Background Health literacy is closely related to mental health, and improving health literacy has been shown to promote mental well-being. However, whether occupational stress among workers in mining and manufacturing is associated with their occupational health literacy remains inconclusive. Objective To study the levels of occupational health literacy and occupational stress among workers in three industrial sectors (metal ores mining, metal smelting, and manufacture of non-metallic mineral products) in Gansu Province, and to analyze the correlation between them. Methods Between May and December 2024, a stratified cluster random sampling method was employed to survey workers from 73 large, medium, and small and micro sized enterprises across the aforementioned industries in Gansu Province. Participants’ occupational health literacy and occupational stress levels were assessed. The LASSO regression model was applied to identifykey factors influencing occupational stress, and subsequently a multilevel random intercept mixed-effects logistic model was used to study factors influencing occupational stress and to explore the relationship between occupational health literacy and occupational stress. Results A total of 3611 workers across the three industries were surveyed, among whom 1031 (28.55%) experienced occupational stress. Workers with adequate occupational health literacy—whether assessed in terms of overall literacy or specific dimensions—demonstrated a significantly lower prevalence of occupational stress compared to those without adequate literacy (P<0.05). Through the LASSO regression analysis, it was found that the factors closely related to occupational stress were dimension one (occupational health legal knowledge), dimension two (basic knowledge of occupational health protection), and dimension four (healthy working methods and behaviors) of occupational health literacy, gender, average monthly income, and night shifts. The results from the three-level random intercept mixed-effects logistic regression model indicated that dimensions one (OR=0.69, 95%CI: 0.58, 0.82), two (OR=0.71, 95%CI: 0.58, 0.87), and four (OR=0.81, 95%CI: 0.67, 0.98) of occupational health literacy were negatively correlated with the risk of occupational stress. Workers with an average monthly income of 3001–≤5000, 5001–≤7000, and ≥7001 yuan reported occupational stress risks that were 61% (OR=0.61, 95%CI: 0.45, 0.81), 56% (OR=0.56, 95%CI: 0.41, 0.78), and 36% (OR=0.36, 95%CI: 0.24, 0.53) of those with an average monthly income ≤3000 yuan, respectively. Male workers (OR=1.66, 95%CI: 1.32, 2.10) and those on night shifts (OR=2.29, 95%CI: 1.90, 2.76) had a higher risk of occupational stress. The random effects variance showed that the intraclass correlation coefficient was 0.12. Conclusion There is a negative correlation between occupational stress and occupational health literacy among workers in mining and manufacturing. Being male, having a low income, and working night shifts are risk factors affecting workers' occupational stress. It is recommended to focus on these groups of workers and incorporate occupational health literacy into workplace mental health promotion.

Background Due to the unique working environment and numerous occupational disease hazards, workers in mining industry are particularly susceptible to psychological problems such as occupational stress. Objective To understand the current status of occupational stress, depressive symptoms, anxiety symptoms and sleep quality of workers in ferrous and non-ferrous metal mining industry in Gansu Province, and to explore the effects of occupational stress on depressive symptoms, anxiety symptoms, and sleep. Methods From April to December 2022, the workers of 25 large, medium, and small and micro enterprises were selected by stratified cluster random sampling and surveyed in ferrous and non-ferrous metal mining industry in Gansu Province. The Occupational Health Literacy Questionnaire of National Key Population, Core Occupational Stress Scale, Patient Health Questionnaire-q, Generalized Anxiety Disorder, and Self-administer Sleep Questionnaire were used to collect basic information, occupational stress, depressive symptoms, anxiety symptoms, and sleep quality of the workers. Chi-square test was used to compare occupational stress, depressive symptoms, anxiety symptoms and sleep disorders among different categories. Logistic regression model was used to study the effects of occupational stress on depressive symptoms, anxiety symptoms, and sleep quality. Results In this study, 2192 workers in mining industry were surveyed, of which 2087 returned