Objective: A variety of questionnaires have been developed to describe and quantify occupational and nonoccupational noise exposure, which are associated with hearing loss and tinnitus. The main aim of this study was to compare and contrast three commonly used nonoccupational noise exposure measurement questionnaires in a group of young adults. Materials and Methods: A total of 197 participants were recruited for this study. All the participants completed three commonly used nonoccupational noise exposure measurement questionnaires via Qualtrics software (Qualtrics, Provo, UT). General patterns in the nature of noise exposure were highlighted and statistical agreement and correlations between the three instruments were calculated. Comparisons were made between self-percept of noise exposure and annual noise exposure metrics obtained using questionnaires. Results: Strong statistical agreement and correlation (r = 0.57, P < 0.001) was found between the selected instruments similar in their constructs of noise exposure. When compared to quantified scores of noise exposure, self-report of exposure to loud noise was highly sensitive but associated with poor specificity (3.61%) and a high false-positive rate (96.38%). The majority of participants reported exposure to noise from listening to music and attending loud recreational activities, with a differential effect of sex on average annual noise exposure values depending on the questionnaire used. Conclusions: The outcomes of this analysis could assist in comparing noise exposure quantifications across research studies, and determining if and how these questionnaires may be utilized clinically to effectively identify and counsel those at risk for noise-induced hearing loss.
Keywords: Nonoccupational noise exposure questionnaires, statistical agreement, young listeners
|How to cite this article:|
Adson K, James K, Srinivasan N, Ananthakrishnan S. A Comparison of Self-Reported Nonoccupational Noise Exposure in a Large Cohort of Listeners. Noise Health 2022;24:237-47
Key Messages: Young adults may benefit from receiving information related to potentially damaging effects of excessive noise levels that could be experienced from listening to music and attending loud recreational events. Also, when providing activity-specific noise awareness information, counseling might be more effective when targeted toward male listeners for certain activities (e.g., use of power tools, heavy machinery, etc.) and toward female listeners for certain other activities (e.g., attending fitness classes, night clubs, etc.).
| Introduction|| |
Noise exposure can occur at the workplace, during recreational pursuits, and from environmental sources. Persistent exposure to excessive noise has been associated with a range of degenerative changes in cochlear structures, such as the inner and outer hair cells, spiral ganglion cells, and synaptic connections between hair cells and auditory neurons. Such degenerative changes can lead to a variety of auditory consequences such as temporary threshold shifts, permanent threshold shifts, tinnitus, and deficits in suprathreshold auditory processing in adverse listening conditions. Taken together with its nonauditory health effects (e.g., annoyance, sleep disturbance, cardiovascular issues, and impaired cognitive function), noise exposure is a pressing public health concern. Indeed, data from the National Health and Nutrition Examination Survey (NHANES) conducted between 2011 and 2012 suggest that one in four Americans between 20 and 69 years of age exhibits some aspect of noise-induced hearing loss (NIHL). The potentially detrimental effects of occupational and nonoccupational noise exposure underscore the need for identification of those individuals at risk for NIHL, and targeted counseling to increase awareness of the damaging effects of noise exposure, strategies to avoid or minimize noise exposure, and monitoring and management of hearing health. In order to achieve these needs, we need standardized protocols that provide in-depth qualitative descriptions and quantification of an individual’s noise exposure. Since there are currently no standardized clinical guidelines for the description and measurement of an individual’s noise exposure, evaluation is often limited to patient-reported exposures collected by clinicians on a case history form. Commonly, audiologists ask a broad question similar to “have you ever been exposed to loud noise,” with the option of adding follow-up questions briefly querying the patient’s work history, military status, and recreational activities in which noise exposure occurred. Thus, documentation of history of noise exposure relies primarily on the patient’s self-perception of exposure to high levels of noise, with no standard clinical guidelines in terms of specific follow-up questions regarding the intensity, frequency, and duration of noise exposures, especially nonoccupational noise exposures. That said, translational research in the area of noise exposure and NIHL in humans has accelerated significantly in the last two decades, particularly following the seminal work of Kujawa and Liberman which identified cochlear synaptopathy in noise-exposed mice. The increased interest in describing the effects of noise exposure in human listeners has led to the development of several questionnaire-based methods to provide more definitive characterizations of noise exposure.,,,,,,,,,,
