1
|
Makaruse N, Maslin MRD, Shai Campbell Z. Early identification of potential occupational noise-induced hearing loss: a systematic review. Int J Audiol 2025; 64:419-428. [PMID: 39468424 DOI: 10.1080/14992027.2024.2418354] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 10/08/2024] [Accepted: 10/14/2024] [Indexed: 10/30/2024]
Abstract
OBJECTIVE This systematic review addressed two questions: 1) For which audiometric test frequencies or pure tone averages are hearing threshold levels (HTLs) most susceptible to early occupational noise induced hearing loss (NIHL) before significant damage? 2) Which early flag metric best detects early hearing shifts due to noise for occupational NIHL surveillance? DESIGN Systematic searches were conducted in Ovid MEDLINE(R) and Embase from July 2021 to May 2024. Eligibility was screened by two independent reviewers using Covidence. HTL results were analysed for susceptibility to noise-induced changes, and sensitivity and specificity of early flag metrics were assessed. STUDY SAMPLE Of 175 studies retrieved, 18 met the inclusion criteria. RESULTS Ten studies emphasised the importance of testing at frequencies above 8 kHz, with HTLs at 12, 14, and 16 kHz frequently identified as the most noise susceptible. Conventional frequencies of 3-6 kHz were also noted as susceptible. NIOSH and OSHA metrics had low sensitivity and specificity, but modifications improved their performance to 100% sensitivity and 98% specificity. CONCLUSION The review highlights the need to refine current metrics and explore extended high frequencies for NIHL monitoring. Research is required to determine frequencies for warning metrics and sensitive metrics for early occupational NIHL detection.
Collapse
Affiliation(s)
- Nyasha Makaruse
- School of Psychology, Speech and Hearing, University of Canterbury, Christchurch, New Zealand
- Eisdell Moore Centre for Hearing and Balance Research, Auckland, New Zealand
- Braun School of Public Health, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Mike R D Maslin
- School of Psychology, Speech and Hearing, University of Canterbury, Christchurch, New Zealand
- Eisdell Moore Centre for Hearing and Balance Research, Auckland, New Zealand
| | - Ziva Shai Campbell
- School of Psychology, Speech and Hearing, University of Canterbury, Christchurch, New Zealand
- Eisdell Moore Centre for Hearing and Balance Research, Auckland, New Zealand
| |
Collapse
|
2
|
Nath H, Adhikary SK, Alsulamy S, Kafy AA, Rahaman ZA, Roy S, Hossain MI, Mamun AA. Assessment of index-based traffic noise annoyance level at major road intersections in a tourist city: A case study towards environmental sustainability. Heliyon 2024; 10:e40005. [PMID: 39559207 PMCID: PMC11570300 DOI: 10.1016/j.heliyon.2024.e40005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2024] [Revised: 09/21/2024] [Accepted: 10/30/2024] [Indexed: 11/20/2024] Open
Abstract
Urban noise pollution poses significant challenges to public health and environmental sustainability, particularly in rapidly developing tourist destinations. Noise pollution and associated annoyance level in five major intersections of Cox's Bazar City, Bangladesh, was assessed in this study during the peak tourist season. Noise measurements were conducted using various indices (L10, Leq, and TNI) across morning, midday, and afternoon time slots. TNI scores were compared with Mean Dissatisfaction Score (MDS) standards to assess traffic-induced noise annoyance levels. Additionally, a survey of 675 respondents was conducted to assess their perceptions of noise pollution. Statistical analyses included linear regression for noise indices, multinomial logistic regression for TNI-related dissatisfaction, and ordinal logistic regression for respondents' perceived annoyances. Results revealed significant noise pollution issues, with Leq scores consistently exceeding national guidelines across all intersections and time periods, particularly on weekends during afternoon timeslots. TNI values frequently surpassed standard dissatisfaction regulations, with 19 out of 105 time slots exhibiting extreme dissatisfaction levels. Link Road and Kolatoli Circle intersections consistently showed higher noise levels and dissatisfaction. Over 95% of survey respondents perceived increased noise pollution during peak tourist seasons, with 87.11% describing it as "extremely" or "very" noisy. Longer exposure duration and awareness of health risks were significantly associated with reported perceived annoyance levels. Respondents reported various health impacts, including annoyance (84.44%), headaches (62.37%), and cognitive impairment (44.44%). This comprehensive study provides valuable insights for policymakers, city planners, and environmentalists to develop sustainable urban strategies that balance the acoustic environment with the well-being of residents and tourists alike.
