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Objective:To study the effects of Jianpi Bushen Jiedu Decoction on the epithelial-mesenchymal transformation of nude mice with HCCLM3 subcutaneous transplanted tumor by regulating JAK2/STAT3 pathway.Methods:HCCLM3 subcutaneous transplanted tumor model was established in mice. After the successful modeling, 24 nude mice were divided into blank group, TCM group and combined group according to random number table method, with 8 mice in each group. Mice in the TCM group were given 0.68 mg/ml alcohol extract of Jianpi Bushen Jiedu Decoction for gavage, and the combined group were given sorafenib suspension plus alcohol extract of Jianpi Bushen Jiedu Decoction 3.5 mg/ml for gavage, once a day, for consecutive 4 weeks. The effects of Jianpi Bushen Jiedu Decoction on tumor volume, tumor weight of HCCLM3 subcutaneous transplanted tumor and mice body weight were observed; Western blot was used to detect the expressions of E-cadherin, N-cadherin, Vimentin and JAK2/STAT3 pathway-related proteins in subcutaneous transplanted tumor tissues of hepatocellular carcinoma of mice in each group.Results:Compared with the control group, the average tumor weight of subcutaneous transplanted tumor decreased significantly in the TCM group and the combined group ( P<0.05), and the expressions of JAK2, STAT3, p-JAK2, p-STAT3, N-cadherin, and Vimentin decreased significantly in subcutaneous transplanted tumor tissue ( P<0.05), while E-cadherin increased ( P<0.05). Conclusion:Jianpi Bushen Jiedu Decoction can inhibit the growth of subcutaneous transplanted tumor of hepatocellular carcinoma in mice. The mechanism may be related to inhibiting the activation of JAK2/STAT3 pathway, thereby inhibiting the epithelial-mesenchymal transformation of hepatocellular carcinoma.
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Background Imidacloprid is a neonicotinoid insecticide that is widely used in agricultural production, with a high detection rate in human biological samples. Previous studies have shown a high correlation between imidacloprid exposure and liver injury, but the specific mechanism is still unknown. Objective To observe potential toxic effects of HepG2 cells and its perturbation of non-targeted metabolic profile after imidacloprid exposure, and to explore possible molecular mechanisms of hepatotoxicity of imidacloprid by analyzing invovlved biological processes and signaling pathways. Methods HepG2 cell suspension was prepared and seeded in a 96-well plate, which was divided into blank control group, dimethyl sulfoxide (DMSO) solvent control group and imidacloprid exposure groups with multiple concentrations. Each group was set with 5 parallel samples. The viability of HepG2 cells viability were determined after 8 h of exposure to different concentrationsof imidacloprid (1, 2.5, 5, 7.5, 10 mmol·L−1), and the dose-effect relationship was analyzed. A proper concentration (3 mmol·L−1 with 80% viability) was chosen for imidacloprid exposure, non-targeted metabolomic analysis was applied to the cultivated HepG2 cells using UHPLC-Q-TOF/MS technology, the differential metabolites between groups were screened, and the bioprocess and related signaling pathways of their enrichment were annotated using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Results Compared to the other two groups, the survival rates of HepG2 cells in the imidacloprid exposure groups decreased. A survival rate of about 86% of HepG2 cells was found in HepG2 cells exposed to 2.5 mmol·L−1 imidacloprid exposure. The non-targeted metabolomics studies showed that 61 metabolites were significantly affected in HepG2 cells after 3 mmol·L−1 imidacloprid exposure, including creatine (variable importance in projection VIP=1.11, P<0.001), arginine (VIP=1.47, P=0.048), taurine (VIP=4.28, P=0.001), and α-D-glucose (VIP=1.90, P=0.006). The differential metabolites enriched in bioprocess and related signaling pathways were mainly directed to mTOR signaling pathways (P<0.001), arginine and proline metabolism (P=0.002), and galactose metabolism (P=0.015). Conclusion Imidacloprid exposure can significantly inhibit the survival rate of HepG2 cells, and interfere with the mTOR signaling pathway, arginine and proline metabolism, galactose metabolism, and so on.
