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Clinical and epidemiological research
Extended report
Relationship between area-level socio-economic deprivation and autoantibody status in patients with rheumatoid arthritis: multicentre cross-sectional study
  1. Sarah L Mackie1,
  2. John C Taylor1,
  3. Sarah Twigg1,
  4. Stephen G Martin1,
  5. Sophia Steer2,
  6. Jane Worthington3,
  7. Anne Barton3,
  8. Anthony G Wilson4,
  9. Lynne Hocking5,
  10. Adam Young6,
  11. Paul Emery4,
  12. Jennifer H Barrett1,
  13. Ann W Morgan1
  1. 1NIHR-Leeds Biomedical Research Unit, Leeds Musculoskeletal Biomedical Research Unit, Leeds Institute of Molecular Medicine, University of Leeds, Leeds, West Yorkshire, UK
  2. 2Department of Rheumatology, King's College Hospital NHS Foundation Trust, London, UK
  3. 3Arthritis Research UK-Epidemiology Unit, The University of Manchester, Manchester, UK
  4. 4Department of Musculoskeletal Sciences, University of Sheffield, Sheffield, UK
  5. 5Division of Applied Medicine, University of Aberdeen, Aberdeen, UK
  6. 6Department of Rheumatology Department, St Albans City Hospital, St Albans, UK
  1. Correspondence to Ann W Morgan, NIHR-Leeds Biomedical Research Unit, Leeds Institute of Molecular Medicine, Level 8, Wellcome Trust Brenner Building, St. James's University Hospital, Leeds, LS9 7TF, UK; a.w.morgan{at}leeds.ac.uk

Abstract

Objectives The aims of this study were to assess the association between area-level socio-economic deprivation and the phenotype of rheumatoid arthritis (RA), defined by rheumatoid factor (RF) and anticitrullinated peptide antibody (AC PA) status, and to determine whether any observed association can be explained by smoking.

Methods The authors performed logistic regression analysis of 6298 patients with RA, defined by American College of Rheumatology classification criteria modified for genetic studies. Analysis was stratified by cohort/recruitment centre. Socio-economic deprivation was measured using the Townsend Index.

Results Deprivation predicted RF but not ACPA positivity, independent of smoking. The ORs for trend across tertiles, adjusted for smoking, gender, period of birth and cohort/recruitment centre, were 1.14 (95% CI 1.01 to 1.29) for RF and 1.01 (95% CI 0.87 to 1.16) for ACPA. Even after adjusting for deprivation, smoking was strongly associated with ACPA positivity (OR 1.38, 95% CI 1.22 to 1.55). There was no evidence of any effect modification by the RA risk alleles (HLA-DRB1 shared epitope and PTPN22 rs2476601) that have previously been shown to modify the effect of smoking on ACPA and RF positivity.

Conclusions Among patients with RA, deprivation predicted RF positivity but not ACPA positivity. The effect of deprivation did not appear to be explained by smoking. Deprivation may be a marker for previously unrecognised, potentially modifiable environmental influences on the immunological phenotype of RA. Furthermore, given the known associations of RF positivity with prognosis and response to treatment in RA, these findings have potential implications for resource allocation and healthcare delivery.

https://doi.org/10.1136/annrheumdis-2011-201003

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    Introduction

    Rheumatoid arthritis (RA) is a chronic, autoimmune inflammatory joint disease (with prevalence of approximately 1% in Western Europe and the USA) that carries significant morbidity and mortality.1 Patients with RA commonly develop two different types of autoantibody: rheumatoid factor (RF) and anticitrullinated peptide antibodies (ACPAs).1 RF and ACPA can precede clinical onset of RA by up to 10 years;2 therefore, autoantibody status in established disease may provide a unique insight into factors affecting immunological events in the preclinical stage of RA. This concept is supported first by accumulating evidence that ACPA-positive RA and ACPA-negative RA have distinct genetic3 and environmental4 risk factors. For example, smoking is a risk factor for both RF positivity5 ,6 and ACPA positivity.4 ,6 The effect of smoking is modified by genetic factors including specific HLA-DRB1 shared epitope (SE) alleles and the rs2476601 functional polymorphism in PTPN22, suggesting that gene–environment biological interactions may be operating in RA pathogenesis.6 ,7 Second, both RF and ACPA autoantibodies may be pathogenic. Immune complexes containing RF become trapped in cartilage of joints affected by RA and can exacerbate local inflammation,8 and citrullination of proteins occurs within inflamed joints.9 The RA-associated HLA-DRB1 SE alleles can present citrullinated peptides, providing a potential mechanism for the gene–environment interaction.10 ,11 Third, autoantibody status predicts response to some treatments, particularly B cell depletion,12 supporting the relevance of RF and ACPA subtypes to clinical practice. A recent large cohort study suggested that both RF and ACPA may independently predict RA progression.13

