DOT/FAA/AM-95/5

Office of Aviation Medicine

Washington, D.C. 20591

A Longevity and Survival

Analysis for a Cohort of

Retired Airline Pilots

Robert O. Besco

Professional Performance Improvement, Inc.

Dallas, Texas

Satya P. Sangal

Wright State University

School ofAerospace Medicine

Dayton, Ohio

Thomas E. Nesthus

Stephen J. H. Veronneau

Civil Aeromedical Institute

Federal Aviation Administration

Oklahoma City, Oklahoma 73125

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February 1995

Final Report 19950316 093

This document is available to the public

through the National Technical Information

Service, Springfield, Virginia 22161.

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U.S. Department

of Transportation

Federal Aviation

Administration
NOTICE

This document is disseminated under the sponsorship of

the U.S. Department of Transportation in the interest of

information exchange. The United States Government

assumes no liability for the contents or use thereof.
Technical Report Documentation Page

1. Report No.

DOT/FAA/AM-95/5

2. Government Accession No. 3. Recipient's Catalog No.

4. Title and Subtitle

A Longevity and Survival Analysis for a Cohort of Retired Airline

Pilots

5. Report Date

February 1995

6. Performing Organization Code

7. Author(s)

R.O. Besco, Professional Performance Improvement, Inc., Dallas, TX; S.P

Sangal, Wright State University School of Aerospace Medicine, Dayton,

OH; and T.E. Nesthus and S.J. H. Veronneau, Civil Aeromedical

Institute

8. Performing Organization Report No.

9. Performing Organization Name and Address

Civil Aeromedical Institute

P.O. Box 25082

Oklahoma City, Oklahoma 73125

10. Work Unit No. (TRAIS)

11. Contract or Grant No.

12. Sponsoring Agency name and Address

Office of Aviation Medicine

Federal Aviation Administration

800 Independence Ave., S.W.

Washington, DC 20591

13. Type of Report and Period Covered

14. Sponsoring Agency Code

15. Supplemental Notes

16. Abstract

There is a popular belief in the aviation industry that retired pilots die at a younger age than the general

population. If this belief is in fact, correct, research into the factors or events precipitating an early mortality among

retired airline crew members could be of interest to the FAA. Few studies have addressed the question "Do retired

airline pilots die at a younger age than their 60 year-old counterparts in the U.S. population?" Airline pilots reach the

mandatory retirement age of 60 after an entire career of active health monitoring and maintenance required by the

Federal Aviation Administration (FAA). In this study, a preliminary survey was made to determine the mortality

and survival profile of retired pilots from a major U.S. airline. An initial sample of 2209 retired pilots and flight

engineers was surveyed. Early and late retirees were dropped from the sample, leaving us with 1494 pilots who

retired at age 60 between the study dates of April 1968 to July 1993. The Life Table Method was identified as the

most suitable approach to analyze the pattern of mortality for this data set. Life Table analysis provides estimates of

probabilities of surviving a given number of years after retirement. This technique allows subjects to enter (i.e., retire

at age 60) or leave the study (i.e., die) at different points in time and it utilizes all the data on partial exposure to the

risk of dying. It is non-parametric and requires no assumptions about the distribution of the survival function. Due to

the anonymity of our sampling and other resultant assumptions, comparisons were made with the 1980 census of the

U.S. general population of 60 year-old white males. A difference in life expectancy of more than 5 years longer was

found for our sample of retired airline cockpit crew members. Half of the pilots in this sample retiring at age 60

were expected to live past 83.8 years of age, compared to 77.4 years for the general population of 60 year-old white

males in 1980. The authors concluded that the question of lowered life expectancy for airline cockpit crews was not

supported by the results of this particular data set.