In performing a comprehensive review of these questionnaires, Guest et al. identified a lack of standardization across these questionnaires as a major issue. While the questionnaires mentioned above share the common goal of quantifying noise exposure, they differ in terms of the period under review (e.g., lifetime, annual, etc.), details queried re: noise exposure (type, frequency, duration, and intensity), method for quantification of noise exposure, consideration of hearing protection use, and inclusion of firearm use. With the availability of multiple measurement instruments with varying protocols to address a common question, it becomes important to evaluate their statistical agreement. If differences exist in the outcome measures (in this case, noise exposure estimation), it is of value to identify the cause of such discrepancies. An assessment of the statistical agreement between the various questionnaires estimating noise exposure will allow for valid comparisons of noise exposure data across studies. To the best of our knowledge, there are no published studies that evaluate the statistical agreement between the different questionnaire instruments characterizing noise exposure. The primary aim of the current research was to assess the statistical agreement between metrics of annual recreational noise exposure in a cohort of young adults obtained using questionnaire-based methods developed by Neitzel et al., Beach et al., and Johnson et al. We chose to focus on noise exposure quantification methods proposed in these three questionnaires for the following reasons. First, nonoccupational/recreational noise exposure was included, or was the sole focus, of each of the noise exposure quantification techniques in the chosen studies. The deleterious effects of occupational noise exposure on the auditory system have been described extensively (for an excellent review see Themann and Masterson, 2019). Further, occupational noise exposure is well-regulated by agencies such as the Occupational Safety and Health Administration (OSHA), International Organization for Standardization (ISO), and National Institute of Occupational Safety and Health (NIOSH). These organizations specify legally permissible noise exposure levels in the workplace, which vary with duration of exposure [e.g., 90 dBA (OSHA) and 85 dBA (ISO and NIOSH) for an 8-hour workday; Sliwinska-Kowalska and Kotylo, 2007]. In addition to limits on intensity and duration of workplace noise exposure, OSHA further requires a hearing conservation program which includes noise monitoring, audiometric testing, and hearing protection training for all OSHA personnel. These regulations offer a degree of protection and create awareness regarding NIHL to individuals exposed to noise at the workplace. However, no such mandated guidelines are available for nonoccupational/recreational activities associated with excessive noise levels (e.g., hunting, target shooting, woodworking, motorsports, concert attendance, use of personal audio systems, etc.). For instance, discharge of a recreational firearm can produce peak Sound Pressure Levels (SPLs) as loud as 150 to 165 dB, and rock concerts average around 140 dBA. Noise levels associated with these pursuits can exceed recommended or permissible limits specified by national and international health agencies. For instance, per NIOSH, the recommended exposure limit is 85 dBA over an 8-hour average, and as per OSHA, the permissible exposure limit is 90 dBA over an 8-hour average. For impulse or impact noise, OSHA limits exposure levels to 140 dB SPL. Hence, the levels of noise exposure encountered during certain nonoccupational activities have the potential to increase risk of NIHL. Indeed, studies have shown associations between nonoccupational noise exposure and auditory symptoms such as permanent threshold shifts, temporary threshold shifts, and tinnitus., Given the impact of nonoccupational noise on public health, the World Health Organization (WHO) released guidelines for environmental noise in the European region in 2018, with specific conditional recommendations for leisure noise levels.
Therefore, it is critical to include nonoccupational noise exposure in the calculation of any noise exposure metric that may be utilized for identifying those at risk for NIHL and for counseling these individuals. A second reason for the selection of the questionnaires developed by Neitzel et al., Beach et al., and Johnson et al. for comparison in the current study was related to potentially improved reporting accuracy of noise exposures for the period of review defined in these instruments (preceding year). Noise-induced changes in the auditory system reflect the effects of noise exposure across the lifespan. Hence, many of the questionnaires developed for characterization of noise exposure ask participants to describe noise exposures that have occurred during the individual’s entire lifetime.[7–9,11–13,16] However, one of the limitations of this approach is the need for participants to accurately recollect and report noise exposures dating back by several decades. Accurate recall and reporting becomes especially challenging when type, intensity, frequency, duration of noise exposure, and hearing protection habits change over the lifetime. Different strategies, such as dividing the lifespan into decades (e.g., 20–30 years) or periods associated with certain noise exposure habits (e.g., time as a university student) have been utilized to minimize inaccuracies in reporting. Even so, participant recall remains a limiting factor for the accuracy of questionnaires that seek to obtain information over the entire lifetime of an individual. In contrast to the majority of instruments querying noise exposure that include the entire lifespan in the period of review, the questionnaires developed by Neitzel et al., Beach et al., and Johnson et al. limit the period of review to just the preceding year. The drawback of estimating annual noise exposure is the exclusion of prior noise exposures that can contribute to NIHL risk. However, since they query noise exposures in a much more limited and recent time frame, the data from these questionnaires may reflect more current noise exposure habits and hence be associated with better recall and reporting accuracy. In the context of the primary aim of the current study, it is hypothesized that strong statistical agreement will be observed between the survey responses obtained to the Neitzel et al. and Johnson et al. questionnaires. This outcome is expected due to the similarity between these questionnaires in terms of the specific noise exposures queried and the mathematical formulae used to calculate annual noise exposure. However, the specific nonoccupational activities queried in the questionnaire developed by Beach et al. have limited overlap with those included in the Neitzel et al. and Johnson et al. questionnaires. Hence, it is expected that annual noise exposure values obtained in response to the questionnaire developed by Beach et al. will be in weaker statistical agreement with those obtained to the Neitzel et al. and Johnson et al.