    Socio-economic deprivation is known to be associated with an adverse prognosis in RA,14,–,16 as in many other diseases.17 Smoking is one of a complex set of inter-related factors related to deprivation. Deprivation may be assessed either at the individual ‘proximate’ level (eg, personal income, occupation, education) or at the area ‘contextual’ level (using relevant census data relating to the neighbourhood of residence); individual- and area-level measures of socio-economic status are often poorly correlated with each other.18 These two levels of deprivation modify each other's effects on functional limitation in RA, suggesting that they may reflect different underlying factors.16 Some of the effect of deprivation on RA may be explained by delays in presentation19 and by difficulties engaging with healthcare professionals once clinical disease is apparent, even in countries with universal free healthcare.16 ,20 Case–control studies of the effect of socio-economic deprivation on RA susceptibility might be confounded by differences in recruitment methods (response bias) between cases and controls.21 We chose to perform a case-only analysis for this reason. Because socio-economic deprivation is correlated with smoking in the UK,22 large cohorts are required to determine whether deprivation has a direct effect on disease independent of smoking. Multicentre collaborations set up to unravel the genetic epidemiology of RA have resulted in large data sets that can be exploited to examine novel complex associations.

    We hypothesised that, in RA, area-level socio-economic deprivation is associated with positive RF and/or ACPA status, independent of smoking. This outcome measure was chosen because the appearance of RF and ACPA usually precedes the onset of clinically overt joint inflammation; we wished to address the immunological events leading to RA, while minimising any effect due to differential engagement with healthcare services in more-deprived areas. Because RF and ACPA status can help inform treatment and prognosis, any association with deprivation may also have implications with regard to public health, preventive medicine, healthcare planning and resource allocation in different geographical areas.

    Methods

    We performed a case-only analysis, using logistic regression to model the effects of area-level socio-economic deprivation on autoantibody (RF or ACPA) status, while controlling for other relevant variables. All patients were Caucasian of Northern European descent, were 18 years or older at disease onset and fulfilled the 1987 American College of Rheumatology classification criteria for RA23 modified for genetic studies.24 Cases were recruited through the UKRAG (UK Rheumatoid Arthritis Genetics) consortium, involving Manchester, Leeds, Aberdeen, Sheffield and London,25 and included RA cases from the Yorkshire Early Arthritis Register (YEAR), the multicentre, cross-sectional Biologics in Rheumatoid Arthritis Genetics and Genomics Study Syndicate (BRAGGSS)26 and the multi-centre Early Rheumatoid Arthritis Study (ERAS)15 (see Appendices for recruiting centres). HLA-DRB1 and PTPN22 typing, HLA-DRB1 SE classification and RF and ACPA determination (‘positive’=ever positive, ‘negative’=never positive) were performed as previously described.6 ,15 ,26 All participants were recruited after providing informed written consent. The YEAR study was a multicentre collaboration across centres in Yorkshire and was approved by the Northern and Yorkshire Research Ethics Committee (MREC 99/3/48). The BRAGGSS study was approved by the UK Central Office of Research Ethics Committees (COREC 04/Q1403/37). UKRAG was approved by the North West Multi-centre Research Ethics Committee (MREC 99/8/84). The ERAS is an inception cohort still in follow-up, which recruited patients between 1986 and 1998, from nine hospitals across England; ethical approval was gained from the East Hertfordshire Ethics Committee. In all three cohorts, patients were treated and followed up according to standard clinical care, including repeated measurement of RF in routine clinical laboratories when clinically indicated. ACPA status was determined retrospectively by measurement on serum samples that had been stored as part of the original research study, as previously described.6

    Area-level socio-economic deprivation was derived from the patient's postcode by calculating the Townsend Index from the 2001 UK census at Lower Super Output Area and Datazone level for England and Scotland, respectively. The Townsend Index27 is a composite index derived from the standardised census-based area proportions of unemployment, household overcrowding, car ownership and housing owner-occupiers. Area-level deprivation was chosen as less likely to be directly affected by RA itself (reverse causation) than individual-level deprivation as assessed by personal income, since job loss can occur early in RA.28 Tobacco exposure prior to the onset of RA was estimated by calculating pack years.

