Aviation, Space, and Environmental Medicine x Vol. 79, No. 11 x November 2008 1047

RESEARCH ARTICLE

 POWELL D, SPENCER MB, HOLLAND D, PETRIE KJ. Fatigue in two-

 pilot operations: implications for fl ight and duty time limitations.

Aviat Space Environ Med 2008; 79: 1047 – 50 . 

Objectives: Two-pilot operations make up the majority of commercial 

fl ights. Fatigue is an important consideration in these operations as there 

is little opportunity for in-fl ight rest. We investigated the role of duty 

length, time of day, and whether one or two sectors were fl own on reported fatigue at the top of descent in two-pilot regional operations. 

Methods: Pilots fl ying two-pilot operations ranging from 3-12 h completed Samn-Perelli fatigue ratings prior to descent at the end of each 

rostered duty over a 12-wk period. We collected 3023 usable ratings 

(72% of rostered duties) comprising 26% single and 74% double sector 

duties. Results: We found that time of day has a marked effect on the 

pattern of fatigue at the start of the duty and on the rate at which fatigue 

levels increased, with the highest levels in the window of circadian low 

(0200 – 0600). Fatigue also increased with the length of duty and was 

0.56 higher at the end of a two-sector compared with a single-sector 

duty. Discussion: The results imply authorities should consider increasing existing limits for daytime duties and reducing those for nighttime 

two-pilot operations. 

Keywords: pilots , time of day , work hours , circadian rhythm , duty time 

limitations . 

 MANAGING FATIGUE is an important component of commercial airline operations. Two-pilot operations, which represent the majority of commercial fl ights, 

present a particular challenge due to the lack of opportunity for pilots to use in-fl ight rest ( 1 ). Often two-pilot duties may be in excess of 10 h, operate through the night, 

and have critical stages of the fl ight during periods of 

circadian lows. Furthermore, there are few scientifi c 

studies available to guide the development of fl ight and 

duty time limitations, which to date have mostly been set 

arbitrarily through regulation or industrial agreement. 

 In order to develop more scientifi cally based fl ight 

and duty regulations it is important to understand how 

fatigue in two-pilot operations is infl uenced by factors 

such as the time of day, the number of sectors fl own, and 

whether the fl ight is returning or traveling away from 

the pilots ’ home base. While previous research has highlighted that the overall risk of aviation accidents is associated with longer duty periods ( 2 ), it is not clear what 

duty period is optimal at any given report time to minimize the chance of hazardous levels of fatigue. 

 The majority of previous research on pilot fatigue has 

focused on long-haul fl ights operated with augmented 

crews and there is comparatively little work on twopilot operations. Early research on long two-pilot duties 

was conducted on crews fl ying between Germany and 

the Seychelles at night ( 5 ). This study highlighted the 

low levels of alertness that can arise at the end of 9-10 h 

two-pilot fl ights, but it is diffi cult to generalize from 

these specifi c fl ights to operations of varying durations 

at different times of day. Other studies have also looked 

at particular operations ( 4 ), but it is not easy to develop 

general principles from this research about the infl uences of factors such as duty length and time of day on 

fatigue. Such work would be useful for identifying twopilot duties that are likely to have high levels of fatigue 

and to guide the development of more scientifi cally 

based schemes for fl ight and duty time regulations. 

 In a recent study of pilot fatigue in short-haul operations where the top of descent was between 0800 and 2200 

we found the most important infl uences on pilot fatigue 

were the number of sectors and the length of the duty period ( 3 ). The nature of the domestic operation with no 

overnight fl ying means that the results are diffi cult to apply to other two-pilot operations that fl y through the 

night. In the current study we examined the role of duty 

length, time of day at the top of descent, and whether one 

or two sectors were fl own. Similar to our previous study, 

we collected alertness ratings from pilots at the end of 

their last duty sector just prior to the top of descent. This 

enabled us to determine the relative importance of these 

factors at a critical stage of the fl ight. Rather than focusing 

on specifi c fl ights or operations, this study used data from 

a large number of duties of variable duration and timing, 

but involving sectors of similar lengths. Using this approach, we can move toward establishing duty time limitations based on fatigue considerations. 

