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Abstract

  1. Top of page
  2. Abstract
  3. PATIENTS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. AUTHOR CONTRIBUTIONS
  7. REFERENCES

Objective

Systemic lupus erythematosus (SLE) and lupus nephritis (LN) disproportionately affect individuals who are members of racial/ethnic minority groups and individuals of lower socioeconomic status (SES). This study was undertaken to investigate the epidemiology and sociodemographics of SLE and LN in the low-income US Medicaid population.

Methods

We utilized Medicaid Analytic eXtract data, with billing claims from 47 states and Washington, DC, for 23.9 million individuals ages 18–65 years who were enrolled in Medicaid for >3 months in 2000–2004. Individuals with SLE (≥3 visits >30 days apart with an International Classification of Diseases, Ninth Revision [ICD-9] code of 710.0) and with LN (≥2 visits with an ICD-9 code for glomerulonephritis, proteinuria, or renal failure) were identified. We calculated SLE and LN prevalence and incidence, stratified by sociodemographic category, and adjusted for number of American College of Rheumatology (ACR) member rheumatologists in the state and SES using a validated composite of US Census variables.

Results

We identified 34,339 individuals with SLE (prevalence 143.7 per 100,000) and 7,388 (21.5%) with LN (prevalence 30.9 per 100,000). SLE prevalence was 6 times higher among women, nearly double in African American compared to white women, and highest in the US South. LN prevalence was higher among all racial/ethnic minority groups compared to whites. The areas with lowest SES had the highest prevalence; areas with the fewest ACR rheumatologists had the lowest prevalence. SLE incidence was 23.2 per 100,000 person-years and LN incidence was 6.9 per 100,000 person-years, with similar sociodemographic trends.

Conclusion

In this nationwide Medicaid population, there was sociodemographic variation in SLE and LN prevalence and incidence. Understanding the increased burden of SLE and its complications in this low-income population has implications for resource allocation and access to subspecialty care.

Systemic lupus erythematosus (SLE) is a complex autoimmune disease whose incidence and prevalence vary substantially by sex, race, ethnicity, and socioeconomic status (1–4). Past estimates of SLE prevalence in the adult US population range from 24 to 150 per 100,000 (1, 5–8, 10–13) and incidence from 2.2 to 5.6 per 100,000 (4, 9, 10, 14) (Table 1). Despite the wide variation in these estimates, rates are consistently higher in women compared to men and in African Americans compared to whites. Prior studies also suggest increased prevalence among Asians, Hispanics, and Native Americans (2, 11–15). To date, however, there have been no US nationwide administrative database examinations of the sociodemographics of adult SLE prevalence or incidence. A number of studies suggest that lupus nephritis (LN), one of the most severe manifestations of SLE, is both more common and more severe in racial and ethnic minorities, and the frequency of progression to end-stage renal disease is increased in minority, uninsured, and low socioeconomic status (SES) groups (3, 15–22). Currently, there are no available studies of the prevalence or incidence of LN in a large low-income US population.

Table 1. Previous estimates of the prevalence and incidence of SLE in the US*
Author, year (ref.)Study method; locationPrevalence estimate per 100,000 adultsIncidence estimate per 100,000 adults
  • *

    SLE = systemic lupus erythematosus; HMO = health maintenance organization; AA = African American; ND = not determined; NHANES-III = Third National Health and Nutrition Examination Survey.

  • This study differentiated between “definite SLE” and “suspected SLE.” Suspected SLE consisted of cases that did not meet American College of Rheumatology SLE criteria (54,55) but were thought to be likely to meet criteria at some point.

Fessel et al, 1974 (1)HMO inpatient and outpatient records; California44 (white adults); 100 (white women); 400 (AA women)ND
Hochberg et al, 1985 (9)First hospitalization discharge diagnosis, age and race adjusted; MarylandND2.2 (white adults); 0.4 (white men); 3.9 (white women); 7.2 (AA adults); 2.5 (AA men); 11.4 (AA women)
McCarty et al, 1995 (4)Medical record review, 3-source capture–recapture technique; PennsylvaniaND2.0 (white adults); 0.4 (white men); 3.5 (white women); 5.3 (AA adults); 0.7 (AA men); 9.2 (AA women)
Maskarinec et al, 1995 (11)Population-based medical records and patient support group; Hawaii55 (white and Japanese adults); 100 (Chinese adults)ND
Jacobson et al, 1997 (5)Pooled from 23 prior studies; North America and Europe23.8 (all adults)ND
Uramoto et al, 1999 (10)Medical record review, age and sex-adjusted; Minnesota130 (all adults)5.56 (overall)
Balluz et al, 2001 (12)Interviews, examination, serology; Arizona103 (Hispanic women)ND
Ward et al, 2004 (7)Self-reported diagnoses and prescriptions, NHANES-III; US53.6 (all adults); 100 (adult women)ND
Naleway et al, 2005 (14)Medical record review; WisconsinND5.1 (overall); 1.9 (adult men); 8.2 (adult women)
Karlson et al, 2007 (13)Medical record review; Massachusetts256 (AA women)ND
Chakravarty et al, 2007 (6)Frequency of hospitalization, discharge diagnoses, chart review; California and Pennsylvania107.6 (all adults, California); 406.3 (AA women, California); 149.5 (all adults, Pennsylvania); 693.7 (all women, Pennsylvania)ND
Helmick et al, 2008 (8)City-based SLE prevalence and 2005 US Census population estimates; US54.3 (definite SLE); 108.6 (suspected SLE)ND

