Objective: To learn about the noise exposure and health status of workers and analyze factors that may affect the health outcomes of workers in an auto manufacturing enterprise in Tianjin City. Methods: In September 2020, occupational hygiene survey, noise exposure level detection and occupational health examination data collection were carried out in an auto parts manufacturing enterprise. Chi square test and unconditional logistic regression analysis were used to analyze the health effects of noise exposure and hearing loss of 361 noise exposure workers. Results: The rates of over-standard noise exposure, hearing loss and hypertension were 69.39% (34/49) , 33.24% (120/361) and 11.36% (41/361) , respectively. There were upward trends on age and noise-working years for hearing loss and hypertension rates (χ(2)=-5.95, -6.16, -2.81, -2.74, P<0.05) . Unconditional logistic regression analysis showed that age>35 years old, noise exposure length of service >10 years and noise L(EX, 8 h)>85 dB (A) were risk factors for hearing loss (OR=3.57, 95%CI: 1.09, 11.75; OR=4.05, 95%CI: 1.97, 8.25; OR=1.75, 95%CI: 1.00, 3.05; P=0.036, 0.001, 0.047) . Conclusion: This company has a high rate of job noise exceeding the standard, and noise-exposed workers have more serious hearing loss. Age, noise exposure and high noise exposure are risk factors for hearing loss.
Adult ; Automobiles ; Deafness ; Hearing Loss, Noise-Induced/etiology* ; Humans ; Hypertension/complications* ; Noise, Occupational/adverse effects* ; Occupational Diseases/complications* ; Occupational Exposure/analysis*

Objective: To investigate the relationship between high frequency hearing loss caused by occupational noise and the risk of hypertension. Methods: In March 2020, a case-control study was conducted. All noise exposed workers who participated in occupational health examination in Wuxi City in 2019 were selected as the study subjects (95432 cases in total) . The hypertension group was defined as the case group, and the normotensive group was defined as the control group. According to the hearing threshold, they were divided into the non high frequency hearing loss group (<40 dB) and the high frequency hearing loss group (≥ 40 dB) . Univariate statistical method and binary logistic regression were used to evaluate the relationship between high-frequency hearing loss and hypertension risk. Stratified analysis was used to compare the risk of hypertension among workers with high-frequency hearing loss of different ages and length of service. Results: There were significant differences in gender, age, length of service, enterprise scale, economic type and high-frequency hearing loss between control group and hypertension group (P<0.05) . Binary logistic regression analysis showed that after adjusting for gender, age, length of service, enterprise scale and economic type, the risk of hypertension in the high-frequency hearing loss group was still increased (OR=1.062, 95%CI: 1.007~1.121, P=0.027) . The risk of hypertension in high-frequency hearing loss patients was higher than that in non high-frequency hearing loss patients in 20-39 years old and 40-59 years old age groups (OR=1.536, 95%CI: 1.353~1.743; OR=1.179, 95%CI: 1.111~1.250; P<0.05) . The risk of hypertension in high-frequency hearing loss patients in <5years, 5-9years, 10-14 years, 15-19 years and ≥20 years working age groups were higher than that in non high-frequency hearing loss groups (OR=1.926, 95%CI=1.007-1.121; OR=1.635, 95%CI=1.478-1.810; OR=1.312, 95%CI=1.167-1.474; OR=1.445, 95%CI=1.238-1.686; OR=1.235, 95%CI=1.043-1.463; P<0.05) . Conclusion: There is a certain relationship between high-frequency hearing loss caused by occupational noise and the risk of hypertension, and the risk of hypertension is different among high-frequency hearing loss patients of different ages and working years.
Humans ; Young Adult ; Adult ; Noise, Occupational/adverse effects* ; Hearing Loss, Noise-Induced/etiology* ; Case-Control Studies ; Hearing Loss, High-Frequency ; Occupational Exposure/adverse effects* ; Hypertension/complications* ; Occupational Diseases/complications*

Occupational and environmental exposure can directly cause specific lung diseases, and can also induce autoimmune diseases that can lead to various types of interstitial lung diseases. In recent years, it was discovered that certain occupational and environmental exposure was related to the increased risk of Idiopathic pulmonary fibrosis (IPF) disease and progression, including metal and mineral dust, wood dust, organic dust, asbestos dust, silica dust, cigarette smoke and air pollution. IPF is a chronic progressive fibrotic lung disease of unknown etiology, with a characteristic imaging and histologic pattern called usual interstitial pneumonia. This article is a review based on the correlation and mechanism of occupational and environmental exposure in the pathogenesis and disease progression of IPF to improve the understanding of the disease and promote the formulation of treatment plans.
Humans ; Idiopathic Pulmonary Fibrosis/etiology* ; Dust ; Environmental Exposure/adverse effects* ; Occupational Exposure/adverse effects* ; Lung Diseases, Interstitial

COVID-19/psychology* ; Global Health/statistics & numerical data* ; Health Personnel/statistics & numerical data* ; Humans ; Mental Disorders/etiology* ; Mental Health/statistics & numerical data* ; Occupational Diseases/psychology*