    The effect of socio-economic deprivation and smoking was estimated from logistic regression by comparing antibody-positive patients versus antibody-negative patients. The Townsend Index was divided into tertiles and fit as a categorical variable, while smoking was fit separately as a categorical variable with four levels: nonsmoker, light smoker (up to 10 pack years), moderate smoker (>10–30 pack years) and heavy smoker (>30 pack years). A test for trend in risk across these categories was also performed. To assess whether Townsend had an effect independent of smoking, we included both categorical variables in the same logistic regression model, adjusting for cohort/centre. Cohort/centre was categorised as follows: patients in the BRAGGSS cohort, patients from the Manchester study centre but not in the BRAGGSS cohort, patients in the YEAR cohort, patients from the Leeds study centre but not in the YEAR cohort, ERAS, Aberdeen, London and Sheffield. Pooled ORs and 95% CIs for trends across cohort/centre for the categorical variables were estimated using Mantel–Haenszel analysis and tested for homogeneity of ORs. All analyses were adjusted for gender and period of birth.6 A case was excluded listwise from a regression model if the case had missing data for one or more of the variables in the model.

    Analysis of the combined effect of deprivation and smoking was undertaken by considering binary classifications of each variable. Deprivation was classified as affluent (Townsend Index<median) versus deprived (Townsend Index>median), and smoking was classified as never smoked versus ever smoked. Departure from additivity was assessed by calculating RR due to interaction (RERI): RR (AE)–RR (ĀE)–RR (AĒ)+1, where A and E denote the presence and Ā and Ē denote the absence of the respective risk factors,29 with 95% CIs calculated using the variance estimates obtained from Taylor series expansion.30 Departure from multiplicity was tested using logistic regression, comparing models with and without an interaction term using the likelihood ratio test. This method was repeated to assess the combined effect of deprivation with HLA-DRB1 SE alleles and PTPN22 alleles (classified as carriage vs non-carriage). All analyses were conducted using STATA version 10 (StataCorp, College Station, TX, USA).

    Results

    The RA population (n=6298) is comparable with other hospital-based series of subjects with RA. The patient characteristics are shown in table 1.

    View this table:
    Table 1

    Demographic, serological, smoking and genetic status of all RA cases and the subsets stratified by tertiles of area-level socio-economic status (Townsend score)

    Where the catchment area of each recruitment centre was similar to county-level administrative regions, the median Townsend score of patients recruited within each region was compared to the regional median. Reflecting the usual bias of recruitment to research studies, patients in this RA cohort came from less-deprived areas than the general population in those regions. Patients from more-deprived areas were more likely to be current/former smokers than those from less-deprived areas (table 1, p=2×10−15, Fisher's exact test between smoking status and deprivation tertile).

    As previously reported for a subgroup of this cohort,6 in univariable analysis, smoking was a risk factor both for RF positivity (OR 1.27, 95% CI (1.15 to 1.41)) and for ACPA positivity (OR 1.38, 95% CI (1.23 to 1.55)), with evidence of a dose–response effect by pack years of tobacco exposure (table 2). In both cases, this association persisted after adjusting for deprivation (table 2).

    View this table:
    Table 2

    Deprivation and smoking as determinants of RF and ACPA status

    The Townsend score overall was a significant risk factor for RF positivity (OR 1.11, 95% CI (1.03 to 1.20)) but not for ACPA positivity (OR 1.00, 95% CI (0.91 to 1.10), table 2). The effect size was not diminished and remained significant for RF, after adjusting for smoking (table 2). When stratified by smoking status, the risk attenuated in the never smokers but not in those who had ever smoked. There was no evidence for a lack of homogeneity of ORs across the study/recruitment centres for either RF positivity (p=0.25) or ACPA positivity (p=0.27). We found no evidence for any bias in our results potentially caused by missing smoking data (Supplementary Text). Analysis of the subgroup of patients with data on both RF and ACPA (Supplementary Table S1) showed very similar results. Of the four combinations of RF and ACPA status, the strongest association with Townsend score is seen in those positive for RF and negative for ACPA, and the strongest association with smoking is seen in those positive for both antibodies (Supplementary Table S2).

