Analysis in risk factors of respiratory tract infectionin preschool children and construction of nomogram prediction model

  Objective  To analyze the risk factors of respiratory tract infection in preschool children, and establish a quantitative nomogram prediction model.

  Methods  A cross-sectional survey and stratified cluster random sampling were used to select 2 208 preschool children from 3 kindergartens, and they were diagnosed according to the diagnostic criteria of recurrent respiratory tract infection, upper respiratory tract infection and lower respiratory tract infection. The main risk factors of respiratory tract infection in preschoolers were analyzed.

  Results  In 2 208 preschoolers, there were 522 children (23.6%) with recurrent respiratory tract infection, 265 children(12.0%) with upper respiratory tract infection and 397 children (18.0%) with lower respiratory tract infection. Logistic regression analysis showed that asthma, allergic history, initial use of antibiotics < 6 months, breastfeeding time < 6 months and increase of maternal body mass index (BMI) for every 3 kg/m² were the main risk factors of recurrent respiratory tract infection and lower respiratory tract infection, while asthma, allergic history, initial use of antibiotics < 6 months and increase of maternal BMI for every 3 kg/m² were the main risk factors of upper respiratory tract infection(P < 0.05). Receiver Operating Curve (ROC) analysis showed that Area Under Curves (AUC) of nomogram for predicting recurrent respiratory tract infection, upper respiratory tract infection and lower respiratory tract infection were 0.865, 0.833 and 0.841, respectively (P < 0.05).

  Conclusion  Preschool children have a high incidence of respiratory tract infection. Asthma, allergic history, initial use of antibiotic < 6 months and increase of maternal BMI for every 3 kg/m² are the main risk factors of recurrent respiratory tract infection and lower respiratory tract infection. The establishment of a quantitative nomogram model can better guide clinical physicians to early identify high-risk children and carry out early intervention.