INTRODUCTION: Frontline healthcare workers (HCWs) exposed to coronavirus disease 2019 (COVID-19) are at risk of psychological distress. This study evaluates the psychological impact of COVID-19 pandemic on HCWs in a national paediatric referral centre. METHODS: This was a survey-based study that collected demographic, work environment and mental health data from paediatric HCWs in the emergency, intensive care and infectious disease units. Psychological impact was measured using the Depression, Anxiety, Stress Scale-21. Multivariate regression analysis was performed to identify risk factors associated with psychological distress. RESULTS: The survey achieved a response rate of 93.9% (430 of 458). Of the 430 respondents, symptoms of depression, anxiety and stress were reported in 168 (39.1%), 205 (47.7%) and 106 (24.7%), respectively. Depression was reported in the mild (47, 10.9%), moderate (76, 17.7%), severe (23, 5.3%) and extremely severe (22, 5.1%) categories. Anxiety (205, 47.7%) and stress (106, 24.7%) were reported in the mild category only. Collectively, regression analysis identified female sex, a perceived lack of choice in work scope/environment, lack of protection from COVID-19, lack of access to physical activities and rest, the need to perform additional tasks, and the experience of stigma from the community as risk factors for poor psychological outcome. CONCLUSION A high prevalence of depression, anxiety and stress was reported among frontline paediatric HCWs during the COVID-19 pandemic. Personal psychoneuroimmunity and organisational prevention measures can be implemented to lessen psychiatric symptoms. At the national level, involving mental health professionals to plan and coordinate psychological intervention for the country should be considered.
Adult ; Anxiety/etiology* ; COVID-19/psychology* ; Depression/etiology* ; Female ; Health Surveys ; Hospitals, Pediatric ; Humans ; Logistic Models ; Male ; Middle Aged ; Multivariate Analysis ; Occupational Diseases/etiology* ; Pandemics ; Personnel, Hospital/psychology* ; Prevalence ; Risk Factors ; Self Report ; Severity of Illness Index ; Singapore/epidemiology* ; Stress, Psychological/etiology*

Automobiles ; Hearing Loss, High-Frequency ; Hearing Loss, Noise-Induced/etiology* ; Humans ; Male ; Noise, Occupational/adverse effects* ; Occupational Diseases/epidemiology* ; Occupational Exposure

Adult ; Candy ; Dust ; Health Surveys ; Hearing Loss, Noise-Induced/etiology* ; Humans ; Male ; Middle Aged ; Noise, Occupational/adverse effects* ; Occupational Diseases ; Occupational Exposure

Adult ; Automobiles ; Hearing Loss, High-Frequency ; Hearing Loss, Noise-Induced/etiology* ; Humans ; Male ; Noise, Occupational/adverse effects* ; Occupational Diseases ; Occupational Exposure

Occupational noise is one of the most common occupational hazards in the workplace. Long-term exposure to occupational noise could not only lead to the damage of the hearing system, but also may cause a certain impact on the cardiovascular system. Studies have shown that occupational noise exposure was positively associated with cardiovascular diseases, including hypertension, coronary heart disease and myocardial infarction. However, the results of studies on occupational noise exposure and stroke are still controversial. This paper reviews the relationship between occupational noise exposure and hypertension, coronary heart disease, stroke, myocardial infarction by summarizing the epidemiological data of domestic and foreign population in recent years. Our study could provide evidence for the design and implementation of well-designed epidemiological and mechanism studies, and the recognition of the role of occupational noise exposure in the occurrence and development of cardiovascular diseases, so as to better protect workers' health.
Cardiovascular Diseases/etiology* ; Hearing Loss, Noise-Induced ; Humans ; Hypertension/etiology* ; Noise, Occupational/adverse effects* ; Occupational Diseases ; Occupational Exposure/adverse effects*

Objective: To determine the factors influencing insomnia and construct early insomnia warning tools for rescuers to informbest practices for early screening and intervention. Methods: Cluster sampling was used to conduct a cross-sectional survey of 1,133 rescuers from one unit in Beijing, China. Logistic regression modeling and R software were used to analyze insomnia-related factors and construct a PRISM model, respectively. Results: The positive rate of insomnia among rescuers was 2.74%. Accounting for participants' age, education, systolic pressure, smoking, per capita family monthly income, psychological resilience, and cognitive emotion regulation, logistic regression analysis revealed that, compared with families with an average monthly income less than 3,000 yuan, the odds ratio ( ) values and the [95% confidence interval ( )] for participants of the following categories were as follows: average monthly family income greater than 5,000 yuan: 2.998 (1.307-6.879), smoking: 4.124 (1.954-8.706), and psychological resilience: 0.960 (0.933-0.988). The ROC curve area of the PRISM model (AUC) = 0.7650, specificity = 0.7169, and sensitivity = 0.7419. Conclusion Insomnia was related to the participants' per capita family monthly income, smoking habits, and psychological resilience on rescue workers. The PRISM model's good diagnostic value advises its use to screen rescuer early sleep quality. Further, advisable interventions to optimize sleep quality and battle effectiveness include psychological resilience training and smoking cessation.
Adolescent ; Adult ; China ; epidemiology ; Cross-Sectional Studies ; Humans ; Incidence ; Income ; statistics & numerical data ; Male ; Models, Theoretical ; Occupational Diseases ; epidemiology ; etiology ; Rescue Work ; statistics & numerical data ; Resilience, Psychological ; Risk Factors ; Sleep Initiation and Maintenance Disorders ; epidemiology ; etiology ; Smoking ; epidemiology ; Socioeconomic Factors ; Young Adult