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Technical kepott Docuanntotion Pase

Report No. 2. G ,o.ernent Acce s.*.n No. 3. Rec.p..nt'i Carolo9 fic.

"'° an .• b " tle . 1 , ie .. . . . R epo r 0, ,.Do e

FU`NCTIONAL AGING IN PILOTS: AN EXAMINATION or A JUNE 1982 6. Pe,,o,a,", .. C~•, oe*

YAThEMATICAL MODEL BASED ON MEDICAL DATA ON GENERAL

PILOTS SNAVIATION 

E 8. Pe0,1o -n9 O,'gc. asorno R-poar No. 7 #~thaer s)

0. Boone SJames 9. Performing Otgon.,otion Nam* arnd Addes, 10. V-o, Un,'r No (TRAISI

FAA Civil Aeromedical Institute 11. Co....roc, of Grnt No.

P.O. Box 25082

Oklahoma City, Oklahoma 73125 13. Type of Reo,, aon P..od Coe,ed

<) 12. Sponsoving Agency Noae and Addres, Office of Aviation Medicine

I Federal Aviation Administration 14. Sonsoring Agency Cod.

.800 Independence Avenue, S.W.

W ashington, D.C. 20591

IS. SVpp$•qe.anoy Notes

ork was performed under task AM-C-82-PSY-87.

16. Abstrecl In a recent series of papers, Cerathewohl reviewed several mathematical proc'Ždures study was employed to apply in mathematical efforts to develop procedures a functional age index.,'-.The purpose of this to the Federal Aviation Administration

(FAA) pilot medical data to examine the feasibility of devising a linear numberinp system such that (1) the cumulative probability distribution functions (CPDF) for ýcrsons who are not diagnosed as having an acute pathology are lower on the scale thar, hoose diagnosed as having an arute pathology, and (A1) the CPDF's for both ,rcups Iverlap minimally.

FAA pilot medical records were employed in a series of two group discriminant function analyses. Group one consisted of records where no pathology was listed. 3roup two consisted of records where a cardiovascular, cerebrovascular, or diabetic

pathology was listed.

The analyses presented some pertinent results. (4) Age is not as accurate in liscriminating between the sudden incapacitating pathology and nonpathology groups as ".he linear discriminant composite. (1) As age increases from post-50, to post-55,

:o post- 6 9!,)classification accuracy uning the discriminant index increases monotoni- :ally. S etter measures that predict these pathologies with more accuracy would "urther separate the CPDF's of the pathology and nonpathology groups. Based on tiesc- esults a possible strategy for future study on pilot certification is discussed.<

17. Key Words1 .Osbv o S e

Aing Document is available to the public

Functional Age Index through the National Technical Informatlon

Hedical Certification Service, Springfield, Virginia 22161

Discriminant Function

9. Security C1o,69 . (of this ,.0 4,) 20. Ste,,,y V se,,l. (of ,s,,. P-rg) 21... H . Pecks ,o 22. 41e,,w

Unclassified Unclassified 8

Varm DOT F 1700.7 (8-721 Repod..wobi, of conpiced page ,,,,,c,,.il
Reproduced From

Best Available Copy

- .1⁄2- - .... :. . 4 .

" .:,.:.. R i . .. o_ -
- - .. T 6 0540 00001477 3 age

u• Report N.. 2. Government Accession No. 3. Recipient's Catalog No.

-FAA-AH-82- 18 _, R Date

4. Title and SMbtitlO S. Rpesor JIYNE Dote 1982

FUNCTIONAL AGING IN PILOTS: AN EXAMINATION OF A 6. Performing OrgAnisation Code

MATHEMATICAL MODEL BASED ON MEDICAL DATA ON GENERAL AVIATION PILOTS

AVIATION.P.LOTS 8. Performing Organiaation Report No.

7. AuthorS)

James 0. Boone

9. Performing Organisation Name ard Address 10. Work Unit No. (TRAIS)

FAA Civil Aeromedical Institute 11. Contract or Grant No.

P.O. Box 25082 Oklahoma City, Oklahoma 73125 13. Type of Report and Period Covered

12. Sponsoring Agency Name and Address

Office of Aviation Medicine

Federal Aviation Administration

800 Independence Avenue, S.W. 14. Sponsoring Agenc•/Code

Washington, D.C. 20591 ..... ...