A secondary aim of this research was to evaluate the agreement between self-perception of noise exposure typically queried by audiologists during case history intake and annual noise exposure calculations measured using these questionnaires. Given that annual noise exposure quantification methods utilized in these questionnaires make use of a mathematical formula that takes into consideration type, duration, frequency, and intensity of noise exposure, as opposed to a subjective “yes/no” self-report of noise exposure, it is hypothesized that the correlation between these two metrics will be limited. Finally, administration of these questionnaires to a group of young adults in the community will allow for an understanding of the type and extent of nonoccupational noise exposure typically experienced by these individuals and the development of targeted noise awareness programs for the community.
| Materials and methods|| |
Participants between the ages of 18 and 40 years were recruited through word-of-mouth. Participation was voluntary and all participants provided informed consent in compliance with a protocol approved by the Institutional Review Board.
Survey materials, administration, and calculation of annual noise exposure
Participants completed an online survey (Appendix A) administered via the Qualtrics software (Qualtrics, Provo, UT). The survey consisted of 107 questions in total, with 101 items selected with permission from annual noise exposure quantification questionnaires developed by Neitzel et al., Beach et al., and Johnson et al. Survey items one to six obtained basic demographic information from participants, while the remainder reflected questions appearing in the three noise exposure quantification questionnaires used in this study. Survey items queried participants on duration and frequency of participation in a variety of occupational and nonoccupational activities associated with high levels of noise, use of hearing protection, and hearing health. While the order of questions within each questionnaire was maintained for scoring purposes, the order in which participants received each of the three questionnaires was randomized. The entire survey took approximately 20 minutes to complete. Annual noise exposure values and risk for NIHL were determined for each participant following the specific protocols and formulae discussed by Neitzel et al., Beach et al., and Johnson et al. Since the focus of the current research was on annual nonoccupational noise exposure, only those items reflecting such noise exposure were included in calculation of the annual noise exposure values. This also ensured consistency in the final noise exposure metrics compared across the three studies, since the Noise Exposure Questionnaire (NEQ) queries both occupational and nonoccupational noise exposure while Beach et al. include only questions on nonoccupational noise exposure. Specific survey items queried and mathematical formulae used to calculate annual noise exposure are provided in [Table 1].
Mean, standard deviation, and range of annual noise exposure metrics obtained using the three questionnaires were calculated for the entire study population, and by sex. Additionally, percent of participants reporting participation and average number of hours/year participating in each nonoccupational activity were calculated for the entire study population, and by sex. Independent samples t tests were conducted to confirm whether or not annual nonoccupational noise exposure metrics were significantly different between male and female participants. Since all the three questionnaires quantify noise exposure, limits of agreement (LoA; Altman and Bland, 1983; Bland and Altman, 1999) was used to evaluate the agreement between them. Further, a Pearson product-moment correlation coefficient was computed to assess the relationships between the annual nonoccupational noise exposure metrics obtained using the three questionnaires on the entire study population (n = 175). Sensitivity, specificity, false-positive, and false-negative values were calculated to determine the accuracy of the annual nonoccupational noise exposure values calculated by the Beach et al. questionnaire relative to participants’ self-report of noise exposure. A Pearson product-moment correlation coefficient was also calculated to evaluate the relationship between self-report of noise exposure and the annual nonoccupational noise exposure obtained by administering the Beach et al. questionnaire. Responses to items corresponding to the questionnaires developed by Neitzel et al. and Johnson et al. were excluded from the correlational analyses as the annual noise exposure values calculated for these questionnaires in the current study did not reflect all the items queried on the original questionnaires.
| Results|| |
A total of 197 adults between the ages of 18 and 40 years (mean age: 25.047 years, Standard Deviation (SD): 4.65 years; males = 73, females = 124) participated in the current study, Twenty-two of these participants were eliminated due to incomplete total responses needed to calculate exposure levels. Therefore, 175 participants, 63 males (age range: 18–40 years, mean age: 27.46 years, SD: 5.34) and 112 females (age range: 19–37 years, mean age: 23.63 years, SD: 3.69) were analyzed for purposes of this study.
