|
Purpose: The objective of the current study was to describe outcomes on physiological and perceptual measures of auditory function in human listeners with and without a history of recreational firearm noise exposure related to hunting. Design: This study assessed the effects of hunting-related recreational firearm noise exposure on audiometric thresholds, oto-acoustic emissions (OAEs), brainstem neural representation of fundamental frequency (F0) in frequency following responses (FFRs), tonal middle-ear muscle reflex (MEMR) thresholds, and behavioral tests of auditory processing in 20 young adults with normal hearing sensitivity. Results: Performance on both physiological (FFR, MEMR) and perceptual (behavioral auditory processing tests) measures of auditory function were largely similar across participants, regardless of hunting-related recreational noise exposure. On both behavioral and neural measures including different listening conditions, performance degraded as difficulty of listening condition increased for both nonhunter and hunter participants. A right-ear advantage was observed in tests of dichotic listening for both nonhunter and hunter participants. Conclusion: The null results in the current study could reflect an absence of cochlear synaptopathy in the participating cohort, variability related to participant characteristics and/or test protocols, or an insensitivity of the selected physiological and behavioral auditory measures to noise-induced synaptopathy.
Keywords: auditory processing, Cochlear synaptopathy, frequency following response, middle-ear muscle reflex, recreational firearm noise exposure
How to cite this article:
Ananthakrishnan S, McElree C, Martin L. Physiological and perceptual auditory consequences of hunting-related recreational firearm noise exposure in young adults with normal hearing sensitivity. Noise Health 2023;25:8-35 |
How to cite this URL:
Ananthakrishnan S, McElree C, Martin L. Physiological and perceptual auditory consequences of hunting-related recreational firearm noise exposure in young adults with normal hearing sensitivity. Noise Health [serial online] 2023 [cited 2023 Sep 27];25:8-35. Available from: https://www.noiseandhealth.org/text.asp?2023/25/116/8/372594 |
| Introduction | |  |
Continuous and high levels of noise exposure can cause metabolic reactions and mechanical damage in cochlear structures[1],[2],[3],[4] that can result in a range of short- and long-term auditory health consequences in human listeners.[1] Such auditory consequences include temporary threshold shifts,[5],[6] permanent threshold shifts,[5],[6],[7],[8],[9] tinnitus,[10],[11],[12],[13],[14],[15] and suprathreshold speech perception deficits in human listeners.[16] Noise exposure can occur at the workplace, during recreational pursuits, and from environmental sources. The detrimental effects of noise exposure have typically been considered in the context of occupational noise exposure, with federal agencies (e.g., Occupational Safety and Health Administration [OSHA])[17] developing and implementing strict guidelines to regulate workplace noise exposure. However, a number of recreational activities are also associated with excessive noise levels, including but not limited to hunting, concerts, motorsports, and use of personal audio systems (for detailed reviews, see Keppler et al.,[3] Meinke et al.,[4] Neitzel & Fligor[18]). Firearm exposure during noisy recreational activities poses the greatest risk for permanent hearing loss.[19] In recent years, a growing body of research has focused on various aspects related to recreational firearm use, including demographics and statistics related to firearm users, acoustic parameters that define the noise from firearm discharge, auditory risks from firearm exposure, pathological changes to the auditory system following firearm exposure and their audiological manifestations, and types and use of hearing protection among firearm users (see Meinke et al.[4] for a detailed review).
Firearm use is common during recreational pursuits such as hunting, target shooting, reenactment of historical events, and scouting.[4] Per the Small Arms Survey,[20] close to 857 million firearms are owned by civilians around the world, with 120.5 firearms per 100 civilians in the United States. Survey data querying reasons for firearm ownership in the United States from 1972 to 2010 have shown that hunting is one of the primary motivations for owning a firearm.[21] Based on the 2016 National Survey of Fishing, Hunting, and Wildlife-Associated Recreation conducted by the US Fish and Wildlife Services,[22] 8% of males and 1% of females above the age of 16 years engaged in hunting in 2016 in the United States. A total of 11.5 million individuals reported hunting, of which 90% were males and 10% were females. Additionally, the survey estimated that 1.4 million 6- to 15 year olds in the United States engaged in hunting. More recently, the National Hunting License Data released by the United States Fish & Wildlife Service[23] reported as many as 15.2 million paid hunting license owners in the United States in 2021.
When considering recreational pastimes involving firearm use, hunting, specifically waterfowl hunting, demonstrates the most significant risk for noise-induced hearing loss (NIHL).[24] Firearm discharge results in brief duration, high-frequency impulse sounds with maximum sound pressure level (SPL) values ranging from 140 to 175 dB; most recreational firearms produce peak SPLs between 150 and 165 dB (see Meinke et al.[4] for a detailed review). Currently, noise generated by recreational firearms is not subject to any federal regulations. However, the maximum SPLs associated with these devices consistently exceed the international standards for safe listening at venues and events (100 dB SPL) recommended by the World Health Organization (WHO),[25] and workplace noise exposure limits mandated by OSHA[17] and the National Institute for Occupational Safety & Health (NIOSH)[26] (140 dB SPL). Further, the auditory system can sustain greater damage from impulse noise as compared to continuous noise, recovery from which may be only partial and require an extended time.[27],[28],[29],[30] Meinke et al.[4] also provide a detailed review of the characteristic auditory outcomes of recreational firearm noise exposure, which include bilateral asymmetric permanent high-frequency hearing loss[31],[32],[33],[34],[35],[36],[37] and tinnitus.[38],[39],[40] Impulse noise can also result in temporary threshold shifts (TTS).[41] Modeling data based on TTS measured 2 minutes following impulse noise exposure in chinchilla auditory brainstem responses predict a 43-hour recovery period for a 25 dB TTS increasing to a 38-day recovery period for a 50 dB TTS in human listeners.[27]
Although hearing may ostensibly recover when the TTS recovers, evidence from animal physiology studies accrued over the past decade suggests this might not always be the case. In their seminal 2009 paper, Kujawa & Liberman[42] demonstrated that mice exposed to short durations of continuous noise experienced and recovered from a TTS with no damage to cochlear outer hair cells (OHCs), but presented with a permanent and significant loss of synapses between inner hair cells and their innervating auditory nerve fibers (“cochlear synaptopathy”). Kujawa and Liberman’s mouse data have subsequently been replicated in several animal studies (see Kobel et al.[43] & Hickman et al.[44] for detailed reviews). Such synaptopathic changes have been noted following impulse noise exposure as well.[44] It is thought that such noise-induced cochlear synaptopathy has the potential to cause deficits in suprathreshold auditory processing in human listeners.[16] Whether cochlear synaptopathy occurs in noise-exposed human listeners and can account for any auditory perceptual deficits in this population is a matter of much debate with mixed findings reported in the literature.[45],[46],[47],[48],[49],[50],[51],[52],[53],[54],[55],[56],[57],[58],[59],[60] A significant challenge associated with identifying cochlear synaptopathy in human listeners is that it has minimal-to-no effect on auditory thresholds, and is hence not observed on the gold standard of hearing testing, the audiogram. Direct verification of cochlear synaptopathy can only occur through an evaluation of synaptic ribbon count during postmortem analysis of the temporal bone. However, several noninvasive physiological measurements of the auditory system, such as the auditory brainstem response (ABR) wave I amplitude, the middle-ear muscle reflex (MEMR), and the frequency following response (FFR) have emerged as potential indirect measures of cochlear synaptopathy in human listeners. These physiological measurements have been compared with self-reported noise exposure and/or performance on suprathreshold perceptual tasks such as amplitude modulation (AM) detection, word recognition scores in quiet and background noise, speech identification in noise, and time-compressed speech recognition (for a detailed review, see Bramhall et al.[61]).
As reductions in ABR wave I amplitudes have been observed in animals with decreased synaptic ribbon count consequent to short-term noise exposure,[42],[62],[63] the majority of studies in human listeners have also utilized the ABR wave I amplitude as an indirect metric of noise-induced synaptopathy.[46],[47],[48],[49],[50],[51],[52],[53],[54],[55],[56],[57],[58],[59] However, changes in ABR wave I amplitude could arise from inner hair cell or auditory nerve damage that may be independent of synaptic count and function[65]; they could also reflect a steepened ABR wave I amplitude-intensity function due to OHC loss.[66] Further, ABR wave I is primarily generated by auditory nerve fibers with low thresholds and high spontaneous rate.[67] On the other hand, it is the low spontaneous rate/high threshold auditory nerve fibers that have been implicated in synaptopathic animals. For these reasons, Bramhall et al.[65] argue that ABR wave I amplitude may not be index of choice for identifying synaptopathy in human listeners.
The acoustic middle-ear muscle response (MEMR) refers to a reflexive contraction of the stapedius muscle in response to a high-intensity signal, which decreases the compliance of the middle-ear system. The MEMR threshold is the least signal intensity that elicits this reflex. In contrast to the ABR wave I, the MEMR arises predominantly from firing of the low spontaneous rate/high threshold auditory nerve fibers[68],[69] that are implicated in synaptopathy. Mouse data suggest that the MEMR threshold is strongly correlated with synaptopathy, and to a larger extent than ABR wave I amplitude.[70],[71] Additionally, as highlighted by Bramhall et al.,[72] the MEMR takes a shorter time to administer than the ABR, and is a part of routine hearing testing, as opposed to the ABR. Elevated MEMR thresholds[73] and reduced MEMR amplitudes[73],[74],[75] have been observed in noise-exposed listeners. MEMR metrics have also been found to correlate with tinnitus and speech perception,[75],[76],[77] which are commonly reported perceptual deficits in synaptopathy.[16] However, Guest et al.[78] found no relationships between MEMR thresholds and speech perception in noise or self-reported lifetime noise exposure. Although not unambiguous, the preponderance of evidence suggests that the MEMR appears to be a more robust and time-efficient index of cochlear synaptopathy in human listeners as compared to the ABR wave I amplitude.
A third physiological metric that has received considerable attention as a possible indicator of synaptopathy in human listeners is the FFR. The scalp-recorded FFR is generated by sustained phase-locked activity occurring in a neural population in the auditory system and may be elicited by a range of auditory stimuli (for detailed reviews, see Chandrasekaran & Kraus[79]; Krishnan;[80] Krizman & Kraus[81]). The neural activity underlying the FFR reflects phase-locking to the envelope and fine structure elements of the stimulus.[82] The phase-locked response to the stimulus envelope, obtained by summing opposite-polarity FFRs, is referred to as the envelope FFR or the envelope following response (EFR). Phase-locked response to stimulus harmonics is enhanced in the spectral FFR, derived by subtracting opposite-polarity FFRs. Lower EFR amplitudes have been measured in mice exhibiting synaptopathic changes due to aging[83] and noise exposure.[84] The increased sensitivity of the EFR to synaptopathy may be attributed in part to the contributions of the low spontaneous rate/high threshold auditory nerve fibers that are thought to dominate EFR generation at low modulation depths.[45],[85] Further, the EFR is typically elicited by relatively high-intensity stimuli (70–90 dB SPL) and is likely unaffected by any OHC damage that may occur following noise exposure in individuals with normal hearing sensitivity.[86] However, findings in the literature about the sensitivity of the EFR as an index of synaptopathy in human listeners are mixed. For example, Bharadwaj et al.[45] found that EFR amplitudes reduced at a faster rate with decrease in modulation depth in individuals with noise exposure. Similarly, Bramhall et al.[46] reported reduced EFR amplitudes in Veterans with significant noise exposure as compared to non-Veterans. On the other hand, some studies have reported weak or no links between EFR magnitude and young listeners with recreational noise exposure.[49],[50],[53]
Several of the synaptopathy studies cited above examine physiological and/or perceptual performance in human listeners while taking into consideration their lifetime noise exposure but do not delineate the relative contributions of recreational and occupational noise exposure. When recreational noise exposure is the focus, the recreational activities are limited to attendance at concerts, loud parties, sporting events, use of earphones, and other forms of music exposure.[45],[52] The literature on physiological and behavioral correlates of auditory processing in listeners with normal hearing sensitivity involved in recreational firearm use remains limited. To our knowledge, there is only one study published to date[46] that discusses cochlear synaptopathy in listeners with recreational firearm use. Although the primary focus of Bramhall et al.[46] was to describe the effects of noise exposure on Veterans, they found that ABR wave I amplitudes were attenuated in non-Veterans with a history of nonoccupational/recreational firearm use as compared to non-Veterans who reported no firearm use. However, Bramhall and colleagues did not measure the FFR and the MEMR in this study, which are thought to be more robust indicators of synaptopathy as compared to the ABR. Although associations between FFR and MEMR metrics, noise exposure history, and auditory perception remain ambiguous in human listeners, it is worth noting that both EFR[65] and MEMR[72] magnitudes have been found to be reduced in amplitude in Veterans with high noise exposure as compared to non-Veteran controls with no firearm exposure. All but two of the participating Veterans in Bramhall et al.[65] and Bramhall et al.[72] reported firearms training. Additionally, the only difference in noise exposure between the non-Veteran groups in Bramhall et al.[46] was the use of recreational firearms. Overall, the data presented by Bramhall and colleagues suggest that firearm exposure may be a risk factor for synaptopathy. Additionally, though Bramhall et al.[46] provide valuable information on the association between self-reported noise exposure and physiological metrics in non-Veterans with recreational firearm use, the study does not describe how these listeners fare on perceptual tasks. Further, although Bramhall and colleagues included non-Veteran listeners with recreational firearm experience in their study, these participants were not specifically queried on whether their firearm use was related to hunting. Here, we aim to describe FFR and MEMR measurements, and performance on commercially available behavioral tests of central auditory processing in listeners with normal hearing sensitivity with and without firearm exposure related to hunting. As far as we know, no study to date has examined this question, which is of central interest given the number of individuals engaged in hunting, the established effects of noise exposure on the auditory system, and the emerging and evolving information on noise-induced cochlear synaptopathy in human listeners. Ultimately, this information may benefit recreational firearm users in the community and clinical audiologists serving them, in terms of awareness, monitoring, counseling, and (re)habilitation.
