During the career life cycle, workers may face various health problems such as occupational injuries, occupational diseases, and work-related diseases. How to comprehensively protect the health of workers is a crucial scientific issue that needs to be solved urgently. Workers show the characteristics of co-exposure to multiple occupational risks or co-existence of multiple health conditions in their occupational activities. Occupational injuries are closely related to occupational diseases and work-related diseases. To carry out prevention and control of occupational injuries in the context of "big health", we should further strengthen the systematic approach and highlight the concept of "overall process" and "all-round". That is to establish an occupational injury surveillance system covering the whole process of surveillance-assessment-intervention and the evaluation of intervention effects, and to set up the joint prevention and control strategy of occupational injuries, occupational diseases, and work-related diseases. This will promote the implementation of efficient and intensive health management at government, society, employers, workers and other levels to achieve all-round protection of workers' health. When exploring the possible effects of job burnout, occupational stress, comorbidity, and other factors on occupational injuries, the introduction of machine learning methods provides a new approach to identifying and analyzing the influencing factors of occupational injuries and to exploring potential underlying mechanisms.

Background As a pillar industry in China, the manufacturing sector has a high incidence of non-fatal occupational injuries. The factors influencing non-fatal occupational injuries in this industry are closely related at various levels, including individual, equipment, environment, and management, making the analysis of these influencing factors complex. Objective To identify influencing factors of non-fatal occupational injuries among manufacturing workers, providing a basis for targeted interventions and surveillance. Methods A total of 2243 frontline workers from cable and shipbuilding enterprises were selected as study subjects to investigate the incidence of non-fatal occupational injuries and collect information at four levels: individual, equipment, management, and environment in past 12 months. Data balancing was performed using resampling, and LASSO regression was used to select factors of non-fatal occupational injuries. The influence degree and type of variables were judged based on the magnitude of the estimated coefficients of each variable, where variables with estimated coefficients > 0 are risk factors, and those <0 are protective factors. The area under the receiver operating characteristic (ROC)curve (AUC) was used to test the performance of the model, with an AUC value > 0.7 indicating good model performance. Results Among the 2243 frontline workers, males accounted for 77.7% (1742 out of 2243), with the main age range being 40-49 years old, representing 29.5% (661 out of 2243), 82.7% of the workers (1854 out of 2243) were married, and 55.6% (1248 out of 2243) had a junior middle school education level. The average monthly income for 51.0% (1144 out of 2243) of the workers was between 5000 and 6999 Chinese Yuan. The incidence of non-fatal occupational injuries among the manufacturing workers was 8.4% (189/2243) in the past 12 months. Among the 22 factors associated with the occurrence of non-fatal occupational injuries (P<0.05), 10 were individual-level factors, including gender, smoking, alcohol consumption, colleague relationships, average exercise duration, job burnout, work fatigue, musculoskeletal disorders, cardiovascular diseases, and neurological and sensory organ diseases; 3 were equipment-level factors, including equipment operability, hazardous workpieces, and safety hazards; 5 were environmental-level factors, including low temperatures, special operations, noise, workspace size, and dirty and disorderly environment; and 4 were management-level factors, including daily working hours, weekly working days, overtime, and pre-job technical training. The AUC value of the LASSO regression model was 0.704 and the final model retained a total of 10 variables. Among them, there were 7 risk factors for non-fatal occupational injuries (coefficient > 0), including safety hazards, musculoskeletal disorders, dangerous workpieces, job burnout, dirty and disorderly environment, smoking, and male gender; and 3 protective factors (coefficient < 0), including pre-job technical training, good colleague relationship, and long working days per week. Conclusion Manufacturing enterprises need to focus on the incidence of non-fatal occupational injuries and conduct targeted interventions for non-fatal occupational injuries by controlling potential safety hazards, providing pre-job technical training, reducing dangerous workpieces, rectifying working environment, and reasonably arranging working hours.

