Variations in the Cadherin 23 Gene Associated With Noise-Induced Hearing Loss.

Background: The relationship between CDH23 gene variants and NIHL is unclear. This study investigates the association between cadherin 23 (CDH23) gene variants and noise-induced hearing loss (NIHL). Methods: This is a case-control study. Workers who were exposed to noise from a steel factory in North China were recruited and divided into two groups: the case group (both ears' high-frequency threshold average [BHFTA] ≥40dB) and the control group (BHFTA ≤25 dB). This study used the generalised multifactor dimensionality reduction method to analyse the association among 18 single-nucleotide polymorphisms (SNPs) in CDH23 and NIHL. Logistic regression was performed to investigate the main effects of SNPs and the interactions between cumulative noise exposure (CNE) and SNPs. Furthermore, CNE was adjusted for age, gender, smoking, drinking, physical exercise and hypertension. Results: This study recruited 1,117 participants. The results showed that for rs11592462, participants who carried the GG genotype showed an association with NIHL greater than that of those who carried the CC genotype. Accordingly, genetic variation in the CDH23 gene could play an essential role in determining individual susceptibility to NIHL. Conclusion: Genetic variations in the CDH23 gene may play an important role in determining individual susceptibility to NIHL. These results provide new insight into the pathogenesis and early prevention of NIHL.

Plasma metabolomics analyses highlight the multifaceted effects of noise exposure and the diagnostic power of dysregulated metabolites for noise-induced hearing loss in steel workers.

Noise exposure can lead to various kinds of disorders. Noise-induced hearing loss (NIHL) is one of the leading disorders confusing the noise-exposed workers. It is essential to identify NIHL markers for its early diagnosis and new therapeutic targets for its treatment. In this study, a total of 90 plasma samples from 60 noise-exposed steel factory male workers (the noise group) with (NIHL group, n = 30) and without NIHL (non-NIHL group, n = 30) and 30 male controls without noise exposure (control group) were collected. Untargeted human plasma metabolomic profiles were determined with HPLC-MS/MS. The levels of the metabolites in the samples were normalized to total peak intensity, and the processed data were subjected to multivariate data analysis. The Wilcoxon test and orthogonal partial least square-discriminant analysis (OPLS-DA) were performed. With the threshold of p < 0.05 and the variable importance of projection (VIP) value >1, 469 differential plasma metabolites associated with noise exposure (DMs-NE) were identified, and their associated 58 KEGG pathways were indicated. In total, 33 differential metabolites associated with NIHL (DMs-NIHL) and their associated 12 KEGG pathways were identified. There were six common pathways associated with both noise exposure and NIHL. Through multiple comparisons, seven metabolites were shown to be dysregulated in the NIHL group compared with the other two groups. Through LASSO regression analysis, two risk models were constructed for NIHL status predication which could discriminate NIHL from non-NIHL workers with the area under the curve (AUC) values of 0.840 and 0.872, respectively, indicating their efficiency in NIHL diagnosis. To validate the results of the metabolomics, cochlear gene expression comparisons between susceptible and resistant mice in the GSE8342 dataset from Gene Expression Omnibus (GEO) were performed. The immune response and cell death-related processes were highlighted for their close relations with noise exposure, indicating their critical roles in noise-induced disorders. We concluded that there was a significant difference between the metabolite's profiles between NIHL cases and non-NIHL individuals. Noise exposure could lead to dysregulations of a variety of biological pathways, especially immune response and cell death-related processes. Our results might provide new clues for noise exposure studies and NIHL diagnosis.

[Relationship between GRM7 gene polymorphisms and the susceptbility to noise-induced hearing loss].