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Chronic hepatitis B is a public health issue worldwide. Nucleotide analogues and interferon therapy can effectively inhibit HBV replication, but they still have the shortcomings such as inability to achieve the clearance of HBV cccDNA and low HBsAg clearance rate. The academic viewpoint of "kidney-tonifying therapy for chronic hepatitis B" provides new ideas and methods for the treatment of hepatitis B. During long-term clinical practice, Department of Hepatology in Shuguang Hospital has identified that "deficiency of spleen and kidney with damp heat remaining" is the key pathogenesis of the continuous progression of chronic hepatitis B and has established the treatment regimen for chronic hepatitis B with the basic treatment method of tonifying the kidney, strengthening the spleen, and promoting diuresis. The clinical research of National Science and Technology Major Project from The 11th Five Year Plan to The 13th Five Year Plan has validated the clinical efficacy of this regimen and clarified that regulating the immune function of the body is the main mechanism of the kidney-tonifying, spleen-strengthening, and diuresis-promoting therapy in the treatment of chronic hepatitis B.
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The UK's work-related diseases and occupational injury surveillance system consists of Reporting of Injuries, Diseases and Dangerous Occurrences Regulations 2013 (RIDDOR), Labour Force Survey (LFS), The Health and Occupation Research network in General Practice (THOR-GP), and Reporting to The Health and Occupation Research network by specialist physicians. This article briefly described the scope, content, and methods of each surveillance programme in the UK work-related diseases and occupational injury surveillance system, and summarized their advantages and disadvantages. Among them, employers are required to report to relevant law enforcement authorities by RIDDOR, data are highly accessible but with a concern of serious underreport, and it is the only data source of fatal occupational injuries; LFS, a representative national household sample survey, covering occupational injuries and work-related diseases, is the primary data source of non-fatal occupational injuries and work-related diseases such as stress, anxiety, and depression, but collects non-clinically proven data based on self-perception; general practitioners report clinically confirmed work-related diseases, which is more scientific in attribution and is a good secondary source of work-related diseases; specialist physicians report clinically confirmed cases of higher severity, which is the primary source of data on conditions such as asthma and dermatitis, but may underestimate morbidity. Each surveillance programme of the system has its own characteristics, intersects, and complements each other, which can provide reference for the construction of occupational injury surveillance system in China.
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In order to promote the development of China's occupational injury surveillance system, this paper presented the legal basis, project overview, reporting procedures, definitions and stati statistical scope, data sources and collection standards, statistical data management and analysis points of the European Statistics on Accidents at Work (ESAW), and combined with existing research and related surveillance management system in China, five key points were proposed for constructing China's occupational injury surveillance system: 1) Establish and improve laws and regulations related to occupational injury surveillance; 2) Promote utilization of nation-level data systems; 3) Establish and optimize a sound national occupational injury surveillance system; 4) Provide standardized protocols for data collection and data application of occupational injury statistics; 5) Strengthen supervision and law enforcement targeting industries and enterprises.
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Globally, manufacturing workers are one of the most vulnerable groups to occupational injuries. Occupational injuries can lead to absenteeism, disability or even death, and most of the inflicted workers involve young adults aged 18-40 years, suggesting a safety and health problem that needs close attention. In the working environment of manufacturing industry, there are a variety of occupational injury risk factors, involving individuals, equipment, environment, and management, which should be considered comprehensively. This study found comprehensive research coverage on the influencing factors of occupational injuries in manufacturing industry at individual, environmental, and management levels at home and abroad, and rich research results on the impacts of psychological factors on occupational injuries. However, factors associated with occupational injuries in equipment safety and engineering like man-machine environment need further research. Influencing factors at all levels should be comprehensively considered in the surveillance and intervention of occupational injuries in manufacturing industry to protect health and safety of workers.
