To establish a nomogram prediction model for the comorbidity risk of myopia and neck and shoulder pain among primary and secondary school students in Nanjing city, Jiangsu province, and to provide a scientific basis for the joint prevention and control of myopia and neck and shoulder pain among these students.

From September to October 2023, a stratified random sampling method was used to select 14 733 primary and secondary school students in urban and suburban areas of Nanjing city for questionnaire surveys and vision tests. A multifactorial unconditional logistic regression analysis was used to screen the influencing factors of myopia and neck and shoulder pain comorbidity among primary and secondary school students in Nanjing city, and a nomogram prediction model was established. The Area Under Curve (AUC) of the Receiver Operating Characteristic (ROC) Curve was used to evaluate the discrimination of the model, and the Hosmer-Lemeshow test and Calibration curve were used to evaluate the goodness of fit of the model.

Among the 12 529 primary and secondary school students finally included in the analysis in Nanjing city, 3 040 had both myopia and neck and shoulder pain, with a comorbidity rate of 24.26%. Multifactorial unconditional logistic regression analysis showed that being in middle or high school, being female, often or always lying down or leaning to read books or electronic screens, continuous near-vision time ≥ 30 min, after-school homework time ≥ 2 h/d, screen time ≥ 2 h/d, and social jet lag > 2 h were risk factors for myopia and neck and shoulder pain comorbidity among primary and secondary school students in Nanjing city. A healthy diet, outdoor breaks between classes, desk and chair height adjusted according to height, often or always keeping a distance of > 1 foot from books when reading and writing, outdoor activity time ≥ 1 h/d, and adequate sleep time were protective factors for myopia and neck and shoulder pain comorbidity among primary and secondary school students in Nanjing city. A nomogram prediction model for the comorbidity risk of myopia and neck and shoulder pain among primary and secondary school students in Nanjing city was established based on these 13 variables. The AUC of the model was 0.741 (95%CI: 0.732 - 0.751). The goodness of fit of the prediction model was good (χ² = 3.933, P = 0.863), and the predicted values were basically consistent with the actual values, indicating that the model had a good predictive effect.

The nomogram prediction model for the comorbidity risk of myopia and neck and shoulder pain among primary and secondary school students in Nanjing city established in this study has a good predictive effect and can provide a reference for the development of personalized intervention measures for myopia and neck and shoulder pain among primary and secondary school students.