Background Workers in the cable manufacturing industry are exposed to high-speed machinery and equipment for a long time, coupled with heavy workload, which poses significant risks to their physical health. However, the issue of occupational injuries in this industry has not received enough attention yet. Objective To understand the incidence of occupational injury of workers in cable manufacturing industry and to analyze the influencing factors. Method A basic information questionnaire and an occupational injury questionnaire were developed to investigate the occupational injuries of 1 343 workers in a cable manufacturing enterprise in the past year, and a total of 1 225 valid questionnaires were recovered, with an effective rate of 91.2%. Descriptive statistics were used to characterize the causes, injury locations, injury types, and other characteristics of employees’ occupational injuries. Chi-square test was used to analyze the occupational injury status of groups with different demographic characteristics, occupational characteristics, lifestyles, and interpersonal relationships. Logistic regression was used to analyze the influencing factors of occupational injuries. Result The incidence of occupational injuries among workers in a cable manufacturing enterprise in the past year was 8.6%, which mainly happened in male workers (80.0%) and occurred from May to July in summer (45.7%). The main causes were mechanical injuries (32.4%) and object blows (27.6%). The main sources of damage were machinery and equipment (36.2%) as well as raw materials and products (15.2%). The main injuries were located in upper limbs (53.3%) and lower limbs (22.9%). The main types of injuries were fractures (33.3%) and abrasions/contusions/puncture wounds (19.0%). The results of univariate analysis showed that there were statistically significant variations in the incidence of occupational injuries by gender, overtime, pre-job training, years of service in current position, alcohol consumption, physical exercise per week, and co-worker relationship (P<0.05). The logistic regression model showed that workers who exercised less than twice a week, did not participate in pre-job training, worked overtime, and had fair/poor/very poor colleague relationship had a higher risk of occupational injury, while women had a lower risk of occupational injury. Conclusion The distribution of occupational injury population is mainly male, and the time distribution is mainly from May to July. Gender, physical exercise, pre-job training, overtime, and colleague relationship are the influencing factors of occupational injuries. We should strengthen pre-job training, arrange work hours reasonably, and create a good working atmosphere to reduce the occurrence of occupational injuries.

Background Social psychological factors have emerged as a key area of research in occupational injury prevention. Occupational stress, a significant component of social psychology, has garnered widespread attention due to its potential impact on occupational injury. Objective To analyze the factors influencing occupational stress among cable manufacturing workers and explore the relationship between occupational stress and occupational injury, and to provide scientific evidence for reducing occupational stress and injury. Methods A questionnaire on basic demographics, occupational injury, and occupational stress (Effort-Reward Imbalance, ERI) was used to investigate 1343 workers in a cable enterprise. Chi-square test was employed to analyze the distribution of occupational stress across different worker characteristics. Logistic regression was used to identify factors influencing occupational stress, and a decision tree model was applied to assess the impact of occupational stress on injury risk. Results A total of 1225 valid questionnaires were collected, yielding a response rate of 91.2%. The positive rate of occupational stress was 28.7%, while the incidence of occupational injury in the past year was 8.6%. The results of univariate analysis revealed that workers who had experienced occupational injuries had a higher positive rate of occupational stress compared to those without injuries (P<0.05), and there were significant differences in the distribution of occupational stress by genders, overtime work, shift work, daily working hours, fatigue levels, sleep duration, family relationships, and colleague relationships (P<0.05). The logistic regression results showed that individuals who worked shifts, had fair/poor/very colleague relationships, and frequently worked overtime had a higher risk of occupational stress (P<0.05). The final decision tree model confirmed that occupational stress was a risk factor for occupational injury. Additional factors influencing occupational injury included physical exercise, colleague relationships, pre-job training participation, and gender. Workers who exercised less than twice per week and experienced occupational stress had a significantly higher risk of injury (23.6%) compared to those without occupational stress (10.9%). Conclusion Shift work, colleague relationships, and overtime work are correlated with the positive rate of occupational stress among cable manufacturing workers. Implementing a reasonable work schedule and fostering a positive work environment are recommended. Reducing occupational stress may help lower the risk of occupational injuries in this industry.

