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Aspects of work organization and reduced sleep quality of airline pilots

Pollyanna Pellegrino1; Claudia Roberta de Castro Moreno; Elaine Cristina Marqueze1,

DOI: 10.5935/1984-0063.20190053

 

ABSTRACT:

OBJECTIVE To estimate the prevalence and association of work organization associated with poor sleep quality among airline pilots.
METHODS 1234 airline pilots filled out an online questionnaire. Independent variables included demographic data, work organization aspects, health, and sleep information. A question derived from the Karolinska Sleep Questionnaire was used to obtain subjective sleep quality. Poisson regression with robust variance was performed.
RESULTS The prevalence of poor sleep quality was 48.2%. Poor sleep quality was associated with high frequency of technical delays, ≥ 5 consecutive night shifts, moderate and great need for recovery after work, difficulty commuting to work, being insufficiently physically active and sleeping 6-8 hours and < 6 hours on days off.
CONCLUSION Pilots' daily work schedules, consisting of frequent delays, long working hours and perceived high work demands preventing adequate recovery were associated with poor sleep quality.

Keywords:
Sleep; Sleep Initiation and Maintenance Disorders; Pilots; Work Schedules.

Citation: Pellegrino P, Moreno CRC, Marqueze EC. Aspects of work organization and reduced sleep quality of airline pilots. 12(1):43. doi:10.5935/1984-0063.20190053
Received: May 29 2018; Accepted: November 07 2018
 

INTRODUCTION

The profession of a commercial aviation pilot requires rigorous physical and psychological aptitude, involving the ability to work under a high level of responsibility, concentration, pressure for fast-decision making and adapting to operational changes1. Working conditions, such as irregular schedules, long work hours and working in different time zones, can cause exhaustion and permanent fatigue2,3, leading to insufficient sleep and greater need for recovery after work4. Fatigue is also associated with factors related to the individual such as advanced age, poor health, low level of physical activity and consumption of alcoholic beverages4.

In contrast with studies on fatigue, little is known about the sleep quality of airline pilots5. Sleep quality is a factor contributing to fatigue, where studies have shown that up to 90% of shift workers report sleepiness and fatigue6. Studies also reveal that working hours, especially night shifts, commonly worked by pilots, can affect sleep, decrease sleep quality and increase sleep disorders. A high prevalence of pilots perceive poor sleep quality7,8. In addition, other negative health consequences are associated with sleep-related problems, such as metabolic diseases, musculoskeletal and cardiovascular disorders, as well as impaired cognitive performance, reducing concentration and the ability to react to unexpected events9. In this context, the objective of the present study was to estimate the prevalence of and factors associated with poor sleep quality among airline pilots.

 

MATERIAL AND METHODS

A cross-sectional study was carried out in Brazilian commercial aviation pilots (captains and co-pilots) who flew national and international flights, affiliated to the Association of Civil Aviation Pilots (ABRAPAC). Approximately half of the pilots registered with the National Aviation Agency (ANAC ) in Brazil belong to ABRAPAC. All member pilots (n=2530) were invited to participate in the study via e-mail and 1234 agreed to take part.

This investigation is part of the study “Chronic fatigue, working conditions and health of Brazilian pilots”10. The study was based on a convenience sample with 91% power, calculated a posteriori (G*Power program 3.1.4) with a confidence level of 95% (α=5%) to detect prevalence ratios ≥ 1.20 as significant using prevalence of poor sleep quality (48.2%) as a parameter.

The following independent variables were analyzed:

- Demographic data1 (gender, age, education, marital status, children under 12 years old),

- Work-related aspects1 (frequency of operational flight delays, commuting time between hotel and airport, difficulty commuting between residence and airport, start times on day and night shifts, finish times on afternoon and night shifts, years working night shifts, maximum number of consecutive work days and nights, flight hours per month),

- Sleep (sleep duration after day and night work, and on days off) - based on a question adapted from the Karolinska questionnaire11,

- Health (need for recovery after work12 - alfa de Cronbach 0,81), time engaged physical activity per week and self-perceived13, diurnal preference - based on a question adapted from the Karolinska questionnaire11.