Collapse
Affiliation(s)
- Hrithik Nath
- Department of Civil Engineering, University of Creative Technology Chittagong (UCTC), Chattogram, 4212, Bangladesh
- Department of Civil Engineering, Khulna University of Engineering & Technology, Khulna, 9203, Bangladesh
| | - Sajal Kumar Adhikary
- Department of Civil Engineering, Khulna University of Engineering & Technology, Khulna, 9203, Bangladesh
| | - Saleh Alsulamy
- Department of Architecture, College of Architecture & Planning, King Khalid University, Abha, 61421, Saudi Arabia
| | - Abdulla Al Kafy
- Department of Urban & Regional Planning, Rajshahi University of Engineering & Technology (RUET), Rajshahi, 6204, Bangladesh
| | - Zullyadini A. Rahaman
- Department of Geography & Environment, Faculty of Human Sciences, Sultan Idris Education University, Tanjung Malim, 35900, Malaysia
| | - Srabanti Roy
- Department of Public Health, University of Creative Technology Chittagong (UCTC), Chattogram, 4212, Bangladesh
| | - Mohammad Iqbal Hossain
- Department of Civil Engineering, University of Creative Technology Chittagong (UCTC), Chattogram, 4212, Bangladesh
| | - Abdulla Al Mamun
- Department of Civil Engineering, University of Creative Technology Chittagong (UCTC), Chattogram, 4212, Bangladesh
| |
Collapse
|
3
|
Khajonklin T, Sun YM, Leon Guo YL, Hsu HI, Yoon CS, Lin CY, Tsai PJ. Utilizing Artificial Neural Networks for Establishing Hearing-Loss Predicting Models Based on a Longitudinal Dataset and Their Implications for Managing the Hearing Conservation Program. Saf Health Work 2024; 15:220-227. [PMID: 39035795 PMCID: PMC11255955 DOI: 10.1016/j.shaw.2024.02.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Revised: 02/02/2024] [Accepted: 02/18/2024] [Indexed: 07/23/2024] Open
Abstract
Background Though the artificial neural network (ANN) technique has been used to predict noise-induced hearing loss (NIHL), the established prediction models have primarily relied on cross-sectional datasets, and hence, they may not comprehensively capture the chronic nature of NIHL as a disease linked to long-term noise exposure among workers. Methods A comprehensive dataset was utilized, encompassing eight-year longitudinal personal hearing threshold levels (HTLs) as well as information on seven personal variables and two environmental variables to establish NIHL predicting models through the ANN technique. Three subdatasets were extracted from the afirementioned comprehensive dataset to assess the advantages of the present study in NIHL predictions. Results The dataset was gathered from 170 workers employed in a steel-making industry, with a median cumulative noise exposure and HTL of 88.40 dBA-year and 19.58 dB, respectively. Utilizing the longitudinal dataset demonstrated superior prediction capabilities compared to cross-sectional datasets. Incorporating the more comprehensive dataset led to improved NIHL predictions, particularly when considering variables such as noise pattern and use of personal protective equipment. Despite fluctuations observed in the measured HTLs, the ANN predicting models consistently revealed a discernible trend. Conclusions A consistent correlation was observed between the measured HTLs and the results obtained from the predicting models. However, it is essential to exercise caution when utilizing the model-predicted NIHLs for individual workers due to inherent personal fluctuations in HTLs. Nonetheless, these ANN models can serve as a valuable reference for the industry in effectively managing its hearing conservation program.
Collapse
Affiliation(s)
- Thanawat Khajonklin
- Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan City, Taiwan
| | - Yih-Min Sun
- Department of Occupational Safety and Health, Chung Hwa University of Medical Technology, Tainan County, Taiwan
| | - Yue-Liang Leon Guo
- Department of Environmental and Occupational Medicine, Medical College, National Taiwan University, Taipei City, Taiwan
| | - Hsin-I Hsu
- Environmental and Labor Affairs Division, Southern Taiwan Science Park Bureau, Ministry of Science and Technology, Tainan City, Taiwan
| | - Chung Sik Yoon
- Department of Environmental Health Sciences, Seoul National University Graduate School of Public Health, Seoul, Republic of Korea
| | - Cheng-Yu Lin
- Department of Otolaryngology, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan City, Taiwan
| | - Perng-Jy Tsai
- Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan City, Taiwan
| |
Collapse
|
4
|
Chen MB, Li MH, Wu LY, Wang R, Long X, Zhang L, Sun W, Guo WW, Pan Y, Zhang YS, Lin C, Shi X, Yang SM. Oridonin employs interleukin 1 receptor type 2 to treat noise-induced hearing loss by blocking inner ear inflammation. Biochem Pharmacol 2023; 210:115457. [PMID: 36806583 DOI: 10.1016/j.bcp.2023.115457] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Revised: 02/09/2023] [Accepted: 02/10/2023] [Indexed: 02/18/2023]
Abstract
NOD-like receptor protein 3 (NLRP3) inflammasomes trigger the inflammatory cascades and participate in various inflammatory diseases, including noise-induced hearing loss (NIHL) caused by oxidative stress. Recently, the anti-inflammatory traditional medicine oridonin (Ori) has been reported to provide hearing protection in mice after noise exposure by blocking the NLRP3-never in mitosis gene A-related kinase 7 (NEK7)-inflammasome complex assembly. Using RNA sequencing analysis, we further elucidated that interleukin 1 receptor type 2 (IL1R2) may be another crucial factor regulated by Ori to protect NIHL. We observed that IL1R2 expression was localized in spiral ganglion neurons, inner and outer hair cells, in Ori-treated mouse cochleae. Additionally, we confirmed that ectopic overexpression of IL1R2 in the inner ears of healthy mice using an adeno-associated virus delivery system significantly reduced noise-induced ribbon synapse lesions and hearing loss by blocking the "cytokine storm" in the inner ear. This study provides a novel theoretical foundation for guiding the clinical treatment of NIHL.
