Visual Abstract
Keywords: clinical epidemiology, glomerular disease, kidney biopsy, lupus nephritis, ANCA, male, female, humans, focal segmental glomerulosclerosis, membranous glomerulonephritis, IGA glomerulonephritis, antineutrophil cytoplasmic antibodies, incidence, risk factors, censuses, British Columbia, confidence intervals, retrospective studies, glomerulonephritis, kidney, biopsy, chronic renal insufficiency, socioeconomic factors
Abstract
Background and objectives
Social deprivation is a recognized risk factor for undifferentiated CKD; however, its association with glomerular disease is less well understood. We sought to investigate the relationship between socioeconomic position and the population-level incidence of biopsy-proven glomerular diseases.
Design, setting, participants, & measurements
In this retrospective cohort study, a provincial kidney pathology database (2000–2012) was used to capture all incident cases of membranous nephropathy (n=392), IgA nephropathy (n=818), FSGS (n=375), ANCA-related GN (ANCA-GN, n=387), and lupus nephritis (n=389) in British Columbia, Canada. Quintiles of area-level household income were used as a proxy for socioeconomic position, accounting for regional differences in living costs. Incidence rates were direct standardized to the provincial population using census data for age and sex and were used to generate standardized rate ratios. For lupus nephritis, age standardization was performed separately in men and women.
Results
A graded increase in standardized incidence with lower income was observed for lupus nephritis (P<0.001 for trend in both sexes) and ANCA-GN (P=0.04 for trend). For example, compared with the highest quintile, the lowest income quintile had a standardized rate ratio of 1.7 (95% confidence interval, 1.19 to 2.42) in women with lupus nephritis and a standardized rate ratio of 1.5 (95% confidence interval, 1.09 to 2.06) in ANCA-GN. The association between income and FSGS was less consistent, in that only the lowest income quintile was associated with a higher incidence of disease (standardized rate ratio, 1.55; 95% confidence interval, 1.13 to 2.13). No significant associations were demonstrated for IgA nephropathy or membranous nephropathy.
Conclusions
Using population-level data and a centralized pathology database, we observed an inverse association between socioeconomic position and the standardized incidence of lupus nephritis and ANCA-GN.
Introduction
Socioeconomic position is an important contributor to the incidence of major health problems, including cardiovascular disease (1,2) and diabetes (3), and is a powerful predictor of mortality (4). Lower socioeconomic position has been consistently associated with CKD, whether investigated in adulthood or throughout the life course (5–7). As a construct, socioeconomic position encompasses a number of susceptibilities that could contribute to an individual’s disease risk (8). For kidney disease, these may include perinatal health, early life weight gain, and access to preventative health measures (9). Some proposed mediating factors such as obesity could be modifiable (10). Hence, a granular understanding of the relationship between socioeconomic position and kidney disease could inform future research and health policy, such as targeted screening for CKD (11).
There is a surprising lack of data regarding socioeconomic position and specific types of kidney disease, including glomerular disease. Studies have shown an association between socioeconomic position and systemic conditions that may involve the kidney, such as SLE, but not necessarily with biopsy-proven glomerular involvement (12). It is important to accurately ascertain the relationship between socioeconomic position and glomerular diseases for a number of reasons. Individuals with lower socioeconomic position represent a vulnerable population that is predisposed to other chronic diseases that can complicate the management of their glomerular disease. Socioeconomic deprivation is associated with less social support and reduced access to care, important factors for rare diseases that require highly specialized care for optimal delivery of expensive immune therapies (13). Finally, establishing a link between socioeconomic position and specific glomerular diseases could inform future research regarding pathogenesis.
We hypothesized that lower socioeconomic position may be associated with a higher population-level incidence of specific glomerular diseases. We tested this using a centralized kidney pathology database in a large Canadian province with universal access to health care services, leveraging census data to adjust for age and sex, and using household income as a proxy for socioeconomic position.