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Background The United Kingdom (UK) adopts active surveillance and passive surveillance to jointly collect occupational injury data, and builds a relatively complete occupational injury surveillance system, which can provide reference for the construction of China's occupational injury surveillance system. Objective To compare the results of active surveillance and passive surveillance of occupational injuries in the UK, and to explore the joint application value of active and passive surveillance methods in the field of occupational injury prevention and control. Methods The non-fatal occupational injury active surveillance data from Labor Force Survey were used to calculate indicators such as number of reported cases, reporting rate, lost workdays per year, lost workdays per capita, and average lost workdays per case. The fatal passive surveillance data reported by the employers were used to calculate number of reported deaths, reported mortality, and other indicators. Join-point regression was used to estimate the reported trends of fatal and non-fatal occupational injuries from 2004 to 2020, and the annual percentage change (APC) and average annual percentage change (AAPC) were calculated. Results The active surveillance data showed that from 2004 to 2020, the number of reported cases of absenteeism ≥0 d due to occupational injury decreased from 89.7 (95%CI: 85.2, 94.2) per ten thousand to 44.1 (95%CI: 39.1, 49.2) per ten thousand, and the reporting rate of occupational injury decreased from 32100/100000 (95%CI: 3050/100000, 3370/100000) to 1410/100000 (95%CI: 1250/100000, 1570/100000), showing a linear downward trend (both APC and AAPC were −3.88%, P<0.05); the average lost workdays per case in 2019 was 9.1 (95%CI: 6.8, 11.5) d. The passive surveillance data showed that from 2004 to 2020, the number of reported deaths due to occupational injury decreased from 223 to 142, and the reporting rate of occupational injury decreased from 0.78/100000 to 0.44/100000, showing a linear downward trend (both APC and AAPC were −4.59%, P<0.05). Conclusion The reporting rates of fatal and non-fatal occupational injuries in the UK are showing a linear downward trend. The active surveillance method based on Labor Force Survey provides more surveillance indicators for non-fatal occupational injuries, and the passive surveillance method based on employer report has more advantages in assessment of fatal occupational injuries. Jointly applying the two surveillance modalities and the combination of trend analysis indicators, such as AAPC, provide a more comprehensive picture of the epidemiological characteristics of occupational injuries.
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Background Falls are one of the most important types of occupational injuries. The incidence of falls is high in manufacturing workers. However, most of the studies on falls in China focus on primary and secondary school students and the elderly, and there are few studies on falls in the occupational population. Objective To evaluate efficiency of Bayesian network model in predicting fall injury risks in manufacturing enterprise staff, and impacts from work content, work environment, enterprise status, and health management on falls and their mutual relationships, and provide a scientific basis for enterprises to carry out fall-associated injury intervention. Methods Data from the European Survey of Enterprises on New and Emerging Risks (ESENER) were used. The survey provided data on work content, working environment, enterprise status, and health management of enterprises in European countries. The outcome indicator, was fall injury risks reported in enterprises. A total of 23 potential impact factors covering work content, working environment, enterprise status, and health management were screened by least absolute shrinkage and selection operator (LASSO) regression, followed by Bayesian network model for structure learning and parameter learning and area under the curve (AUC) for model fitness evaluation, using R and Netica 5.18. Diagnostic inference analysis was also conducted to identify key influencing factors and key influencing chains of fall injury risks based on the change rate of fall injury risks. Results In 5997 enterprises surveyed, 2573 (42.9%) enterprises reported fall injury risks. Ordered by their coefficient estimates from high to low, the 14 variables (mean-squared error=0.20) selected by LASSO regression were: manual handling, repetitive arm movement, poor posture, using desktop computers, and using robots in the category of work content; abnormal temperature and noise in the category of working environment; company size and employee quality in the category of enterprise status; mental health training, regular risk assessment, availability of psychologists, health and safety procedures, and provision of psychological counseling in the category of health management. The fitting result of Bayesian network model for fall injury risks was good (AUC=0.779). The Bayesian network diagnostic inference identified five key influencing factors, including abnormal temperature (change rate=35.9%), poor posture (change rate=27.3%), noise (change rate=23.4%), manual handling (change rate=18.2%), and repetitive arm movement (change rate=5.1%). The key influencing chain was "manual handling - poor posture - repetitive arm movement - fall injury risks" (combined change rate=16.9%). Conclusion The Bayesian network model has a good predictive performance in predicting the risk of falls in manufacturing enterprises. Manufacturing enterprises need to focus on jobs involving manual handling and repetitive arm movement, identify and improve workers' poor posture and mental health problems, and avoid workers working in harsh temperature or noise environment.
