Markov processes for the prediction of aircraft noise effects on sleep

Med Decis Making. 2010 Mar-Apr;30(2):275-89. doi: 10.1177/0272989X09342751. Epub 2009 Aug 14.

Abstract

Background: Aircraft noise disturbs sleep and impairs recuperation. Authorities plan to expand Frankfurt airport.

Objective: To quantitatively assess the effects of a traffic curfew (11 PM to 5 AM) at Frankfurt Airport on sleep structure.

Design: Experimental sleep study; polysomnography for 13 consecutive nights.

Setting: Sleep laboratory. Subjects. 128 healthy subjects, mean age (SD) 38 (13) years, range 19 to 65, 59% female. Intervention. Exposure to aircraft noise via loudspeakers.

Measurements: A 6-state Markov state transition sleep model was used to simulate 3 noise scenarios with first-order Monte Carlo simulations: 1) 2005 traffic at Frankfurt Airport, 2) as simulation 1 but flights between 11 PM and 5 AM cancelled, and 3) as simulation 2, with flights between 11 PM and 5 AM from simulation 1 rescheduled to periods before 11 PM and after 5 AM. Probabilities for transitions between sleep stages were estimated with autoregressive multinomial logistic regression.

Results: Compared to a night without curfew, models indicate small improvements in sleep structure in nights with curfew, even if all traffic is rescheduled to periods before and after the curfew period. For those who go to bed before 10:30 PM or after 1 AM, this benefit is likely to be offset by the expected increase of air traffic during late evening and early morning hours. Limitations. Limited ecologic validity due to laboratory setting and subject sample.

Conclusions: According to the decision analysis, it is unlikely that the proposed curfew at Frankfurt Airport substantially benefits sleep structure. Extensions of the model could be used to evaluate or propose alternative air traffic regulation strategies for Frankfurt Airport.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Aircraft*
  • Female
  • Humans
  • Male
  • Markov Chains*
  • Middle Aged
  • Noise, Transportation / adverse effects*
  • Polysomnography
  • Sleep*
  • Time Factors