17. Key Words

Pilots

Longevity

Survival Probability

Life Table Method

Cohort Analysis

19. Security Classif. (of this report)

Unclassified

20. Security Classif. (of this page)

Unclassified

18. Distribution Statement

Document is available to the public through

the National Technical Information

Service, Springfield, Virginia, 22161

21. No. of Pages

15

22. Price

Form DOT F 1700.7 (8-72) Reproduction of completed page authorized
ACKNOWLEDGMENTS

The authors wish to acknowledge the cooperation ofthe following individuals at American

Airlines: The late Captain Bill James, Vice President of Flight; Dr. Jeff Davis, Corporate

Medical Director; Gayla Coffelt, Manager, Life, Health and Disability Plan Administration;

and Bobbie Rystad, Life and Disability Administrator.

We are also grateful for the contributions ofthe following individuals at the Allied Pilots

Association: Captain Brian Mayhew, Special Projects Director; and Mike Knoerr, Benefits

Manager.

We also give a special thanks to Captain Jack Webb (AAL, Ret.), Secretary of the Grey

Eagles.

Much gratitude is felt for the support and guidance ofthe professional staffmembers ofThe

Civil Aeromedical Institute of the Federal Aviation Administration and particularly, Dr.

Robert E. Blanchard, Manager, Human Factors Research Laboratory.

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A LONGEVITY AND SURVIVAL ANALYSIS FOR A COHORT OF

RETIRED AIRLINE PILOTS

INTRODUCTION

A question that has been discussed, pondered, and

argued for years in the cockpits, briefing rooms,

negotiating tables, and watering holes of commercial

aviation is "What is the life expectancy ofthe typical

retired airline pilot?" The conventional, operational

wisdom has pointed to those incidents where retired

airline pilots were in excellent health and physical

condition and yet, died in the first few years, and even

a few months after retirement. Every airline pilot can

recount several personal anecdotes of colleagues who

died very soon after the mandatory retirement age of

60. Some people believe that factors associated with

this career may have precipitating effects on mortality.

Professional airline pilots should be in far better

health at all ages than the general population. Every

six months, airline pilots must pass a Class One Flight

Physical, which is defined and required by the Federal

Aviation Administration (FAA). Airline pilots reach

age 60 (their mandatory-retirement date) after an

entire career of active health monitoring and maintenance. Some people conclude that the life expectancy

of a 60 year-old retired airline pilot should be considerably longer than the counterpart 60 year-old from

the general population due to the continual medical

scrutiny, early detection and treatment of disorders,

and the selection out ofthose with serious pathology.

However, the "flightline talk" ofthe aviation industry

contends that pilots die at a younger age than the

general population. Each time an airline pilot dies in

the first few years after retirement, the hypothesis of

the airline pilots' premature death is reborn and

reinforced in the minds of the observers.

The underlying questions of a lowered life expectancy hypothesis are believed to be concerned with the

effects ofthose factors to which airline pilots may have

had excessive exposure. Several authors have pointed

out physical and emotional Stressors that may have a

negative effect on the health and well-being of airline

pilots (Besco and Smith, 1990; Mohler and Mohler,

1992;Mohler, 1993; Morgan, 1992; Reinhart, 1988).

In no particular order, some of the most frequently

discussed of these factors are:

1. Fatigue;

2. Cosmic radiation and electromagnetic field effects;

3. Circadian dysrhythmia;

4. Sound and vibration exposure;

5. Lowered humidity, ambient pressure and mild

hypoxia;

6. Potential air quality contaminants;

7. Questionable nutrition;

8. Responsibility for passenger safety and survival;

9. Loss of career threat from corporate failure/

confrontational labor relations;

,10.Anxiety ofdisqualification through professional

errors;

11. Concerns of losing medical certification from

occupational or other accidents, disease and

aging.

If an early mortality trend is in fact, real, research

into some or all of the factors listed above could be

initiated to investigate their precipitating potential.

Epidemiological investigation could also provide critical information concerning such trends as compared

with a matching sample of the general population.

