Category Ranking
98%
Total Visits
921
Avg Visit Duration
2 minutes
Citations
20
Article Abstract
Background: A large portion of Iranian Working Population (IWP) is becoming at risk of Occupational Noise-Induced Hearing Loss (ONIHL). Several primary studies have evaluated the prevalence of ONIHL in Iran with a variety of prevalence rates. We aimed to estimate the prevalence of ONIHL in the IWP using data from relevant studies.
Methods: The present study is a meta-analysis and systematic review of previously published studies on ONIHL in Iran. Accordingly, the relevant articles published until Sep 1, 2021 were searched through Pub-Med, Scopus, and Google Scholar, together with Iranian scientific electronic databases. Heterogeneity between among the studies and data analysis was assessed using the I2 test and Random-Effect Model (REM) respectively.
Results: Having performed a quality assessment, the meta-analysis was performed on the data from twenty-six studies involving a total of 85685 participants. The prevalence of ONIHL was observed to range from 12.9% to 60.5% in the reviewed studies. Moreover, after combining the results from the primary research by the Random Effects Model (REM) approach, the prevalence of ONIHL among IWP was estimated to be 34.69% (95% CI: 29.10, 40.28).
Conclusion: ONIHL is a significant concern with regard to public and occupational health in Iran. The results also highlighted the urgent need for taking appropriate preventive and control measures in the work-places; particularly by encouraging the employers and health-related policymakers to focus on preventive noise control techniques along with administrative and legislative approaches to mitigate the risk of developing ONIHL.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10113583 | PMC |
| http://dx.doi.org/10.18502/ijph.v52i2.11881 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Construction of a risk prediction model for occupational noise-induced hearing loss using routine blood and biochemical indicators in Shenzhen, China: a predictive modelling study.
BMJ Open
April 2025
School of Public Health, Southern Medical University, Guangzhou, Guangdong, China
Objectives: Occupational noise-induced hearing loss (ONIHL) represents a prevalent occupational health condition, traditionally necessitating multiple pure-tone audiometry assessments. We have developed and validated a machine learning model leveraging routine haematological and biochemical parameters, thereby offering novel insights into the risk prediction of ONIHL.
Design, Setting And Participants: This study analysed data from 3297 noise-exposed workers in Shenzhen, including 160 ONIHL cases, with the data set divided into D1 (2868 samples, 107 ONIHL cases) and D2 (429 samples, 53 ONIHL cases).
The Association Between HIV/AIDS, Ototoxicity of Its Treatments, and Occupational Noise Induced Hearing Loss: A Narrative Review Mapping the Existing Literature and Identifying Research Gaps.
Int J Environ Res Public Health
March 2025
Audiology Department, School of Human & Community Development, Faculty of Humanities, University of the Witwatersrand, Johannesburg 2050, South Africa.
Hearing loss remains a significant but underexplored health challenge in individuals with HIV/AIDS, particularly those exposed to occupational noise. The ototoxic effects of antiretroviral therapy (ART) and comorbid conditions like tuberculosis (TB) further compound the risk. This narrative review examines the intersection of HIV/AIDS, ART, and occupational noise-induced hearing loss (ONIHL), emphasizing the South African and broader African contexts.
View Article and Find Full Text PDFApplying machine learning algorithms to explore the impact of combined noise and dust on hearing loss in occupationally exposed populations.
Sci Rep
March 2025
Department of Otolaryngology, Hebei Medical University, Shijiazhuang, China.
This study aimed to explore the combined impacts of occupational noise and dust on hearing and extra-auditory functions and identify associated risk factors via machine learning techniques. Data from 14,145 workers (627 with occupational noise-induced hearing loss (ONIHL)) at Hebei Medical Examination Center (2017-2023) were analyzed. Workers with combined exposure and without specific contraindications or other hearing impairment causes were included.
View Article and Find Full Text PDFTrends in Occupational Hearing Loss: An Analysis of 36,984 Workers With Occupational Noise Exposure in Quebec.
J Occup Environ Med
July 2025
From the Faculty of Medicine, University of Montreal, Montréal, QC, Canada (Z.D.); Division of Otolaryngology-Head and Neck Surgery, Faculty of Medicine, University of Montreal, Montréal, QC, Canada (J.S.); and École de technologie supérieure, Université du Québec, Montréal, Canada, Montreal,
Objectives: This study aimed to characterize trends in occupational noise-induced hearing loss (ONIHL) incidence and to assess noise exposure levels and changes in audiometric thresholds among workers.
Methods: This retrospective study analyzed audiometric data from 72,952 workers between 1980 and 2019. Incidence rates of ONIHL were calculated.
Burden and Risk Factors of Occupational Noise-Induced Hearing Loss Among Employees Working at an International Airport in Eastern India.
Indian J Occup Environ Med
September 2024
Department of Community Medicine, North Bengal Medical College, Sushrutanagar, Darjeeling, West Bengal, India.
Background: Occupational noise-induced hearing loss (ONIHL) is the commonest occupational disease globally. However, literature on ONIHL in airport employees of developing countries is scarce.
Aims: To assess the burden of ONIHL and its associated factors among employees working at an international airport in Eastern India.