DOT/FAA/AM-94/22 

Office of Aviation Medicine 

Washington, D.C. 20591 

94-34657 

... J\.ge 60 Study. Part Ill: 

Consolidated Database 

Experiments Final Report 

E.]. Kay 

D.J. Hillman 

D.T. Hyland 

R.S. Voros 

Lehigh University 

Bethlehem, Pennsylvania 

R.M. Harris 

].D. Deimler 

Hilton Svstems, Inc. 

Cherry Hill, New Jersey 

Civil Aeromedical Insrirute 

Federal Aviation Administration 

Oklahoma City, Oklahoma 73125 

Ocwber 1994 

Final Report 

This do:umem is avaiiable to the public 

through the Na:ional Technica1lnformarion 

S"rvice. Springfield. Virginia 22l6L 

Federal Aviation 

A-a ministration 

.. @ • 
NOTICE 

Thr, d.><:umem i' dr,-emmat~d undc; rhc 'l'<m'-Oghip of 

the t".'\. Dcparrmcm of Tr.m<.pnr!.Jlwr. m the inrcrc" of 

on forma non cx.:hange. The l' nued Star<·' t_;o\"~rnmcm 

a.,sumt"' no itdbiiltx t()r rh<:" content.., 0r u~c rherc-ot-_ 
11. -No I DOT/F~A/AM-94/22 

12 Govemme<>• Accessoon No 

' ... iiMB and $Ubmle 

Age 60 Rule Research, Part 

!Database Experi~ents Final 

I 

III: 

Report 

~ ~Dc:::rte 

Consoli :.!a ted. .:>=~abe!" 1994 b """'W Ogo:uzcv ~"""' 

I

! ~~ay, Ph.D., R.M. Harris. R.S. Voros. 

D.J. Hillman. Ph.D .. D.T. Hylar.d, Ph.D .. 

I ~ ~-~O..,..,...ro!._( ~OCif~< 

~ 8025-3C!R2: 

I

'J.!l. Deimler 

: Q Pl&lb '• '0 QagcsCXAV ~ ::ro ~ 

j Hil!:o~ Systems~ :nc. 

i ~SC North Kings Highway Suite 2 G2 ! Cherr"i Hill. New Jersey 08034 1 ~~FAG2-9:-c-?:!25 

~j ; ·;; ~~~~~~~~~--------------------~~~~~~~~~----~ Soo«.wQ~"'C""W!'!rd~ ·~ ·~~~'7""C'~:-.-.;a~ 

JOffice of Aviation Medic~ne I :~~:~~:;~~ ~~~~~t~~~~on l Washing!: on. D.C. 20591 ' - \ C5 4<Jir ..... - 1 

fThis document is on~ of four products completed as a part of the Age 60 Rule i 

! research contract monitored b-i' Pam Della Rocco. C:i'\til Aeromedical :nstitute, i 

i Contracting Officer· s Tect"..nical Represe-ntative. This work was performed ll, l under Task AM-A-91-HRR-::.38. 

t;o~ f 

!This report was a primary deliverable fro~ the research contract with Hilton! l Systems, !nc. on the FAA· s mandatory retirement for pilots operating under I 

1 Federal Aviation Regulations Part 121, the ·Age 60 Rule. • The purpose of 

1 this study was to examine existing data to assess the relationship between 

'I pilot age. accident rate, and experience. Three existing data bases were 

integrated nn a single computer platform: 1) the FAA Airmen Certificatior. 

l file, 2l the FAA Medical Histor-.1 file, and 3) the National Transportation l

Safety Board (NTSBl Accident data base. The report presents a discussion of 

. the methodological issues with studies in aging and reviews prior research. 

l Limitations of utilizing these data sets are discussed. The methodological 

lapproach was developed from these considerations. Hilton Systems replicated 

!land extended analyses from previous studies, including statistical ~~alyses. 

The report describes outcomes from analyses conducted to ~~swer a series o:: 

I questions examining the relationship between age <u"!d accident rates for 

pilots holding Class I, Class II and Class III medical certificates. Rec~t 

and total flight time are utilized as a measure of risk exposure. The 

I results present a converging body of evidence which fail to support a 1 

~h}~thesis that accident rates increase at or about the age of 60 years. 

l 

17 CavWcnS 

1

1

. ?ilot Age Accident Rates 

Age GO Rule 

jKandatory Pilot Retirement 

1 

1

18. Dis!rlbut;on Stotameot 

Docume_~t is available to the public 

I through the National Tec~..,_ical 

I Information Service, Springfield, 

Virginia, 22161 

l l :10 5ecurOy C>:::s!". (o! lttis page) j 21 No. of Pages 22. PC.ce I 

~---=~Un~c~l~as=s~1~·=f~i~ed~----~~----~~U~n~c~l~~=s==s=i=f~i~ed~~~--~~--~~~9~9~----~~--------------J~ FcMn DOt F lT<Il.7 (!-72) ~ o! completed PO;le auliY.lr2ed 
ACKNOWLEDGMENTS 

This r=rdt was supported by the FAA Civil Aeromc:dical Institute (CAM!) in Oklahoma City, 

Olclaitom2, under contract number DTFA-02-90-90125. 

The authors acknowiedge a number of individuals for their assistance during this research. We thank 

the Project's Panel of Scientific Experts for assistance a.<d advice during the entire course of rhis work: 

Susan Baker, Johns Hopkins University 

Donald Campbell, Ph.D., Lehigh University 

James Danaher, National Transportation Safety Board 

Russell Raymond, M.D., Aerospace Medical Assoctation 

Ilene Siegler, Ph.D., Duke University 

Martha Williams, Ph.D .• University of Illinois 

From CAM!, for guidance, particularly in the early stages of rhe project when dqcloping the research 

strategy, we thank: 

Mac Mclean, Ph.D. 

Carol Manning, Ph.D. 

Steve Veronneau, M.D. 

We thank the following individuals from Lehigh University: 

Dean Nelson for providing assistance in statistical design and analysis 

Tom Smull for his expertise in COBOL prilgl'2mming 

Steve Corbcsero for his assistance with computer system administl'2tion . 

Finally, and foremost, the authors thank the CAMI contract monitor, 

Pam Della Rocco 

for invaluable guidance, assistance, and understanding throughout the duration of the project. 

Ill 

Acces!on For 

NTIS CRA&l 

OTIC TAB 

Unannounced D 

I "s~ . .c,...,~-~-·on L.: \•' ,,_-;;:; u ---- ------

I ! Ava·. :..;·~ ... ~.'or 1 I Dist ! S,. c::d 

I !l-1 I 

~-
PRE~ ACE 

This technical report, entit!ed "Age 60 Rule Research, Part Ill: 

Consolidated Database Experiments Final Report," is the third document in the 

series of products from Hilton Systems resulting from a two year contract to 

scientifically examine issues related to the Federal Aviation Administration's 

(FAA's) mandatory retirement regulations for pilots. The first report, entitied "Age 

60 Rule Research, Part 1: Bibliographic Database," was published as an Office 

of Aviation Medicine Technical Report (DOT/FAA/AM-94/20). The second report 

was published as "Age 60 Rule Research, Part II: Airline Pilot Age and 

Performance-A Review of the Scientific Literature" (DOT/FAA/AM-94/21). 

The Federal Aviation Regulations (FARs), Part 121, prohibit individuals 

from serving as captain or copilot (1st officer) of an aircraft in air carrier 

operaOOfls if those persons have reached their 60th birthday. Commonly 

referred to as the "Age 60 Rule", the regulation was implemented in response to 

concerns about the safety of aging pilots as the airline industry transitioned into 

the jet age. Although the rule has withstood legal and legislative challenges, 

little scientific evidence has been available to either support the rule or to guide 

the FAA to an appropriate alternative. 

In ~990. the FAA's Associate Administrator for Certification and 

Regulation (AVR-1), Mr. Anthony BroderiCk, requested and sponsored a two 

year research contract to examine the relationship between age. experience, 

and acciclent rates. The Civil Aeromedical Institute {CAMI} was assigned the 

task of developing and monitoring the cootract. In September 1990, the contract 

was awarded to Hilton Systems Inc., of Cherry Hill, New Jersey. Hilton Systems 

collaborated with Lehigh University faculty to supplement technical exps:tise. 

The FAA requested that the contractor engage in a fresh, innovatr·e approach to 

the issues involved in the Age 60 Rule. No direction was given by the FAA to 

the contractor on whether the Agency desired to maintain a position either for or 

against the rule. 

This report was a major focus of the research project. Since 1983, a 

primary source of the defenSE; of the Age 60 Rule was a study by Richard 

Golaszewski entitled "The Influence of Total Flight Time, Recent Flight Time and 

Age on Pilot Accident Rates.• The purpose of ~his phase of the contract was to 

replicate and extend the analyses conducted in the Golaszewski study, resolving 

methodological problems in the process. To accomplish this, Hilton systems 

i!ltegrated three existing data sources on a single computer platform: 1) the FAA 

Airmen Certification file, 2) the FAA Medical Hi.,~tory file, and 3) the National 

Transportation Safety Board (NTSB) Accident data base. The integrated data, 

ths Consolidated Data Base (CDB}, was a major project deliverable and survives 

the contract as a significant research tool. The COB currently resides in the CivU 

Aeromedical Institute's (CAM!} Accident Investigation Research Section (AAM610). 

v 
The data in this report represent merely a selection from the myriad 

analyses conducted by Hilton Systems to address the Age 60 issues. !n total, 

approximately 181 separate models of pilot age, accidents and flight time were 

examined by Hilton ln the course of preparation of this report. The analyses 

whioh Hilton and Lehigh felt most directly addressed the Age 60 Rule for Part 

121 pilots are presented here. 

Pamela Della Rocco, COTR 

Hllt:!n Systems, Inc. and Lehigi'l University Personnel 

Mr. Albert za1cman. Program Manager 

Mr. Jim Oe\mler. Principal E~ineer 

Dr. Donald Hillman, Chairman of the Computer 

Science and Electrical Engineering Department {CSEE) 

Dr. Edwin Kay, Faculty member .Jf CSEE Dep.;:<tment 

Dr. Diane Hyland. Ditector of the Center for Social 

Research, lehigh University 

Mr. Nelson Brown. ret. Eastern Airlines pilot 

Ms. Julie Chambliss, Hilton Systems 

M$. R~~ Hams. H\1\oo SysterM. 

Mr. Robert Voros. Lehigh Univers.'ty 

Members of Scientific Group of Experts 

Susan Baker, M.P.H .• The Johns Hopkins University 

Donald Campbell. Ph.D .• Lehigh University 

James Danaher, Na\lonal \ransponatron 

Safety Board 

Russell Raymond. M.D., Aerospace Medical 

Association 

Ilene Siegler, Ph.D .• Duke University; 

Garnett "Mac" Maclean, Ph.D. 

Carol Manning, Ph.D. 

Steve Veronneau. M.D. 

Henry Mertens, Ph.D. 

Mr. A.E. Dillard, National Resource Specialist, 

Simulator Engir.eering 

Mr. Anthony Broderick (AVR-~} 

lJr. Jon Jordan, Federal A1• Surgeon (AAM-1) 
TABLE OF CO!".'TENTS 

SECTION PAGE 

1. 0 INTRODUCI10N .................................•.................................... 1-1 

1.1 Background ..................................................................... 1-1 

1.2 Objectives ..................................•.................................... 1-2 

1.3 Constraints .................................................•.................... 1-2 

1.3.1 Methodological Problems in Studies of Aging ................... 1-3 

1.3.2 Difficulties Calculating Accidc:nt Rates •••••.••.•...•.............. 1-5 

1 .. 4 A-pprctaeh ...................................................... ................... 1-9 

l.S Document Overview ..••••••••••••.•.•••.•.•.•••.•.•.•..•.•.•........•....•... 1-10 

2.0 PRIOR RESEARCH ................................................................... 2-1 

2.1 1983 Golaszewski Analysis ······••·•·•·••·· ········ ··············· ......... 2-1 

2.1.1 Drawbacks to Golaszewski's Methodology ..•.................... 2-2 

2.2 1990 Office of Technology Assessment Analysis ....•...............•.... 2-3 

2.3 1991 Guide and Gibson Analysis .......•.....•••......••.................... 2-4 

2.4 1991 Mortimer Analysis ••••••••••••••.••••••••••..•••. _ .•.•.••.••••••••.••••• 2-4 

3.() C:O~I.II>A1ri:I> DATA~~ .................................................... ;)-! 

3.1 FAA and NTSB Historic Databases ......................................... :)-1 

3.1.1 FAA Comprehensive Airman Information System (CAlS) ..... 3-1 

3.1.2 NTSB Accident Records Database ................................. 3-2 

3.2 CD~ l)atabase Statistics ...................................................... 3-2 

3.3 CD~ Organization ...•••.••...•.•••.••....••.••..•........••.•.•..•...•.•....•. 3-4 

3.4 CD~ Utilization ................................................................ :)-7 

3.4.1 Selection Criteria ................................•.................... ;)-? 

3.4.2 Accident Rate caiculation Pro::edure .............................. :)-7 

3.4.3 Data Limitations .................•...••.•............................. ;)-!() 

4.0 ~()~I.()(J~ ··························--···················-·····················"-1 

4.1 Plan of Analysis .....•.•..............•.•••............•..••............. "' .... "-1 

4.1.1 Accjdent Rate as a Function of Age ................................ 4-l 

4.1.2 Longitudinal View of Accident Rate ...•••..•..•.•••.••.....•••..•. "-2 

4.1.3 Accident Frequency as a Function of Age ........................ "-2 

4.1.4 Subsidiary Analyses ............••.•..........•...•••................. 4-3 

4.2 Assumplions of the Statistics ................................................. 4-3 

4.3 The Statistical Approach ...................................................... "-3 

4.4 Iustificatioo of the Use of Statistics ......................................... 4-4 

Vll 
TABLE OF CONTENTS 

SECTION PAGE 

5.() ~~~ ••••••••••••••••••••••••••••••~••••••••••••••o•••••••••••••••••••••••••••••••••S-1 

5.1 Age and Accident R.ate ........................................................ 5-1 

5.1.1 Did Accident Rates of Class I Pilots Change with Age? •.•.•... 5-1 

5.1.2 What Was the Relationship Between Age and Recent 

Fljght Time for Class I Pilots? ...................................... 5-2 

5.1.3 How Did Accident Rate Change with Age for Pilots with 

Relalively High Recent Flight Time? •••••••••••••••••••••••.•••••• S-3 

5.1.4 What Was the Relationship Between Age and Recent 

Fli&ht Tune for Class n Pilots? ••••••.•••..•••••...•..•.•.•......... 5-7 

5.1.5 What Was the RelatiOI!SbiP Between Age and R=t 

Flight Tune for Class m Piloa? ••••••.•............................ 5-8 

5.2 Longitudinal Vu:w of Accident Rates •••••••••••••••••••.••••.••••••••••.... 5-11 

!S.2.1 Could the Accident Rates of Pilots in the Same BirthCohort Be Examined Over Tune? .................................. 5-11 

5.2.2 What Did a Quasi-I.cngitudinal Analysis of Class I Pilots 

Show? •••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••• 5-12 

5.2.3 What Did a Quasi-Longitudinal Analysis of Class m 

Pilots Show? ••••••••••••••••••••••••••••••••••••••••••••••••••••••••••• 5-14 

5.3 Analyses of Accident F1equeucies .......................................... 5-16 

5.3.1 Chi-Squaze ADalyses •••••••••.•••••••••••••••.•..•••.•.•.•......•.••• 5-17 

5.3.2 Analyses of Variance (ANOVA) ................................... S-19 

5.4 Limitlticm Placed Oil the Anal152=S ty the Data .••••••••••••••••.•.••.••• 5-20 

5.4.1 What Were the Cwlges in Membership Associateri with 

~? .................•.................................................. :i-20 

5.4.2 What w~ the Difficulties in EsliJnatin& Exposure? ............ 5-23 

6.0 SUMMARY A.l\ID DISCUSSION •.•.•....•........•••.....•....•.•..•.............. 6-1 

6.1 ConclusiMs Based Upoa F1ipt Tune Analyses •.••••••••••••••••••••••••• 6-1 

6.2 Conclusions Based Upon the Quasi-I.oagitudinal A!lalyses ..•.••••.•... 6-1 

6.3 Conclusion! Relevant to the Age 60 i. 1le •••••••••••••••••••••.•••••••••••• 6-1 

REFERENCES 

APPENDICES 

A. Comparison of Golaszev.-sti Stuc:ly a.'Mi A&e 60 Study 

B. Data!m: Queries 

V!ll 
LIST OF 'fABLES 

TABLE PAGE 

1-1 Number of Accidents in NTSB Database ........................................... 1-7 

1-2 Number of Pilots in NfSB Database by Medical Certificate ....•............... 1-8 

1-3 Number of Accidents (1976 - 1988) by Medical Class .......................... 1-8 

1-4 Number of Accidents (1976- 1988) for Pilots 

Aged 61-84 ............................................................................ 1-9 

3-1 Comparison of Records in CDB and FAA Statistical Handbook •.........•..... 3-3 

3-2 Medical Certificates in CDB for 1986, by Month ................................ 3-4 

3-3 CDB Records by Soun:e Database ................................................... 3-4 

3-4 Encoding Schemes in Various Databases ...........••....•......................... 3-7 

3-5 Number of Medical Records Used in CDB Experiments, by Year .............. 3-8 

3-6 Number of Accident Records Used in CDB Experiment, by Year .............. 3-9 

3-7 Annualization Factors Used for Determining Annual Flight Hours ............. 3-9 

3-8 Day and Night Landings from Accident Database ••••••.•••.••.••.•.•.....•.••.•.• 3-10 

5-1 Percent of Class I Pilots with Medical Waivers Involved in Accidents .•..•... .S-18 

5-2 Medical Waivers as a Function of Age ...•..................•........•.......•.•...• 5-18 

5-3 Total Flight HO'.rrs in Same Type of Aircraft ..................................... .5-19 

5-4 Recent Flight Hours in Same Type of Aircraft. .................................... 5-20 

' 

lX 
LIST OF FIGURES 

FIGLTRE PAGE 

1-1 Number of Accidents in NTSB Database • . . .. . . . . . . . •. . . .. . . . . . . . . . . .............. 1-5 

3-1 illustration of CDB Linkage by Pilot Certificate Number ..•..................... 3-6 

5-l Accident Rates as a Function of Age, Class I p;Jots .......•..•................... 5-2 

5-2 Accident Rate as a Function c-f Age and RFr, Class I Pilots .................... S-3 

5-3 Accident Rates as a Function of Age, Class I Pilots with > 250 hrs RFT ... .5-4 

5-4 Pilot Count as a Function of Age .....•............................................. . 5-5 

5-5 Accident Rates as a Function c: Age, Class I Pilots, > 2000 hrs TFr, 

> 700 hrs RFr ......................................................................... 5-6 

5-6 Accident Rates as a Function of Age, Class I Pilots, > 2000 hrs TFf, 

> 700 hrs RFT, with A TP ••.........•............................................... 5-7 

5-7 Accident Rates as a Function of Age. Class ll Pilots ............................. 5-8 

5-8 Accident Rates as a Function of Age, Class ill pi Jots ............................ 5-9 

5-9 Accident Rates for Class ill Pilots with > 500 hrs TFT, > 50 hrs RFT •.••• 5-l 0 

5-10 Acciden~ Rates for Class ill Pilots, Ages 50-69, > 500 h..-s TFf, > 50 

hrs RFI' ...................•...•.................................•....................... 5-I 1 

5-11 Accident Rates for Class I Pilots with > 2000 hrs TFf, > 700 hrs 

RFT, by Year of Birth ................................................................. 5-13 

5-12 Accident Rates for Class I Pilot>, by Year of Birth, 5 Year Coho:::rs ........... 5 -14 

5-13 Accident Rates for Class ill Pilots with > 500 hrs TFr, > 50 hrs RFr, 

by Year of birth ........................................................................ 5-15 

5-14 Accident Rates for Class ill Pilots by Year of Bin.~. 5 Year Cohorts .......... S-16 

5-iS Pilot Retention Count, Ciass I Pilots ............................................... .5-21 

5-16 Pilot Retention as a Function of Year. Class I Pilots, Age 26-30 ............... 5-22 

5-17 Pilot Ret'!Iltion as a Functbn of Year, Class I Pilots, Age 46-50 ............... 5-23 

X 
1.0 INTRODUCTION 

J..l Background 

Part 121 of the Federal Aviation Regulations (121.383c) contains a 

provision for mandatorj retirement at age 60 of commercial airline pilots-in-comma11d 

and co-pilots. The Age fiJ rule was established in 1959 with the objective of reducing 

aircraft accidents attributable to the effects of pilot aging. The rationale behind the rule 

was that the increased speeds and passenger loads of ccmmercial airliners placed 

greater demands on pilots with respect to their physi~ fitness and piloting skills. In 

addition, existing stadies reinforced a belief that p1ogressive deterioration of 

physiological and psychological functions regu:arly accompanied increasing age. Other 

studies raised the concern that sudaen incapacitation could be brought on by such 

events as heart attacks or strokes, which occur with greater frequency among older 

members of the general population. Although not all individuals experience equivalent 

age-related deterioration in health and performance, it was nevertheless concluded tllltt 

an age 60 limitation was prudent on the grounds that performance decrements could not 

be reliably and objectively measured or predicted on an individual piiot basis. 

In 1979, the U.S. Congress enacted P.L. 96-171, an Act to requ!re a study 

of the desirability of mandatory age retirement for certain pilots and for other purposes. 

The legislation required the Director of the National Institutl • of Health, in 

consultation with the Secretary of Transportation, to conduct a study to determine tho: 

effect of aging on the ability of individuals to perform the duties of pilots with the 

highest level of safety. The National Institute on Aging was assigned the ~nimary 

responsibility for implementing t.IJe legislation and formed an inter-institute committee 

to prepare the federally-mandated repor~ The committee decided in favor of a"\\--a..T"ding 

a contract to the Institute of Medicine {IOM) of the Naticnal Acaden.y of Sciences to 

provide an objective exarninati.on, SUiru:lai)', and "Ssessment _ of existing scie:.'ltii'ic 

knowledge relevant to the questions posed in P.L. 96-lil. 

The National lnst'tute en Aging established a Panel on the Experienced 

Pilots Study in 1981 to assist in reviewing the IOM report (Institute of Medici11e, 

1981). The pat::! held three public meetings to receive conments on the IOM report 

and to hear oral statements from s...--veral organizations. The panel was unable to 

identify a medical or performance assessment system that could deterrnine which pilots 

would pose a safety hazard because of early or impending deterioration in health or 

performance. It recommended that the Age 60 ruk . -; retainerl, while at the same time 

recommending that a systematic collection of medical and pe.rfor.nailce data be carried 

out for future consideration of the Age 60 rule. This recomrnendatic:t formed the ~s 

for this project. 

1-1 
In 1990, Hilton Systems, Inc. (HSI) b:;,<>an a two-year contract to provide 

support to the Civil Aeromedical Institute (CA.W) of the FAA for studi~ of existing 

data contai .t!ed in several databases concerning aging and pilot perfonnance. This 

project included an exhaustive review of the scientific literature (Hyland, Kay, 

Deimler, & Gurman, 1992). A principal g::la1 of the project w-nS to develop a 

Consolidated Database (CD:B) from sever..! pertinent FAA and !'.'TSB dat~ases in 

order to facilitate analyses that o.-plore relationships between age and pe.rfonP.a::ce and 

identify potential age-sensitive contribut!ng factors. The CDB was designed to identify 

and incorporate relevant pilot, medical, and accident data currently stored L?J several 

dissimilar data files into a structured, organized form capable of s;:ppc;rting rigorous 

data analysis. 

