The role of noise sensitivity in the noise–response relation: A comparison of three international airport studies

TLDR

This study compares socio‑acoustic data from Amsterdam, Sydney, and London airports to test whether noise sensitivity moderates the relationship between aircraft noise and annoyance, independent of measurement technique. The authors examined aircraft noise exposure and annoyance separately for low, medium, and high noise‑sensitive groups, adjusting for confounders. Results confirm that noise sensitivity independently predicts annoyance, adding up to 26 % of explained variance, with no moderating effect across sensitivity levels, and this pattern holds across all three datasets.

Abstract

In order to examine the role of noise sensitivity in response to environmental noise, this paper presents detailed comparisons of socio-acoustic studies conducted around international airports in Amsterdam, Sydney, and London. Earlier findings that noise sensitivity moderates the effect of noise on annoyance were examined to see if they could be replicated in each of the datasets, independent of the technique of measuring noise sensitivity. The relation between exposure to aircraft noise and noise annoyance was studied separately for groups of individuals with low, medium, and high noise sensitivity, with statistical adjustment for relevant confounders. Results support the previous findings that noise sensitivity is an independent predictor of annoyance and adds to the prediction of noise annoyance afforded by noise exposure level by up to 26% of explained variance. There is no evidence of a moderating effect, whereby the covariation between noise exposure level and annoyance is weak for people who score at the extreme high or low end of the sensitivity scale, and strong for people who score in the middle of the sensitivity scale. Generally, noise sensitivity appears to increase annoyance independently of the level of noise exposure after adjustment for relevant confounders. These findings were consistent across the three datasets.