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OBJECTIVE: To analyze the epidemiological characteristics and predict epidemiological trends of occupational chemical poisoning,based on directly reported data during 2006-2015 in Guangdong Province. METHODS: The data of patients with occupational chemical poisoning reported from National Information Surveillance System for Occupational Disease and Occupational Health from 2006 to 2015 in Guangdong Province were collected. The epidemiological characteristics were retrospectively analyzed. The autoregressive integral moving average model( ARIMA model) was established and validated based on the number of the new onset cases and was used to predict the trends of occupational chemical poisoning from 2017 to 2020 in Guangdong Province. RESULTS: From 2006 to 2015,1 288 new cases of occupational chemical poisoning were reported in Guangdong Province,which accounted for 24. 4% of the total number of new cases of occupational diseases in the province( 5 283 cases). Among the new cases,the percentage of acute and chronic poisoning was 21. 7%( 279/1 288) and 78. 3%( 1 009/1 288). There was 74. 7%( 962/1 288) of organic solvent poisoning. Five kinds of new occupational chemical poisoning were found. Most of the new cases were male,accounting for 56. 7%( 729/1 288). They were mainly distributed and concentrated in Pearl River Delta Region,accounting for 95. 9%(1 235/1 288). Shenzhen,Dongguan and Guangzhou were the most three cities which had 425,325 and 209 cases respectively,all of them accounted for 74. 4%( 959/1 288). The new cases of poisoning mainly distributed in medium and small enterprises( 72. 0%),private economic enterprises( 50. 9%) and manufacturing industries(70. 5%). The number of occupational chemical poisoning diseases decreased first,and increased,and the proportion to the total number of occupational diseases in Guangdong Province showed a straight downward trend(P < 0. 01). The median age at diagnosis was 35 years old and the median work year at diagnosis was 2. 0 years,and both of them showed an increasing trend( P < 0. 01). CONCLUSION: Occupational chemical poisoning in Guangdong Province has certain characteristic of crowd aggregation and epidemic trends.
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OBJECTIVE: To explore the association of interaction of noise exposure and superoxide dismutase( SOD) gene polymorphism on the susceptibility of occupational noise-induced hearing loss( ONHL) in Chinese Han population.METHODS: A simple random sampling method was used to select 2 400 Han workers as study subjects.These workers were exposed to 75.0-120.0 dB( A) of normalized continuous A-weighted sound with pressure level equivalent to a 40 hworking-week( L_(EX,W)) in Guangzhou City.A model method was set up to define 201 sensitive workers( sensitive group)and 202 resistant workers( resistant group) by combining results with hearing pure tone threshold test and the cumulative noise exposure( CNE).The genomic DNA was extracted from peripheral blood cells.The single nucleotide polymorphisms analysis of SOD was carried out by using the TaqMan probe with chemical fluorescence allelic identification test.Binary logistic regression method was used to analyze the interaction of noise exposure and SOD.RESULTS: After adjusting confounding factors such as gender,heavy metal exposure,dust exposure and high temperature exposure,the risk for ONHL in individuals interactively carry rs2040724 AG or GG and rs4880( CC + CT) was significantly higher than that in individuals interactively carry rs2040724 AA and rs4880 TT( P < 0.05).The risk for ONHL in individuals interactively carry rs10432782 GT or GG and rs4880( CC + CT) was significantly higher than that in individuals interactively carry rs10432782 TT and rs4880 TT( P < 0.05).The risk for ONHL in individuals exposed to L_(EX,W)≥85 dB( A) and interactively carried with rs2040724 GG and rs4880( CC + CT) was significantly higher than that in individuals exposed to L_(EX,W)< 85 dB( A) and interactively carry rs2040724 AA and rs4880 TT( P < 0.01).The risk for ONHL in individuals exposed to L_(EX,W)≥85 dB( A) and interactively carry rs10432782 GT or GG and rs4880( CC + CT) was significantly higher than that in individuals exposed to L_(EX,W)< 85 dB( A) and interactively carry r10432782 TT and rs4880 TT( P < 0.05).CONCLUSION: In Chinese Han population,noise exposure intensity and SOD1( rs2040724,rs10432782),SOD2( rs4880)gene polymorphism had interacting effects on ONHL susceptibility.