1.2 Cfujedives 

The purpose of this study was to conduct statistical analysis on historical 

data to investigate the relationship between pilot age and accident rates. Tile ultimate 

long-tenn aim of the Age 60 Project was to enhance aviation safety by increasing 

understanding about the relationships among pilot age, experi..:nce, a..-1d accident rates. 

The specific aims ci the project were: 

• To consolidate t.'le currently separate rla:ahases related to pilot 

certificati•m and aviation accidents and incidents. 

• To use this consolidated database to S!atistically examine the 

relationships that exist ll..'llong chronulogical age, accidents, and other 

factors. 

Although ~ study was primarily directed at pilots who fly for FAR Part 

121 air carriers who are subject to the Age 50 Rule, additioruil a!'.alyses were conducted 

for other categories of pilots it:! take adv-antage of ad-.itiw...al data available for <ietive 

pilOts beyond t'le age of 60, and to further exar..ine the influence of confoundmg 

factors. 

1.3 Constraints 

The conclusions ~at could be IL-avtn a_hout fue relationships among 

chronological age and accident rates were constlai.."1ed by the kinds of data in the 

existing databases. It is h'DpO!la.llt to keep i'l mine !!'.at tl:.ere wcre a number of fac:ot--=.: 

confounded with age, factors that would have ac"fec-.ed the ~ults in the s<udy. The 

information contained in t.~e databases did nor allow us to untangle the confoU!",ding 

effects of all of those factors. Tnis section '~'<ill n:vi~w some of t.~e consl:r'alnts that 

were consi-dered in e."al.uating the met.'1C'ds and ~ults of this study. 
1.3.1 Metho:-.io1oe:ca1 Problems in Studies of Amii 

Advancing age is a•sociated with declines in physiological functioning wd 

w increase in the prevalence of disorders. However, it was import2nt to recog>"J7e at 

the outset that individuals vary considerabiy i11 their mes of physiological aging ;md m 

their predisposition to disease. While average levels of functiomng would decrease 

with inC'leasing age, individual variabiLity appea.."'ed to increase. Thus, group averages 

could be particularly poor preilictors of individual performance among older persons. 

Despite these problems in using chronological age as a meacingful marker 

of an individual's functi!Jlling, it v.;as still importl?.llt to i.;westig-..te the relationship 

between increasing age and functioning, at least in terms of grot.'P patterns. However, 

the design of studies on aging presented difficult problems of interpretation. Crosssectional sn·.dies compared (at a single point in time) groups of individuals tl"l:l.t varied 

in age, rather than repeatedly testing t!1e same group of individuals as they aged (a 

longitudinal design). It should be noted that cross-sectional and longitudinal st":ldies did 

not always suggest the same age effects, even when using dala from the same 

population over the same time period. There were interpretation difficulties with ooth 

of those simple research designs. 

Cross-sectional data were di.•fi.cult to interpret because ocr society changes 

so zapidly that individuals born at different times {diffa..rent bi."ih cohor".s) can 

experience very different life cLTCumstances. Tnus, in a cross-sectional study, the 

different age groups can vary on a number ~f dimensions besides age (such as health, 

education, and J.L;;~ experiences). Differences in t.!Je behavior of these groups could 

reflect cohort effects which were difficult if not impossible to sepa..."'ate from aging 

effects. 

In this study, older pilots could differ in significant v.'2.ys from younger 

pilots in ways that were unrelated to the aging process. For example, oider air carrier 

pilots could .have differing educational backgrounds and employment experien= (such. 

as military flying experience) t.!Jan younger pilots. Older pilots also had mor-2 seniority 

than younger pilots and could select routes with substwtially different levels of 

exposure to risk. For example, the number of takeoffs and landings per f!.ight hour 

could decrease with age, as older pilots could use their seniority to c.ltoose longer routes 

with terminal operations confined to major metropolitw airports. Tnis would result in 

fewer takeoffs and landi:1gs per hour of flight. argnab1y a lower risk envh-unment. 

Unfortu!'.ately, the information contained in the existing databases did not allow 

examination of this potential confounding factor because pilots reported only hours 

flown for various periods of time, not the number of landings. One way to minimize 

this con.found was to exa:ni.ne data for Pa..Tt 91 general aviation pilots who did not 

o;eate in the framework of seniority rules. 

1-3 
Since longitudinal studies followed the same individuals over time. they 

avoided the confou!lding of cohort and aging ef'fects tllat v;a.s found in cross-sectional 

studies. Tha£ type of study "'as extremely valuable because it permitted the direct 

examination of changes in individuals as they aged. However, the results of 

longitudinal studies were difficult to interpret for at least two reasons. 

Since iongitu61nal srodi.es Iequi:red many years to comp'lere, signifitam 

numbers of subjects could drop out of the study. This experimental mortality of 

subjeci£ may not have been random, but rather biased in that those subjects v.ith lower 

levels of performance may have been more likely to drop out. Thus, lliterpretation of 

the results of longitudinal studies v.'3.S difficult because aging effects could have been 

confounded with experimental mortality effects. For example, in the study's context it 

was likely that the FA.t\'s rigorous medical and operational performance standards 

~ 'iYUt, GVe> time, ';il'3'& w,cre. likcl] tc be m azcide\'0.~. 

The results of longitudinal studies we."e also difficult to interpret because of 

the confounding of age effects and time-of-measurement effects. Si11ce longitudinal 

studio were carried out over long periods of time, not only were individuals aging but 

the environmental context in which they were developing was also changh>g. For 

example, the context in which air carrier pilots performed had changed significantly 

O"vl:r ·.r.e past ~.~er& ~ m ie= ~f the ~ !IDwn 2liD •,he flying 1:-'il'>"'.ronmen\ 

itself. If a group of pilots had different accident rates in 1960 when they were 30 years 

old compared to 1990 when they where 60 years old, it could be due to changes in the 

flyi.'"lg environment as well as 3eoing-related changes in the pilots themselves. For 

example, as Figure 1-1 illustrates, an overall decline in counts of accidents "-'35 seen in 

the .{X!riod 1976-1988 (as discussed in Section 3, the data for the year 1986 v;as !lot 

used in this study). 
.,_iT _ __.--.. 

lJiet 

l.M t L.-+ 

11.010 + 

1!.510 t 

:1 

o+---~---+--~~--+---~--------~--+---~--~--~ 

1976 1977 1971: 1979 lSleC !!Ill 1912 l9D !9U l9IS 191'7 1911 

AocOioo<Y ... 

Fiprel-L Number of accidents roc:orded in the NTSB datwbase for tbe years 

1976-1988. 

Ideally, what was needed to fully re-evaluate the Age 60 Rule was data from 

several cohorts of Part 121 pilots who had been monitored over time, including data on 

pilots over age 60. Then both cross-sectional and longitudinal comparisons could be 

made of accident rates of pilots over age 60 a.TJd under age 60. Hov."t;-.er, the data that 

would have provided this direct comparison were simply not available in the database, 

primarily because airline pilots had been retired at age 60 since 1959- :E.xamh"lation of 

pilots who were not subject to the Age 60 Rule, such as Part 91 general a>iation pilots, 

could have provided an alternate way to examine the relationsl:rip between chronological 

age and accident rates. However, as the next section will detail, the ability to examine 

specific groups of pilots S'Jch as Part 121 professional pilots versus Part 91 general 

aviation pilots was constrained by limitations inherent in the databases. 

1.3.2 Difficu1ties <;a!culatin~: Accident Rates 

To examine whether accident rate i.11creased v.ith age, it V.'as oecessarv to 

calculate the accident rate as the ratio of t.'te number of accidents to the overall. number 

of hours flown (an estimate of exposure) for Yarious age groups and then to compa..-e 

those accident rates. Also, since there were significant qualitative diffe::ences i..t'l type 

of flying that Part 121 air carrier pilots, Part 135 commuter/air taxi pilots, and Part 91 

general aviation pilots engaged in, it would have been ideal to calculate sepa.Tate 

acciden• Iatios for each of thes<: categories of fl:ing. 

1-5 
For example, ro ~ the question wbetber Part 121 accident rates 

diffemi u a fwetion of pi..klt a&e. it was necess:ry tc identify Part 121 accidents and to 

get a good ~ of tile aposure of pi~ to those accidents. However, the 

infoo;matioo cmlained in ~ ~ woukl not directly wpport those types of 

anai)'3CS. 

While the acciiient darabps:s included information about the numbers of Pan 

121, Part 135, ~Part 91 JCCident.s for pilots of different ages, there was no way to 

directly cab~ exposure mes fur those pilot$. Precise exposure rates would r.ave 

bten !.asc:l oo the number of Part 121, Part 135, and Part 91 hours flown by pilots of 

diffaeut agu. Since the data for awnber of hours flown bad tc be based on all pilots, 

not just pilots ~ had b:en in accidents, thole data were poo=ttially available OPJy in 

the FAA Comprebensi'>-e Airmal; Information System (CAIS) medical da!abase, and 

were not available from the NTSB accident database. 

Unfortunaldy, the CAIS medical database only included m::ent (over the 

past six months) and tolal flight time broken down by the medical class certificate of 

the pilot, not by the type of flying (i.e., Part 121, Pan 135, or Part 91). A Class I 

medical cenifk:ate bad to be renewed every six months and was required of all air 

tr:ansport pilots (ATP); a Class n certificate had to be renewed yearly and was required 

of all COJ:UDerCial pilots; a Class m medical certificate had to be renewed every 2 years 

and was~ of aJ:, private and student pilots. However, while there was £Orne 

relationship betwt:en class of medical certificate a.'Mi type of flying, it was by no mea."IS 

a perfect fit. 

For exampJe. to be certified as a Pa.rt 12i !TJot-in-commmd, a pilot had to 

initially and periodically demonstrate proficiency in flying the ai=aft, posses:; a!:t A TP 

pilot certificate and a Iating for the specific aircraft to be flown, and possess a Class I 

medical =rtificate, obtainable by passing a semi-annual medical examination. Thus, 

all Part 121 hours were accumulated by pilots with a Class I medical certificate, but the 

Ieverse was not true. Not all hours reported by pilots with Class I medical certificates 

rep.tesa:tted Part 121 flying. As Table 1-1 illustrates, only 3.38 percent of all accidentli 

between 1983 and 1988 where the pilot in com•-n.and had a Class ! medical certificates 

involvec! Part 121 flights. L"l fact, the majority of accidents for Class I pilots (72 

percent) were Part 91 flights. 

1-6 
Type of 

Flvin2 

121 

135 

91 

Qlber"l 

Tota! 

Nwuba of • · ' aU!Oided m die NTSB ' • '·• for tbe years 

1983-1911•. f a:'ina of type offi7Ut& (Pat 121, 135, and 91) and 

r " cati~ dMa.. Pet d , •• ;. Iii •te dae perccutage of the 

toe.! DUiilba of" -· wittlin • ....,jjal certification class. 

Caul Class II Class III 

Accident Accident Accident 

Count Percent Count Percent Count Pet cent 

57 3.36 l 0.02 0 0.00 

351 20.72 273 6.23 0 0.00 

1,211 71.49 3,277 74.7?1 4,981 99.64, 

75 4.43 832 18.98; 18 0.36 

1,694 4,383 ~999 

There were many pilots holding a Class I medical certificate who did no: fly 

air transport. For example, an air taxi service may have requi.~ its pilots to have a 

Class I medical certificate, even though FAA regulations allowed a pilot V>i.th a Cl.ass II 

certificate to fly an air taxi. Also note that a pilot may have had to use an out-of-date 

certificate in place of one from a lower class, provided the certificate was not out-ofdate for the lower class. Thus a Class I medical certificate (good for 6 months) was, in 

effect, a Class II certificate for a year or a Class III certificate for 2 years. As Table 1-

2 illusttates, the distribution of pilot certificateS for those who had acciden~ varied 

greatly by medical certification. The number of Class I pilots v.rith A TP and 

Commercial certificates was about the same while the majority of Class III pilots had 

private certificates. 

Under t:ertain conditions it may have been possible to identify Class I pilots 

who were flying under Part 121. For example, the CAIS medical database included 

information about the pilot's employer, the pilot's joo, and the kind of flying (soiely 

business, solely pleasure, or both). Restricting analyses to Liese Class I pilots who 

worked as pilots for scheduled airlines, who did not fly for pleasure alone, and who 

had fioV>'ll a substantial number of hours withi..'l the last year, could have provided 

better estimates of accident rate for pilots most likely to be flying under Part 121. 

1-7 
Table 1-1. 

. 

Number of pilots recorded in the NTSB d•..,se for the years 1976-

1988 as a functi011 of type of certifu:ale held by !be pilot {ATP, 

Commercial, de.) md medical ~011 class. Percentages 

indicate the pen:eutage of !be total llU!ilber of pilots within a medical 

certification class • 

Class I Classll Class ill 

Pilot Pilot Pilot 

Pilot Certificates Count Pe1cent Count Pel cent Count Percent 

ATP 2,328 38. 7ti 810 4.7(] 43 0.27 

Commerci.al 2,553 42.51 11,196 68.46 824 5.25 

Private 270 4.5(J 3,214 18.65 ll,T.:.4 74.82 

Student 75 1.2'i 203 1.18 2,987 19.05 

Other"2 780 12.99 1207 7.01 95 0.61 

Total 6006 17 230 15,683 

Since the Age 60 Rule applied to Part 121 pilots, it may have been ideal to 

focus on age differences in the accident rates of this group of pilots. However, in 

addition to the difficulties estimating exposure rates for Part 121 pilots described 

above, there were two other factors t.iat constrained the types of analyses that could be 

done on that group of pilots. First, Part 121 accidents were so infrequent that the data 

could have been too sparse to allow for valid statistical inferences. Second, because of 

the Age 60 Rule itself, there were no comparable data on accident rates for Part 121 

pilots under and over age 60. As a comparison of Tables 1-3 and 1-4 illusttates, the 

distribution of accidents by type of flying underwent a dr.unatic change for Class I 

pilots at age 60. Those problems could be partially addressed by analyzing other 

grotJps of pilots. 

Tallie 1-3. 

Type of 

Flving 

121 l 135 

91 

Other"1 

Total 

Nuwbe.t of li<>Cidents tecotded in the NTSB "'"'bas- for lbe years 

1976-1988 by pilots aged 20 to 60 as a functioD of type of flying (Part 

121, 13S. and 91) md medical certification class. P=l!ntages 

indicate lbe pen:eatage of the total number of accidents within a 

1lledicd certificatioo class. 

Class I Class I1 Class III 

Accident Accident Accident 

Count Percent I Count Perce!lt Count Percent 

57 3.451 1 0.02 0 0.00 

348 21.()91 264 6.49 0 0.00 

1,170 70.91 2,996 73.70 4,531 99.60 

75 4.55! 804 19.78 18 0.40 

1,650 i 4,065 4,549 

1-8 
Table 1-4. 

T}-peof 

Flying 

121 

135 

91 

Other" I 

Total 

Number of aeeideats reconlo>d in the NTSB clmbase for the years 

1976-1!188 by ptlotsapd 6110 84 u a limctioa of type of flying (Part 

121, 135, llllld 91) ad medicd certificalioa clas. Percentages 

iDdicalc the perceaqge uf the total number of aeeideats within a 

mediee eertifica!ioa c1us. 

ClaSS I Class li C!assill 

Accident Accident Accident 

Count Percent Count Pera:nt Count Perce'lt 

0 0.00; 0 0.00 0 0.00 

3 6.82 9 2.83 0 0.00 

41 93.18 281 88.36 450 100.00 

0 0.00 28 8.81 0 0.00 

44 318 450 

For example, analyses could have focused on Class ID pilots and Part 91 

accidc:nts involving Class m pilots. While those analyses were only indirectly relevant 

to the Age 60 Rule, they did provide a mGie general view of the effects of age on 

accident rate. However, there were limitations 011 the types of interpretations that 

coold be drawn from that app10ach. Part "91 general aviation pilots did not need to 

meet as rigorous medical and proficiency standards as airline pilots, and their selection 

and liamure were not as rigorous. Nevertheless, when Class m pilots and Part 91 

accidents were used to draw tentative inferences about Part 121 accident rates, the data 

nee.ied to be selected g) that the population was reasonably comparable to the group of 

Part 121 pilotll to be analyzed. For example, t.lte analyses could have been restricted to 

expelienc:ed pilots with high hours flown in the last year and high total flight time, both 

of which were cluuacteristic of airline pilots. 

That type of analysis of Part 91 accidents did provide information about the 

general effects of aging on aviation accidents. Further, it did cast light in an area 

where the Part 121 accidents left us totally in the dark: accidents by flyers older than 

60. If the 60th birthday is an important milestone in flying ability, the data from the 

analysis of the Part 91 accidents should have reflected this, especially when age was 

examined year by year. 

1.4 Approach 

The overall approach taken in this project was to f.rst develop the 

Consolidated Database Md then to conduct experiments on the CDB. The CDB was 

designed to support scientific analysis, and is described in detail in Section 3 of this 

report. In the interest of maximizing the efficiency of output during the development 

effort. a parallel approach was adopted. Since the CAIS Medical Database and the 

NTSB accident database were the major databases of interest in this study, they were 

loaded and verified first so that analysis depending on those data could be started while 

1-9 
the renua.ining ctaraNses were loaded. The other database of importance in the analysis 

was the CAIS Certification Database, becl!use it provided a linkage between the 

accident and medical databases t.'lrough the pilot's celtificate number (see Section 3, 

Figure 3-1). Consequently the Certification D2tabase was the third database to be 

installed in the CDB. 

A number of supporting tabulations and analyses were conducted throughout 

the course of :he wort that were necessary and useful, but not revealing in ~ to 

the scientific concl~ions of the study. For e.umple, pilot attrition studies and ;tilot 

counts were conducted to characterize the various groups that were used for analysis. 

These results and many ot.iers were not incorpoiated in this report. 

1.5 Document Overview 

The remainder of this report is organized as follows. SectiM 2 discusses 

prior research CO!Iceming accident rate and the age of the pilot. This includes a 

discussion of the Golaszewski report of 1983, which is the most widely cited previous 

work. Section 3 describes the Consolidated Database and provides an explanation of 

how the CDB was utilized to support the analytical wort contained in this report. 

Section 4 describes in detail the analytical methodology employed in this study. The 

mristical approach used throeghout the analyses is explained and justified. Section S 

presents the results of the analysis. The format used to present the results is to flame 

the discussion in a series of answers to questions that PfO:iress in a logical fashion to 

the conclusions c:onceming chronological age, accidents, and other factors. Finally, 

Section 6 summarizes and discusses the results of the analysis ar.d offers conclusions 

relevant to the At~ 60 Rule. 

As previously noted, the results of analyses piesu•ted in this report are those 

that bear direct!y on the stated objectives cf the research. The analytical results, tables, 

2nd figures contained in the report are but a small fraction of the overall analytical 

t'CS •ch that was conducted throughout the duration of this effort. 

•t OCbel' type offl)"iDc iDcludes misc:ei!IIIIOOI.IS ca~e&orics such os !03, lOS, 123, 125, 127, 129, 133, 

137,8141. 

1-10 
2.0 PRIOR RESEARCH 

A number of studies investigated the relationship be..'Ween accident ra>e and 

the age of the pilot (Golaszewski, 1983; Guide and Gibbon, 1991; Monimer, 1991; 

OTA, 1900). Golaszewski's study was widely cited and c:ar• be considered the basis for 

these subsequent studies. Indeed, both Monimer and the OTA derived their data from 

Golaszewski's study. The methodology of Guide and Gibson was also similar to that of 

Golaszewski. Those studies are summarized below. 

2.1 1983 Golaszewski Allal:ylis 

In 1983, Richard Golaszewski produced a report "The influence of total 

flight time, recent flight time and age on pilot accident rates" (Golaszewski, 1983). 

The report was based on data oontained in the National Transportation Safety Board 

(NTSB) Accident Records Database and the FAA CAlS Medical Certification Database 

for the years 1976-1980. From the two databa'ICS, the age, recent flight time, and total 

flight time of licel!sed pilots were determined. Golaszewski estirnated accident rates 

for different pilot categories as a function of the factorial combination of age, recent 

flight time, and total flight time. Recent flight time was construed as experience within 

the previous 12 months. The data were analyzed in two groups: all pilots and pilots 

holding Class m medical certificates. Golaszewski set up categories of recent flight 

time as 0-20 hours, 21-50 hours, 51-100 hours, 101-400 hours, and 401 hours a.id 

over. He used the NTSB Accident database to tabulate accidents by age, recent flight 

time, and total f',ight time for Class ill pilots and for all pilots. The CAIS Medical 

Certification database was used to estiw.ate the exposure (i.e. number of hours flown) 

for each class of pilot. Golaszewski used annualization factors to compute exposu.-e as 

follows: for Class I pilots who reported ~ery six months, the number of recent hours 

in each record were each divided by two; for Class n pilots, who reported on a yearly 

basis, the number of hours flown was not modified; for C'!ass m pilots, who reported 

biannU2lly, the number of hours flown was multiplied by two. All of Golaszewski's 

analyses were restricted to two groups, Class ID pilots and Class I, II, and ill pllo>.s 

combined. 

After visually inspecting his graphs, Golaszewski concluded: 

1. Accident rates were im·ersely proportional to recent flight time. 

2. For low recent flight time, older pilots h1:1d more accidents than 

younger pilots, while the converse held for higher recent flight time. 

3. For recent flight time less than 50 hours, Class I and II pilots had 

more accidents than Oass m pilots. 

2-1 
4. Accident rates were inversely j)IOp()rtional to total flight time. 

5. Class m pilots had more accidents, regardless of total flight time. 

6. For Class I aDd IT pilots with 101 to 5,000 ~tl!l flight hours, older 

pilots had more accidents than younger ones. 

7. The older the Class m pilot, tl!e less likely an accident until age 60, 

when accidents became more likely. 

8. Pilots with over 1,000 total flight hours and less than 50 recent flight 

hours had the highest accident rates, while pilots with over 1,000 

total hours and greater than 50 rerent hours bad the lowest accident 

rates. 

9. For Class m pilots with low total flight time and fewer than 50 

recent flight hours, accident rates increased with age; the converse 

was true if the n''mber of recent flight hours exceeded 50. 

10. For pilots with more than 50 recent flight hours and less than 1,000 

total flight hours, accident rates decreased with age; the converse 

held for pilots with less than SO recent flight hours a.-:d less than 

1,000 total flight hours. 

2.1.1 Dnwtw;lcs to Go!awws!Q's Methodol~ 

Combining pilot classes, as dcne in the Golaszewski analysis, was 

iMppropriate because it pr..Jduced misl.:ading accident rates. For example, pilots 

holding Cl.ass I medical certificates had relatively fewer accidents and higher f'Jght 

hours. The accident rate profile of a heterogeneous group was influenced by the 

piOpori:ion of Class I pilots in that group. Further, b=use Class I pilots were 

involvOO in so few accidents, Golaszewski did not compute the accident rates within 

various categories of flying by Class I pilots. The fact tiat =idents involvi.ng Class I 

pilots were SCI rare strongly suggested that the distribution of such accidents across the 

various categories was different than for the groups of pilots Golaszewski did study, 

Class ill p;Jots alone and ali pilots. Further, although Class I pilots were involved in 

few accidents they accumulated a substa'ltial number of flight hours. Thus they 

contributed substantially to the denominators (hours flown) of the accident rates and 

contributed relatively little to the numerators (number of accidents). This mea.-tt that 

differences in accident rates could have been artifacts; they could have reflected 

differences in flight hours accumulated by Class I pilots rather than differences in tlte 

likelihood of accidents. 

