FRI0082 In Addition to Individual Demographic and Clinical Measures, Levels of Fatigue Are Dependent on Country of Residence. An Analysis among 3920 Patients from 17 Countries (The Comora Study). (10th June 2014)

• Record Type: Journal Article
• Authors: Hifinger, M.; Putrik, P.; Ramiro, S.; Keszei, A.P.; Hmamouchi, I.; Dougados, M.; Gossec, L.; Boonen, A.
• Is Part Of: Annals of the rheumatic diseases. Volume 73:Supplement 2(2014)
• Page Start: 411
• Page End: 411
• Publication Date: 2014-06-10
• Subjects: Rheumatism -- Periodicals; 616.723005
• DOI: 10.1136/annrheumdis-2014-eular.2098
• Languages: English
• ISSNs: 0003-4967

Abstract

Abstract : Background: For patients with rheumatoid arthritis (RA), fatigue is an important aspect of disease which impacts quality of life. However the complex relationship between fatigue and either disease-related or external factors remains unclear. Country of residence as a surrogate for a variety of cultural, economic, climatological and linguistic aspects might play a role, but this has never been formally explored. Objectives: To investigate how country of residence influences level of fatigue in addition to socio-demographic and objective disease- characteristics. Methods: Data from a multi-national study were used (COMORA). Fatigue was measured using 0-10 VAS scale. A multivariable linear regression model (outcome fatigue) was computed using manual forward selection. Contribution of socio-demographic factors (age, gender, education, marital status, work status), comorbidities (Wolfe-Michaud index), smoking status, clinical disease characteristics (tender and swollen joints (TJC, SJC), erosions in hands or feet (yes/no), erythrocyte sedimentation rate) and medication (all type of DMARDs, steroids and NSAIDs) was tested. Country of residence was added using the country with the highest level of fatigue (Netherlands) as reference. In a second step, sensitivity analyses were developed replacing country of residence by country specific variables including gross domestic product (GPD), human development index (HDI), a climate indicator (latitude) and income inequality (gini index). Results: 3920 patients from 17 countries (range: 30 to 411, mean age 56 years (SD 13), 82% female). Mean fatigue across countries was 4.13 (SD 2.8). 32.8% of all patients had fatigue scores >5. In multi-variable regression, female gender (βf=1 =0.72, CI 0.50/0.93) and a higher comorbidity score (β=0.30, CI 0.24/0.37) were associated with higher fatigue. TJC and SJC had limited influence on fatigue with higher contribution of TJC (βTJC =0.14, CI 0.12/0.16 and βSJC =0.05, CI 0.25/0.79). When adding country, the contribution was significant and increased the overall model fit (Δ R 2 =0.07). Country differences in fatigue varied between -3.9 for Venezuela vs Netherlands (NL) and -0.6 (Italy vs NL) after adjustment for individual factors. When country was replaced by GDP, HDI, latitude or gini index, only GPD and HDI index contributed significantly. The overall model improvement was lower compared to country (R 2 GDP =0.14, R 2 HDI =0.18, R 2 country =0.20). Interactions were not significant. Conclusions: While individual demographics and objective clinical measures of disease have only a small influence on the experience of fatigue, the country of residence adds substantially. Economic and development status of the country only explain small parts of the variation among countries. More research is needed to identify other relevant cultural (attitudes, believes), climatological or linguistic aspects that could explaining fatigue. Disclosure of Interest: M. Hifinger Employee of: Hexal AG, Germany (inactive employment, maternity leave), P. Putrik: None declared, S. Ramiro: None declared, A. Keszei: None declared, I. Hmamouchi: None declared, M. Dougados: None declared, L. Gossec: None declared, A. Boonen: None declared DOI: 10.1136/annrheumdis-2014-eular.2098