儿童孤独症谱系障碍发生预测模型构建研究

Construction of predictive models for the occurrence of autism spectrum disorder in children

目的:探讨儿童孤独症谱系障碍发生危险因素并构建预测模型,旨在为疾病防治方案制定提供更多参考。方法:纳入孤独症谱系障碍患儿131例,并以同期体检健康儿童107名设为对照;对儿童孤独症谱系障碍发生危险因素进行单因素以及多因素分析,后构建儿童孤独症谱系障碍发生预测模型,并进行效能分析。结果:孤独症谱系障碍组与对照组接受民主接纳教养情况、父亲年龄、父亲受教育水平情况、每天累计频繁接触时间比较差异有统计学意义(P<0.05)。多因素分析显示,父亲年龄更大、每天累计频繁接触时间更长、非民主接纳教养、父亲大专以下受教育水平均是儿童孤独症谱系障碍发生的独立危险因素(P<0.05)。利用父亲年龄,每天累计频繁接触时间,民主接纳教养,父亲大专及以上文化对于儿童孤独症谱系障碍发生情况进行预测,约登指数为31.15%、97.71%、38.85%、38.89%。结论:儿童孤独症谱系障碍发生与父亲年龄、每天累计频繁接触时间、教养方式及父亲受教育水平等有关;基于上述危险因素构建预测模型能够准确预测儿童孤独症谱系障碍发生。

Objective:To explore the risk factors of autism spectrum disorder in children and to build a prediction model,in order to provide more references for disease prevention and treatment.Method:A total of 131 children with autism spectrum disorder were included,and 107 healthy children in the same period were taken as control.Univariate and multifactorial analysis of risk factors for autism spectrum disorder in children were carried out.Predictive models for the occurrence of autism spectrum disorder in children were constructed and its efficacy was analyzed.Results:There were statistically significant differences between the autism spectrum disorder group and the control group in democratic acceptance of parenting,paternal age,paternal education level,and daily cumulative frequent contact time(P<0.05).Multivariate analysis showed that older paternal age,longer cumulative daily frequent contact time,non-democratic parenting and paternal college education level were independent risk factors for autism spectrum disorder in children(P<0.05).According to the father's age,daily frequent contact time,democratic acceptance of parenting,father's college education or above,the incidence of autism spectrum disorder in children was predicted by the estimated index of 31.15%,97.71%,38.85%,38.89%.Conclusion:The incidence of autism spectrum disorder in children is related to paternal age,daily cumulative frequent contact time,parenting style and paternal education level.The prediction model based on the above risk factors can accurately predict the occurrence of autism spectrum disorder in children.