| Materials and methods | | |
Participants
A total of 20 adult participants (age range: 20 to 28 years) with self-reported normal hearing were recruited for the study. Participants were divided into two groups (non-hunters and hunters) based on self-report of recreational firearm use through hunting in at least 1 year immediately preceding data collection. Hunter participants consisted of 10 individuals with a history of noise exposure through recreational firearm use while hunting (males = 9, females =░ age range: 20 to 23 years; M: 21.60; SD: 1.07). The nonhunter group also consisted of 10 individuals, but with no hunting-associated recreational firearm use (males = 5, females = 5; age range: 21 to 28 years; M: 23.40; SD: 3.10). Participant age and sex information is provided in [TABLE 1]. Participation was voluntary and participants were recruited through word of mouth. Inclusion was based on the following criteria: an insignificant otologic history (no history of ear surgeries, ear infections, and ototoxicity), normal hearing sensitivity defined by pure-tone audiometric thresholds ≤ 20 dB HL at octave frequencies from .25 to 8 kHz, air-bone gaps of ≤ 10 dB, normal middle-ear compliance and pressure as evidenced by Jerger type A tympanograms, native speaker of English, and history (or lack thereof) of noise exposure due to recreational firearm use from hunting. All participants were paid for their participation and provided informed consent in compliance with a protocol approved by the Institutional Review Board at the institution where the study was conducted. | TABLE 1 Age, LAeq, Pure-Tone Average of .5, 1, 2 kHz (PTA), Speech Recognition Threshold (SRT), and Word Recognition Scores (WRS) for Nonhunter and Hunter Participants.
Click here to view |
Procedures
Testing was performed over two 2-hour sessions. During the first session, all participants completed a detailed case history, the Noise Exposure Questionnaire (NEQ[87]), a comprehensive diagnostic audiologic evaluation, and a battery of behavioral auditory processing tests. The second session consisted of FFR testing. All testing was performed in sound-treated audiometric booths. All equipment was calibrated to American National Standards Institute (ANSI) standards.[88]
Audiologic History, Noise Exposure Questionnaire, and Audiologic Evaluation
All participants were asked to provide a detailed audiologic history using the institution’s audiology clinic case history form Appendix A as well as a comprehensive noise exposure history using the NEQ[87] prior to testing. Annual noise exposure scores (LAeq) were derived using responses on the NEQ to quantify noise exposure for each participant.[87] Immittance testing was conducted using a GSI Tympstar immittance bridge and tympanometry was performed using a 226 Hz probe tone. Pure-tone air conduction audiometry was performed using the GSI Audiostar audiometer via Eartone 3A inserts in octave bands from .25 to 1 kHz, and half octave bands from 2 to 8 kHz, bilaterally. Pure-tone bone conduction testing was performed using a mastoid placement Radioear B71 bone oscillator from .5 to 4 kHz in octave bands, bilaterally. Responses were obtained via a push button. Hearing sensitivity was considered normal if thresholds were ≤ 20 dB HL at all frequencies in both ears. Speech audiometry (Speech Recognition Threshold [SRT] and Word Recognition Score [WRS] testing) was conducted using a Sony CD player. SRTs were obtained via recorded male voice presenting spondee words in each ear. WRS were obtained via monitored recorded male voice using the Northwestern University Auditory Test No. 6 (NU-6) word list at 40 dB SL re: SRT, in each ear. Transient Evoked Oto-acoustic Emissions (TEOAEs) and Distortion Product Oto-acoustic Emissions (DPOAEs) were recorded bilaterally using the ILOv6 software (Otodynamics, Ltd.) to characterize cochlear OHC function. TEOAEs were recorded from 1 to 4 kHz using 260 sweeps. DPOAEs were recorded from 1 to 6 kHz with an L1/L2 combination of 65/55 dB SPL and an f2/f1 ratio of 1.22. Signal-to-noise ratios (SNR) of 6 dB or greater were considered acceptable for oto-acoustic emission testing.
Frequency Following Response (FFR) testing
Stimuli
Previous synaptopathy studies using the FFR have utilized “transposed” tones, consisting of a high-frequency tonal carrier (usually around 4 kHz) amplitude modulated by a lower frequency (e.g., 100 Hz). It is thought that FFRs obtained to such transposed tones would be ideally suited to capture the contribution of low spontaneous rate/high threshold fibers in the 3 to 6 kHz region, thereby reflecting temporal coding deficits in the frequency region known to be most affected by noise exposure. In the current study, a natural version of the vowel/u/(F0 = 122.1 Hz, F1 = 287–338 Hz, F2 = 1051–1477 Hz) was selected from the UT Dallas Vowel database produced by an adult male speaker.[88],[89] FFRs were measured in response to the vowel presented in a quiet (“clean”) listening condition, as well as in three SNR conditions (+5 dB, 0 dB, and −5 dB) with competing noise (male four-talker babble). FFRs to speech in noise were selected as the experimental measure in the current study for the following reasons: 1) speech is an ecologically relevant, amplitude-modulated signal with modulations occurring at the fundamental frequency; 2) the vowel fundamental frequency (F0) (122.1 Hz) occurs below the upper bound of neural phase-locking in the brainstem (1500 Hz);[82],[90],[91] 3) the vowel fundamental frequency (122.1 Hz) was well above 80 Hz, below which the FFR is thought to be dominated by cortical rather than subcortical generators;[92] 4) speech-evoked FFRs have been effectively utilized in the past to describe brainstem phase-locking to both F0 and stimulus harmonics aligning with formant frequencies. Both F0 and formant frequencies are critical for speech perception in challenging listening situations such as background noise and reverberation, a function predicted to be affected in listeners with synaptopathy; 5) both intact and degraded versions of this vowel have been successfully used to elicit FFRs in listeners with normal hearing sensitivity previously;[90],[93],[94],[95] 6) signal level was 70 dB SPL, ensuring contributions to the response from low spontaneous rate/high threshold fibers; and 7) valid comparisons may be performed between behavioral and neural metrics if both measurements involve obtaining responses to speech in noise stimuli.
All stimuli (vowel in quiet, or vowel + four-talker babble) were presented monaurally to the right ear via a magnetically shielded insert earphone (Etymotic, ER-3 A; 6-8 kHz bandwidth) at an intensity of 70 dB SPL and a rate of 3.13/s. Stimulus duration was 265 ms and all stimuli had 10 millisecond on-off ramps. The vowel was presented in alternating polarity; however, the four-talker babble was presented in rarefaction polarity. Use of rarefaction polarity for the four-talker babble was necessitated as the babble was played using the “continuous loop” feature on the Smart-EP module, which does not permit use of alternating polarity. The “continuous loop” feature was selected so that the babble was not synchronized in time with the vowel stimulus.[96] Two thousand sweeps were presented per trial. Each trial was repeated at least once to ensure replicability of the responses. Responses were amplified by 200,000 and a band pass filter (70–3000 Hz) was applied to remove artifact and myogenic background noise from the response. The Smart-EP module in the Intelligent Hearing Systems (IHS, Miami, FL) was used for signal presentation and data acquisition. Stimulus presentation order was randomized within and across all participants.
FFR Protocol
Participants were seated in a comfortable recliner situated in an acoustically and electromagnetically shielded booth. Participants were directed to keep their eyes closed, stay relaxed, and avoid any extraneous body movements to ensure minimal response contamination due to movement artifacts. Most participants fell asleep during FFR acquisition. FFRs were recorded using a two-channel vertical electrode array (Channel 1: Fz [noninverting], A1 & A2 [linked inverting electrodes]; Channel 2: Fz [noninverting], C7 [inverting]; Fpz [common ground]). FFRs measured using such an electrode configuration are considered to reflect predominantly rostral brainstem activity, as the vertical electrode array is aligned similarly to the vertical dipole of the brainstem.[97],[98] In order to minimize response contamination by the cochlear microphonic and stimulus artifact, stimuli were delivered in alternating polarity through transducers that were electromagnetically shielded and separated from electrodes to the extent possible.[99]
FFR Analysis
FFR data measured in the two vertical electrode channels (Fz-linked A1 & A2 and Fz-C7) used in the current study have been previously shown to be strongly correlated with no statistically significant differences.[95] Given this, the current FFR time-waveforms were collapsed across the two measurement channels in each subject and for each test condition in order to increase the response SNR. Thus, this process yielded one FFR time-waveform per participant per stimulus condition. A Fast Fourier Transform (FFT) analysis was conducted on the FFR time-waveforms to obtain the spectral composition of the FFR. The spectral peak magnitude at stimulus F0 (122.1 Hz), as well as the magnitude of the noise floor (calculated by averaging FFT peak magnitudes in a 50 Hz window on either side of 122.1 Hz) were measured for each participant for each stimulus condition. As the magnitude of the noise floor can vary across participants, a ratio of the spectral peak magnitude at F0 to the noise floor magnitude (F0/NF) was calculated for each participant for each stimulus condition, and was used for statistical analyses.
MEMR
Following the standard clinical immittance test battery protocol, ipsilateral and contralateral MEMR thresholds were obtained using a 226 Hz probe tone presented alongside pulsed tonal elicitors at 500 Hz, 1000 Hz, and 2000 Hz in each ear.[100] MEMR measurements were not made for a 4000 Hz elicitor, as increased variability has been noted in acoustic reflexes obtained at this frequency in individuals with normal hearing sensitivity.[101],[102],[103] The MEMR was considered to be present if compliance in the test ear decreased by .02 mL or greater. The lowest elicitor intensity level at which this criterion was met on two out of three stimulus presentations was accepted as the MEMR threshold for that particular elicitor. All MEMR measurements were made using a GSI Tympstar diagnostic middle-ear analyzer. Here, it is worth mentioning that several studies of synaptopathy have utilized wideband probes and stimuli to elicit the MEMR.[72],[75],[76],[77] However, a tonal probe and elicitors were utilized in the current study in order to investigate if effects of synaptopathy are evident using a standard clinical immittance testing protocol.
Behavioral Tests of Auditory Processing
Behavioral tests of auditory processing were administered in the areas of monaural low redundancy, temporal processing, dichotic listening, and binaural interaction. The specific tests employed in this battery included both speech and nonspeech tasks and assessed a range of auditory processes, following the recommendations for behavioral auditory processing test battery selection proposed by AAA[104] and ASHA.[105] Many of the tests included in the test battery (e.g., Time Compressed Sentences Test, Frequency Pattern Test, Gaps In Noise test, Dichotic Digits Test, Masking Level Difference) were similar to those utilized in Gallun et al.,[106] Gallun et al.,[107] Kubli et al.,[108] and Saunders et al.[109] Tests were administered via monitored recorded voice using a Sony CD player connected to a GSI Audiostar audiometer. Test stimuli were calibrated so that the tone peaked at 0 on the VU meter prior to testing. Stimuli were presented at intensity levels specified in the administration instructions for each test. Participants were instructed verbally via standardized prewritten testing instructions prior to administration of each test and were asked to respond to stimuli either verbally or by pressing a button, as required by the test. Order of tests administered and ear tested were randomized to reduce test order and ear effects. Breaks were provided after every third test and/or at the participants’ request.
Monaural low redundancy
Tasks of monaural low redundancy assess a participant’s ability to understand and repeat spectrally or temporally degraded auditory signals.[110] The Auditory Figure Ground (AFG) test and Low Pass Filtered Speech (LPFS) test were used to assess the effects of spectral degradation on speech understanding. The Time Compressed and Reverberated Speech (TCRS) test was administered to assess the effects of temporal degradation on speech perception.
AFG
Participants were asked to repeat back 20 target words in the presence of background noise presented to each ear at the following SNRs: +0 dB, +8 dB, and +12 dB.[111] The number of words repeated back correctly were calculated for each ear (“raw scores”). For diagnostic reporting purposes, raw scores are typically converted to scaled scores. In the current study, in addition to scaled scores, raw scores were utilized in data analysis to allow for ear-specific data comparisons between participants. Stimuli were presented using the SCAN-3:A CD.
LPFS
The LPFS is comprised of 50 NU-6 words that have been passed through a low-pass filter with a cut-off value of 1500 Hz to modify frequency content such that the words consist only of spectral energy below 1500 Hz.[112] The test was administered via the Tonal and Speech Materials for Auditory Perceptual Assessment audio compact disc (developed by the Department of Veterans Affairs). Participants were asked to repeat back words that were presented monaurally to the right ear (25 words) and the left ear (25 words), and to guess if unsure. Percent correct scores were calculated for each ear.
TCRS
The TCRS, also administered via the Tonal and Speech Materials for Auditory Perceptual Assessment audio compact disc (Department of Veterans Affairs), consists of 100 NU-6 words that have been compressed in the time domain.[113] The test in this study utilized both 45% and 65% compression with 0.3 seconds of reverberation. A total of 50 words were presented to each ear and percent correct score was determined for the right and left ears, respectively.