valid questionnaires, and the recovery rate of valid questionnaires was 95.2%. Among them, 728 (38.4%) reported occupational stress. There were statistically significant differences in the positive rate of occupational stress among workers by gender, age, marital status, education level, average monthly income, length of service, enterprise size, and night shifts (P<0.001). The positive rates of depressive symptoms, anxiety symptoms, and sleep disorders in the mining industry workers were 85.6%, 49.8%, and 47.3%, respectively. The positive rates of depressive symptoms, anxiety symptoms, and sleep disorders among workers with higher occupational stress were higher than those among workers without occupational stress (P<0.001). The logistic regression analysis showed that occupational stress was a common risk factor for depressive symptoms (OR=3.29, 95%CI: 2.26, 4.79), anxiety symptoms (OR=2.87, 95%CI: 2.33, 3.53), and sleep disorder (OR=1.78, 95%CI: 1.46, 2.16). In addition, length of service and enterprise-scale were also risk factors for depressive symptoms, anxiety symptoms, and sleep disorders. In the 5−<10 and 10−<20 years of service groups, the risks of reporting depressive symptoms were 1.80 (95%CI: 1.18, 2.74) and 1.73 (95%CI: 1.10, 2.71) times higher than that of workers with less than 1 year of service, respectively; the risks of reporting anxiety symptoms were 1.98 (95%CI: 1.42, 2.76) and 2.11 (95%CI: 1.48, 3.01) times higher than that with less than 1 year of service, respectively; the risks of reporting sleep disorders were 1.58 (95%CI: 1.15, 2.16) and 1.78 (95%CI: 1.29, 2.45) times higher than that with less than 1 year of service, respectively. Workers in large enterprises were inclined to report more depressive symptoms, anxiety symptoms, and sleep disturbances than those in micro and small enterprises (OR=3.53, 95%CI: 2.41, 5.16; OR=2.49, 95%CI: 1.98, 3.13; OR=2.10, 95%CI: 1.67, 2.62). Conclusion The occupational stress level of mining industry workers in Gansu Province is high, and reporting occupational stress, 5−<10 and 10−<20 working age groups, and large enterprises are important risk factors affecting workers' mental health and sleep. It is necessary to increase the attention and develop intervention programs for mental health of miners in the working age group of 5−20 years old and in large enterprises.

Objective:To investigate the level of occupational health literacy (OHL) of key populations in Gansu Province in 2022, analyze the influencing factors, and provide a scientific basis for the formulation of health education measures for occupational populations.Methods:From April to December 2022, a stratified cluster random sampling method was adopted to select 11472 workers engaged in frontline jobs in 8 key industries across 86 counties and districts in Gansu Province as the research subjects. The "National Occupational Health Literacy Monitoring and Survey Personal Questionnaire" was used to investigate their OHL. The content includes basic demographic information and occupational health literacy level, and the chi-square test analysis was carried out by SPSS 23.0 software, and the influencing factors were analyzed by logistic regression analysis model.Results:In 2022, a total of 11 118 valid questionnaires were completed in Gansu Province, and the OHL level of key populations in Gansu Province was 48.3%. The OHL levels of occupational health legal knowledge, basic knowledge of occupational health protection, basic skills of occupational health protection and healthy working methods were 50.3%, 81.7%, 33.1% and 63.3%, respectively. In the eight key industries, the OHL level of workers from high to low is: ferrous and non-ferrous metal smelting and rolling processing industry (56.6%) , non-metallic mineral products industry (56.5%) , ferrous and non-ferrous metal mining and dressing industry (54.3%) , environmental sanitation industry (50.3%) , medical and health industry (49.9%) , education industry (40.9%) , transportation industry (40.4%) , and express delivery/takeaway delivery industry (23.3%) . The results of logistics regression analysis showed that gender, age, ethnicity, marital status, education level, average monthly income, nature and scale of employers, and length of service were the influencing factors of OHL level of front-line workers in eight industries in Gansu Province (all P<0.05) . Conclusion:In 2022, the OHL level of key populations in Gansu Province was 48.3%, which needs to be further improved. Occupational health publicity should be strengthened for low-income, low-educated, newly recruited, young and micro-enterprise occupational groups.

