Complex noise is widespread in industrial environments, and its pronounced temporal impulsiveness leads to a systematic underestimation of hazard under equal-energy exposure. Recent studies have incorporated time-domain kurtosis (hereafter "kurtosis", β) into exposure characterization as a critical complement to energy metrics, clearly revealing the additional risk of noise-induced hearing loss attributable to temporal structure; accordingly, the evaluation paradigm is shifting from “noise energy” to “noise energy + noise temporal characteristics (kurtosis).” Evidence from epidemiology and animal experiments consistently shows that using kurtosis-adjusted equivalent sound level or cumulative exposure yields a more consistent dose-response across different noise types and markedly reduces the underestimation bias of ISO 1999 in high-kurtosis environments. In practice, we recommend full-shift waveform acquisition, calculating kurtosis in 1-minute windows, and using the geometric mean to obtain an overall full-shift kurtosis; alternatively, a segmented adjustment can be applied to derive a kurtosis-adjusted equivalent sound level for risk-based decision-making and task stratification. At the standards and policy level, ISO 1999 revision efforts have placed temporal structure/kurtosis on the agenda and proposed additional corrections for impact/impulsive noise; meanwhile, the evidence indicates that as β increases, permissible exposure limits should be reduced more conservatively and monitoring strengthened. This article advocates systematically embedding a kurtosis-adjusted evaluation framework in regulations/guidelines, accompanied by measurement technical specifications, quality control and harmonized algorithms, and industry pilots and training, with phased management provisions based on kurtosis thresholds, thereby advancing hearing protection from “quantity” to “quality.”

Objective To explore the application value of distortion product otoacoustic emission (DPOAE) and speech in noise(SIN) testing in occupational health surveillance of noise-exposed workers. Methods A total of 220 noise-exposed workers was selected as the study subjects using the convenient sampling method. The study subjects participated questionnaire survey, personal noise exposure assessment, acoustic immittance testing, pure tone audiometry (PTA), DPOAE and SIN testing. According to PTA results, workers were enrolled into a high-frequency hearing loss (HFHL) group and a non-HFHL group. Results The detection rate of HFHL among the study subjects was 41.4%, and the detection rate of speech-frequency hearing loss was 15.9%. Workers′ bilateral DPOAE response amplitudes and signal-to-noise ratios at frequencies of 2.0-8.0 kHz in the HFHL group were lower than those in the non-HFHL group (all P<0.05). The DPOAE amplitudes at frequencies of 1.0-8.0 kHz in both ears of the study subjects were negatively correlated with the PTA threshold (all P<0.01), and were negatively correlated with age (all P<0.01). The signal-to-noise ratio loss score was higher among worker in the HFHL group than in the non-HFHL group (P<0.01) and was positively correlated with PTA thresholds (P<0.05). Conclusion DPOAE and SIN testing can detect early cochlear outer hair cell impairment and reduction of noise-related speech recognition ability in noise-exposed workers and may serve as an effective supplementary tool to routine PTA in occupational hearing surveillance.

Objective:To explore the structural equation model to explore the levels of work-related musculoskeletal disorders (WMSDs) and various risk factors in the feet and ankle of China's occupational population, providing scientific basis for for preventing WMSDs in feet and ankles.Methods:Data of 73497 national occupational epidemiological cases were selected from June 2018 to December 2023 used the Chinese version of the Electronic Questionnaire on Musculoskeletal Disorders. The adverse ergonomic factors and their source classification standard and confirmatory factor analysis were used to investigate foot and ankle WMSDs and their related risk factors (including individual factors, work organization, work posture, work type, fatigue, etc.) in key occupational groups in China, and structural equation model hypothesis, fitting, verification, and path and intermediary effect analysis were carried out. The model fit evaluation indexes included Chi-square specific degrees of freedom ( χ2/ df), gauge fit index (NFI), Tucker Lewis index (TLI), goodness of Fit index (GFI), adjusted Goodness of Fit index (AGFI) and approximate root mean square error (RMSEA) . Results:A total of 73497 occupational workers were surveyed, with local muscle fatigue and WMSDs incidence rates in the feet and ankles being 17.17% and 12.06%, respectively. The fitting index of the adjusted structural equation model basically meets the standard (GFI=1, AGFI=1, RMESA=0.042, NFI=0.716, TLI=0.663). The top three factors affecting feet and ankle WMSDs are feet and ankle muscle fatigue, work type, and work organization, with standardized path coefficients of 0.221, 0.105, and 0.095, respectively. The top two factors affecting feet and ankle muscle fatigue are work organization and work type, with standardized path coefficients of 0.548 and 0.383, respectively. Feet and ankle muscle fatigue, work type, work organization, and work posture have a direct effect on feet and ankle WMSDs, with effect values of 0.221, 0.105, 0.095, and 0.077, respectively. The organization and type of work can also have indirect effects through feet and ankle muscle fatigue, with effect values of 0.121 and 0.084, respectively.Conclusion:Feet and ankle muscle fatigue has a direct impact on WMSDs, and plays a mediating role between ankle and ankle WMSDs caused by work organization and work type. Feet and ankle muscle fatigue is an important pathway leading to feet and ankle WMSDs. It is recommended that employers and managers detect job fatigue early and take corresponding prevention and intervention measures, which can play a key role in preventing feet and ankle WMSDs.