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OBJECTIVE: To explore the application of the autoregressive integrated moving average model( ARIMA model)in predicting incidence of occupational noise-induced deafness( ONID). METHODS: The ARIMA model was established and validated based on the number of new onset ONID cases in Guangdong Province from 2006 to 2015. Then the ARIMA model was used to predict the trend of new onset ONID cases from 2016 to 2020. RESULTS: The number of new ONID cases in Guangdong Province from 2006 to 2015 showed an exponential growth trend. The optimal model fitted with the number of new onset ONID cases from 2006 to 2015 was the ARIMA( 2,2,2) model,which better match the number of new onset ONID cases from 2008 to 2015. According to the ARIMA( 2,2,2) model,the number of new onset ONID cases in Guangdong Province will continue to have a rapidly increasing trend from 2016 to 2020. CONCLUSION: The ARIMA model based on time series matches the time trend of ONID onset,and it can be used for the prediction of ONID incidence trend.
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Objective@#To investigate the characteristics, temporal trend of silicosis, and provide basis for risk assessment and precise prevention and control of occupational diseases.@*Methods@#Using descriptive statistics to analyze the reported cases of silicosis by SPSS 20.0 software. Reported silicosis cases, the constituent ratio, the incidence age and the working age at onset were analyzed by a linear trend test. Analyzing the variation trends of regional, industry, economic type and enterprise scale distributions by the chi-square trend test. Moreover, using Moran's I method for spatial autocorrelation analysis and trend-surface analysis.@*Results@#(1) During 2006 to 2015, Guangdong province had reported 1, 428 cases of silicosis, mainly gathered in Foshan, Zhongshan, Guangzhou, Shenzhen, which included 1391 male cases accounting for 97.41%. And the average incidence age was 45 (39, 51) . The average working age of onset was 9 (5.5, 15) . In economic type distribution, the private economy took the main part, accounting for 59.1%. In enterprise scale distribution, it was dominated by small and medium enterprises (SMEs) , accounting for 32.4% and 37.3% respectively. In industry distribution, most cases were gathered in materials and mining industry, accounting for 32.1% and 22.9% respectively. (2) The number of silicosis cases, the incidence age and the working age of onset showed a rising trend (P<0.01) . Meanwhile, the constituent ratios of medium-sized enterprises and building materials industry were increasing (P<0.05) . The annual variation trends of regional, economic type and age distributions were not statistically significant (P> 0.05) . (3) The spatial distribution trend showed an inverted U type, which was firstly raised and then declined from south to north and from east to west. The distribution characteristic demonstrated some high-high cluster areas, including Chancheng, Nanhai, Shunde, Panyu, Dongguan, Pengjiang, and Zhongshan. While Wuhua showed a high-low outlier form (P<0.01) .@*Conclusion@#Silicosis cases, age and working age of onset were on the rise, as well as the industry and enterprise scale distributions of occupational diseases presented a certain trend in Guangdong province from 2006 to 2015. There were high-high cluster and high-low outlier phenomena in spatial distribution with spatial correlation. Therefore, our work of silicosis epidemic trend and distribution may provide some bases for the occupational disease risk assessment and control.
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Objective@#This study was aimed to analyze the epidemic trend and predict the incidence trend of occupational diseases during 2006-2015 in Guangdong province, which may provide the theoretical foundation for occupational disease risk assessment and precise control and prevention.@*Methods@#We analyzed the number of reported occupational disease cases, the constituent ratio, the average age and working-age of patients. We also performed the linear-by-linear association test of new incidence, median age and median working-age by curve-fitting method, of which the diagnostic year was set as the independent variable. Meanwhile, we designed an ARIMA model to predict the variation tendency of occupational diseases in 2017-2020.@*Results@#(1) During 2006-2015, the total reported cases of occupational disease is 5289, including 2101 cases of occupational pneumoconiosis (39.7%) , 1363 cases of occupational poisoning (25.8%) , and 864 cases of occupational otolaryngological and stomatological disease (16.3%) . (2) The number of occupational diseases and pneumoconiosis have a straight upward trend (R2=0.851, R2=0.856) , while the number of occupational otolaryngological and stomatological disease and occupational tumor have a exponential trend (R2=0.914, R2=0.696) . The constituent ratio of occupational poisoning is decreasing, and the constituent ratio of occupational otolaryngological and stomatological disease is increasing. (3) The average onset age is 40 (33, 46) years old, and the average onset working-age is 6 (3, 11) years. Both of them have a straight upward trend (R2=0.954、R2=0.792) . The onset age of pneumoconiosis, occupational poisoning and occupational otolaryngological and stomatological disease have a upward trend. In addition, the onset working-age of occupational poisoning and pneumoconiosis have a upward trend. (4) The number of occupational diseases in 2017-2020 is predicted to be between 902-1231.@*Conclusion@#Occupational diseases in Guangdong province showed a trend of high incidence. The age and working-age of occupational diseases showed an extended trend. Therefore, our work of occupational epidemic trend may provide some bases for the occupational disease risk assessment and precise control and prevention.