Objective:To investigate the impact of frailty on post-stroke depression (PSD) in patients with acute ischemic stroke and to identify risk factors for PSD in order to construct a risk prediction model.Methods:A convenience sampling method was used to recruit a total of 450 patients with acute ischemic stroke who were treated in the Department of Neurology at the Affiliated Hospital of Jining Medical University from March 2023 to April 2024. Data were collected using the Edmonton Frail Scale, Hamilton Depression Rating Scale, Barthel Index (Activities of Daily Living, ADL), Pittsburgh Sleep Quality Index, and Morse Fall Scale. Binary logistic regression analysis was performed to explore the impact of frailty on PSD and to identify other risk factors. Based on the results, a predictive model was developed.Results:A total of 450 questionnaires were distributed, with 412 valid responses returned, yielding a valid response rate of 91.56%. The incidence of PSD among the 412 patients was 45.63% (188/412). Binary Logistic regression analysis showed that frailty, sleep disturbance, C-reactive protein (CRP), and ADL score were the influencing factors for PSD in patients with acute ischemic stroke ( P<0.05). These factors were incorporated into the predictive model, and a risk nomogram was constructed. The area under the curve of the model was 0.764 [95% CI (0.716, 0.811) ], indicating good discriminative ability. Internal validation of the nomogram using the Hosmer-Lemeshow goodness-of-fit test showed χ 2=5.883, P=0.66 ( P>0.05), suggesting good calibration of the model. Conclusions:Frailty increases the risk of post-stroke depression in patients with acute ischemic stroke. Sleep disturbance, CRP level, and ADL score are important screening indicators for PSD risk. Targeted assessment and early intervention are recommended to reduce the likelihood of PSD.

Objective:To investigate the impact of frailty on post-stroke depression (PSD) in patients with acute ischemic stroke and to identify risk factors for PSD in order to construct a risk prediction model.Methods:A convenience sampling method was used to recruit a total of 450 patients with acute ischemic stroke who were treated in the Department of Neurology at the Affiliated Hospital of Jining Medical University from March 2023 to April 2024. Data were collected using the Edmonton Frail Scale, Hamilton Depression Rating Scale, Barthel Index (Activities of Daily Living, ADL), Pittsburgh Sleep Quality Index, and Morse Fall Scale. Binary logistic regression analysis was performed to explore the impact of frailty on PSD and to identify other risk factors. Based on the results, a predictive model was developed.Results:A total of 450 questionnaires were distributed, with 412 valid responses returned, yielding a valid response rate of 91.56%. The incidence of PSD among the 412 patients was 45.63% (188/412). Binary Logistic regression analysis showed that frailty, sleep disturbance, C-reactive protein (CRP), and ADL score were the influencing factors for PSD in patients with acute ischemic stroke ( P<0.05). These factors were incorporated into the predictive model, and a risk nomogram was constructed. The area under the curve of the model was 0.764 [95% CI (0.716, 0.811) ], indicating good discriminative ability. Internal validation of the nomogram using the Hosmer-Lemeshow goodness-of-fit test showed χ 2=5.883, P=0.66 ( P>0.05), suggesting good calibration of the model. Conclusions:Frailty increases the risk of post-stroke depression in patients with acute ischemic stroke. Sleep disturbance, CRP level, and ADL score are important screening indicators for PSD risk. Targeted assessment and early intervention are recommended to reduce the likelihood of PSD.

