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Purpose: By dividing polysomnographic recordings into intervals of 30 sec, human sleep can be classified in six distinct states: Awake, stages 1&2 (light sleep), stages 3&4 (slow wave sleep, SWS), and rapid eye movement (REM) sleep. The sleep states differ in their contribution to the restorative power of sleep. Environmental noise is a potential disruptor of the sleep process and may cause changes in the structure of sleep. The goal of this study was to predict changes in total sleep structure depending on sound pressure levels and time patterns of aircraft noise events (ANE).
Methods: In four laboratory studies with 128 subjects lasting from 1999 to 2003, the Institute of Aerospace Medicine of the German Aerospace Center (DLR) investigated the influence of aircraft noise on human sleep. Quiet baseline nights of 125 subjects were used to build and validate a model for the simulation of noise-free nights based on autoregressive multinomial logistic regression. Data of 33,000 ANE and related events were used to incorporate the effects of ANE on transition probabilities. Three noise scenarios (see results) with constant maximum sound pressure levels of 65 dB(A) were compared regarding their impact on total sleep structure.
Results: A second order autoregressive model fit the validation criteria best. Comparison of mean sleep stage fractions of baseline nights and 10,000 first-order Monte Carlo trials showed good agreement (model vs. raw data: Awake -0.7%, S1 +27.5%, S2 +0.5%, S3 +2.5%, S4 –8.8%, REM –1.5%). Noise restriction between 11 pm and 5 am (scenario 2: 59.3 min SWS, 47.2 min awake) revealed clear benefits compared to unrestricted traffic (scenario 1: 43 min SWS, 63.5 min awake), although these benefits were reduced if the traffic that formerly took place between 11 pm and 5 am was rescheduled to the time before and after the silent period (scenario 3: 58 min SWS, 54.2 min awake).
Conclusions: It was possible to validly reproduce key features of noise-free baseline nights with a Markov state transition model based on multinomial autoregressive logistic regression. The extension of the model based on extensive data on the reactions to ANEs allows for the comparison of sleep structures induced by different noise patterns and may serve as a valuable tool for structuring nocturnal air traffic and for political decision making.
See more of Poster Session - Clinical Strategies; Judgment and Decison Making
See more of The 26th Annual Meeting of the Society for Medical Decision Making (October 17-20, 2004)