Dichotic listening
Tasks of dichotic listening involve the presentation of two different stimuli, such as words, digits, or sound clusters, to each ear simultaneously.[114] Dichotic listening can be further separated into tasks of binaural integration (combining information coming from the right and left ears) and binaural separation (attending to stimuli presented to a specified ear while ignoring stimuli presented to the opposite ear). The Dichotic Digits Test (DDT) and Competing Words Directed Ear (CWDE) test were used to assess binaural integration, and the Competing Sentences Test (CST) was administered to assess binaural separation.
DDT
The DDT consists of 20 two-digit pairs of numbers presented to the right ear and 20 two-digit pairs of numbers presented to the left ear.[115] Stimuli were presented via the Tonal and Speech Materials for Auditory Perceptual Assessment audio compact disc (Department of Veterans Affairs). Participants were instructed to repeat both pairs of numbers heard in each ear (a total of four numbers) and to guess if unsure. Percent correct scores were determined for the right and left ears.
CWDE
The CWDE consists of 15 word pairs directed to the right ear and 15 word pairs directed to the left ear. Stimuli were presented via the SCAN 3:A CD. Participants were instructed to first repeat back the word heard in the directed ear (determined by the test administrator), then the word heard in the nondirected ear.[111] For example, a participant may hear the word “knock” in the right ear while simultaneously hearing the word “deep” in the left ear. If the right ear is the directed ear, the patient must repeat back “knock, deep” in that order. The number of correct responses were tallied to obtain a raw score for each ear for each participant. As with the AFG test, raw scores obtained on the CWDE test are typically converted to scaled scores for diagnostic purposes. In the current study, raw scores were retained along with scaled scores for ear-specific data analysis.
CST
The CST consists of a set of 30 sentences that are presented to the right ear, whereas a set of 30 different sentences are simultaneously presented to the left ear via the SCAN 3:A CD.[111] Participants were asked to repeat 15 sentences presented to one ear while ignoring the sentences presented to the other ear. Participants were then asked to repeat 15 sentences presented to the opposite ear and to ignore the sentences presented to the first test ear. Key words in the sentence were scored to determine a percent correct score for each ear. Raw scores obtained on the CST are typically converted to scaled scores for diagnostic purposes. In the current study, raw scores were utilized for data analysis, in addition to the scaled scores, in order to retain ear-specific information.
Temporal processing
Tasks of temporal processing assess a participant’s ability to process auditory signals in the time domain[116] and may be categorized as temporal ordering or temporal ordering tasks. Participants underwent the Frequency Pattern Test (FPT) to assess temporal ordering abilities and the Gaps in Noise (GIN) test to assess temporal resolution abilities.
FPT
The FPT consists of a total of 30 patterns of three tones composed of high (1122 Hz) and low (880 Hz) frequencies that are presented to each ear individually.[117] Participants were asked to label the pattern by identifying each tone as either high or low. Each pattern contained at least one high- and one low-frequency tone. Stimuli for the FPT were presented via the Tonal and Speech Materials for Auditory Perceptual Assessment audio compact disc (Department of Veterans Affairs). A percent correct score was calculated for each ear.
GIN
The GIN is comprised of segments of broadband noise that are presented monaurally for 6 seconds with zero to three gaps in each segment. Gaps range in duration from 2 to 20 milliseconds.[118] Stimuli for the GIN were presented via the Gaps In Noise compact disc (Auditec, Inc.). Participants were asked to press a button every time they detected a gap in the noise. Gap detection threshold was determined to be the smallest gap participants were able to detect for four out of six presentations for both the right and left ears.
Binaural interaction
Binaural integration abilities were assessed using the Masking Level Difference (MLD) test, which determines a participant’s ability to detect signals in the presence of noise in both a homophasic (SₒNₒ) and antiphasic (SπNₒ) masking paradigm.[119] In this study, the signal of interest consisted of a 500 Hz tone with a narrowband masker centered around this frequency. Participants were instructed to ignore the masker and to press a button when the tone was detected. Masking level difference was calculated by determining the difference in threshold value between the homophasic and antiphasic conditions. Stimuli were presented using the Masking Level Difference-Tone audio compact disc (Auditec, Inc.)
Statistical Analysis
Mixed-model analyses of variance (ANOVA) were conducted to assess main and interaction effects of group (hunter, nonhunter; between-subjects factor), test ear (right, left; within-subjects factor), test frequency (within-subjects factor) and test condition (within-subjects factor) on audiometric measurements, outcomes of behavioral tests of auditory processing, and brainstem neural representation of F0. Post-hoc pairwise comparisons were conducted using Bonferroni correction. Mixed ANOVAs were supplemented with independent samples t-tests for any comparison of means between hunter and nonhunter participants. All statistical analysis was performed using IBM SPSS Statistics for Windows, version 25 (IBM Corp., Armonk, N.Y., USA).
| Results | | |
NIHL risk classification based on NEQ
Annual noise exposure values, or LAeq scores, calculated for each participant are listed in [TABLE 1]. Johnson et al.[87] consider participants with LAeq scores ≥ 79 to be at high risk for NIHL. A total of five participants (female = 1, male = 4), all of whom described themselves as hunters, exceeded this criterion in the current study. It is important to note that annual noise exposure estimation using the approach proposed by Johnson et al.[87] reflects exposures to continuous noise and does not take into account exposure to impulse noise such as firearm discharge. However, Johnson et al.[87] include a special cautionary note for firearm users taking their 1-Minute Noise Screen, where they indicate that regular use of firearms, even if once in a few months, puts these users at high risk of hearing loss. Thus, based on report of firearm use alone, all participants in the hunter group (female = 1, male = 9) were classified as being high risk for NIHL. NEQ, audiological, FFR, MEMR, and behavioral test outcomes in participants classified as hunters (n = 10) versus non-hunters (n = 10) based on a self-report of hunting in the immediate year preceding experiment participation are presented in detail in section 3.2.
Additionally, though all participants in the hunter group in the current study utilized firearms, two participants (S6 and S7) from the nonhunter group indicated recreational firearm use in the past year, although not for hunting purposes. Following the recommendations for risk categorization based on firearm use outlined by Johnson et al.,[87] the two nonhunter participants would also classify as “high risk.” Two supplemental analyses were conducted on the perceptual and physiological auditory measures to address this potential confound:- Eliminating S6 and S7 (hunters [n = 10] vs. non-hunters [n = 8]).
- Including S6 and S7 in the hunter group based on their history of recreational firearm use (albeit not hunting-related) (hunters [n = 12] vs. non-hunters [n = 8]).
With minor exceptions, the outcomes of these supplemental analyses yielded similar results in terms of effects of group, test ear, test frequency, and test condition on LAeq scores, audiological test results, behavioral auditory processing test outcomes, and FFR F0/NF values, and are briefly summarized in Appendix B.
NEQ, Audiological, FFR, MEMR, and behavioral test outcomes in participants classified as “hunters” vs. “non-hunters”
NEQ in nonhunter and hunter participants
An independent-samples t-test was conducted to compare LAeq scores in hunter and nonhunter participants. Results indicated significantly higher (poorer) LAeq scores in hunters (M = 78.72, SD = 6.09) as compared to non-hunters (M = 69.66, SD = 3.99); t(18) = -3.93, p = 0.001. , five participants in the hunter group (female = 1, male = 4) exceeded the criterion value of 79 for the LAeq in the current study; no individual in the nonhunter group returned an LAeq value exceeding 79.
Audiological outcomes in nonhunter and hunter participants
Mixed-model ANOVAs were used to determine effects of test frequency, test ear, and group (hunters, non-hunters) on audiometric thresholds, MEMR thresholds, TEOAE SNR values, and DPOAE SNR values. Based on the test in question, the dependent variable was audiometric threshold (dB HL), MEMR threshold (dB HL), TEOAE SNR (dB), and DPOAE SNR (dB). Test frequency and test ear were within-subject variables, whereas group was considered the between-subjects variable. Similar mixed-model ANOVAs were used to determine effects of test ear and group (hunters, non-hunters) on pure-tone average and speech recognition thresholds. For these analyses, test ear was considered the within-subjects factor, whereas group was the between-subjects factor, with the dependent variable being pure-tone average or speech recognition threshold. For all mixed-model ANOVAs, Greenhouse Geisser corrections were applied in instances when Mauchly’s test indicated that the assumption of sphericity had been violated.
Pure-tone audiometric thresholds
All participants had pure-tone audiometric thresholds of ≤ 20 dB HL from .25 to 8 kHz in both ears (see [TABLE 2]) with air-bone gaps of ≤ 10 dB, meeting clinical definitions of normal hearing sensitivity. Mean air conduction pure tone thresholds for nonhunter (filled circles) and hunter (open circles) participants are plotted at audiometric test frequencies between .25 and 8 kHz for the right (panel A) and left (panel B) ears in [Figure 1], respectively. A significant main effect was noted for audiometric test frequency (F3.46, 62.43 = 7.72, p < 0.001). Bonferroni-corrected post-hoc multiple comparisons indicated that audiometric thresholds were lower (better) at 6 kHz as compared to .25 kHz and 3 kHz, and higher (poorer) at 3 kHz as compared to 1 kHz. A significant main effect was also observed for group (F1,18 = 4.47, p = 0.04), such that non-hunters had lower (better) audiometric thresholds than hunters. Bonferroni-adjusted post-hoc multiple comparison testing revealed that apart from .25 kHz in the left ear, audiometric thresholds were consistently poorer in participants classified as hunters as compared to non-hunters. There was no significant main effect for test ear (F1,18 = 4.03, p = 0.06), nor were there any significant interaction effects. Additionally, when pure-tone average (0.5, 1, 2 kHz; PTA) was the dependent variable, no significant main effects were observed for test ear (F1,18 =.02, p = 0.65) or group (F1,18 = 2.72, p = 0.11); further, there was no interaction effect. PTA values calculated for each participant are listed in [TABLE 1]. | TABLE 2 Air Conduction Audiometeric Thresholds for Nonhunter and Hunter Participant
Click here to view |
 | Figure 1 Mean air conduction pure-tone thresholds for nonhunter (filled circles) and hunter (open circles) participants at audiometric test frequencies between .25 and 8 kHz for the right (panel A) and left (panel B) ears. Symbols represent the mean, whereas error bars represent the standard error across participants.
Click here to view |
Speech recognition in quiet
SRT values obtained for each participant are listed in [TABLE 1]. For SRT, though there was no main effect of test ear (F1,18 = 1.6, p = 0.22), there was a main effect of group (F1,18 = 6.48, p = 0.02). Specifically, non-hunters (M = 4.75 dB HL, SE = 1.25) had a lower (better) SRT than hunters (M = 9.25 dB HL, SE = 1.25). There was no interaction effect of test ear and group on SRT. Both hunter and nonhunter participants scored 100% on the WRS in both ears; further inferential statistics were not performed as there was no variance in the WRS data.
Distortion Product Oto-Acoustic Emissions
DPOAE SNRs were > 6 dB at all test frequencies for 5/10 nonhunter participants, although different participants met this criterion in each ear. When examining DPOAE SNR levels by test frequency in the nonhunter group, SNR levels were > 6 dB in both ears for all participants at 2.8, 4, and 6 kHz, for 9/10 participants at 1.4 and 2 kHz, and for 5/10 participants at 1 kHz. In the hunter group, the 6 dB SNR criterion was met at all test frequencies for 2/10 participants in the right ear and 3/10 participants in the left ear. When analyzing by test frequency in the hunter group, DPOAE SNR levels were > 6 dB for all participants at 4 and 6 kHz in both ears, for 9/10 participants at 2.8 kHz in both ears, for 8/10 (right ear) and 7/10 (left ear) participants at 2 kHz, and for 2/10 (right ear) and 3/10 (left ear) participants at 1 kHz. DPOAE SNR values at each test frequency are provided for each participant in [TABLE 3]. Mean DPOAE SNR values for nonhunter (filled circles) and hunter (open circles) participants are plotted at test frequencies between 1 and 6 kHz for the right (panel A) and left (panel B) ears in [Figure 2]. A significant main effect was observed for DPOAE test frequency (F1.63,29.45 = 14.04, p < .001). Post-hoc multiple comparison testing with Bonferroni correction indicated that, in general, DPOAE SNRs increased as a function of test frequency. Main effects for test ear (F1,18 =2.14, p =.161) and group (F1,18 =.52, p =.48) were nonsignificant, as were interaction effects. | Figure 2 Mean DPOAE SNR (right ear: Panel A; left ear: Panel B) and TEOAE SNR (right ear: Panel C; left ear: Panel D) values for nonhunter (filled circles) and hunter (open circles) as a function of test frequency in kHz. Symbols represent the mean, whereas error bars represent the standard error across participants.