The dependent variable of self-perceived sleep quality was evaluated by a single question: “In general, how do you rate your sleep?”, adapted from the Karolinska sleep questionnaire11, with response options “very good”, “good”, “neither good nor bad” and “quite/very bad”. For this study, responses were dichotomized into good sleep quality (very good or good) and poor sleep quality (neither good nor bad or quite/very bad).

The variables were expressed as absolute and relative frequencies. The Chi-squared and Fisher's exact hypotheses tests were used for comparing proportions. Poisson regression with robust variance was employed to analyze the factors associated with poor sleep quality, allowing identification of both risk and protective factors in qualitative variables having a high prevalence (>10%) with lower bias in prevalence ratios. Based on the results of the hypotheses tests, independent variables with p<0.20 were tested on the multiple Poisson regression model in increasing order of statistical significance (forward stepwise technique). The models were adjusted for the variables gender, age, children under 12 years of age, education, BMI and marital status.

All tests were considered statistically significant when p<0.05. Data were analyzed using the STATA 12.0 program (Stata Corp, Texas, USA). The ethical issues related to research in humans were duly respected, and the project was approved by the Research Ethics Committee of the Federal Institute of Education, Science and Technology of São Paulo (protocol number 625158).

 

RESULTS

Pilots interviewed were predominantly male (97.1%), aged ≤ 39 years (52.4% - mean age 39.1, SD=9.8 years), had incomplete or complete higher or post-graduate education (79.7%), had a partner (84.7%), no children younger than 12 years (61.3%), were overweight or obese (67.2%) and held the position of national captain (51.7%), followed by national copilot (39.1%). Notably, 53.8% of the pilots did not reside near their work base, having an average commute time of 2 hours, 41 minutes (SD=2 hours, 2 minutes).

Almost half of the pilots (48.2%) reported poor sleep quality. A higher rate of poor sleep quality was observed among pilots who reported: frequent operational flight delays, difficulty commuting between residence and airport, starting morning shifts before 5:00h and finishing after 22:00h, working ≥ 7 consecutive days, ≥ 5 consecutive nights and flying ≥ 66 hours per month. A higher rate of poor sleep quality was also observed among pilots who needed a longer recovery after work, performed < 150 minutes of physical activity per week, had a self-perceived evening preference, and slept < 6 hours on work days and days off (Table 1).

