安阳市中学生个体因素、健康行为预测吸烟行为模型的研究

Astudy on the Predicting Model of Smoking Rate for the Middle School Students and High School Students in Anyang according the Individual Factors and Health Behavior

目的通过安阳市中学生个体因素、健康行为建立预测吸烟行为的模型。方法选择2013年1—12月安阳市8所全日制中学的2 160名学生进行调查,根据不同的学校类型选用中国疾病预防控制中心颁布的《中国青少年健康危险相关行为调查》问卷相对应的初中、高中调查表,通过调查获取所有调查对象的个人基本信息、健康相关行为等因素,建立累积logit模型来预测学生吸烟行为。结果多因素分析筛选出19个因素对模型有意义。logit模型χ~2值为18.383,P=0.343,即本资料适用于logit模型的建立。零假设时,Wald=162.37,进入logit模型的22个因素对模型的反应变量影响差异有统计学意义。拟合优度=293.28,分散度参数为0.271,P=1.000>0.05,说明logit累积模型拟合较好,分散度<1,表明无分散过度的情况。R=0.896,R2=0.803,预测可以应用此模型预测,F=11.239,P<0.05,说明此模型可信。对筛选出的22个因素与中学生吸烟现状建模,计算的累积模型的2 142个调整R2均小于原调整的R2,说明拟合的logit累积模型具有一定的实用性。不同学生吸烟的观察值与预测值一致性程度较好。结论可通过建立可信的模型预测青少年的吸烟情况,并根据影响中学生吸烟的因素采取有效的措施进行干预,减少青少年的吸烟行为。

OBJECTIVE To establish a model for predicting smoking rates for secondary students in Anyang according the individualfactors and health behavior. METHODS To investigate 2 160 students in 8 secondary school in Anyang from Jan. 2013 to Dec. 2013 and establish a model for predicting smoking rates by getting basic information, health related behavior and other factors according tothe questionnaire of Chinese adolescent health risk related behavior issued by the Chinese Center for Disease Control and Preventionfor the different types of schools. RESULTS The multivariate analysis screened out 19 factors that were significant for the model. Theinformation applies to the establishment of Logit model（χ2=18.383, P=0.343）. It had significant difference for 22 factors in the Logitmodel affected the response variables in null hypothesis（Wald=162.37）. It is showed that the model can preferably fit smoking rates（GFI=293.28,dispersion degree=0.27, P=1.000） and had no excessive dispersion（dispersion degree1）. The results showed that itcould be applied to sub model prediction（R=0.896,R2=0.803） and the identified models are reliable（F=11.239, P〈0.05）. The re-sults of the adjusted R2 for 2142 data of the cumulative model was less than the original adjusted R2 showed that fitted Logit cumula-tive model had some practicability. The predicted value and the true value had more consistency for different students. CONCLUSION Smoking of the secondary students could be predicted by establishing a credible model and it could be reduced smoking rate and in-tervening smoking behavior among adolescent by the risk factors of smoking of the secondary students.