    For interaction statistics, the cases were divided into two groups, more deprived and less deprived, based on the median Townsend score for all cases. The relationship of RF with smoking was significant within the more-deprived but not the less-deprived cases; however, formal testing using the RERI statistic did not show a statistically significant interaction between smoking and deprivation as regards RF positivity (table 3, upper section). The relationship of ACPA with smoking remained significant both in the more-deprived and in the less-deprived cases (table 3, lower section). Similar results were obtained when smoking was classified by pack years of tobacco exposure.

    View this table:
    Table 3

    Tests for interaction between deprivation and smoking

    Similar to an interaction analysis, we previously reported between smoking and both HLA-DRB1 SE and PTPN22 in a subgroup of this cohort;6 no interaction was seen between deprivation and either of these genotypes as predictors of antibody positivity (table 4).

    View this table:
    Table 4

    Tests for interaction between deprivation and HLA-DRB1 and PTPN22 status

    Discussion

    The large size of this cohort allowed us to determine whether area-level socio-economic deprivation was associated with RF and ACPA positivity and, in addition, whether this was independent of the influence of smoking. Deprivation had a significant effect on RF status, but not on ACPA status, after adjusting for smoking. Stratification according to both smoking and deprivation did not seem to suggest that the deprivation variable was acting as a simple proxy for smoking, although we acknowledge the limited available data on smoking pack years and the need for further study. The independent relationship of deprivation to RF, but not to ACPA, is of interest because current data suggest that smoking has a specific relationship to ACPA.7 Thus, taking all these results together, it appears unlikely that the deprivation effect can be explained by residual confounding either by smoking itself or by exposure to secondhand tobacco smoke. We suggest that deprivation may be a marker for previously unrecognised environmental influences on the immunological phenotype of RA.

    The strengths of this study include its large size and its case-only design, eliminating the problem of differential recruitment of cases and controls. We observed differential recruitment from more affluent areas than the regional averages and assumed for this analysis that antibody-negative and antibody-positive cases were equally likely to be recruited with respect to socio-economic status. We have carried out analyses stratified by centre to try to ensure that a correlation between socio-economic status and antibody status is not induced by different ascertainment of cases in areas with differing levels of deprivation. The patients in the study are from three types of study: cross-sectional hospital-based cohorts, studies of biological treatment and early arthritis cohorts, which may be expected to differ in the prevalence of autoantibody positivity rates. Each of the eight strata defined included cases from one of these categories, in addition to stratification by study centre, thus minimising the chances of an artefactual association between socio-economic status and antibody status.

    One limitation was that current area-level socio-economic deprivation was used as a proxy for previous deprivation; in this cross-sectional study, we could not exclude reverse causation (eg, loss of income in the more severely affected individuals, potentially resulting in relocation to more socio-economically deprived areas). If this were the case, however, we would predict an association of area-level socio-economic deprivation with both RF and ACPA, since both these independently predict RA severity.13 In healthy women without RA, childhood bedroom sharing is associated with a reduced risk of a positive RF,31 consistent with the ‘hygiene hypothesis’; however, again, this would be expected to bias the findings in the opposite direction to that shown here. Another potential limitation is that although RF status was determined on multiple occasions, ACPA status was usually evaluated on a single cross-sectional serum sample, as this test was not in routine clinical use when these individuals were recruited. This may have reduced the power of the study slightly with regard to ACPA by miscategorising some previously ACPA-positive cases as ACPA-negative. However, the rate of disease progression in those patients who revert from low-positive ACPA to ACPA-negative during treatment is similar to those who were ACPA-negative from the start,32 suggesting that the clinical phenotype of those ACPA-positive cases who then revert to ACPA-negative status may not be very different from those who were ACPA-negative throughout. Although RF was measured on multiple occasions, we could not completely exclude the possibility that the observed association of RF with deprivation might be due to later presentation of cases from more-deprived areas. In this study, we did not measure individual-level deprivation; people in the UK are generally reluctant to disclose their income. Education levels changed substantially during the last 60 years; at the time, many of these patients were in education; few individuals went on to higher education yet there was substantial social mobility in the UK as industry shifted away from manufacturing towards white-collar jobs. Indices of multiple deprivation such as the IMD2007 may be more informative measures of area-level socio-economic deprivation than the Townsend Index, but the former does not cover Scotland and would therefore exclude some of our data from analysis.

