Field study of noise‐induced sleep disturbance
01 Aug 1995-Journal of the Acoustical Society of America (Acoustical Society of America)-Vol. 98, Iss: 2, pp 1025-1033
TL;DR: In this article, the authors found that sound exposure levels of individual noise intrusions were much more closely associated with awakenings than long-term noise exposure levels, and the slope of the relationship between awakening and sound exposure level was rather shallow.
Abstract: Behaviorally confirmed awakenings were recorded during nighttime hours for periods of approximately one month in 45 homes of 82 test participants. Measurements of awakening and of both indoor and outdoor noise exposure were made for a total of 632 subject nights near a military airfield, 783 subject nights near a civil airport, and 472 subject nights in neighborhoods with community noise exposure of nonaircraft origin. Sound exposure levels of individual noise intrusions were much more closely associated with awakenings than long‐term noise exposure levels. The slope of the relationship between awakening and sound exposure level was rather shallow, however. Although the present findings do not resemble those of laboratory studies of noise‐induced sleep interference, they are in good agreement with the results of other field studies.
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TL;DR: An algorithm for the automatic identification of cardiac activations associated with cortical arousals, which uses heart rate information derived from a single electrocardiogram (ECG) channel, may be used as estimates for EEG awakenings.
Abstract: OBJECTIVES: Polysomnography is the gold standard for investigating noise effects on sleep, but data collection and analysis are sumptuous and expensive. We recently developed an automatic algorithm for the identification of cardiac activations associated with cortical arousals, which uses heart rate information derived from a single electrocardiogram (ECG) channel (Basner et al. 2007a). We hypothesized that cardiac arousals can be used as estimates for EEG awakenings. METHODS: Polysomnographic EEG awakenings and automatically detected cardiac activations were systematically compared using laboratory data of 112 subjects (47 male, mean ± SD age 37.9 ± 13 years), 985 nights and 23,855 aircraft noise events (ANEs). RESULTS: The overall agreement was higher in control (81.9 %) compared to noise nights (76.4 %). However, if corrected for chance expected agreement according to Landis and Koch (1977), agreement was higher in noise (к=0.60) compared to control nights (к=0.33), representing “moderate to substantial” and “fair” agreement respectively. The probability of automatically detected cardiac arousals increased monotonously with increasing maximum sound pressure levels of ANEs, exceeding the probability of EEG awakenings by up to 18.1 %. If spontaneous reactions were taken into account, exposure-response curves were practically identical for EEG awakenings and cardiac arousals. CONCLUSIONS: Automatically detected cardiac arousals can be used as estimates for EEG awakenings. This inexpensive, objective, and non-invasive method facilitates large scale field studies on the effects of traffic noise on sleep. More investigations are needed to further validate the ECG algorithm in the field and to investigate interindividual differences in its ability to predict EEG awakenings.
23 citations
TL;DR: In this article, the authors introduce two definitions of reaction probability, discuss their advantages and disadvantages, and develop a model of the influence of the time window duration in which reactions of sleepers are screened on the calculated reaction probability.
Abstract: Some of the activations that occur during sleep, e.g. awakening reactions, can be considered adverse effects of noise events (e.g., airplane overflights or train passings) during the night. The occurrence of such reactions is an important indicator of the sleep disturbing potential of the particular noise stimulus and it is often desired to exactly quantify that potential in terms of a probability. Awakenings are considered the strongest form of reaction to noise stimuli during sleep and are one of the most often adopted criteria in night time noise protection concepts. However, the correct determination of noise induced awakening probability has given rise to debate in the scientific community in recent years. Because during every night’s sleep, spontaneous awakenings can occur at any time, it remains unknown in principle, whether a particular awakening observed during the presence of a noise stimulus was induced by that stimulus or emerged spontaneously. Nevertheless, correctly determining the awakening probability in question is key when it comes to forecasting noise effects during the night. This article introduces two definitions of reaction probability, discusses their advantages and disadvantages, and develops a model of the influence of the time window duration in which reactions of sleepers are screened on the calculated reaction probability.
22 citations
TL;DR: Results indicate that the bell ringing events increase awakenings in a similar fashion as has previously been reported with transportation noise events and that awakening probability first and foremost depends on maximum sound pressure level of an event.
21 citations
Cites background from "Field study of noise‐induced sleep ..."
..., 2011) and field studies (Ollerhead et al., 1992; Carter et al., 1994a; Horne et al., 1994; Fidell et al., 1995; Hofman et al., 1995; Suzuki et al., 1997; Passchier-Vermeer et al., 2002; Hume and Whitehead, 2004; Basner et al., 2006; Brink et al., 2008; Marks et al., 2008; Müller, 2010) stands in this tradition....
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...…et al., 1994b; Carter et al., 2002; Basner et al., 2011) and field studies (Ollerhead et al., 1992; Carter et al., 1994a; Horne et al., 1994; Fidell et al., 1995; Hofman et al., 1995; Suzuki et al., 1997; Passchier-Vermeer et al., 2002; Hume and Whitehead, 2004; Basner et al., 2006; Brink…...
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10 Jun 2017
TL;DR: In this article, the authors describe the basis of community engagement as a parallel approach to mitigate noise issues around airports, setting the focus on the noise metrics and the involvement techniques that must be implemented to engage the community.
Abstract: It seems obvious that the noise levels in local communities surrounding airports influences the level of acceptance of an airport. What is not so evident is the effect of non-acoustic factors that increase the societal rejection, like the lack of sensitivity and empathy from the authorities and airport managers, the lack of trust in them, the lack of information and transparency, the perception of being excluded from the decision making and so on. Complementary to the traditional strategies based on the reduction of noise exposure, a community engagement and involvement approach brings new possibilities to manage noise around airports, trying to exploit the non-acoustic factors that have negatively affected the community response. Building trust among the stakeholders is a key factor in this strategy, and it must be based on a long-term, honest, and transparent two-way communication. In the last decade, the huge growth of the information and communication technologies has opened new opportunities that the aviation organizations and stakeholders are starting to explore in depth trying to reduce the degree of rejection of the airport, which may compromise the utilization of existing and future infrastructure. In this review, we make a short introduction on aircraft noise health effects, to focus annoyance and the influence that non-acoustic factors on it. Then, we describe the basis of community engagement as a parallel approach to mitigate noise issues around airports, setting the focus on the noise metrics and the involvement techniques that must be implemented to engage the community.
21 citations
TL;DR: In this article, the effects of different noise combinations on sleep were assessed in two contexts, with a single noise source and with combined noise sources, and the results showed that the combined noises sources including construction noise decreased the number of participants who fell asleep within an hour and increased the number that were awakened prematurely.
20 citations