Materials and Methods
Study Design
This was a retrospective, population-level cohort study of individuals with incident glomerular disease diagnosed from a native kidney biopsy between January 1, 2000 and December 31, 2012 in British Columbia, Canada. All kidney biopsy specimens in mainland British Columbia during the study period were processed in a single tertiary referral laboratory, registered in the British Columbia Renal Pathology database, and analyzed by one of two kidney histopathologists who prospectively recorded the primary diagnosis using a standardized coding system (14). We included patients with membranous nephropathy, IgA nephropathy, and FSGS. We restricted cases to those with a higher likelihood of immune etiology by excluding patients with an identifiable underlying cause (infection, hypertension, diabetes, another glomerular disease, or systemic autoimmune disease) on the basis of histologic features and clinical data provided at the time of biopsy. We also included patients with lupus nephritis and ANCA-related GN (ANCA-GN). In patients with multiple biopsies showing the same glomerular disease, only the first was considered. We excluded patients with missing data for income (Figure 1). Approval for this study was granted by the research ethics board of the University of British Columbia.
Figure 1.
Flowchart of case ascertainment.
Data Sources
The provincial kidney pathology database contains biopsy information and clinical data at the time of biopsy. Using a unique patient identifier, the pathology database was linked to the British Columbia Renal Agency, a government-funded organization responsible for the provincial delivery of care to patients with kidney disease. All patients receiving KRT or attending multidisciplinary kidney disease clinics are registered in a provincial health administrative database that collects clinical and laboratory data for all registered patients. Additional laboratory data were obtained via linkage to hospital-based and community-based laboratories. Provincial population size and distributions of age, sex, and socioeconomic position were taken from the 2001, 2006, and 2011 census provided by Statistics Canada.
Socioeconomic position at the dissemination area-level was on the basis of income per single-person equivalent from the census data in 2001, 2006, and 2011, accounting for regional differences in the cost of living and categorized into quintiles (see Supplemental Appendix 1 for further details). Dissemination areas are small geographic units used for census purposes that cover all of British Columbia. Each patient in the kidney pathology database was assigned to a dissemination area on the basis of the postal code of their location of residence in the year of their biopsy and thereby assigned the corresponding dissemination area-level income quintile on the basis of data from the closest census year. Area-level income has been used in other studies and has been found to be a reasonable proxy for household income in the Canadian population (15,16). Location of residence was identified from the Ministry of Health Medical Services Plan database, a health insurance plan that provides coverage for all residents of British Columbia (17). Data linkage of patient-level information was conducted by Population Data BC (https://www.popdata.bc.ca/datalinkage) at the University of British Columbia. All data were deidentified before creation of the analytical data set.
Statistical Analyses
The analysis was conducted using SAS version 9.4 (SAS Institute Inc., Cary, NC). Continuous variables are presented as mean (SD) or median (interquartile range) as appropriate. Frequencies are reported as percentages. Age- and sex-stratified population estimates within each socioeconomic position quintile were taken from census data in 2001, 2006, and 2011, which were extrapolated to other calendar years using estimates from the closest census year. The crude rate of each glomerular disease was calculated by dividing the number of cases observed during the study period in a given socioeconomic position quintile by the sum of all person-years in that quintile from the population estimates.
Incidence rates were subsequently direct standardized using categories of age and sex. We chose, as the standard population, the provincial population in 2006 because this was the midpoint of the study period. For standardization, age cut-offs were chosen to ensure a sufficient number of cases in each age band. The age bands for IgA nephropathy and FSGS were <25, 25–44, 45–64, and ≥65 years. For membranous nephropathy and ANCA-GN, we used the following age bands: ≤44, 45–64, and ≥65 years. Lupus nephritis was analyzed separately in men and women because of the female predominance in disease. In women, three age bands were used: <25, 25–44, and ≥45 years. Because of the lower counts in men, we used a binary age category: <25 and ≥25 years. A test for trend was used to determine if standardized rates were increasing or decreasing across socioeconomic position quintiles. Differences in standardized rates for each socioeconomic position quintile versus the reference (highest) quintile were tested using standardized rate ratios and associated 95% confidence intervals (95% CIs) (18). A two-sided P value <0.05 was considered statistically significant.