Objective:To explore the structural relationship between WMSDs in the upper limbs and various risk factors in the occupational population in China, based on a large sample epidemiological survey and structural equation analysis, and to establish a structural equation model, so as to lay a foundation for the prevention and control of such diseases.Methods:The Chinese version of the Musculoskeletal Disorders Electronic Questionnaire was used to conduct a nationwide survey on the prevalence of WMSDs in the upper extremity. Six factors related to WMSDs in the upper extremity were extracted by the classification standard of adverse ergonomic factors and their source and confirmatory factor analysis, including work organization, work type, upper extremity work posture, individual factors, upper extremity fatigue and upper extremity WMSDs. The structural equation analysis was carried out and the structural equation model was established.Results:The incidence of WMSDs and fatigue in the upper limbs was 24.44% and 43.76%, respectively. The adjusted structural equation model fitting indicators were generally up to the standard (GFI=1.000, AGFI=1.000, RMSEA=0.043, NFI=0.808, TLI=0.784) . The four exogenous latent variables of work organization, work type, upper limb work posture and individual factors were correlated. There was a strong positive correlation between job type and upper limb work posture ( r=0.865) , a moderate positive correlation between work organization and job type and upper limb work posture ( r=0.570, 0.490) , and a weak negative correlation between individual factors and the other three exogenous latent variables. Upper limb work posture and individual factors had direct effects on upper limb WMSDs, and the effect coefficients were 0.10 and 0.06, respectively. Upper limb fatigue played a mediating role between work organization, work type, upper limb work posture and upper limb WMSDs. The effect coefficient was 0.46, and the composition ratios of indirect effects were 100.0%, 100.0%, and 38.3%, respectively. The direct path effect of upper limb work posture, individual factors and upper limb WMSDs was weaker than the mediating path through upper limb fatigue. Conclusion:When carrying out the prevention and control of upper limbWMSDs, it is necessary to comprehensively consider the pathogenesis path of upper limb muscle fatigue and upper limb WMSDs caused by work organization, work type, and upper limb work posture, so as to provide theoretical reference for improving the prevention and control level of such diseases.

Occupational noise-induced hearing loss (ONIHL) is a global public health problem; occupational noise deafness is the second most prevalent occupational disease in China. A China-contextualized ONIHL prevention and control system has not yet established. In this issue, the column "Noise kurtosis adjustment and prevention and control of occupational hearing loss" introduced a preliminary study on developing a statistical distribution table of hearing threshold deviation values for otologically normal Chinese population, revealed the role of C-weighted kurtosis in assessing occupational hearing loss, and put forward the effect threshold of kurtosis for occupational hearing loss caused by non-steady noise. The adjustment terms and adjustment coefficients of the kurtosis-adjusted equivalent sound level estimated by nonlinear regression were explored, and the research progress on epidemiological characteristics of ONIHL based on temporal structure (kurtosis), theoretical research, and key technologies for prevention and control and their applications in China were outlined. Research suggestions were proposed regarding theoretical research, mechanism research, technology creation, cohort study, and standard formulation and revision.