In this study we used nationwide Medicaid claims data to investigate sociodemographic differences in the incidence and prevalence of SLE and LN among US adults. Medicaid is a US federal–state jointly run insurance program that provides health and long-term care coverage to eligible low-income individuals (23). Within this population, we investigated whether county-level SES and the number of rheumatologists per state (approximated based on number of American College of Rheumatology [ACR] members) were related to differences in incidence and prevalence of SLE and LN, and the degree to which these variables could explain variation by race and ethnicity. Our goal was to provide a better understanding of the burden of SLE and LN among low-income, high-risk US adults, which will encourage the necessary allocation of resources for early detection and essential treatment. We hypothesized that there would be significant variation in incidence and prevalence of SLE and LN by sociodemographic group, but that SES and the number of rheumatologists would modify these differences.

PATIENTS AND METHODS

  1. Top of page
  2. Abstract
  3. PATIENTS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. AUTHOR CONTRIBUTIONS
  7. REFERENCES

Study population.

The Medicaid Analytic eXtract (MAX) administrative data system contains billing claims and demographic information for all Medicaid enrollees from 47 states and Washington, DC. Arizona, Tennessee, and Maine do not contribute data to the MAX. Our study population was derived using the MAX and included all adults ages 18– 65 years who were enrolled in Medicaid for at least 3 months between January 1, 2000 and December 31, 2004.

Outcome measures.

Individuals were classified as having SLE if they had ≥3 visits ≥3 days apart with an International Classification of Diseases, Ninth Revision (ICD-9) code for SLE (710.0). ICD-9 coding information was obtained from hospital discharge diagnoses or physician visit claims. We required that the SLE billing code appear for at least 3 visits in order to eliminate “rule-out” SLE cases. Among individuals with SLE, we identified those with LN, defined as the presence of ≥2 ICD-9 hospital discharge diagnoses or physician billing claims for nephritis, proteinuria, and/or renal failure, on or after the SLE diagnosis and at least 30 days apart. This algorithm has been demonstrated to have a positive predictive value of 80% for the identification of adults with LN in a Medicaid population (24). We also performed a sensitivity analysis for LN that used ≥2 SLE claims with the above-mentioned ≥2 LN-related claims.

Other characteristics.

We extracted demographic data, including age, sex, and race/ethnicity, on all Medicaid enrollees. Race/ethnicity (based on self-report) is categorized by Medicaid as white, black or African American, American Indian or Alaskan Native, Asian, Hispanic or Latino, Native Hawaiian or other Pacific Islander, Hispanic or Latino, and one or more races (starting in May 2000), more than one race (starting in May 2000), or unknown. Due to small numbers, in our analysis we utilized the following previously defined, combined categories: white, black or African American, Hispanic or Latino (including Hispanic or Latino and one or more races), Asian (including Native Hawaiian or other Pacific Islander), Native American (including American Indian or Alaskan Native), and other (including unknown) (25). We determined location of residence by ZIP code and US Census region (Northeast, Midwest, South, or West).

From the 2000 US Census (26), we identified 7 socioeconomic indicators at the ZIP code level: median household income, proportion with income below 200% of the federal poverty level, median home value, median monthly rent, mean education level, proportion of people age ≥25 years who were college graduates, and proportion of employed persons with a professional occupation (27).

At our request, the ACR provided data on the number of ACR member rheumatologists practicing per year in each ZIP code in the US between 2000 and 2004. We first aggregated the number of ACR member rheumatologists per ZIP code to the number per county. We found that 80% of counties had no ACR member rheumatologists, 6.8% had only 1 ACR member rheumatologist, and 13.2% had more than 1. We thus aggregated these data to the average number of ACR member rheumatologists per year per state.

Statistical analysis.

We calculated the prevalence of SLE and of LN per 100,000 adults ages 18–65 years who were enrolled in Medicaid between 2000 and 2004, with 95% confidence intervals (95% CIs). Overall prevalence was calculated, stratified by sex, age, race/ethnicity, and US region, and then cross-classified by sex and racial/ethnic group. We used Poisson regression techniques to estimate prevalence rate ratios and corresponding 95% CIs.

