{L-End}Objective To study and develop a suitable scale to identify and assess risks of occupational stress in workplaces of enterprises, and to explore the establishment of a workplace occupational stress risk assessment method aimed at guiding enterprises to improve working conditions based on the electronics industry in Beijing City. {L-End}Methods The initial version of the Workplace Occupational Stress Risk Assessment Scale (WOSRAS) was constructed based on literature review and expert evaluation. A total of 1 284 employees from four electronics enterprises in Beijing City were selected as the research subjects using a convenient sampling method. Item analysis and exploratory factor analysis were used to determine the final items of the scale and test its reliability and validity. The method of percentile norms was used to establish risk assessment method for the electronics industry workplace and its stress sources, and the cut-off values of low, medium, high risk was graded by the 50th and 80th percentiles of the total score and the score of each dimension of the risk assessment scale. {L-End}Results i) Based on item analysis and exploratory factor analysis, a WOSRAS consisting of six dimensions and 23 items was constructed, which could explain 63.2% of the total variation of occupational stress. The results of confirmatory factor analysis showed that the root mean square error of approximation and standardized root mean square residual were both <0.080, and the comparative fit index and Tucker-Lewis index were both >0.900. The total criterion validity of the scale was 0.816. The total Cronbach's α coefficient of the scale was 0.835, and the Spearman-Brown coefficient was 0.802. ii) The cut-off values of WOSRAS scores for high, medium and low risk in electronics industry were <53.0, 53.0-60.0 and >60.0,respectively. According to the result, the workplace stress risk levels of the production, research and development, and logistics departments of the electronics industry in Beijing were medium risk, while the management department was low risk. {L-End}Conclusion The WOSRAS constructed in this study has good reliability and validity. The proposed risk assessment method can reflect the actual risk status of enterprises in the electronic industry and is convenient for widespread application.

{L-End}Objective To explore the suitable methods for individual occupational stress examination and evaluation for workers in China based on the electronics industry. {L-End}Methods A total of 1 164 workers from four electronics enterprises in Beijing City were selected as the research subjects using a convenient sampling method. The Occupational Stress Measurement Scale, which was developed based on the Japanese Brief Job Stress Questionnaire, was used to assess the occupational stress of the research subjects, and test the reliability and validity of the scale. Percentile norms and T-score norms were established, and the T-scores of the three dimensions of stress reaction (psychological reaction and physical symptoms), stress factors, and social support were divided into five stages using the normal distribution method with x¯±0.5 s and x¯±1.5 s, which was used to explore a proposed standard for assessing individual stress levels. {L-End}Results The revised scale consisted of 57 items, which could explain 64.0% of the total variation of occupational stress based on the result of item analysis and exploratory factor analysis. The results of confirmatory factor analysis showed that the model fitted well, with root mean square error of approximation of 0.052, standardized root mean square residual of 0.070, comparative fit index of 0.960, and Tucker-Lewis index of 0.958. The Cronbach's α coefficient of the scale was 0.951, and the Spearman-Brown coefficient was 0.837. Cronbach's α coefficients of the three dimensions ranged from 0.794 to 0.952, and the Spearman-Brown coefficients ranged from 0.737 to 0.850. The scores of the three dimensions of stress reaction, stress factors, and social support were (49.1±13.0), (44.9±7.7), and (18.1±3.6), respectively. Workers in the electronics industry met one of the following items were identified as the high level of occupational stress individuals: i) a score of stress reaction dimension ≥72.0 points; ii) a sum of stress factor and social support dimension scores ≥81.0 points, and a stress reaction dimension score ≥58.0 points. {L-End}Conclusion The Occupational Stress Measurement Scale and the criteria for determining high level of occupational stress can be used to assess the individual occupational stress levels of workers in the electronics industry in China. This method can provide a theoretical basis for the formulation of occupational stress examination and assessment for Chinese workers.