Click here to view |
Transient Evoked Oto-Acoustic Emissions
TEOAE SNR levels were > 6 dB at all frequencies in both ears for only one participant each in the nonhunter (participant # 3) and hunter (participant # 11) groups. When analyzing by test frequency, the 6 dB SNR criterion in the nonhunter group was met as follows: 1 kHz (1/10 right ear, 4/10 left ear), 1.4 kHz (6/10 both ears), 2 kHz (4/10 both ears), 2.8 kHz (5/10 right ear, 6/10 left ear), and 4 kHz (4/10 right ear, 7/10 left ear). Test frequency-wise, the 6 dB SNR criterion in the hunter group was met as follows: 1 kHz (3/10 both ears), 1.4 kHz (5/10 right ear, 3/10 left ear), 2 kHz (6/10 right ear, 4/10 left ear), 2.8 kHz (6/10 both ears), and 4 kHz (3/10 right ear, 7/10 left ear). TEOAE SNR values at each test frequency are provided for each participant in [TABLE 4]. Mean TEOAE SNR values for nonhunter (filled circles) and hunter (open circles) participants are plotted at test frequencies between 1 and 4 kHz for the right (panel C) and left (panel D) ears in [Figure 2]. Similar to DPOAEs, a significant main effect was observed for TEOAE test frequency (F2.78, 50.06 = 3.42, p = 0.027). Bonferroni-adjusted post-hoc multiple comparison testing indicated that TEOAE SNRs were lower (poorer) at 1 kHz and 2 kHz as compared to 2.8 kHz. As with DPOAEs, main effects for test ear (F1,18 = 1.02, p =.32) and group (F1,18 =.15, p =.69), as well as interaction effects, were not significant.
FFRs in nonhunter and hunter participants
Grand average FFR time-waveforms and spectra obtained to the English back vowel /u/ presented in clean, +5, 0, and −5 dB SNR conditions in nonhunter (black) and hunter (red) participants are plotted in panels A and B in [Figure 3]. Visual inspection of the FFR time-waveforms suggests a larger amplitude associated with nonhunter as compared to hunter participants, for each SNR condition. FFR time-waveforms ([Figure 3], panel A) show robust periodicity for both nonhunter and hunter participants in the clean condition; whereas clear periodicity is maintained in the nonhunter group at the remaining SNR conditions, there is some degradation apparent in the waveform morphology in hunter participants at +5, 0, and −5 dB SNRs. For any given SNR condition, spectral peaks at F0 (120 Hz) and harmonics were discernable in the spectra of FFR ([Figure 3], panel B) elicited in both nonhunter and hunter participants. Average peak magnitudes were greater in the nonhunter as compared to the hunter participants at all SNR conditions. For both nonhunter and hunter groups, average peak magnitude at F0 decreased with decrease in SNR. | Figure 3 Grand average FFRENV time-waveforms (Panel A) and spectra (Panel B) measured in clean, +5, 0, and −5 dB SNR conditions in nonhunter (black) and hunter (red) participants.
Click here to view |
Mean F0/NF values for the nonhunter (filled circles) and hunter (open circles) participants as a function of the SNR (clean, +5, 0, −5 dB) are plotted in [Figure 4]. A mixed-model ANOVA was conducted with F0/NF as the dependent variable, SNR (clean, +5, 0, −5 dB) and test ear (right, left) as within-subject factors, and group (hunters, non-hunters) as the between-subjects factor. Results indicated a significant main effect for SNR (F3,54 = 7.007, p < 0.001). Bonferroni-adjusted post-hoc multiple comparison testing indicated that FFR F0/NF values were greatest in the clean condition and decreased as a function of SNR (+5 > 0 > −5 dB). There was no effect of group (F1,18 =.193, p = 0.666); further, there were no significant interaction effects. | Figure 4 Mean F0/NF values for nonhunter (filled circles) and hunter (open circles) participants as a function of the SNR (clean, +5, 0, −5 dB). Symbols represent the mean, whereas error bars represent the standard error across participants.
Click here to view |
MEMR thresholds in nonhunter and hunter participants
Ipsilateral and contralateral MEMR thresholds at all test frequencies ([TABLE 5]) were consistent with pure-tone thresholds at corresponding frequencies for all participants.[102] Mean MEMR thresholds for nonhunter (filled circles) and hunter (open circles) participants are plotted at .5, 1, and 2 kHz for the right (right ipsilateral and left contralateral) and left (left ipsilateral and right contralateral) ears in panels A and B of [Figure 5], respectively. Significant main effects were observed for test mode (F1,18 = 516.93, p < .001) and test frequency (F2,36 = 34.67, p < .001. Post-hoc multiple comparison testing with Bonferroni correction indicated that, in general, contralateral MEMR thresholds were higher (poorer) than ipsilateral MEMR thresholds, and MEMR thresholds increased as a function of test frequency. Main effects for test ear (F1,18 =.056, p =.815) and group (F1,18 =.002, p =.962) were nonsignificant. The only significant interaction effect noted was for test frequency and group (F2,36 = 5.87, p = 0.006), where MEMR thresholds were lower (better) at 500 Hz for non-hunters compared to hunters, but higher (poorer) at 1 kHz and 2 kHz. | TABLE 5 Ipsilateral and Contralateral Middle-Ear Muscle Reflex Thresholds for Nonhunter and Hunter Participants.
Click here to view |
 | Figure 5 Mean MEMR thresholds for nonhunter (filled circles) and hunter (open circles) participants at .5, 1, and 2 kHz for right ipsilateral and left contralateral (Panel A), and left ipsilateral and right contralateral (Panel B) conditions. Symbols represent the mean, whereas error bars represent the standard error across participants.
Click here to view |
Behavioral tests of auditory processing in nonhunter and hunter participants
Mean scores and standard deviations for the tests of monaural low redundancy (AFG, LPFS, TCRS), temporal processing (FPT, GIN), dichotic listening (DDT, CWDE, CST), and binaural listening (BMLD) tests for nonhunter and hunter participants are listed in [TABLE 6]. Participant performance was defined as normal or abnormal by comparing individuals’ test scores against corresponding normative data cut-off values.[113],[114],[117],[118],[120],[121],[122] Further, as with the audiological data, mixed-model ANOVAs were used to determine effects of test condition, test ear (right, left), and group (hunters, non-hunters) on various outcome measurements (thresholds, percent correct, scores) of behavioral tests of auditory processing. For the majority of the behavioral tests (LPFS, DDT, CWDE, CST, FPT, GIN), test ear was designated as the within-subjects variable, whereas group was considered the between-subjects variable. For the BMLD test, test condition (S0N0 and SπN0) was the within-subjects variable, whereas group remained the between-subjects variable. Finally, for the Auditory Figure Ground and Time-Compressed & Reverberated Speech, which involve presentation of signals at varying SNRs and compression amounts in both ears, test condition (SNR for AFG, % compression for TCRS) and test ear (right, left) were designated as within-subjects variables, whereas group was the between-subjects variable. As before, Greenhouse-Geisser corrections were applied in any instances when Mauchly’s test indicated that the assumption of sphericity had been violated. Finally, separate independent samples t-tests were conducted to assess if scaled scores obtained in AFG, CST, and CWDE tests, and MLD values derived from S0N0 and SπN0 were significantly different between hunter and nonhunter participants. | TABLE 6 Mean Scores and Standard Deviations for Behavioral Tests of Auditory Processing in Nonhunter and Hunter Participants
Click here to view |
Monaural low redundancy
AFG
For positive SNRs (+8 and +12 dB), all participants, regardless of group, obtained scaled scores greater than the cut-off score of 7,[121] indicating typical performance. When the SNR was 0 dB, performance was within normal limits for 9/10 participants in both hunter and nonhunter groups, indicated by scaled AFG scores greater than 7.[121] When AFG scaled score was the dependent variable, there was a main effect of SNR (F2,26 = 3.67, p =.035). There was no significant main effect of group (F1,18 = 1.604, p =.221) or interaction effect. Similar results were obtained when AFG raw score was the dependent variable. Specifically, there were no main effects for test ear (F1,18 =.86, p =.36) or group (F1,18 = 2.29, p =.14); however, there was a main effect for SNR (F1.08, 19.49 = 71.68, p < 0.001). Post-hoc multiple comparison testing with Bonferroni corrections indicate better performance at +8 and +12 dB SNRs as compared to 0 dB SNR. No interaction effects were observed.
TCRS
When time compression was set to 45%, 3/10 listeners from the nonhunter group and 2/10 listeners from the hunter group obtained scores > 85% (cut-off score)[113] in both ears. 5/10 nonhunter participants and 8/10 hunter participants did not meet the cut-off criterion in both ears. When time compression was set to 65%, 2/10 listeners from the nonhunter group and 1/10 listeners from the hunter group obtained scores > 85% (cut-off score)[113] in both ears. Seven of 10 nonhunter participants and 9/10 hunter participants did not meet the cut-off criterion in both ears. Similar to the AFG results, mixed-model ANOVA indicated no main effects for test ear (F1,18 =.329, p =.573) or group (F1,18 = 1.59, p =.223) for the TCRS. However, there was a main effect for amount of time compression (F1,18 = 114.45, p < 0.001) such that TCRS scores were greater with 45% time compression as compared to 65% time compression. Again, no interaction effects were observed.
LPFS
Two of 10 listeners from the nonhunter group and 1/10 listeners from the hunter group obtained scores > 78% (cut-off score)[120] in both ears. 6/10 nonhunter participants and 8/10 hunter participants did not meet the cut-off criterion in both ears. Mixed-model ANOVA results indicated no significant main effects of test ear (F1,18 =.00, p = 1) or group (F1,18 = 2.33, p =.144), and no interaction effect.
Temporal resolution
FPT
All participants, regardless of group, obtained percent scores > 75% (cut-off score)[117] on the FPT. Results of a mixed-model ANOVA indicated no main effect of test ear (F1,18 =.34, p =.56) or group (F1,18 =.072, p =.791); interaction effects were not significant either.
GIN
For the GIN, all nonhunter participants obtained scores ≤ 6 ms (cut-off value),[118] meeting the definition for typical performance. 8/10 hunter participants met the criterion for typical performance in both ears. Among the nonhunter participants who did not meet the cut-off criterion, one listener did not pass the right ear, whereas the other listener failed both ears. Mixed-model ANOVA results were similar to those obtained for the FPT. Specifically, there were no main effects of test ear (F1,18 = 0.049, p =.828), group (F1,18 =.51, p =.48), or an interaction effect.
Dichotic listening
DDT
Eight of 10 listeners from the nonhunter group and 9/10 listeners from the hunter group obtained scores > 90% (cut-off score)[117] in both ears, indicating typical performance. For both nonhunter and hunter groups, any instance where the cutoff criterion was unmet involved the left ear (2/10 nonhunter and 1/10 hunter participants failed to meet the cut-off in the left ear). A mixed-model ANOVA yielded no significant main effects of test ear (F1,18 = 3.41, p =.08) or group (F1,18 = 1.05, p =.31); there was no interaction effect observed either.
CST
All participants in the nonhunter group and 9/10 listeners in the hunter group obtained scaled scores > 7 (cut-off value),[121] the cut-off criterion determining typical performance on the CST. Results of an independent samples t-test indicated significantly higher (poorer) scaled scores in hunters (M = 9.60, SD = 2.119) as compared to non-hunters (M = 11.30, SD = 1.252); t(18) = 2.185, p = 0.042. When CST raw score was used as the dependent variable, mixed-model ANOVA results indicated a main effect of test ear (F1,18 = 5.25, p =.03) such that right ear performance was better than left ear performance. However, there was no main effect of group (F1,18 = 4.08, p =.05) or interaction effect.
CWDE
All participants, regardless of group, obtained scaled scores >7 (cut-off value),[121] indicating performance within normal limits on the CWDE test. An independent samples t-test indicated no significant difference between scaled scores in hunters (M = 11.40, SD = 2.171) as compared to non-hunters (M = 12.7, SD = 1.252); t(18) = 1.641, p = 0.118. When CWDE raw score was used as the dependent variable, a main effect of test ear (F1,18 = 5.03, p =.03) was noted for the CWDE test such that right ear performance was better than left ear performance. Once again, there was no significant main effect of group: (F1,18 = 2.84, p =.109) and no interaction effect.
Binaural interaction
Nine of 10 listeners from the nonhunter group and 8/10 listeners from the hunter group obtained S0N0 thresholds ≤ −8.9 dB SNR (cut-off value),[122] indicating typical performance. 6/10 listeners from the nonhunter group and 7/10 listeners from the hunter group obtained SπN0 thresholds ≤ −23 dB SNR (cut-off value),[122] the cut-off for normal performance. Mixed-model ANOVA results indicated a significant main effect of test condition (F1,18 = 22.13, p < .001) such that thresholds obtained in the SπN0 condition were lower (better) than those obtained in the S0N0 condition. However, there was no significant main effect of group: (F1,18 =.034, p =.856), nor was the interaction effect significant.
Eight participants in both nonhunter and hunter groups had MLDs > 10 dB (cut-off value),[123] suggesting performance within normal limits. Results of an independent samples t-test indicated that there were no significant differences between the MLDs calculated in hunters (M = 12.8, SD = 4.02) as compared to non-hunters (M = 11.2, SD = 4.54); t(18) = -.834, p = 0.415.
| Discussion | | |
The aim of the current study was to describe performance on auditory perceptual and physiological tests in individuals with hunting-related recreational firearm noise exposure. Data from the current study suggest that: 1) pure tone and speech audiometric thresholds were clinically normal but elevated in hunter as compared to nonhunter participants; 2) performance on physiological and perceptual measures is similar in nonhunter and hunter participants, with a few exceptions; 3) for both FFR and behavioral measures, performance declined as a function of increasing signal degradation for both nonhunter and hunter participants; 4) apart from the CST and CWDE, both of which demonstrated a right ear advantage, test ear effects were rarely observed for the behavioral tests of auditory processing. Similar results were obtained when two nonhunter participants reporting recreational firearm use unrelated to hunting were excluded from the analysis, or assigned to the hunter group based on their firearm use. Thus, one could argue that the outcomes of this study describe the effects of general recreational firearm noise exposure on auditory measures. However, because the majority of our participants with recreational firearm use (10/12) described themselves as hunters, the various results will be interpreted in the context of hunting-related recreational firearm noise exposure.