Background Light gradient boosting machine (LightGBM) has become a popular choice in prediction models due to its high efficiency and speed. However, the "black box" issues in machine learning models lead to poor model interpretability. At present, few studies have evaluated the severity of occupational injuries from the perspective of LightGBM model and model interpretability. Objective To evaluate the application value of LightGBM models and model interpretability methods in occupational injury prediction. Methods The Mine Safety and Health Administration (MSHA) occupational injury data set of mining industry workers from 1983 to 2022 was used. Injury severity (death/fatal occupational injury and permanent/partial disability) was used as the outcome variable, and the predictor variables included the month of occurrence, age, sex, time of accident, time since beginning of shift, accident time interval from shift start, total experience, total mining experience, experience at this mine, cause of injury, accident type, activity of injury, source of injury, body part of injury, work environment type, product category, and nature of injury. Feature sets were screened using least absolute shrinkage and selection operator (Lasso) regression. A LightGBM model was then employed to predict occupational injury, with area under curve (AUC) of the model serving as the primary evaluation metric; an AUC closer to 1 indicates better predictive performance of the model. The interpretability of the model was evaluated using Shapley additive explanations (SHAP). Results Through Lasso regression, 7 key influencing factors were identified, including accident time interval from shift start, experience at this mine, cause of injury, accident type, body part of injury, nature of injury, and work environment type. A LightGBM model, constructed based on feature selection via Lasso regression, demonstrated good predictive performance with an AUC value of 0.9941 (95%CI: 0.9917, 0.9966), accuracy of 0.9743, specificity of 0.9781, and sensitivity of 0.9640. The predicted probability of fatal occupational injuries showed high consistency with the actual probability of fatal occupational injuries. In the occupational injury prediction model, the importance of each indicator was analyzed through its SHAP value, and it was found that the body part of injury and the nature of injury were the two main features that affected the prediction results of the model, and the impacts of other features were relatively small. The distribution of SHAP values across body part of injury was broad, with significant impacts on the model's prediction of fatal risk, particularly for injuries to the head and neck, as well as multi-part injuries. The nature of injury also exerted influences on the model in different directions, with suffocation/drowning, crushing, and multi-part injuries having a greater impact on the risk of fatal occupational injuries. Conclusion LightGBM model is capable of efficiently processing large-scale data and providing high-precision prediction results. Research on model interpretability aids in more accurately exploring and analyzing various key risk factors for fatal occupational injuries among mining workers, and further reveals the complex interactions among these factors. This, in turn, enables better preventive intervention and protection measures, as well as optimal resource allocation for labor workers.

Background Diseases severely affect the efficiency of workers. Comorbidity refers to the coexistence of two or more chronic diseases or health problems in the same individual. Previous studies have primarily focused on occupational injuries caused by environmental exposures, while the analysis of the epidemiological characteristics of self-reported diseases and occupational injuries among manufacturing workers has been insufficient. Objective To analyze the distribution of self-reported diseases and occupational injuries among manufacturing workers, the strength of correlation between different diseases, and common disease combinations, and to preliminarily explore the relationship between self-reported diseases and occupational injuries. Methods A cross-sectional survey was conducted to investigate the occupational injuries of 2382 workers in 2 manufacturing enterprises over the past year, and 2355 questionnaires were valid after cleaning. The questionnaire included three parts: basic information, occupational injury occurrence, and disease prevalence. The self-reported diseases diagnosed by physicians included musculoskeletal diseases, cardiovascular diseases, respiratory diseases, mental health problems, neurological and sensory organ diseases, digestive organ diseases, reproductive and urinary organ diseases, skin diseases, tumors, endocrine and metabolic system diseases, blood diseases and birth defects, a total of 11 types. Log-binomial model was used to calculate the prevalence ratio (PR) value of the association between different diseases, and UpSet diagram was used to present the disease combination pattern. Results In total, 40.2% (946/2355) of the study participants reported at least one disease, while 8.6% (203/2355), 5.2% (122/2355), and 5.9% (140/2355) reported having two, three, and four or more diseases, respectively. A higher prevalence was observed for musculoskeletal diseases, neurological and sensory organ diseases, digestive organ diseases, and skin diseases, which accounted for 18.0% (423/2355), 13.8% (324/2355), 9.3% (218/2355), and 9.1% (214/2355), respectively. Workers with musculoskeletal disorders, cardiovascular diseases, or neurological and sensory organ diseases reported significantly higher incidence of occupational injuries compared with workers without the corresponding diseases (P<0.001, P=0.041, and P=0.006, respectively). Musculoskeletal diseases were strongly associated with comorbidities of neurological and sensory organ diseases (PR values were 1.86 and 1.98, respectively), and the other patters were musculoskeletal diseases and digestive organ diseases (PR and OR values were 1.57 and 2.35, respectively), and musculoskeletal diseases and cardiovascular diseases (PR and OR values were 1.46 and 2.22, respectively). The largest binomial comorbidity group involved musculoskeletal diseases and neurological and sensory organ diseases, accounting for 5.4% (25/465) of the comorbid workers. Conclusion Among the self-reported diseases of manufacturing workers, musculoskeletal diseases, neurological and sensory organ diseases, digestive organ diseases, and skin diseases are more common. Musculoskeletal diseases and neurological and sensory organ diseases are the most common in all comorbidities. Musculoskeletal diseases, cardiovascular diseases, and neurological and sensory organ diseases are associated with occupational injuries. In the prevention and control of occupational injuries, joint prevention strategies targeting multiple diseases should be strengthened.