Background Kurtosis reflecting noise's temporal structure is an effective metric for evaluating noise-induced hearing loss (NIHL), and its threshold is still unclear. Objective To explore the energy range of kurtosis and the threshold of NIHL induced by kurtosis in this energy rangeMethods Using cross-sectional design, 4631 noise-exposed workers in manufacturing industry were selected. The hearing loss and noise exposure data of each worker were collected. Logistic regression model was used to establish the dose-response relationship between noise exposure and hearing loss and estimate the range of energy effects. Restricted cubic spline model was utilized to analyze the dose-response relationship curves of kurtosis to noise-induced hearing loss (NIHI) and high-frequency noise-induced hearing loss (HFNIHL) under different 8 h equivalent sound levels (L_{EX,8 h}), as well as to estimate the kurtosis effect threshold. Results The logistic regression model analysis showed that the prevalence of NIHI and HFNIHL increased significantly with increase of L_{EX,8 h} for steady noise; when L_{EX,8 h} of non-steady noise was 80-100 dB(A), the risk of hearing loss increased with an increase in kurtosis (P<0.05). The restricted cubic spline model showed that when L_{EX,8 h} of non-steady noise was 0-80 dB(A) or >100 dB(A), there was no significant relationship between kurtosis and NIHI or HFNIHL. When L_{EX,8 h} was 80-100 dB(A), there was a significant nonlinear dose-response relationship between kurtosis and NIHL or HFNIHL (P <0.001), and kurtosis > 28.08 exerted effect in elevating NIHI or HFNIHL. Conclusion The effect threshold of kurtosis on NIHL is 28.08 when non-steady noise levels are in the range of 80-100 dB(A). The effect threshold of kurtosis needs further verification.

Background Noise-induced hearing loss (NIHL) is a prevalent occupational health problem in workplace settings, with non-steady noise exposure being particularly widespread. Although kurtosis-adjusted equivalent sound level (\begin{document}$ {{L'}}_{\text{EX,}\text{8}\text{ h}} $\end{document}) methods based on linear regression are available to assess hearing damage, the complexity of kurtosis effects necessitates introducing new metrics through nonlinear regression to improve predictive accuracy for hearing loss from non-steady noise exposure. Objective To examine the adjustment terms [\begin{document}$ \mathrm{lg}(\beta _{N}/{\beta }_{G}) $\end{document}] and coefficients (λ) of \begin{document}$ {{L'}}_{\text{EX,}\text{8}\text{ h}} $\end{document} using nonlinear regression and evaluate the method’s effectiveness in assessing occupational hearing loss associated with non-steady noise exposure. Methods A cross-sectional study design was employed, enrolling 1034 manufacturing workers and evaluating noise exposure to estimate hearing loss metrics. Quantile regression analysis quantified the proportional contributions of influencing factors for noise-induced permanent threshold shift at 3, 4, and 6 kHz frequencies (NIPTS₃₄₆). \begin{document}$ {{L'}}_{\text{EX,}\text{8}\text{ h}} $\end{document} was computed using multiple linear regression and nonlinear least squares optimization. Paired t-tests analyzed predictive efficacy before and after kurtosis adjustment to evaluate its impact on ISO 1999 NIPTS₃₄₆ predictions. Chow tests compared the similarity of logistic regression curves for high-frequency noise-induced hearing loss (HFNIHL) incidence between non-steady noise (\begin{document}$ {{L'}}_{\text{EX,}\text{8}\text{ h}} $\end{document}) and steady noise (\begin{document}$ {{L}}_{\text{EX,}\text{8}\text{ h}} $\end{document}), thereby validating the effectiveness of \begin{document}$ {{L'}}_{\text{EX,}\text{8}\text{ h}} $\end{document}. Results The quantile regression analysis showed that kurtosis was a significant indicator of occupational hearing loss risk from non-steady noise (contribution rate was 27.5%, P<0.05). The linear regression and nonlinear least squares methods obtained six different combinations of coefficients (λ) and adjustment terms [\begin{document}$ \mathrm{lg}(\beta _{N}/{\beta }_{G}) $\end{document}]. Incorporating these \begin{document}$ {{L'}}_{\text{EX,}\text{8}\text{ h}} $\end{document} adjustments into the ISO 1999 predictive model significantly reduced NIPTS underestimation (from 14.2 dB HL with \begin{document}$ {{L}}_{\text{EX,}\text{8}\text{ h}} $\end{document} to 11.5–5.6 dB HL with \begin{document}$ {{L'}}_{\text{EX,}\text{8}\text{ h}} $\end{document}, P < 0.001). The model \begin{document}$ {{{L'}}_{\text{EX,}\text{8}\text{ h}\text{,6}}=L}_{\mathrm{E}\mathrm{X},8\;\mathrm{h}}+7.9\mathrm{lg}({{\beta }_{N}}/{10}) $\end{document} achieved the most significant improvement, reducing underestimation by 8.7 dB HL. The logistic curve analysis further demonstrated that all \begin{document}$ {{L'}}_{\text{EX,}\text{8}\text{ h}} $\end{document} dose-response relationships for non-steady noise aligned more closely with the steady noise group than \begin{document}$ {{L}}_{\text{EX,}\text{8}\text{ h}} $\end{document}, with \begin{document}$ {{L'}}_{\text{EX,}\text{8}\text{ h}\text{,6}} $\end{document} showing the smallest divergence (difference: 4.1%). Conclusions \begin{document}$ {{L'}}_{\text{EX,}\text{8}\text{ h}} $\end{document} demonstrates superior efficacy in assessing the risk of occupational hearing loss induced by non-steady noise exposure. The \begin{document}$ {{L'}}_{\text{EX,}\text{8}\text{ h}} $\end{document} metric, constructed by calculating adjustment terms and coefficients through nonlinear regression analysis, exhibits greater effectiveness than linear regression methods in evaluating occupational hearing loss associated with non-steady noise exposure.