Statistical agreement and correlations between annual noise exposure values obtained across questionnaires
The top panel of [Figure 1] shows the LoA between the questionnaires calculated using Bland–Altman technique., This analysis is based on the mean noise exposure score between any two questionnaires as a function of their mean differences. LoA plots can be used to measure the extent to which the noise exposure scores between two questionnaires agree. The 95% LoA, estimated by mean difference ± 1.96 × standard deviation of the differences, provides an interval within which 95% of differences between the two noise exposure scores are expected to be present. The solid black lines in all the three plots in the top panel indicate the bias (difference between the two scores) and the solid red lines indicate the 95% LoA. As can be observed from the top panels of [Figure 1], the mean difference between the scores for all pairs of questionnaire comparisons was close to zero since the noise exposure scores were normalized using Z-transformation. The 95% LoA for Johnston et al. versus Neitzel et al. comparison was ±1.82 (z units), for Johnson et al. versus Beach et al. was ±2.63 (z units), and for Beach et al. versus Neitzel et al. was ±2.76 (z units). Also, there were three participants outside the 95% LoA for Johnston et al. versus Neitzel et al. comparison, eight for Johnson et al. versus Beach et al. comparison, and 11 for Beach et al. versus Neitzel et al. comparison.
|Figure 1 Statistical agreement and correlations between annual noise exposure values obtained from the three questionnaires.|
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The bottom panel of [Figure 1] shows the scatter plot between the three questionnaires used in this study. The solid lines indicate best fit to the data for each correlation analysis. There was a significant positive correlation between the scores obtained using Neitzel et al. questionnaire and the scores obtained using Johnson et al. questionnaire [r(173) = 0.57, P < 0.001]. However, the correlation between the scores obtained using Johnston et al. questionnaire and the scores obtained using Beach et al. questionnaire [r(173) = 0.10, P = 0.18] and the correlation between the scores obtained using Neitzel et al. questionnaire and the scores obtained using Beach et al. questionnaire [r(173) = 0.007 P = 0.93] were statistically insignificant.
Self-perception of excessive noise exposure versus quantification of annual noise exposure
The majority of participants (169/175) answered in the affirmative when queried about their self-perception of loud noise exposure (“have you ever been exposed to loud noise?”). Acceptable Yearly Exposure (AYE) values obtained from administering the Beach et al. questionnaire considered as the “truth” were compared against participants’ perception of high noise exposure to yield sensitivity, specificity, false-positive, and false-negative rates associated with subjective self-report of high noise exposure. Self-percept of high noise exposure was found to have a 100% sensitivity and a 0% false-negative rate. In other words, all nine individuals who were deemed to be at high risk for NIHL based on AYE values also reported that they had been exposed to loud noise at some point. However, self-report of high noise exposure was associated with a low specificity (3.61%) and a high false-positive rate (96.38%); 160 individuals who had AYE values < 1 answered “yes” to being exposed to high noise levels. There was no statistically significant association between self-perception of high noise exposure and calculated AYE values [χ2(1, n = 175) = 0.337, P = 0.725].
Nature of nonoccupational noise exposure
Participation in nonoccupational activities associated with noise exposure
Percent of participants engaged in each of the nonoccupational activities queried by Neitzel et al., Beach et al., and Johnson et al. are summarized for all survey participants, male survey participants, and female survey participants in [Table 2]. When using the questionnaire developed by Neitzel et al., the highest percentage of participation was reported for loud recreational activities (defined as “attending concerts, dances, races, or commercial sporting events”). This was followed by power tool usage, operation of heavy machinery, riding snowmobiles, and riding motorcycles. None of the participants reported flying aircrafts. When using the Beach et al. questionnaire, survey data indicated that the highest percentage of participation was associated with attending concerts/live music venues, followed by attending sporting events, pubs, night clubs, and fitness classes. For the NEQ developed by Johnson et al., the highest percentage of participation was reported for listening to music via speakers, followed by listening to music via headphones, attending sporting events, using power tools, riding motorized vehicles, using heavy equipment, and playing musical instruments.
