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Samuel Melamed - One of the best experts on this subject based on the ideXlab platform.

  • Industrial Noise exposure and risk factors for cardiovascular disease findings from the cordis study
    Noise & Health, 1999
    Co-Authors: Samuel Melamed, Estela Kristalboneh, Paul Froom
    Abstract:

    Previous studies of the association between occupational Noise exposure and cardiovascular disease (CVD) or risk factors for CVD are primarily either cross-sectional or retrospective, whereas the design of the CORDIS study was both cross-sectional and longitudinal. It had three phases: Phase I was conducted during 1985-87 among 6,016 employees from 21 factories. Recorded were medical, ergonomic, environmental (including Noise levels at the various work stations) and psychological data. Phase II was conducted during 1988-90, at 18 of the 21 original factories and included similar data collected from 3,509 subjects. Phase III was conducted during the years 1995-96 and 4,995 workers who participated in Phases I and II completed questionnaires pertaining to medical, occupational and life style variables. Mortality and cancer morbidity data were obtained over an 8 year follow-up period for all subjects. Results from Phase I, revealed no association between Noise exposure and resting blood pressure. Positive association was found for serum lipids in women and in young men. Noise annoyance had an additive effect on this outcome. In addition, recurrent daily Noise exposure was found to be associated with elevated acute resting heart rate. Results of Phase II showed that chronic exposure to high Noise levels during the 2-4 years of the follow-up resulted in changes of 3.9 mmHg in SBP and 3.3 mmHg in DBP, among workers performing complex jobs. In workers performing simple jobs these changes were 0.3 and 0.4 mmHg. Thus the type of work performed appears to be a significant factor. Results of Phase III revealed that there was a trend for positive association between past Noise exposure measured at Phase I and 8 years incidence of cardiovascular morbidity, mortality and total mortality. This trend was statistically significant for total mortality (hazard ratio = 1.97, 95% CI 1.28-4.54) even after controlling for possible confounders. In summary, tests for association between Noise exposure and cardiovascular risk factors, or cardiovascular morbidity and mortality, and total mortality have yielded mixed results. Reasons for this are discussed, as well as suggestions for further research.

  • the effects of chronic Industrial Noise exposure on urinary cortisol fatigue and irritability a controlled field experiment
    Journal of Occupational and Environmental Medicine, 1996
    Co-Authors: Samuel Melamed, Shelly Bruhis
    Abstract:

    This quasiexperimental field study explored the effect of Noise attenuation on urinary cortisol excretion (sampled three times, at 6:30 and 10:30 AM and 1:30 PM) and reported fatigue and postwork irritability among 35 healthy Industrial workers chronically exposed to high ambient Noise levels (> 85 dB [A]) without using ear protectors. The results indicated that under conditions of chronic Noise exposure the cortisol level at the end of the workshift was high and almost reached the morning level. This elevation in cortisol excretion was accompanied by high levels of accumulated fatigue and postwork irritability. Attenuating the Noise reaching the eardrum by 30 to 33 dB, by fitting the same workers with earmuffs for a period of 7 working days, resulted in a significant improvement in both psychological and physiological stress reactions. Besides decreasing Noise intensity, no other changes were made, either to ongoing work activities or to the other characteristics of the ambient Noise. The cortisol level declined steadily during the workshift and exhibited the normal cortisol diurnal rhythm. At the end of the workshift, this level was significantly lower (P < .05) than that observed under the chronic Noise-exposure condition. There was also a concomitant reduction in reported fatigue (P < .05) and postwork irritability (P < .01). These findings demonstrate the "net" contribution of ambient Noise to elevating stress reactions to regular work demands.

  • acute and chronic effects of Noise exposure on blood pressure and heart rate among Industrial employees the cordis study
    Archives of Environmental Health, 1995
    Co-Authors: Estela Kristalboneh, Samuel Melamed, Gil Harari, Manfred S Green
    Abstract:

    Abstract The effects of Industrial Noise on resting heart rate and blood pressure were studied in 3 105 blue-collar workers. Heart rate and blood pressure were measured in different workers at various times during the workday. After controlling for several possible confounders, we found that resting heart rate in females was associated positively with Noise intensity (p = .036) and with time of day (p = .054). In males, resting heart rate was associated with Noise intensity; however, such association was related to time of day (p = .046). No such associations were found for blood pressure in either sex. We plotted the mean resting heart rate by time of day for workers exposed to high [≥ 80 db(A)] and low Noise, and no difference was evident with respect to morning heart rate in either sex. After 4 h of Noise exposure for males (and less time for females), individuals who were exposed to high Noise had higher heart rates; however, in females this was not observed at the end of the workday. Thus, recurrent ...

