Abstract
Objectives
Arthritis is a broad term covering disparate diseases with varying prognoses. Epidemiological surveys are important tools for arthritis research, but they either fail to specify arthritis subtypes or they provide self-reported arthritis data that are potentially misclassified. This limits their use for research about arthritis subgroups. This study describes and compares characteristics of subjects self-reporting subtypes of arthritis in a Canadian epidemiological survey. We also consider the feasibility of developing methods for distinguishing subtypes of arthritis in such population surveys.
Methods
Using data from 119,904 adult participants in the Canadian Community Health Survey (CCHS) cycle 3.1, we identified those self-reporting one of four subtypes of arthritis and compared the four groups with regard to socio-demographic status, lifestyle and health characteristics, medication use, health care utilization and functional outcomes. Cross-tabulations of weighted prevalence were estimated and tested for statistical significance using the chi-square test.
Results
Descriptive results showed very few distinguishing characteristics across self-reported arthritis subtypes on 34 investigated variables. Participants with osteoarthritis were more likely to be older and female than other groups. Statistical testing showed no difference between rheumatoid arthritis, osteoarthritis and “other“ type of arthritis for physical activity level, health conditions, medication use, health care utilization and functional limitations.
Discussion
Characteristics of subjects who self-report different types of arthritis in a typical population health survey (CCHS) are not sufficiently dissimilar to justify valid data analyses and interpretation by arthritis subgroup. Future studies might focus on identifying and implementing supplemental questionnaire items in epidemiological population surveys.
Key words: Arthritis; arthritis, rheumatoid; osteoarthritis; epidemiologic methods; cluster analysis; health surveys
Résumé
Objectifs
L’arthrite est un terme large qui englobe différentes maladies ayant des pronostics variés. Les enquêtes épidémiologiques sont des outils importants pour la recherche sur l’arthrite. Toutefois, ces enquêtes ne permettent pas distinguer les sous-types d’arthrite. Ce problème limite l’utilisation des enquêtes populationnelles pour la recherche sur des soustypes d’arthrite. Notre étude vise à décrire et à comparer les différentes caractéristiques des sujets ayant déclaré différents sous-types d’arthrite dans l’Enquête sur la santé dans les collectivités canadiennes (ESCC), dans le but de développer une méthode permettant de distinguer les soustypes d’arthrite dans les enquêtes populationelles.
Méthodes
Nous avons analysé les données de 119 904 adultes ayant participé à l’ESCC (cycle 3.1). Les sujets ayant auto-rapportés un de quatre sous-types d’arthrite ont été comparés relativement à leur statut sociodémographique, leur style de vie, leur état de santé, leur utilisation de médicaments, leur utilisation du système de santé et leur statut fonctionnel. La construction de tableaux croisés des fréquences pondérées a permis d’estimer la signification statistique des associations à l’aide du chi-carré.
Résultats
Les résultats descriptifs ont démontré que les sous-groupes de l’arthrite se distinguaient très peu relativement aux 34 variables à l’étude. Les participants ayant auto-déclaré un diagnostic d’arthrose étaient en moyenne plus âgés et plus fréquemment des femmes par rapport aux autres sous-groupes d’arthrite. Il n’y avait aucune différence statistiquement significative entre les catégories arthrite rhumatoïde, arthrose et autre type d’arthrite, en ce qui concerne le niveau d’activité physique, l’état de santé, l’usage de médicaments, l’utilisation du système de santé et les limitations fonctionnelles des individus.
Discussion
Les caractéristiques des sujets auto-rapportant différents types d’arthrite lors d’une enquête typique sur la santé populationnelle (ESCC) ne sont pas suffisamment différentes pour justifier l’analyse valide et l’interprétation des données selon le sous-groupe d’arthrite. Les études à venir devront mettre l’accent sur l’identification et la validation de questions supplémentaires afin de distinguer les plus importants sousgroupes d’arthrite dans les enquêtes épidémiologiques de la population.
Mots clés: arthrite, arthrite rhumatoïde, arthrose, méthode épidémiologique, analyse en grappe
Footnotes
Disclaimer: Analyses were based on Statistics Canada’s Canadian Community Health Survey, cycle 3.1, public use microdata file, which contains anonymized collected data. All computations on these microdata were prepared by the authors, and the responsibility for the use and interpretation of these data is entirely that of the authors.
