Objective: To investigate the status of occupational health examination institutions in Zhejiang Province, so as to provide suggestions for quality control of occupational health examination institutions. Methods: The 312 occupational health examination institutions in Zhejiang Province that have completed filing before September 30, 2023 were selected. The comprehensive capability, service quality, technical capability, and information reporting status were surveyed and evaluated through on-site inspection and skill assessment. Results: There were 161 public hospitals (51.60%), 147 private organizations (47.12%), and 4 centers for disease control and prevention (CDCs)/ occupational disease prevention and control institutes (1.28%). The pass rates of comprehensive capability, service quality, technical capability and information reporting were 90.02%, 69.89%, 84.07% and 86.78%, respectively. Among the indicators of comprehensive capability, the compliance rate for staffing was the highest at 95.06%, while the qualification rate of quality control in occupational health examinations was the lowest at 84.83%. Among the indicators of service quality, the compliance rate of the physical examination report format was the highest at 95.83%, while the accuracy rate of the audiometry examination was the lowest at 76.60%. In terms of technical capabilities, the qualification rates for blood lead testing, pneumoconiosis reading, and audiogram diagnostic ability were 87.92%, 89.42% and 75.34%, respectively. In terms of information reporting, the qualification rates for reporting completeness, reporting timeliness, suspected occupational disease reporting timeliness, and reporting accuracy were 89.10%, 81.09%, 96.47% and 80.45%, respectively. Among the three types of institutions, private institutions had the lowest average qualification rates for comprehensive capability, service quality, and technical capability, which were 89.83%, 69.06% and 80.00%, respectively. Conclusions Public hospitals and private organizations were the main types of occupational health examination institutions in Zhejiang Province. However, there were deficiencies in quality control, audiogram examination and diagnosis, and the accuracy of information reporting among occupational health examination institutions.

Complex noise is the dominant type of noise in workplaces. It can cause more serious hearing loss than steady-state noise. The existing noise measurement and evaluation standards based on the "equal energy hypothesis" are not completely suitable for complex noise. This paper introduced the status quo of workplace noise measurement and assessment techniques, and the research progress of workplace complex noise measurement and assessment techniques. In terms of future research in this area, four proposals were made, including to improve associated population database, develop and revise noise-related standards, establish methodology of kurtosis adjustment, and identify the incidence characteristics of kurtosis-related occupational hearing loss. The paper also introduced the special column "Measurement and assessment techniques of complex noise in the workplace".

The existing measuring methods of noise exposure on the basis of equal energy hypothesis are applicable to Gaussian noise while not fully applicable to non-Gaussian noise. Studies have shown that temporal structure (kurtosis) combined with noise energy has the potential to quantify non-Gaussian noise exposure effectively. However, there is no unified measuring method adopting this joint metric. In this paper, the measuring method of non-Gaussian noise exposure based on kurtosis adjustment was introduced, detailing measurement indicators, adjustment schemes, applicable objects, instrument requirements, and measurement steps. Adjusting the exposure duration of cumulative noise exposure (CNE) by kurtosis or adjusting the equivalent continuous A-weighted sound pressure level (L_Aeq) by an adjustment coefficient based on animal or population studies can more accurately quantify workers' exposure to non-Gaussian noise and improve the underestimation of hearing loss caused by non-Gaussian noise. A large number of population studies are warranted in the future to verify the effectiveness of these two adjustment schemes.