Results
Cohort Description
A total of 2361 patients were included (Figure 1): 392 with membranous nephropathy, 818 with IgA nephropathy, 375 with FSGS, 387 with ANCA-GN, and 389 with lupus nephritis. A description of the British Columbia population is provided in Supplemental Table 1. Patient characteristics at the time of biopsy, stratified by glomerular disease, are summarized in Table 1. The majority of patients had laboratory data available (see Supplemental Table 2 for a description of missing data). Patients with membranous nephropathy had the highest proteinuria, whereas patients with ANCA-GN had the most severe reductions in eGFR. Patients with FSGS had substantial proteinuria, with 40% of patients having >4 g/d. Values for eGFR and proteinuria at the time of biopsy were not statistically significantly different across socioeconomic position quintiles for any of the glomerular diseases (Table 2), suggesting the threshold to perform a kidney biopsy and access to nephrology care did not vary substantially by socioeconomic position.
Table 1.
Characteristics of patients with biopsy-proven glomerular disease and available data for area-level household income in British Columbia, Canada
| Characteristic | Membranous Nephropathy | IgA Nephropathy | ANCA-Related GN | Lupus Nephritis | FSGS |
|---|---|---|---|---|---|
| N | 392 | 818 | 387 | 389 | 375 |
| Age, yr | 56 (17) | 44 (15) | 61 (18) | 35 (14) | 49 (20) |
| Male sex, n (%) | 223 (57) | 499 (61) | 170 (44) | 66 (17) | 218 (58) |
| Race/ethnicity, n (%) | |||||
| White | 103 (45) | 204 (35) | 140 (54) | 51 (18) | 149 (52) |
| Asian | 57 (25) | 284 (48) | 44 (17) | 169 (59) | 63 (22) |
| South Asian | 53 (23) | 70 (12) | 23 (9) | 37 (13) | 40 (14) |
| Aboriginal | 10 (4) | 18 (3) | 44 (17) | 11 (4) | 11 (4) |
| Other | 5 (3) | 15 (2) | 9 (3) | 18 (6) | 24 (8) |
| Creatinine, mg/dl | 1.0 [0.8–1.4] | 1.4 [1.0–2.1] | 3.0 [1.9–4.6] | 1.0 [0.7–1.5] | 1.5 [1.0–2.5] |
| eGFR, ml/min per 1.73 m2 | 77 [46–97] | 57 [32–79] | 17 [11–30] | 77 [47–106] | 42 [23–76] |
| Mean arterial pressure, mm Hg | 97 (15) | 101 (15) | 95 (15) | 96 (17) | 101 (17) |
| Albumin, g/dl | 2.6 (0.8) | 3.8 (0.6) | 3.2 (0.7) | 2.9 (0.8) | 3.4 (0.9) |
| Proteinuria, g/d | 7.0 [3.0–9.0] | 1.6 [0.8–3.0] | 1.2 [0.6–2.2] | 2.4 [1.2–4.0] | 2.8 [1.4–5.6] |
Numbers expressed as mean (SD) or median [interquartile range] unless otherwise stated. (1) Laboratory data and BP were taken as the closest values within 6 months of the biopsy. (2) Daily protein excretion was measured by 24-hour urine collection or estimated from urine albumin- and protein-to-creatinine ratios (see Supplemental Appendix 2 for details). (3) GFR was estimated from provincially standardized creatinine measurements using the CKD Epidemiology Collaboration formula (44). (4) Race/ethnicity was captured from multiple sources: self-report, country of origin, and patient surname to impute Chinese or South Asian ethnicity (45).
Table 2.