To calculate annual incidence rates and 95% CIs for SLE and LN, individuals with newly diagnosed SLE and LN, identified as described above, were included if they had a minimum of 24 months of Medicaid enrollment without any SLE or LN claims. SLE onset was defined as the date of the first claim with a diagnosis of SLE or LN. Individuals contributed to the person-months denominator once they had 24 months of Medicaid enrollment with no SLE-related claims. Once an individual met the billing claim definition for SLE or LN, he or she was censored from the cohort denominator. Average annual incidence rates (per 12 months enrollment) for 2002–2004 were calculated for the total cohort and then stratified by sex, racial/ethnic group, and region. Incidence rate ratios with 95% CIs were calculated using Poisson regression techniques.

As Medicaid patients may have discontinuous coverage, we conducted sensitivity analyses for incidence rate calculations, restricted to adults with 24 months of continuous Medicaid enrollment with no prior SLE-related claims. We also performed sensitivity analyses requiring 36 months of continuous and noncontinuous enrollment with no prior SLE-related claims, to reduce misclassification of prevalent cases.

We defined area-level SES using a previously validated composite score of the above-mentioned US Census variables by ZIP code (27). We aggregated ZIP code–level SES data to the county level and then divided it into quartiles (−1.62 or below, above −1.62 through −0.74, above −0.74 through 0.26, and above 0.26). We adjusted SLE and LN prevalence, prevalence rate ratios, incidence, and incidence rate ratios by these SES quartiles using generalized linear models, and cross-classified by SES and sex, race/ethnicity, and geographic region. We adjusted prevalence in each SES stratum by age, sex, and race/ethnicity. We then performed the Cochran-Armitage trend test to assess for a linear trend across quartiles. We also adjusted SLE and LN prevalence, prevalence rate ratios, incidence, and incidence rate ratios by the number of ACR member rheumatologists per state, categorized by quartiles (fewer than or equal to 13.6, between more than 13.6 and 33.1, between more than 33.1 and 75, and more than 75) and assessed for prevalence and incidence rate ratios and for trend, as above.

All analyses were conducted using SAS, version 9.2. Data were obtained from the Centers for Medicare and Medicaid Services (CMS) through an approved data use agreement and are presented in accordance with CMS policies. The Institutional Review Board of Partners Healthcare waived human subject approval for this study.

RESULTS

  1. Top of page
  2. Abstract
  3. PATIENTS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. AUTHOR CONTRIBUTIONS
  7. REFERENCES

A total of 23,893,092 individuals ages 18–65 years were enrolled in Medicaid from 2000 to 2004. We identified 34,339 individuals with SLE, for an overall prevalence of 143.7 per 100,000. The prevalence of SLE stratified by sociodemographic group is shown in Table 2. SLE prevalence among female Medicaid enrollees was 6 times higher than among male enrollees. Analysis by race/ethnicity revealed that 38.5% of individuals with SLE were African American, 13.9% Hispanic, 4.2% Asian, 1.5% Native American, and 36.2% white. The highest SLE prevalence was in the South (163.5 per 100,000) and the lowest was in the Northeast (125.2 per 100,000). African American women had the highest prevalence of SLE (286.4 per 100,000: nearly twice as high as the prevalence among white women).

Table 2. Prevalence of SLE and LN per 100,000 Medicaid-enrolled adults by sociodemographic group, 2000–2004*
Group or subgroupDenominatorSLELN
Cases (% of total)Prevalence per 100,00095% CICases (% of total)Prevalence per 100,00095% CI
  • *

    SLE = systemic lupus erythematosus; LN = lupus nephritis; 95% CI = 95% confidence interval.

  • Age-range group cases and denominators exceed the total in order to include individuals ages 18–64 years who moved from one age group to another between 2000 and 2004.

  • Using Medicaid categories based on self-report, with some categories combined due to small numbers.

  • §

    As defined in the US Census.