 METHODS 

 The investigation was conducted from January 1 to 

March 31, 2003. Here we report the fi ndings on two-pilot 

operations fl ying 1 or 2 sector duties that ranged from 3 

 From Air New Zealand, Auckland, New Zealand, and the Department of Psychological Medicine, University of Auckland, Auckland, 

New Zealand. 

 This manuscript was received for review in June 2008 . It was 

accepted for publication in July 2008 . 

 Address reprint requests to: D. M. C. Powell, Medical Unit, Air New 

Zealand; Auckland, New Zealand; David.Powell@airnz.co.nz . 

 Reprint & Copyright © by the Aerospace Medical Association, Alexandria, VA. 

 DOI: 10.3357/ASEM.2362.2008 

Fatigue in Two-Pilot Operations: Implications for 

Flight and Duty Time Limitations 

 David Powell , Mick B. Spencer , David Holland , 

and Keith J. Petrie 
1048 Aviation, Space, and Environmental Medicine x Vol. 79, No. 11 x November 2008

FATIGUE IN SHORT-HAUL PILOTS — POWELL ET AL.

to 12 h duty time. Individual sectors were between 3 and 

5 h. Data were gathered from pilots operating Boeing 

737-300, 767, and 747-400 two-pilot operations. 

 During the study period there were a total of 4206 

two-pilot duties between New Zealand and destinations 

within Australia and the Pacifi c Islands. All pilots were 

sent a letter explaining the study and inviting them to 

participate in the research. Pilots were asked to complete 

a brief anonymous questionnaire at the top of descent 

on the last sector of the duty. Details of the questionnaire 

and methodology have been described previously ( 3 ), 

and involved pilots recording the duty start time, time 

at the top of descent, and the sectors fl own. Pilots also 

rated their fatigue on the 7-point Samn-Perelli scale ( 6 ), 

ranging from 1 “ fully alert, wide awake ” to 7 “ completely exhausted, unable to function effectively, ” and 

on a 100-mm visual analogue scale rated “ alert ” to 

 “ drowsy. ” 

 Statistical Methods 

 The analysis was restricted to duties with one or two 

sectors, where the ‘ duty time ’ , defi ned here as the time 

between report and top of descent, was between 3 h and 

12 h. Returns were also excluded where times were 

missing, inconsistent, or unreliable. The data were then 

analyzed by a stepwise least squares (analysis of variance and regression) procedure. The factors included in 

this analysis were: length of duty, covering duties between 3 h and 12 h ( N 5 9); time of day at top of descent, 

at 1-h intervals ( N 5 24); the number of sectors, either 

one or two ( N 5 2); and the type of duty, either departing from or returning to New Zealand, or a round trip 

( N 5 3). Interaction terms were only included if the relevant main effects were signifi cant. 

 Where duties commenced outside New Zealand, time 

zone differences were small (typically 2 h or less) and 

layovers were brief (1 or 2 nights). Therefore, we defi ned 

the time of day relative to local time in New Zealand. 

Alternative defi nitions were considered to account for 

possible adaptation to local time where the departure 

airport was in a different time zone. These included the 

assumption of complete adaptation to local time prior to 

departure, complete adaptation up to a maximum of 2 h, 

and 50% adaptation to local time. However, as all these 

assumptions led to an increase in the residual sum of 

squares, they were not considered further. 

 Contrasts within the main effects were included as regressor variables in the form of polynomials (length of 

duty) and harmonics (time of day). However, polynomials of higher degree than a cubic, and harmonics beyond the second, were not considered. Where the contrast or contrasts accounted for the signifi cant differences 

within a factor, they replaced that factor in subsequent 

analyses, including in the interaction terms. This procedure was used to generate an equation of best fi t to the 

subjective data. The graphical representation of the main 

effects in this paper has been derived from a model in 

which the terms have been taken from the equation of 

best fi t. Finally, the fi tted equation was used to derive 

trends in fatigue related to duty start time. 

 The analysis was carried out on both the visual analogue data and on the Samn-Perelli scores. However, 

these two variables were closely related, with a Pearson 

correlation coeffi cient of 0.89, and the results of both analyses were similar. Therefore, only the results from the 

Samn-Perelli data are presented here. 