Golaszewski included accidents by pilots whose medical certificates had 

lapsed. Their flight hours were not =roed in the CAIS mooical database and their 

exposure to accidents could not be estimated. Thus, those pilots only contributed to the 

2-2 
numentors of the accident rates. Any systematic bias in the distribution of those pilots 

by age would have distorted the correspon~ accident rates. 

Golaszewsla performed no statistical analyses on his data, depending only 

on vis'Jal inspections of the data. As we argue in detail in Section 4.4, the data were 

quite amenable to statistical analysis. Statistical analyses would have told us which 

differences were real and were to be expected in the future as opposed to those 

<Hfferences that were cllance occurrences. For example, points 9 and 10 in 

Go!aszewsld's summary above suggested a triple interaction among age, recent flight 

time, a.11d total flight time. Without a statistical analysis, firm evidence for this 

conclllSion was lacking. 

The Age 60 Rule represents a sharp cutoff, presmnably reflecting some 

relatively dramatic change in the pilots as they approach 60 years. The 10-year age 

categories used by Gola.uewski were too gross to get a clear picture of such a change. 

A more fine grained analysis, say by year, would have been more appmpriate. 

2.2 1990 Omce of Technology Assessment Analysis 

In 1990, the Office of Technology Assessment (OTA) released a report 

(Office of Technology Assessment, 1990) that presented graphs of data supplied by Dr. 

Charles Billings of the NASA Ames Research Center. The figures stated that the data 

were from "Golaszewski 1983, and NTSB 1990". The OTA repon drew the follo~.ng 

major conclusions: 

1. For Class I and II pilots with more that 1,000 hours total f!Jght 

experience and more than 50 hours recent flight experience •an age 

effect was present and was beneficial until 50, after which :ratt:s 

increased". 

2. For Class I and II pilots • a.'l increase in accident rates with increasing 

age was seen after age 39 in pilots with 501-1,000 hours, after age 

49 in pilots with 1001-5,000 hours, and after age 59 in pilots with 

over 5,000 hours". 

3. For Class I and II pilots "who flew more than 100 hou.~year. 

increasing age (and probably total experience) and increased recent 

flying time both had beneficial effects. After age 60, accident rates 

increased even if pilots continued to fly over 400 hours per year•. 

It appea.red that the data fur the OTA revort were obtained by subtracting 

the numbers for Class m pilots from the numbers for the com;sponding combined 

group of Class I, II, and ill p-;kits, thus indirectly obtair.i."tg data for the corresponding 

group of combined C'i2SS I ar.d II pilots. Conclusions from these data were tentative, 

2-3 
because no statistical analyses were performed on the data. Unfortunatzly, whatever t'J.e 

source of the data, they did not bear directly on the Age 60 Ru1e, bec.iuse they 

combined Class I and Class II pilots ro create quite heterogeneous groups. 

2..3 1991 Guide and Gibson Analysis 

A third study was conducted by Guide and Gibson (1991} and reported at 

the 1991 meeting of the Huir.an Factors Society. Their design was similar to 

Golaszewski's and utilized data for the years 1982 - 1988 from four sources: the 

JI.'TSB Accident database, the Aircraft Owners and Pilots Association Air Safety 

Database, the FAA Statistical Handbook on Aviation, and the COMSIS Research 

Corporation. They used 5-year age categories, staning with 20-24 and f.nishing v.ith 

55-59. They computed accident rates in two ways: (1) per number of active pilots and 

{2) per number of annual hours flown. All analyses depended upon visually examini11g 

four figures displaying the above data; no statistical analyses were rz:por..ed. 

Three of the figures displayed the accidents per number of active pilots for 

air transport pilots, for commercial pilots, and for private piJots, respectively. 

Exposure was not accounted for in these figures. The fourth figure displayed accidents 

per hours flown for Part 135 pilots as a function of age and of hours flown in the 

p1ereding year (101-400 versus > 400), altllough the data for the 20-24 age group 

were om;tted for some unstated reasG!l. There appeared to be no discernible trends as a 

futletion of age in the data in the fourth fi,cure. Indeed, differences arnong the various 

age groups appeared minimal, however, this was difficult to verify without statisticaJ. 

tests. For each of the seven age groups displayed, the pilots with more than 400 recent 

flight hours had an accident rate rough! y one third that of the pilots v.ith 101-400 recent 

flight hours. The probability of that happening by chance was less then 0.01 (applying 

the sign test, with N=7). 

2.4 1991 Mortimer Analysis 

Mortimer (1991) examined a ra11dom sa:nple of 1,034 general aVIation 

accidents drawn from the NTSB data base for the years 1985 and 1986. Alt.'J.ough not 

clear from his description, te appeared to have esti!I'.ated exposure by multi.pljing the 

number of pilots in various categories in 1985 and 1986 by the mean mllnber of hou..rs, 

per }rilot, flown by the COriesponding pilots in Golaszev.-ski's report. Mortimer 

concluded from the resulting data, apparently without statistical analysis, that private 

pilots over 60 had accident rates at least tv.'ice tl'lat of their juniors. Mortimer's 

met.iodology had a number of weaknesses, particulariy his estimation of expoStL.--e. If 

the percentage of pilots over 60 m 1985-1986 was twice t.'1at of 1976-i980, Mortime;'~ 

effect disappeared. Because Mortimer was vague about the exact nature of his 

calculations, they could not be readiiy reproduced or anaiyzed using t.11e CDB data and 

therefore were not considered in this study. 

2-4 
3.0 CONSOLIDATED DATA BASE 

11-..is section su!JUI1a,"izes the development of a Consolidated Database (CDB) 

to support diverse research needs in the aviation safety and hu1nan factors researcl: area 

and provide more direct access to the wealth of information collected by the FAA a:;d 

~"'TSB. The CDB merges several NTSB and FAA bistorical databases tha.t 1:re 

cw-rently organized in heterogeneou-s formats into a single relationally sttucmred 

database. Each of the historic databases contains information on a particular aspect of 

available infQmati.On including the results of periodic medical .. xaminations requi...-ed 

for all pilots, pilot certificatiol'..s and ratings information, accident L'lvestigations, pilot 

incidents, and pilot deviations. The consolidatioo of these databaseS allows resea.""Chers 

to pose questions that cannot be :readily determined from a single database. Each of 

these historic databases was developed a.'ld maintained by separate organizational 

entities and organized for the needs of the sp:cific orgarJzation. Researcher access to 

these historic databases to explore new hypotheses is dLfficult, if not impossible. 

Additionally, the individual databases are based upon diverse file and ddtabase 

management systems utilizing a va.Tiety of hardware and software environments. 

Semantically similar information is stored using a variety of formats and data models 

and each database uses different naming conventions. 

A high level description of the F A.J... and NTSB source databases used in 

these :analyses is provided as well as information on the processes used to verify t.~e 

contents and to retrieve the :information required for the analyses presented in this 

report. For additional details about the CDB, the reader is referred to the CDB 

Techl'Jca.l Reports: Age 60 Project Consolidated Database Implementation (Harris, 

Hillman, and Voros, 1992a) and Age 60 Project Consolidated Database User's Guide 

(Harris, Hillman, and Voros, 1992b) (see attached bibliograpbies for citations). 

3.1 FAA and 1\"TSB Historic Databases 

The CDB incorporates information from several existing sources, i.'lcluding 

the FAA Comprehensive Airman L;formation System {CAIS) containing both medical 

history and certification data, the Accident/Incident Database {AIDS), t.ie Pilot 

Deviation System (PDS}, and the ~"'TSB Accident datab:lse. The:;e source databases 

conlain information regarding pilot cha .. -acteristics, operational expe:ience, mediw:l 

data, aviation de'>iations, incidents, at'ld accidents as described below. 

3.1.1 FM Comruehensjve Airman Information Svstem fCAIS) 

The CAMI Compre.iensive Airrn.:m Inforrr-.ation System (CAIS), maintained 

m OkiaOOma City, contains medical data for pilots as well as airman certi.ficare 

ir.funnation. The medical certification Sj'j;'.em contains bfotrr'.ation on ai.T'ffi?!l 

applications for medical certificatio:: b2Sed upon physiczl sta11dards pres..."libed in FAR, 
Parts 61 65, 67, and 187. CAIS aimmn i.111'ormatioH is orgarrized into the following 

two group:.; of information: 

L Pilot certification which contains a single recoro for each pilot with 

the most recent informatton on the pilot's certificates, ratings, 

accidems, violations, cancellation/revocations, a.11d fur.itations. 

2. Medical certification which contains a record for each certification 

physical including date of birth, certification ciass, flight hours 

(civilian total and last six months), medical i.nfonnation 

(canliovascular, vision, hearing, restrictions, and pathology codes). 

From the pilot certificate database no historic information is awillahle. r.or is 

there an indication of ""'hen the information for t.'le pilot cr.anges. For example, no 

information is provided about when a pilot obtained a particuiar ="ti.ficate or rs.:i!;g. 

3.1.2 NTSB Accident Rec:ords Dararew 

Tne :!I.'TSB Accident Records Datahase, maintained in Wash..i.'"lgton, DC, 

ccntai."!S information derived from accidents in~gat::d by the NTSB. Tfu-ee different 

fOI'!T'..S have been used to GOJ.lect the Gala.. From 1962 to 1981, an Aircraft Accident 

Analysis Sheet tNTSB Form 6120.12) based on pu.ltched card images v.'<IS used. In 

1982, tile form was revised (6120.4D NTSB Accident/Incident Report) to fWJitate t.'le 

collection of data in 693 fields plus a free-form narrative. The data collected from 

1983 to the present are based upon the i.-:tfonnation contained on revised form 6120.4, 

NTSB Factual Report Aviation, which has 236 fields. The NTSB accident data for 

1983 to the ~t contail'..s an additional 22 files each of which provides informa:lcn 

on a spect.'lc area such as a text narrative of the accider'!t, causal factorS, copilot 

information, etc. Information contained in the .N!SB Accident Database includes t.'le 

follov.ing: pilot i."lformation (age, flight hours for specific aircraft and all ai..-cra..'t for 

last 24 hours, 30 days, 90 days, and overall total), weather, cabi!: crew and passenger 

info~;:;n, aircraft lnfonnation, operational phase, investigation results, and causes 

and factors. Currently, the l'.'TSB informatiO>'l incorporate<! into t.'le CDB includes the 

core file containing material provided on form 6120.4, the ar.rident na "!ati.ve .. file, cause 

factors detailed in the sequence of events file. and co-pilot file. 

3.2 CDB Database Statistics 

Tne contents of t.ie CDB were verified, where possiole, by comparing the 

number of records loaded from the medic supplied by t:."le database adrrilllist:ratct". In 

ac!dition, statistical sources were consulted where available. Table 3-1 pres...r.ts 

statistics oo the CAIS medical =ords included L'"l the CDB compa.<'Cd to the 

infonr.atioo shown in FAA 1990 Yearoook (Table II.B, Receipts of Medical Certificate 

Applications l>y Class). The data in :'able II.B is based upon r=ipt of medical 

3-2 
' i 

I 

! 

! 

! 

! 

certificates, w!>.ile the data from the CDB is based u-pon year of medical examination 

and only includes those applications that were acceptably processed into L'le CAIS 

system. 

The large ::iscrepancy for 1986 CAIS medical records data shown in Table 

3-1 \Vas investigated further. Table 3-2 presents a month by month analysis of the 

CDB data versus the information pres..."'lted in the FAA 1986 Yearbook (Table Il.B, 

Receipts of Medical Certificate Applications by C.ass). It appea.rs that the missing data 

for 1986 was hrevocably lost. The data for May, June, July, and August of 1986 show 

large variations between that sh0\1.'!1 in the FAA Yearbook. Unfortunately, no 

discernible pattern for the missing data could be established and therefore 1986 data 

were omitted from the analyses included in this report. 

The information extracted from each of the source databases was stored in a 

series of tables in the CDB. Table 3-3 contains the n!L'llber of records included in the 

CDB for each of the source databases used i,; t.l:!::se analyses as well as a11 indication of 

the associated time periods. 

Table3-L 

' 

I 

A comparison of the number of medi<:al certificates applicatiO!!S 

received rqxnted in the FAA statisti<:al handbook with !he number of 

=ords loaded in the CDB for the years 1976-1988. The large 

~-y for 1986 is appa~ently due to lost records. See the text 

for more delails. 

Year 

1976 

1977 

1978 

1979 

1980 

1981 

1982 

1983 

1984 

1985 

1986 

1987 

1988 

' t 

I I FAA 

Statistical CDB I 

Handbook Database Diffe.."'ellce 

542,159 524,449 17,710 

550,243 538,350, 11,8931 

565,534 558,973 6,5611 . - - 1 . 550,1881 551,90;,1 1, 7:71 

529,051 504,0151 25,~,61 529,4181 502,0981 27,,.,20 

463,2411 479,9161 -16,6751 

477,9051' 490,271' -12,3661 

463,617 468,919 -5,302' 

479,849j 474,094, 5,7551 

474,392! 347,6041 126,788; 

470,2081 471,223, -1,015i 

466.3261 463,7491 2.5771 

3-3 
Table3-2. Count of medical =tificates in !!le CDB for I 986 as a function of 

month md class. Note the low tot2ls for May, June, July, and 

August. 

..,olllh Class l l'ercellt Clas• I! Pe=t Class ill ""'=t Total - Januory, 86 

February. 86 

March, 86 

April, 86 

May,86 

l,.,, 86 

July, 86 

~,.,86 

~t:ui: c:r. 86 

October, 86 

November, 86 

Dc:cmber,86 

CDB1986T~ 

FAA 1986 Yearl>ook 

DUfc=cc 

Table3-3. 

12,386 33% 11,273 30% 13,626 37% 37.285 

10,642 33% 9,957 31% 11,822 36% 32,421 

11,562 31% 11,294 30$ 14,446 39$ 37,302 

11,660 30% 11,298 29$ 15,773 41% 38,731 

9,198 31% 8,244 27% 12,602 42% 30,044 

1,358 43$ 80S 25$ 1~024 32% 3,187 

1,437 31$ 1,516 32$ 1,750 37% 4,703 

3,518 27% 4,403 34% S,OlS 39% 12,939 

ll,SlS 29% 11,734 29% 16,6W 41% 40,189 

12,560 31$ 11,730 29$ 16,383 40% 40,673 

10,506 33% 9,144 29% 12,046 38$ 31,696 

11,308 34% 9,136 29% 12,148 37% 33,192 

107,950 32% 101,134 30% 133,278 39% 342,362 

131,304 28% 146,113 31% 194~975 41% 474,392 

25,354 19% 44,979 31$ 61,697 32% 132,930 28% 

Count of the 11umber of =ords in the CDB as a function of the source 

databases 

I Time Period 

l 

' I 

' 

CDB Source Database Number of CDB records L11claded in CDB 

FAA Medical 6,375.566 1976-1989 

NTSB Accident 47,616 1976-1988 

FAA Certification 2,954.999 ! 1962-1988 

FAA Pilot Deviation System 13,895 ! 1986-1990 

FAA Accident/Incident ..11,341 1986-1991 

Total I 9 433.417 

3.3 CDB Organization 

The development of tlle CDB involved designing a global structu...-e that 

unified the diverse database information, identifying semantical1y equivalent data 

elements, and developing consistent formatting a.'ld coding schemes. The CDB was 

developed using the Oracle Relational Database Y.anageme11t Systen1 (RDBMS) on an 

HP 9000n50 tTh:iX Workstation. The information contained in each source database 

v.as examined and similar information, such as aL'"C!'aft ovmer, pilot data, weather, 

accident causes, etc., was grouped into a set of Oracle tables. 

3-4 
Unique identifiers were required to link the CDB tables based upon the 

information available from the source data. For example, a mechanism for associating 

a pilot involved in an accident with that pilot's medical examination information was 

needed. The certification, accident (1982 to present), pilot deviation, and 

accident/incident database information contain the pilot certification number. 

However, the pilot records in the CAIS Medical Certification database are identified 

only by the pilot's social security number. Since the CAIS Certificate Database 

contains both the pilot's certificate number and social security numbe;, this information 

was used to add an additional data element containing the pilot's certificate number to 

each medical rxord for the pilot. This mapping could not be readily accomplished 

because certificate numbers in the CAIS Certificate Database are not unique and it 

appears that the certificate numbers are reused. In order to uniquely identify a pilot, 

the following combination of database elements are required: 

• NTSB Accident, Pilot Deviation - certificate number and date of 

birth 

• FAA Certificate - certificate number and social security number 

It is important to note that the personal identifiers in the 1-."'TSB Accident 

database prior to 1982 were removed and, therefore, accident information in this period 

could not be linked to other databases. Figure 3-1 illustrates how the source databases 

can be linked through the pilot certificate number in combination with appropriate 

additional fields as descn"bed above. For purposes of illustration, this figure only 

shows the certificate number. 

3-5 
CONSOUDATED DATABASE 

... 

.:.:o l!l! 

·'· :~::: 

:;i~ 

A view of the constituent d•tabases of the CDB and how they may be 

linked using the pilot's certificate number. 

,.,, 

,~~ !li~ ,,,. :;:' 

!:!; 

.,.; ~~ 

The source databases used a variety of schemes for encoding information. 

These coding schemes .¥ere '.lSed to associate an abbreviation or a mnemonic with a 

particular entry in a set of possible values for a collll1l11 of information. To facilitate 

the use of the CDB, common encoding schemes were developed for key pieces of data, 

such as pilot medical certiiication class. Table 3-4 illustrates the coding scheme 

dev~oped for the CDB based upon those used in the NTSB Accident and FAA Medical 

for medical class (medical class is not contained in the AIDS and PDS databases). 

3-6 
Table3-4. Encoding schemes for p-:Iot medical class for the CDB, FAA Medical 

md NTSB dab!bases. 

Zlt'TSB 

Pilot 

Medical I 1983 to 

Class CDB FAA Medical Prior to 1982 1982 ! Present 

I 1 11-19 A,D,G I 2 

n 2 21-29 B,E,H n 3 

m 3 31-39 C,F,I m 4 

None 0 0 J Blank 1 

Unknown Null 0 z Blank 0 

3.4 CDB Utilization 

3.4.1 Selection Criteria 

Tne criteria for selecting accident and medical examination database records 

for inclusion in the CDB analyses described here were: 

• The age of the pilot was between 20 and 74; 

• The medical class was 1, 2, or 3; and 

• Recent and total flight time were both valid and greater than zero. 

Table 3-5 presents statistics on the CDB Medical records that were included 

in this study while Table 3-6 presents similar statistics for NTSB accident records. 

Although NTSB accident recon!s were available for 1986, they were not used in any 

analyses that also involved 1986 medical records. 

3.4.2 Accident Rate Q!lculation J>rnrmyre 

The NTSB information in the CDB includes the pilot's age, medical class, 

and to1a1 flight hours and recent flight time (previous 90 days for all aircraft). The 

medical examination data in the CDB contains pilot's date of birth, medical class, total 

flight time, a.'ld recent flight time (previous six months). Tne term "recent flight 

hours• in this report is defined as the number of hours flown by a pilot for a single 

year. 

3-7 
Hours were annualized acrording to the Golaszewski study (see Section 2.1 for 

discussion of the Golaszewski methodology). The accident rate as calculated for a 

given group of pilots is computed as shown below based on the method developed by 

Golaszewski (1983): 

. Count of NTSB Accide:lts 

ACCident Rate= Total of FAA Medica. Annual Flight Hours 

Table3-5. Count of the number of medical records in the COB and the number 

of medical !eCOrds used in the COB experiments as a fimction of year 

(1976-1988). Note that the records from 1986 were not used in the 

C'DB experimeuts, beca!•se & snbstantia! number of records are 

missing for tb2t year. 

Records Used in CDB 

Year CDB Medical Records Analyses 

1976 524,449 338,794 

1977 538,350 348,080 

1978 558,973 342,916 

1979 551,905 347,5901 

1980 504,015 337,6041 

i981 502,098 333,348 

1982 479,916 312,816! 

1983 490,2.71 317,583 

1984 468,919 314,357 

1985 474,094 324,311 

1986 347,604 NotUsed"l 

1987 471,223 334,055 

1988 463,749 334,124 

TOTAL- All Years 6,375,566. 3,985,578 

3-8 
Table3-6. Count of the number of accident records in the CDB and the number 

of accident records used in the CDB analyses as a function of year 

(1976-1988). 

Records Used in CDB 

Year NTSB Accident~ Analyses 

1976 4,367 3,839 

1977 4,468 3,947 

1978 4,699 4,116 

1979 4,208 3,632 

1980 3,961 3,361 

1981 3,8n 3,187 

1982 3,592 3,180 

1983 3,555 2,494 

1,984 3,452 2,370 

1985 3,092 2,247 

1986 2,872 Not Used03 

1987 2,795 2,027 

1988 2,678 1,941 

TOTAL- All Years 47,616 38,414 

The procedure for generating the data required to calculate the accident rates 

for a categorical group of pilots, e.g., year of accident/medical examination, pilot age, 

pilot medical class, and recent flight hours categories (less than 250 per year, more 

than 500 per year, etc.) was as follows. The annual flight hours for the NTSB 

accidents was determined by multiplying the hours reported the past 90 days for flying 

all aircraft by 4. The recent flight hours contained in the medical examination data was 

for the past 6 months and this number was multiplied by 2 to obtain annual flight 

hours. Since pilots varied in the frequency in which medical examinations were 

required by medical class, the annualization factors shown in Tabie 3-7 were applied to 

the annual hours obtained from the medical and accident data. 

T~3-7. Annualization factors used to convert the total number of annual bmlrS 

reported by a class of pilots to an estimate of the number of bcun; 

flown by that class during tbe year. 

I Annualization Factor 

\ Applied to Annual Flight 

Medical Class 

Medical Exa.rmnation 

Frequencv l Hours 

I E:;es six months I ~:~ 2.0 

n 

m 

3-9 
3.4.3 Data Limitations 

When utilizing the CD B for va-rious studies, the limitations of the various 

component source databases were considered in determining the viability of the 

proposed study. Some of those limitations are described below. 

Each of the databases used a different scheme for s,eclfying invalid or 

unknown information. For example, NTSB Accident database filled the field with 9's 

or Z's while the FAA Medical database contained zeroes. Therefore, flight time 

information containing a zero was subject to a variety of interpretation -- it could mean: 

1. The pilot did not have any flight time and actually entered a zero or 

2. The information was unknown or missing and, in some databases, 

blank information was entered as a zero. 

Frequently, data elements for a source database appeared to have potential 

for study but upon careful examination of the data, the element was not sufficiently 

populated to permit statistical analysis. For example, the NTSB Accident database 

contained data elements for day and night landings for the last 90 days for all aircraft. 

However, as Table 3-8 illustrates, the insufficient number of accident records with 

information supplied for this field precluded its use. 

Table3-8. 

NTSB Accidents (1983-

1988) 

Day and night landings for Class I, IT, and ill pilots from NTSB 

Accident Data 1983-1988 . 

Class I Class II Cl2SSill 

! Percent Percent 

Count I Populated Count Populated Count 

Accidents Included in CDB 2,005 5,214 5,933 

Day Undinp (Last 90 406 20.2 895 17.2 886 

Davsl 

Night UDdin!" (Last 90 512 25.5 1,577 30.2 1,944 

Days) 

Percent 

Populated 

14.9 

32.8 

The CAIS Certificate data provided information on pilot certificates, e.g., 

ATP, commercial, private, etc. However, no information was provided about when 

the certificate was obtained and therefore usage of this information for historical data 

analysis was problematic. Although the CAIS Certificate and Medical Databases could 

be linked, generating accident rates for Class m pilots with private certificates for the 

period 1983-1988 could not be meaningfully accomplished since the CAIS certificate 

data was as of 1992 and the piim certificates for the period 1983-1988 could not be 

determined. 