{L-End}Objective To analyze the current status of occupational stress and its influencing factors among workers in pharmaceutical enterprises in Beijing City. {L-End}Methods A total of 860 employees from six pharmaceutical enterprises in Beijing City were selected as the research subjects using convenience sampling method. The Chinese version of the New Brief Job Stress Questionnaire was used to evaluate the occupational stress, and multiple linear regression analysis was used to analyze the influencing factors of occupational stress. {L-End}Results The detection rate of high occupational stress was 1.40% (12/860). The results of multiple linear regression analysis showed that the workers with higher education level and longer length of service had a higher risk of high occupational stress (all P<0.01). Workers who were satisfied with their jobs had a lower risk of high occupational stress than those who were unsatisfied with their jobs (P<0.01). Workers who were satisfied with life had a significantly lower risk of high occupational stress than those who were unsatisfied with life (P<0.01). {L-End}Conclusion The detection rate of high occupational stress in workers of pharmaceutical enterprises is relatively low. Occupational stress is mainly affected by individual factors such as education level and length of service, and work and life satisfaction. Improving job and life satisfaction is helpful to reduce occupational stress level.

Objective To analyze the evaluation results of health enterprises in Beijing City and their influencing factors. Methods A total of 40 enterprises that passed the health enterprise evaluation in Beijing from 2021 to 2022 were selected as the study subjects using the judgment sampling method. The total evaluation scores and influencing factors were analyzed based on the size, nature, industry classification, and establishment time of the enterprises. Results The total evaluation score of the 40 health enterprises was (553.1±18.4) points. Scores for the primary evaluation indicators, including management organization and system, occupational disease prevention measures, health environment, health promotion measures, prevention measures for occupational stress caused damage, and musculoskeletal injury prevention measures, were (94.0±4.8), (94.0±4.3), (94.5±3.8), (89.7±4.8), (89.6±4.6), and (91.4±5.9) points, respectively. The result of multiple linear regression analysis showed that, large enterprises had higher total evaluation scores than medium enterprises and micro and small enterprises after controlling for confounding factors such as industry classification and establishment time (all P<0.10). The total evaluation scores of private enterprises and foreign-funded enterprises were lower than that of state-owned or state-participated enterprises (all P<0.10). Conclusion Enterprise size and nature are influencing factors for the total evaluation score of health enterprises. It is necessary to enhance resource and policy support for medium-sized, micro and small enterprises and private enterprises to improve the development of the health enterprises.

Background Gene sequencing industry is an emerging innovation-driven industry. Employees have high requirements for independent learning and innovation ability and face great professional pressure. Objective To understand the occupational stress, depression, and sleep of gene sequencing enterprise employees and to analyze the effect of occupational stress on depression and sleep. Methods From November to December 2021, occupational stress, depression, and sleep conditions of 469 workers from 34 enterprises in gene sequencing industry were surveyed by Core Occupational Stress Scale (COSS), Patient Health Questionnaire 9 (PHQ-9), and Pittsburgh Sleep Quality Index (PSQI). A total of 427 valid questionnaires were recovered with a questionnaire valid response rate of 91.04%. The relationship of occupational stress with depression or sleep was analyzed by logistic regression. Results The rates of occupational stress, depression, and sleep disorder were 27.40%, 33.50%, and 28.10%, respectively. Significant difference were found in the rates of depression and sleep disorder in different occupational stress groups (P<0.05). The results of logistic regression analysis showed that, for every 1 increase in social support score, the risk of depression increased by 1.206 (95%CI: 1.117−1.304), and the risk of sleep disorder increased by 1.143 (95%CI: 1.059−1.233). For every 1 increase in organization and reward score, the risk of developing depression increased by 1.082 (95%CI: 1.017−1.151). Mild, moderate, and severe occupational stress were all associated with a higher risk of depression in reference to no occupational stress (OR=2.535, 95%CI: 1.465−4.386; OR=3.774, 95%CI: 1.809−7.870; OR=3.823, 95%CI: 1.486−9.837). Severe occupational stress was associated with a higher risk of sleep disorder in reference to no occupational stress (OR=3.141, 95%CI: 1.233−8.006). Conclusion Occupational stress among employees in the gene sequencing industry can increase the risks of depression and sleep disorder. Enterprises need to take intervention measures and pay attention to prevention and treatment.

