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Determination of sex from arm bone measurements.

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AMERICAN JOURNAL OF PHYSICAL ANTHROPOLOGY 84:421-426 (1991)
Determination of Sex From Arm Bone Measurements
DARRYL J. HOLMAN AND KENNETH A. BENNETT
Department of Anthropology, The Pennsylvania State University,
University Park, Pennsylvania 16802 (D.J.H.1; Department of
Anthropology, University of Wisconsin-Madison, Madison, Wisconsin
53706 (K.A.B.1
KEY WORDS
Forensic anthropology, Wrist measurements, Bi-
styloid breadth
ABSTRACT
Discriminant function analysis has been applied to numerous
dimensions of the cranial and postcranial skeleton for sex determination of
U S . blacks and whites and is extended here to five measurements of the arm
and wrist. These include maximum lengths of the long arm bones in addition to
two measurements that reflect wrist breadth. Our results indicate that whites
are more accurately classified than blacks, but seven of the 31 possible
measurement combinations common to both groups yield functions with sex
prediction accuracies comparable to most, but not all, functions based on other
parts of the skeleton.
Forensic anthropologists are currently
able to assess the sex of unidentified adult
skeletal remains with an accuracy approaching loo%, depending on the recovered parts
of the skeleton. In many cases, particularly
those involving an intact cranium and pelvis,
qualitative morphologcal observations are
sufficient for accurate sex attribution. In
other cases, involving only fragmentary or
incomplete remains, sex can be determined
by quantitative metric analyses, although
with somewhat lower accuracy. Some of
these metric techniques have dealt only with
absolute size differences, as in Stewart’s
(1979) finding that vertical humeral head
diameters above 47 mm and below 43 mm
“almost certainly” represent males and females, respectively, and Berrizbeitia’s
(1989) demonstration of size differences between males and females in maximum and
minimum radial head diameters. However,
the most widely used statistical technique
has been discriminant function analysis of
skeletal measurements. Sex determination
of US. blacks and whites by this method has
a history of about 25 years, beginning primarily with the pioneering work by Giles
and Elliot (1963) on the cranium and Giles
(1964) on the mandible. Since then, the
method has been applied to measurements
from other skeletal regions, including a combination of postcranial bones (Giles, 1970),
the calcaneus and talus (Steele, 19761,pelvis
@ 1991 WILEY-LISS,INC.
(Kelley, 1979; .Schulter-Ellis et al., 1983,
19851, tibia (Iycan and Miller-Shaivitz,
1984a), femur (DiBennardo and Taylor,
1979; Iacan and Miller-Shaivitz, 1984b),and
sternal rib end (Iycan, 1985). The population-specificnature of the method was recognized early (e.g., Birkby, 19661, which led to
the development of functions on populations
other thanU.S. blacks and whites (see Igcan,
1988, for a full literature review).
Accuracies for sex prediction vary from
one measurement set to another, but most
generally fall within the middle to upper
80th to low 90th percentile range. Notable
exceptions include the studies by DiBennardo and Taylor (1983), who obtained accuracy levels of about 95% with a combination
of pelvic and femoral measurements for simultaneous sex and ethnic attribution, and
Schulter-Ellis et al. (1983, 19851, who reported accuracies of 96% for black and white
sexing from pelvic measurements. The advantages and limitations of discriminant
function sexing have been discussed clearly
by Giles (1970),and we need not add further
comments on this subject. However, it might
be noted that the method was validated over
a decade ago on a test of 52 forensic cases
(Snow et al., 1979) for both sex and ethnic
attribution.
One of the more important applications of
Received October 17,1989; accepted June 29,1990
422
D.J. HOLMAN AND K.A. BENNETT
discriminant function sexing occurs when a
forensic anthropologist is asked to examine
only parts of a dismembered individual, specifically excluding those structures (the cramium and pelvis) upon which sex can be
determined visually with a high level of confidence. Such cases may be infrequent, but
they do occur; therefore, the development of
sexing functions on as many skeletal structures as possible is clearly desirable. Because dismemberment often involves the
hands and arms at different points, our purpose here is to develop functions on certain
measurements of the upper limb.
The feasibility of this was suggested by
Jamison’s (1972)study on living Eskimos, in
which wrist breadth was the most sexually
dimorphic trait among 28 standard anthropometric variables. In addition, an analysis
comparing anthropometric sex dimorphism
between unlike-sex dizygotic twins and unrelated adults from New York City (Bennett,
unpublished data) indicated that wrist
breadth again was the most sexually dimorphic variable among the 38 measurements
under study. Given other indications of sex
dimorphism in the arm (Stewart, 1979;
Hamilton, 1982; Berrizbeitia, 1989), it
seemed appropriate to use a modified version of wrist breadth, in combination with
maximum lengths of the long arm bones, in
an attempt tc develop discriminant functions for sexing U.S. blacks and whites.
