Influence of Education on Disease Activity and Damage in Systemic Lupus Erythematosus: Data From the 1000 Canadian Faces of Lupus

Abstract

Objective To determine whether socioeconomic status assessed by education is associated with disease activity and the risk of organ damage in systemic lupus erythematosus (SLE). Methods Data from the 1000 Canadian Faces of Lupus, a multicenter database of adult SLE patients, was used to compare education as either low (did not complete high school) or high (completed high school or further) for disease activity and damage. Education was also studied as a continuous variable. The relationships between education and SLE outcomes (any organ damage defined as a Systemic Lupus International Collaborating Clinics/American College of Rheumatology Damage Index [SDI] score ≥1, serious organ damage [SDI score ≥3], and end‐stage renal disease) were evaluated using logistic regression analyses adjusted for age, sex, race/ethnicity, and disease duration. Results A total of 562 SLE patients met inclusion criteria (mean age 47 years, 91% female, and mean disease duration of 10 years); 81% had high education. The low education group was twice as likely to be work disabled (30%; P < 0.0001); they had higher disease activity and reduced renal function. Linear regression analysis revealed that low education was significantly associated with higher disease activity at enrollment into the 1000 Canadian Faces of Lupus database, after adjustment for age (at entry and at diagnosis), race/ethnicity, and sex (B 1.255 + 0.507 [SE], β = 0.115, P = 0.014). In our adjusted logistic regression models we were unable to demonstrate significant associations between education and SLE damage. Results did not change when varying the education variable. Conclusion In this cohort, low education was associated cross‐sectionally with higher disease activity and work disability, but not damage.

Persistent Disease Activity Remains a Burden for Patients with Systemic Lupus Erythematosus

“…Lower incomes or socioeconomic status have been previously associated with increased damage accrual 39,40,41,42 , including in this cohort 16 . We had previously also found that lower educational attainment was associated with higher disease activity in this same cohort in cross-sectional analysis 43 . The relationship between socio- economic status and SLE is not well understood, although it has become clear that the effect goes beyond access to care 44 .…”

Predictors of persistent disease activity and long quiescence in systemic lupus erythematosus: results from the Hopkins Lupus Cohort

“…Consistent with our findings, a multicentre study in Canada which included African American in a smaller percentage (7.7%) showed that low education (less than 12 years) was associated with higher SLEDAI score at baseline, even after adjustment for age, ethnicity and gender. 26 A possible explanation to the association of higher education and pLQ pattern is that higher education is associated with stronger adherence to treatment decisions leading to favourable disease outcomes such as disease inactivity. The effect of educational status on drug adherence has been implied by studies conducted on cutaneous lupus and cardiovascular diseases.…”

Chinese SLE Treatment and Research Group (CSTAR) registry:VIII. Influence of socioeconomic and geographical variables on disease phenotype and activity in Chinese patients with SLE

“…The SES of SLE patients has been evaluated in North America, some European countries and Latin America . However, due to limitations in resources, data regarding the socioeconomic and disease features of SLE in Chinese populations have not been reported, with the exception of some retrospective and regional analyses .…”

“…Then, for the regional economic and climate variables, univariate linear regression was used to evaluate the effects of regional variables on the continuous dependent variables, such as the disease activity score, whereas logistic regression was used for the category‐dependent variables, such as nephropathy. A multivariate linear regression analysis using a stepwise method was performed to determine the potential risk factors for higher SLEDAI in the final model, and a stepwise binary logistic regression was used to determine the risk factors for nephropathy . Multicollinearity was assessed in all of the models with a covariance matrix.…”