Noise Exposure Response: Sleep Disturbance
PROJECT 25A (see below for Project 25B)
Most existing models that predict the effect of aircraft noise on sleep relate the probability of awakening to the indoor maximum noise level of a single aircraft event. In these models it is also assumed that the impact of aircraft noise on sleep is independent of any previous events. Whether an individual will awaken to a noise event depends on more than just the noise level, it also depends on the time of night, sleep stage, noise characteristics such as rise time and spectral content, and individual variables such as age. In addition, noise will not only lead to an increase in awakenings but could affect the amount of deep, restorative sleep. To balance benefits and costs of potential airport operation changes such as noise curfews, changes in flight schedules, or flight paths, more comprehensive sleep models are needed. The focus of Project 25A was to develop a model that predicted changes in sleep structure due to aircraft noise.
Sleep models in the literature were reviewed and an existing model that predicted slow wave activity, rapid eye movement (REM) sleep and awakenings for non-noise disturbed sleep was examined to determine whether it could be modified to predict observed changes due to aircraft noise. This base model was chosen as it predicted well the changes in sleep depth and cyclic changes between Non-REM and REM sleep. However, the model could not predict faster changes such as brief awakenings. To predict these events, a model which predicted Tonic REM, Phasic REM, and awakenings was added to predict activity during REM sleep. In addition, random impulsive excitations were added which varied with noise level in order to predict noise-induced changes in sleep. The model was tuned to match sleep patterns observed in a laboratory and field study on the effects of aircraft noise on sleep that was conducted in the U.K. While there was good agreement between model predictions and measured responses, further refinement is required to match the variation in sleep changes observed among individuals. Also, the model’s performance in predicting responses in other sleep studies needs to be examined. The model was used with sound prediction software to predict changes in sleep in communities around an airport for different nighttime operations scenarios. An increase in time spent awake and a decrease in slow wave sleep due to noise exposure was predicted, the magnitude of these changes were dependent on the number, level and time of the aircraft events.
Patricia Davies, Professor of Mechanical Engineering, Director, Ray W. Herrick Laboratories, School of Mechanical Engineering, Purdue University. firstname.lastname@example.org
Sarah McGuire, Ph.D. Graduate Student, Ray W. Herrick Laboratories, School of Mechanical Engineering, Purdue University, and now a postdoctoral fellow at the University of Pennsylvania working with Dr. Basner. email@example.com
Modeling Aircraft Noise Induced Sleep Disturbance. S. McGuire and P. Davies. A PARTNER Project 24/25 report. December 2013. Report No. PARTNER-COE-2013-004. Download (pdf 10MB)
With the most recent U.S. field study dating back to 1996, and when compared to the sleep disturbance efforts of other, especially European countries, U.S. research on the effects of aircraft noise on sleep has lagged over the past 15 years, while aircraft noise has continued to evolve. Within this period, air traffic has changed significantly, with changes in traffic volume, on one hand, and significant improvements in noise levels of single aircraft, on the other. Due to inter-cultural differences, results from studies performed outside the U.S. may not transfer directly to U.S. domestic airports. Therefore, it is important that U.S. field studies be conducted to acquire current sleep disturbance data for varying degrees of noise exposure. The long-term goal of Project 25B was to conduct U.S. field studies on the effects of noise on sleep and to derive exposure-response relationships for aircraft noise-induced sleep disturbance.
The research completed as part of Project 25B was to prepare for a field study. One outcome of this project was an optimal study design. Because of the large sample size at an airport, required to ensure that a representative group of the total exposed population is sampled, it will not be possible to use polysomnography (i.e., simultaneous recording of the electroencephalogram, electromyogram, and electrooculogram) to monitor sleep, as this method requires trained personnel at the measurement site in the evening and in the morning and is thus too costly. Instead it was proposed to use a combination of actigraphy and electrocardiography (ECG), which will allow a cost-effective and methodologically sound investigation of large subject cohorts. In order to identify awakenings using this approach, an automatic algorithm was developed, which identifies awakenings based on both increases in movement and heart rate, and was shown to have high agreement with awakenings identified using polysomnography. The developed methodology was implemented in a pilot field study conducted around one U.S. airport within ongoing FAA Center of Excellence ASCENT Project 17.
University of Pennsylvania
Mathias Basner, Associate Professor of Sleep and Chronobiology in Psychiatry, University of Pennsylvania Perelman School of Medicine firstname.lastname@example.org
- Design for a U.S. Field Study in the Effects of Aircraft Noise on Sleep. Mathias Basner, PARTNER Project 25B year one report. Report No. PARTNER-COE-2012-003. Download (pdf 1.2M)
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