Trend and prediction of fatality due to occupational injuries in China / 环境与职业医学

Background Occupational injury is one of the important causes of death among the working population and a worldwide hot topic, but there are few relevant studies on the trend and prediction of occupational injury attributable deaths in China. Objective To analyze the trend of occupational injury attributable deaths in China from 2000 to 2019, predict the deaths of occupational injuries in China from 2020 to 2024 by contructing a gray GM(1,1) model, and provid a reference for surveillance and assessment of occupational injuries. Methods Mortality, crude mortality rates, and standardized mortality rates of occupational injuries in China by year, sex, and age groups were calculated using data of the Global Burden of Disease (GBD) 2019 study. Join-point model was used to analyze possible trend of standardized mortality rate from 2000 to 2019, and calculate annual percentage change (APC) and average annual percentage change (AAPC). After a gray model GM(1,1) was established, the accuracy of the model was evaluated by posterior error ratio (C) and small error probability (P) and rated as Level 1 (good, C≤0.35 and P≥0.95) or Level 2 (qualified, 0.35<C≤0.50 and 0.80≤P<0.95). Then the gray model was further used to predict the number of deaths and standardized mortality rates of occupational injuries in China from 2020 to 2024. Results From 2000 to 2019, the deaths due to occupational injuries in China showed a downward trend, the number of deaths decreased from 111557 to 61780, the crude mortality rate decreased from 8.58/100000 to 4.34/100000, the standardized mortality rate decreased from 7.67/100000 to 3.65/100000, and the AAPC of standardized mortality rate was −4.0% (P<0.05); the number of male deaths decreased from 87760 to 49192, and the male standardized mortality rate decreased from 11.78/100000 to 5.68/100000; the number of female deaths decreased from 23797 to 12588, and the female standardized mortality rate decreased from 3.34/100000 to 1.55/100000; the AAPCs of male and female standardized mortality rate were −3.9% and −4.1% respectively. The accuracy of the established gray model for deaths (C=0.09, P=1) was rated as Level 1, and that for standardized mortality rate (C=0.41, P=0.9) was rated as level 2, which allowed for prediction extrapolation. The model showed that from 2020 to 2024, the number of occupational injury attributable deaths would be 76039, 73849, 71721, 69655, and 67649, and the standardized mortality rate would be 4.23/100000, 4.07/100000, 3.92/100000, 3.77/100000, and 3.62/100000, respectively. Conclusion From 2000 to 2019, the standardized mortality rate of occupational injuries in China showed a downward trend, and it is predicted that the standardized mortality rate from 2020 to 2024 will still show a downward trend, but the number of deaths will remain high, so it is necessary to continue to strengthen prevention and control of occupational injuries.

Application of the gray model GM (1, 1) in predicting birth defects / 西安交通大学学报(医学版)

Objective: To investigate the application of gray model GM(1, 1) in predicting the incidence of birth defects at different levels and the effect of data volatility on the prediction outcome. Methods: Based on the monitoring data of birth defects in Xi'an from October 2009 to September 2016, the GM(1, 1) was used to predict the overall incidence of birth defects and incidence of five main birth defects at three levels (month, quarter, and year). We compared the fitting accuracy of different level prediction models. Results: The average relative error for yearly prediction of overall birth defect was 4.6%, and the mean square deviation was 0.259, which might suggest better prediction. Quarterly forecasting results were almost qualified and the average relative error was 10.2%. Monthly prediction was poor with an average relative error of 17.5%. With the extension of the forecast period, the grey model prediction results of the top five birth defects (congenital heart disease, cleft lip and palate, neural tube defects, multiple fingers, and congenital hydrocephalus) in Xi'an all increased, and the fitting accuracy gradually improved. The gray scale of the year was the best. Conclusion: The prediction results of the gray model may be related to the volatility of the data. It may be suitable for predicting the incidence of birth defects by the year.

Analysis and Development Prediction of Current Situation of TCM Human Resources / 中国中医药信息杂志

Objective To understand the current situation of TCM human resources; To forecast the number of TCM human resources in 2020; To provide data for national scientific management policy. Methods Through Statistical Yearbook of China's Health and Family Planning and Yearbook of Chinese Traditional Medicine, the national human resources data of TCM were collected and compiled from 2010 to 2015, and descriptive analysis and gray model method were used for data analysis. Results The TCM human resources continued to grow, but the growth rate of Chinese pharmacists was slow; the lack of TCM human resources in TCM health institutions; the uneven distribution of human resources in inter-provincial TCM; the number of TCM human resources in 2020 could meet the requirements of TCM 13th Five-year Plan. Conclusion The development of Chinese pharmacists should be paid attention to; the proportion of TCM pharmacists should be balanced; the proportion of TCM human resources in TCM institutions should be improved; scientific planning and the coordinated development of TCM human resources in various regions should be promoted.