Median (interquartile range) values of eGFR (in ml/min per 1.73 m2) and proteinuria (in g/d) by quintile of socioeconomic position
| Parameter | Quintile 1 (Lowest) | Quintile 2 | Quintile 3 | Quintile 4 | Quintile 5 (Highest) | P Valuea |
|---|---|---|---|---|---|---|
| Membranous nephropathy | ||||||
| eGFR | 83 (43–102) | 77 (46–92) | 74 (39–96) | 75 (53–97) | 78 (49–96) | 0.82 |
| Proteinuria | 5.6 (3.3–9.0) | 5.4 (3.6–8.7) | 6.1 (2.8–8.7) | 5.8 (2.9–10.0) | 5.7 (3.0–8.3) | 0.99 |
| IgA nephropathy | ||||||
| eGFR | 56 (35–83) | 52 (27–82) | 54 (30–76) | 58 (36–83) | 57 (33–72) | 0.75 |
| Proteinuria | 1.4 (0.8–3.2) | 1.6 (0.8–3.0) | 1.6 (0.8–3.0) | 1.7 (0.8–2.9) | 1.7 (0.9–3.2) | 0.92 |
| FSGS | ||||||
| eGFR | 45 (22–86) | 47 (24–71) | 47 (22–80) | 33 (22–50) | 42 (28–67) | 0.39 |
| Proteinuria | 3 (1.6–5.6) | 3 (1.1–5.3) | 2.6 (1.3–4.1) | 2.7 (1.3–6.0) | 3 (1.1–6.0) | 0.83 |
| ANCA-related GN | ||||||
| eGFR | 18 (11–32) | 16 (11–25) | 20 (11–34) | 16 (10–31) | 18 (11–32) | 0.61 |
| Proteinuria | 1.2 (0.6–2.3) | 1.2 (0.5–2.0) | 1.4 (0.9–2.4) | 0.9 (0.4–2.1) | 0.9 (0.6–2.2) | 0.23 |
| Lupus nephritis | ||||||
| eGFR | 74 (47–102) | 81 (39–105) | 84 (57–116) | 70 (45–107) | 79 (42–107) | 0.48 |
| Proteinuria | 1.9 (1.0–4.2) | 2.6 (1.5–4.0) | 2.6 (1.1–4.0) | 2.9 (1.4–4.3) | 2.0 (0.9–3.8) | 0.64 |
Kruskal–Wallis test for difference across quintiles of socioeconomic position.
Socioeconomic Position and the Incidence of Glomerular Disease
The overall crude incidence rate per 100,000 person-years was 0.90 (95% CI, 0.81 to 0.99) for membranous nephropathy, 1.88 (95% CI, 1.75 to 2.01) for IgA nephropathy, 0.86 (95% CI, 0.78 to 0.95) for FSGS, 0.89 (95% CI, 0.80 to 0.98) for ANCA-GN, 1.46 (95% CI, 1.30 to 1.62) for lupus nephritis in women, and 0.31 (95% CI, 0.24 to 0.39) for lupus nephritis in men. Table 3 shows the crude and standardized incidence rates for each glomerular disease by quintile of socioeconomic position. For ANCA-GN and lupus nephritis (in both sexes), the incidence rate increased in a graded fashion with lower socioeconomic position quintiles (Figure 2). The standardized incidence rate (per 100,000 person-years) of ANCA-GN increased from 0.71 (95% CI, 0.53 to 0.89) in the highest quintile to 1.06 (95% CI, 0.85 to 1.27) in the lowest quintile (P=0.04 for trend). The standardized incidence rate (per 100,000 person-years) of lupus nephritis in women increased from 1.06 (95% CI, 0.75 to 1.38) in the highest quintile to 1.81 (95% CI, 1.42 to 2.19) in the lowest quintile (P<0.001 for trend). The corresponding standardized incidence rates for lupus nephritis in men were 0.24 (95% CI, 0.09 to 0.39) in the highest quintile and 0.40 (95% CI, 0.21 to 0.58) in the lowest quintile (P=0.001 for trend). There was weaker evidence of a graded association for IgA nephropathy and FSGS (P=0.09 for trend in both diseases), and little or no evidence of an association for membranous nephropathy (P=0.23 for trend).
Table 3.
