Risk factors for growth retardation in children with juvenile idiopathic arthritis: a case-control study - Ying Zhang; Liping Song; Weihu Ma; Ye Wang; Peipei Wang; Xiaolin Zhang; Zhe Zhang; Yuan Zhang; Qianhui Yu; Yang Yu; Lin Zhang (BMC Musculoskeletal Disorders)
Abstract Objective This study aimed to investigate the role of various factors contributing to growth retardation, including nutritional intake, disease duration, and treatment history, and further identify key risk factors that may influence growth outcomes in patients with juvenile idiopathic arthritis (JIA). Methods Clinical data from 155 JIA children who were treated at our hospital between January 2019 and December 2022 were analyzed. The children were divided into the growth retardation group (n = 40) and the non-growth retardation group (n = 115) based on the height Z-score < -2 SD or not. The two groups were compared based on their baseline characteristics, disease-related factors, dietary habits, lifestyle, and family background. Logistic regression and receiver operating characteristic (ROC) curve analyses were employed to identify and assess the factors associated with growth retardation. Results Out of the 155 children, 40 (25.81%) were diagnosed with growth retardation. Children with growth retardation were more likely to have a disease duration ≥ 3 years (72.50% vs. 39.13%, P < 0.001), exercise time < 1 h/per day (68.50% vs. 33.04%, P < 0.001), glucocorticoid use (65.00% vs. 34.78%, P = 0.001), and active disease activity (72.50% vs. 37.39%, P < 0.001). These factors were identified as independent risk factors for growth retardation in multivariate analysis. The area under the curve (AUC) values for these factors ranged from 0.651 to 0.676, indicating moderate predictive accuracy. When considering all these factors together, the combined model demonstrated an AUC value of 0.702, suggesting a high predictive value. Conclusion The incidence of growth retardation in children with JIA is high, with factors such as disease duration, exercise time, GC treatment, clinic visits, picky eating, and disease activity contributing to its development. While each of these factors demonstrates moderate predictive value individually, their combined consideration significantly improves predictive accuracy. Clinical trial number Not applicable.