MATERIALS AND METHODS
We took a set of five measurements on
each of 302 adult skeletons chosen at random
from the Smithsonian Institution’s Terry
Collection. The sample consisted of 75 black
females, 75 black males, 76 white females,
and 76 white males. While an assistant selected the skeletons and recorded the pertinent information from the morgue records,
one of us (D.J.H.) took all measurements in
order to avoid interobserver error. These
were taken without prior knowledge of age at
death, sex, or ethnic affiliation of the skeleton. No bones with obvious athologies or
healed fractures were include , and all measurements were taken on bones from the left
side.
Maximum lengths of the humerus, radius,
and ulna were measured with an osteometric
board according to Wilder (1920) and approximated to the nearest 0.5 mm. The remaining two measurements represent an
approximation of bistyloid (wrist) breadth,
t;
which for convenience may be referred to as
the semibistyloid breadth (SBB) of the radius and ulna. The SBB of the radius was
measured from the most lateral point on the
styloid process t o the deepest point of the
ulnar notch, at a right angle to the long axis
of the bone. The SBB of the ulna was measured from the most medial point on the
head t o the most lateral point on the styloid
process, again at a right angle to the long
axis. Both were taken with a sliding caliper
and approximated to the nearest 0.1 mm.
The data were analyzed se arately in
three sets, one composed of blac males and
females, a second of white males and females, and a third of pooled black and white
males and females under the assumption of
unknown ethnic affiliation. This allowed us
to develop separate discriminant functions
for sexing individuals within each group. For
the first two groups, data on the first 50
individuals within each sexiethnic group
combination were used to develop the discriminant functions, and data on the first
100 individuals in the third group were used
for the same purpose.
Each analysis was carried out in three
stages. First, the STEPDISC procedure (SAS
Institute, 1985) was used to generate stepwise entry and terminal statistics for the 31
possible combinations of the five variables.
Twelve of these functions satisfied the following selection criteria, although the five
that contained only one measurement were
subsequently deleted due to their rather
poor prediction accuracies: 1)significance of
each variable when entered into the function, 2) significance of every variable in the
final function, and 3) the requirement that
the same function met the first two criteria
for each of the three groups. Because of the
large number of functions tested, we included this third criterion to reduce the
chance of generating a function with meaning only for a certain data set.
In the second stage, the unstandardized
discriminant function coefficients were enerated with the DISCRIM procedure &AS
Institute, 1985).The remaining25 black and
26 white individuals in the first two sex/
ethnic grou combinations and the 51 individuals in t e pooled third grou served as
test samples that were classifie in order t o
determine accuracy of the method independent of the data used to generate the functions. Finally, structure coefficients were
generated with the DSCRIMINANT procedure (SPSSInc., 1988).
K
R
cp
423
DETERMINATION OF SEX FROM ARM BONE
RESULTS
Tables 1 and 2 contain descriptive statistics for the reference and test samples, respectively, in which female mean values for
all measurements were significantly smaller
than male values at P < 0.001. In Tables
3-5 are the unstandardized discriminant
function coefficients for the seven functions
that met the selection criteria given above,
for blacks, whites, and pooled blacks and
whites. These tables also give percentage
accuracies of each function on the test samples, in addition to the structure coefficients
associated with each discriminant function.
As product-moment correlations between
any single variable and the discriminant
function, structure coefficients are included
to indicate how close the variables are related to their respective functions. The values in Table 6 indicate total discriminating
power of each function, as suggested by
Klecka (19801,and are arranged in descending order of importance for each of the three
groups. These orders, except for minor differences among functions 5 , 6, and 7, are the
same for each group. In Table 6 , the percentage values in the ‘relative importance” column were obtained by dividing each eigenvalue by the sum of all eigenvalues. Because
the magnitudes of the eigenvalues are directly proportional to the discriminating
power of each function, the percentages are
the relative power of each function.
DISCUSSION
From the forensic standpoint, the usefulness of this study rests ultimately with the
percenta e accuracies of the seven functions
for the t ree groups. In this context, it is
discouraging that the functions for blacks
provide the lowest discriminating abilities:
Only functions 1, 2, 5 , and 6 show accuracy
levels of 80% or above for both sexes. Misclassification percentages for these four are
also approximately symmetrical by sex,
which would be expected under the assumptions of a multivariate normal distribution
and equality of group covariance matrices.