Total23,893,09234,339 (100)143.72142.21–145.257,388 (100)30.9230.22–31.63
Sex
 Female16,665,95632,039 (93.3)192.24190.15–194.366,652 (90.0)39.93138.97–40.88
 Male7,227,1362,300 (6.7)31.8230.55–33.15736 (10.0)10.189.47–10.95
Age, years
 18–2912,366,9829,507 (27.7)76.8775.45–78.433,082 (41.7)24.9224.06–25.82
 30–499,907,52319,848 (57.8)200.33197.56–203.143,703 (50.1)37.3836.19–38.60
 50–643,187,9749,320 (27.1)292.35286.47–298.341,364 (18.5)42.7940.57–45.12
Race/ethnicity
 African American5,923,77513,236 (38.5)223.44219.66–227.283,536 (47.9)59.6957.76–61.69
  Female4,334,63012,413 (36.1)286.37281.37–291.453,233 (43.8)74.5972.06–77.20
  Male1,589,145823 (2.4)51.7948.37–55.45303 (4.1)19.0717.04–21.34
 Hispanic3,767,0024,767 (13.9)126.55123.00–130.191,124 (15.2)29.8428.14–31.63
  Female2,739,0304,461 (13.0)162.87158.16–167.721,011 (13.7)36.9134.70–39.26
  Male1,027,972306 (0.9)29.7726.61–33.30113 (1.5)10.999.14–13.22
 White11,146,71012,436 (36.2)111.57109.62–113.541,765 (23.9)15.8315.11–16.59
  Female7,692,68611,546 (33.6)150.09147.38–152.851,547 (20.9)20.1119.13–21.14
  Male3,454,024890 (2.6)25.7724.13–27.52218 (3.0)6.315.53–7.21
 Asian829,2091,452 (4.2)175.11166.33–184.35469 (6.3)56.5651.67–61.92
  Female527,6691,347 (3.9)255.27242.00–269.28426 (5.8)80.7373.42–88.77
  Male301,540105 (0.3)34.8228.76–42.1643 (0.6)14.2610.58–19.23
 Native American310,736515 (1.5)165.74152.02–180.69113 (1.5)36.3730.24–43.73
  Female220,836471 (1.4)213.28194.86–233.4499 (1.3)44.8336.81–54.59
  Male89,90044 (0.1)48.9436.42–65.7714 (0.2)15.579.22–26.29
 Other1,915,6601,933 (5.6)100.9196.51–105.51381 (5.2)19.8917.99–21.99
  Female1,151,1051,801 (5.2)156.46149.40–163.85336 (4.5)29.1926.23–32.48
  Male764,555132 (0.4)17.2614.56–20.4845 (0.6)5.894.39–7.88
Geographic region§
 South7,999,87713,078 (38.1)163.48160.79–166.302,877 (38.9)35.9634.67–37.30
 Northeast5,843,2797,318 (21.3)125.24122.40–128.141,564 (21.2)26.7725.47–28.13
 Midwest4,708,8566,430 (18.7)136.55133.25–139.931,442 (19.5)30.6229.08–32.25
 West5,341,0807,513 (21.9)140.66137.52–143.881,505 (20.4)28.1826.79–29.64

We identified 7,388 individuals with LN, with a prevalence of 30.9 per 100,000 (Table 2). The prevalence of LN was 4 times higher among female Medicaid enrollees compared to male enrollees and nearly 4 times higher among African Americans compared to whites. LN prevalence was also highest in the South, and among African American women (74.59 per 100,000) and Asian women (80.73 per 100,000). Our sensitivity analysis, which required ≥2 SLE claims rather than the original ≥3, resulted in an overall LN prevalence of 34.1 per 100,000, or 8,158 cases.

From 2002 to 2004, the average annual incidence rate of SLE in this Medicaid population was 23.17 per 100,000 person-years. The average incidence rate of LN was 6.85 per 100,000 person-years. Incidence rates by sociodemographic group are presented in Table 3. The incidence of SLE was higher in both the 30–49-year and the 50–64-year age groups compared to the youngest stratum. SLE incidence was highest among African American women (38.62 per 100,000 person-years) and Native American women (37.31 per 100,000 person-years). Similar to the findings with regard to prevalence, the South had the highest incidence of SLE compared to other geographic regions. The incidence of LN was also highest in the older age groups, in women, and in African Americans. The results of our 3 sensitivity analyses for SLE and LN with varying times of enrollment, both continuous and noncontinuous, yielded incidence rates comparable to those observed in our main analyses (data available from the corresponding author upon request).

Table 3. Incidence of SLE and LN per 100,000 person-years among Medicaid-enrolled adults by sociodemographic group, 2002–2004*
Group or subgroupDenominator, person-yearsSLELN
Cases (% of total)Incidence rate per 100,000 person-years95% CICases (% of total)Incidence rate per 100,000 person-years95% CI
  • *

    NR = not reported (data on groups that included ≤10 individuals were not reported in order to protect privacy) (see Table 2 for other definitions).

  • Using Medicaid categories based on self-report, with some categories combined due to small numbers.

  • As defined in the US Census.

