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

### RESEARCH ARTICLE

P OWELL D, S PENCER MB, H OLLAND D, P ETRIE 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 flown on reported fatigue at the top of descent in two-pilot regional operations.

Methods: Pilots flying 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

.



# M ANAGING FATIGUE is an important componentof 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-flight 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 fromthe 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 whatduty 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 augmentedcrews 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 influences of factors such as duty length and time of day onfatigue. 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 fatiguewere 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 difficult 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. Petrie1048 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 thenanalyzed by a stepwise least squares (analysis of variance and regression) procedure. The factors included inthis 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 subsequentanalyses, 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 coefficient 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 , 0.01Aviation, 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-fitting 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 theterms have been added in the presence of the other significant 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 theprogression 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 whilea 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 thetype 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 oflength 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 daytimeduties 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 studiesdespite markedly different sector lengths. Since the results were corrected for duty length, this effect may bedue 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 thatsupport 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 flights. 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, thisstudy has provided a snapshot of all two-pilot mediumrange duties from a single operator, and the derivedtrends 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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