Wei Qiu - One of the best experts on this subject based on the ideXlab platform.

  • machine learning models for the hearing impairment prediction in workers exposed to complex Industrial Noise a pilot study
    Ear and Hearing, 2019
    Co-Authors: Yanxia Zhao, Yu Tian, Meibian Zhang, Hongwei Xie, Wei Qiu
    Abstract:

    OBJECTIVES To demonstrate the feasibility of developing machine learning models for the prediction of hearing impairment in humans exposed to complex non-Gaussian Industrial Noise. DESIGN Audiometric and Noise exposure data were collected on a population of screened workers (N = 1,113) from 17 factories located in Zhejiang province, China. All the subjects were exposed to complex Noise. Each subject was given an otologic examination to determine their pure-tone hearing threshold levels and had their personal full-shift Noise recorded. For each subject, the hearing loss was evaluated according to the hearing impairment definition of the National Institute for Occupational Safety and Health. Age, exposure duration, equivalent A-weighted SPL (LAeq), and median kurtosis were used as the input for four machine learning algorithms, that is, support vector machine, neural network multilayer perceptron, random forest, and adaptive boosting. Both classification and regression models were developed to predict Noise-induced hearing loss applying these four machine learning algorithms. Two indexes, area under the curve and prediction accuracy, were used to assess the performances of the classification models for predicting hearing impairment of workers. Root mean square error was used to quantify the prediction performance of the regression models. RESULTS A prediction accuracy between 78.6 and 80.1% indicated that the four classification models could be useful tools to assess Noise-induced hearing impairment of workers exposed to various complex occupational Noises. A comprehensive evaluation using both the area under the curve and prediction accuracy showed that the support vector machine model achieved the best score and thus should be selected as the tool with the highest potential for predicting hearing impairment from the occupational Noise exposures in this study. The root mean square error performance indicated that the four regression models could be used to predict Noise-induced hearing loss quantitatively and the multilayer perceptron regression model had the best performance. CONCLUSIONS This pilot study demonstrated that machine learning algorithms are potential tools for the evaluation and prediction of Noise-induced hearing impairment in workers exposed to diverse complex Industrial Noises.

  • development of an automatic classifier for the prediction of hearing impairment from Industrial Noise exposure
    Journal of the Acoustical Society of America, 2019
    Co-Authors: Yanxia Zhao, Yu Tian, Meibian Zhang, Wei Qiu
    Abstract:

    The ISO-1999 [(2013). International Organization for Standardization, Geneva, Switzerland] standard is the most commonly used approach for estimating Noise-induced hearing trauma. However, its insensitivity to Noise characteristics limits its practical application. In this study, an automatic classification method using the support vector machine (SVM) was developed to predict hearing impairment in workers exposed to both Gaussian (G) and non-Gaussian (non-G) Industrial Noises. A recently collected human database (N = 2,110) from Industrial workers in China was used in the present study. A statistical metric, kurtosis, was used to characterize the Industrial Noise. In addition to using all the data as one group, the data were also broken down into the following four subgroups based on the level of kurtosis: G/quasi-G, low-kurtosis, middle-kurtosis, and high-kurtosis groups. The performance of the ISO-1999 and the SVM models was compared over these five groups. The results showed that: (1) The performance of the SVM model significantly outperformed the ISO-1999 model in all five groups. (2) The ISO-1999 model could not properly predict hearing impairment for the high-kurtosis group. Moreover, the ISO-1999 model is likely to underestimate hearing impairment caused by both G and non-G Noise exposures. (3) The SVM model is a potential tool to predict hearing impairment caused by diverse Noise exposures.

