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Objective: To define the association between change in body mass index (BMI) and the incidence and progression of the structural defects of knee osteoarthritis as assessed by radiography., Methods: Radiographic analyses of knees at baseline and at 4-5 years of follow-up were obtained from the following 3 independent cohort studies: the Osteoarthritis Initiative (OAI) study, the Multicenter Osteoarthritis Study (MOST), and the Cohort Hip and Cohort Knee (CHECK) study. Logistic regression analyses using generalized estimating equations, with clustering of both knees within individuals, were used to investigate the association between change in BMI from baseline to 4-5 years of follow-up and the incidence and progression of knee osteoarthritis., Results: A total of 9,683 knees (from 5,774 participants) in an "incidence cohort" and 6,075 knees (from 3,988 participants) in a "progression cohort" were investigated. Change in BMI was positively associated with both the incidence and progression of the structural defects of knee osteoarthritis. The adjusted odds ratio (OR) for osteoarthritis incidence was 1.05 (95% confidence interval [95% CI] 1.02-1.09), and the adjusted OR for osteoarthritis progression was 1.05 (95% CI 1.01-1.09). Change in BMI was also positively associated with degeneration (i.e., narrowing) of the joint space and with degeneration of the femoral and tibial surfaces (as indicated by osteophytes) on the medial but not on the lateral side of the knee., Conclusion: A decrease in BMI was independently associated with lower odds of incidence and progression of the structural defects of knee osteoarthritis and could be a component in preventing the onset or worsening of knee osteoarthritis., (© 2022 The Authors. Arthritis & Rheumatology published by Wiley Periodicals LLC on behalf of American College of Rheumatology.)

Objective: The relationship between in vivo knee load predictions and longitudinal cartilage changes has not been investigated. We undertook this study to develop an equation to predict the medial tibiofemoral contact force (MCF) peak during walking in persons with instrumented knee implants, and to apply this equation to determine the relationship between the predicted MCF peak and cartilage loss in patients with knee osteoarthritis (OA)., Methods: In adults with knee OA (39 women, 8 men; mean ± SD age 61.1 ± 6.8 years), baseline biomechanical gait analyses were performed, and annualized change in medial tibial cartilage volume (mm 3 /year) over 2.5 years was determined using magnetic resonance imaging. In a separate sample of patients with force-measuring tibial prostheses (3 women, 6 men; mean ± SD age 70.3 ± 5.2 years), gait data plus in vivo knee loads were used to develop an equation to predict the MCF peak using machine learning. This equation was then applied to the knee OA group, and the relationship between the predicted MCF peak and annualized cartilage volume change was determined., Results: The MCF peak was best predicted using gait speed, the knee adduction moment peak, and the vertical knee reaction force peak (root mean square error 132.88N; R 2 = 0.81, P < 0.001). In participants with knee OA, the predicted MCF peak was related to cartilage volume change (R 2 = 0.35, β = -0.119, P < 0.001)., Conclusion: Machine learning was used to develop a novel equation for predicting the MCF peak from external biomechanical parameters. The predicted MCF peak was positively related to medial tibial cartilage volume loss in patients with knee OA., (© 2021 The Authors. Arthritis & Rheumatology published by Wiley Periodicals LLC on behalf of American College of Rheumatology.)