Evidence map›Paper›PMID 42446329›Full record

ArticleNoise & health

Effectiveness of Workplace Noise-risk Classification with Hearing Protection in Preventing Occupational Hearing Loss.

XuanYu Chen, LianGong Cai

Abstract read
In one paragraph

Article in Noise & health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

XuanYu ChenEmergency Office, Hunan Prevention and Treatment Institute for Occupational Diseases (Affiliated Prevention and Treatment Institute for Occupational Diseases of University of South China), Changsha, Hunan, PR China.
LianGong CaiOccupational Health Examination Room, Hunan Prevention and Treatment Institute for Occupational Diseases (Affiliated Prevention and Treatment Institute for Occupational Diseases of University of South China), Changsha, Hunan, PR China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis study aimed to evaluate the effectiveness of combining workplace noise-risk classification with a hearing protection program to prevent occupational noise-induced hearing loss (ONIHL).

methodsThis retrospective cohort study included 400 male noise‑exposed workers from an automotive manufacturing company. Based on workshop‑level protection strategies implemented by the company, participants were assigned to either a control group ( n  = 200, traditional measures) or an observation group ( n  = 200, risk classification plus standardized hearing protection). Outcomes assessed at the end of 2023 included proper personal protective equipment use, average noise exposure, speech-/high‑frequency hearing loss, high‑frequency standard threshold shift (STS), and ONIHL incidence. Statistical comparisons were performed using independent t tests, χ 2 tests, and logistic regression.

resultsBaseline characteristics were comparable between the groups ( P > 0.05). At follow‑up, the observation group showed significantly better outcomes (all P < 0.05): higher personal protective equipment compliance (87.50% versus 63.00%), lower noise exposure (86.26 ± 1.99 versus 88.72 ± 1.77 dB(A)), and lower rates of speech‑frequency hearing loss (20.00% versus 52.50%), high‑frequency hearing loss (35.00% versus 65.00%), high‑frequency STS (5.00% versus 20.00%), and ONIHL (1.00% versus 5.50%). Job-type subgroup analyses indicated a significant protective effect in stamping (STS: 3.85% versus 15.00%, P  = 0.017), but not in welding (4.48% versus 13.85%, P  = 0.061); machining showed a significant reduction (3.64% versus 14.55%, P  = 0.047).

conclusionThe integrated strategy was associated with improved protection compliance, reduced noise exposure, and lower hearing loss rates. However, due to the non‑randomized, workshop‑level assignment, causal inferences should be made cautiously. Prospective studies are needed to confirm causality.

Indexed as

Ear Protective DevicesHearing Loss, Noise-InducedNoise, OccupationalOccupational DiseasesOccupational ExposureAdultAutomobilesHumansMaleMiddle AgedRetrospective StudiesRisk AssessmentWorking Conditionshearing losshearing protectionnoise-inducedoccupational healthrisk assessment

Identifiers

PMID42446329
PMCPMC13399470

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.