Amount of time engaged in nonoccupational activities associated with noise exposure
Mean, standard deviation, and amount of time spent (hours/year) in each of the nonoccupational activities in the Neitzel et al. and Johnson et al. questionnaires are summarized for all survey participants, male survey participants, and female survey participants in [Table 3]. For data collected using the questionnaire developed by Neitzel et al., the number of hours/year spent in power tool usage was the highest, followed by use of heavy machinery, attendance at loud recreational activities, riding motorcycles, and riding snowmobiles. When the NEQ was administered, the data indicated that the greatest amount of time (hours/year) was spent in listening to music via speakers followed by listening to music via headphones, playing musical instruments, attending sporting/entertainment events, using motorized vehicles, using power tools, and using heavy equipment.
Annual noise exposure scores
Mean, standard deviation, and range of annual nonoccupational noise exposure (measured in LA2000hn, LAeq8760h, and AYE) obtained in each questionnaire are summarized for all survey participants, male survey participants, and female survey participants in [Table 4]. For participant data obtained using the survey questions in Neitzel et al., the average LA2000hn across all participants was 72.51 (SD = 7.56). Further, the average LA2000hn value was significantly greater in male survey participants (n = 63, mean = 76.17, SD = 8.74) as compared to female survey participants [n = 112, mean = 70.49, SD = 5.94; t(173) = 5.06, P < 0.001]. The effect size of this difference (Mdiff = 5.63, 95% CI: 3.43–7.83) is large (d = 0.80, 95% CI: 0.48–1.12). LA2000hn values exceeding 85 dBA (cutoff determining risk for NIHL) occurred in 7.4% (13/175 subjects) of the participants. These estimates were obtained using the average mid-range of exposure levels associated with each episodic activity obtained from the literature as reported in a study by Neitzel et al. For data obtained using the NEQ, the average LAeq8760h (ANE) across all participants was 70.42 (SD = 6.03), with average ANE values significantly greater in male (n = 63, mean = 73.06, SD = 6.75) as compared to female survey participants [n = 112, mean = 68.94, SD = 5.03; t(173) = 4.58, P < 0.001]. The effect size of this difference (Mdiff = 4.11, 95% CI: 2.34–5.89) is large (d = 0.72, 95% CI 0.40–1.04). LAeq8760h values exceeding 79 (cutoff determining risk for NIHL) occurred in 11.42%% (20/175 subjects) of the participants. When examining participant data obtained by administering the Beach et al. questionnaire, the average AYE across all participants was 0.22 (SD = 0.36). Average AYE value was greater in female (mean = 0.26, SD =0.42) as compared to male survey participants (mean = 0.16, SD = 0.22). However, the difference in average AYE values between males and females (Mdiff = −0.10, 95% CI: −0.22–0.01) was not statistically significant [t(173) = −1.79, P = 0.075]. AYE values exceeding one (cutoff determining risk for NIHL) occurred in 5.14% (9/175 subjects) of the participants.
|Table 4 Descriptive statistics for the annual noise exposure for the three questionnaires used in this study|
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| Discussion|| |
The major findings of this study demonstrate that (i) there was a strong significant positive correlation between the scores obtained via the Johnson et al. and the Neitzel et al. questionnaires, (ii) self-perception of noise exposure does not align with quantification of annual noise exposure, (iii) among the various noisy nonoccupational activities queried, participation was greatest in music-related activities and loud recreational activities (e.g., concert attendance), (iv) both average annual noise exposure values as well as the number of individuals exceeding cutoff values associated with a high-risk for NIHL from noise exposure were lower as compared to means and percentages reported in the original surveys, and (v) there was a differential effect of sex on average annual noise exposure values depending on the questionnaire used.