Background Occupational noise-induced hearing loss (NIHL) is one of the most prevalent occupational diseases in the world. With the development of industry, noise sources in the workplace have become increasingly complex. Objective To apply kurtosis-adjusted cumulative noise exposure (CNE) to assess the occupational hearing loss among furniture manufacturing workers, and to provide a basis for revising noise measurement methods and occupational exposure limits in China. Methods A cross-sectional survey was conducted to select 694 manufacturing workers, including 542 furniture manufacturing workers exposed to non-Gaussian noise, and 152 textile manufacturing workers and paper manufacturing workers exposed to Gaussian noise. The job titles involving non-Gaussian noise were gunning and nailing, and woodworking, while those involving Gaussian noise were weaving, spinning, and pulping. High frequency noise-induced hearing loss (HFNIHL) and noise exposure data were collected for each study subject. Noise energy metrics included eight-hour equivalent continuous A-weighted sound pressure level (L_{Aeq,8 h}) and CNE. Kurtosis was a noise temporal structure metric. Kurtosis-adjusted CNE was a combined indicator of noise energy and temporal structure. Results The age of the study subjects was (35.64±10.35) years, the exposure duration was (6.71±6.44) years, and the proportion of males was 75.50%. The L_{Aeq,8 h} was (89.43±6.01) dB(A). About 81.42% of the study subjects were exposed to noise levels above 85 dB(A), the CNE was (95.85±7.32) dB(A)·year, with a kurtosis of 99.34 ± 139.19, and the prevalence rate of HFNIHL was 35.59%. The mean kurtosis of the non-Gaussian noise group was higher than that of the Gaussian noise group (125.33±147.17 vs. 5.86±1.94, t=−21.04, P<0.05). The results of binary logistic regression analysis showed that kurtosis was an influential factor of workers' HFNIHL after correcting for age, exposure duration, and L_{Aeq,8 h} (OR=1.49, P<0.05). The results of multiple linear regression analysis showed that the effects of age, exposure duration, L_{Aeq,8 h}, and kurtosis on noise-induced permanent threshold shift at frequencies of 3, 4, and 6 kHz of the poor hearing ear were statistically significant (all P<0.05). The results of chi-square trend analysis showed that when CNE ≥ 90 dB(A)·year, the HFNIHL prevalence rate elevated with increasing kurtosis (P<0.05). The mean HFNIHL prevalence rate was higher in the non-Gaussian noise group than in the Gaussian noise group (31.7% vs. 22.0%, P<0.05). After applying kurtosis-adjusted CNE, the linear equation between CNE and HFNIHL prevalence rate for the non-Gaussian noise group almost overlapped with that for the Gaussian noise group, and the mean difference in HFNIHL prevalence rate between the two groups decreased from 9.7% to 1.4% (P<0.05). Conclusion Noise kurtosis is an effective metric for NIHL evaluation. Kurtosis-adjusted CNE can effectively evaluate occupational hearing loss due to non-Gaussian noise exposure in furniture manufacturing workers, and is expected to be a new indicator of non-Gaussian noise measurement and assessment.

Background Non-Gaussian noise has become the dominant noise type in industry. However, the epidemiological characteristics of non-Gaussian noise exposure and associated noise-induced hearing loss (NIHL) are still unclear. Objective To summarize the epidemiological characteristics of NIHL associated with non-Gaussian noise in manufacturing industry in China and provide a basis for the early prevention and control of occupational hearing loss. Methods Chinese and English literature on hearing loss associated with non-Gaussian noise in China were retrieved. The overall prevalence was calculated based on the prevalence data provided by each included study. A meta-analysis of studies with Gaussian noise as a control group was also performed and the overall weighted odds ratio (OR) was calculated to compare the effects of non-Gaussian noise and Gaussian noise on hearing loss. Publication bias was evaluated by funnel plot and Egger regression, and a sensitivity analysis was performed by eliminating references in turn. Results A total of 37 cross-sectional studies involving 25 055 Chinese manufacturing workers exposed to non-Gaussian noise were included, 92.5% of whom were male. These workers aged (32.7±9.6) years were exposed to non-Gaussian noise at (87.0±4.2) dB(A) for (6.8±4.9) years. The mean cumulative noise exposure (CNE) was (95.9±8.0) dB(A)·year. The prevalence rate of high-frequency NIHL (HFNIHL) and speech-frequency NIHL (SFNIHL) were 29.0% and 14.2%, respectively. The results of the meta-analysis treating 19 cross-sectional studies with Gaussian noise as a control group showed that there were no significant differences in age, exposure duration, and equivalent continuous A-weighted sound pressure level (L_Aeq), and CNE between the non-Gaussian noise group and the Gaussian noise group. The overall weighted OR of HFNIHL was 1.87 (95%CI: 1.46−2.41), which was statistically significant. The funnel plot showed good symmetry and the result of Egger regression was t=−0.11, P=0.910 (>0.05), suggesting a low risk of publication bias in this meta-analysis. The sensitivity analysis showed no significant changes of results after eliminating references in turn, indicating that the results were robust. Conclusion Chinese manufacturing workers, mainly young adult males, are exposed to non-Gaussian noise at high levels for a long time and have a high prevalence of NIHL. Compared to workers exposed to Gaussian noise, those exposed to non-Gaussian noise suffer from more serious hearing loss.