Total15,064,9373,490 (100)23.1722.41–23.951,034 (100)6.856.44–7.28
Sex
 Female10,774,9053,282 (94.0)30.4629.44–31.52971 (93.9)8.988.43–9.56
 Male4,290,031208 (6.0)4.854.23–5.5563 (6.1)1.471.15–1.88
Age, years
 18–295,650,736807 (23.1)14.2813.33–15.30291 (28.1)5.144.59–5.77
 30–496,426,8601,795 (51.4)27.9326.67–29.25485 (46.9)7.526.88–8.22
 50–642,987,340888 (25.4)29.7327.83–31.75258 (25.0)8.607.61–9.72
Race/ethnicity
 African American4,501,6761,404 (40.2)31.1929.60–32.86481 (46.5)10.659.74–11.65
  Female3,428,0041,324 (37.9)38.6236.60–40.76462 (44.7)13.4312.26–14.71
  Male1,073,67280 (2.3)7.455.98–9.2819 (1.8)1.771.13–2.77
 Hispanic2,278,325506 (14.5)22.2120.36–24.23157 (15.2)6.885.88–8.04
  Female1,703,102485 (13.9)28.4826.05–31.13151 (14.6)8.847.54–10.37
  Male575,22421 (0.6)3.652.38–5.60NRNRNR
 White6,524,8501,172 (33.6)17.9616.96–19.02266 (25.7)4.073.61–4.59
  Female4,514,8421,101 (31.5)24.3922.99–25.87239 (23.1)5.284.65–5.99
  Male2,010,00871 (2.0)3.532.80–4.4627 (2.6)1.340.92–1.96
 Asian713,474119 (3.4)16.6813.94–19.9639 (3.8)5.463.99–7.47
  Female449,005108 (3.1)24.0519.92–29.0534 (3.3)7.565.40–10.57
  Male264,46911 (0.3)4.162.30–7.51NRNRNR
 Native American156,63947 (1.3)30.0122.54–39.9411 (1.1)7.003.88–12.64
  Female115,24043 (1.2)37.3127.67–50.3111 (1.1)9.515.26–17.17
  MaleNRNRNRNRNRNRNR
 Other889,974242 (6.9)27.1923.97–30.8480 (7.7)8.957.19–11.15
  Female564,714221 (6.3)39.1334.30–44.6574 (7.2)13.0310.37–16.36
  Male325,26021 (0.6)6.464.21–9.90NRNRNR
Geographic region
 South3,872,0321,077 (30.9)27.8126.20–29.53353 (34.1)9.098.19–10.09
 Northeast4,243,303875 (25.1)20.6219.30–22.03230 (22.2)5.414.75–6.16
 Midwest2,987,033611 (17.5)20.4618.90–22.14198 (19.1)6.615.75–7.60
 West3,962,569927 (26.6)23.3921.94–24.95253 (22.7)6.375.63–7.20

We investigated the overall prevalence and incidence of SLE and LN by quartile of county-level SES and number of ACR member rheumatologists per state, using both crude analyses and analyses adjusted for age, sex, and race/ethnicity. Stratified SLE and LN prevalence estimates by SES are displayed in Figure 1; incidence did not vary significantly by SES quartile. We found statistically significant differences in prevalence between the lowest SES group, which had the highest SLE prevalence (167.9 per 100,000 [95% CI 160.4–175.7]) and the 2 highest SES quartiles, which had the lowest SLE prevalence. We observed a similar pattern after adjusting for age, sex, and race/ethnicity, with the highest prevalence in the lowest SES group (104.9 per 100,000 [95% CI 99.8–110.3]). The difference in prevalence between the 2 lowest and the 2 highest SES strata was small; however, we noted a trend of decreased SLE prevalence with increased SES (P = 0.001 by Cochran-Armitage test for linear trend). The trend of LN prevalence did not differ significantly across SES quartiles (P = 0.98).

thumbnail image

Figure 1. Prevalence of systemic lupus erythematosus (SLE) and lupus nephritis (LN) per 100,000 US Medicaid enrollees ages 18– 65 years, stratified by socioeconomic status (SES) quartile (SES 1 [lowest] = −1.62 or below, SES 2 = above −1.62 through −0.74, SES 3 = above −0.74 through 0.26, SES 4 [highest] = above 0.26). Results of crude analyses and analyses adjusted for age group, sex, and race/ethnicity are shown. Bars represent 95% confidence intervals.

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Stratification by the average number of ACR member rheumatologists per state in quartiles showed that areas with the fewest rheumatologists had the lowest prevalence of both SLE (127.7 per 100,000 [95% CI 119.4–136.5]) and LN (24.7 per 100,000 [95% CI 21.2–28.8]) (Figure 2). The test for linear trend across quartiles of rheumatologists per state yielded significant results for both SLE prevalence (P = 0.02) and LN prevalence (P = 0.03). However, after adjustment of the SLE and LN estimates for age, sex, and race/ethnicity, this trend was no longer observed. Differences in incidence estimates stratified by number of rheumatologists were not statistically significant.

thumbnail image

Figure 2. Prevalence of systemic lupus erythematosus (SLE) and lupus nephritis (LN) per 100,000 US Medicaid enrollees ages 18– 65 years, stratified by number of American College of Rheumatology member rheumatologists per state (RS), by quartile (RS 1 [lowest] = fewer than or equal to 13.6, RS 2 = between more than 13.6 and 33.1, RS 3 = between more than 33.1 and 75, RS 4 [highest] = more than 75). Results of crude analyses and analyses adjusted for age group, sex, and race/ethnicity are shown. Bars represent 95% confidence intervals.

Download figure to PowerPoint

We calculated prevalence rate ratios and incidence rate ratios with 95% CIs for both SLE and LN, to compare rates between sociodemographic groups (Table 4). The crude rate ratios demonstrated significantly increased prevalence and incidence of SLE and LN among female Medicaid enrollees compared to male enrollees and among African American enrollees compared to white enrollees. Table 4 also shows prevalence and incidence rate ratios adjusted by SES and rheumatologists-per-state quartiles (both separately for the two measures and combined). There were no statistically significant differences in the rate ratios by sex, race/ethnicity, or region after adjustment for SES, number of rheumatologists, or both.