    To our knowledge, no previous studies have addressed the research question posed here. However, two case–control studies from elsewhere in Northern Europe demonstrated an association of individual-level socio-economic deprivation with RF-positive RA but not with RF-negative RA, even after adjustment for smoking. Bengtsson et al33 reported that lack of a university degree predisposed both men and women to RA, but among the women, this was only significant for RF-positive, not RF-negative RA. Pedersen et al34 reported that lower levels of education were a risk factor only for RF-positive RA, not for RF-negative RA, after controlling for smoking and various other environmental risk factors. In both these studies, however, RF-positive RA comprised more than two-thirds of the cases, and thus, the lack of association with RF-negative RA might be attributed to lower power. These studies also did not examine ACPA. The major difference between those studies and the current study was the design. Although both studies selected age- and sex-matched controls derived from population registries (the Bengtsson study also matched for county or municipality), the response rate of control individuals was lower than that of the cases: for the controls, it was 83%33 and 64%.34 This type of bias between cases and controls is a well-known potential limitation of case–control studies,21 and response bias in these studies could not be excluded as an explanation for the findings. The current case-only analysis was designed to eliminate this bias.

    Our study has produced a novel finding, which, if replicated in an independent data set, could suggest an influence of novel environmental factors on the immunological phenotype of RA. Since autoantibody status relates to prognosis and response to treatment of this common, chronic disease, the influence of area-level socio-economic deprivation on autoantibody status would also be relevant to healthcare delivery and service planning with a view to reducing health inequalities.

    Health inequalities are likely to be multifactorial;35 socio-economic deprivation may be associated with vitamin D deficiency,36 deficiency in other micronutrients,37 infections including those associated with periodontal disease38 and psychological stress. Any or all of these factors may affect the functioning of the immune system relevant to the pathogenesis of RA.39 Infection is particularly worthy of future investigation given that transient RF formation is a normal part of the immune response to infections and that infections at distant sites can exacerbate joint inflammation in patients with established RA. Obesity (associated with socio-economic deprivation, particularly in women) has been associated with antibody-negative RA,4 and alcohol consumption may protect against antibody-positive RA;4 thus, these factors would be unlikely to explain our findings. Further research is now warranted to replicate our findings and to further investigate these proposed candidate mediator factors and may eventually inform trials of diet or lifestyle interventions for reducing the risk of autoantibody formation and/or new-onset RA in high-risk individuals, such as those with a strong family history of RA.

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    Supplementary materials

    • Supplementary Data

      This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

      Files in this Data Supplement:

      • Web Only Data - This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.
      • Web Only Data - This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.
      • Web Only Data - This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

    Footnotes

    • Collaborators YEAR consortium, BRAGGSS consortium, UKRAG consortium and ERAS consortium.

    • Funding This study was funded by the National Institute for Health Research-Leeds Musculoskeletal Biomedical Research Unit, Arthritis Research UK (grant numbers: 17552 (BRAGGSS), E0555 and 18066), Leeds Teaching Hospitals Charitable Trustees, Research and Development Support Fund for Guy's and St. Thomas' National Health Service Foundation Trust and the Lewisham Hospital National Health Service Trust. SLM holds a National Institute for Health Research Academic Clinical Lectureship.

    • Competing interests None.

    • Ethics approval The YEAR study was a multicentre collaboration across centres in Yorkshire and was approved by the Northern and Yorkshire REC (MREC 99/3/48). The BRAGGSS study was approved by the UK Central Office of Research Ethics Committees (COREC 04/Q1403/37). UKRAG was approved by the North West Multi-centre Research Ethics Committee (MREC 99/8/84). The ERAS is an inception cohort still in follow-up, which recruited patients between 1986 and 1998, from nine hospitals across England; ethical approval was gained from the East Hertfordshire Ethics Committee.

    • Provenance and peer review Not commissioned; externally peer reviewed.