Results of such analyses would be of interest to the

FAA as indicators of possible health factors to be

monitored in the pilot population. However, because

of the requirement for complete anonymity in the

present, preliminary study, thatlevel ofanalysis could

not be performed. This study is limited, therefore, to

assessing the overall question of differential mortality

for retired airline pilots. Future studies, should the

results from this study indicate they are warranted,

could explore the reasons for any differential effect

noted.
PREVIOUS RESEARCH

The authors could find little research that would

adequately address the question: "Do retired airline

pilots die younger or live longer than the general

population?" One article attempted to use statistical

and actuarial data to address the retired pilot longevity question. In that report, Muhanna and Shakallis

(1992) postulated that retired airline pilots have a

lowered life expectancy when compared to the general

population. The validity oftheir reported conclusions

could not be determined due to incomplete descriptions of their research methodology, sampling techniques, and data analysis. We found that the authors

assessed retired pilot mortality in a manner that does

not account for the changing nature of the sample,

i.e., taking into consideration all of the individuals

who enter (i.e., retire) and leave (i.e., die or enter late

in the study and leave at the close ofthe study, alive)

during each year ofthe study period (i.e., designed as

a cohort study). Also, their rates were expressed as

percentages which presented the mortality data in an

interesting manner, however, we felt it was an inappropriate method for analysis of realistic trends. In

fact, all of their data were presented as percentages.

No actual sample sizes were reported nor were any

survival statistics.

Morgan (1992) assumed the Muhanna and Shakallis

conclusions were valid. Their results prompted

Morgan's discussion of recent changes in the professional aviators' environment that could explain some

ofthe reputed shortened life expectancy. He pointed

out many significant factors in the list cited above

which might add life shortening stress to the professional airline pilot.

Kaji, Asukata, Tajima, Yamamoto and Hokari

(1993) found that the mortality rate from natural

causes was lower in active Japanese airline pilots than

in the generalJapanese population. Oftheir sample of

2327 pilots, 191 had retired. They found that only 16

of the 191 retired pilots had died. Kaji, et al., concluded that the improved health standard of the

airline pilots explained theirlower mortality and higher

life expectancies. However, they did not have a large

enough sample of retired pilots to determine reliable

estimates of differences in post retirement life expectancy between pilots and the general population.

Irvine and Davies (1992) conducted a proportional

mortality study of active and retired British Airways

pilots. Irvine and Davies reported the conclusions of

the actuaries to the British Airways Pension Schemes

in an unpublished study for the period July 1986 to

March 1989. Their emphasis primarily concerned

causes of death, but they quoted the actuaries as

reporting an increase in "life expectancy ofabout 5

years better than other reference pensioners." No

sample size, sampling plan, or analytical methods

were reported for the undocumented actuarial study.

In their study, Irvine and Davies did not report any

survival data for retired pilots in their conclusions.

Salisbury, Band, Threlfall, and Gallagher (1991)

conducted an epidemiological study ofdeceased British Columbia pilots. They reported an elevated Proportional Cancer Mortality Ratio (PCMR) for airline

pilots. Band, Spinelli, Ng, Math, Moody, and

Gallagher (1990) conducted a study on causes of

death in 891 Canadian Pacific Airlines pilots. They

reported elevated PCMRs for the pilots in their sample.

Hoiberg and Blood (1983) in a study of age-specific

morbidity concluded that Navy pilots are in much

better health than the normal population. The oldest

pilots in their study were under 54 years of age. None

of these authors studied survival patterns of retired

pilots.

