLE onset, as opposed to a more insidious subacute onset, was associated with younger age and lower SES and predicted more severe ongoing clinical manifestations and higher disease activity [40]. African–Americans in LUMINA had a strikingly higher risk of developing myocarditis (60.9%) compared with (1.9%) Hispanics from Puerto Rico [44]. LUMINA investigators found that age, smoking, alcohol intake, education, poverty and health insurance were not associated with the risk of myocarditis, however. In addition, LUMINA SLE patients from lower socioeconomic backgrounds were more likely to become disabled [45]. Lotstein et al. [47] found in past work that women with SLE of lower SES as captured by the Hollingshead Index, which incorporates educational level and occupational prestige, had more functional disability and cumulative organ damage. In LUMINA, poverty, total disease duration, disease activity and damage accrual were predictors of work disability [45].

In the Hopkins Lupus Cohort of 1378 individuals with SLE, low SES, defined as a household income less than $25 000, had a 70% survival compared with an 86% survival rate for those with a higher household income [48]. African–American background was associated with decreased survival in univariate analysis, but was not an independent predictor after adjustment for income and education [48]. This suggests that SES influences SLE severity and mortality independently of race/ethnicity.

Following the documentation of clear health disparities in SLE, the research impetus over the past few years has been to go beyond description and to address fundamental questions about their causes. In particular, what aspects of low SES are responsible for disparities in SLE, and can specific potentially modifiable factors be identified to allow the targeting of future efforts to decrease disparities in SLE? These two questions are enormously challenging. The multiple causes of poor outcomes in SLE are overlapping and interactive. Race, SES and factors closely associated with each such as reduced access to quality healthcare, reduced comprehension of disease and the medical system, increased competing home and work demands and reduced self-confidence and social support have been tightly correlated and predictive of SLE disease activity, organ damage and functional ability in past research studies [26,27,47,49–51]. Genetic factors, undoubtedly, contribute to racial and ethnic disparities in SLE outcomes. The identification of new genetic factors involved in SLE pathogenesis promises improved understanding and identification of new molecular pathways and targets. Given the large sociodemographic ‘gap’ in SLE outcomes that continues to grow, genetic factors alone are unlikely entirely responsible. Additionally, genetic factors such as sex are not modifiable, and thus, not amenable to interventions to decrease observed disparities. Current research is taking on the challenge of dissecting the overlapping, nondiscrete aspects of race/ethnicity and SES, and how their components could be acting to create disparities in SLE incidence and long-term outcomes.

Education and self-efficacy

In several studies, the educational level of SLE individuals has been predictive of outcomes. A greater number of years of education may improve outcomes by increasing medical understanding, confidence in one's ability to manage a chronic disease or the ability to communicate and self-advocate effectively in patient–doctor interactions or all. In a multicenter SLE study [51], lower self-efficacy for disease management (the belief that one has the ability to control one's disease), less social support and younger age at diagnosis were associated with greater disease activity and cumulative organ damage. Employing data from the United States Multiple Causes of Death from 1994 to 1997, Ward [52] found that fewer years of education were associated with increased SLE-related mortality, particularly among white people. This was not found among ethnic minorities, however, possibly due to underascertainment of lupus-related deaths in less-educated patients. Not surprisingly, lower educational level was associated with adverse SLE pregnancy outcomes in the LUMINA cohort [53].

Educational level and related medical understanding and self-efficacy are likely related to the quality of patient–physician interactions. Ward et al. [54] audiotaped routine visits between 79 women with SLE and their rheumatologists and assessed for active patient participation and the degree of patient-centered communication of the physician. Patients who had participated more actively in their visits had less permanent organ damage at the end of a median of 4.7 years' follow-up. Karlson et al. [55] enrolled 122 women with SLE into a 12-month randomized controlled trial of a theory-based intervention to improve patient self-efficacy and social support for management of SLE. At the end of the trial, those patients who had received the intervention had improved significantly in measures of global mental and physical health, as well as fatigue, illustrating that self-efficacy and social support are modifiable predictors of long-term outcomes in SLE [55].

Depression and lack of social support

In several studies, being married or living with another person, or having identified individuals to provide social support, has been associated with better outcomes in SLE [33•,51]. In a randomized trial setting, an educational intervention involving SLE patients and an identified social support person to improve both self-efficacy and social support improved SLE outcomes, underscoring the importance of social support [55]. Depression, on the contrary, likely impedes self-efficacy, adherence, and patient–physician communication and is more common in lower SES groups [47,56•].