Agreement between the questionnaires
One of the goals of this study was to compare and contrast the questionnaires developed by Neitzel et al., Beach et al., and Johnson et al. that quantify nonoccupational noise exposure. LoA plots and correlational analyses were performed to answer the question. The zero bias for all Band–Altman plots was expected because the noise exposure scores from all the three questionnaires were converted to z-scores before performing the analyses. Strong significant correlation, smaller standard deviation of the differences, fewer participants outside the LoA lines, and zero bias between Johnson et al. and Neitzel et al. noise scores indicate that these two questionnaires measure similar underlying constructs of noise exposure. However, weak nonsignificant correlation, larger standard deviation of the differences, more participants outside the LoA lines, and zero bias between the comparisons that had Beach et al. noise score indicated that the Beach et al. questionnaire measured a different underlying construct of noise exposure compared to Johnson et al. and Neitzel et al. questionnaires. This is evident in the specific nonoccupational noisy activities included each of the three questionnaires [see [Table 1]. Consider the questionnaire items in Neitzel et al., and Johnson et al. Per Johnson et al., the NEQ was based on the questionnaire developed by Neitzel et al. Four of the five episodic activities listed in the Neitzel et al. questionnaire are identical to activities queried by Johnson et al.: use of power tools, machinery, motorized vehicles (motorcycles, snowmobiles/jet skis), and flying aircrafts. The fifth episodic activity queried by Neitzel et al. is attendance at loud recreational events, defined as “attending concerts, dances, races, or commercial sporting events”; the parallel item on the NEQ was attending sporting/entertainment events. In addition to these activities, ANE calculations in Johnson et al. included activities related to listening to music (via headphones, speakers, or playing instruments). Listening to music was not considered as part of the LA2000hn calculation for the data corresponding to the Neitzel et al. questionnaire in the current study. This activity was excluded from LA2000hn calculation in the current study as Neitzel et al. considered it a part of routine noise exposures instead of episodic noise exposures; only episodic noise exposures were included in annual noise exposure calculations in the current study. Other than this difference, the items included for annual noise exposure calculation were identical across the two questionnaires. However, overlap between questionnaire items is minimal when considering the Beach et al. versus Neitzel et al. or Johnson et al. questionnaires. Specifically, only two out of five activities on the Beach et al. questionnaire (live sporting events and concerts) match activities listed on the two other questionnaires. The remaining activities listed by Beach et al. (pubs/bars/registered clubs, fitness classes, and nightclubs) are not explicitly queried by Neitzel et al. or Johnson et al., although one may argue that questionnaire participants could list these activities as “entertainment.” Thus, the observations of statistical agreement and correlation between the three questionnaires are likely driven by the (dis)similarities between the specific nonoccupational activities queried by these questionnaires.
Self-perception of noise exposure versus quantification of annual noise exposure
In the current study, the question related to self-perception of exposure to loud noise (“have you ever been exposed to loud noise?”) was chosen to reflect commonly asked questions related to noise exposure appearing on most audiological case histories. When compared to quantified scores of noise exposure, self-report of exposure to loud noise was highly sensitive but associated with poor specificity and a high false-positive rate. This result suggests that commonly utilized case history questions pertaining to nonoccupational noise exposure may be too broad and not serve as a feasible screening tool for predicting high levels of nonoccupational noise exposure. This is because many individuals without significant nonoccupational noise exposure would report being exposed to high levels of noise; these individuals are less likely to develop auditory symptoms related to noise exposure. Such an outcome has consequences for effectiveness of noise awareness counseling. For example, consider that all patients who report significant exposure to high levels of nonoccupational noise are provided with counseling related to prevention and awareness of nonoccupational noise exposure when only a few truly have such exposure and experience related auditory consequences. In such a scenario, the information provided during counseling may be considered too broad and deemed irrelevant, and not have the necessary impact on individuals who should actually follow this advice to minimize or prevent NIHL. In contrast, utilizing a method of estimating nonoccupational noise exposure that is both sensitive and specific will ensure that messaging related to prevention and awareness of noise exposure is targeted and customized to those who actually need it.
Nature of noise exposure
With a few minor exceptions, the current data largely reflect the patterns reported by Neitzel et al., Beach et al., and Johnson et al. in terms of the percentage of participants engaged in the queried nonoccupational noisy activities, as well as the amount of time (hours/year) spent in each activity. A uniform pattern noted across the current data obtained from administering the three questionnaires was that the majority of participants reported exposure to noise from listening to music and attending loud recreational activities. This result was generally consistent with the data reported in the original surveys, with the highest participant engagement reported for loud recreational activities (defined as “attending concerts, dances, races, or commercial sporting events”), nightclub attendance, and listening to music.