As part of the on-going research program on the

question ofmandatory retirement at age 60 for airline

pilots, the FAA's Civil Aeromedical Institute has been

investigating the relationship of age and performance

in airline pilots. Hyland, Kay, Deimler, and Gurman

(1992) conducted an extensive literature review on

the subject. They did not specifically address the

question of retired airline pilots longevity. Nor did

they investigate the potential effects of a career-long

exposure to the unique factors associated with a pilot's

profession.
OBJECTIVES

This study was proposed as a preliminary investigation of the distribution of age at death of retired

airline pilots and to investigate a large enough sample

ofretired pilots to provide reliable and valid estimates

of post retirement survival. Survival patterns of retired airline pilots have a far-reaching impact on

pilot's careers, life insurance and retirement benefits

(Mayhew, 1992; Muhanna and Shakallis, 1992; and

U. S. Congress, 1990). Survival patterns ofretired air

crew may also provide evidence that could lead to

more research and epidemiological investigation of

factors of unknown importance, associated with the

conduct of a pilot's profession. The authors also felt

that the question should be addressed specifically to

provide the aviation community with scientific evidence, supporting or refuting the premature mortality

hypothesis and hopefully to clear a way for the sharing

of critical information contained in such data bases.

In our preliminary survey, no attempt was made to

determine cause of death. This was agreed upon in

order to preserve anonymity ofour sample and secure

the cooperation of the airline providing the data.

Therefore, no attempt was made to conduct any

epidemiological investigations of such variables as

smoking, diet, exercise, family history, current health

status, or cause of death. Dates in the corporate

records were assumed to be accurate since the dates of

hire, birth, retirement, and death are critical for salary, seniority level, and pension benefits for all air

crew members.

METHODS

Cooperation from American Airlines (AAL), the

Allied Pilots Association, and the Grey Eagles (retired

AAL pilots) was received. The study was based on the

receipt of data for 2209 pilots and flight engineers

who had retired from active service with American

Airlines during the 25 years between April 1968 and

July 1993. The records of our sample were kept on a

computerized data base. Each flight crew member was

identified by birth date, date of hire, date of retirement, and date of death. No employee identification

such as social security, employee, or FAA certificate

numbers were provided for the study. The records of

an estimated 250 additional pilots who had retired

before April 1968 were recorded on a micro fiche data

base, but the economics of retrieving these data

prevented these pilots from being included in this

survey.

Throughout the period in which the pilots in this

sample were employed, American Airlines maintained

stringent medical screening and high health standards, even at the initial hiring. American Airlines

required an annual company flight physical in addition to the FAA flight physical. Ifthere is any bias in

the sample, it should be in the direction of better

health and increased longevity of the entire population of AAL pilots compared to the general population.

Since both pilots and flight engineers have the same

kind of exposure, in terms of working environment

and flying hours, it could be argued that they should

be treated as one population for the purposes of a

study such as this one. However, since the flight

engineers were not required to pass a Class I Flight

Physical and they are not required to retire at age 60,

it was decided to treat them as a separate population

from the 60 year-old pilot retirees.

Some of the pilots and flight engineers retired as

early as age 50. The information on the reasons for

early retirements was not available. Since it was observed that many pilots retired early because ofmedical disqualification, the early retirees were not included

in oursample of60 year-old retirees. This group could

potentially provide information concerning early incidence of the effects of career-related disability or

mortality, but, for our purposes in this study, they

were excluded from the sample. Hence, of the 2209

retirees, 360 had retired before age 60 and 355 stayed

with the airline in another presumed capacity and

retired after their 60th birthday. With the early and

late retirees parsed out of the sample, 1494 pilots

retiring at age 60 remained for analysis.

All the pilots in our sample retired at age 60 and in

different calendar years. The survival status of each

pilot was known at the close ofthe study in July 1993.

The sample was still maturing at the cutoffdate ofthe
study, because 1298 pilots were still living. Thus, each

pilot was in the study for a different length of time,

starting at their date of retirement.

One popular and practical technique for describing

survival experience over time is the actuarial or life

table method. Described by some authors in detail

(Griswold, Wilder, Cutler, and Pollack, 1955; Pearl,

1923), Cutler and Ederer (1958) described one very

important advantage ofthe life table method, which is

why we felt the technique was the most suitable

approach to analyze the pattern of mortality for this

data set. Specifically, this technique utilizes all survival information and data on partial exposure to the

risk of dying to provide the best estimates ofsurvival.