Background Bus drivers are a high-risk group for work-related musculoskeletal disorders (WMSDs). There are a large number of bus drivers in mega-cities. High volumes of passenger traffic and complexity of road conditions may elevate their risk of WMSDs, but there are few studies related to this group. Objective To investigate the prevalence of WMSDs among bus drivers in a mega-city and to analyze potential influencing factors. Methods Based on cross-sectional study design and self-administered questionnaire, the prevalence of WMSDs in past 12 months were estimated by stratified cluster sampling among bus drivers in a mega-city. Pearson χ² and logistic regression models were used to analyze the influencing factors for the body regions with a high prevalence. Results The overall prevalence of WMSDs in past 12 months among bus drivers in a mega-city was 49.5% (551/1113). The prevalence of WMSDs by body regions ranged from 4.0% to 38.5%, and led by neck pain (38.5%), lower back pain (25.5%), and shoulder pain (20.8%). The results of logistic regression showed that the risk factors for neck pain were age (>50 years), smoking, tiredness after work (moderate, severe), long sitting (frequently), awkward postures (sometimes, often, frequently), overtime(occasionally, often), workplace temperature (uncomfortable), and noise (severe) (OR=2.014、1.577、2.793、3.025、2.708、2.032、3.406、2.746、1.442、2.998、1.456、3.506；P<0.05); the lower back pain risk factors were current work experience (6-10 years, 11-15 years, and 16-20 years), smoking, tiredness after work (moderate, severe), and awkward postures(sometimes, often, frequently)(OR=1.777、2.130、2.400、1.503、2.951、3.364、1.836、4.569、2.786，P<0.05); and the shoulder pain risk factors were age (46-50 years, and >50 years), smoking, tiredness after work (moderate, severe), vehicle type (hybrid power, diesel oil), awkward postures (often, frequently), overtime (often), and workplace temperature (uncomfortable) (OR=1.737、2.357、1.553、2.259、2.489、1.659、3.295、2.777、3.320、2.266、1.426，P<0.05). Identified protective factors for neck and lower back pain were off-duty physical activity (1-2 times per week, and ≥3 times per week) (OR=0.553、0.470、0.586、0.485，P<0.05). Conclusion Nearly half of the bus drivers in the mega-city report symptoms of WMSDs, mainly in the neck, lower back, and shoulders. The prevalence is related to individual and occupational factors, and prevention and intervention measures should be actively taken.

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}${χ} _{{{\rm{trend}}}} ^2$\end{document}=11.144, P<0.05; legs, \begin{document}${χ} _{{{\rm{trend}}}} ^2$\end{document}=6.767, P<0.05; shoulders, \begin{document}${χ} _{{{\rm{trend}}}} ^2$\end{document}=15.666, P<0.05). The results of log-binomial model found that lower back and legs (PR values were 1.57 and 1.43, respectively) as well as neck and shoulders (PR values were 2.00 and 2.07, respectively) among the main affected parts have a strong association with comorbidities. The prevalence of multi-site WMSDs showed that 50.4% of the workers had comorbidity of two or more sites of WMSDs. The results of multi-classification logistic regression analysis indicated that the influencing factors of WMSDs in two sites involved high-level cumulative exposure (OR=2.41, 95%CI: 1.34-4.33) and female (OR=3.27, 95%CI: 2.07-5.16); the influencing factors of WMSDs in three or more sites also included medium-level cumulative exposure (OR=3.78, 95%CI: 1.70-8.39), high-level cumulative exposure (OR=7.34, 95%CI: 3.41-15.80), and female (OR=5.66, 95%CI: 3.48-9.22). Conclusion In this study, the prevalence rates of WMSDs in lower back, legs, neck, and shoulders are high among selected solar greenhouse workers, and WMSDs comorbidity of lower back-legs and neck-shoulders are identified. Greenhouse workers with high cumulative exposure level and female workers report more WMSDs comorbidities in two or more sites.

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.

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.

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.