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Background Occupational injuries, which can result in absenteeism, disability, or death, are closely related to poor working conditions. However, the improvement of operating conditions are often time-consuming and require significant economic inputs. Both occupational psychology and enterprise risk factors have been proved to be related to the occurrence of occupational injuries, but their roles in the influence path of adverse working conditions leading to occupational injuries remain unclear. Objective To explore the roles of occupational psychology and enterprise risk factors in the impact of adverse working conditions on occupational injury, so as to provide a scientific basis for enterprises with adverse working conditions to carry out targeted occupational injury intervention programs. Methods The survey data of 5997 manufacturing enterprises were obtained from the European Survey of Enterprises on New and Emerging Risks (ESENER) database. The data on enterprise risk characteristics, occupational injuries, working conditions, and occupational psychological factors were extracted and assigned. Occupational injury differences by enterprise categories were examined by chi-square test. Correlations between interest variables were evaluated by Spearman test. Path analysis with Bootstrap method was conducted using AMOS 26 software, and ratio of chi-square statistic to degree of freedom (χ2/ν), comparative fit index (CFI), Tucker-Lewis index (TLI), and root mean square error of approximation (RMSEA) were used to evaluate the path model candidates. The effect size and its proportion were calculated for variables (occupational psychological factors, enterprise risk factors, and adverse working conditions) included in the final model. Results The M (P25, P75) scores of occupational injuries, adverse working conditions, and occupational psychological factors were 40 (20, 50), 50 (30, 60), and 20 (10, 30), respectively. The enterprises that reported occupational injuries accounted for 25.5% (1550 enterprises) of the total enterprises. Proportions of the enterprises that reported occupational injuries varied significantly by company scale, branch companies, temporary employment, language barriers, and establishment time (P<0.05). The results of Spearman test showed that occupational injuries were positively correlated with working conditions (rs=0.440), occupational psychological factors (rs=0.205), company scale (rs=0.307), temporary employment (rs=0.282), and language barriers (rs=0.158); but negatively correlated with branch companies (rs=−0.180) and establishment time (rs=−0.176) (P<0.05). In the path analysis, the fitness indexes of the final model were χ2/ν=2.85, CFI=0.997, TLI=0.993, and RMSEA=0.018 (90%CI: 0.011, 0.025). The indirect effect size values and constituent ratios of enterprise risk factors and occupational psychological factors in the effect of adverse working conditions on occupational injuries were 0.166 (30.01%) and 0.013 (3.13%) respectively. The indirect effect size value of occupational psychological factors in the effect of enterprise risk factors on occupational injuries and its constituent ratio were 0.022 and 6.85%. Conclusion Enterprises with adverse working conditions may control the risk of occupational injuries by offering better solutions to surmount language barriers and temporary employment, developing occupational psychological intervention and optimization programs such as improving working hours system. At the same time, large enterprises, enterprises without branches, or enterprises with a long history are the focus of occupational injury prevention and control.
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Background The severity of occupational injury in countries such as the United Kingdom, the United States, and Germany is usually analyzed using lost workdays, but in existing occupational injury surveillance research in China, the application of this index is rare. Objective To evaluate the application value of lost workdays in non-fatal occupational injury surveillance, and provide a reference for the construction of occupational injury surveillance index system. Methods The public data of European Statistics on Accidents at Work (ESAW) from 2010 to 2019 on non-fatal injury accidents in 27 member states of the European Union were used. Non-fatal occupational injury is defined as an injury event during occupational activities or at work resulting a victim's absence from work for ≥4 d. According to the European Statistics on Accidents at Work-Summary methodology, the lost workdays were divided into 8 categories (4-6 d, 7-13 d, 14-20 d, 21-30 d, 31-91 d, 92-182 d, 183 d and above, and unknown). Annual percentage change (APC) and the average annual percentage change (AAPC) were used to evaluate the overall trend changes in the incidence rate of non-fatal occupational injury accidents in different lost workdays from 2010 to 2019, and the non-fatal occupational injury accidents in key industries. The characteristics of the occurrence of non-fatal occupational injuries were analyzed in conjunction with the changes in non-fatal occupational injuries in different lost workdays in the industry. Results From 2010 to 2019, the overall incidence of non-fatal occupational injury accidents in the European Union showed a downward trend, and the AAPC was −1.0% (P<0.05). The accident rates of lost workdays of 4-6 d and 92-182 d showed an upward trend, and the AAPC were 7.9% and 5.8% respectively (P<0.05). The average annual accident rates of non-fatal occupational injuries (≥4 d) in Categories C (manufacturing industry), E (water supply, sewage treatment, waste management and remediation), and F (construction industry) showed a linear downward trend, and the AAPC were −3.0%, −2.5%, and −1.5%, respectively (P<0.05). However, among them, the rate of non-fatal occupational injury accidents with 92-182 d of lost workdays in the manufacturing industry showed a significant upward trend, with an AAPC of 3.7% (P<0.001). Conclusion Using lost workdays combined with APC and AAPC by Join-point linear regression analysis can measure the severity and trend changes of non-fatal occupational injury accidents in different industries and different lost workdays. This indicator has an important practical significance in evaluating the effectiveness of occupational injury prevention and control strategies adopted by countries and enterprises.
