摘要
目的采用线性和非线性回归模型拟合广东省职业病新发病例数量的变化趋势,筛选最优拟合模型。方法以广东省2003—2017年职业病新发病例数为因变量(y),以年份为自变量(x),采用线性回归、三次函数、二次函数、复合函数、增长函数、指数函数、Logistic函数、幂函数、对数函数、S型函数、逆函数等11种数学模型对数据进行拟合,筛选拟合效果最好的模型描述新发职业病的变化趋势并进行验证。结果11种数学模型中,三次函数回归模型拟合结果的决定系数最高(为0.94,P<0.01),拟合效果最好,拟合曲线为y=165.66+8.90x+5.66x^2-0.20x^3。采用该模型拟合2003—2019年广东省职业病新发病例数量的结果显示,除2011年外,其余年份新发病例数量实际值均在模型拟合值的95%可信区间内;拟合值与实际值的相对偏差绝对值为中位数和第25、75百分位数为8.9%(4.3%,14.7%)。结论基于三次函数回归模型可较好地拟合职业病发病的变化趋势,可用于职业病发病趋势描述。
Objective To screen the optimal fitting model for the change trend of the number of new cases of occupational diseases in Guangdong Province by using linear and nonlinear regression models.Method The number of new cases of occupational diseases in Guangdong Province from 2003 to 2017 was used as the dependent variable(y)and the year(time)as the independent variable(x).Eleven mathematical models including linear regression,cubic function,quadratic function,composite function,growth function,exponential function,logistic function,power function,logarithmic function,S-type function and inverse function were used to fit the data,and the best-fit model was selected to describe and verify the change of new occupational diseases.Results Among the 11 mathematical models,the determination coefficient of fit results of cubic curve regression model was the highest(0.94,P<0.01),and the fit effect was the best.The fitting curve was y=165.66+8.90x+5.66x^2-0.20x^3.The cubic curve regression model was used to fit the number of new cases of occupational diseases in Guangdong Province from 2003 to 2019.The results showed that the measured value of new cases in all those years,except 2011,was within 95%confidence interval of the fitting value.The median(25 th,75 th percentile)of absolute relative deviation between the fitting value and the actual value was 8.9%(4.3%,14.7%).Conclusion The regression model based on cubic curve can better fit the incidence of occupational diseases and can be used to describe the occurence of occupational diseases.
作者
刘晓勇
李旭东
周珊宇
余宏伟
郑倩玲
温贤忠
LIU Xiaoyong;LI Xudong;ZHOU Shanyu;YU Hongwei;ZHENG Qianling;WEN Xianzhong(Guangdong Province Hospital for Occupational Disease Prevention and Treatment,Guangdong Provincial Key Laboratory of Occupational Disease Prevention and Treatment,Guangzhou,Guangdong 510300,China)
出处
《中国职业医学》
CAS
北大核心
2020年第4期410-413,共4页
China Occupational Medicine
基金
国家临床重点专科建设项目(2011-09)
广东省医学科研基金(C2017008,B2015010)
广东省职业病防治重点实验室(2017B030314152)。
关键词
职业病
新发病例
变化趋势
拟合
模型
Occupational disease
New cases
Change trend
Prediction
Model