Table 1. Work, health and sleep aspects according to self-perceived sleep quality, 2018.
VARIABLE CATEGORY GOOD QUALITY POOR QUALITY χ2
n (%) n (%) p-value
Work-related aspects        
Frequency of operational flight Never, rarely, or sometimes 430 (67.2) 303 (51.0) < 0.01
Delays Frequently or always 210 (32.8) 291 (49.0)  
Commute time between hotel and < 42 minutes 451 (70.7) 394 (66.7) 0.12
Airport ≥ 42 minutes 187 (29.3) 197 (33.3)  
Difficulty commuting between Never or almost never 434 (67.8) 323 (54.4) < 0.01
residence and airport Sometimes 156 (24.4) 183 (30.8)  
  Frequently or always 50 (7.8) 88 (14.8)  
Start time of day shift 24:00-4:59h 92 (14.7) 128 (22.4) < 0.01
  5:00-5:59h 294 (47.2) 289 (50.4)  
  6:00-6:59h 158 (25.3) 96 (16.7)  
  7:00-11:00h 80 (12.8) 60 (10.5)  
End time of afternoon shift 16:00-21:59h 230 (39.1) 173 (32.2) 0.01
  22:00-23:59h 287 (48.8) 274 (50.9)  
  24:00-6:00h 71 (12.1) 91 (16.9)  
Start time of night shift 14:00-21:59h 360 (59.8) 326 (58.6) 0.95
  22:00-23:59h 203 (33.7) 190 (34.2)  
  24:00-1:59h 22 (3.7) 22 (3.9)  
  2:00-4:59h 17 (2.8) 18 (3.3)  
End time of night shift < 5:00h 319 (53.0) 278 (50.1) 0.67
  5:01-8:00h 213 (35.4) 210 (37.8)  
  8:01-12:00h 66 (10.9) 61 (11.0)  
  12:01-16:00h 4 (0.7) 6 (1.1)  
Years working night shifts Does not work nights 359 (56.1) 317 (53.4) 0.19
  1-5 years 101 (15.8) 119 (20.0)  
  6-10 years 86 (13.4) 78 (13.1)  
  11-15 years 32 (5.0) 36 (6.1)  
  ≥16 years 62 (9.7) 44 (7.4)  
Maximum number of consecutive ≤ 6 days 540 (84.9) 459 (77.9) < 0.01
days worked ≥ 7 days 96 (15.1) 130 (22.1)  
Maximum number of consecutive 1-2 nights 130 (21.0) 74 (13.0) < 0.01
nights worked 3-4 nights 351 (56.8) 318 (55.9)  
  ≥ 5 nights 137 (22.2) 177 (31.1)  
Flight hours per month ≤ 65 hours 317 (50.0) 256 (43.7) 0.02
  ≥ 66 hours 317 (50.0) 329 (56.3)  
Health and sleep aspects        
Need for recovery after work Less need 295 (46.1) 97 (16.4) < 0.01
  Moderate need 210 (32.8) 218 (36.7)  
  Greater need 135 (21.1) 279 (45.2)  
Weekly physical activity time ≥ 150 minutes 359 (56.2) 268 (45.2) < 0.01
  < 150 minutes 280 (43.8) 325 (54.8)  
Self-perceived diurnal preference Intermediary 91 (14.2) 50 (8.4) < 0.01
  Morning 266 (41.6) 225 (37.9)  
  Evening 283 (44.2) 319 (53.7)  
Sleep duration after day shift > 8 hours 70 (10.9) 36 (6.1) < 0.01
   6-8 hours 529 (82.8) 446 (75.1)  
  < 6 hours 40 (6.3) 112 (18.8)  
Sleep duration after night shift > 8 hours 113 (17.7) 81 (13.7) < 0.01
  6-8 hours 382 (59.7) 301 (50.7)  
  < 6 hours 145 (22.6) 211 (35.6)  
Sleep duration during days off > 8 hours 459 (71.9) 367 (62.0) < 0.01
  6-8 hours 176 (27.6) 207 (34.9)  
  < 6 hours 3 (0.5) 18 (3.1)  

The bivariate model revealed that the factors frequent operational flight delays, sometimes or often having difficulty commuting between residence and airport, starting the morning shift very early and finishing the evening shift very late, working ≥ 7 consecutive days, working ≥ 5 consecutive nights, flying ≥ 66 hours per month, greater need for recovery after work, evening preference, engaging in < 150 minutes of physical activity per week, sleeping < 6 hours after day and night shifts and on days off were associated with poor sleep quality. On the adjusted multiple model, the factors frequent operational flight delays, often having difficulty commuting between residence and airport, working ≥ 5 consecutive nights, greater need for recovery after work and sleeping < 6 hours on days off were associated with poor sleep quality (Table 2).

Table 2. Work, health and sleep factors associated with poor sleep quality, 2018.
VARIABLE CATEGORY Bivariate Multiple*#
PR (95% CI) PR (95% CI)
Work-related aspects      
Frequency of operational flight Never, rarely, or sometimes 1 1
Delays Frequently or always 1.40 (1.25-1.57) 1.14 (1.01-1.28)
Difficulty commuting between Never or almost never 1 1
residence and airport Sometimes 1.26 (1.11-1.43) ns
  Frequently or always 1.49 (1.28-1.73) 1.19 (1.04-1.38)
Start time of day shift 7:00-11:00h 1  
  24:00-4:59h 1.36 (1.08-1.69)  
  5:00-5:59h 1.16 (0.93-1.42)  
  6:00-6:59h 0.88 (0.68-1.13)  
End time of afternoon shift 16:00-21:59h 1  
  22:00-23:59h 1.14 (0.98-1.30)  
  24:00-6:00h 1.31 (1.09-1.56)  
Maximum number of consecutive ≤6 days 1  
days worked ≥ 7 days 1.25 (1.09-1.42)  
Maximum number of consecutive 1-2 nights 1 1
nights worked 3-4 nights 1.31 (1.07-1.59) ns
  ≥ 5 nights 1.55 (1.26-1.91) 1.33 (1.09-1.62)
Flight hours per month ≤ 65 hours 1  
  ≥ 66 hours 1.14 (1.01-1.28)  
Health and sleep aspects      
Need for recovery after work Less need 1 1
  Moderate need 2.06 (1.69-2.50) 1.96 (1.60-2.41)
  Greater need 2.73 (2.26-3.27) 2.38 (1.94-2.91)
Weekly physical activity time ≥150 minutes 1 1
  < 150 minutes 1.26 (1.11-1.41) 1.17 (1.05-1.32)
Self-perceived diurnal Indifferent 1  
Preference Morning 1.29 (1.01-1.64)  
  Evening 1.49 (1.18-1.89)  
Sleep duration after day shift > 8 hours 1  
   6-8 hours 1.35 (1.02-1.77)  
  < 6 hours 2.17 (1.63-2.87)  
Sleep duration after night shift > 8 hours 1  
  6-8 hours 1.05 (0.87-1.27)  
  < 6 hours 1.41 (1.17-1.71)  
Sleep duration during days off > 8 hours 1 1
  6-8 hours 1.22 (1.07-1.37) 1.16 (1.03-1.31)
  < 6 hours 1.93 (1.59-2.33) 1.59 (1.31-1.93)