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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.
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Background Occupational injuries are one of the leading causes of death or disability in occupational populations. According to the World Health Organization and the International Labour Organization, occupational injuries were the occupational contributor responsible for the largest loss of disability-adjusted life years (DALY) globally in 2016. Objective To analyze the burden of deaths attributed to occupational injuries in Chinese population from 1990 to 2019, and provide a reference for further construction of occupational injury surveillance system. Methods Using the results and data of the Global Burden of Disease 2019 (GBD 2019), this study estimated the burden of deaths attributable to occupational injuries by year, sex, and age groups, and the indicators included deaths, years of life lost (YLL), mortality, and YLL rates. Age-standardized rates of deaths and YLL rates were calculated using a world standard population presented by GBD 2019. Annualized rate of change (ARC) was use to evaluate changes in the indicators over time. All results were presented as point estimates with 95% uncertainty intervals (95%UI). Results In 2019, the deaths attributable to occupational injuries among women in China accounted for 33.16% of that among world's women, their YLL accounted for 31.88%, and the two indicators among Chinese men accounted for 17.98% and 17.09%, respectively. Compared with 1990, the standardized mortality rate and the standardized YLL rate attributable to occupational injuries in China in 2019 decreased, among which the ARCs of the standardized mortality rate in the whole population, men, and women were −0.68 (95%UI: −0.78, −0.51), −0.68 (95%UI: −0.80, −0.47), and −0.68 (95%UI: −0.82, −0.46), respectively. The ARCs of the standardized YLL rate in the whole population, men, and women were −0.68 (95%UI: −0.78, −0.51), −0.67 (95%UI: −0.80, −0.48), and −0.68 (95%UI: −0.81, −0.44), respectively. Absolute values of the ARCs of the standardized mortality rate and the standardized YLL rate attributable to occupational injuries from 1990 to 2010 were higher than those from 2010 to 2019. The ARCs of the standardized YLL rate for road injuries, falls, and drowning from 1990 to 2010 were −0.55 (95%UI: −0.67, −0.36), −0.57 (95%UI: −0.73, −0.38), −0.77 (95%UI: −0.84, −0.63), and the ARCs from 2010 to 2019 were −0.27 (95%UI: −0.46, −0.02), −0.07 (95%UI: −0.34, −0.26), −0.06 (95%UI: −0.32, −0.29), respectively. In 2019, the standardized mortality rate attributable to occupational injuries among Chinese men was 5.68/100000 (95%UI: 3.89/100000, 8.23/100000), and the standardized YLL rate was 286.27/100000 (95%UI: 197.58/100000, 411.38/100000); the standardized mortality rate attributable to occupational injuries among Chinese women was 1.55/100000 (95%UI: 0.99/100000, 2.36/100000), and the standardized YLL rate was 80.85/100000 (95%UI: 51.61/100000, 122.07/100000). Conclusion From 1990 to 2019, the burden of deaths attributable to occupational injuries in China is declined, but the rate of decline is slowed down in the last decade. The burden of deaths attributable to occupational injuries among women in China still accounts for a high proportion of the global burden among women. The burden of deaths attributable to occupational injuries among Chinese men is higher than that among Chinese women.
