Prediction of Probabilistic Sleep Distributions Following Travel Across Multiple Time Zones

Study Objectives:

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.

Design:

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

Participants:

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

Measurement and 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.

Citation:

Darwent D; Dawson D; Roach GD. Prediction of probabilistic sleep distributions following travel across multiple time zones. SLEEP 2010;33(2):185-195.