OBJECTIVE: To investigate the relationship between metabolic glutamate receptor 7 gene( GRM7) polymorphisms and the susceptibility to noise-induced hearing loss( NIHL) in Chinese Han occupational population. METHODS: Using a nested case-control study with a 1 ∶ 1 matching, a total of 277 cases of contacting noise workers were selected from a cohort in a steel factory. According to the matching criteria: the same sex, the same type of work, the age difference ≤ 5 years, contact noise length ≤ 2 years, 277 controls were selected. The 8 single nucleotide polymorphisms( SNPs) of the GRM7 gene, rs3749380, rs11928865, rs9877154, rs3828472, rs9819783, rs11920109, rs1485175 and rs9826579, were detected by SNPscanTMmethod. The 4 gene models, the additive model, dominant model, recessive model, codominant model, were constructed to explore the biological association with NIHL susceptibility. The possible diplotype of each subject was constructed using Phase 2. 0. 2 to analyze its relationship with NIHL. According to the layered cumulative noise exposure( CNE), the interactions between the influencing factor were analyzed. The relationship between the GRM7 gene and NIHL was analyzed by single factor and multivariate factors conditional logistic regression analysis. RESULTS: The comparison of general demographic characteristics between the hearing loss group and control group showed that smoking could increase the risk of developing NIHL by 2. 051 times( 95 % CI 1. 456-2. 891, P< 0. 001). No statistically significant difference was found in the analysis of GRM7 polymorphisms and the susceptibility to NIHL. CONCLUSION: Smoking may increase the risk of NIHL. The relationship between GRM7 polymorphisms and the susceptibility to NIHL has not been found in this study.

Increased levels of urinary biomarkers of lipid peroxidation products among workers occupationally exposed to diesel engine exhaust.

Diesel engine exhaust (DEE) was found to induce lipid peroxidation (LPO) in animal exposure studies. LPO is a class of oxidative stress and can be reflected by detecting the levels of its production, such as malondialdehyde (MDA) and 4-hydroxynonenal (4-HNE), and etheno-DNA adducts including 1,N(6)-etheno-2'-deoxyadenosine (ɛdA) and 3,N(4)-etheno-2'-deoxycytidine (ɛdC). However, the impact of DEE exposure on LPO has not been explored in humans. In this study, we evaluated urinary MDA, 4-HNE, ɛdA, and ɛdC levels as biomarkers of LPO among 108 workers with exclusive exposure to DEE and 109 non-DEE-exposed workers. Results showed that increased levels of urinary MDA and ɛdA were observed in subjects occupationally exposed to DEE before and after age, body mass index (BMI), smoking status, and alcohol use were adjusted (all p < 0.001). There was a statistically significant relationship between the internal exposure dose (urinary ΣOH-PAHs) and MDA, 4-HNE, and ɛdA (all p < 0.001). Furthermore, significant increased relations between urinary etheno-DNA adduct and MDA, 4-HNE were observed (all p < 0.05). The findings of this study suggested that the level of LPO products (MDA and ɛdA) was increased in DEE-exposed workers, and urinary MDA and ɛdA might be feasible biomarkers for DEE exposure. LPO induced DNA damage might be involved and further motivated the genomic instability could be one of the pathogeneses of cancer induced by DEE-exposure. However, additional investigations should be performed to understand these observations.

[Analysis of relationship between shift-work and occupational stress among workers from different companies].

OBJECTIVE: To investigate the relationship between work in shifts and occupational stress. METHODS: A total of 5338 employees from 13 companies were investigated by cluster sampling, and occupational stress measuring tools, job content questionnaire, and effort-reward imbalance questionnaire were used to investigate occupational stress factors, stress reaction, and the condition of work in shifts. RESULTS: The employees who worked in shifts accounted for 46.6%. The condition of work in shifts varied significantly across different companies, employees with different individual features (including sex, job title, degree of education, age, working years, smoking, and drinking), and employees with different weekly working times(P<0.01 or P<0.05); health status was associated with work in shifts(P<0.01); compared with the employees who did not work in shifts, those who worked in shifts had significantly lower scores of technology utilization, work control level, psychological need, reward, social support, and job satisfaction(P<0.01 or P<0.05), as well as significantly higher scores of physical demands, effort, depressive symptoms, and negative affectivity(P<0.01). CONCLUSION: Work in shifts can affect health status, and is associated with occupational stress.

[Relationship between job satisfaction and occupational stress in the workers of a thermal power plant].