Average annual noise exposure values in the current data obtained to the Neitzel et al., Beach et al., and Johnson et al. questionnaires were consistently lower than the average annual noise exposure scores reported in the original questionnaires. In the current study, the average LA2000hn value was 72.51 dBA, lower as compared to 78 dBA in the original data presented in Neitzel et al. Similarly, the average AYE value was 0.22 in the current data, lower as compared to 0.75 (weighted average for age 18–24 years), 0.46 (weighted average for age 25–29 years), and 0.30 (weighted average for 30–35 years) in the data reported by Beach et al. Likewise, the average LAeq8760h value was 70.42 dBA for the current survey participants as compared to 75 dBA recorded by Johnson et al. In the same way, the percent of individuals found to exceed cutoff values associated with a risk of NIHL utilized by Neitzel et al., Beach et al., and Johnson et al. and categorized as high risk for NIHL was consistently lower in the current data as compared to the data reported in the original questionnaires. Specifically, LA2000hn values exceeded 85 dBA in 7.4% of the participants in the current data versus 19% reported by Neitzel et al.; AYE values exceeded one in 5.14% of the participants in the current data versus 14.1% reported by Beach et al.; and LAeq8760h values exceeded 79 in 11.42% of the participants in the current data versus 32% in the original Johnson et al. data. The discrepancies noted between the current data and the findings in the original questionnaires may be attributed in part to differences in the methods of calculation of annual noise exposure values. Certain items were intentionally omitted from the Neitzel et al. and Johnson et al. questionnaires in the current study to ensure some degree of parity across the three questionnaires being compared. For instance, in addition to episodic nonoccupational noise exposures, the original questionnaires in Neitzel et al. and Johnson et al. included noise exposures from routine activities (e.g., traveling in car/bus, yard work, computer/television use, and eating at a restaurant) in their final calculations of annual noise exposure. In contrast, Beach et al. only queried participants on specific leisure activities and did not take into consideration routine noise exposures. Further, in their 2004 study, Neitzel et al. estimated routine noise exposure levels using dosimetry data obtained from study participants, as opposed to sound levels published in prior literature. Additionally, Johnson et al. include noise exposures from occupational sources in their final estimate of annual noise exposure, which are excluded in the noise exposure calculations in Neitzel et al. and Beach et al. questionnaires. Items related to routine noise exposure (appearing in Neitzel et al. and Johnson et al.) and occupational noise exposure (appearing in Johnson et al.) were removed from the questionnaires administered in the current study. These items were omitted so that annual noise exposure values obtained for each questionnaire reflected only nonoccupational, episodic/leisure activities for which sound levels were reported in the literature, thereby facilitating an equivalent comparison across all questionnaires. However, in doing so, the annual noise exposure values calculated in the Neitzel et al. and Johnson et al. questionnaires as administered in the current study reflect fewer items than the corresponding values reported in the original questionnaires. This may explain the differences in average annual noise exposure values, as well as percentage of individuals exceeding the cutoff values associated with NIHL risk in the current data versus original reports.
The differences in the average ANE values as well as percentage of individuals classified as “at risk” for NIHL in the current data as compared to the data reported by Johnson et al. could also be attributed in part to the differences in percentage of participants reporting listening to music via headphones [94.86% (current data) versus 86% (original study)], and the interactions between participation rate, sound level, duration, and frequency of exposure on the dose level associated with a given noise source. As discussed by Johnson et al., the average sound level associated with listening to music via headphones is 76 dB LAeq, as compared to a much higher average sound level of 97 dB LAeq for heavy machinery. Hence, for the current data which report a mean of 372.48 hours spent in listening to music via earphones, the average dose associated with this activity would contribute 2.13% toward the ANE calculation. On the other hand, a mean of 13.67 hours spent in operating heavy machinery, as reported in the current study, would translate to a dose of 9.99% in the ANE. Thus, increased participation in listening to music in conjunction with the lower dose associated with this activity may be partly responsible for the differences in the ANE values obtained in the original Johnson et al. questionnaire versus that administered in the current study.