3-10 
An additional limitation was that the information obtained from the NTSB 

Accident database varied depending upon the particular time period. For example, the 

specific:Won of the regulation the flight was conducted under, e.g., Part 121, Part 135, 

Part 91, was not available for data prior to 1982. Pilot identifier information, such as 

certificate number, was removed for data prior to 1982 and ~erefore data for this 

period could not be linked to the other databases for analysis. 

In analyzing accidents based upon various groupings of causes, the NTSB 

Accident database information for the period 1982 to 1988 contained numerous detailed 

cause codes in the sequence of events file. No higher level cause categories such as 

medical, mechanical, pilot error, etc., were provided and therefore, each researcher 

had to examine the numeric codes and establish their own particular mapping of the 

codes to higher level causes categories. 

"3 2,073 accicleat records for 1986 met the selection criteria stated in Section 3.4.1. 

3-11 
4.0 METHODOLOGY 

4.1 Plan or Analysis 

A number of principles guided the analyses. First, it was inappropriate to 

aggregate data across medical classes, because this created heterogeneous groups with 

misleading accident rates. For example, Class I pilots had relatively few accidents and 

relatively high flight hours. If the medical class of the pilots was ignored in forming 

groups, the accident rates of the groups would have reflected differences in the 

proportion of Class I pilots in the various groups. 

Second, the data for Class I pilots shed some light on the accident rates of 

Part 121 pilots, subject to a number of constraints. Only pilots younger than 60 should 

have been included, because no Part 121 pilots flew a_f'ter 60. Further, the data for 

Class I pilots with high recent flight time were more cha--acteristic of Part 121 pilots. 

Third, the data fer Class m pilots provided convergent ev:dence on the effects of age 

on accident rate. While Class m pilots were less like Part 121 pilots, the data for that 

class were less affected by changes in the membership of the groups ·with age, 

especially the dramatic change seen for Class I pilots after age 60. Further, the 

accident rates for Class m pilots provided evidence for the general effects of aging. 

Finally, the Class II pilots formed a heterogeneous group and were the least useful 

group for shedding light on the age 60 rule. 

All the analyses were based upon sets of data retrieved from the CDB. The 

details of the query used to obtain a given set of data from the CDB are shown in 

Appendix B. The analyses were of four general kinds as described in subsequent 

paragraphs: 

1. Accident rates as a function of age, 

2. Longitudinal view of accident rates, 

3. Accident frequency as a function of age, and 

4. Subsidiary analyses. 

4.1.1 ACcident Rate as a Function of A~ 

The CDB provided medical records of all pilots for t.i.e years 1976-1985 and 

!?87-1988. These records contained the number of hours of recent flight time and of 

total flight time for all pilots of a given age in each me.iical. class (I, II, and III), and 

these data, in turn, were used to estimate the total number of hours flown by a group of 

pilots in the preceding year. The CDB also provided records of all accidents during the 

4-1 
years 1976-1985 and 1987-1988, :records which contained the pilot's medical class, 

age, and number of hours of recent and of total flight time. From these data, t.lte 

number of accidents by pilots in a given group could be counted. Thus, for some 

group of interest (e.g., Class I pilots who had at least 700 recent flight hours, who had 

at !east 2,000 total flight hours, and who were of age 50-54) the accident rate was 

estimated by dividing the number of accidents for the group by the estimated number of 

hours flown by the group. 

To validate the integrity of the CDB, the data set described by Golaszewski 

(1983) (i.e., for the years 1976-1980) was retrieved to determi!le whether our data 

agreed in deWl with those reported by Gola'!Zewski. Examination of those data 

indicated good agreement. See Appendix A for details. 

Focusing on Class I pilots, the interaction of recent flight tim~ and age on 

accident rate was explored. Then attention was restricted to those Class I pilots most 

like pilots of scheduled air carriers by considering only those pilots who had the 

necessary minimum total flight hours and who had the number of recent flight hours 

characteristic of pilots of scheduled air carriers. Next, only Pa."t 121 pilots wit.il ATP 

rating and high recent flight hours were considered. Finally, at>..ention was shifted to 

Class m pilots with high recent flight hours to provide a different view of the effect of 

age on accident rate. In all cases above, the data were aggregated in a cross-sectional 

manner. For example, the data for 50-year-o!d pilots were aggregated for all pilots of 

t.!Jat age without respect to the year in which the data were collected. Thus, the 50 year 

old pilot of 1976 was the 51 year old pilot of 1977. In 1976 that pilot's data were 

grouped with the 50-year-olds' data; in 1977 that pilot's data were grouped with the 

51-year-olds' data. 

4.1.2 Loneffildinal View of Accident Rate 

Because the data i..,, the CDB spanned the yea.T"S 1976-1985, one could take a 

longitudinal view of accident rate by following the same group for 10 years. In that 

analysis, accident rate as a function of birth year was examined. For example, the 

accident rate of pilots born from 1946-1950 was examined for each of the 10 years 

from 1976 to 1985. 

4.1.3 Accident Frequency as a Function of A~:e 

In addition to the age of the pilot, the CDB recorded a great deal of 

infonr.ation about each accident. Thus the accidents recorded in the CDB rould be 

classified according to the age cf the pilot and some second factor, e. g., the time of 

day when the accident occ•Jrred. The resulting data could be analyzed to determine 

whether the distribution of accidents in t.':le various categories of the second facto; 

differed as a function of age, e.g., whether older pilots were more likely to be involved 

in an accident at dusk than younger pilots. 

4-2 
4.1.4 Subsidiazy Ana1vses 

The analyses above raised a number of questions about the underlyin~ 

population of pilots. For example, given that the formation of the groups was not 

under the experimenters' control, how did the membership of the groups ch<mge as a 

function of age? This question suggested that the attrition and accretion of groups as a 

function of age should have been studied. 

4.2 Assumptions of the Statistics 

To maintain their certification, holders of Class I certificates obtained 

medical exa..ilinations every six months, holders of Class II certificates every year, and 

holders of Class m certificates every two years. In all cases, pilots stated the number 

of hours flown in the last six months and the number of total hours flown. We defined 

"recent flight hours flown• as the number of hours flown in the previous year. Thus, 

doubling the number of hours flown in the previous six months was a :reasonable 

estimate of recent hours flown. To use those data to estiir.ate the recent hours flown by 

various categories of pilots, the data had to be further "annualized." Thus, because the 

Class I pilots reported their recent hours twice a year, those recent flight hours were 

divided by two when aggregated. Si..-nilarly, the recent hours flov.-n which were reported 

by Class ill pilots were multiplied by two when aggregated. 

The statistical approach, which is described in more detail below, assu.lned 

accident rate was normally distributed in the case of t.'te F-test of the a11alysis of 

~.ance and assumed accidents were independent events in the case of the chi-squa."e 

test. The latter assumption obviously held, whlie the former assumption merited more 

discussion. A member of any particular group of pilots had a given probability of 

being in an accident. Each observation from that group constituted an independent 

Bernoulli trial, i.e., a trial for which there was or was not an accident. Because the 

observations were independent, the number of accidents for the given group was 

binomially distributed. (Drake, 1967). The normal distribution is a goo:i 

approximation or the binomial when the mean is larger than 3 standard deviations alld 

at least 3 standard deviations less than the number of observations (Drake, 1967). Our 

analyses were restriC'..ed to tho.se data that satisfied that criterion, and the accident rates 

were therefore approximately normally distributed. 

4.3 The Statistical Approach 

The analysis of va .. -iance (ANOVA) V.'as used to analyze the accident rate 

data, and the chi-square statistic was used to analyze the frequency data. For statistical 

analyses using the .4.NOV A, the test \\-"as applied to completely crossed factorial 

designs, i.e., designs in which all combinations of levels of each factor occurred. Such 

an ANOV A yields a.., F statistic for each l!'.ai.n effect a'ld interaction. VI-'hen 

4-3 
i.\'lteractions are significant i'l completely crossed designs, t.'le interpretation of a!1Y 

significant main effects must take into account the significant interaction(s). Indeed, in 

some cases, the significant main effect takes a back seat to the significant interaction. 

That is, ignoring the significant mail' effect in favor of the sigr:.ificant interaction may 

clar'Jy the interpretation. Tnat approl!Ch was taken in bterpreting the results s.'lo\\'!1 

below. 

In our analysis of accident rates, a.'l ANOV A was used that treated the data 

as proportions {Ga!r.es, 1978). For such an analysis, the value of the degrees of 

freedom (df) for the denominator was infinite, because the estimate of the w..a.'lce "'-as 

exact (Games, 1978, table 3). For all F values reported, only the degrees of freedom 

for the numerator were given, and it should be understood that the value of the degrees 

of fr=dom for the denominator was infinite. 

The chi-square test was applied to cou.'lts of accidents wf!ich were 

categorized according to the age-group of the pilot and according to some second 

factor, e.g., season of the year. Those categorizations led to two-dimensional tables of 

counts (so called two-way contingency tables). The chi-squa."e test ca.'l be applied to 

any two-way table each of whose cells have expected frequency (as computed in 

prepa<·ation for the chi-square test) equal to 5 or greater (Hays, 1973, p. 723). 

4.4 Justii~eation of the Use of Statistics 

Golaszewski (1983) argued tr.at statistical analyses should not have bee:! 

applied to his data because the data constituted the whoie population, and the data were 

not normally distributed. Following his lead, Billings (OTA, 1990), Guide a.'1d Gibson 

(1991), and Mortimer (1991) also failed to apply statistical ar.alyses to Llteir data. 

Above, it was explained why it v.-as reaso!'.able to assu:ne that ti'l.e data were 

normally distributed. The question of whether the data constituted the whole 

population depended on the inferences desired. This study required inferences about 

the population of all possible flights. 1"1 particular, the probability of an accident as a 

function of age in the population of all possible frights needed to be infe."red. Ot:r data 

could indeed be USfd to make such infer~.nce.s. To understand this, consider the logic 

of statistical testing in more detail for L'Ie exair:ple of compa.~g t.ie probabilities of an 

accident in two groups. Tne probability of an accide::.t in each group was estimated by 

conducting an analysis in which we drew a sample of observations from each group a.'ld 

computed the proportion of observations i'l each sample that were accidents. Then a 

statistical test was performed to determir;e whet'1er t.':e two proportior.s differed 

sufficiently to conclude that it v.-as urceasona:Jle :o assume that the probability of a.'1 

accident v.-as the same for both groups. If it ;;.-as unreasonable to assume equal 

probabilities, then a similar difference L-: ~ie sa.-ne dL:-ection v.-as expected when 

repeating the anaylsis. If the assumptior: of equal pmba:Jilities v.-as reasonable, tltere 
was no statistical evidence for predicting the outcome wh~ repeating t.'le analysis. Our 

Gala were from an analysis which was more elaborate (and very lal:ge) but perfectly 

analogous to the above exampie. It w--..s important to i11fer whether the sa...-ne results 

would occur when the aJ"..flysis was repeated {the following year). Without infere."1ce, 

the data. spoke for a population and the question became •was the policy of rnandarory 

retirement at age 60 justified for that population (and only t.hal: population)?" That 

question might have had some academic interest, but providW no direction for fuUL.-e 

policy decision, unless one also asked, •CouJ.d we infer anyt.'ring from past 

performance of the policy to the performance of the policy now and in the future'r 

4-5 
S.O RESt.i'LTS 

The results of the data analyses were organized according to a series of 

questions to be answered. Tne text following a question presented first the <iata that 

addressed the question, followed by the results of statistical analyses on the data which 

were usually presented in ;m accompanying figure. Appendix B contains the backup 

data for each figure along with the parameters used to extract the n=ssa.J' infom1ation 

from the CDB. Usually, the text wou!d be silent about effects that were statistically 

insignificant. The analyses of va...~ce (ANOV As) were fer completely crossed 

factorial designs and subsidiary comparisons (or contrasts, St::e Hays, 1973), where the 

degrees or freedom for the denominator were always infir.ite. Thus, for A.~OV As, 

only the degrees of freedom for the numerator were reported. Finally, how the results 

of the statistical analyses had a bearir_g on the ori~.nal question V.'l!S discu..<sed. 

·when discussing the results, it is important to keep in mind that there were a 

number of factors confounded with age, factors that could affect the outcomes in this 

study. First, the composition of various groups changed v.'ith age. For example, it 

was likely that the FAA's rigorous medical and operational proficiency standards 

screened out, over time, pilots more likely to be in accidents. That issue was addressed 

to some extent with appropriate samples of data from the CDB. Furthermore, the 

proportion of pilots flying under Part 121 decreased suddenly and dramatically at age 

60. Second, the number of la.'ldings per flight hour could decrease v.'ith age, because 

older pilots could use their seniority to choose longer routes. Tnird, the safety 

characteristics of the route and the airports could be correlated v.'it."l age for similar 

reasons. Those latter two factors in regard to Part 121 pilots could not be addressed by 

the data in the CDB but weakened some interpretations of the results. Note that if an 

increase in accident rate v.'ith age .,,,.as observed in the data, sr;ch an increase would 

have occurred despite the above confounds, whereas if a decrease in accident rate was 

observed in the data, such a decrease could be attributed to the above confounds. 

Analysis of data for Class III (Part 91) :;illots minimized the effect of these confounds 

because those pilots did not operate in the framewor-k of the more rigorous standards or 

of seniority rules. 

· S.l Age and Accident Rate 

5.1.1 Did Accident Rates of Class ! Pilots Change wiL1 Age? 

Here, all Class I pilots were grouped together v.'ithout regard to total and 

recent flight experience. We 1olr&nted to get an overall view of the relationshiu between 

age and accident rate, kno'K'i.'lg that we could not readily generalize to Part 12I pilots, 

who were a select subgroup of Class I pilots. Data were restricted to pilots between 30 

and 59, grouped in 5-year age groups, because that v.-as the age range of P"ar: 121 

pilots. Figure 5-1 displays those Ca.~. Pilot age affected accident rate for t.~Iose data 

J-~ -' 
(F{5)=84.69, p< .01). In particular, accident rate decreased with i. ..1creased age for the 

younger pilots, leveling off for the older pilots (l.inear trend, F(1)=306.03, p< .01; 

and quadratic trend, F(l}=l06.02, p<.Ol}. 

1.10 

- F.gure 5-1. 

1976-1!1<!5 A U87·1lllll 

a-Il'llolo 

Aa 4 d' 

Accident rates for all Class I pilots for the ye&IS 1976-1985 and 1987-

1988 as a function of age. Pilots were grouped in 5-year intervals. 

The llUIIletator for !2!e was obtained by counting all accideats in the 

NTSB for the given group of pilots. The deaominalor was obtained 

by accurmlating from the medical database the total annualized bows 

flown during the yev: by pilots in the given group. See Table 3-6 for 

the annwilizalion factors. 

5.1.2 What Was the Relationship Between Age and Recent Flight Time for Oass I 

Pilots? 

Golaszewski's (1983) data suggested u'lat flight time affected accident rate 

and interacted with pilot age. That relations.!tip was exa1nined more closely for Oass I 

pi.lots with more than 2,000 hours of total flight time. A minimum 2,000 hours of total 

flight time was chosen because it "'-as the Air Transport Pilot (ATP) requirement for 

Part 121 pilots. A preliminary analysis determined how total flight time affected the 

accident rates of pilots with more than 2,000 total flight hours. With three levels of 

total flight time {2,000-5,000 hours, S,000-10,000 hou..rs, and > 10,000 hours), a11 

ANOV A showed no effect for total ffight hours and no interaction with pilot age. 

Therefore, subsequent analyses ignored total flight hours as a factor, other tlmn 

focusing on pilots witll more than 2,000 total flight hours. Figure 5-2 displays accident 

rates for Oass I pilots with more <.'Jan 2,000 total flight hours as a fu11ction of age and 

of recent flight time, where recent flight time v.-as defined as t.ie number cf hours 

5-2 
flown in the previous year. For those data, accident rate decreased with increased age 

until 40 and then leveled off (F(5)=34.01, p<.Ol), accident rate decreaseo with 

increased recent flight time (F(7)=415.75, p<.Ol), and the differences in accident rate 

among the recent flight time groups decreased v..ith increased age (F(35)=1.65, 

p<.Ol). 

40.01 

if ; 35.0 

§ _., :il 30.0 

g _..., .5 25.0 t l~ 20.o T 

=;;: 1s.o r 

1976-1985 & 1987-1988 

Clas I Pilots 

Total FliPt Tuae >2,1100 BoluS 

J---+--- U'! >100& <aZX) 

1 ~--- iL-.>'lOO&:<-XD 

; ---•· 1..""''>XOA~ I i --o- JF! >lOCI A: <-500 

~ 110.0 +==::.:-- ~a: s.o ~ ---=:•-------·-------·--------·--------.. 0.0 -·· i ; 6 ~ --=1 

!---<>--- I:FT>!r004 Oo6iX) 

l ----.:r-- EFr >SXI& <-1'0::1 

I 

i -o-- JU'T>'700 

' 

»34 35-39 4044 45-49 S0-54 55-59 

FtgureS-2. 

PilotAge 

Accident tates far all C'.ass I pilots "'ith more than 2,000 hours 

total flight time for the }'C2IS 1976-1985 and 1987-1988 as a 

:fimction of age and of recent flight hours (OOws flown in the 

pm:cding 12 months). Pilots are grouped in 5-year intervals. 

The ntl!llClatOr for !ate is obtained by counting all sccidents in the 

~"TSB fur the given grollp of pilots. The tknoo,.mllli)T is ooll!ined 

l:IY accumulating from the medical dalabase the total annnalizrrl 

hours flo...n during the year by pilots in the gi>..::n group. See 

Table 3-6 for the annualization factors. 

5.1.3 How Did Accident Rate Cham~e with A~e for Pilots with Relatively Hi~h 

Rm•nt Fli~ht Time'? 

The data of Figure 5-2 show that recent flight time was a crucial variable 

when stud)-ing accident rate, especially because it interacted v..ith the effects of age. 

Because Part 121 pilots typically had high recent flight time, Class 1 pilots v..ith at least 

250 hours of recent flight time were next examined, a group quite likely to include 

most Part 121 pilots. The data for those pilots are shO'\J\.11 in Figure 5-3. Accident rates 

changed v..ith age (F(5)=68.82, p < .01), initially decreasi.-,g and then leveling off 

(contrast for lin= trend, F(l)=247.06, p< .01; contrast for quadratic tr>...nd, 

F(l)=S0.37, p<.Ol). 

5-3 
lAloi:pre S-3. 

~"' 1Jil7-llW 

C..ll'!looa 

-liP< 'l'llloo >250 

Tac.J~Tiooe >:2800 

Accide::!t rates for all Class I pilots with more than 2,000 total flight 

hours ~ more than 250 recent flipt hours (hours flown in the 

p~ 12 monlbs) for 1976-1985 and 1987-1988 as a function of 

age. Pilots were gzouped in 5-year intervals. The numenitOr for me 

was oh!ained by COIIIIting all accidems in the 1\'TSB for the given 

group of pilots. ne denominator was obtained by I<)'Almulaljng from 

the medical d•tsbose the total anzmaJ;:zro hours flown dli..oing the year 

by pilots in the given group. See Table 3-6 for the annualiz:ation 

fzctms. 

A full-time pilot for a scheduled air carrier typically 1ogge-rl about 70 flight 

hours a month (Brown, 1992). Thus, it ·was likely that ~e group of Class I pilots who 

had 700 or more recent flight hours and more than 2,000 totai flight hours more closely 

fit a profile of scheduled air carrier pilots tha.TJ did the groups of Figure 5-3. To be 

sure that 700 recent flight hours was a reasonable number for Class I pilots, the 

distribution of Class I pilots as a function of age and recent flight hours v;as 

determined. Those data are shown in Figure 5-4. Clearly a substantial proportion of 

Class I pilots had more than 700 hours of recent fright time, independent of age. In 

genenU., 30.0 percent of Class I pilots with more tha11 2,000 total flight hou..--s had more 

than 700 recent flight hours. 

5-4 
1976-1985" 1!187-1988 

Class I Pilots 

Total F'li&lX T"ame >2,000 Hours 

; --o- U'!'>400 ... <>-500 i 

l 1 i ---<>---2FT>~- -=-60:1 i 

I~·-·- El'T>iOOII:<o-iOO l 

! ! ' - -·¢- -·· ZP'!'>700 l 

0~----------------------------~------ ! i 

35-39 

FtgureS-4. 

55-59 

Counts of pilots in the CDB for 1976-1985 and 1987-1988 with 

moR than 2,000 total flight hours as a function of age and of 

r=tt flight hours (hours flown in the preceding 12 months). 

Figure 5-5 shows accident rate as a function of age for Class I pilots with 

more than 700 recent flight hours and more than 2,000 total flight hours. Accident rate 

decreased with increased age and then leveled off (overall F(5)=23.62, p< .01; linear 

trend, F(l)=98.60, p< .01; quadratic trend, F(l)=12.74, p< .01). 

5-5 
120 

FJgUre5-5. 

U7~l!IIIS .. 19117-lllll!l 

a-I Nob 

-l!ipt "I-. >700 H... 

Tcal~t!ao >2,9110-., 

Accident 1llteS for all CIMs I pilots with more than 2,000 total flight 

bows and more than 100 recent fught hours (hours flown in the 

preceding 12 months) for 1976-1985 and 1987-1988 as a function of 

age. Pilots were grouped in 5-y= intervals. The numemtor for !ale 

was obtained by counting all accidents in the !I.'TSB for the given 

group of pilots. The denonlimltor was obtained by &CCUm".zlating from 

the medical database the total annualized hours flown during the year 

by pilots in the given group. See Table 3-6 for the ::nnualization 

factors. 

Given the power of the CDB, the above analysis could be further refined. In 

particular, the medical and certificate databases provided information about the pilot's 

employer and the pilot's level of certification. We chose to again examine accident rate as 

a function of age, restricting our attention to pilots with ATP ratings v.-ho were employed 

by major airlines and who had more than 700 recent flight hours. The data for those pilots 

are shown in Figure 5-6. Analysis of those data was problematic, for two reasons. First, 

the certificate data about when a particular certification was obtained were only the 

current certifications for a pilot, and, second, because t\1ose pilots had so few accide11ts. 

The lower the probability of an accident the mon· fragile (unreliable) is t.~e statistical 

analysis. Thus, we were confronted with a statistical uncertainty principle: the more 

refined the analysis, the less reliable is the analysis. For the data of Figure 5-6, there was 

no effect due to age (F(5)=0.84). 

5-6 
J-.DII541!1117-JWB 

a-JWldoAW ...... A_ft&lol_ >'IOOBoars 

oro+---------~------~---------+---------+--------~ 

Accident ntes for all Class I pilots with more than 2,000 total flight 

houts ad more than 700 recent flight bows (bouts flown in the 

preceding 12 moDths), who bad m ATP rating, aDd who were 

employed by a Jn1!ior airline, for 1976-1985 ad 1987-1988 as a 

fimctloa of age. Pilots were jlouped in 5-year intervals. The 

liUIIIIlralor for rate was obtained by counting all accidents in the NTSB 

for the Jivea group of pilots. The denominator was obtained by 

am•mnloting from the medical dofl!base tb: total annualized hours 

flawD dJuine the year by pilots in the givea jl011p. See Table 3-6 for 

the IIUI1!a'Jiption factors. 