Background Temporal kurtosis (without frequency weighting, i.e., Z-weighted kurtosis) can evaluate noise-induced hearing loss (NIHL). However, few studies have considered the function of frequency weighting (A- or C-weighted) kurtosis on NIHL. Objective To study the significance of A- and C-weighted kurtosis adjustment for equivalent sound level (L'_{EX,8 h}) in evaluating occupational hearing loss. Methods A cross-sectional survey was used to select 973 noise-exposed workers in seven industries as the subjects. The noise exposure of all workers was assessed by distributions of A-, C-, and Z-weighted kurtosis (e.g., K_A, K_C, and K_Z) and respective adjusted equivalent sound level (e.g., L'_{EX,8 h}-K_A, L'_{EX,8 h}-K_C, and L'_{EX,8 h}-K_Z). The significance of A- and C-weighted kurtosis in evaluating NIHL was evaluated by correlations between three types of L'_{EX,8 h} and NIHL, and improvement of noise-induced permanent threshold shift (NIPTS) underestimation predicted by the ISO prediction model (Acoustics—Estimation of noise-induced hearing loss, ISO 1999-2013). Results The median K_A, K_C, and K_Z were 68.33, 28.22, and 19.82, respectively. The binary logistic regression showed that L_{EX, 8 h}-K_A, L_{EX, 8 h}-K_C, and L'_{EX, 8 h}-K_Z were risk factors for NIHL (OR>1, P<0.001). The receiver operating characteristic (ROC) curve showed that when the outcome variable was noise-induced hearing impairment (NIHI), the areas under the curves corresponding to L'_{EX,8 h}-K_A, L'_{EX,8 h}-K_C, and L'_{EX,8 h}-K_Z were 0.625, 0.628, and 0.625, respectively. When the outcome variable was high-frequency noise-induced hearing loss (HFNIHL), the areas under the curves corresponding to L'_{EX,8 h}-K_A, L'_{EX, 8 h}-K_C, and L'_{EX,8 h}-K_Z were 0.624, 0.623, and 0.622, respectively (P<0.05). The order of underestimation improvement values predicted by L'_{EX,8 h} for NIPTS₁₂₃₄ was: L'_{EX,8 h}-K_A (4.68 dB HL)>L'_{EX,8 h}-K_C (4.38 dB HL)>L'_{EX,8 h}-K_Z (4.28 dB HL) (P<0.001). The order of underestimation improvement values predicted by L'_{EX,8 h}-K for NIPTS₃₄₆ was: L'_{EX,8 h}-K_A (7.20 dB HL)>L'_{EX,8 h}-K_C (6.83 dB HL)>L'_{EX,8 h}-K_Z (6.71 dB HL) (P<0.001). Conclusion The adjustment of A- and C-weighted kurtosis to equivalent sound level L_{EX,8 h} can effectively improve the accuracy of the ISO 1999 prediction model in NIPTS prediction, and compared with the C-weighted, the A-weighted kurtosis can improve the result of the ISO 1999 prediction model in terms of underestimating NIPTS.