Adherence and nonadherence

Lack of education and understanding, distrust in medical institutions and cultural misunderstanding may lead to nonadherence to medical therapy. In an older study, Petri et al. [23] reported that although African–American lupus patients in the Johns Hopkins Rheumatology Clinic had lower education, income and job status and poorer medical insurance coverage than did white lupus patients, they also had poorer adherence to medical care as assessed by the physician. In multivariable analyses, medical adherence and hypertension were more important predictors of the development of renal disease than were race or classical measures of SES. Lack of disease comprehension and reduced self-confidence and social support are related to racial/ethnic background and SES and are also predictive of SLE activity, organ damage and functional ability [26,27,47,49–51]. In the LUMINA cohort, loss to follow-up, defined as failure to attend two or more of the consecutive yearly visits, was highest among African–Americans, followed by white and then Hispanic patients who were the least likely to become lost due to follow-up [57].

Access to care: provider and hospital experience (volume) and subspecialist care

Employing data from the United States Renal Datasystem, which include approximately 94% of all individuals in the United States with end-stage renal disease requiring chronic renal replacement, Ward [58] examined the age at onset of end-stage renal disease among patients with lupus nephritis according to their medical insurance. He found that when analyzed within their own racial/ethnic group, those with Medicaid or no insurance were younger at onset of end-stage renal disease than those with private insurance. This illustrates that the type of medical insurance is related to the rate of progression of renal failure in SLE, but it is not clear what aspect of medical insurance or a variable closely associated with medical insurance is responsible.

Access to quality healthcare or ‘the realized ability to receive appropriate medical care in a timely manner, free from geographic or financial barriers’ [27] is a challenge for minority and disadvantaged groups and a potentially remediable factor that is associated with outcomes in SLE. Care for patients with lupus, like that of many chronic diseases, necessitates advanced training, experience, strong physician–patient communication skills and access to other subspecialists and medical technology. In many complex diseases, including rheumatoid arthritis, diabetes mellitus and chronic kidney disease, the involvement of medical specialists results in better long-term outcomes [59–66].

In California, lack of medical insurance was strongly associated with fewer physician visits for SLE patients [27]. Yazdany et al. [67•] conducted a telephonic survey of more than 900 SLE patients concerning their subspecialty care and found that older age, lower income and being male were associated with lack of rheumatology follow-up care. Medicaid SLE patients in California also traveled farther to receive SLE healthcare and were more likely to see a generalist or be seen in the emergency department compared with those with other insurance [68•]. In addition, SLE patients enrolled in health maintenance organizations, compared with those in fee-for-service (FFS) health plans, utilized less ambulatory care and were less likely to have outpatient surgery and hospital admissions [69•]. In other diseases, lack of physician continuity and regular follow-up, which can be dictated by medical insurance plans, is associated with medical nonadherence as well [70].

Hospital and physician experience in treating SLE have been associated with SLE outcomes. In-hospital mortality was lower for SLE patients hospitalized at California hospitals with more SLE admissions per year compared with those at hospitals with less experience [71]. Ward [72] found that the risk of in-hospital mortality for SLE patients in New York and Pennsylvania was inversely associated with the average number of SLE patients that the attending physician had recently admitted. The inverse relationship between physician experience and SLE mortality was stronger for nonwhite than white patients. This suggests that provider volume may be an important, and potentially modifiable, barrier to better long-term outcomes among nonwhite SLE patients [72]. The association between physician volume and SLE patient mortality was also stronger for those patients without private medical insurance than for those having it, suggesting that for this vulnerable population, in particular, access to high quality care is paramount [72]. Among lupus nephritis patients, having an attending physician who was highly experienced was associated with a 60% reduction in in-hospital mortality risk [72].

In another study, Ward [73•] examined 16 751 hospitalizations for patients with SLE and classified 12.3% as avoidable, an indicator of underutilization or poor access to healthcare. Rates of ‘avoidable hospitalizations’ such as those for pneumonia, cellulitis and congestive heart disease, all potentially avoidable with prompt and correct medical attention and indicative of substandard outpatient care, were lower at medical centers in the New York State with high volumes of SLE admissions [73•]. These avoidable hospitalizations for SLE patients were most frequent for older patients and for those in the lowest quartile of SES quartile [73•]. These findings reinforce the importance of physician and hospital experience in preventing avoidable SLE admissions.