5.1.4 Wbat Was the Relationship Between Aee a.'ld Recent Flight Time for Class 

Hpj1ots? 

As pointed out in Section 4.1, the data for Class II pilots were not very useful 

for our purposes, because groups of Class II pilots are heterogeneous. Nevertheless, for 

the sake of completeness, accident rates for Class ll pilots were briefly examined. Figure 

5-7 shows the accident rates of Class II pilots as a f.mction of age. Note that here the 

data for pilot ag~ 30 through 69 was examined. For those data, accident rate decreased 

with age, leveling off for older pilots (overall F(7)=12.30, p<.Ol; linear trend, F(l)=S9.70, 

p<.Ol; quadratic trend, F(l)=10.16, p<.Ol}. 

5-7 
IJIO 

l 1.110 

J om 

J e 5.00 Eg 

§=4.00 gl jl=3.oo 

l 2.110 

~ 1.00 

__ ... 087--

a..D!IIoD 

All' '] 2 

0.00+------+------+------+------+------+------+-----~ 

~34 

F!pft5-7- Accident rates for all Class II pilots for the y:la!S 1976-1985 and 

1987-1988 as " function of age. Pilots wme grooped in 5-year 

intervals. The !llllDelalor for me wu obtojned by counting all 

accidents in !he NTSB for tbe Jiven group of pilo!s. The denominator 

was obl&ined by IICCUIIIIIlatiD from the medical database the lotal 

unma!ized bours flown during the y- by pilots in the given group. 

See Table 3-6 for the azmualizati.on fllclors. 

5.1.5 Whit Was the Relationship Between Age and Recent Fli~ht Time for Class 

ill Pilots? 

The accident rates of Class m pilots were examined, starting with a broad 

picture of Class ill pilots, followed by rr.ore narrowly focused pictures. Figure 5-8 

presents accident rates for ail Class ill pilots. Just as for all Class I pilots and for all Class 

n pilots, accident rate decreased with age for all Class m pilots, leveling off for older 

pilots (overall F(7)=27.49, p<.Ol; linear trend, F(l)=l65.34, p<.Ol; quadratic trend, 

F(l)=l2.16, p<.Ol). 

5-8 
14.00 

!!!1 

li: 12.00 

J 10.110 

~~ 1.00 ij 6.110 

l 4.110 

I 2..110 

0.00 

»-34 

F"!pl'e!-8. 

U76--AIJII7..U. 

~mAIU if , 

35-:19 4s-49 !0-54 ~59 

-· 

Accideat rates for all Clr.ss m pilots for the yean; 1976-1985 and 

1987-1988 as a fimction of age. Pilots were grouped in 5-ycar 

intemds. The Il1lmeilltor for rate was obtained by counting all 

accideats in the NTSB for the given group of pilots. The denominator 

wu obtained by accumulating from the modical database the total 

azmualized hours flown during the year by pilots in the given group. 

See Table 3-<i for the ann-ola!Uation factors. 

Next, the focus was on Class m pilots who were relatively experienced in 

terms of total flight time and relatively practiced in terms of recent flight time. The 

distn"bution of Class m pilots as a function of recent flight time showed that 27.8% of 

Class m pilots had more than 50 hours of recent flight time. That is the percentage of 

Class m pilots with more than 50 hours of recent flight time (30.0"/o) was roughly the 

same as the percentage of Class I pilots with more than 700 hours of recent flight <ime 

(30.0%). Consequently, we chose to examine the accident mtes of Class III pilots with 

more than 50 recent flig.ltt hours and more than 500 total flight hours. Those data are 

shown in Figure S-9. Accident rate decreased with age, leveling off for older pilots 

(overall F(7)=6.75, p<.Ol; linear trend, F{l)=33.86, p<.Ol; quadratic trend, F(1)=7.23, 

p<.Ol). 

5-9 
9.00 

J 1.00 

7.00 

l j 1.00 

h'm jl4m &: Jm 

I 1.00 

tm 

om 

JG-34 

___ .., ___ 

a-mlliT >'!A 

TIT >AI 

35-39 4S.09 5(1.~ 'S.S9 

PilOt Ale 

Accident rates for .n Class m pilots with more than soo total flight 

bows and more than SO recent flight bows (boas flown in the 

preceding 12 months) for the years 1976-1985 mel 1987·1988 as a 

fimcti011 of age. Pilots were grouped in S-year inte:vals. The 

numerator for rate was obtained by counting all accideuts in the NTSB 

for the given group of pilots. The denominator was obtained by 

ICCUII1Ulating from the medical database the total amwa1ized hou.-s 

flown during the year by pilots in the given group. See Table 3-6 for 

tbe annualization factors. 

Whereas the membership of the groups of pilots underwent dramatic change at 

age 60 for Class I pilots, no such change occurred for Class m pilots. Thus. while Class 

m pilots differed in many ways from Class I pilots. their accident rate after age 60 

revealed more about the general effect of age. Further, because accidents were more 

numerous for Class m pilots, analyses of accident rate were statistically more reliable. In 

particular, the accident rate for each year of age could be examined in a more robust 

manner, rather than aggregating pilots in five-year age categories. Our main interest lay in 

the years near age 60. Thus, we examined the accident rates of Class ill pilots who had 

more than 500 total flight hours, who had more than 50 recent flig.ljt hours, and who were 

between the ages of 50 and 69. Those data were shown in Figure 5-10. For those pilots, 

age had no effect on accident rate (overall F(19)=0.99; linear trend, F(l)=O.l2). 

5-10 
U76-HIIS.J:DII7- Ciooom,_ 

UT>SI-.J: 

TIT>RI0~~~--+-~~--+-~~--+-~~--+-~~--+---~~+-~ 

~ ~ ~ n ~ ~ ~ ~ ~ ~ ~ a ~ s ~ ~ ~ ~ M $ 

Pilotll&e 

Fipre 5-18. Accident rates for Class m pilots between lhe qes of so and 69 with 

JIICltelbm 500 total flight hours and - tbm so recent flight hours 

(hours flown in the pT"C"'ting 12 months) for the years 1976-1985 and 

1987·1988 u a fimction of age. Pilots were grouped in single-year 

intervals. The numerator for tale was obtained by counting all 

ICcidalts in the NTSB for the &iven group of pilots. The denominator 

was obtained by "CC'U'PJ!ating from the modical datwbao;e the total 

amrualiud hours flown during the year by pilots in the given group. 

See Table 3-6 for the arnmali'D!tion factors. 

5.2 Longitudinal VIew of Accident Rates 

5.2.1 Could the Accident Rates of Pilots in the Same Bi!th-Cohort Be Examined 

OverTime? 

Yes. All pilots born in a particular period could be characterized for a 

particular year in the database, and those pilots with the same characteristics who 

appeared in the database in subsequent years could be identified. Then the accident rates 

of the group whose membership changed to some degree each subsequent year could be 

computed for each year. By necessity, previous studies approached the data from a crosssectional point of view, examining pilots of different ages at one particular time. 

However, the greater scope of the data in. the CDB afforded a more lon6itudinal view. To 

take advantage of that powerful feature, cohorts of pilots for the years 1975-1985 were 

studied. Because there were some changes in group composition over time, this was not a 

true longitudi'll!.l study but was referred to ;.'1 this report as quasi-longitudinal It would 

have been desin;.ble to follow the cohorts longer, i.e., from 1976 to 1988, but the absence 

5-11 
of data for 1986 made such an analysis problematic. The analyses descn~ below 

focused on Class I and Class m pilots with hig.lt flight hours. In each case, the accident 

rate of a group of pilots born during a particular 5-year period was exanli11ed in each of 

the ten years from 1976 to 1985. For example, pilots born in 1952-1956 were followed by 

computing the accident rate of20-24 year-ollis in 1976, the accident rate of21-25 yearaids in 1977, the accident rate of22-26 year-olds in !978, etc. In this fashion, pilots in a 

particular birth-cohort could be tracked over a ten year period. 

5.2.2 ~Did a Onasj-Lonmil.!dinal Analysis of Class I Pilots Show? 

Figure 5-11 displays accident rates for Class 1 pilots with more than 700 recent 

flights hours anci more than 2,000 total flight hours as a function of year of birth and as a 

function of the year in which the accident occurred (1976-1985). The data ofFigUre 5-I 1 

can be thought of as overlapping snapshots of the curve relating accident rate to age. For 

example, the pilots bom from 1946-1950 appear as 31-35 year olds in 1981, v.ilile the 

pilots born from 1941-1945 appear as 31-35 year olds in 1976. Note that the various 

groups suffered both from attrition and from accretion as some pilots fillied to renew their 

certifica1ion and other pilots gamed initial certification or renew lai,')sed certification. For 

those data, accident~ decreased with age, i.e., time from birth (F(4)=23.49, p<.Ol), 

decreased with year in which data were collected, i.e., a second way to measure age, 

(F(9)=5.35, p<.Ol), and the decrease in accident rate with year of data collection was 

greater for younger pilots than older pilots (interaction of age and year of data collection, 

(F(36)=2.03, p<.Ol). Accident rate initially decreased as function of age (linear cont:ras+., 

F(1)953.76, p<.Ol), and then leveled off (quadratic contrast, F(1)=28.46, p<.Ol). 

Accident rate linearly decreased as a function of year of data collection (linear contrast, 

F(1)=44.30, p<.Ol). Figure 5-12 displays the data of Figure 5-11 as a fun..--tion of age, 

distinguishing the pilots by date of birth. The data were obtained directly from Figure 5-

11 by shifting the curve for the pilots bam from 1941-1945 five years to the right, shifting 

fue curve for 1he pilots born from 1936-1940 ten years to the right, etc. For the data of 

Figure 5-12, accident rate decreased as a function of age (F(4)=4.06, p<.OI), as a function 

of the year in which the data were collected (age from a different point of '1-iew, 

F(3)=11.08, p<.Ol), and accident rate~ lower when the data for an age group were 

coliected five years later (F(l )=6.43, p<. OS). 

5-12 
3.50-

3.110 I 

l~! .. 2.110, 

y_._....(Ap~ 

!

--·-........ , 

1

=::::::::, !! -.uo __ __.,_._ l11Sl--»~~ I 

r1 

lt.oo i~t-.,.-.-t 

~ 03) 

om 

1916 !977 tm 1979 1910 19S1 19!2 1913 1- 198S 

~yYJ&Ure 5-lL Al:cidmt r&les for Class I pilots wlth more !han 2.000 toll! flight 

hours md more than 700 =mt flight homs (hours flown in the 

pteo;oljr~ 12 m!llllbs) for 1be }UIS 1976-1985 md 1987-1988 as a 

fimcti<m of dm of birth md of the year in '\Wi;::b the data were 

collected. Pilots were gxoupet! in 5-year intavais according to date of 

birth md in single year inlerva1s mniiug to the year in '\Wi;::b the 

data were colkc:!ed. The oldest age fur including pilo(s was 59. The 

num=ator fur rate was oblzined by coonti!lg &II accidmts in the ?lo'TSB 

for the give:! group of pilots. The de!lominatDr was obWned by 

WX1Il!!JHating from the medical d•talwse the Ictal llllmlali=i h<lurs 

flown durmg the Yf!S!4: by pilots in the given group. See Table H for 

the a:nntlllization factcrs.. 

The data ofFigures 5-11 and 5-12 are quite striking. They appear to provide 

various vi...->wS of an underl}ing curve showing accident rate decreasing with age. Only 

pilots under 60 were included for the data of Figures 5-11 and 5-12, because the age 

groups over 60 had a dramaticaLly different membership. The milder changes in the 

groups under 60 as time passed could also explain the decrease of accident rate with age. 

If poorer pilots dropped out of the groups and better pilots entered the gronps ·with the 

passage of time, :hen the accident rate would go do~-n. An absence of cha.11ges in the 

membership of the groups over time would argue agaim."t this interpretation. This 

question will be examined in more detail below. 