OBJECTIVE: To explore the relationship between job satisfaction and occupational stress in the workers of a thermal power plant. METHODS: The cluster sampling method was used to investigate 875 workers in a thermal power plant. The job satisfaction, occupational stressors, strains, personalities, meeting strategy and social support were measured using occupational stress instruments, job content questionnaire and effort-reward imbalance questionnaire. RESULTS: There were no significant differences of job satisfaction scores between different groups according to sex, educational level, marriage status, smoking and drinking (P > 0.05). But there were significant differences of job satisfaction scores between different age groups or between different service length groups (P < 0.01). The correlation analysis revealed that job satisfaction scores were related positively to responsibility for persons and things, promotion opportunity, job control, job stabilization, rewards, mental health, positive affectivity, self-esteem, superior support and coworker support scores (P < 0.05 or P < 0.01), negatively to role ambiguity and conflict, job future ambiguity, job demands, negative affectivity, depressive symptoms, patience, and mental locus of work control(P < 0.05 or P < 0.01). The results of variance analysis indicated that the job relationship, responsibility for persons and things, promotion opportunity, job control, job stabilization, reward, mental health, positive affectivity, self-esteem and buffer scores of the workers with high job satisfaction scores were significantly higher than those of workers with moderate and lower job satisfaction scores (P < 0.01), but the role ambiguity and conflict, job future ambiguity, job demands, and depressive symptoms scores and mental locus of work control of the workers with high job satisfaction scores were significantly lower than those of workers with moderate and lower job satisfaction scores (P < 0.05 or P < 0.01). The results of multivariate logistic regression analysis showed that the risk of job dissatisfaction for workers with low reward was about four times as high as that for workers with high reward (OR = 3.773), the risks of job dissatisfaction for workers with low social support and mental locus of external work control were about two times as high as that for workers with high social support or mental locus of internal work control (OR = 2.419 and 2.219, respectively). The daily life stress, low control strategy, low support strategy, low job control and negative affectivity were risk factors of job dissatisfaction (OR = 1.125 approximately 1.790), but the self-esteem and positive affectivity could reduce the risk of job dissatisfaction. CONCLUSION: Increasing the decision level, social support, meeting strategy and reward or decreasing the role conflict and ambiguity, demands and negative affectivity could improve worker's job satisfaction level.

[Effect of occupational stress on hypertension].

OBJECTIVE: To explore the effect of occupational stress on hypertension. METHODS: 498 workers whose accumulative length of service was more than two years were investigated with questionnaire by method of cluster sampling from a thermal power plant in Henan province in China; 446 respondents returned qualified questionnaire including 281 male and 165 female Han People. After the patients with secondary hypertension, diabetes patients, and patients with liver or kidney disease were excluded, 84 workers (58 males and 26 females) were diagnosed as hypertension. The occupational stressors, personalities, buffering factors and occupational strain were measured by using the Job Demand-control Model, the Effort-reward Imbalance Model questionnaires and Occupational Stress Measurement Scale. Main risk factors for the development of hypertension such as heredity, body mass index, high salt diet, alcohol use, smoking habit and lack of physical activity were investigated. 498 whole blood samples were collected from workers in field epidemiologic survey. All of the samples were detected TG, CHO and FPG by common biochemistry methods. Multivariate logistic regression analysis were used to determine the relationship between occupational stressors and prevalence rate of hypertension. The difference of morbidity of hypertension between different stress level subjects was analyzed by chi2 test. RESULTS: (1) Logistic regression analysis of the hypertension by all occupational stressors and risk factors of hypertension indicated that not only some common factors such as parents' hypertensive history, BMI, alcohol use and TG, but also responsibility for person, work locus of control and social support were significantly correlated with elevated risks of hypertension. (2) Logistic regression analysis of the hypertension by main dimensions of effort-reward imbalance model and risk factors of hypertension indicated that parents' hypertensive history, BMI, alcohol use, TG, and effort were significantly correlated with elevated risks of hypertension. Logistic regression analysis indicated the risk of hypertension had an effect on the FRI and effort (OR was 1.71 and 2.43 respectively). (3) For the job strain model, results indicated that parents' hypertensive history, UMI, alcohol use, TG, work locus of control and social support were significantly correlated with elevated risks of hypertension. But the main dimensions of job strain model (job demands and decision latitude) didn't enter regression equation. (4) The difference of prevalence of hypertension between high- and low stress level groups in male was statistically significant (OR = 3.13, P < 0.01), but the case was not the same in female (P > 0.05). CONCLUSIONS: Occupational stress might be risk factor of hypertension; The predictive power of effort-reward imbalance model for the development of hypertension would be larger than that of job strain model.

