Background/Aims Glucocorticoids (GCs) used in the treatment of inflammatory rheumatic conditions can impact on patients in different ways. The objective of this study was to identify socio-demographic and clinical factors associated with health-related quality of life (HRQoL) in patients undertaking GCs for a rheumatic disease. Methods This was a cross-sectional study using online survey methods. Participants taking GCs for a rheumatic disease from Australia, United Kingdom and the United States of America were included. HRQoL was measured using the EQ-5D-5L converted into a linear EQ5D index value. Eight explanatory factors (age, sex, country, educational level, employment status, disease group, self-reported disease state, and dose of GCs) were tested for potential association with HRQoL using univariable and multivariable (hierarchical) analyses. Factors found to have a significant association with EQ5D index at a P < 0.05 level in the multivariable model were considered to be independently associated with HRQoL. Results A total of 945 patients completed the EQ-5D-5L with no missing values: UK n = 742 (79%); USA n = 139 (15%); Australia/New Zealand n = 64 (7%); mean age 57.6 (SD = 13.6); 833 (88%) women. Participants with inflammatory arthritis n = 197 (21%), connective tissue disease and/or vasculitis n = 402 (43%), giant cell arteritis and/or polymyalgia rheumatica n = 346 (37%) were included. Those with self-reported active disease were 726 (77%). Mean (SD) EQ5D index was 0.64 (0.25); there were significant differences between groups in EQ-5D-5L index by age (median split, t=-3.77, p < 0.001); sex (t = 3.40, p < 001); educational level (F[3]=10.51, p < 0.001); employment status (F[6]=37.67, P < 0.001); disease group (T[2]=20.23, p < 0.001); disease state (T=-8.46, p < 0.001); and the dose of GCs(T = 2.95, p < 0.001). Worse HRQoL was associated with older age, being female, low educational attainment, being unemployed, having an inflammatory arthritis or a CTD, disease being active, and taking a higher dose of GC. Of the eight factors that were tested in the multivariable model, five were found to be independently associated with HRQoL. These were: disease state (beta = 0.12, p < 0.001), disease group (beta = 0.06, p < 0.001), employment status (beta = 0.05, p < 0.001), sex (beta = 0.05, p < 0.001), and educational level (beta = 0.04, p < 0.001). This 5-factor model explained 18% of the variance in EQ5D index scores (F[1, 926] = 4.97, P = 0.026). The excluded factors in the model were age, dose, and country. Conclusion In our data, we identified 5 factors independently associated with worse HRQoL in patients being treated with GCs. Over 80% of the variance was not explained by our model likely due to use of a generic HRQoL measure (EQ-5D-5L) as outcome variable, and the small number of explanatory variables tested within this survey. Further research is required to identify potential targets to support interventions.