15. Supplementary Notes

Work was performed under task AM-C-82-PSY-87.

16. Abstract

In a recent series of papers, Gerathewohl reviewed several mathematical procedures employed in efforts to develop a functional age index. The purpose of this

study was to apply mathematical procedures to the Federal Aviation Administration

(FAA) pilot medical data to examine the feasibility of devising a linear numbering

system such that (i) the cumulative probability distribution functions (CPDF) for

ersons who are not diagnosed as having an acute pathology are lower on the scale than

those diagnosed as having an acute pathology, and (ii) the CPDF's for both groups

overlap minimally.

FAA pilot medical records were employed in a series of two group discriminant

unction analyses. Group one consisted of records where no pathology was listed.

wroup two consisted of records where a cardiovascular, cerebrovascular, or diabetic

?athology was listed.

The analyses presented some pertinent results. (i) Age is not as accurate in

iscriminating between the sudden incapacitating pathology and nonpathology groups as

he linear discriminant composite. (ii) As age increases from post-50, to post-55,

o post-60, classification accuracy using the discriminant index increases monotonially. (iii) Better measures that predict these pathologies with more accuracy would

urther separate the CPDFts of the pathology and nonpathology groups. Based on these

esults a possible strategy for future study on pilot certification is discussed.

Y17. Key Wordle 18. Distribution Statement

ing Document is available to the public

unctional Age Index through the National Technical Information

edical Certification Service, Springfield, VIrginia 22161

iscriminant Function

19. Security Cleslf. (of dti. repswot) 20. Security Cloself. (of this Page) 21. No. af Pages 22. Price

Unclassified Unclassified 8

Form DOT F 1700.7 (-72) Reproduction of completed page authorized
FUNCTIONAL AGING IN PILOTS: AN EXAMINATION OF A MATHEMATICAL

MODEL BASED ON MEDICAL DATA ON GENERAL AVIATION PILOTS

Introduction.

In a recent series of papers Gerathewohl (1,2,3) cogently reviewed the

literature on aging in relation to efforts to develop a precise indication

of a person's ability to function. He also reviewed several efforts to

develop a "functional age" index. The development of such an index has a

very compelling intuitive basis. Everyone probably knows some

chronologically younger persons who function less capably than others who

are chronologically older.

The most significant criticism of efforts to develop a functional index

has been aimed at the selection of the criterion. Most of the studies have

involved a regression of some type using age as the criterion (1). This

strategy, however, contains a serious flaw in that the linear composite (the

functional index) is formed by maximizing the prediction of age which is the

variable one is seeking to replace. Any study of a functional index must

consider this criticism.

If a functional age index were to be developed it would have many

applications. The application of interest in this study is pilot

certification. In March 1960, Federal Aviation Administration (FAA) Civil

Air Regulation 40-22 was implemented which stated that "no individual who

has reached his 60th birthday shall be utilized or serve as a pilot on any

aircraft engaged in air carrier operations." The ruling came under immediate

fire from several groups, including the Air Line Pilots Association (ALPA).

In 1960, the FAA then began what was planned to be a 20-year study on pilot

aging at the Georgetown Clinical Research Institute (GCRI), designed to

develop a physiological aging rating (PAR). Due partly to Federal budgetary

cuts, the Georgetown facility was closed in 1966 and the aging project was

abandoned far short of its goal (4). The recent work by Gerathewohl is the

first major work in the FAA on functional aging since the Georgetown

project.

Gerathewohl's approach to the development of a functional age index

involves three interacting components: (i) physiological measurement, (ii)

psychological measurement, and (Iii) performance measurement. He reasoned

that if an individual were physiologically and psychologically healthy and

could demonstrate sufficient ability to perform well, then that person could

safely be allowed to fly regardless of chronological age. Gerathewohl's

writings reviewed several mathematical procedures employed in efforts to

develop a functional age index. He regarded the FAA medical certification

examination records as one possible source of data that could be used in

developing an index. The purpose of the present study was to apply

mathematical procedures to the FAA pilot medical data to examine the

feasibility of devising a linear numbering system such that (1) the

cumulative probability distribution functions (CPDF) for persons who are not

1
diagnosed as having an acute pathology is lower on the scale than the CPDF's

for those diagnosed as having an acute pathology, and (ii) the cumulative

probability distribution functions for both groups overlap minimally.