Objective:To investigate the level of occupational health literacy (OHL) of key populations in Gansu Province in 2022, analyze the influencing factors, and provide a scientific basis for the formulation of health education measures for occupational populations.Methods:From April to December 2022, a stratified cluster random sampling method was adopted to select 11472 workers engaged in frontline jobs in 8 key industries across 86 counties and districts in Gansu Province as the research subjects. The "National Occupational Health Literacy Monitoring and Survey Personal Questionnaire" was used to investigate their OHL. The content includes basic demographic information and occupational health literacy level, and the chi-square test analysis was carried out by SPSS 23.0 software, and the influencing factors were analyzed by logistic regression analysis model.Results:In 2022, a total of 11 118 valid questionnaires were completed in Gansu Province, and the OHL level of key populations in Gansu Province was 48.3%. The OHL levels of occupational health legal knowledge, basic knowledge of occupational health protection, basic skills of occupational health protection and healthy working methods were 50.3%, 81.7%, 33.1% and 63.3%, respectively. In the eight key industries, the OHL level of workers from high to low is: ferrous and non-ferrous metal smelting and rolling processing industry (56.6%) , non-metallic mineral products industry (56.5%) , ferrous and non-ferrous metal mining and dressing industry (54.3%) , environmental sanitation industry (50.3%) , medical and health industry (49.9%) , education industry (40.9%) , transportation industry (40.4%) , and express delivery/takeaway delivery industry (23.3%) . The results of logistics regression analysis showed that gender, age, ethnicity, marital status, education level, average monthly income, nature and scale of employers, and length of service were the influencing factors of OHL level of front-line workers in eight industries in Gansu Province (all P<0.05) . Conclusion:In 2022, the OHL level of key populations in Gansu Province was 48.3%, which needs to be further improved. Occupational health publicity should be strengthened for low-income, low-educated, newly recruited, young and micro-enterprise occupational groups.

Objective:To explore the correlation between frailty and carotid plaque stability in patients with ischemic stroke.Methods:This study was a cross-sectional study. From May to December 2023, convenience sampling was used to select 360 patients with ischemic stroke in the Department of Neurology of Affiliated Hospital of Jining Medical University and underwent carotid artery color Doppler ultrasound examination as the study subject. Patients were surveyed using the General Information Questionnaire, Barthel Index and the Edmonton Frail Scale. Carotid artery color Doppler ultrasound was used to evaluate the stability of carotid plaques in patients. Multivariate Logistic regression was used to explore the correlation between frailty and carotid plaque stability.Results:A total of 360 questionnaires were distributed, and 352 valid questionnaires were collected, with a valid response rate of 97.78%. The incidence of frailty in 352 ischemic stroke patients was 44.89% (158/352). Multivariate analysis showed that compared to stable plaques, unstable carotid plaques were an independent risk factor for frailty in patients with ischemic stroke ( OR=2.127, 95% confidence interval: 1.247-3.626) . Conclusions:Compared to stable plaques, unstable carotid plaques increase the risk of frailty in patients with ischemic stroke. Strengthening the assessment of carotid plaques in patients with ischemic stroke by nursing staff can early identify high-risk individuals for frailty, and timely carry out personalized interventions, thereby reducing the occurrence of adverse health events in patients.

Objective:To establish the normal reference range of atrial septal excursion index (ASEI) and foramen ovale membrane angle in normal fetuses aged 16-40 weeks, and to analyze the correlation between ASEI and foramen ovale membrane angle in normal fetuses.Methods:A total of 378 normal singletons with gestational ages of 16-40 weeks undergoing by fetal echocardiography were selected in the Department of Diagnostic Ultrasound & Echocardiography, Sir Run Run Shaw Hospital, Zhejiang University College of Medicine, from January to June 2021, and 349 fetuses successfully finished all measurements. After all fetuses completed the systematic fetal echocardiography, fetal foramen ovale diameter and foramen ovale membrane angle were measured on the four chamber view. The maximum distance of foramen ovale valve