References
- 1.Ensworth S. Rheumatology: 1. Is it arthritis? Can Med Assoc J. 2000;162(7):1011–16. [PMC free article] [PubMed] [Google Scholar]
- 2.Lagacé C, Perruccio A, DesMeules M, Badley E. The impact of arthritis on Canadians. In: Arthritis in Canada: An Ongoing Challenge. Ottawa, ON: Health Canada; 2003. [Google Scholar]
- 3.Stokes J, Desjardins S, Perruccio A. Arthritis in Canada: An Ongoing Challenge. Ottawa, ON: Health Canada; 2003. Economic burden. [Google Scholar]
- 4.Perruccio AV, Power JD, Badley EM. Revisiting arthritis prevalence projections- it’s more than just the aging of the population. J Rheumatol. 2006;33(9):1856–62. [PubMed] [Google Scholar]
- 5.Picavet HSJ, Hazes JMW. Prevalence of self reported musculoskeletal diseases is high. Ann Rheum Dis. 2003;62(7):644–50. doi: 10.1136/ard.62.7.644. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Watson DJ, Rhodes T, Guess HA. All-cause mortality and vascular events among patients with rheumatoid arthritis, osteoarthritis, or no arthritis in the UK General Practice Research Database. J Rheumatol. 2003;30(6):1196–202. [PubMed] [Google Scholar]
- 7.Keefe FJ, Smith SJ, Buffington AL, Gibson J, Studts JL, Caldwell DS. Recent advances and future directions in the biopsychosocial assessment and treatment of arthritis. J Consult Clin Psychol. 2002;70(3):640–55. doi: 10.1037/0022-006X.70.3.640. [DOI] [PubMed] [Google Scholar]
- 8.Dickens C, McGowan L, Clark-Carter D, Creed F. Depression in rheumatoid arthritis: A systematic review of the literature with meta-analysis. Psychosom Med. 2002;64(1):52–60. doi: 10.1097/00006842-200201000-00008. [DOI] [PubMed] [Google Scholar]
- 9.Ling SM, Fried LP, Garrett E, Hirsch R, Guralnik JM, Hochberg MC. The accuracy of self-report of physician diagnosed rheumatoid arthritis in moderately to severely disabled older women. Women’s Health and Aging Collaborative Research Group. J Rheumatol. 2000;27(6):1390–94. [PubMed] [Google Scholar]
- 10.Cooper GS, Wither J, McKenzie T, Claudio JO, Bernatsky S, Fortin PR. The prevalence and accuracy of self-reported history of 11 autoimmune diseases. J Rheumatol. 2008;35(10):2001–4. [PubMed] [Google Scholar]
- 11.Karlson EW, Mandl LA, Aweh GN, Grodstein F. Coffee consumption and risk of rheumatoid arthritis. Arthritis Rheum. 2003;48(11):3055–60. doi: 10.1002/art.11306. [DOI] [PubMed] [Google Scholar]
- 12.Gram IT, Riise T, Honda Y. Rheumatoid arthritis: A commonly misused diagnosis by the general population. Clin Rheumatol. 1997;16(3):264–66. doi: 10.1007/BF02238961. [DOI] [PubMed] [Google Scholar]
- 13.Kvien TK, Glennas A, Knudsrod OG, Smedstad LM. The validity of self-reported diagnosis of rheumatoid arthritis: Results from a population survey followed by clinical examinations. J Rheumatol. 1996;23:1866–71. [PubMed] [Google Scholar]
- 14.Szoeke CEI, Dennerstein L, Wluka AE, Guthrie JR, Taffe J, Clark MS, et al. Physician diagnosed arthritis, reported arthritis and radiological non-axial osteoarthritis. Osteoarthr Cartilage. 2008;16(7):846–50. doi: 10.1016/j.joca.2007.12.001. [DOI] [PubMed] [Google Scholar]
- 15.Statistics Canada. Canadian Community Health Survey Cycle 3.1. Master file documentation. Ottawa, ON: Statistics Canada; 2005. [Google Scholar]
- 16.Statistics Canada. Canadian Community Health Survey 2003. Non-medical Determinants of Health. Ottawa, ON: Statistics Canada; 2006. [Google Scholar]