background Current assessment of noise-induced hearing loss relies on the hearing threshold statistical distribution table of ISO 7029-2017 standard (ISO 7029), which is based on foreign population data and lacks a hearing threshold distribution table derived from pure-tone audiometry data of the Chinese population, hindering accurate evaluation of hearing loss in this group. Objective To establish a statistical distribution table of hearing threshold level (HTL) for otologically normal Chinese adults and to provide a scientific basis for revising the diagnostic criteria of occupational noise-induced deafness in China. Methods A total of 1271 otologically normal Chinese adults aged 18-60 years were divided into four groups with 10-year age intervals. Based on the pure tone audiometry data and power function operation formula, the relevant parameters of the median and percentile calculation formula of ISO 7029 were adjusted. Based on the adjusted parameters, a statistical distribution table of HTL of normal Chinese adults in otology was preliminarily constructed according to the calculation formula of ISO 7029. A nonparametric rank sum test was used to compare the difference between the adjusted median deviation value and the ISO 7029 calculation. Results Except for a few frequencies (2000, 3000, and 8000 Hz), the value of parameter α adjusted for the auditory threshold deviation of the Chinese population (α_CHN-md) increased with the increase of frequency, while the value of parameter β adjusted for the auditory threshold deviation of the Chinese population (β_CHN-md) decreased with the increase of frequency. The preliminary distribution table of otologically normal Chinese adults' median hearing threshold deviation (ΔH_CHN-md) showed that the hearing threshold deviation increased with age and frequency. At 8000 Hz, the increase in ΔH_CHN-md with age was the greatest for both men and women, from 0 dB to 23 dB and 21 dB respectively. The minimal threshold elevation was noted at 500, 1000, and 2000 Hz, which increased from 0 dB to 2 dB. In otologically normal Chinese adults, the maximum increase of ΔH_CHN-md with frequency was observed at age of 50 years, which increased from 2 dB at 500 Hz to 23 dB at 8000 Hz in men and from 2 dB at 500 Hz to 21 dB at 8000 Hz in women. The comparison results with the ISO 7029 calculation showed that the trend was consistent. The median hearing threshold deviation value of the adjusted Chinese population was lower than that of the ISO 7029 calculation (ΔH_md). However, they had no significant statistical difference (P>0.05). For otologically normal normal Chinese men and women, the maximum difference of ΔH_md between the 50-year-old group and the ISO calculation at 8000 Hz was 7 dB and 9 dB, respectively. Conclusion This preliminary analysis of hearing threshold deviations in otologically normal Chinese adults suggests that current standards may potentially underestimate hearing loss at frequencies below 8000 Hz while possibly overestimating it at 8000 Hz. These findings require further validation through expanded sample sizes to more accurately assess the characteristics of hearing thresholds in the Chinese population and their discrepancies with existing standards.

Objective:To explore the structural equation model to explore the levels of work-related musculoskeletal disorders (WMSDs) and various risk factors in the feet and ankle of China's occupational population, providing scientific basis for for preventing WMSDs in feet and ankles.Methods:Data of 73497 national occupational epidemiological cases were selected from June 2018 to December 2023 used the Chinese version of the Electronic Questionnaire on Musculoskeletal Disorders. The adverse ergonomic factors and their source classification standard and confirmatory factor analysis were used to investigate foot and ankle WMSDs and their related risk factors (including individual factors, work organization, work posture, work type, fatigue, etc.) in key occupational groups in China, and structural equation model hypothesis, fitting, verification, and path and intermediary effect analysis were carried out. The model fit evaluation indexes included Chi-square specific degrees of freedom ( χ2/ df), gauge fit index (NFI), Tucker Lewis index (TLI), goodness of Fit index (GFI), adjusted Goodness of Fit index (AGFI) and approximate root mean square error (RMSEA) . Results:A total of 73497 occupational workers were surveyed, with local muscle fatigue and WMSDs incidence rates in the feet and ankles being 17.17% and 12.06%, respectively. The fitting index of the adjusted structural equation model basically meets the standard (GFI=1, AGFI=1, RMESA=0.042, NFI=0.716, TLI=0.663). The top three factors affecting feet and ankle WMSDs are feet and ankle muscle fatigue, work type, and work organization, with standardized path coefficients of 0.221, 0.105, and 0.095, respectively. The top two factors affecting feet and ankle muscle fatigue are work organization and work type, with standardized path coefficients of 0.548 and 0.383, respectively. Feet and ankle muscle fatigue, work type, work organization, and work posture have a direct effect on feet and ankle WMSDs, with effect values of 0.221, 0.105, 0.095, and 0.077, respectively. The organization and type of work can also have indirect effects through feet and ankle muscle fatigue, with effect values of 0.121 and 0.084, respectively.Conclusion:Feet and ankle muscle fatigue has a direct impact on WMSDs, and plays a mediating role between ankle and ankle WMSDs caused by work organization and work type. Feet and ankle muscle fatigue is an important pathway leading to feet and ankle WMSDs. It is recommended that employers and managers detect job fatigue early and take corresponding prevention and intervention measures, which can play a key role in preventing feet and ankle WMSDs.