Abstract
Objectives: Noise is a pervasive environmental factor in manufacturing settings and is a well-known cause of noise-induced hearing loss. However, its effects on autonomic nervous system function and cognitive work performance have not been thoroughly investigated. This study aimed to elucidate the impact of high-intensity noise exposure on autonomic activity and cognitive performance using objective physiological and behavioral indicators.
Methods: Task performance was assessed using two 15-minute sessions of the Uchida-Kraepelin test. Autonomic nervous system activity was evaluated through continuous monitoring of heart rate variability (HRV) and measuring salivary amylase activity at 3 time points: immediately before the first test, between the 2 test sessions, and immediately after the second test. All measurements were conducted on 2 separate days under the absence of noise or the presence of 90 dB(A) pink noise.
Results: Exposure to noise significantly increased low-frequency (LF) and the LF/(LF + high-frequency [HF]) ratio. HF and the coefficient of variation of R-R intervals (CVRR) showed no significant change. Salivary amylase activity was also significantly elevated during noise exposure, particularly after task completion. Performance on the Uchida-Kraepelin test revealed a significant decrease in the response volume ratio under noise exposure. The number and rate of incorrect responses remained unchanged.
Conclusions: High-intensity noise exposure activates the sympathetic nervous system and impairs work performance by reducing processing speed while maintaining accuracy. These findings underscore the importance of considering noise not only as an auditory hazard but also as a factor affecting cognitive ergonomics and occupational performance.
Keywords: noise, work performance, Kraepelin test, salivary amylase, heart rate variability
Key points
By measuring biological indicators such as heart rate variability and salivary amylase levels, in addition to assessing work performance outcomes, this study demonstrated that noise activates the sympathetic nervous system and influences work performance.
1. Introduction
Noisy work environments are prevalent in manufacturing sites. In Japan, according to the Industrial Safety and Health Regulations and the Guidelines for the Prevention of Noise-Induced Disorders, workers exposed to noise levels of 85 dB(A) or higher are recommended to undergo regular audiometric testing. In the fiscal year 2023, a survey by the Ministry of Health, Labour and Welfare reported that 346 200 workers in noise-exposed workplaces underwent hearing examinations, the highest number among all health examinations recommended or mandated by governmental authorities.1 These measures highlight the strong emphasis placed by the Japanese government on the prevention of occupational noise-induced hearing loss.
Whereas noise is a well-known cause of hearing loss, recent studies have linked it to mental health issues that impair work performance.2,3 The auditory system has evolved as an early alarm system to detect threats in the environment—a function conserved across animal species, including humans. Auditory signals transmitted via the auditory nerve branch into the brainstem, eliciting a startle response. Additionally, these signals connect to the limbic system and the autonomic nervous system, directly transmitting information to brain regions that regulate vegetative, autonomic, and endocrine functions. Thus, noise is considered to trigger stress responses via 2 pathways: a direct pathway, whereby auditory stimuli immediately influence the brainstem and autonomic nervous system, and an indirect pathway mediated by the neuroendocrine system, specifically the hypothalamic-pituitary-adrenal (HPA) axis.4 Exposure to noise levels above 60 dB has been reported to induce nonspecific stress responses in rats, primarily involving activation of the HPA axis.5
Whereas temporary noise may cause a transient stress response that is resolved spontaneously, chronic or repeated noise exposure leads to a sustained stress response. When the “defeat reaction,” characterized by a perception of uncontrollability, predominates, passivity and depression become prominent, leading to hyperactivation of the HPA axis and a chronic elevation of cortisol levels. Consequently, neuronal damage may occur, resulting in memory impairment, cognitive decline, and an increased risk of depression.4
Epidemiological studies have also investigated the association between noise exposure and depression. Some surveys have suggested that exposure to road traffic noise in residential areas exacerbates depressive symptoms.6 A clear dose–response relationship has been reported between transportation noise and subjective annoyance.7 People living near airports have been reported to be more sensitive to noise, experience stronger noise annoyance, and experience lower sleep satisfaction.8
Noise is considered to have a detrimental effect on work performance, especially in complex cognitive tasks. Although daily exposure to noise may lead to a degree of habituation, complete adaptation does not occur, and physiological responses such as elevated heart rate and raised noradrenaline and adrenaline levels have been observed, suggesting ongoing stress responses. Furthermore, noise exposure has been shown to reduce mood and performance the following day and to alter social behaviors, potentially increasing aggression. Nevertheless, a strong causal relationship with clinical psychiatric disorders has not been firmly established.9
Saeki et al10 found that, during a short-term memory task performed under noise conditions, higher noise levels were associated with increased annoyance and more pronounced difficulty in concentrating. They speculated that noise induced sympathetic nervous system dominance, impaired concentration, increased task errors, and ultimately degraded work performance. However, the background noise used in their study consisted of relatively low sound pressure levels of speech or white noise, differing from the noise typically encountered in manufacturing environments. Moreover, the evaluation indicators were limited to subjective indicators, accuracy rates, and reaction times, without incorporating quantifiable physiological measures.
