Prediction of probabilistic sleep distributions following travel across multiple time zones.
OBJECTIVE
To parameterize and validate a model to estimate average sleep times for long-haul aviation pilots during layovers following travel across multiple time zones. The model equations were based on a weighted distribution of domicile- and local-time sleepers, and included algorithms to account for sleep loss and circadian re-synchronization.


METHODS
Sleep times were collected from participants under normal commercial operating conditions using diaries and wrist activity monitors.


METHODS
Participants included a total of 306 long-haul pilots (113 captains, 120 first officers, and 73 second officers).


RESULTS
The model was parameterized based on the average sleep/wake times observed during international flight patterns from Australia to London and Los Angeles (global R2 = 0.72). The parameterized model was validated against the average sleep/wake times observed during flight patterns from Australia to London (r2 = 0.85), Los Angeles (r2 = 0.79), New York (r2 = 0.80), and Johannesburg (r2 = 0.73). Goodness-of-fit was poorer when the parameterized model equations were used to predict the variance across the sleep/wake cycles of individual pilots (R2 = 0.42, 0.35, 0.31, and 0.28 for the validation flight patterns, respectively), in part because of substantial inter-individual variability in sleep timing and duration.


CONCLUSIONS
It is possible to estimate average sleep times during layovers in international patterns with a reasonable degree of accuracy. Models of this type could form the basis of a stand-alone application to estimate the likelihood that a given duty schedule provides pilots, on average, with an adequate opportunity to sleep.
Darwent
David
D
Centre for Sleep Research, University of South Australia, Level 7, Playford Building, City East Campus, Frome Road, Adelaide SA 5000, Australia. david.darwent@unisa.edu.au
Dawson
Drew
D
Roach
Greg D
GD
D056044:Actigraphy; D000337:Aerospace Medicine; D000465:Algorithms; D002940:Circadian Rhythm; D003198:Computer Simulation; D006306:Health Surveys; D006801:Humans; D020179:Jet Lag Syndrome / Q000175:diagnosis / Q000453:epidemiology*; D009784:Occupational Diseases / Q000175:diagnosis / Q000453:epidemiology*; D012890:Sleep; D012892:Sleep Deprivation / Q000175:diagnosis / Q000453:epidemiology; D012984:Software; D013021:South Australia; D014195:Travel; D014851:Wakefulness