Crude incidence rates (per 100,000 person-years), direct standardized incidence rates (per 100,000 person-years), and standardized rate ratios for each glomerular disease as a function of socioeconomic position
| Income Quintile | N (%) | Crude Rate (95% CI) | Standardized Rate (95% CI) | Standardized Rate Ratio (95% CI) |
|---|---|---|---|---|
| Membranous nephropathy | ||||
| 1 (lowest) | 86 (22) | 0.97 (0.76 to 1.17) | 0.98 (0.77 to 1.19) | 1.11 (0.81 to 1.52) |
| 2 | 89 (23) | 1.02 (0.81 to 1.23) | 1.03 (0.82 to 1.24) | 1.17 (0.86 to 1.59) |
| 3 | 70 (18) | 0.80 (0.61 to 0.98) | 0.81 (0.62 to 1.00) | 0.92 (0.67 to 1.28) |
| 4 | 72 (18) | 0.83 (0.64 to 1.03) | 0.85 (0.65 to 1.04) | 0.96 (0.69 to 1.33) |
| 5 (highest) | 75 (19) | 0.89 (0.69 to 1.10) | 0.88 (0.68 to 1.08) | 1.0 (Reference) |
| ANCA-related GN | ||||
| 1 (lowest) | 96 (25) | 1.08 (0.86 to 1.30) | 1.06 (0.85 to 1.27) | 1.50 (1.09 to 2.06)a |
| 2 | 80 (21) | 0.91 (0.71 to 1.11) | 0.91 (0.71 to 1.10) | 1.28 (0.92 to 1.79) |
| 3 | 84 (22) | 0.95 (0.75 to 1.16) | 0.98 (0.77 to 1.19) | 1.39 (1.0 to 1.94)b |
| 4 | 68 (18) | 0.79 (0.60 to 0.98) | 0.83 (0.64 to 1.03) | 1.18 (0.83 to 1.67) |
| 5 (highest) | 59 (15) | 0.70 (0.52 to 0.88) | 0.71 (0.53 to 0.89) | 1.0 (Reference) |
| IgA nephropathy | ||||
| 1 (lowest) | 190 (23) | 2.14 (1.83 to 2.44) | 2.12 (1.82 to 2.43) | 1.22 (0.98 to 1.51) |
| 2 | 187 (23) | 2.14 (1.83 to 2.44) | 2.12 (1.82 to 2.42) | 1.22 (0.98 to 1.51) |
| 3 | 166 (20) | 1.89 (1.60 to 2.17) | 1.87 (1.59 to 2.16) | 1.08 (0.86 to 1.34) |
| 4 | 130 (16) | 1.51 (1.25 to 1.76) | 1.50 (1.24 to 1.76) | 0.86 (0.68 to 1.09) |
| 5 (highest) | 145 (18) | 1.73 (1.45 to 2.01) | 1.74 (1.46 to 2.03) | 1.0 (Reference) |
| FSGS | ||||
| 1 (lowest) | 100 (27) | 1.13 (0.91 to 1.35) | 1.12 (0.90 to 1.33) | 1.55 (1.13 to 2.13)b |
| 2 | 78 (21) | 0.89 (0.69 to 1.09) | 0.89 (0.70 to 1.09) | 1.24 (0.89 to 1.74) |
| 3 | 64 (17) | 0.73 (0.55 to 0.91) | 0.74 (0.56 to 0.91) | 1.02 (0.72 to 1.46) |
| 4 | 73 (19) | 0.85 (0.65 to 1.04) | 0.87 (0.67 to 1.06) | 1.20 (0.86 to 1.70) |
| 5 (highest) | 60 (16) | 0.71 (0.53 to 0.90) | 0.72 (0.54 to 0.90) | 1.0 (Reference) |
| Lupus nephritis in women | ||||
| 1 (lowest) | 83 (26) | 1.82 (1.43 to 2.22) | 1.81 (1.42 to 2.19) | 1.70 (1.19 to 2.42)c |
| 2 | 75 (23) | 1.68 (1.30 to 2.06) | 1.66 (1.29 to 2.04) | 1.56 (1.08 to 2.26)a |
| 3 | 66 (20) | 1.47 (1.12 to 1.83) | 1.44 (1.10 to 1.79) | 1.36 (0.93 to 1.98) |
| 4 | 54 (17) | 1.24 (0.91 to 1.57) | 1.23 (0.90 to 1.56) | 1.15 (0.78 to 1.72) |
| 5 (highest) | 44 (14) | 1.04 (0.73 to 1.34) | 1.06 (0.75 to 1.38) | 1.0 (Reference) |
| Lupus nephritis in men | ||||
| 1 (lowest) | 17 (25) | 0.39 (0.21 to 0.58) | 0.40 (0.21 to 0.58) | 1.64 (0.76 to 3.55) |
| 2 | 15 (22) | 0.35 (0.17 to 0.53) | 0.35 (0.17 to 0.53) | 1.45 (0.66 to 3.21) |
| 3 | 13 (19) | 0.30 (0.14 to 0.46) | 0.30 (0.14 to 0.46) | 1.24 (0.55 to 2.83) |
| 4 | 12 (18) | 0.28 (0.12 to 0.44) | 0.28 (0.12 to 0.44) | 1.16 (0.50 to 2.69) |
| 5 (highest) | 10 (15) | 0.24 (0.09 to 0.39) | 0.24 (0.09 to 0.39) | 1.0 (Reference) |
P<0.01.
P<0.05.
P<0.001.
Figure 2.
Standardized incidence rate per 100,000 person-years and associated 95% confidence interval for each quintile of area-based household income. The P values represent a test for trend across income quintiles for each glomerular disease. ANCA-GN, ANCA-related GN; Q, quintile.
