a b s t r a c t Objective: To estimate the association between fine particulate (PM 2.5 ) and nitrogen dioxide (NO 2 ) pollution and systemic autoimmune rheumatic diseases (SARDs). Methods: Associations between ambient air pollution (PM 2.5 and NO 2 ) and SARDs were assessed using land-use regression models for Calgary, Alberta and administrative health data (1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007). SARD case definitions were based on Z 2 physician claims, or Z 1 rheumatology billing code; or Z1 hospitalization code (for systemic lupus, Sjogren's Syndrome, scleroderma, polymyositis, dermatomyositis, or undifferentiated connective tissue disease). Bayesian hierarchical latent class regression models estimated the probability that each resident was a SARD case, based on these case definitions. The sum of individual level probabilities provided the estimated number of cases in each area. The latent class model included terms for age, sex, and an interaction term between age and sex. Bayesian logistic regression models were used to generate adjusted odds ratios (OR) for NO 2 and PM 2.5 . pollutant models, adjusting for neighbourhood income, age, sex, and an interaction between age and sex. We also examined models stratified for First-Nations (FN) and non-FN subgroups. Results: Residents that were female and/or aged 445 had a greater probability of being a SARD case, with the highest OR estimates for older females. Independently, the odds of being a SARDs case increased with PM 2.5 levels, but the results were inconclusive for NO 2 . The results stratified by FN and non-FN groups were not distinctly different. Conclusion: In this urban Canadian sample, adjusting for demographics, exposure to PM 2.5 was associated with an increased risk of SARDs. The results for NO 2 were inconclusive