Evidence map›Paper›PMID 35886248›Full record

ArticleInternational journal of environmental research and public health2022

Influencing Factors Identification and Prediction of Noise Annoyance-A Case Study on Substation Noise.

Guoqing Di, Yihang Wang, Yao Yao, Jiangang Ma, Jian Wu

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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 synthesis or guideline pooled it.

  1. The Impact of Non-Acoustic Factors on Chinese Community Response to Noise: A Systematic Review.International journal of environmental research and public health · 2025
    Pooled it
  2. Indoor Environmental Comfort Assessment of Traditional Folk Houses: A Case Study in Southern Anhui, China.International journal of environmental research and public health · 2023
    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

5 authors.

Guoqing DiCollege of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China.ORCID 0000-0003-1428-7674
Yihang WangCollege of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China.
Yao YaoCollege of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China.
Jiangang MaState Grid Shaanxi Electric Power Research Institute, Xi'an 710054, China.
Jian WuState Grid Shaanxi Electric Power Research Institute, Xi'an 710054, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Noise-induced annoyance is one person's individual adverse reaction to noise. Noise annoyance is an important basis for determining the acceptability of environmental noise exposure and for formulating environmental noise standards. It is influenced by both acoustic and non-acoustic factors. To identify non-acoustic factors significantly influencing noise annoyance, 40 noise samples with a loudness level of 60-90 phon from 500-1000 kV substations were selected in this study. A total of 246 subjects were recruited randomly. Using the assessment scale of noise annoyance specified by ISO 15666-2021, listening tests were conducted. Meanwhile, basic information and noise sensitivity of each subject were obtained through a questionnaire and the Weinstein's noise sensitivity scale. Based on the five non-acoustic indices which were identified in this study and had a significant influence on noise annoyance, a prediction model of annoyance from substation noise was proposed by a stepwise regression. Results showed that the influence weight of acoustic indices in the model accounted for 80% in which the equivalent continuous A-weighted sound pressure level and the sound pressure level above 1/1 octave band of 125 Hz were 65% and 15%, respectively. The influence weight of non-acoustic indices entering the model was 20% in which age, education level, noise sensitivity, income, and noisy degree in the workplace were 8%, 2%, 4%, 4%, and 2%, respectively. The result of this study can provide a basis for factors identification and prediction of noise annoyance.

Indexed as

Loudness PerceptionNoiseAcousticsAuditory PerceptionEnvironmental ExposureHumansinfluence weightnoise annoyancenon-acoustic factorsprediction modelsubstation noise

Identifiers

PMID35886248
PMCPMC9315821

What OpenQuestion holds

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Registered trials

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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.