 RESULTS 

 There were 3181 questionnaires returned (72% response rate), and these were reduced to 3023 after the 

application of the exclusion criteria. On average pilots 

completed fatigue ratings on six occasions, but as the 

survey was anonymous, the exact number for individual 

pilots cannot be determined. Of the duties, 26% were 

single sector and 74% two sector. The breakdown by type 

of duty was as follows: 12% departing from New Zealand, 

20% returning to New Zealand, and 68% round trip. 

Reporting and top of descent occurred at all times of day. 

However, the commonest reporting times were between 

0500 and 0600 (17%), between 1400 and 1600 (24%), and 

between 2000 and 2200 (9%). Top of descent occurred 

most frequently between 0400 and 0600 (15%), between 

1400 and 1500 (15%), and between 2300 and 0000 (18%). 

The median duty length was 8.2 h, and the lower and 

upper quartiles were 7.1 h and 9.0 h, respectively. 

 All four factors (time of day, length of duty, number of 

sectors, and type of duty) contributed signifi cantly to 

levels of fatigue at top of descent (see Table I ). With regard to time of day, fatigue followed a standard circadian pattern with fatigue levels highest in the early hours 

of the morning and lowest in the early evening ( Fig. 1 ). 

Mean levels related to type of duty varied between 3.88 

(round trip), 4.04 (returning to New Zealand), and 4.23 

(leaving New Zealand). The main effect of length of duty 

( P , 0.001) was explained by quadratic trend where the 

increase in fatigue was greater for shorter than for 

TABLE I. THE CONTRIBUTION OF VARIOUS TERMS TO THE EQUATION OF BEST FIT. 

 In Model Order Included Last 

Factor or interaction df % Total Sum of Squares Signifi cance % Total Sum of Squares Signifi cance 

Time of day 4 24.23 P , 0.001 20.48 P , 0.001 

Length of duty 2 11.30 P , 0.001 3.66 P , 0.001 

Sectors 1 0.13 P , 0.05 0.45 P , 0.001 

Type of duty 2 0.51 P , 0.001 0.24 P , 0.01 

Time of day x length of duty 6 1.55 P , 0.001 1.50 P , 0.001 

Sectors x length of duty 2 0.23 P , 0.01 0.23 P , 0.01 
Aviation, Space, and Environmental Medicine x Vol. 79, No. 11 x November 2008 1049

FATIGUE IN SHORT-HAUL PILOTS — POWELL ET AL.

longer duties. With respect to sectors, two-sector operations were associated with fatigue levels that were 0.56 

higher than single-sector operations. 

 In addition to the main effects, two interaction terms 

were signifi cant. The effect of the length of duty varied 

with time of day ( P , 0.001), as is shown in Fig. 2 . Thus 

there was little increase among duties ending between 

0300 – 0600 as fatigue levels are high for all lengths of 

duty; this contrasts with duties ending between 1200 –

 1500, where the effect of time of duty was substantial. 

There was also a signifi cant interaction between length 

of duty and the number of sectors fl own ( P , 0.05). The 

increase in fatigue with duty length was more evident in 

single-sector than in two-sector operations. 

 The contribution of the various factors and interaction 

terms to the best-fi tting model of fatigue at the top of descent is presented in Table I . We have described the contribution of the factors where the individual terms have 

been added in sequence (in model order) and where the 

terms have been added in the presence of the other signifi cant factors (included last). The time of day component is represented by a 24-h sinusoidal function together 

with the second harmonic, and the length of duty by a 

quadratic function of time. For the time of day by length 

of duty interaction, the second harmonic of time of day 

crossed with the quadratic component of length of duty 

has been excluded, as it did not contribute signifi cantly 

to the overall fi t. Terms up to and including the second 

harmonic explained 95% of the variance associated with 

time of day, and a quadratic trend explained 99% of the 

variance associated with length of duty. 

 In order to demonstrate the effect of start time on the 

progression of fatigue we looked at start time in 3-h intervals ( Fig. 3 ). There are marked differences at different 

times of day in both the fatigue level after 3 h duty and 

the rate at which fatigue increases. For duties starting at 

0300, fatigue is at a moderately high level after only 3 h 

duty, but changes little with duty length. In contrast, a 

short duty starting at 1800 ends with little fatigue while 

a 12-h duty ends with high levels of fatigue. Duties commencing later at 2100 or 0000 reach fatigue levels above 

5 after only 6-7 h of duty, whereas duties starting at 0300 

do not reach this level, even after 12 h. 