Pure tone and speech audiometric thresholds are clinically normal, but elevated in hunter compared to nonhunter participants
Normal hearing sensitivity applies to a range of hearing thresholds (-15 to 25 dB HL, depending on the published definition followed). All audiometric and speech recognition thresholds measured in the nonhunter group fell within the limits for normal hearing sensitivity. Even so, pure-tone thresholds and speech recognition thresholds were consistently elevated in nonhunter participants as compared to hunter participants. The average difference in hearing thresholds across audiometric test frequencies between hunter and nonhunter participants was 3.18 dB in the right ear and 1.72 dB in the left ear. Additionally, when examining averaged thresholds by frequency, it was noted that the largest differences between non-hunters and hunters occurred at 6 (4.5 dB) and 8 (5 dB) kHz in the right ear. It is tempting to suggest that these differences, especially at the highest test frequencies, may reflect permanent shifts following hunting-related recreational firearm noise exposure. Studies have shown permanent threshold shifts in the extended high-frequency audiometric range (9–20 kHz) following noise exposure.[124],[125] Obtaining extended high-frequency audiometric thresholds would have been a valuable supplement to the current data set; however, this testing could not be conducted in the current study due to equipment limitations. That said, it is probable that the observed group difference in audiometric thresholds reflects a spurious statistical outcome. All participants in the study had hearing thresholds < 15 dB HL, with the exception of one listener in the hunter group who consistently exhibited 20 dB HL thresholds for multiple test frequencies. When this participant was excluded, the average differences in audiometric hearing thresholds between hunters and non-hunters ranged between −2.2 and 2.9 dB, and the group effect was no longer statistically significant (p =.079). Overall, given the limitations of the current data set and experimental protocol, it would be premature to make definitive conclusions based on the group difference in audiometric thresholds observed here.
Performance on physiological and perceptual measures is similar in nonhunter and hunter participants
At the outset, it is important to note that there are no studies in the literature that specifically query the effects of hunting-related recreational firearm use on physiological and perceptual tests of auditory processing in individuals with normal hearing sensitivity. Therefore, the current findings can at best be compared against results from studies that examine the effects of general recreational noise exposure on auditory percept and physiology in normal hearing sensitivity. Such general recreational noise exposure may or may not include firearm exposure, among various other sources of recreational noise such as concerts, personal audio systems, motorsports, etc. Overall, there is considerable ambiguity in the literature reporting on behavioral and objective auditory measures in normal hearing individuals with low and high levels of recreational noise exposure.
In the current study, brainstem neural representation of F0 as indexed by the FFR was not significantly different in hunter participants as compared to nonhunter participants for any SNR condition. The neural data in the current study are consistent with reports from Grose et al.,[49] Prendergast et al.,[54] and Skoe & Tufts.[55] Grose et al.[49] found no differences in EFR data between listeners with and without a history of attending loud concerts. Similarly, no group differences were observed when contrasting suprathreshold (75–80 dB SPL) click-ABR wave I amplitude between listeners with low versus high noise exposure.[54],[55] To the best of our knowledge, there are no studies contrasting MEMR measurements between individuals with low and high degrees of recreational noise exposure that provide evidence of synaptopathy. However, the tonal MEMR threshold data in the current study follow similar patterns as noted by Guest et al.,[78] who reported no differences in tonal MEMR thresholds in individuals with and without tinnitus, a correlate of noise-induced synaptopathy. As with the physiological measures, non-hunters performed similarly to hunters on all but one aspect of one of the behavioral tests of auditory processing, the Competing Sentences Test. When scaled scores of the Competing Sentences Test were considered, nonhunter participants returned significantly higher (better) scores than hunter participants; however, no group effect was observed for ear-specific raw scores of this test. In general, the minimal differences in auditory processing between nonhunter and hunter participants observed in the current study are in alignment with the outcomes described in Grinn et al.[48] and Grose et al.,[49] which suggest little-to-no association between recreational noise exposure and cochlear synaptopathy. Grinn et al.[48] reported a decrease in the Words In Noise (WIN) test scores in participants 4 days following attending a loud event; however, scores were not significantly different from baseline 1 week postnoise exposure. Similarly, Grose et al.[49] found no differences in performance on spectral and temporal modulation detection, interaural phase differences detection, consonant nucleus consonant (CNC) phoneme recognition, and speech in noise recognition using Bamford-Kowal-Bench (BKB) sentences between listeners with and without a history of attending loud concerts.
In contrast to the results presented here, a handful of studies[45],[46],[52],[55] have described perceptual and physiological outcomes that are potentially consistent with synaptopathy in individuals with normal hearing sensitivity and a history of recreational noise exposure. Bharadwaj et al.[45] reported higher (poorer) AM and interaural time difference (ITD) thresholds, and steeper slopes for EFR amplitude with modulation depth obtained by presenting AM tones in notched noise with varying modulation depths in listeners with a history of participating in loud recreational activities. Along similar lines, Liberman et al.[52] found poorer scores when NU-6 words were presented with background noise, and a greater SP/AP ratio in response to a suprathreshold (94.5 dB nHL) click-ABR in music-performance students deemed “high-risk” versus nonmusic performance students classified as “low-risk.” Likewise, Skoe & Tufts[55] reported delayed ABR wave V latencies in individuals classified as a “high-noise exposure” group based on a week of dosimetry data. Additionally, Bramhall et al.[46] described reduced ABR wave I amplitudes in non-Veterans with a history of nonoccupational/recreational firearm use as compared to non-Veterans who reported no firearm use. Finally, though not directly comparing groups with high and low recreational noise exposure, Wojtczak et al.[77] have observed lower wideband MEMR magnitudes in listeners with noise-induced tinnitus as compared to those without, suggesting a potential role for the MEMR in identification of synaptopathy.
The absence of a group effect on performance on the behavioral and neural auditory measures observed in the current study can be attributed to the following reasons:- Noise exposure from hunting-related recreational firearm use does not result in synaptopathy in young listeners with normal hearing sensitivity
- Noise exposure from hunting-related recreational firearm use results in subtle and variable synaptopathic changes
- Physiological and behavioral procedures used were insensitive to changes in auditory processing following noise exposure from hunting-related recreational firearm use
Noise exposure from hunting-related recreational firearm use does not result in synaptopathy in young listeners with normal hearing sensitivity
First, one must consider the possibility that noise exposure from hunting-related recreational firearm use may not, by itself, precipitate significant synaptopathic changes in young human listeners with normal hearing sensitivity. It has been suggested that synaptopathy in human listeners may occur consequent to aging, or due to interactions between age and noise exposure, or only following noise intensity levels sufficient to cause permanent threshold shifts.[50],[53] Thus, the lack of group effects in the current study may, in part, be driven by the age and hearing acuity of the participants; all of whom were young adults less than 30 years of age, with normal hearing sensitivity. Further, animal work has suggested species-specific abilities in recovery from and resistance to noise-induced synaptopathy. For instance, though synaptic loss is permanent in mice post noise exposure, synapses in guinea pigs demonstrate an ability to recover to a certain extent following an initial reduction after noise exposure, albeit with remaining functional deficits.[126],[127] Further resistance to synaptic loss following noise exposure has been noted in nonhuman primates (e.g., macaques).[128] Based on increased cortical neural plasticity seen in humans as compared to rodents in studies of synaptic protein composition,[129],[130] Yeend et al.[60] hypothesize that human listeners may demonstrate high levels of synaptic repair post noise exposure. At the moment, it is unclear where human listeners lie along this spectrum of synaptic vulnerability following noise exposure.[50],[53] To date, there is only one published study[46] that discusses the possibility of synaptopathic changes in the auditory system following recreational firearm use, reflected in reduced wave I amplitudes in the suprathreshold click-ABR in the presence of normal hearing thresholds. However, as previously discussed, it is thought that the low spontaneous rate/high threshold auditory nerve fibers that are affected in synaptopathy have a minimal role to play in ABR wave I generation.[67] Further, ABR wave I amplitudes may also be affected as a consequence of isolated IHC loss, slight OHC loss that may not be captured by OAE testing, or auditory nerve damage unrelated to synaptopathy.[46] Thus, it remains unclear if diminished ABR wave I amplitudes observed in recreational firearm users are associated with cochlear synaptopathy. Apart from data from Bramhall et al.,[46] there is no other published evidence confirming synaptopathic changes following recreational firearm use.
Noise exposure from hunting-related recreational firearm use results in subtle and variable synaptopathic changes
Second, it could also be possible that synaptopathic changes do occur following exposure to recreational firearm use during hunting; however, these changes might be miniscule in nature and vary significantly across participants and test protocols. Variability in the manifestation of synaptopathy in human listeners could stem from a number of factors, including but not limited to, cell biology, genetics, anatomy, age, sex, noise exposure history, use of hearing protection, and the specific test protocols utilized. There is greater variation in synaptic proteins in human listeners as compared to rodents.[130] Further, it is possible that spiral ganglion cell death post noise exposure follows a longer time course in human listeners as compared to animals.[130] Yeend et al.[60] suggest that this extended timeline can offer opportunities for both synaptic repair as well as further damage due to additional noise exposures, which can lead to more variation across listeners. Differences in genetics, anatomy (e.g., ear-canal length), and inherent susceptibility to noise exposure (see Yeend et al.[60] for a detailed review) may also contribute to intersubject variability in perceptual and physiological outcomes following noise exposure. As compared to animal studies where the type, intensity, frequency, and duration of noise exposure can be homogenized, nature of noise exposure can span a wide range in human listeners and influence the extent of auditory deficits, if they occur. Participants in the current study were classified into the nonhunter or hunter groups based on a self-report of hunting. However, it is possible that individuals in either group could have been exposed in varying degrees to other forms of recreational, occupational, or environmental noise. Indeed, two participants in the nonhunter group reported recreational firearm noise exposure unrelated to hunting. Further, if all participants were exposed to a baseline level of environmental or nonfirearm related noise, it could potentially cause similar auditory changes in both groups of listeners, thus resulting in a lack of group differences on the study measures. One might argue that if this were the case, LAeq scores in the nonhunter group should have captured such high levels of noise exposure. As such, there were no participants in the nonhunter group whose LAeq scores exceeded 79, the cut-off score for risk for NIHL proposed by Johnson et al.[87] Indeed, LAeq scores were consistently lower (better) in the nonhunter group as compared to the hunter participants. That said, it should be noted that the LAeq score derived from the NEQ[87] reflects noise exposure arising from a set of defined activities occurring only in the preceding year. It is possible that participants could be exposed to sources of noise not included in the NEQ, or that occurred in timeframes outside the year under question, that could have influenced the results. Such variations related to noise exposure are also applicable to participants within the hunter group. Additionally, Bramhall et al.[65] suggest that synaptopathy risk may increase with the intensity level of noise exposure. Firearm discharge results in peak SPLs ranging from 140 to 175 dB SPL.[4] Given the higher noise levels associated with firearms use as compared to say, use of personal music players (105–113 dBA)[131] one would predict that individuals such as hunters who engage with firearms would be at greater risk for synaptopathy. However, the effects of noise exposure on the auditory system are dependent on not only intensity level, but also the frequency and duration of exposure, and use of hearing protection.[132] In the current study, participants were included if they confirmed in engaging in hunting with firearm use. However, they were not queried on frequency and duration of hunting. Moreover, the type and fit of hearing protection, if used, and frequency and duration of their use can influence level of attenuation of the impulse noise associated with firearm use (see Meinke et al.[4] for a detailed review of hearing protection specific to hunting). This in turn may affect the extent of noise-induced changes in the auditory system. Although the use (or lack thereof) of hearing protection during hunting was noted in the current study, further details regarding device type, fit, and use were not obtained. Thus, variability related to participant characteristics, nature of noise exposure, use of hearing protection may, at least partially, account for the null results in the current study, as well as the mixed findings in the broader human synaptopathy literature. It is important to add that variability in experimental outcomes in studies of synaptopathy could also be attributed to differences in test protocols across studies. These studies have included a range of behavioral and electrophysiological measures, as well as different methods of estimating noise exposure (see LePrell[133] for a review). The lack of consistent test protocols renders it challenging to compare data across studies.