- 17.Young A, Koduri G. Extra-articular manifestations and complications of rheumatoid arthritis. Best Pract Res Clin Rheumatol. 2007;21(5):907–27. doi: 10.1016/j.berh.2007.05.007. [DOI] [PubMed] [Google Scholar]
- 18.Felson DT, Lawrence RC, Dieppe PA, Hirsch R, Helmick CG, Jordan JM, et al. Osteoarthritis: New insights. Part 1: The disease and its risk factors. Ann Intern Med. 2000;133(8):635–46. doi: 10.7326/0003-4819-133-8-200010170-00016. [DOI] [PubMed] [Google Scholar]
- 19.Kopec JA, Rahman MM, Berthelot JM, Le Petit C, Aghajanian J, Sayre EC, et al. Descriptive epidemiology of osteoarthritis in British Columbia, Canada. J Rheumatol. 2007;34(2):386–93. [PubMed] [Google Scholar]
- 20.Mili F, Helmick CG, Moriarty DG. Health related quality of life among adults reporting arthritis: Analysis of data from the Behavioral Risk Factor Surveillance System, US, 1996–99. J Rheumatol. 2003;30(1):160–66. [PubMed] [Google Scholar]
- 21.Kaplan MS, Huguet N, Newsom JT, McFarland BH. Characteristics of physically inactive older adults with arthritis: Results of a population-based study. Prev Med. 2003;37(1):61–67. doi: 10.1016/S0091-7435(03)00059-8. [DOI] [PubMed] [Google Scholar]
- 22.Machado G. Health status indicators among community-dwelling elders with arthritis: The Bambui Health and Aging Study. J Rheumatol. 2006;33(2):342–47. [PubMed] [Google Scholar]
- 23.Berard A, Solomon DH, Avorn J. Patterns of drug use in rheumatoid arthritis. J Rheumatol. 2000;27(7):1648–55. [PubMed] [Google Scholar]
- 24.Michaud K, Wolfe F. Comorbidities in rheumatoid arthritis. Best Pract Res Clin Rheumatol. 2007;21(5):885–906. doi: 10.1016/j.berh.2007.06.002. [DOI] [PubMed] [Google Scholar]
- 25.Sacks JJ, Harrold LR, Helmick CG, Gurwitz JH, Emani S, Yood RA. Validation of a surveillance case definition for arthritis. J Rheumatol. 2005;32(2):340–47. [PubMed] [Google Scholar]
- 26.Bombard JM, Powell KE, Martin LM, Helmick CG, Wilson WH. Validity and reliability of self-reported arthritis: Georgia Senior Centers, 2000–2001. Am J Prev Med. 2005;28(3):251–58. doi: 10.1016/j.amepre.2004.12.004. [DOI] [PubMed] [Google Scholar]
- 27.Lawrence RC, Felson DT, Helmick CG, Arnold LM, Choi H, Deyo R N A D Workgroup, et al. Estimates of the prevalence of arthritis and other rheumatic conditions in the United States: Part II. Arthritis Rheum. 2008;58(1):26–35. doi: 10.1002/art.23176. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Cunningham LS, Kelsey JL. Epidemiology of musculoskeletal impairments and associated disability. Am J Public Health. 1984;74(6):574–79. doi: 10.2105/AJPH.74.6.574. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Peat G, Thomas E, Duncan R, Wood L, Hay E, Croft P. Clinical classification criteria for knee osteoarthritis: Performance in the general population and primary care. Ann Rheum Dis. 2006;65(10):1363–67. doi: 10.1136/ard.2006.051482. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.O’Reilly SC, Muir KR, Doherty M. Screening for pain in knee osteoarthritis: Which question? Ann Rheum Dis. 1996;55(12):931–33. doi: 10.1136/ard.55.12.931. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.March LM, Schwarz JM, Carfrae BH, Bagge E. Clinical validation of self-reported osteoarthritis. Osteoarthr Cartilage. 1998;6(2):87–93. doi: 10.1053/joca.1997.0098. [DOI] [PubMed] [Google Scholar]