Methods.

Medical Data. Medical data were drawn from 8,600 randomly selected

pilot medical certification records taken from the current FAA pilot medical

certification files stored on computer at the Mike Monroney Aeronautical

Center in Oklahoma City. The records were transferred via magnetic tape and

placed on a VAX 11/780 computer for analyses.

Measures. The FAA medical records contain the most recent

physiological measures taken by aviation medical examiners across the

country for pilot medical certification. The records also contain coded

information on various pathologies and abnormalities. A full listing of the

measures in each record can be obtained from the FAA Aeromedical

Certification Branch in Oklahoma City.

Analyses. The first step in the analyses involved variable selection.

In order to view the orthogonal variable structure related to aging, a

factor analysis with a varimax rotation was performed on all the measures.

Loadings on factors where age loaded more highly were examined, and

selection of variables was made on the basis of the factor description. The

selected variables were then employed in a series of two group discriminant

function analyses. Group I consisted of records where no pathology was

listed. Group 2 consisted of records where a cardiovascular,

cerebrovascular, or diabetic pathology was listed. These pathologies were

selected as having an important relationship to sudden incapacitation (4).

This methodology eliminates the inappropriate use of age as a criterion,

replacing it with the criterion of concern, known incapacitating pathology.

As a baseline for comparison, the CPDF's for the two groups were separately

computed and plotted as a function of age (i.e., the cumulative probability

for being a certain age or less and being in either group); the optimum

classification accuracy for the two groups was then calculated. A

comparison with age data was performed by calculating discriminant

functions, optimum classification accuracies, and CPDF's for the two groups.

CPDF's were plotted as a function of discriminant scores for (i) all 8,600

records, (ii) records for those 50 years of age and older, (iii) records for

those age 55 and older, and (iv) records for those age 60 and older. Since

this was a feasibility study and since a large sample size was involved, no

cross-validation was done.

Results and Discussion.

Table 1 shows the factors derived from the factor analysis and the

loadings for each variable. Factors were derived until the eigenvalue fell

below 1.0. Three distinct factors related to age were revealed by the

analysis: (1) a sensory factor (il) a cardiovascular factor, and (Iii) a

blood pressure factor. These factors were used to select variables listed

2
in Table 2 for further analysis. While these factors are congruous with

prior research on aging (1), there are many other variables in the

literature not included in our data base that better discriminate aging,

particularly more stringent cardiovascular measures and simple performance

tasks such as grip strength.

Table I. Factors Associated with Age, Based on

Selected Pilot Medical Data

Measure Loading Measure Loading

Factor I (Sensory) Factor 2 (Arterial-Cardiovascular)

Distant Vision ECG

Right Uncorrected .58 Having I defect code .36

Left Uncorrected .32 Having 2 defect codes .58

Right Corrected .56 Having 3 defect codes .61

Left Corrected .36 Having 4 defect codes .65

Near Vision Having 5 defect codes .49

Right Uncorrected .79 Age .23

Left Uncorrected .41

Right Corrected .79 Factor 3 (Blood Presure)

Left Corrected .36 Systolic .48

Hearing Dystolic .51

Right Ear .78 Age .24

Left Ear .79

Age .45

Table 2. Measures Selected for Analyses, Based on

Factor Analysis

Height Near Vision-Right Eye Uncorrected

Weight Near Vision-Right Eye Corrected

Hearing - Left Ear Near Vision-Left Eye Uncorrected

Hearing - Right Ear Near Vision-Left Eye Corrected

Distant Vision-Right Eye Uncorrected Urinalysis - Albumin

Distant Vision-Right Eye Corrected Urinalysis - Sugar

Distant Vision-Left Eye Uncorrected ECG Defect Code

Distant Vision-Left Eye Corrected Blood Pressure - Systolic

Blood Pressure - Dystolic

Figures I and 2 compare the accuracy of age and the discriminant index

in correctly classifying all records as pathology or nonpathology. The

calculated classification accuracy listed'on the figures is reflected

visually in the CPDF's. Optimizing, the predietion of pathology and

nonpathology groups results in an overall accuracy of 617, using age, and an

accuracy of 822, using the discriminant index. Figures 3 through 5 compare

3
classification accuracy by using the discriminant index for a more refined

grouping based on age. Figure 3 is for those 50 years and older, Figure 4

is for those age 55 and older, and Figure 5 is for those age 60 and older.