It allows subjects to enter (i.e., retire) or leave the

study (i.e., die or enter late and leave at the close ofthe

study alive) at different points of time during the 25

years ofthe study. Also, the life table approach is nonparametric and requires no assumptions about the

distribution of the survival function.

The Life Table analysis provides estimates ofprobabilities of surviving a given number of years after

retirement and emphasizes the advantage gained by

including survival information on individuals entering the series too late to have had the opportunity to

survive the extent ofthe 25 year study. In addition, it

estimates median residual lifetime or median remaining life expectancy for each year after retirement. This

method indicates that, among those pilots who survive a given number of years past retirement, half of

the survivors will die before the median life expectancy is reached and half will live beyond this median

residual lifetime age.

RESULTS

Figure 1 contains the distribution of new retirees

for each year in the 25-year study period. All 2209

retirees are represented in this figure. Early in the

surveyed years, the annual number of retirees was

much lower than in the later years of the study. This

increase merely reflects the growth ofthe airline after

World War II. Across the 25-year study period, 360

pilots and flight engineers took early retirement and

355 flight engineers stayed on past age 60. Ofthe 360

early retirees, 85% (306) had survived until the end of

the study period. Of the 355 flight engineers who

retired after age 60, 90% (321) survived until the

conclusion ofthe study. Ofthe 1494 age 60 retirees,

1298 (87%) survived throughout the study period.

The survival probability curves for the three retiree

groups (early, age 60, and late) are shown in Figure 2.

250 -r

68 70 72 74 76 78 80 82 84 86 88 90 92

Calendar Year

Figure 1: Distribution of pilots by retirement year.
There were no significant differences in the survival

probability for the three groups. However, to maximize the generalizability of this sample, as stated in

the methods section, it was decided to focus further

comparisons on the pilots who retired at age 60. The

analysis, Figures and Table that follow, involve only

the sample of 1494 retired pilots.

Initially, the retired pilots were divided into two

groups: those who retired through December 31,

1979, and those retiring from January 1980 to July

1993. This was done to determine if there were

different mortality experiences among pilots who retired in the early years ofthe study period, versus those

who retired in the later years. These two groups were

established to examine the issue that longer exposure

to high-altitude flying by pilots retiring in the second

half of the study period could be related to survival

patterns after retirement.

Figure 3 compares the survival distributions of

pilots who retired during the first half of the study

period, April 1968 to the end ofDecember 1979, with

the survival times ofthose pilots who retired in the last

half, January 1980 to July 1993. Using the log-rank

and the Wilcoxson test (Kalbleisch and Prentice,

1980), the difference between the above two survival

functions was not significant. Since no significant

difference was found between the survival patterns of

these two retired pilot groups, the two samples were

combined and analyzed as a single group (n=l494) of

retired pilots.

Because our sample was anonymous, we could not

verify the gender nor race of each retired pilot. It was

also not possible to determine other factors, such as,

socio-economic status, health consciousness, previous health-related histories, etc. of our sample. In

view of the high estimated percentage ofwhite males

in this pilot sample and our preliminary approach to

analyzing the data, the authors were required to make

certain assumptions for comparisons with a sample of

60 year-olds from the general population. Hence, the

survival rates ofthe pilots in our sample were compared

with those from the U.S. life tables of 1980, 1985 and

1989 for 60 year-old white males (U.S. Department of

Health and Human Services, 1984, 1988, and 1991).

The survival rates of retired pilots and that of the

U.S. white male population for the years 1980, 1985,

and 1989 were plotted. As seen in Figure 4, all three

survival curves in 1980, 1985, and 1989 for 60 yearold U.S. white males were very close. There were no

significant differences among the three years. The

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Retired before age 60

Retired at age 60

Retired after age 60

I I I I 1 I I I I I I 1 I 1 I I I I 1 I I 1 1 I

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

Years after Retirement

Figure 2: Comparison ofsurvival distributions ofthree groups of pilots who

retired at different ages.
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APR '68-DEC '79

JAN '80-JUL '93

I 1 1 I I I I I I I I I I I I I I I I I 1 I I I I I

8 10 12 14 16 18 20 22 24

Years after Retirement

Figure 3: Survival distribution of pilots who retired during April 1968

December 1979 and January 1980 - July 1993.

