Early Auditory Deficits in Normal Hearing Young Adults with High Non-Occupational Noise Exposure

INTRODUCTION Noise exposure, both occupational and non-occupational, is a leading factor affecting auditory health worldwide.1,2 Occupational noise, prevalent in industrial and construction settings, is a well-established cause of noise-induced hearing loss (NIHL).3 More recently, non-occupational noise from personal listening devices (PLDs), gaming, nightclubs, and concerts has emerged as a widespread but under-recognized threat, particularly among young adults.4,5Figure 1: (a) Mean and standard deviation of the pure-tone hearing thresholds of the right ears in the LNE and HNE groups. (b) Mean and standard deviation of SNRs in dB of the TEOAE.Figure 2: Mean MDT (dB) between HNE and LNE groups across modulation rates (2–128 Hz) for a broadband noise carrier stimulus.Unlike occupational noise, non-occupational exposure often occurs repetitively at dangerously high intensities, with no regulation or monitoring. Long-term noise exposure can also affect the body and mind, With prolonged exposure, it can increase blood pressure, affect sleep, cause stress, and tiredness.6–9 This exposure can damage inner hair cell structures, especially the basilar membrane and cochlear hair cells, leading to irreversible damage.10,11 Prolonged exposure may also impair synapses between inner hair cells and cochlear neurons, affecting neural transmission necessary for understanding speech in noise and processing temporal cues.12–14 These changes occur immediately and worsen over time, affecting ribbon synapses that transmit signals from inner hair cells to auditory nerves.15 Prolonged noise exposure preferentially damages LSR fibres, which are crucial for detecting timing and modulation cues.13 These nerve fibres are also responsible for listening in noise. Studies done on animals show that such damage may occur before hair cell loss or threshold shifts are evident. Individuals exposed to occupational noise who have normal hearing often report difficulty with speech in noise and poor temporal resolution.16,17 They also report tinnitus and increased listening effort.18 Evidence shows that individuals with occupational noise exposure have poorer speech perception in noise abilities than individuals without occupational noise exposure.19 A study done to evaluate amplitude modulation detection abilities reported that individuals with high recreational noise exposure had poorer modulation detection thresholds, especially at high modulation rates.20 While the effects of occupational noise exposure are well-documented, research on non-occupational noise exposure in normal hearing young adults is limited. This population frequently engages in high-risk listening behaviours using PLDs or attending loud recreational venues, often without awareness of the potential damage. Even in the absence of measurable hearing loss, synaptic damage from chronic non-occupational noise exposure may result in early auditory deficits, particularly in speech-in-noise understanding and temporal processing. As these subtle deficits are not typically detected by conventional audiometry, they remain underdiagnosed and unaddressed. Hence, there is a critical need to investigate the early auditory consequences of non-occupational noise exposure in young adults with normal hearing. This study aims to investigate speech in noise and amplitude modulation detection abilities in low and high annual non-occupational noise exposed young adults with normal hearing. METHODS Study setting and design The study was conducted in a sound-treated room at the Audiology Lab of Nitte Institute of Speech and Hearing in Mangalore, India. A between-group comparison design was employed, and participants were recruited through convenience sampling. Sample Size: The sample size was determined using the formula n = (2(z + z )²²)/d², where z = 1.96 at 95% confidence, z = 1.28 at 90% power,  = 0.99, and d = 1. Based on this formula and referring to Vasudevamurthy & Kumar (2022), the estimated sample size was 21 per group.16 However, 50 participants were included in total. Participants Young adults aged 18 to 30 years were categorized into low and high-noise-exposed groups based on their annual noise exposure (ANE). Individuals with normal hearing, normal middle ear function and no auditory processing deficits were included in the study. These were confirmed through pure-tone audiometry, immittance audiometry, transient evoked otoacoustic emissions (TEOAEs), and the Screening Checklist for Auditory Processing in Adults (SCAP-A). Participants with <15 dB HL, type ‘A’ tympanogram with present reflexes, TEOAEs with >6 dB signal-to-noise ratio (SNR) at three consecutive frequencies and <6 scores for SCAP-A were included in the study. Participants