Background Noise is the most common occupational hazard in the automobile manufacturing industry with the most workers exposed. Automobile manufacturing industry is a high-risk industry for noise-induced hearing loss. Objective To understand the epidemiological characteristics of noise-induced hearing loss among workers in automobile manufacturing industry and explore related influencing factors. Methods A questionnaire survey, individual noise recording, and pure tone audiometry were conducted among workers (n=656) exposed to noise from five automobile manufacturing enterprises. The data on age, sex, exposure duration, noise intensity, kurtosis, and hearing loss were obtained. The positive rates of high-frequency noise-induced hearing loss (HFNIHL) and speech-frequency noise-induced hearing loss (SFNIHL) were calculated, and each factor was compared between workers with and without HFNIHL. Chi-square test and analysis of trend were conducted among different groups of age, sex, exposure duration, A-weighted equivalent continuous sound pressure level normalized to a nominal 8-hour working day (L_Aeq,8h), and kurtosis. Logistic regression analysis was conducted to analyze the factors influencing the positive rates of HFNIHL and SFNIHL. Results The exposure rates of non-Gaussian noise was 73.6%. The positive rates of HFNIHL and SFNIHL were 32.6% (214 workers) and 6.7% (44 workers), respectively. The HFNIHL workers showed older age, higher proportion of male, longer exposure duration, higher noise intensity (L_{Aeq,8 h}), and increased kurtosis than those without HFNIHL (P<0.05). The positive rates of HFNIHL increased with the increase of age, exposure duration, L_{Aeq,8 h}, and kurtosis (\begin{document}$ {\chi ^2} $\end{document}_trend-age=49.25, P<0.001; \begin{document}$ {\chi ^2} $\end{document}_{trend-duration}=22.19, P<0.001; \begin{document}$ {\chi ^2} $\end{document}_trend-LAeq=6.91, P=0.009; \begin{document}$ {\chi ^2} $\end{document}_{trend-kurtosis}=8.56, P=0.003). The results of logistic regression showed that age (OR=2.13, 95%CI: 1.67-2.71, P<0.001), sex (OR=2.29, 95%CI: 1.44-3.62, P<0.001), exposure duration (OR=1.43, 95%CI: 1.11-1.85, P=0.006), L_Aeq,8h (OR=1.37, 95%CI: 1.08~1.76, P=0.011), and kurtosis (OR=1.37, 95%CI: 1.14-1.63, P=0.001) were factors associated with the risk of HFNIHL, while only age was associated with the risk of SFNIHL (OR=2.15, 95%CI: 1.33-3.33, P=0.001). Conclusion Workers exposed to noise in automobile manufacturing industry are at a high risk of hearing loss. Age, sex, exposure duration, L_{Aeq,8 h}, and kurtosis are key influencing factors of hearing loss.

Background Equivalent continuous A-weighted sound pressure level is not appropriate for evaluating the risk of non-steady noise exposure, and need to be corrected by noise time-domain structure, but the correction method and its applicability need to be discussed. Objective To validate the application of the kurtosis-adjusted normalization of equivalent continuous A-weighted sound pressure level to a normal 8 h working day ( L_{Aeq,8 h}) in assessing noise-induced hearing loss (NIHL), and to improve the methods for assessing occupational hearing loss associated with different types of noise. Methods Audiometric and shift-long noise exposure data were acquired from a population(n=2 466) of screened workers exposed to noise between 70 dB(A) and 95 dB(A) from 6 industries in China. The cohort data were collapsed into 1 dB(A) bins, and the average kurtosis and noise-induced permanent threshold shifts at 3 kHz, 4 kHz, and 6 kHz (NIPTS₃₄₆) within 1 dB(A) were calculated respectively. According to the existing correction method, the adjustment coefficient λ was calculated by multiple regression, and L_{Aeq,8 h} was corrected by λ (L'_{Aeq,8 h}). The entire cohort was divided into K₁ (≤10; steady noise), K₂ (10~50; non-steady noise), and K₃ (＞50; non-steady noise) groups based on mean kurtosis levels. Predicted NIPTS₃₄₆ was calculated using the ISO 1999 model for each participant and the actual measured NIPTS₃₄₆ was corrected for age and gender. The underestimated NIPTS₃₄₆ was the difference between the values of estimated NIPTS₃₄₆ and the corresponding actual NIPTS₃₄₆. To validate the applicability of L′_{Aeq,8 h} in evaluating NIHL, the correlation between L′_{Aeq,8 h} and HFNIHL, and the mean difference between real NIPTS₃₄₆ and estimated NIPTS₃₄₆ were analyzed. Results The adjustment coefficient λ was determined at 5.43. The results of multiple logistic regression analysis showed that the relationship between L'_{Aeq,8 h} and HFNIHL increased from 6.6% to 9.6% after the kurtosis adjustment. The DRR of L_{Aeq,8 h} and HFNIHL showed that the percentage of HFNIHL decreased after the adjustment of kurtosis in the non-steady noise groups, and the regression lines of the non-steady noise groups approached that of the steady noise group. The R² of the K₂ group increased from 0.935 3 to 0.986 3, and the R ² of the K₃ group increased from 0.905 6 to 0.951 6. Under the un-adjusted condition, the NIPTS₃₄₆ underestimation for the K₃ group was significantly higher than that for the steady noise group (t=−3.23, P=0.001). After the L_{Aeq,8 h} was adjusted by kurtosis, the NIPTS₃₄₆ underestimation decreased significantly in the three kurtosis groups (K₁: t=6.78, P＜0.001; K₂: t=14.31, P＜0.001; K₃: t=11.06, P＜0.001). There was no significant difference in the degree of underestimation between the three kurtosis groups (K₁ vs K₂: t=−0.22, P=0.830; K₁ vs K₃: t=−1.40, P=0.205) as the curves of the three kurtosis groups were nearly overlapped. Conclusion The kurtosis-adjusted L_{Aeq,8 h} can effectively estimate the hearing loss associated with non-steady state noise.