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AAL Sample

1980

1985

1989

60 65 70 75 80 85

Age

Figure 4: Comparison ofsurvival probability ofretired pilots

(from April 1968 to July 1993) with 60-year-old U.S. white male

population for 1980, 1985, and 1989.
Table 1. Combined Life Table and Survival Estimates of Pilots Retiring at Age 60 From April

1968 to July 1993

Years After

Retirement

Interval

Alive at

Beginning

of Interval

Died

During

Interval

Withdrawn

Alive

During

Interval*

Effective

Number

Exposed to

Risk of

Proportion

Dying

(Col. 3-5-

Col. 5)

Proportion

Surviving

(1-Col. 6)

Cumulative

Proportion

Surviving

Interval

Survival

Standard

Error

Median

Residual

Lifetime

(MRL)

MRL

Standard

Error

(1)

x to x+1 (2) (3) (4)

Dying

(5) (6) (7) (8) (9) (10) (11)

'x d

x

w

x 'x % Px P

x

0-1 1494 10 172 1408.0 0.0071 0.9929 0.9929 0.0022 23.812 0.25

1 -2 1312 14 147 1238.5 0.0113 0.9887 0.9817 0.0037 22.979 0.28

,\ 2-

3 1151 7 114 1094.0 0.0064 0.9936 0.9754 0.0043 21.986 0.28

3-4 1030 7 69 995.5 0.0070 0.9930 0.9685 0.0050 NA* NA

4-5 954 13 42 933.0 0.0139 0.9861 0.9550 0.0062

5-6 899 11 31 883.5 0.0125 0.9875 0.9431 0.0071

6-7 857 17 44 835.0 0.0204 0.9796 0.9239 0.0084

7-8 796 8 31 780.5 0.0102 0.9898 0.9145 0.0089

8-9 757 9 60 727.0 0.0124 0.9876 0.9032 0.0095

9-10 688 12 68 654.0 0.0183 0.9817 0.8866 0.0105

10-11 608 7 61 577.5 0.0121 0.9879 0.8758 0.0111

11-12 540 8 79 500.5 0.0160 0.9840 0.8618 0.0120

12- 13 453 9 77 414.5 0.0217 0.9783 0.8431 0.0133

13-14 367 7 57 338.5 0.0207 0.9793 0.8257 0.0145

14-15 303 14 53 276.5 0.0506 0.9494 0.7839 0.0176

15-16 236 9 41 215.5 0.0418 0.9582 0.7511 0.0200

16-17 186 5 23 174.5 0.0287 0.9713 0.7296 0.0216

17-18 158 9 19 148.5 0.0606 0.9394 0.6854 0.0248

18-19 130 6 21 119.5 0.0502 0.9498 0.6510 0.0272

19-20 103 7 21 92.5 0.0757 0.9243 0.6017 0.0309

20 - 21 75 3 23 63.5 0.0472 0.9528 0.5733 0.0335

21 - 22 49 1 10 44.0 0.0227 0.9773 0.5603 0.0352

22 - 23 38 1 11 32.5 0.0308 0.9692 0.5430 0.0381

23-24 26 2 11 20.5 0.0976 0.9024 0.4901 0.0495

24-25 13 0 11 7.5 0.0000 1.0000 0.4901 0.0495

25-26 2 0 2 1.0 0.0000 1.0000 0.4901 0.0495

Notes: * Those individuals who were alive at the conclusion of the 25-year study, in July 1993.

* NA denotes data are not available.

year 1980 was chosen for subsequent comparisons

with retired pilots because it occurred almost in the

middle ofthe 25-year span during which this sample

of pilots had retired.