[Analysis of occupational stress in workers of a steel plant].

OBJECTIVE: To investigate level and its influential factors of occupational stressors and strains in workers of a steel plant and explore the feasibility of occupational stress and mental health as indicators of effect evaluation of health promotion at workplace. METHODS: 1039 workers were investigated by using cross-sectional method. The questionnaires included job stressors, skill discretion, job control latitude, mental health and sleep disorders. RESULTS: 54.5% of respondents reported "job doesn't allow mistakes" as stressor, while 47.6% of respondents reported "too job responsibility" as stressor. The scores of job stressors were significantly higher than female workers (P<0.01). Workers with high education level scored more skill discretion, job control latitude and lower mental health than ones with low educational level (P<0.05 or P<0.01). Elder workers had more skill discretion and job control latitude scores than younger. There were significant differences in scores of skill discretion among different length of service groups (P<0.05). There were also significant differences in scores of skill discretion among different job title groups (P<0.01). Occupational stressors were correlated significantly positively with sleep disorder (r=0.37, P<0.01), but job control latitude negatively to mental health (r=-0.19, P<0.01). CONCLUSION: The workers in the steel plant report occupational stressors, which is related to poor self-reported health symptoms. The occupational stressors and mental health should be considered as one of effect evaluation indicators of health promotion at workplace.

[The relationship between occupational stress and cardiovascular disease risk factor].

OBJECTIVE: To explore the relationship between the occupational stress and cardiovascular disease risk factors. METHODS: The subject was 93 male freight train dispatchers, the occupational stressors, personalities, and occupational strain response were measured by using questionnaires. Blood pressure, heart rate, the concentrations of the cholesterol, triglyceride, and glycosylated hemoglobin in blood serum were also measured. RESULTS: Social support score were significantly positively related to systolic pressure (r = 0.22) and diastolic pressure (r = 0.30) (P < 0.05), while job satisfaction negatively related to them and concentration of triglyceride (r = -0.37, -0.47 and -0.28 respectively, P < 0.05, P < 0.01), and self-esteem negatively to systolic pressure (r = -0.21, P < 0.05). The differences in diastolic pressure [(78.5 +/- 13.1), (83.6 +/- 8.2), (88.1 +/- 12.3), (85.8 +/- 9.8) mm Hg, P < 0.05] among groups of social support score, body mass index (BMI) (P < 0.01) among groups of job difficulty the differences in systolic pressure [(124.9 +/- 14.4), (129.7 +/- 13.1), (118.4 +/- 16.4), (133.5 +/- 23.1) mm Hg] and diastolic pressure [(85.5 +/- 11.3), (87.0 +/- 9.8), (80.1 +/- 10.1), (88.9 +/- 12.0) mm Hg] and cholesterol level in serum [(4.96 +/- 1.18), (5.39 +/- 0.85), (5.00 +/- 1.15), (4.34 +/- 0.91) mmol/L] among groups of vulnerability to stress (P < 0.05), as well as the difference in systolic pressure and glycosylated hemoglobin level in serum among groups of competition score (P < 0.05) were all statistically significant. Stepwise regression analysis showed that job time demands and negative coping affected the change of cholesterol (R(2) > 0.05); the job relation decision latitude, social support, job difficulty, personality (self-esteem and anxiety trait) and negative coping were the predictors of smoking (R(2) > 0.05). Heart rate was related to home income and competition factor of Type A Behavior (R(2) = 0.06). CONCLUSION: The psychosocial stress aspects of work may be related to some cardiovascular risk factors.