Diet quality and nutritional risk in patients with Wilson’s disease: a cross-sectional study

Objective This study aimed to evaluate diet quality in patients with Wilson’s disease (WD), identify associated factors, and investigate the relationship between diet quality and nutritional risk in this population. Methods This cross-sectional study enrolled patients with WD at a tertiary hospital in Fujian Province from November 2023 to February 2025. Dietary quality was evaluated using the Dietary Quality Index-International (DQI-I), and nutritional risk was assessed with the Mini Nutritional Assessment (MNA). A DQI-I score of 61 (median) was used to dichotomize dietary quality. Logistic regression identified factors associated with lower DQI-I scores. Associations between DQI-I and nutritional risk were examined using three models: unadjusted (Model 1); adjusted for age, sex, and BMI (Model 2); and further adjusted for educational attainment, disease duration, smoking, clinical classification, comorbidities, chelator, zinc preparation, self-reported medication adherence, liver damage, 24-h urinary copper, and albumin (Model 3). A linear regression scatterplot was used to visualize the association. Results A total of 91 patients with WD were included, with a mean DQI-I score of 59.51 ± 7.42. Overall, 74.7% were either malnourished or at risk of malnutrition. Lower DQI-I scores were significantly associated with female sex, lower educational attainment, longer disease duration, and smoking (all p < 0.05). In the unadjusted model (Model 1), a DQI-I score ≤61 was associated with a 34.83-fold increased risk of malnutrition and a 4.98-fold increased risk of nutritional risk (both p < 0.05), compared to scores >61. These associations remained significant after multivariable adjustment (Models 2 and 3). DQI-I scores were moderately correlated with nutritional risk ( r = 0.448, p < 0.001). Conclusion Patients with WD exhibit suboptimal dietary quality and a high prevalence of nutritional risk. Lower DQI-I scores independently predict malnutrition, emphasizing the utility of diet quality assessment in clinical care. Early identification of at-risk individuals, coupled with targeted, dietitian-led interventions, may improve dietary variety, mitigate nutritional risk, and support better long-term outcomes.