Physiological and behavioral procedures used were insensitive to changes in auditory processing following noise exposure from hunting-related recreational firearm use
Finally, it is possible that the electrophysiological and behavioral procedures used in the current study were simply not sensitive enough to reflect deficits in auditory processing following recreational firearm use. In the current study, FFRs were obtained to a vowel presented with and without competing multitalker babble, a departure from the transposed tone stimulus design used in previous FFR-based studies of cochlear synaptopathy. The vowel in noise was selected for a variety of reasons, including its ecological relevance, the fundamental frequency and its relationship to limits of brainstem neural phase-locking, the amplitude modulated nature and intensity level of the stimulus, and potential to reflect brainstem neural phase-locking to both F0 and formant frequencies. Due to stimulus set-up constraints in the signal generation platform used, FFRs in the current study were recorded using a single polarity (rarefaction), which precluded the derivation of envelope and spectral FFRs. All spectral energy in voiced speech is amplitude modulated at F0; thus, energy at F0 in the FFRs measured in the current study may arise from envelope modulation at F0 due to interaction between any two consecutive harmonics, and therefore reflect function of any place along the cochlear partition. FFR F0 energy could also reflect place-specific brainstem neural phase-locking to the first harmonic, which is the stimulus F0. Finally, cochlear nonlinearities can generate intermodulation distortion products at the cubic difference tone (e.g., 2f1–f2) or difference frequencies (e.g., f2–f1, f14–f8), which may contribute to spectral energy at F0 in the neural response.[82],[134] Ultimately, though F0 measurements made in FFRs recorded in this study elicited by this particular stimulus might reflect function of low spontaneous rate/high threshold fibers to a certain extent, they cannot be mapped to function of these fibers in a specific frequency region on the basilar membrane. Further, although the competing multitalker babble used here mimics real-world situations, the spectral composition of the babble was not specifically configured to act as an “off-frequency” masker for the target F0. Hence, the lack of group differences for the FFR observed here could reflect an inadequate stimulus design rather than an absence of synaptopathy. That said, apart from Bharadwaj et al.,[45] EFR data obtained using the more traditionally utilized transposed tones have not reflected evidence for synaptopathy in human listeners with recreational noise exposure either. Another factor with potential to influence study outcomes is the response analysis technique. Absolute FFR/EFR measurements can be affected by differences in response phase across channels, variations in noise-floor across individuals, and subject-to-subject contrasts in response amplitude with changing stimulus parameters such as modulation depth.[45] A number of analysis techniques have been utilized to mitigate the effects of such extraneous variables on FFR metrics, including the use of principal component analysis, phase-locking value (PLV) measures, and normalization of neural responses by dividing the FFR/EFR amplitude by modulation depth.[45] In the current study, variation in noise-floor across individuals was accounted for by dividing the spectral energy at F0 in the neural response for each participant by the noise floor, also estimated for each participant. However, FFR data were collapsed across the recording channels. Although this was done on the basis of previous evidence suggesting high correlations in the neural response between the specific recording channels used in this study,[95] the potential impact, even if minimal, for phase differences occurring between channels on the collapsed FFR data cannot be ruled out. Further, the current analysis was conducted entirely in the spectral domain; time-domain analyses may offer additional perspective on these data. Thus, if synaptopathy does occur following recreational noise exposure, the overall lack of differences in FFR/EFR measurements between high- and low-noise exposed groups in the current and previous studies reiterates the need to establish if the FFR/EFR is indeed a feasible technique to capture such synaptopathy. The answer to this question lies partly in identification of appropriate stimulus and recording parameters, and optimal response analysis technique(s).
Likewise, the absence of a group effect on tonal MEMR thresholds observed in the current study could be ascribed to an insufficient MEMR protocol. MEMR studies that have obtained results consistent with synaptopathy have utilized wideband probes and reflex elicitors,[72],[75],[76],[77] as compared to the standard clinical protocol utilizing tonal stimuli implemented in the current study. It has been argued that the probe frequency utilized can affect MEMR thresholds,[135] and that wideband MEMR measurements demonstrate increased sensitivity to changes in middle-ear impedance than tonal MEMR procedures[136],[137],[138] (see Wojtczak et al.[77] for a detailed review). It is also possible, as discussed by Guest et al.,[78] that the frequency range assessed by the tonal reflex elicitors in the current study (500–2000 Hz) did not overlap with the frequency region likely to be affected by affected by synaptopathic changes (3–6 kHz). Lastly, differences in the dependent variable (MEMR magnitude vs. MEMR threshold) could account for the inconsistencies observed across MEMR studies.
Similar to the physiologic data, there were no differences in performance between nonhunter and hunter participants on ear-specific performance for any of the 10 behavioral tests used in the current study. Assuming synaptopathic changes can be observed as suprathreshold perceptual deficits, the current outcome could be attributed to stimulus design. Behavioral stimuli included both speech (digits, words, sentences) and nonspeech (low and high pitches, tones in noise, gaps in noise) signals presented at suprathreshold levels in a variety of complex listening environments (e.g., multitalker babble, low-pass filtering, time compression, reverberation). The stimuli and listening conditions used here mimic challenging real-world listening situations, and the intensity levels used likely recruit the low spontaneous rate/high threshold fibers of interest in synaptopathy. However, the competing signals utilized in these tests (single competing speaker, multitalker babble, narrow-band noise, broadband noise) are not specifically spectrally or temporally designed to act as off-frequency maskers, a feature of optimal stimulus design to measure synaptopathy as discussed by Bharadwaj et al.[45] Here it is important to note that it is currently unknown if and how noise-induced physiological changes, even if they do occur, are translated into perceptual deficits in individuals with normal hearing sensitivity.[47] Indeed, modeling work has demonstrated that suprathreshold auditory perception may remain unaffected even with significant damage to auditory neurons.[139] As an example, a 50% synaptic loss would result in a shift of a just-noticeable-difference of 1 dB to 1.4 dB. It is possible, as posited by Carney,[140] that suprathreshold speech perception may be driven factors other than synaptopathic changes at the level of the auditory nerve, such as cochlear gain, IHC saturation, and rate-based neural encoding mechanisms at the midbrain. If this is indeed the case, and if the presence or absence of synaptopathy was the only differentiating factor between the nonhunter and hunter participants in the current study, the lack of group differences on suprathreshold tests of behavioral auditory processing are not unexpected. Finally, another possibility that could account for the current results is that performance on tests of behavioral auditory processing is modulated by higher-order mechanisms. The tests used here examine a wide range of auditory behaviors (auditory closure, temporal processing, dichotic listening, binaural processing); many of these behaviors could rely on higher functions such as memory, cognition, attention, and language processing.[141] Thus, performance on these behavioral tests could reflect a combination of bottom-up sensory encoding as well as top-down processing abilities, rather than purely synaptopathic deficits. Ultimately, this could result in a robust auditory percept that is resistant to physiological changes at the auditory nerve level. The nonmodular nature of auditory processing may also explain why poorer performance has been consistently documented in Veterans with blast exposure, as compared to those without, on many of the same tests included in the current study (Time Compressed Speech Test (TCST), FPT, GIN, DDT, MLD; see Tepe et al.[142] for a review). Clearly, these data reflect occupational noise exposure, and noise exposures beyond that from routine firearm use. However, beyond differences in the type, frequency, and duration of noise exposure, the physiological (e.g., traumatic brain injury) and psychological (e.g., posttraumatic stress disorder) changes experienced by the Veteran population as a consequence of such exposures[142],[143] are vastly different from those experienced by a civilian engaged in recreational firearm use, and may hence have different consequences on auditory perception.
Effects of listening condition and test ear
Although group effects were nonexistent in the current study, effects of listening condition and test ear were observed for certain tests. Effects of listening condition were noted for the AFG (0, +8, +12 dB SNR), TCRS (45% and 65% time compression), MLD (SₒNₒ and SπNₒ), and the FFR (clean, +5, 0, −5 dB SNR). In general, performance declined as a function of listening condition difficulty, for both nonhunter and hunter participants. That is, AFG scores were poorer in the 0 dB SNR as compared to +12 dB SNR conditions, TCRS scores were reduced when stimuli were time-compressed by 65% as compared to 45%, and thresholds were lower (worse) in the SₒNₒ condition as compared to the SπNₒ condition. Overall, this pattern of results is consistent with the idea that participant performance on perceptual tasks decreases as test difficulty increases.[144] Similarly, brainstem neural representation of F0 declined with reducing SNR. Again, this result is in alignment with the findings of Russo et al.[145] and Song et al.,[146] who demonstrated a reduction in neural encoding of F0 amplitude with the introduction of background noise, although F0 amplitude was generally more robust to the effects of noise as compared to other FFR measures in these studies. Ear effects were seen on two tests of dichotic listening, the CST and CWDE test, such that performance in the right ear was better than that in the left ear. The right-ear advantage in dichotic listening tasks is expected and well established, and is attributed to: 1) the dominant role of the left hemisphere in language processing, and 2) stronger contralateral pathways in the auditory system.[147]
Limitations and future directions
One of the primary limitations of the current study was the low sample size, which could have affected the statistical power of the analyses. The relatively low number of participants in the current study can be ascribed to challenges related to subject recruitment. Participation in hunting differs significantly in urban versus rural populations.[148] Statistics from the United States Fish and Wildlife Services and the United States Census Bureau[149] indicate that greatest participation in hunting occurs in areas with a population < 50,000 and the least occurs in areas with populations > 1 million (for a detailed summary, see Wilkins et al.[148]). For the current study, the majority of the participants were recruited from Baltimore County, with a population of approximately 849,316; this may explain the challenge associated with subject recruitment that resulted in the small sample size. Second, the majority of the participants were male. Future studies should recruit a larger sample size where participants are matched for age and sex. A third limitation was that participants were grouped into the nonhunter and hunter categories by reporting whether or not they engaged in hunting in the past year, but additional details regarding the type, frequency, and duration of firearms exposure, as well as type and use of hearing protection were not obtained. Fourth, two of the 10 non-hunters disclosed nonhunting related recreational firearm use and consequently qualified to be at high risk for NIHL based on the NEQ. As such, the statistical outcomes in the current study were similar regardless of participant grouping (hunting history, hunting history adjusted for general recreational firearm use, or general firearm use), but adequate querying of general recreational firearm use (apart from hunting) is essential. Fifth, participants’ noise exposure history was documented only for the immediate year preceding experiment participation using the NEQ; prior noise exposure from hunting-related or other recreational firearm use was not considered. A sixth limitation of the study was related to the stimulus design and test protocol across physiologic and perceptual measurements. Deriving both the envelope and spectral FFRs will allow for a comparison of brainstem neural representation of F0 as well as stimulus harmonics critical for speech perception in noise, in noise-exposed listeners. This would be especially relevant given that brainstem neural phase-locking to F0 and stimulus harmonics is impacted differentially by the introduction of competing signals. Additionally, future work should examine physiological response strength in recreational firearm users using stimulus designs that allow for an examination of the 3 to 6 kHz region on the basilar membrane that is known to be most impacted by noise exposure. This may include use of transposed tones for FFR recordings, and wideband probes and elicitors for MEMR measurements. On a related note, stimulus design should be revisited for behavioral tests so that performance on these tests reflects specific physiological changes thought to occur in synaptopathy, to the maximum extent possible. Extended high-frequency audiometric thresholds are known to be an early index of NIHL, but could not be obtained in the current study due to equipment constraints. Such high-frequency hearing acuity measures would be a valuable addition to the test battery. Finally, in addition to behavioral tests and neural measures of brainstem function, future work should consider the inclusion of cortical auditory evoked potentials to ensure a systems-level approach to address the issue of synaptopathy in recreational firearm use.
| Conclusions | | |
In summary, the present results showed no differences in auditory physiological metrics (indexed by the FFR and tonal MEMR) or performance on perceptual auditory tasks in human listeners with and without a history of recreational firearm noise exposure due to hunting. The patterns of data observed here could reflect an absence of cochlear synaptopathy in the population studied, variability related to participant characteristics and/or test protocols, or an insensitivity of the selected physiological and behavioral auditory measures to noise-induced synaptopathy.
INSTITUTIONAL REVIEW BOARD APPROVAL: All participants were paid for their participation and provided informed consent in compliance with a protocol approved by the Institutional Review Board at Towson University.
DISCLOSURES: This research was funded by the Graduate Student Association at Towson University.