BACKGROUND:As a dominant breed pig in southwest China,the southern Yunnan small-ear pig has been widely used as an experimental animal in the basic research of other disciplines,but there are still no reports on its application in anterior cruciate ligament reconstruction. OBJECTIVE:To establish a large animal model of the southern Yunnan small-ear pig with anterior cruciate ligament with autologous Achilles tendon was established. METHODS:Twenty adult female Yunnan small-ear pigs were equally randomized into two groups.In the autologous Achilles tendon group,the right knee anterior cruciate ligament was reconstructed with autologous Achilles tendon as a graft,while in the sham-operated group,a similar operation was performed on the right knee without any treatment of the anterior cruciate ligament.General conditions of each pig were observed and recorded before and 12 months after surgery.Ligaments and grafts were taken for gross observation and MAS scoring.Hematoxylin-eosin staining was performed to observe morphological characteristics of ligaments.The staining and arrangement of type I and type Ⅲ collagen were evaluated by immunohistochemistry.Transmission electron microscopy was used to observe the type,size,diameter,ratio,and distribution of collagen fibers in ligaments. RESULTS AND CONCLUSION:All animals had normal diet and activity,good wound healing,no obvious inflammatory reaction,no local purulent infection,and no significant changes in mental and urinary conditions compared with those before surgery.The reconstructed cruciate ligament of the knee was intact,with no stiffness and normal range of motion.Both the anterior drawer and Lachman tests were negative.Gross observation of the graft:12 months after surgery,the grafts was in good position,with good integrity,obvious tension,ligament color close to the original anterior cruciate ligament,and complete surface synovial coverage.Most of the intraarticular ligaments in the autologous Achilles tendon group were defined as MAS I type and a few were defined as MAS Ⅱ type.In the sham-operated group,the intraarticular ligament was defined as MAS I type.Hematoxylin-eosin staining indicated that,12 months after surgery,collagen fibers in the autologous Achilles tendon group began to appear bundled,isotropic,and uniformly arranged,with more obvious isotropic corrugations,and the nuclei were mainly linear or spindle-shaped,which were similar to those in normal anterior cruciate ligament tissue of the sham-operated group.Immunohistochemistry results indicated that,12 months after surgery,there was a higher expression of type I collagen and significantly less expression of type Ⅲ collagen in the reconstructed anterior cruciate ligament in the autologous Achilles tendon group.The degree of type I and type Ⅲ staining was similar in the two groups.Under the transmission electron microscope,the diameter,arrangement and density of collagen fibers in the reconstructed anterior cruciate ligament of the autologous Achilles tendon group were similar to those of the original anterior cruciate ligament at 12 months after surgery,indicating that the ligament remodeling process had been basically completed in the autologous Achilles tendon group at 12 months after surgery.Through a comprehensive evaluation of animal general conditions,ligament general view,MAS score,hematoxylin-eosin staining,immunohistochemistry,and transmission electron microscopy observation,we successfully established a large animal model of anterior cruciate ligament reconstruction using autogenous Achilles tendon in southern Yunnan small-ear pigs,with good morphological,histological and ultrastructural results.