  • the value of a kurtosis metric in estimating the hazard to hearing of complex Industrial Noise exposures
    Journal of the Acoustical Society of America, 2013
    Co-Authors: Wei Qiu, Roger P Hamernik, Robert I Davis
    Abstract:

    A series of Gaussian and non-Gaussian equal energy Noise exposures were designed with the objective of establishing the extent to which the kurtosis statistic could be used to grade the severity of Noise trauma produced by the exposures. Here, 225 chinchillas distributed in 29 groups, with 6 to 8 animals per group, were exposed at 97 dB SPL. The equal energy exposures were presented either continuously for 5 d or on an interrupted schedule for 19 d. The non-Gaussian Noises all differed in the level of the kurtosis statistic or in the temporal structure of the Noise, where the latter was defined by different peak, interval, and duration histograms of the impact Noise transients embedded in the Noise signal. Noise-induced trauma was estimated from auditory evoked potential hearing thresholds and surface preparation histology that quantified sensory cell loss. Results indicated that the equal energy hypothesis is a valid unifying principle for estimating the consequences of an exposure if and only if the equivalent energy exposures had the same kurtosis. Furthermore, for the same level of kurtosis the detailed temporal structure of an exposure does not have a strong effect on trauma.

D Jerwood - One of the best experts on this subject based on the ideXlab platform.

  • occupational Noise exposure and hearing loss of workers in two plants in eastern saudi arabia
    Annals of Occupational Hygiene, 2001
    Co-Authors: Hafiz O Ahmed, John H Dennis, O Badran, M Ismail, Seifeddin G Ballal, A Ashoor, D Jerwood
    Abstract:

    Abstract Objective: To determine the prevalence of hearing loss associated with occupational Noise exposure and other risk factors. Design: A cross-sectional study involving 269 exposed and 99 non-exposed subjects (non-Industrial Noise exposed subjects) randomly selected. Current Noise exposure was estimated using both sound level meter and Noise-dosimeter. Past Noise exposure was estimated by interview questionnaire. Otoscopic examination and conventional frequency (0.25–8 kHz) audiometry were used to assess the hearing loss in each subject. Results: 75% (202 subjects) from the exposed group were exposed to a daily Leq above the permissible level of 85 dB(A) and most (61%) of these did not and had never used any form of hearing protecion. Hearing loss was found to be bilateral and symmetrical in both groups. Bivariate analysis showed a significant hearing loss in the exposed vs non-exposed subjects with a characteristic dip at 4 kHz. Thirty eight percent of exposed subjects had hearing impairment, which was an 8-fold higher rate than that found for non-exposed subjects. Multivariate analysis indicated exposure to Noise was the primary, and age the secondary predictor of hearing loss. Odds of hearing impairment were lower for a small sub-group of exposed workers using hearing protection (N=19) in which logistic regression analysis showed the probability of workers adopting hearing protective devices increased with Noise exposure, education, and awareness of Noise control. Hearing loss was also greater amongst those who used headphones to listen to recorded cassettes. Conclusion: Gross occupational exposure to Noise has been demonstrated to cause hearing loss and the authors believe that occupational hearing loss in Saudi Arabia is a widespread problem. Strategies of Noise assessment and control are introduced which may help improve the work environment.

  • high frequency 10 18 khz hearing thresholds reliability and effects of age and occupational Noise exposure
    Occupational Medicine, 2001
    Co-Authors: Hafiz O Ahmed, John H Dennis, O Badran, M Ismail, Seifeddin G Ballal, A Ashoor, D Jerwood
    Abstract:

    The objective was to investigate the reliability and effects of age and Noise on high-frequency hearing thresholds. A cross-sectional study was used involving 187 exposed and 52 non-Industrial Noise-exposed subjects selected randomly from Noise-exposed and non-Industrial Noise-exposed subjects, respectively. Each subject was tested with both conventional-frequency (0.25–8 kHz) and high-frequency (10–18 kHz) audiometry. Test–retest results showed that high-frequency audiometry (HFA) was as reliable as the conventional procedure. Although the inter-subject variation was large, the intra-subject variation was small, indicating that HFA can be used more reliably than the conventional procedure to monitor individual cases over time. Both the hearing threshold at high frequencies and the upper frequency limit deteriorated as a function of age and frequency. The exposed subjects had significantly higher hearing thresholds than the non-exposed subjects at all the high frequencies tested, the difference between the two groups being greatest at 14 kHz. Multivariate analysis indicated that age was the primary predictor and Noise exposure the secondary predictor of hearing thresholds in a high frequency range (10–18 kHz). In contrast, multivariate analysis indicated the reverse order—Noise exposure as the primary predictor, then age—for a conventional frequency range (0.25–8 kHz). The results of this study suggest that HFA might be used as an early indicator for Noise-induced hearing loss and acoustic trauma rather than audiometry at a conventional frequency (4 kHz), particularly for younger groups.