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Background Identification and analysis of influencing factors of occupational injury is an important research content of feature selection. In recent years, with the rise of machine learning algorithms, feature selection combined with Boosting algorithm provides a new analysis idea to construct occupational injury prediction models. Objective To evaluate applicability of Boosting algorithm-based model in predicting severity of miners' non-fatal occupational injuries, and provide a basis for rationally predicting the severity level of miners' non-fatal occupational injuries. Methods The publicly available data of the US Mine Safety and Health Administration (MSHA) from 2001 to 2021 on metal miners' non-fatal occupational injuries were used, and the outcome variables were lost working days < 105 d (minor injury) and ≥ 105 d (serious injury). Four different feature sets were screened out by four feature selection methods including least absolute shrinkage and selection operator (Lasso) regression, stepwise regression, single factor + Lasso regression, and single factor + stepwise regression. Logistic regression, gradient boosting decision tree (GBDT), and extreme gradient boosting (XGBoost) were selected to construct prediction models by training with the four feature sets. A total of 12 prediction models of severity of miners' non-fatal occupational injuries were built and their area under the curve (AUC), sensitivity, specificity, and Youden index were calculated for model evaluation. Results According to the results of four feature selection methods, age, time of accident occurrence, total length of service, cause of injury, activities that triggered injury occurrence, body part of injury, nature of injury, and outcome of injury were identified as influencing factors of non-fatal occupational injury severity in miners. Feature set 4 was the optimal set screened out by single factor+stepwise regression and the GBDT model presented the best predictive performance in predicting the severity of non-fatal occupational injuries. The associated specificity, sensitivity, and Youden index were 0.7530, 0.9490, and 0.7020, respectively. The AUC values of logistic regression, GBDT, and XGBoost models trained by feature set 4 were 0.8526 (95%CI: 0.8387, 0.8750), 0.8640 (95%CI: 0.8474, 0.8806), and 0.8603 (95%CI: 0.8439, 0.8773), respectively, higher than the AUC values trained by feature set 2 [0.8487 (95%CI: 0.8203, 0.8669), 0.8110 (95%CI: 0.8012, 0.8344), and 0.8439 (95%CI: 0.8245, 0.8561), respectively] . The AUC values of GBDT and XGBoost models trained by feature set 4 were higher than that of logistic regression model. Conclusion The performance of the prediction models constructed by predictors screened out by two feature selection methods is better than those by single feature selection methods. At the same time, under the condition of optimal feature set, the performance of model prediction based on Boosting is better than that of traditional logistic regression model.
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Occupational injuries cause a large number of personal injuries, illnesses, or deaths, resulting in a huge burden of disease, and has become an important global occupational safety and health problem. Developed countries in Europe and the United States have provided strong support for occupational injury prevention and control by establishing continuous and stable occupational injury surveillance systems. The occupational injury problem has not attracted enough attention and concern in China, with few relevant research reports, and the current occupational injury surveillance system is far from perfection. From the perspective of protecting workers' occupational health, this paper analyzed and compared the classification and scope of occupational injuries at home and abroad, as well as the status quo of occupational injury surveillance and assessment, and proposed to set up an occupational injury surveillance system with multiple surveillance methods and multiple data sources that complement with each other, so as to strengthen the continuity of surveillance activities, consistency of data formats, and comparability of assessment indicators. Step by step, we can set up a surveillance system covering the whole process of surveillance, assessment, intervention, and evaluation of intervention effects.
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Background The aging of the labor force has become a global trend, and various occupational activities can affect blood biochemical indexes and increase the risk of metabolic diseases. Elderly workers are the main laborers in the solar greenhouse industry, and their blood biochemical indexes need more attention. Objective The purpose of this study is to explore the alternation of selected blood biochemical indexes and provide clues for conducting management programs of metabolic diseases in the elderly solar greenhouse workers. Methods The research subjects of the greenhouse group and the non-greenhouse group were selected from a vegetable production base in Northwest China. The elderly workers were selected from a recruited subjects pool for an earlier project by means of matching and non-matching respectively. The matching conditions were gender (consistent), age (±2 years old), body mass index (BMI) (±1 kg·m−2), education level (±1 level), smoking (consistent), and drinking (consistent). Routine clinical tests were used to detect serum total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDLC), low-density lipoprotein cholesterol (LDLC), fasting blood glucose (GLU), and albumin (ALB), and single-factor and multi-factor analyse were used to identify different indexes in matching and non-matching samples, respectively. The matching and the non-matching samples included 80 pairs of subjects and 327 subjects, respectively. Results In the matching sample set, the greenhouse group's HDLC [(1.61±0.34) mmol·L−1] was lower than the non-greenhouse group's [(2.09±0.37) mmol·L−1] (P<0.05), the level of TG/HDLC in the greenhouse group was (1.17±0.74), higher than that in the non-greenhouse group (0.78±0.47) (P<0.05), and the level of LDLC/HDLC in the greenhouse group was (1.87±0.36), also higher than that in the non-greenhouse group(P<0.05), while there was no statistical difference of the other indexes between the two groups (all Ps>0.05). In the non-matching sample set, the results of multiple linear regression analysis showed that solar greenhouse working correlated with decreased HDLC, and increased TG/HDLC and LDLC/HDLC among the elderly workers (all Ps<0.05). Conclusion Solar greenhouse working may correlate with variations of selected blood biochemical indexes in elderly workers, and the occupational health surveillance of elderly workers should be strengthened.