Acknowledgments
S. A. designed the experiment. C.M. and L.M. collected all data and conducted preliminary data analysis. S. A. analyzed the data. S.A, C.M. and L.M. wrote the paper. C.M. and L.M. contributed equally to the paper. The authors wish to thank Dr. Gavin M. Bidelman (University of Memphis), Dr. Christopher J. Smalt (MIT Lincoln Laboratory) and Mr. Venkatakrishnan Vijayaraghavan for assistance with MATLAB coding. The authors also wish to thank Ms. Radhika Kansangra for assistance with manuscript formatting and creation of tables. Research was supported by the Graduate Student Award (GSA) funding mechanism at Towson University and the Department of Speech-Language Pathology and Audiology of Towson University. This article is based on two theses submitted by C.M. and L.M. in partial fulfillment of the requirements for the degree of Doctor of Audiology at Towson University.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
| References | | |
| 1. | Basner M, Babisch W, Davis A et al. Auditory and non-auditory effects of noise on health. Lancet 2014;383:1325–32.  |
| 2. | Henderson D, Bielefeld EC, Harris KC, Hu BH. The role of oxidative stress in noise-induced hearing loss. Ear Hear 2006;27:1–19. |
| 3. | Keppler H, Dhooge I, Vinck B. Hearing in young adults. Part II: the effects of recreational noise exposure. Noise Health 2015;17:245–52. |
| 4. | Meinke DK, Finan DS, Flamme GA et al. Prevention of noise-induced hearing loss from recreational firearms. Semin Hear 2017;38:267–81. |
| 5. | Gopal KV, Mills LE, Phillips BS, Nandy R. Risk assessment of recreational noise-induced hearing loss from exposure through a personal audio system—iPod Touch. J Am Acad Audiol 2019;30:619–33. |
| 6. | Ryan AF, Kujawa SG, Hammill T, Le Prell C, Kil J. Temporary and permanent noise-induced threshold shifts: a review of basic and clinical observations. Otol Neurotol 2016;37:e271–e5. |
| 7. | Eldredge DH, Mills JH, Bohne BA. Anatomical, behavioral, and electrophysiological observations on chinchillas after long exposures to noise. Adv Otorhinolaryngol 1973;20:64–81. |
| 8. | Lonsbury‐Martin BL, Martin GK, Bohne BA. Repeated TTS exposures in monkeys: alterations in hearing, cochlear structure, and single‐unit thresholds. J Acoust Soc Am 1987;81:1507–18. |
| 9. | Ryan A, Bone RC. Noise‐induced threshold shift and cochlear pathology in the mongolian gerbil. J Acoust Soc Am 1978;63:1145–51. |
| 10. | Axelsson A, Prasher D. Tinnitus induced by occupational and leisure noise. Noise Health 2000;2:47–54. [ PUBMED] [Full text] |
| 11. | Axelsson A, Sandh A. Tinnitus in noise-induced hearing loss. Br J Audiol 1985;19:271–6. |
| 12. | Bohlin MC, Erlandsson SI. Risk behaviour and noise exposure among adolescents. Noise Health 2007;9:55–63. [ PUBMED] [Full text] |
| 13. | Davis AC, Lovell EA, Smith PA, Ferguson MA. The contribution of social noise to tinnitus in young people-a preliminary report. Noise Health 1998;1:40. [ PUBMED] [Full text] |
| 14. | Gilles A, Van Hal G, De Ridder D, Wouters K, Van de Heyning P. Epidemiology of noise-induced tinnitus and the attitudes and beliefs towards noise and hearing protection in adolescents. PloS One 2013;8:e70297. |
| 15. | Widen SO, Erlandsson SI. Self-reported tinnitus and noise sensitivity among adolescents in Sweden. Noise Health 2004;7:29. |
| 16. | Kujawa SG, Liberman MC. Synaptopathy in the noise-exposed and aging cochlea: primary neural degeneration in acquired sensorineural hearing loss. Hear Res 2015;330:191–9. |
| 17. | United States Occupational Safety and Health Administration (OSHA). Occupational noise exposure; hearing conservation amendment; final rule (29 CFR 1910. 95). Federal Register 1983;48:9738–85. |
| 18. | Neitzel RL, Fligor BJ. Risk of noise-induced hearing loss due to recreational sound: review and recommendations. J Acoust Soc Am 2019;146:3911–21. |
| 19. | Clark WW. Noise exposure from leisure activities: a review. J Acoust Soc Am 1991;90:175–81. |
| 20. | |
| 21. | Koeppel MD, Nobles MR. Understanding female gun ownership: 1973–2010. Fem Criminol 2017;12:43–71. |
| 22. | United States Fish & Wildlife Service. 2016 National survey of fishing, hunting and wildlife-Associated Recreation [Data Set]. United States Department of the Interior. 2018. |
| 23. | United States Fish & Wildlife Service. Historical hunting license data for 2021. Wildlife and Sport Fish Recreation Program. 2021. |
| 24. | Ivory R, Kane R, Diaz RC. Noise-induced hearing loss: a recreational noise perspective. Curr Opin Otolaryngol Head Neck Surg 2014;22:394–8. |
| 25. | |
| 26. | National Institute for Occupational Safety and Health (NIOSH). Revised criteria for a recommended standard: Occupational noise exposure. U.S. Department of Health and Human Services, Public Health Service, Centers for Disease Control and Prevention. Cincinnati, USA. 1998;98–126. |
| 27. | Chan P, Ho K, Ryan AF. Impulse noise injury model. Mil Med 2016; 181(suppl_5):59–69. |
| 28. | Hamernik RP, Ahroon WA, Hsueh KD, Lei SF, Davis RI. Audiometric and histological differences between the effects of continuous and impulsive noise exposures. J Acoust Soc Am 1993;93:2088–95. |
| 29. | Hamernik RP, Ahroon WA, Patterson Jr JA. Threshold recovery functions following impulse noise trauma. J Acoust Soc Am 1988;84:941–50. |
| 30. | Henderson D, Hamernik RP. Impulse noise: critical review. J Acoust Soc Am 1986;80:569–84. |
| 31. | Axelsson A, Lindgren F. Pop music and hearing. Ear Hear 1981;2:64–9. |
| 32. | Hoffman HJ, Dobie RA, Losonczy KG, Themann CL, Flamme GA. Declining prevalence of hearing loss in US adults aged 20 to 69 years. JAMA Otolaryngol Head Neck Surg 2017;143:274–85. |
| 33. | Kramer MB, Wood D. Noise-induced hearing loss in rural schoolchildren. Scand Audiol 1982;11:279–80. |
| 34. | Nondahl DM, Cruickshanks KJ, Wiley TL, Klein R, Klein BE, Tweed TS. Recreational firearm use and hearing loss. Arch Fam Med 2000;9:352. |
| 35. | Taylor GD, Williams E. Acoustic trauma in the sports hunter. Laryngoscope 1966;76:863–79. |
| 36. | Toynbee J. The diseases of the ear. Blanchard and Lea. 1860. |
| 37. | Updike CD. Hearing loss in recreational shooters. Hearing J 1990;43:22–4. |
| 38. | Griest SE, Bishop PM. Tinnitus as an early indicator of permanent hearing loss: a 15 year longitudinal study of noise exposed workers. AAOHN 1998;46:325–9. |
| 39. | Stewart M, Borer SE, Lehman M. Shooting habits of US waterfowl hunters. Noise Health 2009;11:8. [ PUBMED] [Full text] |
| 40. | Stewart M, Meinke DK, Snyders JK, Howerton K. Shooting habits of youth recreational firearm users. Int J Audiol 2014;53:S26–S34. |
| 41. | Ahmed MM, Allard RJ, Esquivel CR. Noise-induced hearing loss treatment: systematic review and meta-analysis. Mil Med 2022;187:e661–e666. |
| 42. | Kujawa SG, Liberman MC. Adding insult to injury: cochlear nerve degeneration after “temporary” noise-induced hearing loss. J Neurosci 2009;29:14077–85. |
| 43. | Kobel M, Le Prell CG, Liu J, Hawks JW, Bao J. Noise-induced cochlear synaptopathy: past findings and future studies. Hear Res 2017;349:148–54. |
| 44. | Hickman TT, Smalt C, Bobrow J, Quatieri T, Liberman MC. Blast-induced cochlear synaptopathy in chinchillas. Sci Rep 2018;8:10740. |
| 45. | Bharadwaj HM, Masud S, Mehraei G, Verhulst S, Shinn-Cunningham BG. Individual differences reveal correlates of hidden hearing deficits. J Neurosci 2015;35:2161–72. |
| 46. | Bramhall NF, Konrad-Martin D, McMillan GP, Griest SE. Auditory brainstem response altered in humans with noise exposure despite normal outer hair cell function. Ear Hear 2017;38:e1. |
| 47. | Fulbright AN, Le Prell CG, Griffiths SK, Lobarinas E. Effects of recreational noise on threshold and suprathreshold measures of auditory function. Semin Hear 2017;38:298–318. |
| 48. | Grinn SK, Wiseman KB, Baker JA, Le Prell CG. Hidden hearing loss? No effect of common recreational noise exposure on cochlear nerve response amplitude in humans. Front Neurosci 2017;11:465. |
| 49. | Grose JH, Buss E, Hall Iii JW. Loud music exposure and cochlear synaptopathy in young adults: isolated auditory brainstem response effects but no perceptual consequences. Trends Hear 2017;21:2331216517737417. |
| 50. | Guest H, Munro KJ, Plack CJ. Tinnitus with a normal audiogram: role of high-frequency sensitivity and reanalysis of brainstem-response measures to avoid audiometric over-matching. Hear Res 2017;356:116. |
| 51. | Guest H, Munro KJ, Prendergast G, Millman RE, Plack CJ. Impaired speech perception in noise with a normal audiogram: no evidence for cochlear synaptopathy and no relation to lifetime noise exposure. Hear Res 2018;364:142–51. |
| 52. | Liberman MC, Epstein MJ, Cleveland SS, Wang H, Maison SF. Toward a differential diagnosis of hidden hearing loss in humans. PloS One 2016;11:e0162726. |
| 53. | Prendergast G, Millman RE, Guest H et al. Effects of noise exposure on young adults with normal audiograms II: behavioral measures. Hear Res 2017;356:74–86. |
| 54. | Prendergast G, Tu W, Guest H et al. Supra-threshold auditory brainstem response amplitudes in humans: test-retest reliability, electrode montage and noise exposure. Hear Res 2018;364:38–47. |
| 55. | Skoe E, Tufts J. Evidence of noise-induced subclinical hearing loss using auditory brainstem responses and objective measures of noise exposure in humans. Hear Res 2018;361:80–91. |
| 56. | Spankovich C, Le Prell CG, Lobarinas E, Hood LJ. Noise history and auditory function in young adults with and without type 1 diabetes mellitus. Ear Hear 2017;38:724–35. |
| 57. | Stamper GC, Johnson TA. Auditory function in normal-hearing, noise-exposed human ears. Ear Hear 2015a;36:172. |
| 58. | Stamper GC, Johnson TA. Letter to the editor: examination of potential sex influences in auditory function in normal-hearing, noise-exposed human ears. Ear Hear 2015b;36:738–40. |
| 59. | Valderrama JT, Beach EF, Yeend I, Sharma M, Van Dun B, Dillon H. Effects of lifetime noise exposure on the middle-age human auditory brainstem response, tinnitus and speech-in-noise intelligibility. Hear Res 2018;365:36–48. |
| 60. | Yeend I, Beach EF, Sharma M, Dillon H. The effects of noise exposure and musical training on suprathreshold auditory processing and speech perception in noise. Hear Res 2017;353:224–36. |
| 61. | Bramhall N, Beach EF, Epp B et al. The search for noise-induced cochlear synaptopathy in humans: mission impossible? Hear Res 2019;377:88–103. |
| 62. | Lin HW, Furman AC, Kujawa SG, Liberman MC. Primary neural degeneration in the Guinea pig cochlea after reversible noise-induced threshold shift. J Assoc Res Otolaryngol 2011;12:605–16. |
| 63. | Sergeyenko Y, Lall K, Liberman MC, Kujawa SG. Age-related cochlear synaptopathy: an early-onset contributor to auditory functional decline. J Neurosci 2013;33:13686–94. |
| 64. | Ridley CL, Kopun JG, Neely ST, Gorga MP, Rasetshwane DM. Using thresholds in noise to identify hidden hearing loss in humans. Ear Hear 2018;39:829. |
| 65. | Bramhall NF, McMillan GP, Kampel SD. Envelope following response measurements in young Veterans are consistent with noise-induced cochlear synaptopathy. Hear Res 2021;408:108310. |
| 66. | Verhulst S, Altoe A, Vasilkov V. Computational modeling of the human auditory periphery: auditory-nerve responses, evoked potentials and hearing loss. Hear Res 2018;360:55–75. |
| 67. | Bourien J, Tang Y, Batrel C et al. Contribution of auditory nerve fibers to compound action potential of the auditory nerve. J Neurophysiol 2014;112:1025–39. |
| 68. | Liberman MC, Klang NYS. Single-neuron labeling and chronic cochlear pathology. IV. Stereocilia damage and alterations in rate-and phase-level functions. Hear Res 1984;16:75–90. |
| 69. | Kobler JB, Guinan Jr JJ, Vacher SR, Norris BE. Acoustic reflex frequency selectivity in single stapedius motoneurons of the cat. J Neurophysiol 1992;68:807–17. |
| 70. | Valero MD, Hancock KE, Liberman MC. The middle ear muscle reflex in the diagnosis of cochlear neuropathy. Hear Res 2016;332:29–38. |
| 71. | Valero MD, Hancock KE, Maison SF, Liberman MC. Effects of cochlear synaptopathy on middle-ear muscle reflexes in unanesthetized mice. Hear Res 2018;363:109–18. |
| 72. | Bramhall N, Reavis KM, Feeney MP, Kampel SD. The impacts of noise exposure on the middle ear muscle reflex in a Veteran population. Am J Audiol 2022;31:126–42. |
| 73. | Billings CJ, Dillard LK, Hoskins ZB, Penman TM, Reavis KM. A large-scale examination of Veterans with normal pure-tone hearing thresholds within the Department of Veterans Affairs. J Am Acad Audiol 2018;29:928–35. |
| 74. | Houghton JM, Greville KA, Keith WJ. Acoustic reflex amplitude and noise-induced hearing loss. Audiology 1988;27:42–8. |
