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A new method to estimate adult age-at-death using the acetabulum.

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AMERICAN JOURNAL OF PHYSICAL ANTHROPOLOGY 000:000–000 (2012)
A New Method to Estimate Adult Age-at-Death
Using the Acetabulum
Stephanie E. Calce*
Department of Anthropology, University of Victoria, Victoria, BC, Canada V8N 1M5
KEY WORDS
bioarchaeology; forensic anthropology; age estimation; stepwise multiple regression
ABSTRACT
Rissech et al. (J Forensic Sci 51 (2006)
213–229) described a method to estimate age-at-death of
adult males using seven traits of the fused acetabulum.
This study simplifies Rissech et al.’s technique and extends
its application to adult females. Rissech et al.’s original
scoring method was applied to a sample of 100 known-aged
adults, three variables were selected based on stepwise
multiple regression, and ages were collapsed into three
broad ranges: young adult (17–39 years), middle adult (40–
64 years), and old adult (651 years). The revised method
was applied to 249 new known-aged individuals from two
other samples. To minimize observer bias, highlight the
most critical traits, and encompass more age-related variation, unique digital renderings accompany morphological
Estimating age-at-death with accuracy is important in
bioarchaeological and forensic investigations because it
is a component of both (1) the biological profile, which
establishes the basic physical identity of a person,
including sex, stature, and ancestral background and (2)
the demographic profile, which helps to form the sample
age distribution. It is well known that activity, genetics,
health, and overall lifestyle affect the rates at which
_ can,
age-related changes are expressed in the skeleton (Is
1989; Boldsen et al., 2002). Because individual growth
rates vary, age-at-death is always reported as a range.
To account for variation in the aging process, continual
testing of skeletal age-at-death techniques is essential.
One area of the skeleton that has frequently been used
for aging adults is the os coxae. Methods using the auricular surface and pubic symphysis are both well documented (Lovejoy et al., 1985; Suchey and Katz, 1998;
Buckberry and Chamberlain, 2002) and employed often
in skeletal aging. Recently, another area of the os coxae,
the acetabulum, has shown promise as an effective age
indicator (Rissech et al., 2006; Rougé-Maillart et al.,
2007; Stull and James, 2010). Due in part to its postdepositional preservation in comparison to other osseous
regions, acetabular patterns of observable degeneration
were first reported in 2004 by Rougé-Maillart et al. who
identified four potentially age-related skeletal features:
the acetabular rim, the acetabular fossa, the lunate surface, and apical activity. Rougé-Maillart et al. (2004) proposed that these acetabular aging traits complemented
Lovejoy et al.’s (1985) auricular surface technique to estimate age, both of which were tested by Rougé-Maillart
on a small modern sample of known age European males
(n 5 30) from Spain and France. The high correlation
between osseous changes and age-at-death led to further
research (Rissech et al., 2006, 2007) on a larger European sample (n 5 394) of adult males from 18th to 20th
century cemetery collections in Portugal, Spain, and
C 2012
V
WILEY PERIODICALS, INC.
descriptions of age categories instead of photos. Three statistically significant characteristics highly correlated with
age (P < 0.05) are capable of estimating age-at-death with
81% accuracy, both sexes combined. For misidentified individuals the tendency was to underestimate age. Results of
both intraobserver error testing and inter-rater reliability
demonstrated a moderate to substantial agreement in scoring between observers. When estimating the degree of development of features osteophyte development of the acetabular rim was the most inconsistent between observers.
The revised acetabular method shows promise in estimating age for adults, particularly for those over the age of 65
V 2012
years. Am J Phys Anthropol 000:000–000, 2012.
C
Wiley Periodicals, Inc.
England. Using a Bayesian calculation procedure for developmental stages of seven age-related traits of the
fused acetabulum, Rissech’s work produced encouraging
results in distinguishing stages within the senior age
category. Because estimating the age of those over 60
years is notoriously difficult for many morphological age
estimation techniques, degeneration of the acetabulum
has a valuable role to play in the identification of the
elderly. Stull and James (2010) recently evaluated
Rougé-Maillart et al.’s (2004) original aging criteria and
found that although acetabular features demonstrate the
capability to estimate age, an improved coding system
and percent correct classification approach is necessary
to determine accuracy and precision.
Further to the work by Stull and James (2010), a preliminary study was conducted (Calce and Rogers, 2011)
to test Rissech et al.’s (2006) adult age estimation
method using the acetabulum on a sample (n 5 100) of
males from the Grant Collection (GRO) housed at the
University of Toronto. The objective of such preliminary
research by the current author was to determine the accuracy and repeatability of several aging criteria proposed by Rissech et al. (2006) on a North American population. Three main problems were identified. First, that
the statistical software program associated with Ris-
*Correspondence to: Stephanie Calce, Department of Anthropology, University of Victoria, P.O. Box 3050, STN CSC, Victoria, BC,
Canada V8W 3P5. E-mail: scalce@uvic.ca
Received 17 February 2011; accepted 28 December 2011
DOI 10.1002/ajpa.22026
Published online in Wiley Online Library
(wileyonlinelibrary.com).