Collapse
Affiliation(s)
- Meng-Bing Chen
- The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, Fujian, China; College of Otolaryngology Head and Neck Surgery, Chinese PLA General Hospital, Beijing 100853, China; Ankang People's Hospital, Ankang 725000, Shanxi, China
| | - Meng-Hua Li
- Key Laboratory of Tropical Biological Resources of Ministry of Education, School of Pharmaceutical Sciences, Hainan University, Haikou 570228, Hainan, China; Academician Workstation of Hainan University (School of Pharmaceutical Sciences), Yazhou Bay, Sanya 572000, Hainan, China; Artificial Auditory Laboratory of Jiangsu Province, Xuzhou Medical University, Xuzhou 221000, Jiangsu, China
| | - Li-Yuan Wu
- Artificial Auditory Laboratory of Jiangsu Province, Xuzhou Medical University, Xuzhou 221000, Jiangsu, China; The Second Affiliated Hospital of Jiaxing University, Jiaxing 314000, Zhejiang, China
| | - Rong Wang
- The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, Fujian, China; College of Otolaryngology Head and Neck Surgery, Chinese PLA General Hospital, Beijing 100853, China
| | - Xi Long
- Chongqing Academy of Animal Sciences, Chongqing 402460, China
| | - Liang Zhang
- Chongqing Academy of Animal Sciences, Chongqing 402460, China
| | - Wei Sun
- Department of Communicative Disorders and Sciences, Center for Hearing and Deafness, the State University of New York at Buffalo, Buffalo 14200, NY, USA
| | - Wei-Wei Guo
- College of Otolaryngology Head and Neck Surgery, Chinese PLA General Hospital, Beijing 100853, China
| | - Yong Pan
- Xuzhou Infectious Diseases Hospital, Affiliated Hospital of Xuzhou Medical University, Xuzhou 221000, Jiangsu, China
| | - Yun-Shi Zhang
- Xuzhou Infectious Diseases Hospital, Affiliated Hospital of Xuzhou Medical University, Xuzhou 221000, Jiangsu, China
| | - Chang Lin
- The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, Fujian, China.
| | - Xi Shi
- Key Laboratory of Tropical Biological Resources of Ministry of Education, School of Pharmaceutical Sciences, Hainan University, Haikou 570228, Hainan, China; Academician Workstation of Hainan University (School of Pharmaceutical Sciences), Yazhou Bay, Sanya 572000, Hainan, China; Artificial Auditory Laboratory of Jiangsu Province, Xuzhou Medical University, Xuzhou 221000, Jiangsu, China.
| | - Shi-Ming Yang
- College of Otolaryngology Head and Neck Surgery, Chinese PLA General Hospital, Beijing 100853, China.
| |
Collapse
|
5
|
Moroe N, Mabaso P. Quantifying traffic noise pollution levels: a cross-sectional survey in South Africa. Sci Rep 2022; 12:3454. [PMID: 35236867 PMCID: PMC8891330 DOI: 10.1038/s41598-022-07145-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Accepted: 02/14/2022] [Indexed: 11/18/2022] Open
Abstract
Despite the alarming increase in environmental noise pollution, particularly road traffic noise, in developing countries, there seems to be no awareness regarding the long-term impacts of noise, specifically traffic noise, on the health outcomes of individuals exposed to excessive noise. Additionally, there is a dearth of studies on noise and its effects utilising the pollution modelling technique known as Pollution Standard Index (PSI) to analyse the impact of noise pollution on exposed individuals. The aim of this study was to investigate the noise levels commuters are exposed to and to apply PSI to determine the level of exposure. We conducted a cross-sectional study at two taxi ranks, over 28 days. Eighty-four noise measurements were collected using a sound level meter and a dosimeter at different times of the day and month, peak vs off-peak hours and busy days vs quiet days. Data were collected between April and July 2019. We used the Pollution Standard Index to analyse the data. Noise levels were above the permissible commercial noise levels as they fell within the extremely dangerous noise sensitivity zone as determined by the PSI. Furthermore, the noise levels fell below the WHO maximum permissible level of 90 dB. There was no statistical difference between the means of the open and closed ranks. Dosimeter noise level recordings fell within the satisfactory zone as measurements were below 300 PSI, which is considered unhealthy. There is a need to raise awareness on the dangers and effects of noise pollution in developing countries, as their populations are exposed to road traffic noise.
Collapse
Affiliation(s)
- Nomfundo Moroe
- Department of Speech Pathology and Audiology, University of the Witwatersrand, Johannesburg, South Africa.
| | - Paballo Mabaso
- Department of Speech Pathology and Audiology, University of the Witwatersrand, Johannesburg, South Africa
| |
Collapse
|