| 75. | Shehorn J, Strelcyk O, Zahorik P. Associations between speech recognition at high levels, the middle ear muscle reflex and noise exposure in individuals with normal audiograms. Hear Res 2020;392:107982. |
| 76. | Mepani AM, Kirk SA, Hancock KE et al. Middle-ear muscle reflex and word-recognition in “normal hearing” adults: evidence for cochlear synaptopathy?. Ear Hear 2020;41:25. |
| 77. | Wojtczak M, Beim JA, Oxenham AJ. Weak middle-ear-muscle reflex in humans with noise-induced tinnitus and normal hearing may reflect cochlear synaptopathy. eNeuro 2017;4: ENEURO. 0363–17.2017. |
| 78. | Guest H, Munro KJ, Prendergast G, Plack CJ. Reliability and interrelations of seven proxy measures of cochlear synaptopathy. Hear Res 2019;375:34–43. |
| 79. | Chandrasekaran B, Kraus N. The scalp‐recorded brainstem response to speech: neural origins and plasticity. Psychophysiol 2010;47:236–46. |
| 80. | Krishnan A. Human frequency following response. Auditory evoked potentials: Basic principles and clinical application. 2007;313–35. |
| 81. | Krizman J, Kraus N. Analyzing the FFR: a tutorial for decoding the richness of auditory function. Hear Res 2019;382:107779. |
| 82. | Aiken SJ, Picton TW. Envelope and spectral frequency-following responses to vowel sounds. Hear Res 2018;245(1-2):35–47. |
| 83. | Parthasarathy A, Kujawa SG. Synaptopathy in the aging cochlea: characterizing early-neural deficits in auditory temporal envelope processing. J Neurosci 2018;38:7108–19. |
| 84. | Shaheen LA, Valero MD, Liberman MC. Towards a diagnosis of cochlear neuropathy with envelope following responses. J Assoc Res Otolaryngol 2015;16:727–45. |
| 85. | Bharadwaj HM, Verhulst S, Shaheen L, Liberman MC, Shinn-Cunningham BG. Cochlear neuropathy and the coding of supra-threshold sound. Front Syst Neurosci 2014;8:26. |
| 86. | Encina-Llamas G, Harte JM, Dau T, Shinn-Cunningham B, Epp B. Investigating the effect of cochlear synaptopathy on envelope following responses using a model of the auditory nerve. J Assoc Res Otolaryngol 2019;20:363–82. |
| 87. | Johnson TA, Cooper S, Stamper GC, Chertoff M. Noise exposure questionnaire: a tool for quantifying annual noise exposure. J Am Acad Audiol 2017;28:14–35. |
| 88. | ANSI 2010 |
| 89. | Assman P. UTD North Texas Vowel Database. n.d. |
| 90. | Krishnan A. Human frequency-following responses: representation of steady-state synthetic vowels. Hear Res 2002;166:192–201. |
| 91. | Moushegian G, Rupert AL, Stillman RD. Scalp-recorded early responses in man to frequencies in the speech range. Electroencephalogr Clin Neurophysiol 1973;35:665–7. |
| 92. | Kuwada S, Anderson JS, Batra R, Fitzpatrick DC, Teissier N, D’Angelo WR. Sources of the scalp-recorded amplitude-modulation following response. J Am Acad Audiol 2002;13:188–204. |
| 93. | Ananthakrishnan S, Krishnan A, Bartlett E. Human frequency following response: neural representation of envelope and temporal fine structure in listeners with normal hearing and sensorineural hearing loss. Ear Hear 2016;37:e91. |
| 94. | Ananthakrishnan S, Luo X, Krishnan A. Human frequency following responses to vocoded speech. Ear Hear 2017;38:e256. |
| 95. | Ananthakrishnan S, Grinstead L, Yurjevich D. Human frequency following responses to filtered speech. Ear Hear 2021;42:87–105. |
| 96. | Bidelman GM, Bush LC, Boudreaux AM. Effects of noise on the behavioral and neural categorization of speech. Front Neurosci 2020;14:153. |
| 97. | Bidelman GM, Moreno S, Alain C. Tracing the emergence of categorical speech perception in the human auditory system. Neuroimage 2013;79:201–12. |
| 98. | Galbraith GC. Two-channel brain-stem frequency-following responses to pure tone and missing fundamental stimuli. Electroencephalogr Clin Neurophysiol 1994;92:321–30. |
| 99. | Skoe E, Kraus N. Auditory brainstem response to complex sounds: a tutorial. Ear Hear 2010;31:302. |
| 100. | American National Standards Institute. Specification for audiometers. ANSI S3. 6-2010. New York, NY: ANSI; 2010. |
| 101. | American Speech-Language-Hearing Association. Hearing Loss − Beyond Early Childhood. N.d. |
| 102. | Gelfand SA, Piper N. Acoustic reflex thresholds: variability and distribution effects. Ear Hear 1984;5:228–34. |
| 103. | Silman S, Silverman CA. Auditory diagnosis: principles and applications. Academic Press. 1991. |
| 104. | |
| 105. | American Speech-Language-Hearing Association. American Speech-Language-Hearing Association Working Group on Auditory Processing Disorders. Technical report: (Central) auditory processing disorders − Working group on auditory processing disorders. 2005. |
| 106. | Gallun FJ, Diedesch AC, Kubli LR et al. Performance on tests of central auditory processing by individuals exposed to high-intensity blasts. J Rehabil Res Dev 2012;49:1005–25. |
| 107. | Gallun FJ, Lewis M, Folmer RL et al. Chronic effects of exposure to high-intensity blasts: results of tests of central auditory processing. J Rehabil Res Dev 2016;53:705. |
| 108. | Kubli LR, Pinto RL, Burrows HL, Littlefield PD, Brungart DS. The effects of repeated low-level blast exposure on hearing in marines. Noise Health 2017;19:227. [ PUBMED] [Full text] |
| 109. | Saunders GH, Frederick MT, Arnold M, Silverman S, Chisolm TH, Myers P. Auditory difficulties in blast-exposed Veterans with clinically normal hearing. J Rehab Res Dev 2015;52:343–60. |
| 110. | Karlsson A, Rosenhall U. Clinical application of distorted speech audiometry. Scand Audiol 1994;24:155–60. |
| 111. | Keith RW. Development and standardization of SCAN-A: test of auditory processing disorders in adolescents and adults. J Am Acad Audiol 1995;6:286–92. |
| 112. | O’Beirne G, McGaffin AJ, Rickard NA. Development of an adaptive low-pass filtered speech test for the identification of auditory processing disorders. Int J Pediatr Otorhinolaryngol 2012;76:777–82. |
| 113. | Wilson RH, Preece JP, Salamon DL, Sperry JL, Bornstein SP. Effects of time compression and time compression plus reverberation on the intelligibility of Northwestern University Auditory Test No. 6. J Am Acad Audiol 1994;5:269–77. |
| 114. | Musiek FE. Assessment of central auditory dysfunction: the dichotic digit test revisited. Ear Hear 1983;4:79–83. |
| 115. | Musiek FE, Gollegly KM, Kibbe KS, Verkest-Lenz SB. Proposed screening test for central auditory disorders: follow-up on the dichotic digits test. Am J Otol 1991;12:109–13. |
| 116. | Shinn JB. Temporal processing: the basics. Hear J 2003;56:52. |
| 117. | Musiek FE. Frequency (pitch) and duration pattern tests. J Am Acad Audiol 1994;5:265–8. |
| 118. | Musiek FE, Shinn JB, Jirsa R, Bamiou D, Baran JA, Zaidan E. GIN (gaps-in-noise) test performance in subjects with confirmed central auditory nervous system involvement. Ear Hear 2005;26:608–18. |
| 119. | Wilson RH, Moncrieff DW, Townsend EA, Pillion AL. Development of a 500-Hz masking-level difference protocol for clinical use. J Am Acad Audiol 2003;14:1–8. |
| 120. | Bornstein SP, Wilson RH, Cambron NK. Low- and high-pass filtered Northwestern University Auditory Test No. 6 for monaural and binaural evaluation. J Am Acad Audiol 1994;5:259–63. |
| 121. | Keith RW. SCAN 3: A: for Adolescents and Adults: Tests for Auditory Processing Disorders. San Antonio, TX: The Psychological Corp oration; 2009. |
| 122. | Wilson RH, Weakley DG. The 500 Hz masking-level difference and word recognition in multitalker babble for 40- to 89- year-old listeners with symmetrical sensorineural hearing loss. J Am Acad Audiol 2005;16:367–82. |
| 123. | Wilson RH, Moncrieff DW, Townsend EA, Pillion AL. Development of a 500-Hz masking-level difference protocol for clinical use. J Am Acad Audiol 2003;14:1–8. |
| 124. | Biassoni EC, Serra MR, Richter U et al. Recreational noise exposure and its effects on the hearing of adolescents. Part II: Development of hearing disorders. Int J Audiol 2005;44:74–85. |
| 125. | Serra MR, Biassoni EC, Richter U et al. Recreational noise exposure and its effects on the hearing of adolescents. Part I: An interdisciplinary long-term study. Int J Audiol 2005;44:65–73. |
| 126. | Liu L, Wang H., Shi L et al. Silent damage of noise on cochlear afferent innervation in guinea pigs and the impact on temporal processing. PLoS One 2012;7:e49550. |
| 127. | Shi L, Liu L, He T et al. Ribbon synapse plasticity in the cochleae of Guinea pigs after noise-induced silent damage. PloS One 2013;8:e81566. |
| 128. | Burton JA, Valero MD, Hackett TA, Ramachandran R. The use of nonhuman primates in studies of noise injury and treatment. J Acoust Soc Am 2019;146:3770–89. |
| 129. | Bayés À, Collins MO, Croning MD, Van De Lagemaat LN, Choudhary JS, Grant SG. Comparative study of human and mouse postsynaptic proteomes finds high compositional conservation and abundance differences for key synaptic proteins. PloS One 2012;7:1–13. |
| 130. | Pinto JG, Jones DG, Williams CK, Murphy KM. Characterizing synaptic protein development in human visual cortex enables alignment of synaptic age with rat visual cortex. Front Neural Circuits 2015;9:3. |
| 131. | Kim G, Han W. Sound pressure levels generated at risk volume steps of portable listening devices: types of smartphone and genres of music. BMC Public Health 2018;18:1–7. |
| 132. | Rachiotis G, Alexopoulos C, Drivas S. Occupational exposure to noise, and hearing function among electro production workers. Auris Nasus Larynx 2006;33:381–5. |
| 133. | Le Prell CG. Effects of noise exposure on auditory brainstem response and speech-in-noise tasks: a review of the literature. Int J Audiol 2019;58:S3–S32. |
| 134. | Smalt CJ, Krishnan A, Bidelman GM, Ananthakrishnan S, Gandour JT. Distortion products and their influence on representation of pitch-relevant information in the human brainstem for unresolved harmonic complex tones. Hear Res 2012;292:26–34. |
| 135. | Bharadwaj HM, Mai AR, Simpson JM, Choi I, Heinz MG, Shinn-Cunningham BG. Non-invasive assays of cochlear synaptopathy-candidates and considerations. Neuroscience 2019;407:53–66. |
| 136. | Feeney MP, Keefe DH. Estimating the acoustic reflex threshold from wideband measures of reflectance, admittance, and power. Ear Hear 2001;22:316–32. |
| 137. | Keefe DH, Feeney MP, Hunter LL, Fitzpatrick DF. Aural acoustic stapedius-muscle reflex threshold procedures to test human infants and adults. J Assoc Res Otolaryngol 2017;18:65–88. |
| 138. | Schairer KS, Ellison JC, Fitzpatrick D, Keefe DH. Wideband ipsilateral measurements of middle-ear muscle reflex thresholds in children and adults. J Acoust Soc Am 2007;121:3607–16. |
| 139. | Oxenham AJ. Predicting the perceptual consequences of hidden hearing loss. Trends Hear 2016;20:2331216516686768. |
| 140. | Carney LH. Supra-threshold hearing and fluctuation profiles: implications for sensorineural and hidden hearing loss. J Assoc Res Otolaryngol 2018;19:331–52. |
| 141. | DeBonis DA. It is time to rethink central auditory processing disorder protocols for school-aged children. Am J Audiol 2015;24:124–36. |
| 142. | Tepe V, Papesh M, Russell S, Lewis MS, Pryor N, Guillory L. Acquired central auditory processing disorder in service members and Veterans. J Speech Lang Hear Res 2020;63:834–57. |
| 143. | Reavis KM, Snowden JM, Henry JA, Gallun FJ, Lewis MS, Carlson KF. Blast exposure and self-reported hearing difficulty in service members and Veterans who have normal pure-tone hearing sensitivity: the mediating role of posttraumatic stress disorder. J Speech Lang Hear Res 2021;64:4458–67. |
| 144. | Wilson RH, McArdle RA, Smith SL. An evaluation of the BKB-SIN, HINT, QuickSIN, and WIN materials on listeners with normal hearing and listeners with hearing loss. J Speech Lang Hear Res 2007;50:844–56. |
| 145. | Russo N, Nicol T, Musacchia G, Kraus N. Brainstem responses to speech syllables. Clin Neurophysiol 2004;115:2021–30. |
| 146. | Song JH, Skoe E, Banai K, Kraus N. Perception of speech in noise: neural correlates. J Cogn Neurosci 2011;23:2268–79. |
| 147. | Kimura D. Cerebral dominance and the perception of verbal stimuli. Canad J Psychol/Revue canadienne de psychologie 1961;15:166. |
| 148. | Wilkins EJ, Cole NW, Miller HM, Schuster RM, Dayer AA, Duberstein JN, Raedeke AH. "Rural-urban differences in hunting and birdwatching attitudes and participation intent." Hum Dimens Wildl 2019;24:530-47. |
| 149. | |
Correspondence Address:
Saradha Ananthakrishnan
Department of Speech-Language Pathology & Audiology, Towson University, 8000 York Road, Towson, MD 21252
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/nah.nah_53_22
[Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5]
[TABLE 1], [TABLE 2], [TABLE 3], [TABLE 4], [TABLE 5], [TABLE 6] |
Search Pubmed for