from the base of atrial septum to the free wall of left atrium and the transverse diameter of left atrium were measured, and ASEI was calculated. The differences of ASEI, foramen ovale membrane angle and foramen ovale diameter of the groups with different gestational weeks were compared. The correlations among ASEI, foramen ovale membrane angle and foramen ovale diameter were analyzed by Pearson correlation analysis.Results:All 349 fetuses were divided into 6 groups according to their gestational weeks, including 17 cases at 16-20 weeks, 46 cases at 21-24 weeks, 114 cases at 25-28 weeks, 105 cases at 29-32 weeks, 31 cases at 33-36 weeks and 36 cases at 37-40 weeks. The ± s of ASEI was 0.492 7±0.059 7, 95% CI was 0.486 4-0.499 0, 95% normal reference value range was 0.375 7-0.609 8. Significant differences were found in ASEI among different groups( P<0.05). The ± s of foramen ovale membrane angle was (44.03±5.48)°, 95% CI was 43.46-44.61°, 95% normal reference value range was 33.29-54.78°. Significant differences were found in the foramen ovale membrane angle among different groups( P<0.05). The ± s of foramen ovale diameter was (4.32±1.30)mm, 95% CI was 4.18-4.45 mm, the differences among different groups were significant( P<0.05) and foramen ovale diameter was found increased with the increase of gestational weeks. There was a significant positive correlation between ASEI and foramen ovale membrane angle ( r=0.558, P<0.05). There was no correlation between foramen ovale diameter and ASEI and foramen ovale membrane angle ( r=-0.166, -0.084; all P>0.05). Conclusions:The normal reference ranges of ASEI and foramen ovale valve angle of normal fetuses aged 16-40 weeks was successfully established. These parameters may be useful for evaluating diastolic cardiac function by assessing foramen ovale.

Objective:To investigate the association of left and right ventricular diameters in normal early pregnancy and early middle pregnancy to the biological growth parameters of fetus, and to establish the reference and Z-score model for left and right ventricles.Methods:Two hundred and forty-six fetuses in normal early pregnancy (11-13 + 6 weeks) and early middle pregnancy (14-17 + 6 weeks) from February 2019 to May 2019 in Sir Run Run Shaw Hospital were examined by routine ultrasound. Non-cardiac fetal biometric parameters included crown-rump length (CRL), biparietal diameter (BPD) and femoral length (FL) and gestation age (GA) based on menstrual age were assessed. The left and right ventricular widths (LVW, RVW) and ventricular lengths (LVL, RVL) were measured at the end of diastolic period by obtaining the standard four chamber view of fetal echocardiography. The end-diastolic areas (LVA, RVA) as the products of the ventricular widths and lengths, the global spherical indexes (GSI) of left and right ventricles (LVSI, RVSI), the ratios of left and right ventricular widths (LVW/RVW), the length ratios (LVL/RVL) and the area ratios (LVA/RVA) of both ventricles were calculated.GA, BPD and FL were used as independent variables. The predicted cardiac parameters and its derivative parameters were used as dependent variables. The corresponding reference range was established. The correlation between each standard deviation (SD) and independent variables was analyzed, and the corresponding Z-scores of left and right ventricular diameters were calculated by using the formula. Results:①LVW, RVW, LVL, RVL were found positively correlated with the increase of GA, BPD and FL, and the correlation between GA and LVW, RVW was the highest ( r=0.928, 0.930; all P<0.000 1). ②There was a positive correlation between LVA, RVA and GA ( r=0.868, 0.872; all P<0.000 1). LVSI, RVSI were found negatively correlated with GA ( r=-0.844, -0.861; all P<0.000 1), and LVSI>RVSI. LVW/RVW<1 and almost close to 1, the ratios decreased with the increase of GA( r=0.147, P<0.000 1). LVL/RVL>1, the ratios increased with the increase of GA( r=0.313, P<0.000 1). LVA/RVA>1, but there was no correlation with GA. ③The SD values of LVW, RVW, LVL, RVL positively correlated with independent variables. Taking GA and LVW as an example, the linear regression equation of LVW was Y=-5.338+ 0.549GA ( r=0.928, P<0.000 1), and the linear regression equation of LVW-SD was Y=-0.322+ 0.037GA( r=0.131, P<0.000 1). The Z-scores of LVW, RVW, LVL, RVL, LVA, RVA did not change with the changes of GA, BPD, and FL. Conclusions:The normal reference range and Z-scores of left and right ventricular lengths and widths can be simply and reliably established using statistical analysis, and these parameters might have potentials for more accurately and more early evaluating the normal development of fetal heart.