Therefore, the present study aimed to examine how high sound pressure level noise—representative of manufacturing environments—affects work performance and autonomic nervous system activity, by employing objective and quantifiable physiological stress indicators.
2. Methods
2.1. Participants
The study participants consisted of 22 individuals (16 males and 6 females) with a mean (±SD) age of 24.3 ± 3.5 years. All participants had pure-tone hearing thresholds below 20 dB in the frequency bands 125, 250, 500, 1000, 2000, 4000, and 8000 Hz. Participants were instructed to adjust their living conditions as required during the study.
This experiment was conducted from November 1 to December 31, 2016, in an anechoic room at the Joint Research Center of the University of Occupational and Environmental Health, to eliminate the effects of environmental noise.
The study design and procedures were approved by the Ethics Committee of Medical Research at the University of Occupational and Environmental Health, Japan (approval number H28-139). All procedures were in accordance with the ethical standards of the Declaration of Helsinki and its amendments. All participants were provided with a detailed explanation of the study’s purpose and procedures and gave their written informed consent prior to participation.
2.2. Noise specification
Pink noise was used as the background noise for the experiment. This type of noise has uniform acoustic energy across each octave band as perceived by the human ear. Previous studies have indicated that the sound pressure level of the low-frequency band is relatively high, and noise generated by machinery in factories often exhibits a waveform similar to pink noise.11 Therefore, pink noise was selected in this study to approximate the acoustic environment of the workplace.
In this study, pink noise with a sound pressure level of 90 dB(A) was adopted, ensuring that the exposure remained within the permissible limit of 91 dB(A) for 2 hours, as recommended by the Japan Society for Occupational Health.12 To protect the participants’ hearing and minimize the mutual influence of each condition, the experiment was conducted once per day.
2.3. Heart rate variability
We used a portable electrocardiograph (WHS-1; Union Tool Co, Ltd) to measure heart rate variability (HRV). WHS-1 detected the coefficient of variation of the R-R interval (CVRR) and performed a fast Fourier transform (FFT). After FFT was performed, HRV was divided into high-frequency components (HF: 0.15 to 0.4 Hz) and low-frequency components (LF: 0.04 to 0.15 Hz).
CVRR is most commonly used as a time domain analysis method for R-R interval fluctuations.13 HF reflects parasympathetic activity, and LF reflects sympathetic nerve activity. The LF/(HF + LF) ratio can evaluate the dominance of autonomic activity. If the LF/(HF + LF) ratio is high, sympathetic nerves are dominant, indicating a heightened sympathetic response.14 The LF/(HF + LF) ratio is often considered to be inversely correlated with CVRR. However, although LF is predominantly influenced by autonomic innervation originating from the central nervous system, both HF and CVRR are subject to regulation by multiple mechanisms. Consequently, the relationship between these indices may not always align. HRV was recorded continuously throughout the experiment.
