Prediction of maternal and child health care indicators in China based on GM(1,1) model / 中华疾病控制杂志

Objective To study the predictive effect of model ［GM(1,1)］ in China’s maternal and child health indicators, and to predict the future maternal and child health indicators in a short-term, and provide a scientific basis for the gradual improvement of maternal and child health care services in China. Methods The maternal mortality rate (MMR), neonatal mortality rate (NMR), infant mortality rate (IMR) and under-five mortality rate (U5MR) were collected from 2008 to 2017 in China. Models were established and MATLAB 2018b software was used for predictive analysis. Results The prediction models of maternal mortality rate, neonatal mortality rate, infant mortality rate and under-five mortality rate were as follows: x

Temporal Trend and Prediction of Mortality of Life Lost due to Esophageal Cancer in Residents in Tieling / 中国卫生统计

Objective To explore the trend of mortality and years of life lost due to Esophageal Cancer in residents in Tieling,so as to provide the basis data on preventing Esophageal cancer in Tieling.Methods The data of residents in Tieling dying of Esophageal cancer from 2007 to 2015 was collected and cleared up to calculate the evaluation indexes including the mortality rate,the average percentage change of mortality rate.GM(1,1) model was used to predict the future mortality.Results From 2007 to 2015,the Average Esophageal cancer Mortality Rate of in residents in Tieling was 5.26 per 100000 persons,and especially 1.95％ raised a year.The Mortality Rate would increase from 2016 to 2019.Conclusion Tieling Esophageal Cancer mortality rate is on the rise,especially for elder men more than 60.So that the proper prevention measures should be car ried and strengthened.

Study on the application of information renewal GM (1,1)—linear regression coupling model in the prediction of health personnel resources: taking nurses relative number prediction for example / 中华医学科研管理杂志

Objective Taking nurses relative number prediction for example,this paper discussed the application of Information Renewal GM (1,1)—Linear Regression Coupling Model in the prediction of health personnel resources,so as to provide methodology reference for forecasting health personnel.Methods The information renewal GM(1,1) and linear regression coupling model was built and explored to predict and fit analyzing.Results The error between the predictive value that calculated by information renewal GM(1,1) and the actual value was small,and the prediction accuracy of coupling model was high.Conclusion The coupling model not only remedied the defect that grey system model did not including linear factors,but also improved the fact that linear forecasting model could not express exponential growth.Therefore the coupling model was reasonable and feasible.