Meibian Zhang - One of the best experts on this subject based on the ideXlab platform.

  • new metrics needed in the evaluation of hearing hazard associated with Industrial Noise exposure
    Ear and Hearing, 2021
    Co-Authors: Meibian Zhang, Hongwei Xie, Jiena Zhou, Xin Sun, Hua Zou, Lifang Zhou, Ming Zhang, Chucri A Kardous, Thais C Morata, William J Murphy
    Abstract:

    OBJECTIVES To evaluate (1) the accuracy of the International Organization for Standardization (ISO) standard ISO 1999 [(2013), International Organization for Standardization, Geneva, Switzerland] predictions of Noise-induced permanent threshold shift (NIPTS) in workers exposed to various types of high-intensity Noise levels, and (2) the role of the kurtosis metric in assessing Noise-induced hearing loss (NIHL). DESIGN Audiometric and shift-long Noise exposure data were acquired from a population (N = 2,333) of screened workers from 34 industries in China. The entire cohort was exclusively divided into subgroups based on four Noise exposure levels (85 ≤ LAeq.8h 10 years), and four kurtosis categories (Gaussian, low-, medium-, and high-kurtosis). Predicted NIPTS was calculated using the ISO 1999 model for each participant and the actual measured NIPTS was corrected for age and sex also using ISO 1999. The prediction accuracy of the ISO 1999 model was evaluated by comparing the NIPTS predicted by ISO 1999 with the actual NIPTS. The relation between kurtosis and NIPTS was also investigated. RESULTS Overall, using the average NIPTS value across the four audiometric test frequencies (2, 3, 4, and 6 kHz), the ISO 1999 predictions significantly (p < 0.001) underestimated the NIPTS by 7.5 dB on average in participants exposed to Gaussian Noise and by 13.6 dB on average in participants exposed to non-Gaussian Noise with high kurtosis. The extent of the underestimation of NIPTS by ISO 1999 increased with an increase in Noise kurtosis value. For a fixed range of Noise exposure level and duration, the actual measured NIPTS increased as the kurtosis of the Noise increased. The Noise with kurtosis greater than 75 produced the highest NIPTS. CONCLUSIONS The applicability of the ISO 1999 prediction model to different types of Noise exposures needs to be carefully reexamined. A better understanding of the role of the kurtosis metric in NIHL may lead to its incorporation into a new and more accurate model of hearing loss due to Noise exposure.

  • machine learning models for the hearing impairment prediction in workers exposed to complex Industrial Noise a pilot study
    Ear and Hearing, 2019
    Co-Authors: Yanxia Zhao, Yu Tian, Meibian Zhang, Hongwei Xie, Wei Qiu
    Abstract:

    OBJECTIVES To demonstrate the feasibility of developing machine learning models for the prediction of hearing impairment in humans exposed to complex non-Gaussian Industrial Noise. DESIGN Audiometric and Noise exposure data were collected on a population of screened workers (N = 1,113) from 17 factories located in Zhejiang province, China. All the subjects were exposed to complex Noise. Each subject was given an otologic examination to determine their pure-tone hearing threshold levels and had their personal full-shift Noise recorded. For each subject, the hearing loss was evaluated according to the hearing impairment definition of the National Institute for Occupational Safety and Health. Age, exposure duration, equivalent A-weighted SPL (LAeq), and median kurtosis were used as the input for four machine learning algorithms, that is, support vector machine, neural network multilayer perceptron, random forest, and adaptive boosting. Both classification and regression models were developed to predict Noise-induced hearing loss applying these four machine learning algorithms. Two indexes, area under the curve and prediction accuracy, were used to assess the performances of the classification models for predicting hearing impairment of workers. Root mean square error was used to quantify the prediction performance of the regression models. RESULTS A prediction accuracy between 78.6 and 80.1% indicated that the four classification models could be useful tools to assess Noise-induced hearing impairment of workers exposed to various complex occupational Noises. A comprehensive evaluation using both the area under the curve and prediction accuracy showed that the support vector machine model achieved the best score and thus should be selected as the tool with the highest potential for predicting hearing impairment from the occupational Noise exposures in this study. The root mean square error performance indicated that the four regression models could be used to predict Noise-induced hearing loss quantitatively and the multilayer perceptron regression model had the best performance. CONCLUSIONS This pilot study demonstrated that machine learning algorithms are potential tools for the evaluation and prediction of Noise-induced hearing impairment in workers exposed to diverse complex Industrial Noises.