2.4. Salivary amylase
Salivary amylase activity was measured using a salivary amylase monitor (CM-2.1; Nipro Corporation, Osaka, Japan), an enzymatic analyzer specifically designed for salivary testing.15 Salivary amylase activity is a rapid and noninvasive marker of sympathetic activation.16 Various biomarkers are available to assess stress, but this study focused on short-term stress responses. To avoid stress caused by the measurement itself, we did not use invasive methods such as blood or urine sampling. Although salivary cortisol, chromogranin A, and catecholamines can be measured, their low concentrations and rapid degradation in the oral cavity make accurate measurement difficult. Salivary amylase activity was chosen because it is noninvasive, simple, fast, and convenient.
2.5. Kraepelin test
Task performance was assessed using the Uchida-Kraepelin test (Kraepelin test), which is designed to provide a standardized and reproducible assessment of workload.17 It serves as an index of efficiency and accuracy, measured by the number of calculations completed per unit time.18 The response volume ratio, also referred to as the late stage surpass rate, is considered to indicate the learning effect when performing the Kraepelin test on consecutive schedules. It is defined as the ratio of the increase in the number of responses in the first half and the next half. A decrease in the response volume ratio suggests that task efficiency decreased over time.
2.6. Protocol of experiment
The experimental protocol is shown in Figure 1. Participants underwent an audiometric test using an audiometer to confirm their normal hearing ability. We asked them to equalize their lifestyle during the experiment, including regular wake-up and bedtimes, as well as standardized meal times and frequency. The night before the experiment, they were instructed to get enough sleep. In addition, in order to eliminate the influence of the circadian variation of salivary amylase as much as possible, meal contents were specified, and an interval of at least 1 hour was required from the last meal intake to the start of the experiment. They rinsed their mouths 5 minutes before the experiment started.
Figure 1.
Experimental protocol: the Uchida-Kraepelin test. Time periods: (1) “immediately before test 1”: 5-minute period immediately preceding the start of test 1; (2) “between tests 1 and 2”: 5-minute period beginning 10 minutes after the start of test 1; (3) “immediately after test 2”: 5-minute period immediately following the completion of test 2.
First, the participants were asked about their physical condition and the time after their last meal (eg, breakfast) on the day of the experiment; these were recorded on an interview sheet. Electrodes were placed on the left precordial midclavicular line, and electrocardiography started sampling. After confirming that the heart rate was properly collected, the participants moved into an anechoic chamber and sat quietly for 5 minutes. They then performed a 15-minute Kraepelin test (test 1). After completing test 1, salivary amylase activity was measured, followed by a second test of the same duration (test 2). HRV and salivary amylase activity were assessed at 3 time points: (1) “immediately before test 1,” defined as the 5-minute period immediately preceding the start of test 1; (2) “between tests 1 and 2,” defined as the 5-minute period beginning 10 minutes after the start of test 1; and (3) “immediately after test 2,” defined as the 5-minute period immediately following the completion of test 2.
On 1 of the 2 experimental days, participants were exposed to a noise load condition (“presence of noise”) in which 90 dB(A) pink noise was applied immediately after they entered the anechoic chamber. The noise exposure continued until the end of the experiment, during which participants completed the workload and tests. On the other day, without the noise condition (“absence of noise”), the same procedure was followed without any background noise. Participants were randomly divided into 2 equal groups in a crossover design, with one group first undergoing the “presence of noise” condition and then the “absence of noise” condition (Group A), and the other group undergoing the reverse order (Group B). A pre-practice session was conducted to familiarize the participants with the experimental protocol.
3. Results
3.1. Heart rate variability
A significant difference was observed in LF between the presence and absence of noise, as determined by the Wilcoxon signed-rank test (P < .01, Figure 2A). When a 2-way analysis of variance (ANOVA) was performed considering the task condition factor, there was a significant main effect of background noise and task condition, as well as a significant interaction between the 2 factors (background noise: P < .03; work condition: P < .03; interaction: P = .05). Post hoc multiple comparisons were performed to identify specific group differences, and results showed that “between tests 1 and 2” showed a significant difference compared with all work conditions in the absence of noise.
