Evidence map›Paper›PMID 28704890›Full record

ArticleJournal of audiology & otology2017

Analysis of Subway Interior Noise at Peak Commuter Time.

Donguk Lee, Gibbeum Kim, Woojae Han

Abstract read
In one paragraph

Article in Journal of audiology & otology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

2 citing papers in PubMed.

  1. Article
  2. Article
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

3 authors.

Donguk LeeDepartment of Speech Pathology and Audiology, Graduate School, Hallym University, Chuncheon, Korea.
Gibbeum KimDepartment of Speech Pathology and Audiology, Graduate School, Hallym University, Chuncheon, Korea.
Woojae HanDivision of Speech Pathology and Audiology, Research Institute of Audiology and Speech Pathology, College of Natural Science, Hallym University, Chuncheon, Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectivesAlthough mass transit systems are convenient and efficient for urban people, little attention has been paid to the potential hearing hazard from their noise. The purpose of the current study was to measure and analyze levels of subway interior noise at peak commuter times and to provide information about commuters' daily dose of noise exposure. MATERIALS AND

methodsTo measure the subway interior noise, nine subway lines inside Seoul (i.e., lines 1-9) and six lines surrounding the capital city area (i.e., Central, Bundang, Sinbundang, Incheon, Gyeongui, and Gyeongchun) were chosen. The noise was measured and recorded by a sound level meter for two-hour periods in the morning and evening.

results1) In the LZeq analysis, the average noise level of all 15 lines was 72.78 dB; the maximum and minimum noise levels were 78.34 and 62.46 dB, respectively. The average noise level of the nine lines inside Seoul was 73.45 dB, which was 1.68-dB louder than that of the six lines surrounding the capital city area. 2) Based on the LZeq analysis of 33 measured frequencies, 12.5 Hz was the highest frequency and 20,000 Hz was the lowest. 3) There was no remarkable difference in the level of subway interior noise between morning and evening peak commuter times.

conclusionsWe concluded that the level of subway interior noise was not loud enough for commuters to incur noise-induced hearing loss. Regardless, environmental noise control efforts in the subway system might be needed for commuters who take a subway every day.

Indexed as

Environmental noiseMass transit systemNoise exposureNoise-induced hearing lossSubway noise

Identifiers

PMID28704890
PMCPMC5516701

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.