Among 6521 hospitalized SLE patients in South Carolina, African–Americans were more likely than white people to experience both in-hospital mortality and mortality after 1 year following hospital discharge [74•]. In South Carolina, where 30% of the population is African–American, African–Americans with SLE had lower levels of education, were more likely to have public insurance, earned lower incomes, had increased hospitalizations and also died at significantly younger ages than their white counterparts. Even after multivariable adjustment for comorbidities, which were more common in African–Americans, African–American lupus patients had a 15% increased mortality risk compared with white people with lupus [74•].

Geographic and area-level factors

There is growing literature about the important effects of geographic residence and area-level factors, neighbourhood poverty level, population composition, employment, educational level, dwelling type, household and family size and housing occupancy on a variety of health outcomes including infectious diseases, childhood asthma, orthopedic surgery and end-stage renal disease [75–80]. In many cases, one's individual behavior may be better explained by the characteristics of one's neighbours than by individual factors.

Investigators from the University of California at San Francisco utilized data from a large geographically, socioeconomically and racially diverse SLE cohort to assess the independent effects of neighborhood poverty and individual SES on SLE outcomes [56•]. Both low neighborhood and individual SES were associated with increased disease activity, poorer physical functioning and greater symptoms of depression. The increase in depressive symptoms suggests that SLE patients living in low-income neighborhoods have more difficulty dealing with chronic disease, and this likely contributes to decreased self-efficacy for disease management.

Employing the United States Renal Data System, Ward [81] examined the influence of area-level SES on the incidence of end-stage renal disease due to SLE, diabetes mellitus and autosomal dominant polycystic kidney disease. He used an area-based measure of SES on the basis of patients' zip codes of residence, encompassing area poverty, household income, house value, employment and education levels. Among white people, the risk of developing end-stage renal disease from lupus nephritis for those in the lowest compared with highest category was 50–60% higher. For African–Americans, however, there was no statistically significant change in risk related to this SES measure. Thus, although this area-based SES measure was associated with SLE renal outcomes among white people, it was not independently predictive among African–Americans. When comparing different disease causes of end-stage renal disease, area-based SES had a more important influence on outcomes for SLE renal disease than for polycystic kidney disease, in which genetic factors may play a larger role, but less so than for diabetic renal disease, in which area SES factors had an even larger influence.

Environmental exposures

Factors responsible for the increased incidence and severity of SLE in disadvantaged populations may also be driving increased severity of disease and poorer survival in these groups. As with many complex diseases, environmental exposures likely trigger disease development, particularly in individuals who are genetically predisposed [82]. Disadvantaged groups may have higher rates of incident SLE and SLE progression due to both genetic and environmental factors. Cigarette smoking and exposure to occupational and agricultural silica, as well as use of exogenous reproductive hormones among women, have been associated with increased risk of developing SLE in epidemiologic studies [83–86]. Smoking is associated with more severe SLE and worse outcomes from lupus nephritis in several studies [87–89], as has hypertension [87,90,91]. Differential rates of comorbidities such as smoking, obesity and hypertension may explain some of the observed sociodemographic disparities in SLE. Exposures to infectious agents, occupational hazards, pollutants, drugs, dietary, cosmetic or recreational factors that could heighten SLE risk could very likely be related to socioeconomic position.


Alarming sociodemographic disparities in the incidence and severity of SLE have been documented. Their causes are multifactorial and SES-related factors play a large role. The complex effects of SES include access to appropriate medical care with delayed and poorer quality healthcare, poor medical understanding and medication adherence and lower self-efficacy and confidence in the healthcare system and its providers.

W.E.B. DuBois [92] prophetically declared at the beginning of this century that ‘the problem of the twentieth century is the problem of the color line’. He also wrote, ‘To be a poor man is hard, but to be a poor race in a land of dollars, is the very bottom of hardships’. Belonging to a racial or ethnic minority group and having low socioeconomic status are significant predictors of increased risk of SLE and poor SLE outcomes even today.