5-13 
~~~~~~~~~~~;~~~~~~~~~~~~~~~~~~ 

&o&cAF otS.,...Ca>a:< 

--y-~ 

j---~ 

~--<>---... 

,----:~ 

' 

1

___ 

--6-- -~ ,.,... 

F~ 5-:U. Accident nues for Class I p~.."'ots with !llD!'e than 2,000 total :ffigb1 

hours cd """" than 700 recmt flight boars {hollis flown in the 

p!eceding 12 m:mlhs) for the ye&rS 1976-1985 aDd 1987-1988 as a 

f.mction of dale of birth cd of qe year in which !he elm. we:-e 

collo::sed. Pilois ~ grCJtl!"'d in 5-year inten>als acwnling to dale of 

bitlh and in single year inteov2Js a:cor:ling to the year i'l which the 

dala were collectl:d. This figure recapitalms the dala of Figure 5-11 

by Jistin& the various groops acwtding to the ending age of each 5-

y- cobort.. The oldest age for inclur.iing pilots wzs 59. The 

".:meratot for.- was oblained by cou:nting all accidents in the :1\"TSB 

for the given group of pilots. The Oonominotor "''liS o~ by 

• '"'""iating from the medical datpbose the total mnnalized hours 

:flown during the year by pilols in the given group. See Table 3-6 for 

tbe ll!llmalizzti<l!l fildors. 

5.2.3 \\!hat Did a Onasi-l.on~J Analysis of Class ill Pilots Show'! 

Longitudinal analyses analogous to the ones in Se::!ion 5.2.1 w= ca:rried 

out for Class m pilots who were between the ages of 26 and 60 in 1976, who had more 

than 500 to121 flight hou.-s, and who had more than 50 recent flight hours. Note that 

for Class m pilots the data extended to pilots as old as 69, whereas in the longitudinal 

analysis for Class I pilots the pilots were no older t.'lan 59. Figure 5-13 presents the 

accident rates of C'JaSS ill pilot.s as a function of year of birt.h and of year in which the 

data were collected. For those data, accident rate decreased as year increased 

(F(9)=6.93, p< .01), accident rate dc....---eased as ti.:ne from birth increased 

(F(6)=7.1l, p< .01), and the decrease over yea..'"S w-as greater for the younger pilots 

5-14 
(mteraction, F(54)=1.52, p< .01). Finally, the decrease in accident rate over years 

was strictly linear (linear contrast, F(1)=53.82, p< .01). 

The data for the Class ill pilots mirrored the data for the Class I pilots, 

except that there was no leveling off of accident :rate with year for the Class m pilots. 

16.00 T 

1.am 

--

4- ..... ' i 

• 

, " ' 

' ' ' 

l~~~ 

I, 

j ·---l"'l..UG:-:t,fl 

!..__!.,....~ 

I j - -+--· ~I!Jl.S.S4t~~ 

j~:tQ6.-~ 

1 --- !C-:5($~.$:$3 

i 

~ \ -.r- m~:o~ 

1!176 I917 19ll 1979 l91l 19Cl l3!:l 1m 19M !9!5 

j 

\ 

FJ~Ure S-13. 

DD.Yt:a: 

Accidmt rates ro.- Class m pi.l.>ts ... m more lila;J. 500 tot::<l !light 

hours and more than SO :=t flight hours {boors flown in the 

prec< ding i2 months) fm the yearn 1976-1985 md 19&7-1988 as & 

timction of date of birth and of the year in which the elm were 

collected. Pil~ were grouped in 5-yea:- intervals =rding to dale of 

birth :ll'd in single year inten'&l.s accor-'....ing to the year in wllich the 

data w= collected. The oldest age for incl'toding pilots was 69. The 

numerator for r:ate W2S obtained by coccting all accidents in the STSB 

for the given groop of pilots. The deaD~ was obtained by 

accuiiilllating from l!le mediC&! d2:siwse the toW moualired !:oms 

flown dnring the year by pilots in the gn= group. See Table 3~ for 

the znnnaiintion fzctors. 

Figure 5-14 recapitulates the data of Figure 5-E in the same "''3.Y that 

Figure 5-12 recapiU!iates the data of Figu....-e 5-1 I. For the data of Figure 5-14 accident 

:rate decreased as a function of age (F(5)=4.19, p< .01), accident rate decreased as a 

function of the year in which the data were collec.ed (a clli"'ferent V:ew of ~oe, 

F(4)=3.35, p< .01), accident rate "''as lower when the data for an age group were 

collected five years later (F(l)= 19.54, p< .01), and the de!2ils of the changes in 

accident rate over time differed for the va.-ious groups (triple interaction, P(20)=1.58, 

p< .05). 

5-15 
F!Jift 5-14. 

I --------- 1""""' jl 

I--~- HIU-45 l---...... 1 1 ---·;!;-·-- lftl~ ! 

i • 

t~U»3t! i i 

l 

_____ ,.j 

.. ' ---+---- tfi6.lO J 

A<cident nileS for Class m pilots with - thm 500 total flight 

hours md more thm SO r=t ffiiht hems (hems ftawn in the 

p1ectding 12 mo<tlhs) for the years 1976-1985 md 1987-1988 s 11 

f1mction of date of birth &Dd of age year in Which the data ~ 

col1ec:tod. Pilots wee gwuped in 5-year intetwls .occwding to date of 

birth md in single year inl="als acc:mliDg to the year in whil:h the 

data were colleded. This figure ro:apitlllatcs the data of FigUre 5-11 

by 1istiDg !he various groups accotding to tbe eoding age of e.ch 5· 

year cohort. The oldest age for ir.cluding p'.l<>ts was 69. The 

~for :m --.s ob«ained by counting an accide<lts in the NTSB 

for tbe given r-oup of pilots. The clenominotor W!lS obtained by 

..,.,mmlating from !he medical database tbe total :tmrl!31iw hams 

fiOW!I. during the year by pilots in the givm ll""'P· Sec Tabk 3-6 for 

the mnnaJinrion fac.ttk-s.. 

5.3 Analyses of Accident Frequencies 

A number of analyses were colbidered, based upon the accident records 

originating in the NTSB database. First, a.'lalyses were considered which were based 

upon the Chi-Squa..<-e statistic, and then some :malyses were considered based upon the 

analysis of variance (ANOV A), i.e., t.'le F statistic. 

In all of the Chi-Square analyses, t!le accidents were categorized according 

to the age of tl1e pilot and according to some second factor, e.g., season of the year, 

5-16 
and then the number of accidents were counted for each combination of age category 

and second factor category. Thus, if the ages were categorized as 30-34, 35-39, ... , 

55-59 (six categories of age) and the second factor was season of the year (four 

categories), then there would be 6 x 4 = 24 wcells• each containing the number of 

accidents appropriate for the cell, e.g., accidents by 30-34 year olds in winter. 

The Chi-Square analysis was appropriate for such data, so long as the cellentries were "reasonably large" (usually taken to mean numbers >5; Hays, 1973). 

The Chi-Square statistic answered !he question, "Was it reasonable to believe that the 

proportion of accidents in each of the categories of the second factor did not depend 

upon age'?- Thus, when we had a significant Chi-Square (here taken to mean p> .05), 

we concluded that "the proportions of accidents among the various categories of the 

serond factor varied as a function of age. • 

In all cases, all accidents occurring from 1983 to 1988 for Class I pilots 

were considered. 

5.3.1 Chi-SfC!lllre Analyses 

5.3.1.1 Did the proportion of pilots with a medical waiver change as a function of 

age? 

Yes, Chi-Square(5)=12.99, p=.024. A greater proportion of the older 

pilots in accidents had medical waivers than did the younger pilots. The proportions 

for !he various groups are displayed in Table 5-1. The increase in proportion of 

medical waiver for older pilots in accidents could reflect a con'Cemitant increase for all 

Class I pilots. To check this, the CDB was used b obtai., the proportion of all Class I 

pilots with a medical waiver as a function of age, where attention was restricted to 

pilots examined between 1 February 1988 and 30 June 1988. Those data are displayed 

in Table 5-2. The proportion of pilots with medical waivers differed with age, ChiSquare(5)=102.40, p<.OOl. The patterns seen in Tables 5-1 and 5-2 differ somewhat, 

but for both tables, the older pilots had more medical waivers, and it did not appear 

that possess!on of a medical waiver was implicated with having an accident. 

5-17 
Table5-L 

Pe<ceut 

Pen:eut of Class I pilots who had a medical waiver acd were mvolved 

m an accideolt as a function of age. Dala are from the NTSB d••abase 

fur the years 1983-1988. 

Age 

30-34 35-39 40-44 4549 50-54 

4.8 3.6 3.1 4.9 7.0 

Number of A<:c:idents 419 415 318 224 200 

Table 5-1. 

Pe<ceut 

Numbc:c of Pilots 

Pen:mt of Class I piloo who had a ,c!jcal waiver as a function of 

age. Dala are from !he Medical dmbue fur 1 Fcbnwy 1988 to 30 

Iuuel988. 

Ap 

30-34 35-39 40-44 45-49 50-54 

9.1 8.1 6.8 6.3 6.9 

10291 9479 10329 10085 7595 

SS-59 

10.3 

116 

55· 59 

9.9 

4008 

5.3.1.2 Did the proportions of accidents in the various seasons of the year change 

with age, if we defined the seasons by the quarters of the year? 

No, Chi-Square(l5)=24.04, p> .05. 

5.3.1.3 Did the proportion of accidents that involved (at least in part) pilot error 

vary with age? 

No, Chi-Square(5)=4.75, p>O.OS. 

5.3.1.4 Did the proportion of accidents in which there was a weather visibility 

restriction depend on age? 

No, Chi-Square(5)=8.27, p>O.OS, although it is worth noting that the vast 

majority of the accidents involved such a restriction. 

5.3.1.5 Did the proportions of accidents during 'l.'arious times of day (daylight, dusk, 

nighttime, dawn) vary as a function of age? 

A careful analysis of this question would involve taking the geographical 

location and the time of year into account in determining when dusk and dawn occur. 

We crudely defined dusk as the hours 16:30 to 19:39 and dawn as the hocrs 4:30 to 

7:30. For this crude approximation the answer was no, Chi-Square(l5)=11.78, 

p>O.OS. 

5-18 
5.3.1.6 Did the proportions of accidents during various phases of flight ( (a) takeoff, 

climb, (b) approach, descent, landing, (c) other) vary as a function of age? 

No, Chi-Square(10)=14.82, p=O.lS. 

5.3.2 Analyses of Variance CANOVA) 

The NTSB recorded the amount of recent and total flight time flown by the 

pilot in the same type of aircraft as the one in which the accident occurred. For each 

year of age, the average amount of recent flight time and of total flight time the pilots 

spent in an aircraft of the same type was computed. Thus, for each group of five years 

(30-34, ••• , 55-59), we had five data points. To those data a one-way ANOVA was 

applieci. 

5.3.2.1 Did the tolal time in the same type aiicra..."t vary as a function of age? 

Yes, F(5,24)=5.66, p<.Ol. The older the pilot, the greater time spent in 

the same type aircraft. This was not surprising. The data are displayed in Table 5-3. 

Table 5-3. Mean number of tola1 flight hours, as a fimcticn of age, in lhe same 

type of air::nft as !he oae in .wich m accident occurred. 'I'he5e data 

we:e for Class I pi1oCs involved in aa:idmts during 1983-1988. 

Mean hours 

Total Flight 

A2e Tune 

30-34 601 

35-39 727 

40-44 755 

45-49 1,143 

50-54 1,232 

55-59 2,094 

5.3.2.2 Did the recent time in the same type aircraft vary as a function of age? 

No, F(5,24)=0.56, p> .50). The data are shown in Table 5-4. One 

might hypothesize that lack of recent experience with an aircraft was more 

likely to lead to an accident for a pilot with less overall experience with the 

aircraft, !mt the data (Sections 5.3.2.1 and 5.3.2.2) lent no support to that 

hypothesis. 

5-19 
Mean number of recent fliaht haws. as a function of age, in the same 

type of aircr.lft as the oae in which 1111 ac::cic!mt occuned. These data 

were for Class I pilots involved in aa:idem:s during 1983-1988. 

Mean hours 

Recent Flight 

Age Group Time 

30-34 57 

35-39 51 

4(}.44 52 

45-49 46 

S0-54 55 

55-59 43 

5.4 Limit.atioos Placed on the Analyses by the Data 

All analyses had been conducted on intact data. This meant that the "groups 

of interest• were self-selected in numerous ways and were not under experimental 

control. Thus, extreme care had to be taken to be sure that other factors were not 

confounded with factors examined in this study. Below, two possible confounding 

factors were considered in detail, factors we had previously alluded to: the change in 

membership of groups over time and the possibility that the number of takeoffs per 

flight hour changed with age. 

5.4.1 Wbat Were the Chanees in MeJl'lbershiD Associated with A~e? 

Change in the membership of groups is best illustrated in the context of the 

data shown in Figures 5-11, 5-12, 5-13, and 5-14. Those figures purport to follow the 

same pilots over 10 years, but, as suggested at the end of Section 5.2.1, this was only 

partially true, because the membership of the groups changed to some extent each year 

as some pilots allowed their medical certificates to lapse and other pilots obtained their 

initial certificates or :renew lapsed certificates. lf the changes in the membership of the 

groups we.re small, then those changes would have, at most, small effects on the 

accident rates. Figures 5-15, 5-16, and 5-17 view from two different perspectives the 

degree to which groups changed in membership. The data in these figures are not 

exhaustive but indicate the nature of the problem. An exhaustive study of the problem 

would only serve to determine the precise size of the problem but would provide no 

insight into how changes in membership of the groups affected accident rates. Figure 

5-15 displays the change in membership, from one year to the next, of the group of 

Class I pilots aged 36-40 in 1976, with at least 250 recent flight hours and at least 

2,000 total flight hours. The left (black) bar of a pair gives the number of pilots in the 

group fer the first year, and the right (gray) bar gives the number of those pilots still in 

the group the following year. For example, of t.'le approximately 11,800 pilots in the 

5-20 
group in 1976, approximately 9,200 remained in 1977. Meanwhile, the group in 1977 

consisted of approximately 12,200 pilots, infOI'bla.tion that can be gle.med from the set 

of bars for 1977-1978. Approximately 85 percent of the pilots appearing one year 

were still present the following year. In general, the group for the followi..-1g year was 

larger than the group the previous year so that the "holdovers" represented less than 

85% of the pilots the following year. 

~ • 8 

l 

1tiOCO 

1CXX) 

120CD 

1COCO 

ICilO 

IICIX) 

CXlO 

2000 

0 

PUotR.-doa8-..ly 

a-IPUo111 

R-tFIIghtl'he -· T~tal Flight 111M >2.GCO Hovro 

AeeGroup:-

1175-77 1W77-78 1Jn-79 1178-10 l.,..l l!Bi-.»2 ll82-a3 1lJS3.84 1984-85 

y_, 

:FiprE 5-15. Count of Class I pilots aged 36-40 with more lhan 2,000 total flight 

hours aDd more lhan 2SO !:llCalt flight hours (llour flown the 

prcc:tding 12 months) fur the yean; 1976-1985. The Walt bar gives a 

count of all pilots who ~ in the given year. The light bar 

gives a oount of those pilots who appeared in the following year and 

in the liven year, i.e., the light bar measures retention. 

One might infer from the data of Figure 5-15 that the groups had changed 

membership completely after about 5 years, but this assumes that pilots who leave a 

group never return. The data of Figures 5-16 and 5-17 suggest this is not the case. 

Each figure follows the change in size of a group over ten years and contrasts that with 

the number of pilots from 19n who appeared in subsequent years. Figure 5-16 

displays data for 26-30 r-ar old, Class I pilots, and Figure 5-17 displays data for 46-50 

year old, Class I pilots. In each case, the change in count for t.lte pilots originally 

counted in 1976 was largest the first year. For the younger pilots, there was actually a 

slight increase in count in later years as pilots appare.'ltly renP.wed lapsed certificates 

more frequently tha.'l they let them lapse. For t.lte older pilots, the irJlux of new pilots 

led to minimal changes i.'l the membership of the group originally counted in 1976. On 

the other hand, the group was decreasing substantially in size in the iater years, 

5-21 
probably reflecting the effect of the Age 60 rule. For younger pilots, the groups were 

changing substantially in size because of the influx of new pilots, and for older pilots 

the groups were changing in size because of attrition. In either case, the groups 

underwent substantial change in membership, opening the door to a confounding of 

changes in membership with age. 

25,000 

20.000 

1976-1!1118 

Refe-Shidy 

C..IPI!als 

Aae llllf'l': 26-30 

-- ! 15000 l . ---a-J.udila 

it 

10.000 -..... ... 

5,000 + .. ---~----+----+--------·----.-------------~ 

o~=*==*==*==*==*==*=~==*=~==*=~ 

~ n n ~ ~ n ~ c u c n ~ 

Yar 

---+--- a-.1-m 

Figure 5-16. Counts of Class I pilots aged 26-30 for the years 1976-1985 and 

1987-1988 as a function of year. The top tine CC".Illls all pilots. The 

secoad tine counts those pilots appearing in 1976 and in the given 

subsequent year, i.e., the data point for 79 counts those pilots "'no 

appeaRd bolh in 1976 and 1979, a measure of retention. The bottom 

two !iDes count those Class I pilots appeariJlg in 1976 who appeared 

in a subsequent year as a Class n or Class m pilot. 

As an aside, it is interesting to note that Figure 5-17 shows that very few 

Class r pilots who allowed their medical certificate to lapse continued to fly, i.e., they 

usually did not get Class II or Class m medical certificates. Thus, the accident rates of 

Class II and Class ill pilots should have been relatively unaffected by an influx of 

former Class I pilots. 

5-22 
5.4.2 What Were the Difficulties in Estimating Exposure? 

In all of the analyses, exposure was measured in terms of the number of 

flight hours. However, accidents were more likely to occur during takeoff and landing. 

For example, Trammell (1980), in a study of corporate flight, found that 47 perce.tt of 

the accidents occurred in the landing of the aircraft phase which represented 3 percent 

of the total flight time. All things being equal, pilots flying longer flights should have 

had fewer accidents per flight hour, i.e., a lower accident rate. It is reasonable to 

assume that older pilots of scheduled air carriers could exercise seniority to opt for 

longer flights thus reducing their risk of an accident. If so, then age was confounded 

with length of flight, masking an increased likelihood of being in an accident. If, on 

the other band, the number of flights per hour was constant with respect to age, then 

flight hours, as a measure of exposure were not confounded with age. The data from 

the NTSB database were used to assess this question, at least for pilots in accidents. 

10000 

19'76-191111 ·-·Siady C.. I Pilots 

Ale ;, 1976: ""!Ill 

moot-'·-~~=--=-------~-~------------ -- ______ ..,. ____ _ 1 6000 -----... d ---......... 

t ~ «!00 ' ', "-........... 

20GOO -.=1 tF==*==*==t=~~::::::=:: I I =t= t t i t i : · : 

76 T7 '71 79 1!0 II 12 13 U 8S 17 

1---"""·-1 1----.,_,_ i 

1

---·---· I =·--·---a.:- DJ ___j 

Fipre5-1'i. Counts of Class I pilots aged 46-SO for the years 1976-1985 and 

1987-1988 as a function of yea:. The top lille counts all pilots. 

The second line counts those pilots ~ in 1976 and in the 

&M:n subsequent ye.a, i.e., the data point for 79 COliDis those 

pilots wbo :q>peUed both in 1976 and 1979, a measure of 

reteation. The bottom two lines count those Class I pilots 

lppellring in 1976 wbo appeared :i:l a subsequent year as a Class 

n or Class m pilot. 

5-23 
The :!'.'TSB database includes fields to record the number of takeoffs by the pilot 

in the last 90 days, however, approximately 80 percent of the time this field was empty 

for Class I pilots and therefore could not be meaningfully analyzed. Additionally, 

whether age was confounded with number of flights or flight hours was not the sole 

criterion of whether flight hours were a good measure of exyosure, although it was 

most relewnt in this case. Night flight time, weather, etc. also influenced quality of 

exposure. 

5-24 
6.0 SUMMARY AND DISCUSSION 

The foundation for analyzing data from the CDB was based on the 

justification presented in Section 4, which supported traditional statistical analyses. 

Aggregating data from 1976-1988 (excluding 1986) provided a more extensive data set 

and improved the reliability of the analyses. 

6.1 Conclusions Based Upon Flight Time Analyses 

When the accident rate for each medical certificate class of pilots was 

examined as a function of age (Figures 5-1, 5-7, and 5-8, for Classes I, II, and m, 

respectively), a decrease in accident rate was found for the younger pilots, followed by 

a leveling off for older pilots. 

The data of Figure 5-2, which display the accident rates of Class I pilots 

with more than 2,000 total flight hours, show that the more recent flight time a pilot 

had, the less likely the pilot would be in an accident. Indeed, recent flight time was the 

dominant factor affecting accident rates. Further, for Class I pilots with more than 

2,000 total flight hours, no effect of total flight time on accident rates was foqnd. 

The data of Figures 5-l, 5-2, 5-3, 5-5, and 5-6, represent progressive 

attempts to home in on groups of pilots that ar: most typical of Part 121 pilots. With 

the exception of the data of Figure 5-6, for which no eff~t of age was found, all the 

data indicated a modest decrease in accident rate with age, with a leveling off for older 

pilots. 

When the rates of Class m pilots aged 50 to 70, with more than 500 total 

flight hours, and with more than 50 recent flight hours were examined as a function of 

age, year by year, no effect for age was found (Figure 5-10). 

6.2 Conclusions Based Upon the Quasi-Longitudinal Analyses 

Accident rates of Class I and of Class m pilots with high recent flight time 

were examined from a longitudinal perspective, i.e., various cohorts were followed for 

a 10 year period. Again, accident rates initially decreased with age and then leveled 

off (Figures 5-11, 5-12, 5-13, and 5-14). 

6.3 Conclusions Relevant to the Age 60 Rule 

The Age 60 rule :ip?lies to pilots employed by scheduled air carriers. 

Lacking the ability to directly determine the flight hours of that specific groUP of pilots, 

6-1 
the accident rates of reasonably comparable groups were examined, i.e., Cl..ass I pilots 

with at least 2,000 total flight hours and at least 700 recent flight hours, and pilots with 

more than 700 recent flight hours who had ATP certificate altd who were employed by 

a major airline. For the former group, accident rates decreased with age, leveling off 

for older pilots (Figure 5-5), and for the latter group no effect was found due to age, 