Figure 2.
Changes in heart rate variability (HRV) parameters under the presence or absence of noise conditions (n = 22). A, Low-frequency (LF) component. P values indicate results of multiple comparisons using Tukey honesty significant difference (HSD) test. B, High-frequency (HF) component. C, LF/(LF + HF) ratio. D, Coefficient of variation of R-R intervals (CVRR). P values in B-D indicate the results of 2-way analysis of variance (ANOVA). Time periods: “immediately before test 1”: 5-minute period immediately preceding the start of test 1; “between tests 1 and 2”: 5-minute period beginning 10 minutes after the start of test 1; “immediately after test 2”: 5-minute period immediately following the completion of test 2. *P < .05, **P < .01. CVRR, coefficient of variation of R-R intervals; HF, high-frequency spectrum; LF, low-frequency spectrum.
A comparison of HF between the presence and absence of noise revealed that this difference was not statistically significant (P = .08). HF was compared across the 6 conditions combining the presence or absence of noise and work conditions, as shown in Figure 2B; 2-way ANOVA also revealed no significant differences for either the background noise factor or the work condition factor.
A significant difference in the LF/(HF + LF) ratio was observed between the presence and absence of noise according to the Wilcoxon signed-rank test (P < .01). After adjusting for the work condition, 2-way ANOVA demonstrated a significant difference in LF/(HF + LF) depending on the presence or absence of background noise (Figure 2C).
A statistical comparison of CVRR in noise and no noise conditions showed a significant difference (P < .05). As shown in Figure 2D, the 2-way ANOVA for CVRR revealed no significant main effects of either the background noise factor or the work condition factor, nor a significant interaction effect.
3.2. Salivary amylase
No statistically significant difference in overall salivary amylase activity was observed between the presence and absence of noise conditions (P = .59). However, when activity was compared across the 6 conditions (3 time points × 2 noise conditions), a significant increase was observed under noise exposure, particularly “immediately after test 2” (Figure 3).
Figure 3.
Salivary amylase activity at 3 time points under the absence/presence of noise (n = 22). P values are from multiple comparisons performed using the Wilcoxon signed-rank test. Time periods: “immediately before test 1”: 5-minute period preceding the start of test 1; “between tests 1 and 2”: 5-minute period beginning 10 minutes after the start of test 1; “immediately after test 2”: 5-minute period following the completion of test 2. **P < .01.
3.3. Kraepelin test
In the Kraepelin test, the response volume ratio was significantly decreased in the presence of noise (P < .01; Figure 4A,B). However, no statistically significant differences were observed in the number of incorrect responses and the incorrect response ratio (Figure 4C,D).
Figure 4.
Performance indicators for the Kraepelin test under the presence or absence of noise (n = 11). A, Response volume ratio, defined as the number of responses during the second 15 minutes divided by the number during the first 15 minutes. B, Total number of responses. C, Incorrect response ratio, calculated as the number of incorrect responses divided by the total number of responses. D, Total number of incorrect responses. All indicators were statistically analyzed using the 2-tailed Wilcoxon signed-rank test. **P < .01.
4. Discussion
This study used noninvasive, quantifiable biological indicators of stress to examine the effects of high-intensity noise simulating a workplace on work performance and demonstrated that loud noise indeed activates the sympathetic nervous system and reduces work performance.
4.1. Heart rate variability
A significant increase in LF and the LF/(HF + LF) ratio under noise exposure indicated a shift toward sympathetic nervous system dominance in response to auditory stress. In contrast, neither HF nor CVRR showed any significant change. These findings align with previous studies,18 and support the interpretation that noise exposure elicits a sympathetic response independent of parasympathetic withdrawal, and that cognitive demands may modulate cardiac autonomic regulation through mechanisms distinct from those induced by environmental stressors.