Table 4. SLE and LN prevalence rate ratios and incidence rate ratios among Medicaid-enrolled adults, with and without adjustment for SES and for number of rheumatologists in the state*
Condition, group or subgroupPrevalence rate ratio (95% CI)Incidence rate ratio (95% CI)
CrudeAdjusted for SESAdjusted for no. of rheumatologists in stateAdjusted for SES and no. of rheumatologists in stateCrudeAdjusted for SESAdjusted for no. of rheumatologists in stateAdjusted for SES and no. of rheumatologists in state
  • *

    Socioeconomic status (SES) and number of rheumatologists in the state (determined based on the number of American College of Rheumatology members) were assessed by quartile. See Table 2 for other definitions.

  • Using Medicaid categories based on self-report, with some categories combined due to small numbers.

  • As defined in the US Census.

SLE
 Sex
  MaleReferentReferentReferentReferentReferentReferentReferentReferent
  Female6.04 (5.79–6.30)6.04 (5.79–6.30)6.03 (5.79–6.29)6.03 (5.78–6.29)6.28 (5.25–7.23)6.29 (5.47–7.24)6.26 (5.44–7.21)6.27 (5.45–7.21)
 Race/ethnicity
  WhiteReferentReferentReferentReferentReferentReferentReferentReferent
  African American2.00 (1.95–2.05)2.03 (1.99–2.09)2.01 (1.96–2.06)2.03 (1.98–2.08)1.74 (1.61–1.88)1.75 (1.62–1.90)1.76 (1.62–1.90)1.76 (1.63–1.90)
  Hispanic1.13 (1.10–1.17)1.18 (1.14–1.22)1.17 (1.13–1.21)1.19 (1.15–1.23)1.24 (1.11–1.37)1.24 (1.11–1.38)1.28 (1.15–1.43)1.27 (1.14–1.42)
  Asian1.57 (1.49–1.66)1.64 (1.56–1.74)1.61 (1.52–1.70)1.66 (1.57–1.76)0.93 (0.77–1.12)0.93 (0.77–1.13)0.95 (0.78–1.15)0.94 (0.77–1.13)
  Native American1.49 (1.36–1.62)1.46 (1.34–1.59)1.47 (1.35–1.61)1.46 (1.33–1.60)1.67 (1.25–2.24)1.67 (1.23–2.23)1.59 (1.19–2.14)1.60 (1.19–2.15)
 Geographic region
  NortheastReferentReferentReferentReferentReferentReferentReferentReferent
  South1.30 (1.27–1.34)1.34 (1.29–1.38)1.29 (1.25–1.32)1.33 (1.29–1.37)1.35 (1.23–1.47)1.49 (1.34–1.65)1.32 (1.20–1.45)1.45 (1.30–1.62)
  West1.12 (1.09–1.16)1.17 (1.12–1.21)1.13 (1.10–1.17)1.18 (1.14–1.22)1.13 (1.03–1.24)1.17 (1.05–1.30)1.14 (1.03–1.25)1.17 (1.05–1.30)
  Midwest1.09 (1.05–1.13)1.12 (1.08–1.16)1.07 (1.03–1.11)1.10 (1.07–1.15)0.99 (0.89–1.10)1.07 (0.96–1.20)0.97 (0.88–1.08)1.05 (0.93–1.18)
LN
 Sex
  MaleReferentReferentReferentReferentReferentReferentReferentReferent
  Female3.92 (3.63–4.23)3.92 (3.64–4.23)3.92 (3.62–4.23)3.92 (3.63–4.23)6.12 (4.74–7.89)6.15 (4.77–7.93)6.07 (4.70–7.83)6.09 (4.72–7.86)
 Race/ethnicity
  WhiteReferentReferentReferentReferentReferentReferentReferentReferent
  African American3.77 (3.56–3.99)3.84 (3.63–4.07)3.77 (3.56–4.00)3.82 (3.61–4.05)2.61 (2.25–3.04)2.62 (2.26–3.05)2.63 (2.26–3.06)2.61 (2.24–3.04)
  Hispanic1.88 (1.75–2.03)1.96 (1.81–2.11)1.93 (1.79–2.09)1.98 (1.83–2.14)1.69 (1.39–2.06)1.70 (1.39–2.08)1.80 (1.47–2.01)1.77 (1.45–2.18)
  Asian3.57 (3.23–3.95)3.74 (3.37–4.16)3.65 (3.29–4.04)3.78 (3.40–4.20)1.34 (0.96–1.88)1.33 (0.95–1.88)1.41 (1.01–1.99)1.37 (0.97–1.92)
  Native American2.30 (1.90–2.78)2.25 (1.86–2.72)2.29 (1.89–2.77)2.26 (1.87–2.74)1.72 (0.94–3.14)1.67 (0.92–3.06)1.66 (0.90–2.05)1.62 (0.88–2.98)
 Geographic region       
  NortheastReferentReferentReferentReferentReferentReferentReferentReferent
  South1.34 (1.26–1.43)1.41 (1.32–1.51)1.36 (1.28–1.45)1.43 (1.33–1.53)1.68 (1.42–1.98)1.80 (1.49–2.18)1.65 (1.39–1.97)1.73 (1.42–2.11)
  West1.05 (0.98–1.13)1.04 (0.97–1.12)1.08 (1.00–1.15)1.07 (0.99–1.16)1.18 (0.99–1.41)1.08 (0.89–1.33)1.20 (1.00–1.43)1.09 (0.89–1.33)
  Midwest1.14 (1.07–1.23)1.20 (1.11–1.30)1.15 (1.07–1.23)1.20 (1.11–1.30)1.22 (1.01–1.48)1.25 (1.02–1.54)1.19 (0.98–1.44)1.20 (0.97–1.48)