probably because of lack of statistical power, i.e., the sample size was too small. 

In an attempt to examine accident rates for the age range 50-70 and to 

minimize the possible confound of older pilots of scheduled carriers having fewer 

takeoffs and landings rr flight hour (which would mask an increase in accident rate), 

experienced Class m pilots with high recent flight time were examined. For Class m 

pilots with at least 500 total flight hours and at least 50 recent flight hours, age had no 

effect on accident rate (Figure 5-10). 

Our analyses provided no support for the h}pothesis that the pilots of 

scheduled air carriers had increased accident rates as they neared the age of 60. Most 

of the ar.alyses indicated a slight downward trend with age, but those results must be 

treated cautiously because of the number of potentially confounding factors. The data 

did provide indirect evidence that any changes in takeoffs and la."ldings per flight hour 

with age had little affect on accident rate, because such an effect would only occur for 

Part 121 pilots exercising seniority. Yet the data for all the various groups of pilots 

were remarkably consistent in showing a modest decrease in accident rate with age, a 

trend shared by the data of FJgUre 5-5. That is, the same modest effect of age appeared 

in all the data and was not solely due to changes in takeoffs per flight hour as the pilot 

aged. On the other hand, substantial changes in membership of the groups of pilots 

from year to year made interpretation cf the modest decrease in accident rate with age 

problematic. It was as easy to conclude that the FAA's system improved the 

composition of the groups over time as it was to conclude that pilots' performance 

improved with age. 

In all of our analyses, we saw no hint of an increase in accident rate for 

pilots of scheduled air carriers as they neared their 60th birthday. There were no data 

available on scheduled air carrier pilots beyond age 60. To wh'it age could retirement 

for those pilots be safely put off! This question must be answered very conservatively 

because of the possibility of catastrophic results. 

Statisticians distinguish between •planned• and •post-hoc" tests. Planned 

tests are formulated before collecting the data while post-hoc tests are formulated after 

looking at the data. Statistical controls a..-e applied to the latter test to counte.tact their 

being biased in favor of finding statistical significance. In the analyses discussed 

below, the statistical tests were treatea as planned tests to maximize the probability of 

finding even hints of an increase in accident rate with age for pilots near age 60. It is 

quite likely that any trend detected is spurious, but we were being consen-ative. 

6-2 
Because we were concerned with accident :rates for pilots after age 60, we were forced 

to look at the data for Medical Class II and m pilots. 

Examining the data for all Medical Class 1I pilots (see Figure 5-7), the 

accident :rate for group 60-64 did not differ from that of group 55-59 (F(l)=2.99, 

p> .05), but was lower than that of group 65-69 (F(1}=8.41, p< .01 if planned; 

F(7)=1.20, not significant if post-hoc). 

For all Class ill pilots, (see FJgUrC S-8), the accident rate for group 60-64 

did not differ from that of 50-59 (F(1)=2. 7, p> .05) but was lower than that of group 

65-69 (F(l)=5.9, p< .05 if planned; F(7)=0.84, not significant if post-hoc). 

For Class m pilots with more than 500 total flight hours and more than 50 

recent flight hours (see Figure 5-9), the accident rate for group 60-64 did not differ 

from that of group 55-59 (F(l)=0.75, p>.OS) or from that of group 65-69 

(F(1)=2.01, p> .05). 

Fmally, looking year-by-year at the accident rates of Class m pilots with 

more than 500 total flight hours and more than 50 recent flight hours (see Figure 5-10), 

there was an inciease in accident rate for the years 63 through 69 (linear trend, 

F(l)=5.93, p< .05 if planned; not significant if post-hoc). 

Taken together, these analyses give a hint, and a hint only, of an increase in 

accident rate for Class m pilots older than 63 years of age. This suggests that one 

could cautiously increase the retirement age to age 63. 

6-3 
Brown, N. (1992) Personal communic-.IDon. 

Civil Aeromedical Institute. (1991). Aervmedicai Certification Statistical Handbook, 

~No. AC8500-l. 

Drake, A. W. (1967). fundamentals of AWlied J>mhahility Theozy, New York: 

McGraw Hill. 

Games, P. A. {1978). A three-factor model encompassing ma.'ly possible s statistical 

tests on independent groups, Psych. Bull.,~. 168-182. 

Golaszewski, R. {1983). The influence of total fli,.ht time. Tl"f'P!lt fli~:ht time and aze 

on pilot accident rates· Technical Report DTRS57-83-P-80750. Bethesda, 

MD:Acumenics Rescan:h and Tec!mology, Inc. 

Guide, P.C. & Gibson, R.S. (1991). An analytical study of the effects of age and 

experience on ::light safety. Proceedinis of the Hull".an Factors Society 35th 

Annual Meetin5 (pp. 180-184). 

Ha.'Tis, R., Hillman, D., Voros, R. (1992a). A~ 60 PrQject Consolidated Database 

Implementation. Hilton Systems Technical Reprot 8025-3D, Cherry Hill, NJ: 

Hilton Systems, be. 

Harris, R., Hillman, D., Voros, R. (1992b). Age 60 Proiect Consolidated Database 

User's Guide. Hilton Systems Technical Report 8025-3E, Cherry Hill, NJ: 

Hiltrm Systems, Inc. 

Hays, W. L. (1973). Statistics for the Social Sciences. 2nd Ed. Holt, Rinehart and 

Wmston, Inc., New York. 

Hyland, D.T., Kay, E. J., Deimler, J.D., & Gu.T'!r:an, E.B. (1992). Air1ine pilot aze 

and performance: A review of the scientific literature- Technical Report 8025-

lA. Cherry Hill, NJ: Hilton Systems, Inc. 

Institute of Medicine, National Academy of Sciences (1982). Airline pilot ~- health 

and pqfvrmance. Washington, DC: National Academy Press. 

Mortimer, R.G. (1991). Some factors assr-:iated with pilot a,.ae in general aviation 

mshes. Fifth International Svmposium on Aviation Psvchoiogy. 

Office of Technology Ass::ssrnent (1990). Meriica] risk; as.••r;:;sment ?Jld t.~e Sie 60 rul~ 

for airline pilots. Washington, DC: Subcommittee on Investigatior.s an,; 

Oversight, Committee on Public Works and Tra:1sportation, U.S. House of 

Representatives. 

Tiammel, A. (1980). Cl"$ and CiryumswJCe, Zifi-Davis, New York. 

Wmet, B.J. (1971). Statistical Principles in E..~mental t\esign, Second Edition, 

Nev.r Yorlc McGraw-Hill. 
APPENDIX A 

Comparison of Golaszewski Study and Age 60 Study 
APPENDIX A. COMP~ONOFGO~~~STU~Y&,~AGE~ 

STIJDY 

When the accidents in the CDB were segregated into the fine-grained categories 

used by Golaszewski (e.g., Pilots aged 17019, wit.h Class m certificate, and with 501-

1000 total flight hours), the CDB data agreed almost exactly with that of Golaszewski, 

as shown in Table A-1. For example, for the recent flight time analysis, the CDB 

included 18,101 of the i8,366 accidents coun!eG by Golaszewski (Golaszewski, 1983, 

Appendix A-1) and 306,775 summed recent flight time versus 307,579 included by 

Golaszewski. 
Table A-1. 1976-1980 Data-~ Golaszewski versus Age 60 Study 

Closs 1,11,&111 Pilots Difference 

All Ages Golas7.cwski Age 60 1976-1980 Golaszewski • Age 60 

Recent Flight Time 

Pilots RFf Hours Accident Pilots RFf Hours Accident Pilots RFf Hours Accident 

Recent Time Interval (OOOs) (OOOs) Accidents Rate (OOOs) (OOOs) Accidents Rate I <OOOs> <OOOs> Accidents Rate 

0-20 1,930 9,031 1,684 18.7 794 8,980 1,603 17.9 1,136 51 81 0.8 

21-50 459 16,660 2,415 14.5 459 16,683 2,338 14.0 0 ·23 77 0.5 

51-100 382 30,759 3,577 11.6 383 30,896 3,521 11.4 ·1 -138 56 0.2 

1 Ol-400 339 74,006 6,585 8.9 339 73,982 6,523 8.8 0 24 62 0.1 

>400 241 177,124 4 105 2.3 240 176,.!.35 4116 2.3 1 889 ·11 0.0 

All 3,351 307,579 18,366 6.0 2,215 306,775 18,101 5.9 1,136 804 265 0.1 

NOTE: Golaszew.l'ki may have included itrcidenll' (342 from 1976-1980) from/he NTSB database 

~!:!~~!!LFIIght Time Golaszewski 

Pilots RFf Hours Accident Pilots RFf llours Accident Pilots RFf Hours Accident 

Total Time Interval (<~lOs) (OOOs) Accidents Rate (OOOs) (OOOs} Accidents Rate I <OOOs> <OOOs> Accidents Rate ·-

0-1 00 1,621 20,704 2,960 14.3 782 20,602 2,637 12.8 839 102 323 1.5 

101-500 868 45,291 5,561 12.3 667 45,654 4,980 10.9 201 ·363 581 1.4 

501-1000 261 28,1124 2,688 9.3 221 28,960 2,384 8.2 40 -136 304 1.1 

1 OOJ-5000 3112 911,641 6,249 6.3 338 911,823 5,610 5.7 44 ·182 639 0.6 

>5000 2111 114,118 2,780 2.4 206 112,736 2,490 2.2 12 1,383 290 0.2 l.':l<,..tr.·~~ -

All 3,350 307,578 20,2311 6.6 2,215 306,775 18,101 5.9 1,135 802 2,137 0.7 

NOTE: Goiaszewski only required total flight time to be valid i11 NTSB for Total Flight Time a11alyses 

Heccnt ond Toto I 

_flight Time Golaszewski 

Recent& Total Time Pilots RFf Jlours Accidents Accid~nt Pilots RPT !lours Accidents Accident Pilots RFf Hours Accidents Accident 

Interval - (OOOs) (OOOs) Rate (OOOs) (OOOs) Rate (OOOs) (qOOs) Rate 

:>50 & >1000 466 210,539 7,389 3.5 465 209,332 7,420 3.5 1 1,207 -31 0.0 

<"'50 & >1000 134 2,222 700 31.6 80 2,227 680 30.5 54 ·5 20 1.0 

:>50 & <=1000 495 71,350 6,837 9.6 498 71,780 6,740 9.4 -3 -430 97 0.2 

<"50 & <= 1000 

-· 

2,255 23,469 3,375 14.4 1,173 23,436 3,261 13.9 I ,0112 33 ll4 0.5 

All 3,350 307,580 18,301 5.9 2,215 306,775 18,101 5.9 1,135 805 200 0.0 

A·2 
APPENDIXB 

Database Queries 
APPENDIX B. DATABASE QUERIES AND BACKUP DATA 

This appendix contains the parameters that were used to extract the data 

from the CDB for each of the figures in Section 5. The database parameters are 

grouped by source database. After the set of parameters, the spreadsheet containing the 

data used to generate t.'le named figure is shewn. 

Table B-IA. Figure 5-1 (Accident rates for all Class I pilots for the 

years 1976-1985 and 1987-1988-as a.function of age) 

Database Query Parameters 

. Database· .. Parameter 

Accident Accidentllncident=Accident 

Accident Year = 1976-1988 

Medical Class == 1 

Pilot Age: 

30-34• 35-39• 40-44· 45-49• 50-54• 55-59 

Recent Flight Time > 0 

Total Flight Time > 0 

Medical Examination Medical Examination Year= 1976-1988 

Medical Class = 1 

Pilot Age: 

30-34· 35-39· 40-44· 45-49• 50-54; 55-59 

Recent Flight Time > 0 

Total Flie:ht Time > 0 

Table B-IB. Figure 5-1 (Accident rates for all Class I pilots for the 

yea."S 1976-1985 and 1987-1988 as a function of age) 

Spreadsheet 

1976-1985 & 1987-1988 

Class I Pilots 

All Accidents 

Pilot Age Accident Annualized Accident 

Rate Recent Time Count 

30-34 1.78 56 737 745 1,009 

35-39 1.19 61,136,517 I 729 

40-44 0.75 62.044,266 I 464 

45-49 0.63 55,719 557 I 352 

50-54 0.72 40 084::.35 287 

55-59 0.67 28,424,898 190 

B-1 
Table B-2A. Figure 5-2 (Accident rates for all Class I pilots with 

more than 2,000 hours total flight time for the years 

1976-1985 and 1987-1988 as a function of age and of 

recent flight hours ) Database Query Parameters 

Database Patameter 

Accident Accident!Incident=Accident 

Accident Year = 1976-1988 

Medical Class = 1 

Pilot Age: 

30-34; 35-39; 40-44; 45-49; 50-54; 55-59 

Recent Flight Time: 

1-100; 101-200; 201-300; 301-400; 401-500; 501-600; 

601-700· > 700 

Total Flight Time > 2,000 

Medical Examination Medical Examination Year= 1976-1988 

Medical Class = 1 

Pilot Age: 

30-34; 35-39; 40-44; 45-49; 50-54; 55-59 

Recent Flight Time: 

1-100; 101-200; 201-300; 301-400; 401-500; 501-600; 

601-700• > 700 

Total Flight Time > 2,000 

Table B-2B. Figure 5-2 (Accident rates for all Class I pilots with 

more than 2,000 hours total flight time for the years 

1976-1985 and 1987-1988 as a function of age and of 

recent flight hours) Spreadsheet 

Recent Flight RFT > = 1 & < = 100 RFT > 100 & < = 200 

Time Cate2ories 

PilotAge Annualized Annualized 

Recent Accident Accident Recent Accident Accident 

Time Count Rate Time Count Rate 

30-34 230 426 70 30.4 674 613 67 I 9.9 

35-39 274,127 56 20.4 857,034 52 6.1 

40-44 250,828 37 14.8 849,293 47 I 5.5 

45-49 217 995 34 15.6 711,689 37 5.2 

50-54 164,737 17 10.3 522,016 30 5.7 

55-59 148 464 25 16.8 396 124 19 4.8 

B-2 

. 
Recent Flight RFT>=200&. <=300 RFT > 300& <=400 

Time""· ·es 

PilotAge Annualized ! Annuali7ed! 

Recent Accident Accident Recent Accident Accident 

Time Count Rate Time Count. Rate 

30-34 1 032,608 74 7.2 3~107,194 81 2.6 

35-39 1,396,077 61 4.4 4,077 475 73 1.8 

40-44 1356930 40 2.9 4 161,049 37 0.9 

45-49 1,101,346 27 2.5 3,505,594 26 0.7 

50-54 858,691 21 2.4 2,492,696 27 1.1 

55-59 676,359 21 I 3.1 1 678 659 27 1.6 

Recent Flight RFI' > = 400 & < =·SOO RFr > 500& <= 600 

Tune ~. ories 

Aimualized Annuali7ed : 

Recent Accident Accident Recent Accident Accident 

PilotA2e Time Count Rate Time Count Rate 

30-34 3 057,868 87 I 2.8 7,388,744 93 1.3 

35-39 4.335 532 69 1.6 10 863,095 57 0.5 

40-44 4,723,456 44 0.9 13,058,950! 47 0.4 

45-49 4 098,322 36 0.9 12 325 819 24 0.2 

50-54 2,866,359 34 1.2 8,631,5321 28 0.3 

55-59 1,963,496 17 0.9 5,641,909 11 0.2 

Recent Flight RFr >= 600& <= 700 RFI' >= 700 

Time Cate2ories 

Pilot Age Annualized Annua iized 

Recent Accident Accident Recent I Accident Accident 

Time Count Rate Time , Count Rate 

30-34 3,385,503 64 1.9 25,422,449 261 1.0 

35-39 5,310 635 39 iJ.7 '27 658 475 173 I 0.6 

40-44 6,698,412 24 O.t: ~6.891,304 130 0.5 

45-49 6,435 119 24 0.4 24 218 236 89 0.4 

50-54 4,845,841 20 0.4 18,107.355 73 0.4 

55-59 3,950,581 H \ ~.3 13 008,110\ 36 0.3 

B-3 
Accident 

Table B-3A. Figure 5-3 {Accident rates for all Class I pilots with 

more than 2,000 total flight hours and more than 250 

recent flight hours for 1976-1985 and 1987-1988 as a 

function of age) Database Query Parameters 

Database Parameter 

Accident/Incident= Accident 

Accident Year= 1976-1988 

Medical Class = 1 

Pilot Age: 

30-34· 35-39· 40-44: 45-49; 50-54; 55-59 

Recent Flight Tune > 250 

Total Flisrht Time > 2.000 

Medical Exa.-nination Medical Examination Year= 1976-1988 

Medical Class - 1 

Pilot Age: 

. 30-34: 35-39· 40-44: 45-49; 50-54; 55-59 

Recent Flight Time > 250 

Total Flight Time > 2,000 

Table B-3B. Figure 5-3 (Accident rates for all Class I pilots with 

more than 2,000 total fright hours and more than 250 

recent flight hours for 1976-1985 and 1987-1988 as a 

function of age) Spreadsheet 

Annnaliud Recent Accident 

Pilot Aflt'. Time Count Accident Rate 

30-34 44 791490 605 1.4 

35-39 54 331,786 436 0.8 

40-44 56 993,943 294 0.5 

45-49 51.599 381 211 0.4 

S0-54 37 611 987 I 193 0.5 

55-59 26,664,584 I 111 0.4 
Table B-4A. Figure 5-4 (Counts of pilots in the CDB for 1976-

1985 and 1987-1988 with more than 2,000 total flight 

hours as a funcr..on of age and of recent f.tight hours) 

Database Query Parameters 

. Database .· .. Patameter 

Accident AccidentlL'lcident= Accident 

Accident Year = 1976-1988 

Medical (."lass = 1 

PilotAge: 

30-34; 35-39; 40-44; 45-49; 50-54; 55-59 

Recent Flight TliDe: 

1-100; 101-200; 201-300; 301-400; 401-500; 501-600; 

601-700; > 700 

Total Flight Time > 2 000 

Medical Examination Medical Examination Year= 1976-1988 

PilotAge 

30-34 

35-39 

40-44 

45-49 

50-54 

55-59 

Medical Class = 1 

Pilot Age: 

30-34· 35-39· 40-44· 45-49; 50-54· 55-59 

Recent Flight Time: 

1-100; 101-200; 201-300; 301-400; 401-500; 501-600; 

601-700; > 700 

Total Fli~ht Time > 2,000 

Table B-4B. Figure 5-4 (Counts of ?ilots in the CDB for 1976-

1985 and 1987-1988 with more than 2,000 total flight 

hours as a function of age and of recent flight hours) 

Spreadsheet 

RFT >= RFT> RFT > RFT> RFT>IRFT> RFr > 

1&<= 100& 200& 300& 400& 500& 6GO& 

100 <=200 <=300 <=40Cl <=5CO <= 600 <=700 

7597 7387 7 258 15,858 ! 12,477 24,815 9,843 

8,752 9,404 9,858 20,872 117,747 36.549 15.550 

7 827 9400 9 629 21 316 19 446 44,064 19,765 

6.656 7,947 7914 18,015 i 16 969 41,644 19,080 

5,230 5 925 6,197 12,863 1 11,929 29,233 14 407 

4,891 4 614 4,920 8,746 l 8,252 ! 19,222 11,807 

B-5 

RFT > 

700 

154,584 

61 816 

61,393 

55,953 

42,150 

30,826 
Accident 

Table B-SA. Figure 5-5 (Accident rates for all Class I pilots with 

more than 2,000 total flight hours and more than 700 

recent flight hours for 1976-1985 and 1987-1988 as a 

function of age) Database Query Parameters 

Database Para.'lleter 

Accident/Incident= Accident 

Accident Year= 1976-1988 

Medical Class = 1 

Pilot Age: 

30-34· 35-39· 40-44; 45-49· 50-54· 55-59 

Recent Flight Time > 700 

Total Flight Time > 2,000 

Medical Examination Medical Examination Year= 1976-1988 

Medical Clas.~ = 1 

PilotAge: 

30-34; 35-39; 40-44; 45-49; 50-54; 55-59 

Recent Flie;ht Time > 700 

Total Flight Time > 2,000 

Table B-SB. Figure 5-5 {Accident rates for all Class I pilots with 

more tha., 2,000 total flight hours and more than 700 

r.:cent flight hours for 1976-1985 and 1987-1988 as a 

function of age) Spreadsheet 

Annualized Recent Accident I 

Pilot Ae:e Time Count Accident~ 30-34 25 422 449 ' 261 1.0 

35-39 27,658 475 173 0.6 

40-44 26,891 304 130 0.5 

45-49 24,218,236 89 0.4 

50-54 18 107 355 73 0.4 

55-59 13,098,110 36 0.3 

B-6 
Table B-6A. Figure 5-6 (Accident rates for all Class I pilots with 

more than 2,000 total flig.'lt hours a'ld more tha., 700 

recent flight hours, who had an ATP rating, and who 

were employed by a major airline, for 1976-1985 and 

1987-1988 as a function of age) Database Query 

Parameters 

·Database ·Parameter 

Accident Accident!Incident=Accident 

Accident Year = 1976-1988 

Medical Class = 1 

Pilot Age: 

30-34; 35-39; 40-44; 45-49; 50-54; 55-59 

Recent Fli2ht Time > 700 

Total Flight Time > 2,000 

Pilot Certificates = • A • or • AI" 

Medical Examination Medical Examination Year= 1976-1988 

Medical Class = 1 

PilotAge: 

30-34· 35-39· 40-44· 45-49· 50-54• 55-59 

Recent Flight Time > 700 

Total Fli2:ht Time > 2 000 

Employer code: 

ASA;TPA;AAL;BNF;CAL;DAL;EAL;~A; 

NWA' PDA- PAI· SWA; TWA; UAL· USA 

Pilot Certificate Pilot Certificate Ratings: 

AALL; AAMEL; AAt..ffiLC; AAMES; AASEL; 

AASES; BAMEL 

Table B-6B. Figure 5-6 (Accident rates for all Class I pilots \\>ith 

more than 2,000 total flight hours and more than 700 

recent flight hours, who had an A TP rating, and who 

were employed by a major airline, for 1976-1985 and 

1987-1988 as a function of age) Spreadsheet 

· I Annnaliud Recent I Accident 

Pilot AEe Time , Count Accident Rate 

30-34 6,910,366 I ' 6 0.09 

35-39 11,765,684 ! I 3 l 

! O.Q3 

40-44 15 024 225 ' 9 0.06 

45-49 15,488,962 11 ! 0.07 

50-54 11,881 263 7 ! 0.06 

55-59 ! 8,612,907 .. 

J I 0.06 

B-7 

I 

! 

I 

I 
Accident 

Table :B-7 A. Figure 5-7 (Accident rates for all Class II pilots for 

the years 1976-1985 and 1987-1988 as a function of 

age) Database Query Parameters 

Database I Parameter 

I Accident!Incident=Accident 

Accident Year = 1976-1988 

Medical Class = 2 

·Pilot Age: 

130-34; 35-39; 40-44; 45-49; 50-54; 55-59; 60-64; 65-

69 

Recent Flililit Tune > 0 

Total ~t Tune > 0 

Medical Rumination Medical Examination Year = 1976-1988 

Medical Class = 2 

Pilot Age: 

30-34; 35-39; 40-44; 45-49; 50-54; 55-59; 60-64; 65-

69 

Recent Fli2ht Time > 0 

Total Flis;ht Time > 0 

Table B-7B. Figure 5-7 (Accident rates for all Class II pilots for 

the years 1976-1985 a.,d 1987-1988 as a function of 

age) Spreadsheet 

Annualized Recent Accident l 

PilotA2e Time Count Accident Ra!f30-34 35,264 264 ! 2,687 7.62 

35-39 37,746,188 2.488 6.59 

40-44 32,345 42t' 1,991 6.16 

45-49 25.599.502 1,670 6.52 

50-54 21 094 996 1,224 5.80 

55-59 17.438.224 l 969 5.56 

60-64 9,866 110 499 l 5.06 ' 65-69 3,444,256 203 5.89 

B-8 
Accident 

Table B-8A. Figure 5-8 (Accident rates for all C'J:aSS ill pilots for 

the years 1976-1985 and 1987-1988 as a function of 

age) Database Query Parameters 

Database Paiameter 

Accident!Incident=Accident 

Accident Year= 1976-1988 

Medical Class = 3 

Pilot Age: 

30-34; 35-39; 40-44; 45-49; 50-54; 55-59; 60-64; 65-

69 

Recent Flie:ht Tune > 0 

Total Flight Tm1e > 0 

Medical Examination Medical Examination Year= 1976-1988 

Medical Class = 3 I Pilot Age: 

30-34; 35-39; 40-44; 45-49; 50-54; 55-59; 60-M; 65-

l ~ecent Flight Time > 0 

I Total Fl!iht Tune > 0 

Table B-8B. Figure 5-8 (Accident rates for all Class ill pilots for 

the years i976-198S and 1987-1988 as a function 'Jf 

age) Spreadsheet 

Pilot~ Annua~:e Recent Accident 1 

Count lA<rident Rate 

30-34 . 16,484,312 2,129 l 12 .. 92 

35-39 18.678 968 2,090 l 11.19 

40-44 18,990,832 2.066 10.88 

45-49 19,325,124 I 2,026 I 10.48 

50-54 18,763,440 l 1,728 ! 9.21 

55-59 14,4!0.584 1,249 8.67 

60-64 8,216,628 ' l 659 8.02 

65-69 ! 3.M3,696 1 327 i 8.97 

B-9 

I 
Accident 

Table B-9A. Figure 5-9 (Accident :rates for all Class ill pilots wit..'! 

more than 500 total flight hours liild more than 50 

recent flight hours for the years 1976-1985 a'ld 1987-

1988 as a function of age) Database Q'.lery Parameters 

Database I Parameter 

l Accident!Ir..cident=Accident 

Accident Year= 1976-1988 

Medical Class = 3 

Pilot Age: 

30-34; 35-39; 40-44; 45-49; 50-54; 55-59; 60-64; 65-

fB 

Recent Flight Time > 50 - Total Fright Tlille > 51¥! 

Medical Exarr>.ination Medical Examination Year= 1976-1988 

Medical Class = 3 

Pilot Age: 

30-34; 35-39; 40-44; 45-49; 50-54, 55-59; 60-64; 65- l ~t Flight Time > 50 

Total Fli .t Time > 500 

Table B-9B. Figure 5-9 (Accident :rates for all Class ill pilots ·with 

more than 500 total flight hours and more than 50 

recent flight hours for the years 1976-!985 a;1d 1987-

1988 as a function of age) Spreads.ieet 

1 Annualized Recent 1 Accident 

Pilot Age Time I Coont Accident Raj 

30-34 3.049.488 I 261 l 8.56 ' ! 

35-39 5.420, .. 84 ; 370 I 6.83 

40-44 7,389.344 i 510 6.90 

45-49 I 9,165,756 618 6.74 I 50-54 I 10.106.600 603 J 

J 5.97 

55-59 8.630,068 507 5.87 

60-64 ! 

J 5.254,668 287 ! 5.46 

65-69 1 2,448,168 150 I 6.13 

lHO 

I 

I 
Accident 

Table B-lOA, Figure 5-10 (Accident rates for Class ill pilots 

between the ages of 50 and 69 with more than 500 

total flight hours and more than 50 recent flight hours 

for the years 1976-1985 and 1987-1988 as a function 

