Article Text

PDF
OP0047 Metabolic and Lifestyle Predictors of Inflammatory Polyarthritis in the EPIC-2-NOAR Study
  1. J.C. Sergeant1,2,
  2. S.M.M. Verstappen1,
  3. C. Morgan1,
  4. R.N. Luben3,
  5. A. Bhaniani3,
  6. S. Anuj3,
  7. A. MacGregor4,
  8. N. Wareham3,
  9. D.P.M. Symmons1,2,
  10. K.-T. Khaw3,
  11. I.N. Bruce1,2
  12. on behalf of RA-MAP consortium
  1. 1Arthritis Research UK Centre for Epidemiology, Centre for Musculoskeletal Research, Manchester Academic Health Science Centre, University of Manchester
  2. 2NIHR Manchester Musculoskeletal Biomedical Research Unit, Central Manchester University Hospitals NHS Foundation Trust, Manchester
  3. 3Department of Public Health and Primary Care, University of Cambridge School of Clinical Medicine, Cambridge
  4. 4Norwich Medical School, University of East Anglia, Norwich, United Kingdom

Abstract

Background Linkage of the European Prospective Investigation of Cancer, Norfolk (EPIC-Norfolk) population and the Norfolk Arthritis Register (NOAR), the EPIC-2-NOAR study, has enabled investigation of potential lifestyle predictors of incident inflammatory polyarthritis (IP) [1]. However, potential metabolic predictors of IP have not been as well investigated in this population and have not been considered alongside lifestyle factors.

Objectives To assess the addition of metabolic factors to an established multivariate lifestyle factor model for incident IP [1], with updated record linkage in EPIC-2-NOAR.

Methods Data on lifestyle factors (pack-years of smoking (adjusted for never being a smoker), smoking status, alcohol consumption (adjusted for being a teetotaller), body mass index, socio-economic status, self-reported diabetes mellitus (DM), parity and duration of breast feeding) was collected by questionnaire at entry to EPIC-Norfolk. Metabolic factors (serum uric acid, HDL-C, Apo-A1, Apo-B and HbA1c) were measured using a non-fasting blood sample taken at the same time. EPIC-Norfolk participants who subsequently developed IP were identified via linkage with NOAR, a primary care based inception cohort study of early IP. Associations between the metabolic predictors and incident IP were assessed using Cox regression: univariately, adjusting for age and gender, and by adding individual predictors to the existing multivariate Cox models [1], one for all participants (with an interaction term for gender and pack years of smoking) and one for females only. Subjects were followed until development of IP, death, loss to follow-up or May 2014, whichever came first.

Results Data was available on 25 636 subjects (55% female), including 231 incident cases of IP (66% female). Median (IQR) age at entry to EPIC-Norfolk was 59 (51-67) years, median follow-up was 214 (198-230) months and median time to onset of IP was 79 (34-136) months. No significant association was observed between incident IP and serum uric acid, HDL-C, Apo-A or Apo-B. Baseline HbA1c was positively associated with incident IP in univariate analysis (HR 1.22, 95% CI (1.03, 1.44)), when adjusted for sex and age (HR 1.27 (1.08, 1.49)) and when added to the existing multivariate lifestyle factor models for all (HR 1.26 (1.07, 1.47)) and for females only (HR 1.23 (1.00, 1.52)). Inclusion of HbA1c in the multivariate models led to self-reported DM no longer being significantly associated with IP.

Conclusions Baseline HbA1c was significantly associated with incident IP, at the expense of self-reported DM in an established multivariate lifestyle factor model. While DM is an established risk factor for IP, HbA1c levels may capture additional information on those in a prediabetic state and could prove a more sensitive marker of future IP.

References

  1. Lahiri et al. Ann Rheum Dis 2014; 73: 219

Disclosure of Interest None declared

Statistics from Altmetric.com

Request permissions

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.