completed the Noise Exposure Questionnaire (NEQ) to calculate their annual noise exposure (ANE). The ANE represents the noise exposure in LAeq8760h. The LAeq8760h metric represents the equivalent continuous noise level over 8,760 hours per year, using an A-weighted scale and a 3-dB exchange rate. Participants with ANE ≥79 dB were classified as high noise exposure (HNE), while those with ANE <79 dB were categorized as low noise exposure (LNE). Pure-tone audiometry (PTA) was conducted using the Inventis-Piano audiometer (250–8,000 Hz) with TDH-39 headphones. Pure tone average was calculated for the thresholds of 500, 1,000, 2,000, and 4,000 Hz. Immittance audiometry was performed using the Clarinet {Inventis) system with a 226 Hz probe tone. Ipsilateral and contralateral reflexes were evaluated at 0.5, 1, and 2 kHz. Transient evoked otoacoustic emissions (TEOAEs) were recorded using Otodynamics ILO-v6 with 80 dB SPL using click stimuli. A total of 260 sweeps were recorded for each ear. Procedure Speech Perception in Noise (SPIN) was conducted through the Smriti-Shravan software.21 Nonsense CVCV words were presented at 90 dB SPL through circumaural headphones. The stimuli were routed through an audiometer connected to a personal computer. An adaptive procedure of 3-down, 1-up was employed to determine the SNR-50, which corresponds to the signal-to-noise ratio at which the participant correctly identified 50% of the presented words. The SNR-50 was calculated as the mean of 6 reversals. The Temporal Modulation Transfer Function (TMTF) was ­assessed using the Psychoacoustic Software Package.22 The broadband noise carrier stimuli were presented at 90 dB SPL. The modulation depth was measured at different modulation rates (2, 4, 8, 16, 32, 64, and 128 Hz). Modulation detection thresholds were determined using a 3-alternative forced-choice (3-AFC) procedure. Each trial contained three successive stimuli, one of which was modulated while the other two remained unmodulated. Participants were instructed to identify the modulated signal, and the order of the stimuli was randomized. The stimulus duration was 500 ms, including 20-ms rise/fall times. The interstimulus interval was 300 ms. A 2-down 1-up adaptive procedure was employed, and thresholds were derived from the mean of eight reversals. The test was done at 90 dB SPL to presumably tap the functioning of low spontaneous rate auditory nerve fibers.23,24 The use of 90 dB SPL aimed to effectively engage LSR fibres, which are crucial for temporal modulation detection in challenging listening conditions. RESULTS Participants A total of 50 participants were included and divided equally into LNE and HNE groups. The LNE group had a mean age of 22.0 years (SD = 2.5) while the HNE group had a mean age of 23.2 years (SD = 2.8). The Shapiro-Wilk tests of normality revealed a normal distribution for speech perception in noise but a non-normal (p < 0.05) distribution for modulation detection threshold, which led to the selection of parametric and non-parametric tests respectively. Noise Exposure Questionnaire: Annual noise exposure (ANE) was quantified using a structured questionnaire, expressed in LAeq8760h. The low noise exposure group had a mean ANE of 70.70 dB (SD = 3.74), while the high noise exposure group had a significantly higher mean of 83.2 dB (SD = 2.2) as confirmed by an independent t-test (t = 14.3, p <0.001). It is crucial to perform a proper test here to see whether this ANE is different statistically. LNE group showed a mean PTA of 9.4 dB HL (SD = 1.40), and the HNE group showed a mean PTA of 9.0 dB HL (SD = 1.3.) (See Fig. 1[a].) Participants in the low noise exposure group had a mean TEOAE SNR of 11.8 dB (SD = 2.00) while the high noise exposure group had a mean of 12.1 dB (SD = 1.1). (See Fig. 1[b].) There was no significant difference in either PTA or TEOAE SNR between the two groups (independent t-test, p > 0.05). All participants exhibited type ‘A’ tympanograms with present ipsilateral and contralateral acoustic reflexes at 0.5, 1, and 2 kHz, confirming normal middle ear function. All participants scored below 6 on the SCAP-A, indicating no auditory processing difficulties. Speech Perception in Noise Participants with high noise exposure showed a higher ­SNR-50 (M = -5.3 dB, SD = 1.0) compared to the low-noise ­exposed group (M = -7.2 , SD = 2.5). Independent t-test showed that the SNR 50 for the low-noise exposed group was significantly lower than the high-noise exposed group (t 3.4, p < 0.001). Amplitude Modulation for BBN The mean modulation detection thresholds (MDTs) were found to be relatively better in the low noise-exposure group across all modulation rates. The mean MDTs for the LNE and HNE are depicted in Figure 2. Two-way analysis of variance (ANOVA) was performed with modulation frequency