Forecast of healthcare professionals quantity in China′s primary medical institutions :based on GM(1 ,1) Gray Model / 中华医院管理杂志

Objective To forecast the number of healthcare professionals at China′s primary medical institutions from 2016 to 2020 ,so as to provide the healthcare authorities with references for optimizing healthcare human resource allocation .Methods The Grey model was used to predict numbers of healthcare professionals in China from 2016 to 2020 on the base of health technicians data from 2010 to 2015 .Results The forecast results show that the number of healthcare professionals may be increased to about 600000 people a yearfrom 2015 to 2020 .The number of healthcare professionals at China′s primary medical institutions is expected to grow about 204000 people a year ,and general practitioner is increased to about 22000 people a year .The annual growth rates of medical(assistant) practitioners ,medical practitioners ,registered nurses ,pharmaceutical personnel and examiners in China are expected to be 3.20％ ,2.81％ ,6.88％ ,1.53％ and 2.16％ respectively. The annual average growth rates of postgraduates ,undergraduates and junior college graduates are expected to be 16.95％ ,12.08％ and 5.46％ respectively .Conclusions in the future ,the requirements for healthcare professionals at primary institutions will still be higher than demand in China ,with a gap to be filled and their professional makeup and academic title make to be optimized. Therefore greater efforts are required for their development to enhance their competence and professionalism ,with reasonable staffing of the human resources .

Application of gray model in predication of brucellosis incidence in Anyang City, Henan Province / 中华地方病学杂志

Objective To predict incidence trend of brucellosis in Anyang,Henan Province,so as to provide basis for instituting aimed preventive management.Methods To construct gray model (GM) according to incidence and rate of brucellosis of Anyang from 2004 to 2015,and predict the incidence rate of brucellosis of Anyang from 2016 to 2018.The data of brucellosis in Anyang were from the Infectious Disease Report Information Management System for Disease Control,China Information System for Disease Control and Prevention,the population data were from Anyang Bureau of Statistics.Results The GM (1,1) had good accuracy in predicting and test,the posterior error ratio (C) =0.32,and the probability value (P) =0.99.The model could be used for extrapolating prediction.The actual incidence rate was compared with the predicted value,the value was basically consistent,fit effect was good.The predictive morbidity of brucellosis was 2.92/105,3.12/105 and 3.43/105 from 2016 to 2018 in Anyang,the incidence showed an increasing trend.Conclusions The GM (1,1) has high precision for predicting incidence of brucellosis.We need to take into account the epidemic characteristics of infectious diseases and social factors in actual practice.

Grey prediction model for medical institutions of health workforce quantity prediction research / 中国医学装备

Objective:To realize Tangshan City’s medical institutions of health and human resources. Methods: Using gray predict model to prognosis Tangshan City’s main medical human resources, and find out the phenomena of lacking of medical administrative staff, disproportional of nursing staff, and shorting of assistant departments staff, such as pharmacy and medical laboratory.Results: In the next few years, we should focus on strengthening the ability of the health technical personnel, except practicing(assistant)doctors.Conclusion:Through increasing the orientation training and recruitment, improving treatment, changing ideas, etc, to achieve the rationalization of health personnel allocation. In order to coping with health care reform, we should complete the allocation and reserve of health human resources.

Death analysis and mortality prediction in children under 5 from 2006 to 2012 in Zhabei District, Shanghai / 上海预防医学

Objective] By the use of GM(1,1) model to predict mortality trends of children un-der 5 years, on the basis of the analysis of cause of death in children under 5 from 2006 to 2012 in Zhabei District of Shanghai City . [ Methods] Nearly 5 years of monitoring data were used for analysis of the cause of death , and the grey model ( GM) was used to fit and predict mortality . [ Results] The death of children under 5 was mainly infant death and the infant death was mainly newborns death from 2006 to 2012 in Zhabei District.During this five-year period, children mortality under 5 fluctuated from 3.30‰ to 4 .98‰and was slightly increased in 2010 .The main cause of death in the neonatal period was birth as-phyxia ,accounting for 31 .82%.For infant period , The first cause was congenital anomaly , accounting for 30.43% and the second cause was birth asphyxia ,accounting for 20.29%.The fitting effect of GM was fine and the predicted mortality of children under 5 years was 3.88‰in 2013. [Conclusion] Congenital a-nomalies , birth asphyxia and accident death seriously threaten the lives of children under 5 years.We must strengthen neonatal screening , neonatal accidental death education , thus effectively reducing the mortality of children under 5.The fitting effect of GM(1, 1) on mortality rate of children under 5 is good and can be ap-plied for prediction .