OBJECTIVE To investigate the current situation of the review and comment on inpatient medical orders in Beijing municipal hospitals， and to put forward countermeasures and suggestions for further improving related work. METHODS A questionnaire survey was conducted to investigate the current situation of the review and comment on inpatient medical orders in 22 Beijing municipal hospitals. The statistical analysis was conducted for the survey results. RESULTS A total of 22 questionnaires were distributed， with recovery effective rate of 100%. The 22 hospitals carried out inpatient medical order comment， but their proportion varied among hospitals （0.88%-98.54%）； medical order comment mainly focused on antibiotics， proton pump inhibitors， anesthetic drugs/class Ⅰ psychotropic drugs， auxiliary drugs and other categories； 205 pharmacists participated in the comment of inpatient medical orders， most of whom hold intermediate or higher professional titles （89.27%）； 21 hospitals conducted inpatient medical order comment and feedback the results to relevant departments/responsible persons， but the intervention situation was not the same. Eighteen hospitals had carried out the review of inpatient medical orders； reviewed drug category was roughly the same as the category involved in the medical order comment； review content involved the suitability of administration routes， dosage， etc. The review was conducted mainly through the cooperation of audit software and pharmacists. CONCLUSIONS The comment and review of inpatient medical orders in Beijing municipal hospitals carried out in an orderly manner， and preliminary results have been achieved； at the same time， it is necessary to further increase the ability of participating pharmacists， improve audit standards， optimize pre-audit （No.ZYLX201805） software， and promote rational drug use among hospitalized patients through doctor-pharmacist collaboration.

Objective:To understand the uptake of post-exposure prophylaxis (PEP) and related factors among male sex workers (MSW) and provide references for the promotion of PEP.Methods:A cross-sectional study was conducted using convenience sampling to recruit MSW participants with the help of a community-based organization in October 2023, in Wuxi City, Jiangsu Province. The sample size was estimated at 340 people. A self-administered questionnaire was used to collect their social demographic characteristics, sexual behaviors, knowledge, beliefs, and uptake of PEP. A logistic regression model was used to analyze factors associated with the uptake of PEP in MSW. The SPSS 26.0 software was used for statistical analysis.Results:A total of 357 participants were recruited, mainly aged 18-20 (55.7%,199/357), unmarried (94.4%,337/357), and having an education background of junior high school or below (50.1%,179/357). Among 357 participants, 64.4% (230/357) knew about PEP, 51.0% (182/357) believed in the efficacy of PEP, and 13.4% (48/357) had experience of using PEP. Among 68 respondents having high-risk sexual behaviors in the past 3 months, 17.6% (12/68) have had uptake of PEP. Multivariable logistic regression analysis showed that group sex with men in the past 3 months (a OR=7.51, 95% CI: 1.37-41.09), HIV testing in the past 3 months (a OR=2.89, 95% CI: 1.16-7.16), the experience of using pre-exposure prophylaxis (a OR=30.18,95% CI: 12.60-72.24) and believing in the efficacy of PEP (a OR=2.94, 95% CI: 1.04-8.29) were the associated factors with the uptake of PEP in MSW. Conclusions:Although the overall uptake rate of PEP in MSW was high, the proportion of using PEP was still low among participants having high-risk sexual behaviors in the past 3 months. Therefore, it is necessary to strengthen HIV risk awareness education considering their characteristics and promote timely uptake of PEP to interrupt HIV transmission.

Anthropometric indexes play a crucial role in identifying obesity. However, as an internationally commonly used indicator of obesity diagnosis, BMI has limitations in distinguishing lean body mass from fat mass. The weight-adjusted waist index (WWI), a novel anthropometric index, assesses adiposity through standardized waist circumference for weight, which presents an excellent capacity to predict the morbidity and mortality risks of various diseases. However, research on WWI is still in the exploratory stage, and there is a lack of unified standards for using this indicator to determine obesity. In addition, its potential application in children and adolescents also urgently needs to be explored. Therefore, this article comprehensively summarizes and compares the distinctive characteristics between WWI and other obesity-related anthropometric indexes. Bibliometric methods are used to analyze the hotspots and trends of WWI-related research, and we focus on discussing the value of WWI in predicting adverse health outcomes, including cardiovascular disease, diabetes, liver and kidney diseases. We aim to promote the application of WWI in a broader field and fully demonstrate its important public health significance and broad application prospects.