The standardized rate ratios for each socioeconomic position quintile versus the reference (highest) quintile for each glomerular disease are provided in Table 3. The strongest association was observed in women with lupus nephritis, where the lowest quintile had a 70% higher incidence (standardized rate ratio, 1.70; 95% CI, 1.19 to 2.42). A similar figure was demonstrated in men; however, the lower sample size contributed to wider error bounds. The lowest quintile was associated with a 50% (standardized rate ratio, 1.50; 95% CI, 1.09 to 2.06) higher incidence of ANCA-GN and a 55% (standardized rate ratio, 1.55; 95% CI, 1.13 to 2.13) higher incidence of FSGS. In IgA nephropathy, there was weaker evidence to suggest a higher incidence rate in the lowest quintile (standardized rate ratio, 1.22; 95% CI, 0.98 to 1.51), whereas an even weaker association was found for membranous nephropathy (standardized rate ratio, 1.11; 95% CI, 0.81 to 1.52).
Discussion
This is the first study to describe the relationship between socioeconomic position and the standardized incidence of specific biopsy-proven glomerular diseases captured from a centralized kidney pathology database with an accurately defined source population. The incidence of ANCA-GN and, in particular, lupus nephritis increased in a graded fashion with lower socioeconomic position, suggesting that these conditions are not merely a function of poverty versus sufficiency, but rather that the risk of disease varies across levels of socioeconomic position. The incidence of FSGS was also higher in the lowest socioeconomic position quintile but was not higher among other, less deprived categories. No statistically significant association was observed between socioeconomic position and the incidence of either IgA nephropathy or membranous nephropathy.
There is a paucity of literature describing the association between measures of socioeconomic position and glomerular disease. A study from a regional kidney biopsy registry in Scotland, representing an approximate catchment population of 1.5 million inhabitants, investigated the association between social deprivation and the incidence of biopsy-proven kidney diseases from 2000 to 2010 (19). Of the 1555 patients identified, 703 had a primary diagnosis of GN. Greater social deprivation was associated with higher overall incidence of GN, which was driven by differences in the incidence of IgA nephropathy (20.0 versus 9.1 per million population per year in the most versus least deprived quintile). No statistically significant differences were shown for FSGS (n=146), vasculitis (n=212), or lupus nephritis (n=60). Our results suggest a much weaker relationship between socioeconomic position and the incidence of IgA nephropathy, and stronger associations between socioeconomic position and the incidence of lupus nephritis, ANCA-GN, and FSGS. There are a number of important differences between this study and our analysis that could explain these discrepancies. First, rates of each disease were not standardized in the Scottish study. This could have influenced the results for the glomerular diseases evaluated, because the distributions of age and sex may differ by socioeconomic position, and certain diseases have an age- or sex-related predominance. Second, the sample was primarily urban, whereas we included both urban and rural regions within an entire province and therefore covered a larger socioeconomic spectrum. Third, the sample size was relatively small and from a poorly defined source population, which could have hindered the ability to demonstrate disease-specific associations. In contrast, our analysis captured all patients with biopsy-proven glomerular disease from a well defined source population, culminating in a more than three-fold larger sample size overall and a two- to six-fold larger sample size for individual diseases.