DISCUSSION

  1. Top of page
  2. Abstract
  3. PATIENTS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. AUTHOR CONTRIBUTIONS
  7. REFERENCES

In the present study we used national Medicaid claims data to investigate sociodemographic variation in SLE and LN, and the impact of SES and rheumatologist number on disease prevalence and incidence. We found the overall prevalence of SLE to be 143.7 per 100,000 adults, which is slightly greater than prior US-based estimates (Table 1), but is in accordance with what would be expected in the high-risk population included in this study. The prevalence of LN was 30.9 per 100,000, or 21.5% of SLE cases, with higher rates among all racial/ethnic minority groups compared to whites. The prevalence of LN observed in this study, particularly among African Americans (26.7% of SLE cases), is lower than prior estimates (20). This may be a reflection of the short followup period of the study, or of underdiagnosis among low-income patients with public insurance, a group previously shown to have limited access to subspecialty care (19). We found the incidence of SLE to be 23 per 100,000 person-years, notably higher than prior US-based estimates, but consistent in multiple sensitivity analyses. Both prevalence and incidence of SLE and of LN varied considerably among demographically, socioeconomically, and geographically defined subgroups.

A complex interplay of genetic, hormonal, environmental, and socioeconomic factors likely contributes to the incidence and prevalence of SLE, and to variations by sex, race/ethnicity, and income level (28, 29). Genetic differences by race have been invoked to explain the younger age at onset of SLE among African Americans, and the higher prevalence of serologic abnormalities in African Americans compared to whites (4, 9, 30). In addition to genetics, however, occupational and environmental exposures may relate to the risk of SLE development (13, 28, 29, 31, 32). Low SES neighborhoods are often in closer proximity to hazardous wastes and experience more air pollution (33), and workplace exposures, particularly to silica dust, are more likely from manual labor jobs. Risk of SLE is likely higher among current cigarette smokers, and rates of smoking are higher in poorer populations (34, 35). A relationship between psychosocial stress and the development of autoimmune diseases such as SLE has been suggested (36), and there are known associations between residence in a high-poverty neighborhood and increased stress (37).

The US Medicaid population is a high-poverty group, with significant racial and ethnic minority representation and a considerable burden of chronic diseases. Prior studies have demonstrated that living in a low SES area confers increased risk of progressive chronic illnesses and an additional mortality risk (38–41). After stratifying Medicaid enrollees by SES quartile and adjusting for age, sex, and race/ethnicity, we found that the quartile with the lowest county-level SES had the highest prevalence of both SLE and LN. Although there are no previous studies of prevalence of SLE according to SES, a relationship between poverty and increased SLE severity and mortality, independent of race and ethnicity, has been demonstrated (2, 42–44). Chronic disease and poor health likely also contribute to lower SES because of disability, missed work, and decreased earning potential (45). The trend of decreasing prevalence with increasing SES was statistically significant for SLE but not for LN. This suggests that genetics may be a more important determinant in the development of LN compared to SLE. It is also possible that once individuals enter the health care system for their SLE, socioeconomic factors contribute less to disease complications.

Neither SLE nor LN incidence was strongly related to county-level SES. Similarly, prevalence and incidence rate ratios were not significantly different after stratification by sociodemographic group and adjustment for SES. The Medicaid population is enriched for lower SES compared to the overall US population, and therefore, variation by degree of poverty may be less pronounced. It is also plausible that the relatively small sample size within each of the stratified groups reduced the possibility of detecting subtle differences.

We also demonstrated a relationship between the average number of ACR member rheumatologists per state and the prevalence of SLE and LN, suggesting that access to subspecialty care may play a role in both diagnosis and management. Lower income, even when adjusted for health insurance status, has been associated with decreased access to rheumatologic care (46). A previous study showed that individuals with SLE who were older and poorer were significantly less likely to identify a rheumatologist as their primary provider for the disease (46). African Americans, and women in particular, were also shown to have significantly fewer visits to a rheumatologist compared to white men (47). We found the lowest prevalence of SLE and LN in the areas with the fewest rheumatologists and a statistically significant trend toward higher disease prevalence in areas with more rheumatologists. However, after adjustment for age, sex, and race/ethnicity, this trend was no longer observed. Our analysis parallels a recent study whose results suggested that subspecialty care might modify the relationship between race and receipt of appropriate medications among individuals with rheumatoid arthritis (48).