* Adjusted for gender, age, having children < 12 years of age, education, BMI and marital status

# Area ROC = 0.73

ns not significant

 

DISCUSSION

The work organization of airline pilots and situations that increase the likelihood of fatigue, worsen the sleep quality of these professionals. Sleep disturbance is also highly prevalent in shift and night work, and may be more important than other health problems7. Excessive fatigue and sleep disturbances can also have negative effects on other aspects of work, such as a decline in work performance and increases in errors, work accidents and absenteeism14.

A greater need for recovery after work was associated with a higher probability of poor sleep quality, suggesting that piloting is a high-stress activity that leads to fatigue which consequently affects sleep6,8.

The long working hours can promote physical and mental exhaustion among these professionals, impairing sleep quality. Flights that start very early and end very late, as well as night flights that cause circadian desynchronization, contribute to excessive drowsiness and lead to unintentional sleep at work and increased risk of accidents1. Working five or more consecutive nights may indicate long working hours and lead to sleep deprivation. Folkard and Tucker15 showed that the risk of accidents when working four consecutive nights was 36% higher than for a single night's work. To reduce the risk of accidents and chronic fatigue among pilots, Rodionov16 suggested they make only two consecutive night flights.

According to current regulations - Law 13475 of August 8, 2017, the working day is counted between the time of arrival at the workplace, which must be at least 30 minutes before the flight time, and ends 30 minutes after engine shutdown17. Thus, operational delays lengthen the pilot´s working day, who may already be at their limit. In addition, operational delays can reduce the productivity of working hours, leading to pilots having to work overtime1,18.

Another factor associated with poor sleep quality among the pilots studied was commuting time. Since most pilots worked far from their residence, the average time spent commuting was 2 hours and 41 minutes. This factor, associated with very early morning shifts, late night shifts, as well as long working hours, extend pilots wake time and reduce rest time between work shifts or during time off1,2,19. Even on days off, a substantial percentage of pilots reported sleeping less than eight hours. Several epidemiological studies have shown that sleep deprivation and short sleep are risk factors for health20.

During days off, the pilots were unable to increase sleep duration, thus contributing to chronic sleep restriction and poor self-perceived sleep quality. Moreover, these professionals were unable to perform enough physical activity to improve sleep quality. Irregular working hours may be a relevant factor promoting sleep restriction and a sedentary lifestyle, leading to poor sleep quality21.

The design of the present study precluded the determination of cause and effect for the variables assessed. However, the high number of participants (about 1/4 of all Brazilian pilotsa) provided good internal reliability for the factors associated with poor sleep quality among Brazilian commercial aviation pilots.

 

CONCLUSION

Pilots' daily work schedules, consisting of frequent delays, long working hours and perceived high work demands preventing adequate recovery were associated with poor sleep quality. Further studies are needed to investigate the association between poor sleep quality and health, performance and flight safety.

 

ACKNOWLEDGEMENTS: ABRAPAC, CAPES (NO 1439999) AND PROF ELIANA ZUCCHI.

 

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