However, misclassifications for functions 3
and 4 are widely different, as is evident in
Table 3. Such distortion in the probabilities
of group membership can arise when either
or both of the above assumptions are not met,
and, indeed, the only significant difference
(P < 0.002) in variances between the sexes is
for ulna length in blacks. This may explain
the sex difference in predictive accuracy for
a
TABLE 1. Reference sample means and standard
deviations (in mm)
Variable
Blacks
N
Radius SBB
Ulna SBB
Radius length
Ulna length
Humeruslength
Whites
N
Radius SBB
Ulna SBB
Radius length
Ulna length
Humerus length
Pooled black/white
N
Radius SBB
Ulna SBB
Radius length
Ulna 1engtYh
Humerus length
Females
Mean
S.D.
Males
Mean
S.D.
50
28.53
2.05
18.43
1.35
237.03
13.22
254.66
13.62
309.55
16.43
50
32.82
1.88
21.50
1.75
263.38
16.37
282.18 21.58
339.05
19.79
50
27.88
1.78
18.15
1.90
219.96
13.04
236.48
13.06
300.20
15.21
50
31.78
1.80
21.37
1.85
243.59
14.26
260.44
13.70
326.21
18.06
100
28.21
18.29
228.50
245.57
304.88
100
32.30
1.91
21.44
1.80
253.49
18.23
271.31
21.04
332.63
19.93
1.94
1.65
15.63
16.12
16.43
TABLE 2. Test sample means and standard deviations
f i n mmJ
Variable
Blacks
N
Radius
SRR
~~~.~~
Ulna SBB
Radius length
Ulna length
Humerus-length
Whites
N
Radius SBB
Ulna SBB
Radius length
Ulna length
Humerus length
Pooled black/white
N
Radius SBB
Ulna SBB
Radius length
Ulna length
Humerus length
Females
Mean
S.D.
Males
Mean
S.D.
25
25
28.40
1.92
2.56
~~. 32.14
.
~
18.76
21.79
2.04
1.78
17.41
235.92
15.86 253.48
252.36
16.83
15.35 270.76
306.62
17.74 330.66
19.67
26
28.15
1.85
18.27
1.48
11.49
219.88
237.87
11.69
297.90
14.96
26
31.99-- 2.16
21.12
1.41
243.17
12.05
260.35
12.45
327.63 15.74
51
28.27
1.87
1.64
18.51
227.75
15.88
244.97
15.33
302.18
16.80
51
32.06
2.34
21.45
1.76
248.23
15.66
15.53
265.45
329.12 17.66
function 4 (but not necessarily 3 ) , and, if so,
this function should be viewed with considerable caution for both black and pooled
black and white samples.
The results are far more satisfactory for
whites, with all seven functions giving accuracy levels of 85%or better. Misclassification
rates, furthermore, are approximately symmetrical. These levels are comparable to
~
424
D.J. HOLMAN AND K.A. BENNETT
TABLE 3. Unstandardized discriminant function coefficients and structure coefficients (in parentheses)
for U S . blacks'
Measurements
1
Radius SBB
0.827340
(0.807)
0.679517
(0.727)
0.061764
(0.657)
Ulna SBB
Radius length
Ulna length
2
0.883005
(0.848)
0.911964
(0.763)
3
Discriminant function
4
5
0.942549
(0.861)
6
0.936834
(0.886)
0.076352
(0.801)
0.089038
(0.701)
0.998052
(0.904)
0.053734
(0.645)
Humerus length
Constant
Test samole
Correctmale (%)
Correct female (%I)
7
0.959288
(0.920)
1.025215
(0.924)
0.049033
(0.719)
-54.4009
-45.2963
-51.1904
-43.8494
-37.8103
84.0
88.0
84.0
80.0
72.0
92.0
68.0
96.0
80.0
80.0
0.055499
(0.748)
-37.9272
-33.6330
80.0
80.0
84.0
72.0
ITotal discriminant scares less than 0 classify as female.