In accordance with the findings of earlier studies, our SLE prevalence and incidence estimates were significantly higher in women compared to men. The incidence of LN paralleled that of SLE, with both being 6 times higher in women than men, whereas the prevalence of LN was only 4 times higher in women than men. Male patients with LN have more significant renal dysfunction and laboratory abnormalities than do female patients (49, 50). Health care providers may be more likely to suspect SLE in female patients than among male patients, and women therefore may be diagnosed earlier, with less severe disease. It is also possible that the stringent definition of LN we used restricted inclusion to the most severe cases and shifted the observed female-to-male ratio downward.

There are other limitations to administrative database analyses. A previous Canadian-based study utilized 2 SLE billing diagnoses at least 2 months apart to determine prevalence and incidence of SLE and demonstrated a sensitivity of 98.2% and a specificity of 72.5% for this method (51). In the present study we raised this to 3 billing diagnoses in an attempt to increase specificity, to account for the inability to differentiate between provider specialties in this Medicaid database, and to exclude individuals who were seen for one “rule-out” SLE visit and once in followup. Given our more stringent definition of SLE, it is plausible that the higher prevalence of SLE found in our investigation compared to prior studies is a reflection of the increased disease burden in this high-risk population.

A validation study using adult Medicaid enrollees showed an 80% positive predictive value for correctly identifying LN cases with the ICD-9 diagnostic codes we utilized (24). Diagnoses of both SLE and renal disease were required for classification of an individual as having LN, although these diagnoses could occur simultaneously. Thus, it is possible that cases were excluded if the combination of ICD-9 codes for both SLE and renal disease did not appear. While the prevalence of LN did not vary substantially in a sensitivity analysis in which fewer visits with a diagnosis of SLE were required, some cases may have been missed given the duration of Medicaid enrollment necessary to accumulate the required codes.

The incidence rates found in the present analysis may be higher than in prior studies as only 5 years of billing claims data were available. Sensitivity analyses utilizing 24–36 months of prior disease-free continuous and noncontinuous enrollment yielded similar incidence rates. Given fluctuations in Medicaid coverage, however, it is possible that a proportion of these incident cases may have been misclassified prevalent cases. These incidence rates therefore reflect the number of new SLE cases without a prior diagnosis while the individual was enrolled in Medicaid during the study period, which is not necessarily generalizable to the incidence of SLE in the US population.

Our study was also constrained by Medicaid's prespecified categories for race and ethnicity, which we had to further combine into related groups to allow for sample sizes that were large enough for analysis. However, prior studies have shown different risks between individuals categorized within the same racial/ethnic group, for example, between African Americans of varying degrees of European ancestry, and among Hispanics with higher Native American ancestry (52). Crossover between the groups may have reduced even more significant variations.

In addition, we utilized data from the ACR to approximate the number of practicing rheumatologists per state. A previous study used a combination of American Medical Association records and ACR records and determined that in 2005, there were 5,164 total US rheumatologists (53); in 2005, 4,146 (80.3%) were ACR members. To our knowledge, there were no significant temporal changes between 2000 and 2004 that would contribute to a different percentage of ACR membership compared to 2005. We do note, however, that the percentage of rheumatologists who do not choose to be ACR members may not be evenly distributed geographically, and this is a limitation of the present study.

In summary, we have examined the incidence and prevalence of SLE and LN in a nationwide Medicaid database with information on nearly 24 million racially, ethnically, and geographically diverse individuals. The prevalence of disease was highest among Medicaid enrollees from the lowest SES areas. Prevalence was lowest in areas with the fewest ACR member rheumatologists, suggesting underdiagnosis and likely unequal access to treatment. Medicaid enrollees are among the poorest subset of the US population. It is clear that increased resources need to be allocated to this group to target this heightened burden of chronic disease.

AUTHOR CONTRIBUTIONS

  1. Top of page
  2. Abstract
  3. PATIENTS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. AUTHOR CONTRIBUTIONS
  7. REFERENCES

All authors were involved in drafting the article or revising it critically for important intellectual content, and all authors approved the final version to be published. Dr. Feldman had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study conception and design. Feldman, Hiraki, Costenbader.

Acquisition of data. Feldman, Costenbader.

Analysis and interpretation of data. Feldman, Hiraki, Liu, Fischer, Solomon, Alarcón, Winkelmayer, Costenbader.

REFERENCES

  1. Top of page
  2. Abstract
  3. PATIENTS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. AUTHOR CONTRIBUTIONS
  7. REFERENCES