Hearing Hazard Associated with Industrial Noise Exposure

描述（由申请人提供）：等能量假设（EEH）是我们目前噪音暴露标准的基础。EEH在许多工业环境中的应用严重低估了听力损失。在过去的两个资助周期中，我们一直在研究，在动物模型中，复杂噪声暴露的统计特性，体现在单数字度量，峰度，对听力的影响。峰度[(t)]定义为振幅分布的四阶中心矩与二阶矩的平方之比，已被证明在识别和量化复杂工业噪声环境对听力的危害方面很重要。早期工作的主要目的是开发一种测量噪音的方法，以预测长期工业暴露导致的听力损失。这一建议是这一努力的延续，有一个特定的目标：发展对定义复杂噪声的变量如何影响峰度固定值的听力损失的理解。在我们之前的工作中，我们改变了参数，如(i)峰值直方图和（ii）间隔直方图以及（iii）冲击噪声瞬态的持续时间，以便在恒定的能量下产生一个广泛的(t)范围，在这个范围内可以研究EEH和听力损伤。这项工作的延伸，也是在噪声评估和测量实践中建立使用(t)的指导方针所必需的，是了解上述三个“主要变量”[(i), （ii）和（iii）]如何在恒定(t)下影响听力创伤。考虑到对于给定的能量频谱分布，实际上有无数不同的噪声暴露可以具有相同的(t)，我们要问的问题是：为了估计长时间暴露造成的听力损失，我们需要了解多少关于定义复杂噪声的“主要变量”的信息，或者峰度是一个足够涵盖的度量？所有计划的暴露都将具有相同的能量，并将按照持续三周的理想工作周的一些基本特征进行结构设计。[长期暴露所产生的结果往往与短期急性暴露所产生的结果不同。暴露将是非澳大利亚的，断断续续的。对于峰度(t) = 10,25和50的三个值，我们将建立以下关系：(i)反映复杂噪声的基本统计特性的三个主要变量（峰值、间隔和影响持续时间直方图）；（ii）峰度；（三）由听力阈值和感觉细胞丧失确定的噪声性听力损失。这些结果将通过评估(t)对定义复杂噪声的主要变量的敏感性来补充前两个资助周期产生的结果。这些数据是将(t)应用于工业听力保护/噪声测量协议的必要先决条件。这些数据也将有助于我们继续评估、应用和理解EEH。项目简介：等能量假设（EEH）是我们目前噪音暴露标准的基础。EEH在许多工业环境中的应用严重低估了听力损失。本研究旨在开发一种新的噪声测量与评价策略。这将预测工业噪音造成听力损失的可能性。

DESCRIPTION (provided by applicant): The equal energy hypothesis (EEH) is the basis of our current noise exposure criteria. Application of the EEH in many industrial environments severely underestimates hearing loss. For the past two funding cycles we have been studying, in an animal model, the effects that the statistical properties of a complex noise exposure, as embodied in the single number metric, the kurtosis, have on hearing. The kurtosis [(t)], defined as the ratio of the fourth-order central moment to the squared second-order moment of the amplitude distribution, has been shown to be important in identifying and quantifying the hazard to hearing from complex industrial noise environments. The primary aim of the earlier work was to develop an approach to measuring noise that would predict the hearing loss that will result from long-term industrial exposures. This proposal, which is a continuation of this effort, has a single specific aim: To develop an understanding of how the variables that define a complex noise affect hearing loss for a fixed value of the kurtosis. In our previous work we varied parameters such as (i) the peak and (ii) interval histograms and (iii) duration of the impact noise transients in order to produce, at a constant energy, a broad range of (t) over which the EEH and hearing trauma could be studied. An extension of the work, and one that is necessary to establish guidelines for using (t) in noise assessment and measurement practice, is to understand how the above three `primary variables' [(i), (ii), and (iii)] affect hearing trauma at a constant (t). Considering that for a given spectral distribution of energy, there is virtually an infinite number of different noise exposures that can have the same (t), the question that we are asking is: In order to estimate hearing loss from prolonged exposure, to what extent do we need to know something about the `primary variables' that define the complex noise or is the kurtosis a sufficiently encompassing metric? All planned exposures will be of equal energy and will be structured to model some of the essential features of an idealized workweek lasting three weeks. [Long-term exposures often yield results that differ from those found from shorter acute exposures.] Exposures will be nonGaussian, interrupted and intermittent. For three values of the kurtosis, (t) = 10, 25 and 50, we will establish the relation among: (i) the three primary variables (peak, interval and impact duration histograms) that reflect the basic statistical properties of a complex noise; (ii) the kurtosis; and (iii) the noise-induced hearing loss as established by hearing thresholds and sensory cell loss. These results will complement the results generated over the previous two funding cycles by evaluating the sensitivity of (t) to the primary variables that define a complex noise. Such data is a necessary prerequisite to the application of (t) to industrial hearing conservation/noise measurement protocols. This data will also contribute to our continuing evaluation, application and understanding of the EEH. Project Narrative: The equal energy hypothesis (EEH) is the basis of our current noise exposure criteria. Application of the EEH in many industrial environments severely underestimates hearing loss. The proposed research is aimed at developing a new noise measurement and evaluation strategy. That will predict the potential of an industrial noise to produce hearing loss.