Recent research has identified factors that may contribute to these observed disparities in SLE, including, but not limited to, education, adherence, social support, medical insurance type, geographic area of residence, access to high volume hospitals and physicians and potential environmental exposures. This research suggests we should focus on healthcare access, education and increasing disease awareness and adherence among high-risk patients, concentrating on regular follow-up and adherence to therapy. We should also develop strategic interventions designed to eliminate these disparities aimed at the barriers research has shown to exist. Developing teams of experienced physicians, educators and caregivers, working with patients and their loved ones to strengthen social support, enhance self-efficacy, decrease comorbidities such as smoking, hypertension and obesity and increase adherence would be a good start [50].

References and recommended reading

Papers of particular interest, published within the annual period of review, have been highlighted as:

• of special interest

•• of outstanding interest

Additional references related to this topic can also be found in the Current World Literature section in this issue (p. 190).

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56• Trupin L, Tonner MC, Yazdany J, et al. The role of neighborhood and individual socioeconomic status in outcomes of systemic lupus erythematosus. J Rheumatol 2008; 35:1782–1788. Neighborhood socioeconomic status was correlated with high depressive symptoms in patients with SLE. Individual SES was also related to greater disease activity, poor physical functioning and depressive behavior/symptoms. This is an important new study highlighting the role of neighborhood status in SLE outcomes.
57 Bertoli AM, Fernandez M, Calvo-Alen J, et al. Systemic lupus erythematosus in a multiethnic U.S. cohort (LUMINA) XXXI: factors associated with patients being lost to follow-up. Lupus 2006; 15:19–25.
58 Ward MM. Medical insurance, socioeconomic status, and age of onset of endstage renal disease in patients with lupus nephritis. J Rheumatol 2007; 34:2024–2027.
59 Ward MM, Leigh JP, Fries JF. Progression of functional disability in patients with rheumatoid arthritis: associations with rheumatology subspecialty care. Arch Intern Med 1993; 153:2229–2237.
60 Yelin EH, Such CL, Criswell LA, Epstein WV. Outcomes for persons with rheumatoid arthritis with a rheumatologist versus a nonrheumatologist as the main physician for this condition. Med Care 1998; 36:513–522.
61 Lafata JE, Martin S, Morlock R, et al. Provider type and the receipt of general and diabetes-related preventive health services among patients with diabetes. Med Care 2001; 39:491–499.
62 Valderrabano F, Golper T, Muirhead N, et al. Chronic kidney disease: why is current management uncoordinated and suboptimal? Nephrol Dial Transplant 2001; 16(Suppl 7):61–64.
63 Avorn J, Winkelmayer WC, Bohn RL, et al. Delayed nephrologist referral and inadequate vascular access in patients with advanced chronic kidney failure. J Clin Epidemiol 2002; 55:711–716.
64 Winkelmayer WC, Glynn RJ, Levin R, et al. Late nephrologist referral and access to renal transplantation. Transplantation 2002; 73:1918–1923.
65 Winkelmayer WC, Glynn RJ, Levin R, et al. Late referral and modality choice in end-stage renal disease. Kidney Int 2001; 60:1547–1554.
66 Winkelmayer WC, Glynn RJ, Levin R, et al. Determinants of delayed nephrologist referral in patients with chronic kidney disease. Am J Kidney Dis 2001; 38:1178–1184.
67• Yazdany J, Gillis JZ, Trupin L, et al. Association of socioeconomic and demographic factors with utilization of rheumatology subspecialty care in systemic lupus erythematosus. Arthritis Rheum 2007; 57:593–600. This study analyzed the relationship between socioeconomic and demographic factors including income, education, age, race, ethnicity and sex in the utilization of rheumatology subspeciality care in SLE. Although race and educational level were not associated with visiting a rheumatologist and older age.
68• Gillis JZ, Yazdany J, Trupin L, et al. Medicaid and access to care among persons with systemic lupus erythematosus. Arthritis Rheum 2007; 57:601–607. This study evaluated the association between SLE patients' type of health insurance and the distances they traveled to see a physician. Medicaid patients with SLE traveled longer distances to see an SLE physician, suggesting that these patients may face challenges in obtaining quality and comprehensive care in proximity to their residences.