  • development of an automatic classifier for the prediction of hearing impairment from Industrial Noise exposure
    Journal of the Acoustical Society of America, 2019
    Co-Authors: Yanxia Zhao, Yu Tian, Meibian Zhang, Wei Qiu
    Abstract:

    The ISO-1999 [(2013). International Organization for Standardization, Geneva, Switzerland] standard is the most commonly used approach for estimating Noise-induced hearing trauma. However, its insensitivity to Noise characteristics limits its practical application. In this study, an automatic classification method using the support vector machine (SVM) was developed to predict hearing impairment in workers exposed to both Gaussian (G) and non-Gaussian (non-G) Industrial Noises. A recently collected human database (N = 2,110) from Industrial workers in China was used in the present study. A statistical metric, kurtosis, was used to characterize the Industrial Noise. In addition to using all the data as one group, the data were also broken down into the following four subgroups based on the level of kurtosis: G/quasi-G, low-kurtosis, middle-kurtosis, and high-kurtosis groups. The performance of the ISO-1999 and the SVM models was compared over these five groups. The results showed that: (1) The performance of the SVM model significantly outperformed the ISO-1999 model in all five groups. (2) The ISO-1999 model could not properly predict hearing impairment for the high-kurtosis group. Moreover, the ISO-1999 model is likely to underestimate hearing impairment caused by both G and non-G Noise exposures. (3) The SVM model is a potential tool to predict hearing impairment caused by diverse Noise exposures.

Geoggrey Kwabla Amedofu - One of the best experts on this subject based on the ideXlab platform.

  • Industrial Noise pollution and its effects on the hearing capabilities of workers a study from saw mills printing presses and corn mills
    African Journal of Health Sciences, 2005
    Co-Authors: Charles Asamoah Boateng, Geoggrey Kwabla Amedofu
    Abstract:

    The purpose of this study was to ascertain Industrial Noise pollution and its effects on the hearing capabilities of workers. The procedure adopted included Noise measurements, otoscopy, audiometric evaluation and assessment of medical history. The results showed that Noise levels in corn mills and saw mills exceed 85dBA. The average Noise level measured in the printing industry was 85dBA. It was also found that 23%, 20% and 7.9% of workers in corn mills, saw mills and the printing industry have evidence of Noise-induced hearing loss (NIHL). A highly significant correlation was found between Noise exposure level, duration of exposure and the development of NIHL in corm mills and saw mills but not in the printers. Hearing - impairment was also observed at the speech frequencies among some of the workers exposed to hazardous Noise. These findings suggest that more specific intervention is required to protect workers exposed to such hazards at the work places employed in this study. African Journal of Health Sciences Vol.11(1&2) 2004: 55-60

  • Industrial Noise pollution and its effects on the hearing capabilities of workers a study from saw mills printing presses and corn mills
    African Journal of Health Sciences, 2005
    Co-Authors: Charles Asamoah Boateng, Geoggrey Kwabla Amedofu
    Abstract:

    The purpose of this study was to ascertain Industrial Noise pollution and its effects on the hearing capabilities of workers. The procedure adopted included Noise measurements, otoscopy, audiometric evaluation and assessment of medical history. The results showed that Noise levels in corn mills and saw mills exceed 85dBA. The average Noise level measured in the printing industry was 85dBA. It was also found that 23 %, 20 % and 7.9 % of workers in corn mills, saw mills and the printing industry have evidence of Noise-induced hearing loss (NIHL). A highly significant correlation was found between Noise exposure level, duration of exposure and the development of NIHL in corm mills and saw mills but not in the printers. Hearing - impairment was also observed at the speech frequencies among some of the workers exposed to hazardous Noise. These findings suggest that more specific intervention is required to protect workers exposed to such hazards at the work places employed in this study.