as a within-group variable and noise exposure as a between-group variable. The results revealed a significant main effect of modulation frequency (F = 42.30, p < 0.05), indicating that the response varied across modulation frequencies. However, there was no significant main effect of group (F = 3.20, p > 0.05), and no significant interaction between group and frequency was observed (F = 0.62, p < 0.05). For the purpose of examining correlations between TMTF and other auditory variables (PTA, TEOAEs SNR, and SNR-50), peak sensitivity (the lowest modulation detection threshold observed across modulation frequencies) was estimated by fitting each participant’s modulation detection thresholds to a low-pass filter regression model using customized MATLAB code. Spearman’s rank-order correlation analysis revealed no significant associations between peak sensitivity and either PTA or the mean SNR of TEOAEs, which aligns with expectations, as these measures were controlled through participant inclusion criteria. However, a significant positive correlation was observed between peak sensitivity and SNR-50 ( = 0.31, p = 0.03), irrespective of participant group, indicating that better temporal resolution is associated with improved speech perception in noise. DISCUSSION The noise exposure questionnaire includes questions from occupational, environmental, and recreational sources. Since the participants were university students, it can be assumed that they were exposed to non-occupational noise, which included environmental and recreational noise exposure. Speech Perception in Noise The present study evaluated speech perception in noise among individuals with low and high levels of noise exposure. Results showed that those in the high exposure group had significantly higher SNR-50 thresholds, indicating poorer speech understanding in noisy environments. This suggests that prolonged noise exposure affects the auditory system’s ability to process speech in background noise, even when pure-tone thresholds remain within normal limits. Similar findings were reported in noise-exposed individuals, whether from occupational or recreational sources, that can damage synaptic connections in the auditory nerve, leading to degraded speech perception in noise.16,25,26 Synaptic loss impairs the encoding of temporal fine structure and envelope cues, reducing the auditory system’s ability to separate speech from background noise and leading to poorer speech-in-noise performance despite normal pure-tone thresholds.27 Noise exposure can lead to the reduction of functional auditory nerve fibers, particularly those with low spontaneous rates, which are crucial for hearing in challenging listening environments like noisy backgrounds.28,29 These low spontaneous rate fibers are not essential for detecting quiet sounds, but they are critical for encoding sound in noisy settings.30 Amplitude Modulation Detection in low and high-noise-exposed individuals The LNE group exhibited overall better MDTs across all modulation rates compared to the HNE group; however, the differences between the two groups were not significant. A previous study has reported similar results in individuals with occupational noise exposure.19 However, a study reported poorer amplitude modulation detection in individuals with occupational noise exposure than in individuals without a history of noise exposure.17 The elevated MDTs in noise-exposed individuals can be due to the reduced synchronization of neural response, particularly at higher modulation rates.31 The brain’s ability to synchronize neural firing with sound timing is stronger at low frequencies and declines as the frequency increases.27,32 This decline affects the rapid envelope fluctuations, leading to elevated modulation detection thresholds at higher modulation rates.33 As a result, individuals with noise exposure or early hearing loss may experience diminished sensitivity to amplitude modulation, especially at higher frequencies.11 The noise exposure may affect modulation detection, but the effect was not strong enough in this study to reach statistical significance, possibly due to variability within groups or a limited sample size. CONCLUSION These findings highlight the need for monitoring suprathreshold auditory functions, such as speech perception in noise, among young adults exposed to non-occupational noise. Although all participants exhibited normal hearing sensitivity, the observed differences in speech-in-noise performance suggest that prolonged exposure to recreational noise may lead to subtle auditory deficits not captured by conventional audiometry. This underscores the importance of early identification and prevention strategies aimed at preserving auditory health in populations at risk due to high levels of non-occupational noise exposure.