Finally, average annual noise exposure values were found to be significantly greater in males as compared to females for data obtained to the Neitzel et al. and Johnson et al. questionnaires, but the reverse was observed for the Beach et al. questionnaire. In general, the literature describing the effects of sex on nonoccupational noise exposure is ambiguous. Studies have reported no differences in nonoccupational noise exposure between male and female listeners, greater noise exposure in male listeners, and interaction effects of sex and education level for leisure noise exposure such that no sex differences were observed except for low education levels when males reported higher levels of noise exposure. For the current data, the differential effects of sex on annual nonoccupational noise exposure metrics observed across the three studies may be attributed to the specific activities queried by each questionnaire, dose levels associated with each activity, and participation rates of male versus female participants in each activity. The similarities and differences between the specific items across the three questionnaires have already been discussed above; questionnaire items are summarized in [Table 1]. Further, for the questionnaires developed by Neitzel et al. and Johnson et al., average participation rates are consistently greater for male as compared to female participants for the following activities: power tools, machinery, and motorized vehicles [Table 3]. Participation rates are comparable across males and females, or marginally greater for female participants for activities related to music listening, sporting/entertainment, and loud recreational events. As previously discussed, the dose levels associated with power tools, machinery, and motorized vehicles are greater than those estimated for activities such as listening to music. Thus, for the Neitzel et al. and Johnson et al. data in the current study, it follows that greater participation rates in activities with higher dose will result in a high ANE value for male participants. In contrast, even though participation rates may be higher in female participants for activities such as music listening, the contribution of such activities to the overall noise dose may not be as significant, which would result in a lower ANE value for these listeners. For the data obtained in response to the Beach et al. questionnaire, greater participation rates were observed for female as compared to male participants for four out of five activities. Recall too that the Beach et al. questionnaire included only two items (concerts and live sporting events) that overlapped with the items queried by the Neitzel et al. and Johnson et al. Participation rates for these activities were greater for female as compared to male participants in the Beach et al. questionnaire as compared to the Neitzel et al. and Johnson et al. questionnaires administered in the present study. None of the high-dose activities where male participants reported greater participation (e.g., power tools, heavy machinery, motorized vehicles), in the current study or the original questionnaire data published by Neitzel et al. and Johnson et al., appeared in the Beach et al. questionnaire. Together, these factors explain why female participants had a significantly higher AYE than male participants for the Beach et al. data collected in the current study.
Overall, two major themes were emergent from the nature of noise exposures observed across the three questionnaires administered in the current study that could shape targeted counseling regarding awareness of the auditory risks of nonoccupational noise exposure in the participating cohort. First, young adults, such as those surveyed here, may benefit from receiving information related to potentially damaging effects of excessive noise levels that could be experienced from listening to music and attending loud recreational events, acceptable sound levels for these activities, means to protect hearing, and when and how to seek professional services for hearing healthcare. Second, when providing activity-specific noise awareness information, counseling might be more effective when targeted toward male listeners for certain activities (e.g., use of power tools and heavy machinery) and toward female listeners for certain other activities (e.g., attending fitness classes and night clubs).
Limitations and future directions
In our knowledge, this is the first study assessing the statistical agreement between questionnaires describing quantitative metrics of annual nonoccupational noise exposure, as well as the correlation between such metrics and a self-percept of noise exposure. In the long term, the outcomes of this analysis could assist in comparing noise exposure quantifications across research studies, and determining if and how these questionnaires may be utilized clinically to effectively identify and counsel those at risk for NIHL. However, a limitation of this study was that the annual noise exposure values calculated using the responses obtained to the Neitzel et al. and Johnson et al. questionnaires in the current study did not reflect all original questionnaire items. Items from the original questionnaires were eliminated to ensure an equivalent comparison of nonoccupational noise exposure levels calculated across all three questionnaires. As a consequence, comparisons between the current data and those obtained from the original questionnaires were limited in scope. Second, some survey participants reported no engagement in any of the episodic nonoccupational noisy activities listed in the questionnaire developed by Neitzel et al. Due to constraints with applying the mathematical formula for annual noise exposure estimation to a value of zero, the data from these survey participants could not be considered for statistical analysis. Additionally, correlations with self-percept of noise exposure could only be performed against AYE values obtained by administering the Beach et al. questionnaire, which was completed in its entirety, and not against “incomplete” annual noise exposure values computed by administering either the Neitzel et al. or Johnson et al. questionnaires. Future studies performing such comparative analyses should consider the selection of questionnaires that are more equitable in terms of nature of noise exposure activities queried. Finally, administration of such questionnaires can highlight the nature of noise exposure experienced by participating populations, allowing for the development of targeted strategies to increase awareness of (un)acceptable noise levels, and resources to prevent, diagnose, and manage NIHL.
This article is based partially on a thesis submitted by Dr Eryn Evans in partial fulfillment of the requirements for the degree of Doctor of Audiology. The authors wish to thank Dr Eryn Evans for her assistance with survey design, dissemination, and portions of data collection.
Financial support and sponsorship
The work was partially supported by Towson University’s College of Health Professions’ Summer Undergraduate Research Internship awarded to KA.Conflicts of interest
There are no conflicts of interest.
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Department of Speech-Language Pathology and Audiology, Towson University, 8000 York Road, Towson, Maryland 21252
Source of Support: None, Conflict of Interest: None
[Table 1], [Table 2], [Table 3], [Table 4]