Applying Kurtosis as an Indirect Metric of Noise Temporal Structure in the Assessment of Hearing Loss Associated With Occupational Complex Noise Exposure

Abstract

Objective: The association of occupational noise-induced hearing loss (NIHL) with noise energy was well documented, but the relationship between occupational noise and noise temporal structure is rarely reported. The objective of this study was to investigate the principal characteristics of the relationship between occupational NIHL and the temporal structure of noise. Methods: Audiometric and shift-long noise exposure data were collected from 3102 Chinese manufacturing workers from six typical industries through a cross-sectional survey. In data analysis, A-weighted 8-h equivalent SPL ( L Aeq.8h ), peak SPL, and cumulative noise exposure (CNE) were used as noise energy indicators, while kurtosis (β) was used as the indicator of noise temporal structure. Two NIHL were defined: (1) high-frequency noise-induced hearing loss (HFNIHL) and (2) noise-induced permanent threshold shift at test frequencies of 3, 4, and 6 kHz (noise-induced permanent threshold shift [NIPTS 346 ]). The noise characteristics of different types of work and the relationship between these characteristics and the prevalence of NIHL were analyzed. Results: The noise waveform shape, with a specific noise kurtosis, was unique to each type of work. Approximately 27.92% of manufacturing workers suffered from HFNIHL, with a mean NIPTS 346 of 24.16 ± 14.13 dB HL. The Spearman correlation analysis showed that the kurtosis value was significantly correlated with the difference of peak SPL minus its L Aeq.8h across different types of work ( p < 0.01). For a kurtosis-adjusted CNE, the linear regression equation between HFNIHL% and CNE for complex noise almost overlapped with Gaussian noise. Binary logistic regression analysis showed that L Aeq.8h , kurtosis, and exposure duration were the key factors influencing HFNIHL% ( p < 0.01). The notching extent in NIPTS at 4 kHz became deeper with the increase in L Aeq.8h and kurtosis. HFNIHL% increased most rapidly during the first 10 years of exposure. HFNIHL% with β ≥ 10 was significantly higher than that with β < 10 ( p < 0.05), and it increased with increasing kurtosis across different CNE or L Aeq.8h levels. When L Aeq.8h was 80 to 85 dB(A), the HFNIHL% at β ≥ 100 was significantly higher than that at 10 ≤ β < 100 or β < 10 ( p < 0.05 and p < 0.01, respectively). Conclusions: In the evaluation of hearing loss caused by complex noise, not only noise energy but also the temporal structure of noise must be considered. Kurtosis of noise is an indirect metric that is sensitive ...

Assessment of Occupational Hearing Loss Associated With Non-Gaussian Noise Using the Kurtosis-Adjusted Cumulative Noise Exposure Metric: A Cross-Sectional Survey

“…The more impulsive the noise, the greater the kurtosis. Zhang et al (2021b) reported that kurtosis was significantly associated with the difference of peak SPL (L peak ) minus its L Aeq,8h across different types of work. The temporal structure of a non-Gaussian noise can be indirectly characterized by estimating the kurtosis.…”

“…They plotted the dose–response curve between CNE (CNE′) and NIHL prevalence and found that the curve of non-Gaussian noise almost overlapped that of Gaussian noise when using CNE′. Zhang et al (2021b) also plotted the dose–response curves and further calculated the differences in NIHL prevalence between the non-Gaussian noise group and Gaussian noise group; the authors found that after kurtosis adjustment, the average difference of NIHL prevalence significantly decreased from 7.63% to 1.12%. These findings suggested that CNE′ was able to consistently estimate the prevalence of hearing loss across varied noise environments using a single metric.…”

“…Temporal characteristics of noise waveform contain many elements such as the peak level, duration of an impulse, and inter-peak interval ( Zhang et al, 2021b ). Kurtosis ( β ) has been shown to incorporate these elements and can be used as a simple and feasible metric to indirectly reflect the temporal characteristics of noise ( Erdreich, 1986 ; Hamernik and Qiu, 2001 ; Hamernik et al, 2003 ).…”

Epidemiological characteristics of hearing loss associated with noise temporal structure among manufacturing workers

“…Nonetheless, many industrial noise environments are non-Gaussian noise (Zhou et al, 2020 ). Studies have revealed that complex noise exposure could cause a greater risk of NIHL than Gaussian noise (Zhao et al, 2010 ; Goley et al, 2011 ; Suter, 2017 ; Zhang et al, 2021b ). The energy metric of noise alone does not apply to the assessment of hearing loss caused by non-Gaussian noise in the workplace and the temporal metric of noise should be considered to be a supplemental indicator of NIHL assessment (Davis et al, 2009 , 2012 ; Seixas et al, 2012 ; Xie et al, 2016 ; Zhang et al, 2022 ).…”

“…Studies have indicated that the prevalence of NIHL increased with exposure duration, noise energy levels, sex, and age (Lie et al, 2014 ; Chen et al, 2019 ; Zhou et al, 2020 ; Zhang et al, 2021b ). A total of 24.4% of adults had an audiometric notch in the United States, this was more common among males than females (Carroll et al, 2017 ).…”