69• Yelin E, Trupin L, Katz P, et al. Impact of health maintenance organizations and fee-for-service on healthcare utilization among people with systemic lupus erythematosus. Arthritis Rheum 2007; 57:508–515. A survey of 982 SLE patients compared the healthcare utilization of patients enrolled in health maintenance organizations (HMOs) with those with FFS health plans. Their results suggest that patients with SLE in HMOs utilized substantially less ambulatory care and were less likely to have outpatient surgery and hospital admissions than those in FFS. This study is important in highlighting the influence of insurance type on SLE outcomes.
70 Brookhart MA, Patrick AR, Schneeweiss S, et al. Physician follow-up and provider continuity are associated with long-term medication adherence: a study of the dynamics of statin use. Arch Intern Med 2007; 167:847–852.
71 Ward MM. Hospital experience and mortality in patients with systemic lupus erythematosus. Arthritis Rheum 1999; 42:891–898.
72 Ward MM. Association between physician volume and in-hospital mortality in patients with systemic lupus erythematosus. Arthritis Rheum 2005; 52:1646–1654.
73• Ward MM. Avoidable hospitalizations in patients with systemic lupus erythematosus. Arthritis Rheum 2008; 59:162–168. Avoidable hospitalizations can indicate underutilization or poor access to healthcare. In this study, avoidable hospitalizations occurred more commonly among older and poorer SLE patients. These avoidable hospital visits suggest inequity and inefficiency in the healthcare delivery system and more specifically in the treatment of older and socioeconomically disadvantaged lupus patients.
74• Anderson E, Nietert PJ, Kamen DL, Gilkeson GS. Ethnic disparities among patients with systemic lupus erythematosus in South Carolina. J Rheumatol 2008; 35:819–825. When compared with white people and after controlling for comorbidities, African–American SLE patients in South Carolina had a greater risk of in-hospital mortality and mortality after discharge possibly reflecting the existing inequalities of access and quality of care for people of different ethnic backgrounds.
75 Diez Roux AV. Investigating neighborhood and area effects on health. Am J Public Health 2001; 91:1783–1789.
76 Adler NE, Newman K. Socioeconomic disparities in health: pathways and policies. Health Aff (Millwood) 2002; 21:60–76.
77 Krieger N, Chen JT, Waterman PD, et al. Choosing area based socioeconomic measures to monitor social inequalities in low birth weight and childhood lead poisoning: the Public Health Disparities Geocoding Project (US). J Epidemiol Community Health 2003; 57:186–199.
78 Rodriguez RA, Sen S, Mehta K, et al. Geography matters: relationships among urban residential segregation, dialysis facilities, and patient outcomes. Ann Intern Med 2007; 146:493–501.
79 Losina E, Wright EA, Kessler CL, et al. Neighborhoods matter: use of hospitals with worse outcomes following total knee replacement by patients from vulnerable populations. Arch Intern Med 2007; 167:182–187.
80 Volkova N, McClellan W, Klein M, et al. Neighborhood poverty and racial differences in ESRD incidence. J Am Soc Nephrol 2008; 19:356–364.
81 Ward MM. Socioeconomic status and the incidence of ESRD. Am J Kidney Dis 2008; 51:563–572.
82 Sarzi-Puttini P, Atzeni F, Iaccarino L, Doria A. Environment and systemic lupus erythematosus: an overview. Autoimmunity 2005; 38:465–472.
83 Costenbader KH, Kim DJ, Peerzada J, et al. Cigarette smoking and the risk of systemic lupus erythematosus: a meta-analysis. Arthritis Rheum 2004; 50:849–857.
84 Finckh A, Cooper GS, Chibnik LB, et al. Occupational silica and solvent exposures and risk of systemic lupus erythematosus in urban women. Arthritis Rheum 2006; 54:3648–3654.
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86 Costenbader KH, Feskanich D, Stampfer MJ, Karlson EW. Reproductive and menopausal factors and risk of systemic lupus erythematosus in women. Arthritis Rheum 2007; 56:1251–1262.
87 Ward MM, Studenski S. Clinical prognostic factors in lupus nephritis. The importance of hypertension and smoking. Arch Intern Med 1992; 152:2082–2088.
88 Falk RJ. Treatment of lupus nephritis: a work in progress. N Engl J Med 2000; 343:1182–1183.
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91 de Castro WP, Morales JV, Wagner MB, et al. Hypertension and Afro-descendant ethnicity: a bad interaction for lupus nephritis treated with cyclophosphamide? Lupus 2007; 16:724–730.
92 DuBois WEB. The souls of black folk. Cambridge, MA: University Press; 1903.

health disparities; heath care access; socioeconomic status; systemic lupus erythematosus

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