 DISCUSSION 

 This study examined pilot fatigue at the top of descent 

across routine commercial two-pilot operations. We found 

time of day, length of duty, the number of sectors, and the 

type of duty (to or from home base) all contributed significantly to the level of fatigue at the top of descent. The 

strongest infl uence on fatigue was time of day with the 

highest levels in the window of circadian low (0200 – 0600). 

As anticipated, fatigue also increased with the length 

of duty and the number of sectors fl own. We further 

found duties involving a trip away from home base were 

Fig. 1. The main effect of time of day 

on subjective fatigue at top of descent. 

Error bars correspond to 6 1 SEM. 

Fig. 2. The combined effect of 

length of duty and time of day on subjective fatigue at top of descent. Error 

bars correspond to 6 1 SEM. 
1050 Aviation, Space, and Environmental Medicine x Vol. 79, No. 11 x November 2008

FATIGUE IN SHORT-HAUL PILOTS — POWELL ET AL.

associated with slightly increased levels of fatigue, but it 

is possible that this may be infl uenced by the pattern of 

work preceding the duty rather than the duty itself. 

 The study also found that the effect of the length of 

duty depended on the time of day at the top of descent. 

When this effect was translated into report time we 

found that time of day has a marked effect on the overall 

level of fatigue at the start of the duty and on the rate at 

which fatigue levels increase. While existing fl ight time 

limitations such as CAP371 and EU regulations make a 

relatively minor distinction between day and night (2 – 3 h 

duty time), the fatigue patterns we have found exhibit a 

much greater difference. For example, we have seen the 

level of fatigue after 12 h for duties starting between 

0600 and 1200 is already exceeded after 3 h when the 

duty starts between midnight and 0300. The fi nding of 

this study would suggest relaxing the limits for daytime 

duties and tightening those for two-pilot nighttime duties. Other studies also point to a circadian effect greater 

than is refl ected in current limitations but are based on a 

less comprehensive dataset ( 7 ). 

 The results are also broadly consistent with our recent 

study of short-haul multisector operations ( 3 ) which 

found a similar relationship between time of day and 

length of duty; however, the current study extends this 

analysis to cover the full 24-h period. Furthermore, the 

effect of an additional sector was similar in both studies 

despite markedly different sector lengths. Since the results were corrected for duty length, this effect may be 

due to the workload associated with an additional approach and landing. 

 It should be noted that the current study is based on 

pilot subjective reports and no performance testing was 

carried out. We did not include information about infl ight napping or operational considerations that may 

have infl uenced workload. Furthermore, the study is 

limited by a lack of information about the pattern of 

work immediately preceding duty. While it is diffi cult to 

see how this would systematically confound the results, 

this possibility cannot be excluded. 

Fig. 3. Trends in fatigue with increasing length of duty, for duties starting at different times of day. The seven 

points on each curve relate to lengths 

of duties of 3 h, 4.5 h, 6 h, 7.5 h, 9 h, 

10.5 h, and 12 h, respectively. 

 However, there are several aspects of the study that 

support the validity of the results. As a result of the simplicity of the methodology, it has been possible to collect 

information from a very large number of fl ights. In addition the response rate is considerably higher than in 

most comparable studies where participation has relied 

on pilot volunteers. While the data have been collected 

from one airline operation, it has been possible to study 

duties of different duration covering all times of day, 

and this has enabled greater confi dence to be placed in 

the parameters of the fi tted model. In conclusion, this 

study has provided a snapshot of all two-pilot mediumrange duties from a single operator, and the derived 

trends in the build-up in fatigue have important implications for fl ight-time limitations. 

 ACKNOWLEDGMENTS 

Authors and affi liations: Keith J. Petrie, Ph.D., Department of 

Psychological Medicine, University of Auckland, Auckland, New 

Zealand; David M. C. Powell, FAFOEM, and David Holland, Medical 

Unit, Air New Zealand, Auckland, New Zealand; and Mick Spencer, 

M.Sc., no institutional affi liation. 

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