4.2. Salivary amylase
Salivary amylase activity did not show a significant change under workload conditions alone. However, a significant increase was observed during noise exposure, particularly at the same point when compared with the workload-only condition. It has been reported that salivary amylase responds within 1 to several minutes following sympathetic nervous system activation, reaching a stable level after approximately 5 minutes. Previous studies have shown that amylase activity decreases in response to comfort stimuli and increases with discomfort stimuli,15,16 suggesting that salivary amylase serves as a useful indicator for distinguishing between comfort and discomfort. In this study, the observed increase in salivary amylase activity under noise conditions suggests that the noise load heightened discomfort and elicited a stronger sympathetic response compared with cognitive load alone. The pattern of amylase activity mirrored the initial HRV changes, suggesting consistency in physiological responses. Given that salivary amylase is a rapid-responding biomarker that reflects acute autonomic activation within minutes, the observed gradual increase “between tests 1 and 2,” and its significant elevation at “immediately after test 2,” represents a plausible and physiologically meaningful response to noise load.
4.3. Kraepelin test
In relation to the Kraepelin test, Washino and Nishida18 and Takai et al19 reported that both the number and rate of incorrect responses increased proportionally with rising noise levels, specifically when the noise intensity was incrementally raised from 50 dB to 75 dB in 5-dB steps. Fujii et al20 found that the total number of responses increased with repeated administrations of the Kraepelin test, whereas the response ratio decreased under noise exposure. Although participants in this study also were given sufficient practice before the experiments, a significant decrease in the response volume ratio was observed under noisy conditions. This supports the interpretation that noise exposure reduces work speed during the Kraepelin task. Despite the simplicity of the 2-digit calculation task, the fact that noise exposure produced significant effects is noteworthy. In this experiment, the number of responses declined under noise conditions, whereas the number and rate of incorrect responses did not show a significant increase. It is conceivable that a task with higher cognitive demands might have elicited a more pronounced stress response, thereby allowing the effects of noise to be more clearly demonstrated.
The results of this study demonstrate that noise acts as a stressor, as evidenced by objective physiological indicators. Regarding work performance, consistent with the findings of Fujii et al,20 previous studies have also reported impaired cognitive function during mental arithmetic tasks under noisy conditions,21 and prolonged recognition and decision-making times due to decreased attentional capacity.22 With respect to physiological responses, it has been suggested that magnetic resonance imaging–related noise influences peripheral autonomic activity, amygdala activation, and subjective perceptions, in that order.23 In this experiment, HRV peaked mid-task under noise exposure, whereas salivary amylase levels tended to rise in the later phase, suggesting a sequential activation from peripheral to central nervous responses. Furthermore, significant differences in task performance were observed between participants who maintained high response accuracy and those who exhibited increased error rates. This implies a decline in both cognitive responsiveness and increased mental workload under noise exposure. These findings suggest that work performance, physiological responses, and psychological reactions are interrelated rather than unidirectional, and the temporal progression model proposed in this study holds some empirical validity.
In Japan, noise protection policies have focused on the physical impact of noise, particularly noise-induced hearing loss. Similarly, epidemiological studies of noise-related stress have largely emphasized long-term health effects. However, recent findings suggest that acute indicators, such as temporary threshold shifts, may help identify the risk of long-term hearing impairment at an earlier stage.24
In this study, autonomic nervous system activity was altered within approximately 30 minutes of noise exposure. These short-term physiological changes may reflect acute stress responses. Given prior findings that acute indicators such as temporary threshold shifts may signal future auditory risks, these responses may also suggest the potential for short-term markers to reflect longer-term health impacts. However, further research is needed to clarify their predictive value.
