ABSTRACT
Objective:To analyze the influencing factors of attention deficit hyperactivity disorder (ADHD) in children and construct a Nomogram prediction model.Methods:A total of 5 409 children aged 7 to 16 from 5 schools in Xinjiang were investigated by using SNAP-Ⅳ assessment scale and influencing factors questionnaire.Least absolute shrinkage and selection operator (LASSO) regression and multivariate Logistic regression were used to analyze and investigate the influencing factors of ADHD in children, and then Nomogram prediction model was established. Results:(1)The detection rate of ADHD was 7.3%.(2) The LASSO- Logistic regression model showed that the history of febrile convulsions ( OR=5.97, 95% CI: 3.52-9.86), the history of epilepsy disease ( OR=11.86, 95% CI: 7.83-17.89), the history of head trauma disease ( OR=10.0, 95% CI: 7.27-13.71), mother′s delivery method ( OR=2.53, 95% CI: 1.99-3.23), mother′s education level ( OR=2.26, 95% CI: 1.45-3.67), mother′s smoking more than 1 year ( OR=12.65, 95% CI: 8.30-19.34), whether the family environment is quiet ( OR=1.27, 95% CI: 1.00-1.63), and the education method of beating and scolding ( OR=3.05, 95% CI: 2.13-4.31) was an indepen-dent risk factor for children with ADHD; (3)The Nomogram prediction model was built and verified by Bootstrap for 1 000 samples.The C-index was 0.81(95% CI: 0.78-0.83), suggesting that the Nomogram prediction model has good prediction ability, accuracy, and distinction.Decision curve analysis (DCA) of the clinical decision curve suggested that patients with Nomogram model with a predictive probability threshold greater than 0.2 had a higher clinical net benefit. Conclusions:The detection rate of ADHD was 7.3%, which was higher than the national average.The Nomogram prediction model drawn here can provide individualized ADHD risk predictions for children based on the history of hyperthermia, epilepsy, and head trauma, maternal mode of childbirth, maternal education level, maternal education level, maternal smoking for more than 1 year, quiet family environment, and scolding education methods.
ABSTRACT
Objective To investigate differences between Han and Uyghur children in dyslexia prevalence and potential environmental risk factors as well as to provide diagnosis and treatment evidence for dyslexia children . Methods We used cluster sampling to recruit 2 854 students in grades 3~6 from five Uyghur -Chinese bilingual primary schools in Xinjiang province .The children with dyslexia were selected step by step according to the defini‐tion of ICD-10 and DSM -IV .The children with DD and children without DD were selected and compared by 1∶1 of the same class ,ages and genders .Then single factor analysis and logistic regression analysis were used to as‐sess children'environmental risk factors .Results In total ,2 438 effective quostionnaires have been got .The difference between Han (3 .89% ) and Uyghur (7 .05% ) dyslexia prevalence was statistically significant .The factor analysis revealed that educational grades ,family income ,father's and mother's occupations ,and their education levels as well as some home literacy environmental factors were significantly different for the two groups of children with dyslexia (P<0 .05) .Conclusion The prevalence of dyslexia was high in both groups ,and especially for Uyghur children . Some environmental factors may be responsible for the differences noted ,especially for the occupation of mother .