There are no other studies examining the relationship between socioeconomic position and the incidence of membranous nephropathy, IgA nephropathy, FSGS, or ANCA-GN. A study of 189 patients with SLE did not demonstrate an association between socioeconomic position and the development of proteinuria; however, the study was underpowered and did not study biopsy-proven lupus nephritis (20). Another study investigating the incidence of lupus nephritis in the United States using Medicaid data demonstrated no association with socioeconomic position after adjustment for age and sex (12). This analysis may have been limited by the restriction to low-income individuals who were eligible for Medicaid, and the use of International Classification of Diseases, Ninth Revision codes instead of kidney biopsies to identify cases. Therefore, our results provide the first robust investigation of the incidence of glomerular disease associated with socioeconomic position that uses a wide range of socioeconomic strata, that captures all cases of biopsy-proven disease, and that adjusts for the potential confounding effects of age and sex.
Our findings have a number of important clinical implications. Patients with glomerular disease require highly specialized nephrology care, vigilant follow-up, and access to increasingly expensive therapies. We previously demonstrated clusters of FSGS and ANCA-GN in sparsely populated regions of British Columbia with poor geographic access to nephrology centers (21). Compounding this with socioeconomic deprivation could further hinder access to specialist care and optimal treatment, as has been observed for patients with moderate-to-severe CKD (22). Although understudied in the context of glomerular disease, individuals with CKD from lower socioeconomic backgrounds have poorer long-term outcomes, including a higher likelihood of progression to ESKD, cardiovascular events, disability, and all-cause mortality (22–26), thus reinforcing the need for earlier identification and intervention. The increased burden of illness associated with ESKD places additional financial constraints on patients through work absences and reductions in earning capacity (27,28). This would be particularly detrimental to patients with glomerular disease who are at an especially high risk of disease progression from a younger working age (29,30). A vicious cycle may ensue in which individuals at lower socioeconomic position are more likely to get glomerular disease, encounter barriers to accessing optimal care, progress to ESKD, and then experience further financial losses, thereby exacerbating their socioeconomic situation.
Socioeconomic position serves as a proxy for a series of life course influences on health that could contribute individually and/or cumulatively to the risk of developing kidney disease through a number of potential mechanisms. In our study, glomerular diseases characterized by systemic inflammation (lupus nephritis and ANCA-GN) had the strongest association with lower socioeconomic position. In the general population, it has been hypothesized that exposure to social adversity during one’s life course contributes to a “defensive” phenotype characterized by upregulation of proinflammatory genes (31). In keeping with this, several studies have shown an association between socioeconomic position and higher levels of inflammatory markers such as C-reactive protein (32,33). Social adversity is associated with increased DNA methylation in genes that regulate inflammation, suggesting that changes in the epigenome could explain the link between socioeconomic position and chronic inflammation (34,35). Epigenome-wide association studies have demonstrated a link between DNA methylation and kidney dysfunction, including kidney fibrosis (36). DNA methylation levels have also been implicated in active and relapsing cases of ANCA-associated vasculitis, demonstrating a negative correlation with expression of the MPO and PRTN3 genes that encode, respectively, the autoantigens myeloperoxidase and proteinase 3 (37). Other proinflammatory states are more common in lower socioeconomic position groups and could play a role in the pathogenesis of kidney disease. For example, periodontal disease is socially patterned and has been consistently linked with cardiovascular disease (38,39), diabetes (40), and systemic autoimmune diseases (41,42). An association with all-cause CKD has also been described, although the relationship between periodontal disease and specific kidney diseases has not been well studied (43).