Also shown in Figure 4 is the survival probability

curve for the retired pilots in our sample compared to

the three curves for the general population. The retired pilot group shows a much higher survival probability curve than does any of the other three curves

displayed. It can also be seen in Figure 4, that by age

85, the probability of survival would be more than

49% for the retired pilot sample.

Table 1 contains the results of the Life Table

Analysis for the 1494 retirement aged pilots (i.e.,

those who retired at age 60). An explanation ofsome

entries in Table 1 might clarify and help in understanding the table:

7
Years After Retirement Interval Column

(1) (x to x+1) i.e., 0-1 refers to the first year after

retirement at age 60; 1-2, the second year, etc. Each

interval is a cohort for the survival function.

Alive at Beginning ofInterval Column (2) (1 ) is

the number of cases that have survived to the beginning of the current interval. All 1494 were alive

during their first year after retirement. Successive

entries in this column are obtained by this formula: (1 +1) = 1 - (d + w ).

X XX X

Number Died Column (3) (d ) gives the number of

pilots who died during the interval. For example, ten

pilots died during their first year after retirement.

Fourteen during the second year, etc.

Withdrawn Alive During Interval Column (4)

(w ) refers to the pilots who were known to be alive at the

close ofthe study, butwere in the study for the maximum

duration denoted by the upper limit ofthe interval. At

the conclusion ofthe 25-year study period in July 1993,

172 surviving pilots had been retired for less than 1 year

during the first interval. Thus, each cohort (in each year

of 25-year study) contributes some information to our

knowledge ofsurvival during the interval.

Effective Sample Size Column (5). It is assumed

that pilots lost or withdrawn from observation during an

interval were exposed to the risk ofdying, on the average,

for one-halfthe interval. Thus, 1 ' = 1 - (w -^-2).

X X

V X '

Proportion Dying During Interval Column (6).

An estimate of the probability of dying during the

interval. Itis obtained by dividing the number ofdeaths

by the effective number exposed to risk: q = d * 1 '.

Proportion Surviving the Interval Column (7) is

referred to, alternately as the probability ofsurviving

the interval, or the survival rate. It is obtained by

subtracting the proportion dying during the interval

from unity: p = 1 - q .

Cumulative Proportion Surviving the Interval

Column (8) is generally referred to as the cumulative

survival rate, and gives the probability of a pilot

surviving to the end of the specified yearly interval

after retirement. Calculated by cumulatively

multiplying the proportion surviving each interval: Px = pj • p2 • p • ...px . Table 1 indicates

that the probability of a pilot surviving for 2 years

after retirement is 0.98. For 20 and 25 years after

retirement, survival probability is 0.60 and 0.49,

• fo.7

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I 0.5

lo.4

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a 0.3

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0.2

0.1

0

Retired AAL Pilots

Upper Interval

Lower Interval

White Males

I 1 I I 1 I I I I I I I I I I I I I 1 I I 1 I I I I I

60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86

Age

Figure 5: Survival probability curve of pilots retired during April 1968 to

July 1993, and 95% confidence interval, compared to 60-year-old U.S. white males.

8
respectively. Figure 5 depicts this column with the

95% confidence interval derived from the standard

error.

Survival Standard Error Column (9) provides a

measure of confidence with which one may interpret

the statistical results. Refer to Culter and Ederer,

1958 for the computational formula.

Median Residual Lifetime (MRL) Column (10)

An estimate ofthe time point at which the value ofthe

cumulative survival function is 0.50. That is, it is the

time point by which halfofthe pilots retiring at age 60

are expected to have died. Table 1 shows that this

point for our sample occurs during the 23-24 year

interval. Linear interpolation is used to calculate the

precise year value. So, halfofour sample retiring at age

60 is expected to live 23.81 years beyond retirement

age (after interpolation), i.e. to 83.81 years of age (60

+ 23.81). For those surviving the first year after

retirement a median life expectancy of 22.98 more

years was shown, to an age of 83.98 years old. For

those surviving two years after retirement, their median life expectancy was increased to 21.99 more years

or to an age of 83.99 years old. MRLs for surviving

beyond this point in our sample cannot be accurately

estimated because an insufficient percentage of retirees had died to compute reliable estimates.

