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Background: Complex noise and its relation to hearing loss are difficult to measure and evaluate. In complex noise measurement, individual exposure results may not accurately represent lifetime noise exposure. Thus, the mean L Aeq,8 h values of individuals in the same workgroup were also used to represent L Aeq,8 h in our study. Our study aimed to explore whether the mean exposure levels of workers in the same workgroup represented real noise exposure better than individual exposure levels did., Methods: A cross-sectional study was conducted to establish a model for cumulative noise exposure (CNE) and hearing loss in 205 occupational noise-exposed workers who were recruited from two large automobile manufacturers in China. We used a personal noise dosimeter and a questionnaire to determine the workers' occupational noise exposure levels and exposure times, respectively. A qualified audiologist used standardized audiometric procedures to assess hearing acuity after at least 16 h of noise avoidance., Results: We observed that 88.3% of workers were exposed to more than 85 dB(A) of occupational noise (mean: 89.3 ± 4.2 dB(A)). The personal CNE (CNEp) and workgroup CNE (CNEg) were 100.5 ± 4.7 dB(A) and 100.5 ± 2.9 dB(A), respectively. In the binary logistic regression analysis, we established a regression model with high-frequency hearing loss as the dependent variable and CNE as the independent variable. The Wald value was 5.014 with CNEp as the independent variable and 8.653 with CNEg as the independent variable. Furthermore, we found that the figure for CNEg was more similar to the stationary noise reference than CNEp was. The CNEg model was better than the CNEp model. In this circumstance, we can measure some subjects instead of the whole workgroup and save manpower., Conclusions: In a complex noise environment, the measurements of average noise exposure level of the workgroup can improve the accuracy and save manpower.

A series of Gaussian and non-Gaussian equal energy noise exposures were designed with the objective of establishing the extent to which the kurtosis statistic could be used to grade the severity of noise trauma produced by the exposures. Here, 225 chinchillas distributed in 29 groups, with 6 to 8 animals per group, were exposed at 97 dB SPL. The equal energy exposures were presented either continuously for 5 d or on an interrupted schedule for 19 d. The non-Gaussian noises all differed in the level of the kurtosis statistic or in the temporal structure of the noise, where the latter was defined by different peak, interval, and duration histograms of the impact noise transients embedded in the noise signal. Noise-induced trauma was estimated from auditory evoked potential hearing thresholds and surface preparation histology that quantified sensory cell loss. Results indicated that the equal energy hypothesis is a valid unifying principle for estimating the consequences of an exposure if and only if the equivalent energy exposures had the same kurtosis. Furthermore, for the same level of kurtosis the detailed temporal structure of an exposure does not have a strong effect on trauma.

This study examined: (1) the value of using the statistical metric, kurtosis [β(t)], along with an energy metric to determine the hazard to hearing from high level industrial noise environments, and (2) the accuracy of the International Standard Organization (ISO-1999:1990) model for median noise-induced permanent threshold shift (NIPTS) estimates with actual recent epidemiological data obtained on 240 highly screened workers exposed to high-level industrial noise in China. A cross-sectional approach was used in this study. Shift-long temporal waveforms of the noise that workers were exposed to for evaluation of noise exposures and audiometric threshold measures were obtained on all selected subjects. The subjects were exposed to only one occupational noise exposure without the use of hearing protection devices. The results suggest that: (1) the kurtosis metric is an important variable in determining the hazards to hearing posed by a high-level industrial noise environment for hearing conservation purposes, i.e., the kurtosis differentiated between the hazardous effects produced by Gaussian and non-Gaussian noise environments, (2) the ISO-1999 predictive model does not accurately estimate the degree of median NIPTS incurred to high level kurtosis industrial noise, and (3) the inherent large variability in NIPTS among subjects emphasize the need to develop and analyze a larger database of workers with well-documented exposures to better understand the effect of kurtosis on NIPTS incurred from high level industrial noise exposures. A better understanding of the role of the kurtosis metric may lead to its incorporation into a new generation of more predictive hearing risk assessment for occupational noise exposure.

