Explore the change trend fitting prediction model on new cases of occupational diseases in Guangdong Province
10.11763/j.issn.2095-2619.2020.04.005
- Author:
Xiaoyong LIU
1
;
Xudong LI
1
;
Shanyu ZHOU
1
;
Hongwei YU
1
;
Qianling ZHENG
1
;
Xianzhong WEN
1
Author Information
1. Guangdong Province Hospital for Occupational Disease Prevention and Treatment, Guangdong Provincial Key Laboratory of Occupational Disease Prevention and Treatment Guangzhou,Guangdong 510300,China
- Publication Type:Journal Article
- Keywords:
Occupational disease;
New cases;
Change trend;
Prediction;
Model
- From:
China Occupational Medicine
2020;47(04):410-413
- CountryChina
- Language:Chinese
-
Abstract:
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(■) 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 ■. 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.