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Background As a new type of vegetable production method, solar greenhouse has been widely promoted nationwide. The influence of solar greenhouse working on blood lipid cannot be ignored. Objective The aim of the study is to explore the relationship between solar greenhouse working and blood lipid and family clustering. Methods A total of 744 solar greenhouse workers in northwestern China were selected as the greenhouse group, and 231 general open field farmers in the same area were selected as the non-greenhouse group. The levels of serum total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDLC), and low-density lipoprotein cholesterol (LDLC) in the two groups were detected. Dyslipidemia was determined by a two-classification criteria in the national guideline of 2007. Multiple logistic regression model and multilevel multiple linear regression model were used to explore the relationship of blood lipid with solar greenhouse working, and its family clustering. Results The number of dyslipidemia cases in the greenhouse group and non-greenhouse group was 142 (19.1%) and 43 (18.6%), respectively, and the difference was not statistically significant (P>0.05). The results of multiple logistic regression analysis showed that increasing age (OR=1.019, 95% CI: 1.001-1.038) and increased BMI (OR=1.162, 95% CI: 1.106-1.220) were related to elevated risk of dyslipidemia (all Ps<0.05). The results of multilevel multiple linear regression model showed that the changes of TC, HDLC, and TG/HDLC had family clustering (b=0.238, 95%CI: 0.132-0.430; b=0.044, 95%CI: 0.033-0.065; b=1.003, 95%CI: 0.947-1.059) (all Ps<0.05). Conclusion Solar greenhouse working does not significantly increase the incidence of dyslipidemia, but the levels of TC, HDLC, and TG/HDLC levels in the solar greenhouse workers have family clusters.
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Background Due to long working time and complex and changeable lighting conditions, greenhouse workers' anisometropia is an issue of concern. Objective This study is conducted to evaluate the relationship between solar greenhouse working and anisometropia of workers. Methods Subjects of a solar greenhouse group and a non-greenhouse group in northwest area of China were selected. Questionnaire survey was used to collect general demographicinformation. Standard Logarithmic Visual Acuity Chart (GB 11533—2011) was used to measure naked eye vision before working, the absolute value of binocular visual acuity difference was calculated and converted into classification variables, and both anisometropia absolute value and classification variables of anisometropia were used as indicators to compare the difference of the two groups. A cumulative exposure index that multiplies exposure time and number of greenhouses was further introduced to evaluate cumulative exposure levels of the greenhouse workers and was used to divide them into low, medium, and high cumulative exposure subgroups. Generalized linear model and logistic regression model were used to analyze possible risk factors associated with anisometropia. Results A total of 1002 subjects were enrolled in this study, including 739 workers in the greenhouse group and 263 workers in the non-greenhouse group. The medians (interquartile intervals) of anisometropia of the greenhouse group and non-greenhouse group were 0.1 (0, 0.2) and 0 (0, 0.1) respectively, and the difference was statistically significant (P<0.05). The proportions of anisometropia=0, ≤0.2, and >0.2 in the greenhouse group were 34.2%, 55.2%, and 10.6%, respectively, and those in the non-greenhouse group were 58.2%, 34.6%, and 7.2%, respectively. The difference of anisometropia distribution between the two groups was statistically significant (P<0.05). According to the cumulative exposure index, the greenhouse group was divided into low, medium, and high cumulative exposure subgroups, with 154 (21.0%), 188 (25.6%), and 392 (53.4%) workers, respectively. There was no statistical significance in anisometropia among workers with different cumulative exposure levels (P>0.05). The results of multiple generalized linear analysis showed that greenhouse working was a risk factor of anisometropia (b=0.053, P<0.05), and the results of multiple logistic regression analysis showed that greenhouse working was associated with an increased risk of anisometropia (OR=2.586, 95%CI: 1.473-4.539). The results of multiple generalized linear analysis showed that medium exposure level increased the degree of anisometropia after adjusting age, gender, and other factors (b=0.054, P<0.05). Conclusion Solar greenhouse working may be a risk factor for increasing anisometropia in workers.
