[Application of negative binomial regression and modified Poisson regression in the research of risk factors for injury frequency].

Autor:	Cao Q; School of the Public Health of Anhui Medical University, Hefei 230032, China., Wu Z, Sun Y, Wang T, Han T, Gu C, Sun Y
Jazyk:	čínština
Zdroj:	Wei sheng yan jiu = Journal of hygiene research [Wei Sheng Yan Jiu] 2011 Nov; Vol. 40 (6), pp. 702-4, 708.
Abstrakt:	Objective: To Eexplore the application of negative binomial regression and modified Poisson regression analysis in analyzing the influential factors for injury frequency and the risk factors leading to the increase of injury frequency. Methods: 2917 primary and secondary school students were selected from Hefei by cluster random sampling method and surveyed by questionnaire. The data on the count event-based injuries used to fitted modified Poisson regression and negative binomial regression model. The risk factors incurring the increase of unintentional injury frequency for juvenile students was explored, so as to probe the efficiency of these two models in studying the influential factors for injury frequency. Results: The Poisson model existed over-dispersion (P < 0.0001) based on testing by the Lagrangemultiplier. Therefore, the over-dispersion dispersed data using a modified Poisson regression and negative binomial regression model, was fitted better. respectively. Both showed that male gender, younger age, father working outside of the hometown, the level of the guardian being above junior high school and smoking might be the results of higher injury frequencies. Conclusion: On a tendency of clustered frequency data on injury event, both the modified Poisson regression analysis and negative binomial regression analysis can be used. However, based on our data, the modified Poisson regression fitted better and this model could give a more accurate interpretation of relevant factors affecting the frequency of injury.
Databáze:	MEDLINE
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