On the Need for an "Industry-Wide Standard" Definition of an Audiometric Notch and the Lack of Specificity of the Audiometric Notch in the Diagnosis of Noise-Induced Hearing Loss

Audiometric data analysis for prevention of noise-induced hearing loss: A new approach

Compliance with noise regulations in the past three decades has significantly reduced workplace noise exposures, particularly in the loudest industries and occupations. However, the overall effectiveness of hearing conservation programs in preventing occupational noise-induced hearing loss remains uncertain and unquantified, while the incidence and cost of occupational hearing loss remain inexplicably high. This review/commentary critically explores this paradox by examining why the billions of annual audiograms conducted worldwide have not been aggregately utilized or applied to predict early NIHL in groups of workers or to measure the efficacy of exposure controls. Principal contributory reasons include regulation of noise as a safety standard rather than as a health standard, the inherent complexity of audiometric data, and the lack of a standardized method of interpretation for audiograms. The unsuccessful history of efforts to develop and adopt methods and tools to analyze aggregate audiometric data is described. Consequently, the Standard Threshold Shift-a regulatorily defined, lagging indicator of individual, irreversible hearing loss that is not an effective preventive metric-remains the de facto standard of care. A population-based Best Practices approach is proposed to leverage the raw audiometric data already available and turn it into actionable data for effective secondary prevention to strategically manage and reduce occupational hearing loss risk. This approach entails statistical methods and information management tools necessary to transform audiometry from a compliance-driven, individual screening test with limited preventive capability into a medical surveillance process directly linked to aggregate corrective and prevention actions.

Association of self-reported noise exposure and audiograms processed with algorithms proposed to quantify noise-induced hearing loss

OBJECTIVE

The objective of this study was to assess the association of self-reported noise exposure and audiograms processed with ten algorithms proposed to quantify noise-induced hearing loss using receiver operating characteristic (ROC) curves.

DESIGN

Participants were placed into groups based on self-reported noise exposure. Self-reported noise exposure served as a predictor for noise-induced hearing loss (NIHL). Audiograms were analysed with ten algorithms: The Guidelines, Brewster's Rules, two versions of military Noise-induced Hearing Loss, the Bulge Depth, the age-adjusted 8 kHz threshold and four versions of a new algorithm called the Adjusted Notch Depth (AND). The area under the ROC curves were calculated for each algorithm.

STUDY SAMPLE

Data were collected from three cycles of the National Health and Nutrition Examination Survey.

RESULTS

Only one version the AND significantly identified those with self-reported noise exposure with an area under the curve of 0.562.

CONCLUSIONS

The association between the AND and self-reported noise exposure was marginally better than the previous algorithms in identifying those with self-reported noise exposure. These findings do not support using puretone thresholds for identifying those with NIHL in a cross-sectional research study without stratifying the participants. More research is needed to determine how the AND can be applied to stratified designs.

Audiometric Phenotypes of Noise-Induced Hearing Loss by Data-Driven Cluster Analysis and Their Relevant Characteristics

Background: The definition of notched audiogram for noise-induced hearing loss (NIHL) is presently based on clinical experience, but audiometric phenotypes of NIHL are highly heterogeneous. The data-driven clustering of subtypes could provide refined characteristics of NIHL, and help identify individuals with typical NIHL at diagnosis.

Methods: This cross-sectional study initially recruited 12,218 occupational noise-exposed employees aged 18–60 years from two factories of a shipyard in Eastern China. Of these, 10,307 subjects with no history of otological injurie or disease, family history of hearing loss, or history of ototoxic drug use were eventually enrolled. All these subjects completed health behavior questionnaires, cumulative noise exposure (CNE) measurement, and pure-tone audiometry. We did data-driven cluster analysis (k-means clustering) in subjects with hearing loss audiograms (n = 6,599) consist of two independent datasets (n = 4,461 and n = 2,138). Multinomial logistic regression was performed to analyze the relevant characteristics of subjects with different audiometric phenotypes compared to those subjects with normal hearing audiograms (n = 3,708).

Results: A total of 10,307 subjects (9,165 males [88.9%], mean age 34.5 [8.8] years, mean CNE 91.2 [22.7] dB[A]) were included, 3,708 (36.0%) of them had completely normal hearing, the other 6,599 (64.0%) with hearing loss audiograms were clustered into four audiometric phenotypes, which were replicable in two distinct datasets. We named the four clusters as the 4–6 kHz sharp-notched, 4–6 kHz flat-notched, 3–8 kHz notched, and 1–8 kHz notched audiogram. Among them, except for the 4–6 kHz flat-notched audiogram which was not significantly related to NIHL, the other three phenotypes with different relevant characteristics were strongly associated with noise exposure. In particular, the 4–6 kHz sharp-notched audiogram might be a typical subtype of NIHL.

Conclusions: By data-driven cluster analysis of the large-scale noise-exposed population, we identified three audiometric phenotypes associated with distinct NIHL subtypes. Data-driven sub-stratification of audiograms might eventually contribute to the precise diagnosis and treatment of NIHL.

Sex differences in noise-induced hearing loss: a cross-sectional study in China

BACKGROUND

Significant sex differences exist in hearing physiology, while few human studies have investigated sex differences in noise-induced hearing loss (NIHL), and the sex bias in previous studies resulted in inadequate female data. The study aims to investigate sex differences in the characteristics of NIHL to provide insight into sex-specific risk factors, prevention strategies and treatment for NIHL.

METHODS

This cross-sectional study included 2280 industrial noise-exposed shipyard workers (1140 males and 1140 females matched for age, job and employment length) in China. Individual noise exposure levels were measured to calculate the cumulative noise exposure (CNE), and an audiometric test was performed by an experienced technician in a soundproof booth. Sex differences in and influencing factors of low-frequency (LFHL) and high-frequency hearing loss (HFHL) were analyzed using logistic regression models stratified by age and CNE.

RESULTS

At comparable noise exposure levels and ages, the prevalence of HFHL was significantly higher in males (34.4%) than in females (13.8%), and males had a higher prevalence of HFHL (OR = 4.19, 95% CI 3.18 to 5.52) after adjusting for age, CNE, and other covariates. Sex differences were constant and highly remarkable among subjects aged 30 to 40 years and those with a CNE of 80 to 95 dB(A). Alcohol consumption might be a risk factor for HFHL in females (OR = 3.12, 95% CI 1.10 to 8.89).

CONCLUSIONS

This study indicates significant sex differences in NIHL. Males are at higher risk of HFHL than females despite equivalent noise exposure and age. The risk factors for NIHL might be different in males and females.