of age) Database Query Parameters 

Database ' .. Parameter 

Accident/Incident= Accident 

Accident Year = 1976-1988 

Medical Class = 3 

Pilot Age: 

50-69 in one-year age steps 

Recent Flight Time > 50 

Total Flight Time > 500 

Medical Examination Medical Examination Year = 1976-1988 

Medical Class = 3 

Pilot Age: 

5()-69 in one-year ~e steps 

Recent Flight Time > 50 

Total J:!!g_ilt Time > 500 

B--11 
Table B-lOB. Figure 5-10 (Accident rates for Class ill pilots 

between the ages of 50 and fB wit1 more than 500 

total flight hours and more than 50 recent flight hours 

for the years 1976-1985 and 1987-1988 as a function 

of age) Spreadsheet 

Annualized Recent · Accident 

PilotAge ·Time Count Accident Rate 

50 2,004 992 105 5.24 

51 1 998,476 132 6.61 

52 2,065 376 126 6.10 

53 2 002,584 133 6.64 

54 2,035 172 107 5.26 

55 1 931,404 119 6.16 

56 1,880 172 110 5.85 

57 1 718,264 103 5.99 

58 1,613 868 88 5.45 

59 1 486,360 87 5.85 

60 1,312,312 85 6.48 

61 1,191 620 62 5.20 

62 1 013,704 52 5.13 

63 927,036 38 4.10 

64 809,996 50 6.17 

65 679 204 34 5.01 

66 568,724 34 5.98 

67 479 816 37 7.71 

68 389,636 24 6.16 

69 330 788 21 6.35 

B-12 
Accident 

Table B-llA. Figure 5-11 (Accident rates for Class I pilots with 

more than 2,000 total flight hours and more than 700 

recent flight hours for the years E."'. '985 and 1987-

1988 as a function of date of birth and of the year in 

which the data were collected) Database Query 

Parameters 

Database Parameter 

Accident/Incident= Accident 

Accident Year and Pilot Age Combinations: 

1976- Age 26-30; 31-35; 36-40; 41-45; 46-50 

1977- Age 27-31; 32-36; 37-41; 42-46; 47-51 

1978 - Age 28-32; 33-37; 38-42; 43-47; 48-52 

1979 -· Age 29-33; 34-38; 39-43; 44-48; 49-53 

1980- Age 30-34; 35-39; 40-44; 45-49; 50-54 

1981 -Age 31-35; 36-40; 41-45; 46-50; 51-55 

1982- Age 32-36; 37-41; 42-46; 47-51; 52-56 

1983 - Age 33-37; 38-42; 43-47; 48-52; 53-57 

1984- Age 34-38; 39-43; 44-48; 49-53; 54-58 

1985 - A~e 35-39_;_ 40-44; 45-49; 50-54; 55-59 

Medical Class = 1 

Recent Fli2ht Time > 700 

Total Flight Time > 2,000 

Medical Examination Medical Examination Year and Pilot Age 

Combinations: 

1976- Age 26-30; 31-35; 36-40; 41-45; 46-50 

1977- Age 27-31; 32-36; 37-41; 42-46; 47-51 

1978 -Age 28-32; 33-37; 38-42; 43-47; 48-52 

1979- Age 29-33; 34-38; 39-43; 44-48; 49-53 

1980 --Age 30-34; ~5-39; 40-44; 45-49; 50-54 

1981 --Age 31-35; 36-40; 41-45; 46-50; 51-55 

1982 --Age 32-36; 37-41; 42-46; 47-51; 52-56 

1983 --Age 33-37; 38-42; 43-47; 48-52; 53-57 

1984 - Age 34-38; 39-43; 44-48; 49-53; 54-58 

1985 -Age 35-39; 40-44· 45-49· 50-54· 55-59 

Medical Class = 1 

Recent Flight Time > 700 

Total Fli_ght Time > 2,000 

B-13 
Table B-UB. Figure 5-11 (Accident rates for Class I pilots with 

more than 2,000 total flight hours and more than 700 

recent flight hours for the years 1976-1985 and 1987-

1988 as a function of rlate of birth and of the year in 

which the data were oollected) Spreadsheet 

Birth Year Recent Flight Accident 

Year (Pilot A2e) Time Totals · Count Accident Rate 

1976 1946-50 (26-30) 1,282 718 21 1.64 

1976 1941-45 (31-35) 1,848,586 22 1.19 

1976 1936-40 (36-40) 2 107 671 16 0.76 

1976 1931-35 (41-45) 1, 789,551 10 0.56 

1976 1926-30 (46-50) 1 174 220 4 0.34 

1977 1946-50 (26-30) 1,524,842 34 2.23 

1977 1941-45 (31-35) 2 008 595 17 0.85 

1977 1936-40 (36-40) 2 250 490 11 0.49 

1977 1931-35 (41-45) 1,886,066 5 0.27 

1977 1926-30 (46-50) 1,174,284 7 0.60 

1978 1946-50 (26-30) 1,804,094 30 1.66 

1978 1941-45 (31-35) 2,232,406 19 0.85 

1978 1936-40 (36-40) 2,462,137 12 0.49 

1978 1931-35 (41-45) 2 002 937 12 0.60 

1978 1926-30 (46-50) 1,233,583 6 0.49 

1979 1946-50 (26-30) 2,185 602 31 1.42 

1979 1941-45 (31-35) 2 504.728 18 0.72 

1979 1936-40 (36-40) 2,617,210 9 0.34 

1979 1931-35 (41-45) 2 095 368 8 0.38 

1979 1926-30 (46-50) 1,230,315 9 0.73 

1980 1946-50 (26-30) 2,336 362 34 1.46 

1980 1941-45 (31-35) 2,386,439 22 0.92 

1980 1936-40 (36-40) 2 531,144 7 0.28 

1980 1931-35 (41-45) 2,041,254 6 0.29 

1980 1926-30 (46-50) 1,151,415 2 0.17 

1981 1946-50 (26-30) 2,353,842 24 1.02 

1981 1941-45 <31-35) 2,273 752 12 0.53 

1981 1936-40 (36-40) 2,347,014 11 0.47 

1981 1931-35 (41-45) 1,917,546 6 0.31 

1981 1926-30 (46-50) 1,036 140 4 0.39 

1982 1946-50 (26-30) 2,275,248 19 0.84 

1982 1941-45 (31-35) 2,111,816 9 0.43 

1982 1936-40 (36-40) 2 248,276 9 0.40 

B-14 
Birth Year Recent Flight . Accident 

Year (Pilot Aae) Time Totals Count Accident Rate 

1982 1926-30 (46-50) 992 458 5 0.50 

1983 1946-50 (26-30) 2,377 316 13 0.55 

1983 1941-45 (31-35) 2 269 669 13 0.57 

1983 1936-40 (36-40) 2,410,256 16 0.66 

1983 1931-35 (41-45) 1 958 217 4 0.20 

1983 1926-30 (46-50) 1,024 058 7 0.68 

1984 1946-50 (26-30) 3,031,633 15 0.49 

1984 1941-45 (31-35) 2,648,838 15 0.57 

1984 1936-40 (36-40) 2 771 686 7 0.25 

1984 1931-35 (41-45) 2,247,937 6 0.27 

1984 1926-30 (46-50) 1 098,166 1 0.09 

1985 1946-50 (26-30) 3,319,334 8 0.24 

1985 1941-45 (31-35) 2 887,167 11 0.38 

1985 1936-40 (36-40) 2 977 187 6 0.20 

1985 1931-35 (41-45) 2,287 ,4!r;) 7 0.31 

1985 1926-30 (46-50) 1 032,529 8 0.77 

B-15 
Accident 

Table B-12A. Figure 5-12 (Accident rates for Class I pilots with 

more than 2,000 total flight hours and more than 700 

recent flight hours fo: the years 1976-1985 and 1987-

1988 as a function of date of birth and of the year in 

which the data were collected) Database Query 

Parameters 

Database Parameter 

Accident/Incident=Accident 

Accident Year and Pilot Age Combinations: 

1976- Age 26-30; 31-35; 36-40; 41-45; 46-50 

19n- Age 27-31; 32-36; 37-41; 42-46; 47-51 

1978 - Age 28-32; 33-37; 38-42; 43-47; 48-52 

1979 -- Age 29-33; 34-38; 39-43; 44-48; 49-53 

1980 - Age 30-34; 35-39; 40-44; 45-49; 50-54 

1981 -Age 31-35; 36-40; 41-45; 46-50; 51-55 

1982- Age 32-36; 37-41; 42-46; 47-51; 52-56 

1983 - Age 33-37; 38-42; 43-47; 48-52; 53-57 

1984 -- Age 34-38; 39-43; 44-48; 49-53; 54-58 

1985 -- Age 35-39· 40-44; 45-49· S0-54; 55-59 

Medical Class = 1 

Recent Flight Time > 700 

Total Fli2ht Time > 2 000 

Medical Examination Medical Examination Year and Pilot Age 

Combinations: 

1976 --Age 26-30; 31-35; 36-40; 41-45; 46-50 

19TI- Age 27-31; 32-36; 37-41; 42-46; 47-51 

1978 --Age 28-32; 33-37; 38-42; 43-47; 48-52 

1979 --Age 29-33; 34-38; 39-43; 44-48; 49-53 

1980 -- Age 30-34; 35-39; 40-44; 45-49; 50-54 

1981 -Age 31-35; 36-40; 41-45; 46-50; 51-55 

1982 --Age 32-36; 37-41; 42-46; 47-51; 52-56 

1983 - Age 33-37; 38-42; 43-47; 48-52; 53-57 

1984 --Age 34-38; 39-43; 44-48; 49-53; 54-58 

1985 --Age 35-39· 40-44· 45-49· 50-54· 55-59 

Medical Class = 1 

Recent Fli2ht Time > 700 

Total Flight Time > 2,000 

B-16 
Table B-UB. Figure 5-12 (Accident rates for Class I pilots with 

more than 2,000 total flight hours and more than 700 

recent flight hours for the years 1976-1985 and 1987-

1988 as a function of date of birth and of the year in 

which the data were collected) Spreadsheet 

. . . . : ::. Birth Year .• Recent Flight . .. ·.Accident Year · (PilotAge) · · ·. Time TOtalS · ..···· .. •···Count Accident Rate 

1976 1946-50 (26-30) 1 282,718 21 1.64 

1976 1941-45 {31-35) 1,848 586 22 1.19 

1976 1936-40 (36-40) 2 107,671 16 0.76 

1976 1931-35 (41-45) 1,789,551 10 0.56 

1976 1926-30 (46-50) 1174,220 4 0.34 

1971 1946-50 (26-30) 1,524,842 34 2.23 

1977 1941-45 (31-35) 2,008 595 17 0.85 

1977 1936-40 (36-40) 2,250,490 11 0.49 

1977 1931-35 (41-45) 1,886 066 5 0.27 

1977 1926-30 (46-50) 1 174 284 7 0.60 

1978 1946-50 (26-30) 1,804,094 30 1.66 

1978 1941-45 (31-35) 2 232 406 19 0.85 

1978 1936-40 (36-40) 2,462,137 12 0.49 

1978 1931-35 {41-45) 2,002 937 12 0.60 

1978 1926-30 (46-50) 1 233 583 6 0.49 

1979 1946-50 (26-30) 2,185 602 31 1.42 

1979 1941-45 (31-35) 2 504 728 18 0.72 

1979 1936-40 (36-40) 2,617,210 9 0.34 

1979 1931-35 {41-45) 2 095 368 8 0.38 

1979 1926-30 (46-50) 1,230,315 9 0.73 

1980 1946-50 (26-30) 2,336,362 34 1.46 

1980 1941-45 {31-35) 2 386,439 22 0.92 

1980 1936-40 (36-40) 2 531 144 7 0.28 

1980 1931-35 (41-45) 2 041 254 6 0.29 

1980 1926-30 (46-50) 1,151 415 2 0.17 

1981 1946-50 (26-30) 2 353,842 24 1.02 

1981 1941-45 (31-35) 2,273 752 12 0.53 

1981 1936-40 (36-40) 2,347,014 11 0.47 

1981 1931-35 (41-45) 1 917,546 6 0.31 

1981 1926-30 (46-50) 1,036,140 4 0.39 

1982 1946-50 (26-30) 2 275 248 19 0.84 

1982 1941-45 (31-35) 2 Ill 816 9 0.43 

1982 1936-40 (36-40} 2,248,276 9 0.40 

1982 1931-35 (41-45) 1,867,412 3 0.16 

B-17 
Birth Year Recent Flight Accident 

Year {Pilot Ate) Time Totals r.ount Accident Rate 

1983 1946-50 {26-30) 2 377 316 13 0.55 

1983 1941-45 (31-35) I 2,269,669 13 0.57 

1983 1936-40 {36-40) 2 410 256 16 0.66 

1983 1931-35 (41-45) 1,958,217 4 0.20 

1983 1926-30 (46-50) 1,024 058 7 0.68 

1984 1946-50 !26-~0) 3 031 633 15 0.49 

!984 1941-45 (31-35) 2,648,838 15 0.57 

1984 1936-40 (3640) 2,771,686 7 0.25 

1984 1931-35 (41-45) 2,247 937 6 I 0.27 

1984 1926-30 (46-50) 1,098 166 1 0.09 

1985 1946-50 (26-30) 3 319 334 8 0.24 

1985 1941-45 (31-35) 2.887,167 11 0.38 

1985 1936-40 (36-40) 2 977 187 6 0.20 

1985 1931-35 (41-45) I 2,287,490 ., 

; 0.31 

1985 1926-30 (46-50} 1,032,529 8 0.77 

B-i8 
Accident 

Table B-13A.Figure 5-13 (Accident rates for Class ill pilots with 

more than 500 total flight hours and more than 50 

recent flight hours for the years 1976-1985 and 1987-

1988 as a function of date of birth and of the year in 

which the data were collected) Database Query 

Parameters 

Database Parameter 

Accidentllncident=Accident 

Accident Year and Pilot Age Combinations: 

1976- Age 26-30; 31-35; 36-40; 41-45; 46-50 

1977- Age 27-31; 32-36; 37-41; 42-46; 47-51 

1978 - Age 28-32; 33-37; 38-42; 43-47; 48-52 

1979- Age 29-33; 34-38; 39-43; 44-48; 49-53 

1980- Age 30-34; 35-39; 40-44; 45-49; 50-54 

1981- Age 31-35; 36-40; 41-45; 46-50; 51-55 

1982- Age 32-36; 37-41; 42-46; 47-51; 52-56 

1983 - Age 33-37; 38-42; 43-47; 48-52; 53-57 

1984 - Age 34-38; 39-43; 44-48; 49-53; 54-58 

1985 - Arz.e 35-39; 40-44; 45-49; 50-54; 55-59 

Medical Class = 3 

Recent Flirz.ht Time > 50 

Total Fli2.ht Time > 500 

Medical Examination Medical Examination Year and Pilot Age 

Combinations: 

1976- Age 26-30; 31-35; 36-40; 41-45; 46-50 

1977- Age 27-31; 32-36; 37-41; 42-46; 47-51 

1978 - Age 28-32; 33-37; 38-42; 43-47; 48-52 

1979 - Age 29-33; 34-38; 39-43; 44-48; 49-53 

1980- Age 30-34; 35-39; 40-44; 45-49; 50-54 

1981 -Age 31-35; 36-40; 41-45; 46··50; 51-55 

1982 - Age 32-36; 37-41; 42-46; 47-51; 52-56 

1983 - Age 33-37; 38-42; 43-47; 48-52; 53-57 

1984- Age 34-38; 39-43; 44-48; 49-53; 54-58 

1985- Age 35-39; 40-44; 45-49; 50-54; 55-59 

Medical Class = 1 

Recent Flight Time > 50 

· Total Flie:ht Time > 500 

B-19 

------------ -
i 

Table B-13B. Figure 5-13 (Accirient rates for Class ill pilots with 

more than 500 total flight hours and more than 50 

recent flight hours for the years 1976-1985 and 1987-

1988 as a function of date of birth and of the year in 

which the data were collected) Spreadsheet 

Birth Year Recent Flight Accident 

Year . (Pilot Age) Time Totals Count Accident Rate 

1976 1946-50 (26-30) 113,000 17 15.04 

1976 1941-45 (31-35) 276,072 28 10.14 

1976 1936-40 (36-40) 435 580 37 8.49 

1976 1931-35 (41-45) 641,452 61 9.51 

1976 1926-30 (46-50) 952 892 78 8.19 

1976 1921-25 (51-55) 908,928 58 6.38 

1976 1916-20 (56-60) 533 160 41 7.69 

1977 1946-50 {26-30) 152,764 23 15.06 

1977 1941-45 (31-35) 337 336 20 5.93 

1977 I 1936-40 (36-40) 492,856 I 42 8.52 

1977 1931-35 (41 45) 692,096 48 6.94 ; 

1977 1926-30 (46-50) 957,608 80 8.35 

1977 1921-25 (51-55) 842,008 68 8.08 

1977 1916-20 (56-60) 475,348 35 7.36 

1978 1946-50 (26-30) 201,708 18 8.92 

1978 1941-45 (31-35) 406 176 47 11.57 

1978 1936-40 (36-40) . 542,308 35 6.45 

1978 I 1931-35 (41-45) 755,236 57 I 7.55 - 1978 1926-30 (46-50) 1,041,196 73 l 7.01 

1978 1921-25 (51-55) 892,744 75 8.40 

1978 1916-20 (5eKiO) I 4lS5 636 16 I 3.29 

1979 1946·50 (26-30) 259,240 23 8.87 

1979 1941-45 (31-35) 467,012 34 7.28 

1979 1936-40 (36-40) 585,052 46 7.86 

1979 1931-35 (41-45) 793,128 59 7.44 

1979 1926-30 (46-50) 989,096 61 l 6.17 

1979 1921-25 (51-55) 816,496 I 47 I 5.76 

1979 1916-20 (56-60) 431,544 I 23 5.33 

1980 1946-50 (26-30) 288,420 I ' 30 10.40 

1980 1941-45 {31-35) I 499.036 44 8.82 

1980 1936-40 (36-40) 641,804 I 54 8.41 

1980 1931-35 (41-45) 778.156 i 52 6.68 

1980 1926-30 (46-50) 980,60!! 56 5.71 

1980 1921-25 (51-55) 771,856 l 32 4.15 ! 

B-20 
BirJl Year Recent Flight Accident 

Year (Pilot Age) Time Totals · Count Accident Rate 

1981 1946-50 (26-30) 326 332 29 8.89 

1981 1941-45 (31-35) 551,736 39 7.07 

1981 1936-40 (36-40} 659 432 50 7.58 

1981 1931-35 (41-45) 792 120 55 6.94 

1981 1926-30 (46-50) 889,928 47 5.28 

1981 1921-25 (51-55) 718,364 43 5.99 

1981 1916-20 (56-60) 363,160 26 7.16 

1982 1946-50 (26-30) 339 900 20 5.88 

1982 1941-45 (31-35) 531 600 30 5.64 

1982 1936-40 (36-40) 626,276 30 4.79 

1982 1931-35 (41-45) 701172 48 6.85 

1982 1926-30 (46-50) 830,064 45 5.42 

1982 1921-25 (51-55) 635 812 23 3.62 

1982 1916-20 (56-60) 301,164 21 5.97 

1983 1946-50 (26-30) 369,504 20 5.41 

1983 1941-45 (31-35) 567,128 35 6.17 

1983 1936-40 (36-40) 625,012 32 5.12 

1983 1931-35 (41-45) 701,628 53 7.55 

1983 1926-30 (46-50) 796,996 46 5.77 

1983 1921-25 (51-55) 590,112 41 6.95 

1983 1916-20 (56-60) 274,024 I 14 5.11 

~J84 1946-50 (26-30) 359,596 23 6.40 

1984 1941-45 (31-35) 571,236 43 7.53 

1984 1936-40 (36-40) 650,932 I 37 5.68 

1984 1931-35 (41-45) 680,036 i 33 4.85 

1984 1926-30 (46-50) 741,160 48 I 6.48 

1984 1921-25 (51-55) 537 404 28 5.21 

1984 1916-20 (56-60) 244.376 17 6.96 

1985 1946-50 (26-30) 456,216 27 5.92 

1985 1941-45 (31-35) 614,916 i 37 6.02 

1985 1936-40 (36-40) 672,324 I 

I 40 5.95 

1985 1931-35 (41-45) 701,448 i ' 40 5.70 

1985 1926-30 (46-50) 752,564 i 42 5.58 

1985 1921-25 (51-55) 516,316 i 28 ! 5.42 

1985 1916-20 (56-60) 242,592 j 8 3.30 ' 

B-21 
Accident 

Table B-14A. Figure 5-14 (Accident rates for Class ill pilots with 

more than 500 total flight hours and more than 50 

recent flight hours for the years 1976-1985 and 1987-

1988 as a function of date of birth and of the year i.'l 

which the data were collected) Database Qt.ery 

Parameters 

Database ! Parameter 

Accident/Incident=Accident 

Accident Year and Pilot Age Combinations: 

1976- Age 26-30; 31-35; 36-40; 41-45; 46-50 

1977- Age 27-31; 32-36; 37-41; 42-46; 47-51 

1978- Age 28-32; 33-37; 38-42; 43-47; 48-52 

1979 - Age 29-33; 34-38; 39-43; 44-48; 49-53 

1980 - Age 30-34; 35-39; 40-44; 45-49; 50-54 

1981 -Age 31-35; 36-40; 41-45; 46-50; 51-55 

1982 -Age 32-36; 37-41; 42-46; 47-5i; 52-56 

1 1983 -Age 33-37; 38-42; 43-47; 48-52; 53-57 

1984- Age 34-38; 39-43; 44-48; 49-53; 54-58 

1985- Age 35-39· 40-44; 45-49· 50-54; 55-59 

Medical Ciass = 3 

Recent Flight Time > 50 

Total Fli_ght Time > 500 

Medical Examination Medical Examination Year and Pilot Age 

Combinations: 

1976- Age 26-30; 31-35; 36-40; 41-45; 46-50 

1977- Age 27-31; 32-36; 37-41; 42-46; 47-51 

1978- Age 28-32; 33-37; 38-42; 43-47; 48-52 

11979- Age 29-33; 34-38; 39-43; 44-48; 49-53 

1980- Age 30-34; 35-39; 40-44; 45-49; 50-54 

11981 -Age 31-35; 36-40; 41-45; 46-50; 51-55 

jt982 -- Age 32-36; 37-41; 42-46; 47-51; 52-56 

11983 -Age 33-37; 38-42; 43-47; 48-52; 53-57 

, 1984- Age 34-38; 39-43; 44-48; 49-53; 54-58 l 

! 1985- Age 35-39; 40-44; 45-49; 50-54; 55-59 

! Medical Class = 1 

! Recent Flight Time > 50 

Total Flight Time > 500 

B-22 
I 

Table B-14B. Figure 5-14 (Accident rates for Class ill pilots with 

more than 500 total flight hours and more than 50 

recent flight hours for the years 1976-1985 and 1987-

1988 as a function of date of birth and of the year in 

which the data were collected) Spreadsheet 

I ~Year Recent Flight ' Accident 

Year (PilotAge} . TuneTotals t Count Accident Rate 

1976 1946-50 (26-30) 113000 17 15.04 

1976 1941-45 (31-35) 276,072 I 28 I 10.14 

1976 1936-40 (36-40) 435 580 37 8.49 

1976 1931-35 (41-45) 641,452 61 l 9.51 

1976 1926-30 (46-50) 952,892 I 78 ! 8.19 

1976 1921-25 (51-55) 908,928 I 58 ! 

I 6.38 

1976 1!:116-20 (56-60) 533 160 41 I 7.69 

1977 1946-50 (26-30) 152,764 23 15.06 

1977 1941-45 (31-35) 337,336 20 5.93 

1977 1936-40 (36-40) 492,856 42 8.52 

1977 1931-35 (41-45) 692,096 i 48 6.94 

1977 1926-30 {46-50) 957,608 80 8.35 

1977 1921-25 (51-55) 842 008 68 8.08 

1977 1916-20 (56-60) 475,348 35 I 7.36 

1978 1946-50 (26-30) 201,708 18 8.92 

1978 1941-45 (31-35) 406.176 47 I 11.57 

1978 1936-40 (36-40) 542,308 ' 35 6.45 

1978 1931-35 (41-45) 755.236 I -7 ;:). 7.55 

1978 1926-30 (46-50) 1.041,1% ' 73 I I 7.01 ' 

1978 1921-25 (51-55) I 892,744 I 75 • i 8.40 

1978 1916-20 (56-60) i 485,636 I 

I 16 I 3.29 

1979 1946-50 (26-30} 259,?.40 I 23 i 8.87 

1979 1941-45 (31-35) I 467,012 i 34 7.28 • 

1979 1936-40 (36-40) I 585,052 I 

! 46 7.86 

1979 1931-35 (41-45) 793.128 ! 59 7.44 

1979 1926-30 {46-50) 989,096 I ' 61 i 6.17 

1979 1921-25 {Sl-55) l 816.4% I 

! 47 ' 5.76 

1979 1916-20 (56-60) I 431,544 i 23 5.33 

1980 1946-50 (26-30) ! 288.420 i 30 10.40 

1980 1941-45 (31-35) 499.036 ' i 44 ! 8.82 

1980 1936-40 (36-40} I 641.804 i 54 ! 8.41 ' 1980 1931-35 (41-45) I ' 778,156 52 I 6.68 

1980 1926-30 (46-50) l 980.608 56 I 5.71 

1980 1921-25 (51-55) ' ! nl,856 32 I 4.15 

B-23 

I 

I 

i 
I Birth Year i Recent Flight i Accident i i ~ I 

Year ti"Jot A£e) Time Totals l Count iAccident Rate l l 

1981 I 1946-50 (26-30) i 326 332 ! 29 i 8.89 

1981 I 1941-45 (31-35) l 551,736 I 39 i 7.07 

1981 1936-40 {36-40) I 659 432 i 50 i 7.58 

1981 1931-35 (41-45) I 792,120 I 55 ' 6.94 

1981 1926-30 (46-50) 889 928 I 47 i 5.28 

1981 1921-25 (51-55) 718,364 I l 43 ! 5.99 

1981 1916-20 (56-60) 363,160 j 26 I 7.16 I 

1982 1946-50 (26-30) I 339.900 ) 20 ' ! ' 5.88 

1982 1941-45 (31-35) l 

I 531,6{!G I 30 5.64 ' 

l-1982 I 1936-40 (36-40) 626,276 I ' 30 j 4.79 

1982 l931-35 (41-45) 70!,172 I 48 I 6.85 

1982 1926-30 (46-50) 830,064 ! 45 i 5.42 

1982 1921-25 (51-55) I 635,812 I 23 i 3.62 

1982 !916-20 (56-60) 301,164 l 

I 21 ! 6.97 

1983 1946-50 (26-30) ; 369,504 ! 20 I I ' 5.4! I 

1983 1941-45 (31-35) 56i.l28 ' 35 i 

! j 6.17 

1983 1936-40 (36-40) i 625,012 l 32 I 5.12 I ' l 

1983 1931-35 (41-45) 70i.628 i 53 I 7.55 

1983 I 1926-30 (46-50) i 796,996 i 46 ' 

I 5.77 

1983 I 1921-25 (51-55) I 590,112 ' 41 : I I I 6.95 

1983 I 1916-20 (;,6-60) ! 274,024 l 14 ! 

' ~ ~, _ .. .!..I. 

1984 1946-50 (26-30' ! 359.5% j 23 ! 6.40 

1984 1941-45 (31-35) i 571,236 i 43 I 

l 7.53 

1984 1936-40 {36-40) 650,932 l 37 l 5.68 I 

1984 I 1931-35 (41-45) I 680,036 33 ! 4.85 I ! ! 

1984 1926-30 (46-50) l 741.160 l ; 48 6.48 

1984 1921-25 {51-55) 537.404 28 i 5~21 

1984 1916-20 (56-60) ! 244,376 ·-1! i 6.96 

1985 1946-50 (26-30) l 456.2J6 ' .... 

- ' 5.92 ' ,;./ i I 

1985 1941-45 (31-35) ; 614.916 ' 37 i 6.!)2 

1985 !936-40 (36-40) 672,324 4) 5.95 ! 

1985 1931-35 {41-45) 701.448 ; 40 f 5.70 

1985 1926-30 

, (46-50} . 752 564 ' 42 5.58 l 

1985 1921-25 (51-55) ~ ~ 5.42 

1985 ! 1916-20 (56-60) 242~592 8 3.30 
Table B-15A. Fxgm1: 5-15 (Count of Class I pilots aged 36-40 with 

ID011: than 2,000 iOial flight hours and more than 250 

recent flight hours for the years 1976-1985) Database 

Query Parameters 

Medical Examination 

Total Flight Time > 2,000 

Medical Eunrlnatiort Year and Pilat Age 

Combinations: 

1976 - Age J6..40 

1m •• Age 37-41 

1978 - Age 38-42 

1979 - Age 39-43 

1980 - Age 40-44 

1981 -Age 41-45 

1982 - Age 42-46 

1983 - Age 43-47 

1984 - Age 44-48 

1985-

Table B-15B. Figure 5-15 (Count of Class I pilots aged 36-40 with 

more than 2,000 total flight hours and more than 250 

recent flight hours for the years 1976-1985) 

Spreadsheet 

Years Year 1 Year2 

1976-77 11580 9.254 

tm-78 12 261 i 9,932 

1978-79 13.582 11.202 

1979-80 14,922 12.135 

1980-81 15 078 12 218 

1981-82 15,028 12.145 

1982-83 14 789 ' 11.974 

1983-84 I4,m 12.077 

1984-85 15.367 12.77-4 

B-25 
Table B-16A. Figure 5-16 (Counts of Class I pilots ·ged 26-30 for 

tbe years 1976-1985 and 1987-1988 ~ a function of 

year) DataNse Query Parameters 

IF certific:ale number EXISTS in 1976 AND class I in 

1977. illuemertt I 977 Clus I count. 

IF certificate ~!Umber EXISTS in !976 AND class II in 

. 1977. incteaDent 1977 Class n count. 

lF cutificale number EXISTS in 1976 AND class rn in 

!977. i:nerement 1977 aass m c:ount. 

Tllble a..t&. Fipre 5-16 (Counts of Class I pilots a&ed 26-30 for 

tbe years 1976-1985 and 1987-1988 as a fun;:tioo of 

year) Spreed*et 

Year O¥erall 0au I Class I Class I- Oassi- m 

foryar AUritioa ausn 

76 10049 10,059 286 8 

77 12,367 7.852 l fm l 

! 4 

71 15.979 7,858 628 32 

79 18~760 7,665 540 32 

eo 19.275 7,503 i 551 16 

81 19.788 7.440 l 691 29 

12 II 736 7,212 l 863 43 

83 18.959 7.203 92S 38 

14 20641 l 7.465 ! 921 46 

IS 22,140 I 7,758 i 853 ! 42 

17 24.._069 ' 8.060 l 838 ! 42 

• 25,339 I 8.084 %5 47 
Table B-17A.F~ 5-17 (Counts of Class I pilots aged 46-50 for 

the yean 1976-1985 and 1987-1988 as a function of 

year) Database Query Parm!eters 

DllnN• ~ 

Medical Euminatioon M'd'K:Il Class - 1 

' 

Rererrt . ,.._ > "'0 

TOial~Tnne > =0 

) fli5ciJ ElamiJialion Year and Pilol Age Combination: 

1976- Ale 46-50 

Certificalr. Number IF c:ertif.care number EXISTS in 1976 AND class I in 

1977, iuuemeut 1m Class I count. 

IF cenific:ate fiW!Iber EXISTS in 1976 AND class n in 

1977, increment 1977 C'.ass n count. 

IF c:ertificat= number EXISTS in 1976 AND class rn in 

1977, increment 1977 Class m count. 

REPEAT above for vears 1978- 1988 (excludin2 1986) 

Table B-11B. FJilR 5-17 (Counts of Class I pilots aged 46-50 for 

the years 1976-1985 and 1987-1988 as a function of 

year) Spreadsheet 

Year OYerall Class I Class I Class I- Class I- m 

for year Attrition Class n 

76 8 335 8 283 33 3 

77 8,312 7,ffJ7 141 7 

78 8,503 7 390 185 20 

79 8,650 7,229 185 15 

8C 8,177 7 f12.7 211 11 

81 8 449 6,943 253 10 

82 8,161 6 724 280 25 

83 7,767 6,407 320 24 

84 7 395 6 046 309 25 

85 6,929 5,416 355 42 

87 4 721 3,535 509 68 

88 3,554 2,586 ! 630 86 

B-27