TABLE 4. Unstandardized discriminant function coefficients and structure coefficients (in parentheses)
for U.S. whites'
Measurements
1
Radius SBB
0.814838
(0.860)
0.511105
(0.676)
0.068677
(0.681)
Ulna SBB
Radius length
2
1.002704
(0.914)
0.557965
(0.718)
3
Discriminant function
4
5
0.994788
(0.917)
6
0.962512
(0.932)
0.743261
(0.786)
0.103340
(0.780)
0.075379
(0.726)
0.764397
(0.820)
0.072218
(0.764)
Ulna length
-50.3240
92.3
84.6
0.680562
(0.794)
0,103546
(0.828)
Humerus length
Constant
Test sample
Correct male (%)
Correct female (%)
7
-40.9365
-47.1465
-46.6558
-38.6377
92.3
84.6
92.3
88.5
96.2
88.5
88.5
92.3
0.073635
(0.744)
-38.1665
-39.1739
84.6
92.3
84.6
84.6
'Total discriminant scares less than 0 classify a s female.
those given b Igcan and Miller-Shaivitz
(1984a,b)and teele (1976)for other nonpelvic bones of the postcranial skeleton as well
as those given by Giles (1970)for cranial and
mandibular measurements. Finally, for the
pooled black and white sample, the results
are, as expected, intermediate between the
black and white groups. All but function 4
show predictive accuracies of 80% or above,
with generally symmetrical misclassifications.
Functions with the strongest discriminating power (1,2,3, and 4)and contain radius
SBB, which, in each case, has the highest
structure coefficient of any variable in the
function. It would therefore seem that this
B
dimension is a more biologically significant
indicator of sexual dimorphism than any of
the other four variables. This is not overly
sur rising with respect to bistyloid breadth,
in %at radius SBB contributes about 60% to
the total breadth in both sedethnic roup
combinations (as inferred from corn ined
mean values of radius SBB and ulna SBB in
Table 1).Ulna SBB is evidently of less biological significance, and none of the long bone
lengths would appear to be of comparable
utility.
Our results suggest that Terry Collection
blacks are less sexually dimorphic than
whites for the dimensions considered, a finding for which no good anatomical or environ-
%
425
DETERMINATION OF SEX FROM ARM BONE
TABLE 5. Unstandardized discriminant function coefficients and structure coefficients (in parentheses)
for U S . blacks and whites'
Measurements
1
Radius SBB
2
0.800243
(0.858)
0.658418
(0.735)
0.032589
(0.593)
Ulna SBB
Radius length
0.888901
(0.877)
0.721568
(0.751)
3
Discriminant function
4
5
0.956186
(0.947)
0.881177
(0.884)
0.059728
(0.713)
0.870315
(0.875)
0.030833
(0.626)
0.893665
(0.911)
0.046487
(0.686)
Humerus length
Constant
Test sample
Correct male (%)
Correct female (W)
7
0.982161
(0.971)
0.046121
(0.654)
Ulna length
6
-45.1420
-41.2248
-40.0423
-37.6819
-31.8971
86.3
84.3
86.3
80.4
80.4
86.3
76.5
84.3
80.4
82.4
0.058092
(0.729)
-35.8044
-29.7653
82.4
84.3
80.4
82.4
ITotal discriminant scores less than 0 classify as female.
TABLE 6. Eigenualues, canonical correlations, and relative importance of functions
Discriminant
function
Eiszenvalue
Relative
imaortance !%)
Canonical
correlation
1.8516
1.6792
1.6291
1.4261
1.2464
1.1988
1.1466
18.19
16.50
16.01
14.01
12.25
11.78
11.27
0.8058
0.7917
0.7872
0.7667
0.7449
0.7376
0.7309
1.6460
1.4577
1.4456
1.4006
1.2339
1.1924
1.1168
17.34
15.36
15.23
14.75
13.00
12.56
11.76
0.7887
0.7701
0.7688
0.7638
0.7432
0.7375
0.7264
1.5563
1.4925
1.2801
1.2163
1.0983
1.0767
1.0119
17.82
17.09
14.66
13.93
12.58
12.33
11.59
0.7803
0.7738
0.7493
0.7408
0.7235
0.7201
0.7092
Blacks
1
2
3
4
5
6
7
Whites
1
2
3
4
5
7
6
Pooled black/white
mental explanation is readily ap arent. This
might or mi ht not apply to mo ern individuals, depengng on the extent to which these
groups are comparable to Terry Collection
skeletons. In this context, Jantz and MooreJansen (1988) have shown convincingly that
accuracy in sex prediction is improved considerably with discriminant functions developed from both cranial and postcranial measurements on modern forensic cases now
B
being registered in the forensic data bank at
the University of Tennessee. For example,
correct sex classification of whites based on
three humeral measurements on these forensic cases approaches 95%. The implication, of course, is that morphological changes
due to secular change or differences in nutrition or other environmental variables have
occurred between the time of growth and
development of Terry Collection individuals
426
D.J. HOLMAN AIVD K.A. BENNETT
and today. Although this would render the
older anatomical collections less appropriate
for the development of sexing discriminant
functions for use in modern situations, as
Jantz and Moore-Jansen (1988) have
stressed, we could not use the University of
Tennessee forensic data bank for the simple
reason that our distal radius and ulnar measurements have not previously been taken
by forensic anthropologists. Substantial improvement in the method might therefore
arise with new functions developed from contemporary measurements. Until then, however, the usefulness of this study will await
practical testing on forensic cases.