It can be seen in Figure 5 that in the 1980 U.S.

white male population the survival probability curve

is entirely below the lower 95% confidence limit for

pilot survival. Therefore, the pilots in this sample live

significantly longer than U.S. white males. The median survival age for the retired pilots in this sample is

83.8 years. For the 60 year-old U.S. white male, the

median survival ages for the years 1980, 1985, and

1989 are 77.4, 78.1, and 79.0, respectively. In our

sample, the retired pilots have more than a 5 year

advantage of median life expectancy compared to the

60 year-old U.S. white male population.

DISCUSSION

The hypothesis of premature mortality among retired airline pilots compared to their counterparts in

the general population was not supported by the data

in this study. Retired pilots in this sample appeared to

enjoy a life expectancy of more than 5 years longer

than the 1980 U.S. general population ofwhite males.

However, before it can be concluded that this is true

for all retired airline pilots, the adequacy of this

sample to represent the population of retired airline

pilots should be determined. This sample represents

only one industry airline.

It could be argued that compared with other airline

pilots, this sample may have been subjected to higher

medical standards at the time of initial hiring and

monitored more closely throughout their careers. It

could be hypothesized that an even greater increase in

life expectancy should have been realized, but was not

because ofthe purported effects ofthe environmental

and personal stress factors associated with this occupation. This would, however, require much more

information than was provided in our sample ofdata.

A question concerning the adequacy ofour general

population sample could also be raised. Because our

pilot sample was anonymous, we could not match

personal characteristics (e.g., socio-economic status,

education, health consciousness, family history or specific health attributes) that could be influential in promoting longevity, to the general population we sampled.

Questions such as these are recommended for investigation and that a follow-up or updated survey ofAAL

pilots be conducted on a regular basis to track changes in

the median residual lifetime estimates of the surviving

pilot population. As the age ofthis sample matures, more

accurate life expectancies for each year following retirement will become available. If mortality dates in the

survival distribution prove to be earlier than projected

more precise epidemiological studies could be proposed

to assess the relationships of the potential stress factors

associated with this career.

A practical next step would be to conduct a more

exhaustive survey ofretired airline pilots with a sample

that would be more representative ofthe entire population. World-wide, there is a very high number of pilots

who have retired from major airlines. A follow-on study,

which would obtain a larger sample of these pilots and

contain data on causes of death and reasons for early

retirement, would certainly yield information to verify

and refine the results found in this study.
An anonymous and confidential program, which

would utilize the data bases on air crew members in

the current major U.S. airlines, should result in a

sample of greater than 10,000 retired pilots. By calling on the data bases in all departments ofthe airlines

(at least the flight, medical, personnel, and benefits

departments) the data on health history, causes of

death, and reasons for early retirements should be

available. The data needed for this type of survey

would not require personal identification or references, such as names, social security numbers, employee numbers, pilot's or drivers license numbers. A

wealth ofinformation from this type ofsurvey could

also yield a more definitive answer to the retired

pilots' longevity question.

CONCLUSIONS

The hypothesis that retired airline pilots die at

younger ages than their general population counterparts was not supported by this study. On the contrary, this study revealed a significantly longer life

expectancy for this 25-year sample of retired pilots

from American Airlines as compared to their 60 yearold counterparts in the 1980 U.S. general population

census of 60 year-old white males. The airline pilots'

median residual lifetime for this sample was greater

than five years longer than their counterparts in the

U.S. white male population. A more exhaustive survey

ofairline pilots including all ofthe major U.S. airlines

and international airlines is recommended.

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