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Background In the process of greenhouse working, labor intensity is high and repetitive work involves multiple body parts such as limbs, neck, upper back, and lower back. The prevalence and comorbidity of work-related musculoskeletal disorders (WMSDs) in greenhouse workers are worthy of attention. Objective This study is conducted to investigate the prevalence and comorbidity, as well as potential influencing factors of WMSDs in greenhouse workers. Methods A total of 722 greenhouse workers were selected as the subjects for a cross-sectional epidemiological survey. Through questionnaire survey and physical examination, basic information of the subjects and the prevalence of WMSDs were collected. The participants were divided into low, medium, and high cumulative exposure groups by cumulative exposure index matrix. Chi-square test was used to analyze the difference of prevalence among different cumulative exposure levels, the correlation between the prevalence of WMSDs in paired sites was calculated as prevalence ratio (PR) by using the log-binomial model, the prevalence of multi-site WMSDs in each group was compared by Wilcoxon rank sum test, and the influencing factors of multi-site WMSDs were evaluated by multi-classification logistic regression model. Results The prevalence rate of WMSDs in the greenhouse workers was 78.7% (568/722). The main affected sites of body were lower back, legs, neck, and shoulders, and associated prevalence rates were 47.6%, 46.0%, 27.1%, and 23.8%, respectively. By constructing a cumulative exposure index matrix, the low, medium, and high cumulative exposure groups contained 121, 196, and 405 workers respectively. The prevalence rates of WMSDs in lower back, legs, or shoulders were significantly different among groups with different exposure levels (P<0.05), and the prevalence rates increased with higher cumulative exposure levels (lower back, \begin{document}${χ} _{{{\rm{trend}}}}
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With the development of modern agriculture and horticulture, solar greenhouse technology has been widely used in China, and solar greenhouse workers are gradually becoming a new occupational group. The single exposures or co-exposures to chemical, biological, physical, and human ergonomic factors in solar greenhouses may cause adverse health effects on multiple systems and organs. The special column "Solar greenhouse workers' health" focused on the associations of solar greenhouse working with the workers' health status of musculoskeletal system and eyes, and the relationship with the blood biochemical indicators related to metabolic diseases.
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ObjectiveTo investigate the effect of sustained virologic response on disease progression and the development of hepatocellular carcinoma (HCC) in patients with compensated hepatitis B cirrhosis receiving antiviral therapy with nucleos(t)ide analogues (NAs). MethodsA total of 542 patients with compensated hepatitis B cirrhosis who attended Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine from January 1 to December 31, 2013, received antiviral therapy, and were followed up for more than 5 years were enrolled, and according to the status of virologic response during follow-up, they were divided into a sustained virologic response cohort with 496 cases and a non-sustained virologic response cohort with 46 cases. With disease progression as the outcome event, general information and examination data were collected during the 5-year follow-up period. The t-test was used for comparison of normally distributed continuous data between groups, and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between groups; the chi-square test was used for comparison of categorical data between groups. A multivariate logistic regression analysis was performed; relative risk and 95% confidence interval (CI) were used to investigate the degree of correlation of factors measured with the progression of liver cirrhosis. The life-table method was used to calculate the 1-, 3-, and 5-year progression-free survival rates, and the Kaplan-Meier method was used to plot survival curves; the log-rank test was used for univariate analysis, and the Cox regression model was used for multivariate regression analysis. ResultsFor the 542 patients, the mean progression-free survival time was 62.50 months (95% CI: 61.01-63.92), and the 1-, 3-, and 5-year progression-free survival rates were 94%, 82%, and 71%, respectively. The sustained virologic response cohort had a significantly longer mean progression-free survival time than the non-sustained virologic response cohort ［63.10 months (95% CI: 61.65-64.55) vs 55.95 months (95% CI: 50.19-61.71), χ2=12.058, P=0.001］. Compared with the non-sustained virologic response cohort, the sustained virologic response cohort had significantly lower 5-year cumulative incidence rate of HCC than (20.6% vs 34.8%, χ2=5.759, P=0.016) and 5-year cumulative incidence rate of decompensated cirrhosis (5.0% vs 15.2%, χ2=8.239, P=0.004). Virologic response was an independent risk factor for disease progression (hazard ratio=232, 95% CI: 1.45-3.72). ConclusionSustained virologic response can reduce the incidence rates of complications and HCC, improve long-term prognosis, and prolong survival time in patients with compensated hepatitis B cirrhosis.