Quantifying Mediators of Racial Disparities in Knee Osteoarthritis Outcome Scores: A Cross-Sectional Analysis

Studies on symptomatic osteoarthritis suggest that Black patients report worse pain and symptoms compared with White patients with osteoarthritis. In this study, we aimed to quantify the relationship among variables such as overall health and socioeconomic status that may contribute to disparities in patient-reported outcomes. METHODS: A total of 223 patients were enrolled. A mediation analysis was used to evaluate cross-sectional associations between race and the Knee injury and Osteoarthritis Outcome Score (KOOS) questionnaire, which was administered to patients prior to undergoing primary total knee arthroplasty. RESULTS: Black patients had worse KOOS pain, symptoms, and activities of daily living subscale scores than White patients. In our cohort, Black patients were younger, more likely to be female, and more likely to report lower educational status. We identified age, sex, Charlson Comorbidity Index, and education as partial mediators of racial disparities in KOOS subscale scores. Insurance status, deformity, radiographic (Kellgren-Lawrence) grade, C-reactive protein level, marital status, body mass index, and income did not show mediating effects. We found that, if age and sex were equal in both cohorts, the racial disparity in KOOS symptom scores would be reduced by 20.7% and 9.1%, respectively (95% confidence intervals [CIs], −5.1% to 47% and −5.5% to 26.3%). For KOOS pain scores, age and education level explained 18.9% and 5.1% of the racial disparity (95% CIs, −0.6% to 37% and −10.8% to 22.9%). Finally, for KOOS activities of daily living scores, education level explained 3.2% of the disparity (95% CI, −19.4% to 26.6%). CONCLUSIONS: No single factor in our study completely explained the racial disparity in KOOS scores, but our findings did suggest that several factors can combine to mediate this disparity in outcome scores. Quantification of variables that mediate racial disparity can help to build models for risk adjustment, pinpoint vulnerable populations, and identify primary points of intervention. LEVEL OF EVIDENCE: Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.