Roger P. Hamernik, Ph.D. - US grants

Synergistic interactions among various ototraumatic agents have been shown to be of importance in determining the hearing loss in a number of industrial situations. The interactions between continuous and impulse noise and vibration and impulse noise will be studied using an experimental animal model (chinchilla). The rationale for these studies is that noise rarely exists as a sole hazard to hearing in many industrial and military work environments. Specific studies will include: (1) Long term combination noise exposures leading to a state of asymptotic threshold shift (ATS). The intensity and spectrum of both the impulse and bacground noise will be varied to provide a perspective on the noise parameters essential for the "interaction effect". (2) Using an ATS exposure paradigm, the influence of acceleration on the interaction of noise and vibration will be studied; and (3) Psychophysical tuning curves will be used to study changes in frequency selectivity resulting from some of the complex patterns of damage induced by the noise exposures. The final format of the data will include a comprehensive description of the noise exposure, a profile of the animal's hearing capability before and after the treatment and a detailed quantitative morphological analysis of the cochlea. Our problem for this research grant is to experimentally examine the factors that influence the interaction between vibration and various noise exposure paradigms. The potential for syngeristic interactions among the various physical agents is large, and for the most part unexplored. While standards cannot be developed to cover all situations, we should at least be cognizant of the various risks entailed under a variety of exposure conditions. The results will also provide some insights into the establishment of scientificatlly based noise exposure standards.

DESCRIPTION: (Adapted from Investigator's Abstract) Considering that many industrial and military noise environments are non-Gaussian, and that energy metrics (i.e., a weighted equivalent energy, Leq) commonly used to assess the adverse effects of a noise exposure on hearing are suitable metrics only for Gaussian noise, the investigator proposes to develop and test the validity of an alternate approach to noise analysis for the purpose of hearing conservation which will more precisely predict the audiometric and morphological consequences of an exposure. Specifically, the investigator will show that an energy metric in combination with the statistical metrics of frequency- and time-domain kurtosis and the joint peak-interval histogram will provide necessary (and possibly sufficient) information on essentially any industrial noise environment to evaluate its potential for causing hearing loss. Animals (chinchillas) will be exposed to non-Gaussian, non-stationary noises having the same energy and spectra of a Gaussian reference noise (two reference noise conditions will be used having spectral and level parameters typical of an industrial environment). Noise stimuli designed with very specific but diverse statistical properties will be produced using recently-designed software. New analytical methods developed in the investigator's laboratories over the past three years involving the wavelet transform and higher-order cumulant-based inverse filtering will be applied to the continuously sampled noise stimuli to extract temporal and peak statistical properties of the noise stimulus. Effects on hearing, quantified by pure-tone thresholds, otoacoustic emissions, and sensory cell losses will be correlated with the noise metrics to establish the validity of these metrics. Considering that the algorithms for the analytical methods mentioned above have been developed and can be integrated into commercial noise analysis systems, the successful outcome of these experiments can lay the foundations for a new and more generalized approach, as well as a more accurate approach to the evaluation of noise environments. The suggested analytical methods may also have some engineering applications in identifying features of the noise environment that can be reduced or altered at their source. It is important to understand what features of a noise are most hazardous to hearing in order that engineering procedures can be implemented on specific noise-producing components of machinery or designed into hearing protective devices. A database consisting of results from at least 408 subjects run through one of two control or 32 different complex noise exposure conditions will be constructed. A large sample size and a wide variation of exposure parameters are necessary to insure statistical power for the correlations that will be developed. While the experimental methods in this proposal are routine, the demonstration of good correlations between the proposed metrics and hearing loss following realistic and diverse exposure conditions has widespread implications for industrial safety standards and noise measurement systems.

DESCRIPTION (provided by applicant): Existing damage risk criteria for noise exposure are based entirely on an energy metric. Our animal model experiments have shown that energy alone is not sufficient to characterize a complex noise for hearing conservation purposes. These data suggest that energy and the statistical metric kurtosis may constitute necessary and sufficient metrics for the prediction of hearing loss that will result from long-term industrial exposures. This proposal is a continuation of this effort but focuses on the human condition. It is important to verify the animal results with comparable human exposure and hearing loss data. The main aim is to develop a noise measurement/analysis strategy that can be used to estimate the hearing loss that will develop in workers exposed to complex industrial noise* environments. Statistical learning models will be developed to achieve this goal. Model development will require that the following data be obtained: (1) Stable audiograms on a population of highly screened workers exposed to Gaussian and nonGaussian noise environments. (2) Record, archive and analyze the noise waveforms that each subject is exposed to over the course of an entire work shift. The models developed from this database will identify the noise variables that are important in the production of hearing loss and can also be used to develop exposure criteria. In addition, in response to ethical concerns of collecting data from unprotected workers, elements of a hearing conservation program will be introduced. The experimental paradigm will generate data needed for the development of an empirical basis for using in addition to an energy metric to predict the hazards of an exposure, variables that quantify the temporal and peak characteristics of a noise such as the kurtosis, impact interval and peak histograms, and transient durations. Data will be collected in collaboration with researchers at Peking University and include a population of at least 1,250 workers employed in various complex, high noise level industrial settings in China. This noise exposure and cross-sectional audiometric data will constitute a unique database that will fill a NIOSH acknowledged void in the data available for developing exposure criteria for hearing conservation purposes. [*Throughout this proposal our use of the term 'complex noise'refers to non-Gaussian noise, which in the course of a work cycle, may be intermittent, interrupted and of variable level. Non-Gaussian noise is very common in industry and the military where it consists of a background Gaussian noise with embedded high- level transients (impacts or noise bursts).] Existing safety criteria for noise exposure are based entirely on an energy metric. New data indicate that energy alone is not a suitable metric to use for this purpose. The main aim of this proposal is to develop a noise measurement/analysis strategy that can be used to estimate the hearing loss that will develop in workers exposed to complex industrial noise environments. Statistical learning models will be developed to achieve this goal.