RESUMO
INTRODUCTION: Current models of fatigue and alertness use a combination of biological (circadian) and homeostatic factors to predict sleep and wake. Such models do not include social factors in their calculations. The aim of our analysis was to compare the relative contributions of social and biological factors in models designed to predict the total sleep time (TST) during layover periods between transmeridian flights. METHOD: The study actigraphically collected sleep information from 86 cockpit crew (mean age 46.7 yr, SD 4.3 yr) during round-trip patterns from Australia to Los Angeles (n=15), Europe (n=42), New York (n=10), and Hong Kong (n=19). Linear regression models were constructed to predict TST using data from airline schedules. This schedule information included layover length, flight duration, the number of night hours at the destination (social hours), the number of night hours in Australian Eastern Standard time (biological hours), and time zone displacement. These models were then validated using independent data. RESULTS: Analysis indicated that the schedule data was highly correlated. Linear regression analyses indicated that social night hours account for more variance than biological night hours (r = 0.8 vs. 0.7). Additionally, the layover length achieved a correlation coefficient of 0.9. These results were strengthened when the model parameters were applied to the cross-validation dataset. DISCUSSION: Social night hours significantly influence sleep during international layovers and may be a better predictor than biological night hours. More research must be carried out to determine the validity of these findings in a larger, randomly collected flight sample.
