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FRI0263 Country of Residence and Its Wealth Determine Disease Activity Levels in RA: Results from Multi-National Study in 17 Countries (COMORA)
  1. P. Putrik1,2,
  2. S. Ramiro3,4,
  3. A.P. Keszei5,
  4. I. Hmamouchi6,
  5. M. Dougados7,
  6. T. Uhlig8,
  7. T.K. Kvien8,
  8. A. Boonen2
  1. 1Health Promotion and Education, Maastricht University
  2. 2Rheumatology, Maastricht University, CAPHRI, MUMC, Maastricht
  3. 3Clinical Immunology & Rheumatology, ARC, Amsterdam, Netherlands
  4. 4Rheumatology, Hospital Garcia de Orta, Almada, Portugal
  5. 5Epidemiology, Maastricht University, Maastricht, Netherlands
  6. 6Biostatistics Epidemiology LBRCE, Université Mohamed-V Souissi, Rabat, Morocco
  7. 7Paris-Descartes University, Paris, France
  8. 8Rheumatology, Diakonhjemmet Hospital, Oslo, Norway


Background Socio-economic (SE) inequalities in health persist both between and within countries and even increased in the recent years. Therefore, it is important to explore whether country level factors may contribute to health inequities in patients with RA.

Objectives The objectives of this study were to (1) investigate whether country level factors contribute to explain Disease Activity Score (DAS28) (2) explore whether uptake of biologic disease modifying anti-rheumatic drugs (bDMARDs) mediates the relationship between country welfare and DAS28.

Methods Data from a cross-sectional multinational (17 countries) study (COMORA) was used. The outcome was DAS28. Contribution of country to DAS28 was explored in multivariable linear regression models, adjusting for potential confounders, using forward selection and accounting for multiple testing. The Netherlands (NL) with lowest DAS28 was used as reference. Next, the country of residence was replaced by GDP (in tertiles), to investigate the contribution of socio-economic welfare. Improvement in R2 (model fit) of the two models that included either country or GPD was compared. Finally, the mediating role of uptake of bDMARDs in the relationship between GDP and DAS28 was explored by testing indirect effects.

Results A total of 3920 RA patients from 17 countries (range 30-411) were included in the COMORA dataset. Mean age was 56 y.o. (SD13), 82% females. Mean DAS28 was 3.7 (range 2.6 (NL) – 5.2 (Morocco)), and 32% of patients were currently treated with bDMARDs (range 3% (Uruguay) – 74% (UK)). Country differences in DAS28 varied from 0.2 (France) to 2.3 (Morocco) compared to NL, after adjustment for individual factors. Additional contribution of country to R2 was 0.15 and of GDP 0.08. Fifty and 13% of the relationship between DAS28 and medium and low GDP (vs. high GDP), respectively, was mediated by uptake of bDMARDs (total and indirect effect 0.06 and 0.03 (95% CI [0.02;0.04]) and 0.31 and 0.04 (95% CI [0.02;0.05]) for medium and low GDP, respectively, vs high GDP). Final model with countries classified into GDP groups is presented in Table 1.

Table 1.

Association between age, gender, education and GDP with DAS28

Conclusions Substantial differences in DAS28 between countries were observed after adjusting for individual factors. In societies with GDP in the two lowest tertiles disease activity was on average 1.2 and 0.2 units higher compared to high GDP countries. While total effect for medium GDP was negligibly small, 13% of the differences in DAS28 between low and high GDP countries was mediated by (lower) uptake of bDMARDs. Inequities across countries should come at focus of international societies of rheumatology and policy-makers.

Disclosure of Interest None declared

DOI 10.1136/annrheumdis-2014-eular.3650

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