The classification accuracies for the age group analyses are 78%, 81%, and

892, respectively.

C

o. Nonpathology

x '0

N." Pathology

Classification

0

C:) Accuracy - 617'

010.00 46.00 82.00

AGE

Figure 1. Cumulative probability functions for

nonpathology and pathology across age.

The figures and classification accuracies present some pertinent

resultst (it Age is not as accurate in discriminating between the selected

sudden incapacitating pathology and nonpathology groups as is the optimized

linear discriminant composite of the selected measures from medical

certification records. (ii) As age increases from post-50, to post-55, to

post- 6 0, classification accuracy using the discriminant index increases

monotonically. (iiM) Better, perhaps more stringent, measures that predict

these pathologies with more accuracy would further separate the CPDF's of

the pathology and nonpathology groups, and the distance of separation would

be greater as age is increased. This would result in far greater

classification accuracy for all age groups, and particularly the older

groups.

4
C)

SPathology

Q- 0 

Classification

0o Accuracy - 82%

01 00 11.00 21.00

INDEX x10

Figure 2. Cumulative probability functions for nonpathology

and pathology across discrimnnant function score

for all records.

0

0, Nonpathology

0 x LI

Pathology

ClassifIcation

0 Accuracy - 78%

1.00 11.00 21.00

INDEX x 10'

Figure 3. Cumulative probability functions for nonpathology

and pathology across discriminant scores for those

age 50 and older.

5
Cý- Nonpatholo

CD

Pathology

C) Classification

ccuracy -81

1i. 00 11.00 21 .00

INDEX x 10'

Figure 4. CUMLiative probability function for nonpathology

and pat~hology across discriminant scores for those

age 55 arnd older.

C)

Nonpathology

0

N Pathology

Co Classification CD Accuracy - 89%

01.00 11.00 21.00

INDEX 10'

Figure 5. Cumulative probability functions for nonpathology

and pathology across discriminant scores for those

age 60 and older.

6
Based on these results, information from prior research where more

stringent measures related to aging were employed, and prior research that

shows a strong relationship between performance and agtng, a possible

strategy for future study emerges. Using the cumulative probability for

pathology across age, an age where sufficient probability for acute

pathology exists could be selected. For pilots above this age, more

stringent physical measures, especially cardiovascular tests, could be made,

and performance measures could be taken during simulator and/or actual

flights. This data base could be utilized to more accurately establish

pathology and to develop a refined, optimized discriminant index. After the

development of the index, a sequential decision process covld occur for

pilot certification. Persons below the selected age could be certified

through utilizing the usual process. Those above the selected age who

desired to continue as pilots could be required to take a more stringent

physical. Pilots with profiles with sufficiently high probability for

pathology based on the more refined measures might not be medically

certified. Pilots with profiles with sufficiently high probability for

nonpathology could move to the next step, i.e., demonstration of pilot

performance. A successful demonstration of performance could then lead to

certification. This strategy could permit pilots above the selected age

whose health profiles match those of healthy persons and who can demonstrate

sufficient performance ability to be allowed to continue flying, while it

could serve to identify those over the selected age whose health profiles

match those of the pathological group and who, consequently, might not be

certified.

7
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REFERENCES

1. Gerathewohl, S.J. 1977. Psychophyslological effects of aging: Developing

a functional age index for pilots: I. A survey of the pertinent

literature. Dept. of Transportation, Federal Aviation Administration,

FAA-AM-77-6. Washington, D.C.

2. Gerathewohl, S.J. 1978. Psychophysiological effects of aging: Developing

a functional age index for pilots: II. Taxonomy of psychological factors.

Dept. of Transportation, Federal Aviation Administration, FAA-AM-78-16.

Washington, D.C.

3. Gerathewohl, S.J. 1978. Psychophysiological effects of aging: Developing a functional age index for pilots: III. Measurement of pilot performance.

Dept. of Transportation, Federal Aviation Administration, FAA-AM-78-27.

Washington, D.C.

4. Holbrook, Heber. 1974. Civil aviation medicine in the bureaucracy.

Bethesda: Banner Publishing Co.

8

.. S. (;vr- n J'rft Ing Off [Ce :1982 394-66A2/326