Our study has a number of limitations. Population-level data for race/ethnicity were not available within income quintiles, therefore we were unable to adjust for race/ethnicity in our analysis. Supplemental Table 3 describes a number of other indicators of socioeconomic position among white, Chinese, and South Asian individuals using census data. These three racial groups account for approximately 90% of the population of British Columbia. For most of these indicators, differences between these racial groups are small. In contrast, there are differences in educational attainment and family income for individuals who identify as First Nations or Aboriginal ethnicity. This group represents 3.6% of the provincial population, therefore the magnitude of potential confounding on the basis of Aboriginal race/ethnicity is likely to be small at the population level; however, further research would be needed to explore this. We did not have data regarding specific comorbidities that are associated with glomerular disease and could plausibly be more frequent among individuals with lower socioeconomic position, such as cancer, obesity, smoking, and liver disease. Income data were available only at the time of biopsy, so we cannot rule out the possibility of reverse causation: that is, the development of glomerular disease could have negatively affected an individual’s household income, leading to socioeconomic drift downward. We feel that this is unlikely given the usually short time frame between disease presentation and kidney biopsy. The use of area-level income, specific for regional differences in the cost of living in British Columbia, hampers the generalizability of our findings. On the other hand, our analysis compared individuals with those living in regions with homogeneous costs of living, and therefore are independent of the absolute level of income, which could facilitate relative comparisons within other homogeneous jurisdictions outside of British Columbia. We did not have data regarding access to care. However, given the kidney function and proteinuria at the time of biopsy were similar across socioeconomic position quintiles, and the province has a universal health care system, this was likely a relative limitation. Finally, income is just one measure of socioeconomic position, and exploration of other measures such as education or occupation are needed to demonstrate consistency of our findings.
In conclusion, we demonstrated an inverse graded association between socioeconomic position and the standardized population-level incidence of biopsy-proven lupus nephritis and ANCA-GN in a large Canadian province. Although not a graded relationship, the incidence of FSGS was also higher in the lowest socioeconomic position category. An improved understanding of socioeconomic determinants of glomerular disease could inform future research regarding disease pathogenesis, as well as health policy directed toward vulnerable populations at increased risk of organ-threatening autoimmune diseases.
Disclosures
Dr. Hladunewich reports receiving grant support from Calliditas Therapeutics AB, Chemocentryx, Genentech, and Pfizer outside of the submitted work. Dr. Barbour, Dr. Canney, Dr. Gill, Ms. Induruwage, Dr. McCrory, and Ms. Sahota have nothing to disclose.
Funding
Dr. Barbour reports salary support to conduct this work from the Michael Smith Foundation for Health Research in British Columbia, Canada.
Supplementary Material
Acknowledgments
We thank Dr. Alex Magil from the British Columbia Renal Pathology Laboratory at St. Paul’s Hospital for creating the British Columbia Renal Pathology Database.
All inferences, opinions, and conclusions drawn in this manuscript are those of the authors and do not reflect the opinions or policies of the Data Steward(s).
Footnotes
Published online ahead of print. Publication date available at www.cjasn.org.
Supplemental Material
This article contains the following supplemental material online at http://cjasn.asnjournals.org/lookup/suppl/doi:10.2215/CJN.08060719/-/DCSupplemental.
Supplemental Table 1. Distribution of population of mainland British Columbia (2006 census) by age, sex, and quintile of socioeconomic position.
Supplemental Table 2. Missing data (%) for baseline characteristics.
Supplemental Table 3. Comparison of indicators of socioeconomic position among race/ethnicity groups in British Columbia.
Supplemental Appendix 1. Creation of socioeconomic position variable.
Supplemental Appendix 2. Calculation of 24-hour proteinuria values from albumin-to-creatinine ratio (ACR) and protein-to-creatinine ratio (PCR.).
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