Objective To explore the influencing factors of dwarfism in children and construct a nomogram model.

Methods From June 2020 to December 2022, 1, 500 children were selected as the research objects, and 1, 422 cases were effectively investigated. According to incidence of dwarfism, the children were divided into normal group (n=1, 351) and dwarfism group (n=71). Univariate and multivariate Logistic regression analyses were used to explore the influencing factors of dwarfism in children; the R software was used to construct a nomogram model for prediction of the occurrence of dwarfism in children, and the receiver operating characteristic (ROC) curve and calibration curve were used to evaluate the discrimination and consistency of the nomogram model.

Results Among the 1 422 children, 71 cases had dwarfism, with an incidence rate of 4.99%. Multivariate Logistic regression analysis showed that birth weight, family history of dwarfism, milk intake and physical exercise were the influencing factors for the occurrence of dwarfism in children (P < 0.05). The area under the curve of the ROC curve predicted by the nomogram model for the occurrence of dwarfism in children was 0.897 (95%CI, 0.856 to 0.938), with good discrimination; the calibration curve slope of the nomogram model for predicting the occurrence of dwarfism in children approached 1, and the Hosmer-Lemeshow goodness of fit test showed that the was 5.020 and P was 0.740, indicating good consistency.

Conclusion The nomogram model for predicting the occurrence of dwarfism in children based on four influencing factors of birth weight, family history of dwarfism, milk intake and physical exercise has good discrimination and consistency, which can provide reference for the development of personalized intervention measures in clinical practice.