Objective: Develop dose-response relations for two groups of industrial workers exposed to Gaussian or non-Gaussian (complex) types of continuous noises and to investigate what role, if any, the kurtosis statistic can play in the evaluation of industrial noise-induced hearing loss (NIHL)., Design: Audiometric and noise exposure data were acquired on a population (N = 195) of screened workers from a textile manufacturing plant and a metal fabrication facility located in Henan province of China. Thirty-two of the subjects were exposed to non-Gaussian (non-G) noise and 163 were exposed to a Gaussian (G) continuous noise. Each subject was given a general physical and an otologic examination. Hearing threshold levels (0.5-8.0 kHz) were age adjusted (ISI-1999) and the prevalence of NIHL at 3, 4, or 6 kHz was determined. The kurtosis metric, which is sensitive to the peak and temporal characteristics of a noise, was introduced into the calculation of the cumulative noise exposure metric. Using the prevalence of hearing loss and the cumulative noise exposure metric, a dose-response relation for the G and non-G noise-exposed groups was constructed., Results: An analysis of the noise environments in the two plants showed that the noise exposures in the textile plant were of a Gaussian type with an Leq(A)8hr that varied from 96 to 105 dB whereas the exposures in the metal fabrication facility with an Leq(A)8hr = 95 dB were of a non-G type containing high levels (up to 125 dB peak SPL) of impact noise. The kurtosis statistic was used to quantify the deviation of the non-G noise environment from the Gaussian. The dose-response relation for the non-G noise-exposed subjects showed a higher prevalence of hearing loss for a comparable cumulative noise exposure than did the G noise-exposed subjects. By introducing the kurtosis variable into the temporal component of the cumulative noise exposure calculation, the two dose-response curves could be made to overlap, essentially yielding an equivalent noise-induced effect for the two study groups., Conclusions: For the same exposure level, the prevalence of NIHL is greater in workers exposed to non-G noise environments than for workers exposed to G noise. The kurtosis metric may be a reasonable candidate for use in modifying exposure level calculations that are used to estimate the risk of NIHL from any type of noise exposure environment. However, studies involving a large number of workers with well-documented exposures are needed before a relation between a metric such as the kurtosis and the risk of hearing loss can be refined.

Objective: To highlight a selection of data that illustrate the need for better descriptors of complex industrial noise environments for use in the protection of hearing., Design: The data were derived using a chinchilla model. All noise exposures had the same total energy and the same spectrum; that is, they were equal energy exposures presented at an overall 100 dB(A) SPL that differed only in the scheduling of the exposure and the value of the kurtosis, beta(t), a statistical metric. Hearing thresholds were determined before and after noise exposure using the auditory-evoked potential measured from the inferior colliculus in the brain stem. Cochlear damage was estimated from sensory-cell counts (cochleograms)., Results: (1) For equivalent energy and spectra, exposure to a high-kurtosis, non-Gaussian noise produced substantially greater hearing and sensory-cell loss in the chinchilla model than a low-kurtosis, Gaussian noise. (2) beta(t) computed on the amplitude distribution of the noise could clearly differentiate between the effects of Gaussian and non-Gaussian noise environments. (3) beta(t) can order the extent of the trauma as determined by hearing thresholds and sensory-cell loss., Conclusions: The noise level in combination with the statistical properties of the noise quantified by beta(t) clearly differentiate the effects between both continuous and interrupted and intermittent Gaussian and non-Gaussian noise environments. For the same energy and spectrum, the non-Gaussian environments are clearly the more hazardous. The use of both an energy and kurtosis metric can better predict the hazard of a high-level complex noise than the use of an energy metric alone (as is the current practice). These results point out the need for a new approach to the analysis and quantification of industrial noise for the purpose of hearing conservation practice.