In Japan, noise is considered a contributing factor to work-related cardiovascular events and is included among the environmental stressors in the official criteria for overwork-related death (karoshi) certification, as defined by the Ministry of Health, Labour and Welfare.25
From an occupational health practice perspective, our results indicate that HRV and salivary amylase activity can be used as feasible, noninvasive biomarkers for routine stress monitoring in noisy workplaces. Their ease of implementation and sensitivity to acute stress make them suitable for periodic screening. Practical considerations—such as timing of measurement, worker compliance, and equipment accessibility—should be addressed when adopting these tools in occupational settings.
Although workplace noise is often perceived as a ubiquitous and minor nuisance, our findings suggest that its reduction may enhance not only worker comfort but also cognitive function and organizational productivity. These potential benefits support the implementation of noise control measures from both employee well-being and managerial perspectives. For example, brief HRV-based assessments conducted during shift transitions could help identify early signs of stress accumulation, enabling timely interventions and individualized work adjustments.
Furthermore, taking into account individual variability in noise sensitivity,26 early identification of vulnerable workers may facilitate better job placement and more targeted preventive strategies.
5. Limitations
This study focused on younger participants and examined only short-term effects of noise exposure. Therefore, the physiological and psychological responses observed here may differ in other populations, such as healthy older adults or individuals with pre-existing hearing impairments.
Since many of the participants were students, we cannot rule out the possibility that their lack of habituation to noise may have influenced the outcome measures. This remains a limitation of the study. Nevertheless, as reported by Basner et al,27 physiological stress responses can persist even in individuals who are subjectively habituated to noise. Therefore, despite this limitation, our findings may still retain a certain degree of generalizability.
Although male participants constituted the majority in this study, the measures employed—namely the Kraepelin test, salivary amylase activity, and HRV—have previously been validated as gender-independent indicators.28 Consequently, any potential interaction effects related to gender are considered to be minimal.
6. Conclusions
Objective physiological and performance-related measures showed that high-intensity noise, such as that commonly encountered in the workplace, activates the sympathetic nervous system, reduces concentration, and reduces work performance.
Acknowledgments
We gratefully acknowledge the Shared-Use Research Center, UOEH, Japan, for providing the anechoic room and measurement equipment.
Contributor Information
Toshitaka Yokoya, Department of Health Policy and Management, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Japan, Kitakyushu, Japan.
Chikage Nagano, Department of Health Policy and Management, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Japan, Kitakyushu, Japan.
Yukimi Endo, Department of Health Policy and Management, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Japan, Kitakyushu, Japan; Health Support Center, Yajima Plant, Automotive Business, Subaru Corporation, Ohta, Japan.
Yuichiro Tanaka, Department of Health Policy and Management, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Japan, Kitakyushu, Japan; Division of Occupational Health, Sakai Plant, Daikin Industries, Ltd, Sakai, Japan.
Jinro Inoue, Department of Health Policy and Management, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Japan, Kitakyushu, Japan.
Seichi Horie, Department of Health Policy and Management, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Japan, Kitakyushu, Japan.
Author contributions
T.Y. invented and designed this research. J.I. collaborated on all the experiments. Y.T. and Y.E. organized and carefully controlled the quality of the experiments. All authors were involved in the interpretation of the data. T.Y., C.N., and S.H. drafted the manuscript. All authors contributed to revising the manuscript and approved the final version of the manuscript.
Funding
This study was conducted with the financial support of our departmental research fund and the corporate-sponsored research donations from Kamakura Seisakusho Co, Ltd and Shigematsu Works Co, Ltd.
Conflicts of interest
S.H. was supported by donations from Kamakura Seisakusho Co, Ltd and Shigematsu Works Co, Ltd. However, the funders had no role in study design or analysis. T.Y. is employed by Mitsubishi Heavy Industries, from which he receives a salary. Other authors declare that they have no competing interests.
Data availability
The data that support the findings of this study are available from the corresponding author upon reasonable request. They are not publicly available due to their containing information that could compromise the privacy of research participants.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request. They are not publicly available due to their containing information that could compromise the privacy of research participants.