Aim: To evaluate the potential role of age, sex, body mass index (BMI), radiographic features and pain in knee osteoarthritis (OA) case ascertainment.
Methods: A cross-sectional study was performed using information from the EPIPorto cohort; social, demographic, behavioral and clinical data was obtained. Pain was assessed using a pain frequency score (regarding ever having knee pain, pain in the last year, in the last 6 months and in the last month). Knee radiographs were classified using the Kellgren-Lawrence scale (0-4). Path analysis was used to assess the plausibility of the causal assumptions and a classification tree to identify characteristics that could improve the identification of patients with radiographic OA.
Results: Higher age and higher BMI were associated with higher radiographic score, but sex had no statistical association. Females, higher age, higher BMI and higher radiographic score were statistically associated with higher pain scores. For both genders, the classification tree estimated age as the first variable to identify individuals with knee radiographic features. In females older than 56 years, pain frequency score is the second discriminator characteristic, followed by age (> 65 years) and (BMI > 30 kg/m2 ). Higher pain frequency and BMI > 29 kg/m2 were relevant for identifying OA in men with ages between 43.5 and 55.5 years.
Conclusions: Age, BMI and pain frequency are independently associated with radiographic OA and the use of information on these characteristics can improve the identification of patients with knee OA. Beyond age, pain complaints are particularly relevant but the level of pain is different by sex.
Keywords: clinical aspects; decision analysis; knee osteoarthritis; pain; radiography.
© 2015 Asia Pacific League of Associations for Rheumatology and Wiley Publishing Asia Pty Ltd.