ACKNOWLEDGMENTS
We thank Douglas Ubelaker for permitting access to the Terry Collection and Kathy
Murray for valuable assistance during data
collection. We are also grateful to David
Steven for skeleton selection and t o Luci
Kohn and James Cheverud for their comments.
LITERATURE CITED
Berrizbeitia EL (1989) Sex determination with the head
of the radius. J. Forensic Sci. 34:1206-1213.
Birkby WH (1966) An evaluation of race and sex identification from cranial measurements. Am. J. Phys.
Anthropol. 24:21-28.
DiBennardo R, and Taylor JV (1979) Sex assessment of
the femur: A test of a new method. Am. J. Phys.
Anthropol. 50:635-637.
DiBennardo R, and Taylor JV (1983) Multiple discriminant function analysis of sex and race in the postcranial skeleton. Am. J. Phys. Anthropol. 61:305-314.
Giles E (1964) Sex determination by discriminant function analysis of the mandible. Am. J . Phys. Anthropol.
22:129-135.
Giles E (1970) Discriminant function sexing of the human skeleton. In TD Stewart (ed.): Personal Identification in Mass Disasters. Washington, DC: National
Museum of Natural History, Smithsonian Institution,
pp. 99-109.
Giles E, and Elliot 0 (1963) Sex determination by discriminant function analysis of crania. Am. J. Phys.
Anthropol. 21 :53-68.
Hamilton ME (1982) Sexual dimorphism in skeletal
samples. In RL Hall (ed.): Sexual Dimorphism in
Homo sapiens. A Question of Size. New York: Praeger
Publishers, pp. 107-163.
Iacan MY (1985) Osteometric analysis of sexual dimorphism in the sternal end of the rib. J. Forensic Sci.
30:1090-1099.
Igcan M y (1988) Rise of forensic anthropology. Yrbk.
Phys. Anthropol. 31:203-230.
Igcan M y , and Miller-Shaivitz P (1984a) Determination
of sex from the tibia. Am. J. Phys. Anthropol. 645358.
fgcan MY, and Miller-Shaivitz P (1984b) Determination
of sex from the femur in blacks and whites. Coll.
htropol. 8:169-177.
Jamison P (1972) The Eskimos of northwestern Alaska:
Their univariate and multivariate anthropometric
variation. Unpublished PhD Dissertation, University
of Wisconsin-Madison.
Jantz RL, and Moore-Jansen PH (1988) A Data Base for
Forensic Anthropology: Structure, Content and Analysis. Report of Investigations No. 47. Knoxville; The
University of Tennessee.
Kelley MA (1979) Sex determination with fragmented
skeletal remains. J. Forensic Sci. 24:154-158.
Klecka WR (1980) Discriminant Analysis. Sage University Paper series on Quantitative Applications in the
Social Sciences No. 07-019, Beverly Hills, CA: Sage
Publications.
SAS Institute Inc. (1985) SAS User’s Guide: Statistics.
Cary, NC: SAS Institute Inc.
Schulter-Ellis FP, Hayek LA, and Schmidt DJ (1985)
Determination of sex with a discriminant analysis of
new pelvic bone measurements. Part 11. J. Forensic
Sci. 30:178-185.
Schulter-Ellis FP, Schmidt DJ, Hayek LA, and Craig J
(1983)Determination of sex with a discriminant analysis of new pelvic bone measurements. Part I. J.
Forensic Sci. 28:169-178.
Snow CC, Hartman S, Giles E, and Young FA (1979) Sex
and race determination of crania by calipers and computer: A test of the Giles and Elliot discriminant
functions in 52 forensic science cases. J. Forensic Sci.
24:448460.
SPSS Inc. (1988) SPSSRC + Version 2.0 Base Manual.
Chicago; SPSS Inc.
Steele DG (1976)The estimation of sex on the basis ofthe
talus and calcaneus. Am. J. Phys. Anthropol. 45.581588.
Stewart TD (1979) Essentials of Forensic Anthropology:
Especially as Developed in the United States. Springfield, IL: Charles C. Thomas.
Wilder HH (1920)A Laboratory Manual of Anthropometry. Philadelphia: P. Blakiston’s Son & Co.
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