2
S.E. CALCE
sech’s (2006) technique required considerable study and
familiarity before operating; misuse of the program
resulted in erroneous age estimates. The second issue
was intra- and interobserver error. Macroscopic morphological changes for variables two (acetabular rim shape)
and seven (fossa porosity) were difficult to distinguish
and score precisely because descriptions of lesions or
specific regional changes are unclear. This resulted in
subjective coding and high dissimilarity in scoring
between tests where states of rim shape and fossa porosity were scored differently in over half of the cases
(Calce and Rogers, 2011). Lastly, of the seven age-related
traits proposed by Rissech et al. (2006), four did not correlate with chronological age in the GRO collection sample. The purpose of this current research is to create a
more user-friendly and comprehensible scoring method
using morphological traits of the acetabulum that will
reduce data collection time and maintain the accuracy
and precision of estimating age for adults. At this juncture, emphasis is on the need to clarify some of the more
ambiguous trait descriptions and to improve reproducibility of scoring age-associated features. This study simplifies Rissech et al.’s (2006) technique and extends its
application to adult females. Broad age divisions are
used to ensure that the revisions are capable of capturing age-related changes of the acetabulum between geographical populations. The revised method will be particularly useful in bioarchaeological analyses of in situ
remains.
MATERIALS AND METHODS
Several steps were employed in the development of the
present method. Rissech et al.’s (2006) seven acetabular
criteria were originally scored and tested on 100 male
individuals from the GRO (Calce and Rogers, 2011).
Results of this previous research formed the basis of the
first step in this study to simplify the technique (condensing variables from seven to three) by stepwise multiple regression (to be discussed later herein; see also
Results). To reduce intra- and interobserver error, the
author refined three age-related variables and associated
descriptions by seriating male and female ossa coxae
and inspecting broad age-related changes across three
adult age phases. Young, middle, and older aged morphological traits were examined for sex-specific characteristics. Through this assessment, adult age ranges were
defined and form the revised acetabulum method in the
identification of unknown individuals, which was later
tested on two new known-age and -sex samples of male
and female ossa coxae (n 5 249) from the University of
Tennessee (UTen) and University of New Mexico (UNM).
Reducing variables
NCSS 2004 (Hintze, 2006) was used to calculate stepwise multiple regression on the GRO data to determine
which of Rissech et al.’s (2006) original seven variables
were contributing (or affecting) age estimation. Multiple
regression statistics are appropriate because they use
more than one variable (x1, x2, . . ., xi) to estimate the
value of ‘‘y,’’ that is, determine which variables (traits of
the acetabulum) are contributing to estimate age (Manly,
2005). All possible values of ‘‘x’’ (seven variables) were
listed to estimate ‘‘y’’ (age). In this study, a stepwise
selection was performed and all ‘‘x’’ variables (traits of
the acetabulum) not strongly correlated with age
American Journal of Physical Anthropology
Fig. 1. Revised definitions of Variables 1–3: acetabular
groove, denoted by curved line; osteophyte development,
denoted by circle; and apex growth, denoted by arrow. (1) Acetabular groove: found along the rim, the groove becomes more
pronounced with increased age and covers a larger surface area
between the lunate surface and the acetabular rim. (2) Osteophyte development of the acetabular rim: osteophytes develop
below the anterior inferior iliac spine and travel along the acetabular rim to invade the superior area of the lunate surface as
age increases. (3) Apex growth: with age, a sharp spicule forms
at the posterior horn of the lunate surface, and osteophytic development enters the acetabular notch.
(P-value [0.05) were eliminated to find the best fitting
model to predict age for the given variables, i.e., could
not reject the null hypothesis (Ho) for such variables
(where Ho5 acetabular trait correlation with age). A
mixed stepwise selection procedure was used because it
results in the most parsimonious model and is essential
to identify the minimum number of variables needed to
predict age, which in this case were three.
Defining variables and categories of age
Three traits (as determined by stepwise multiple
regression), accounted for most of the variation associated with age: acetabular groove, rim porosity, and apex
activity (see Results). Due to ambiguities with Rissech et
al.’s (2006) original descriptions, these traits were clarified and redefined for this research (Fig. 1). Variable 3
from Rissech et al. (2006; acetabular rim porosity) was
changed to ‘‘osteophyte development of the acetabular
rim’’ to encompass a greater range of variation observed
in this area, and is designated as Variable 2 in the revised method. To evaluate the usefulness of these variables to accurately assign unknown individuals as belonging to broad age categories (young, middle, and old),
ossa coxae of 90 males from the GRO and 39 females
from the William M. Bass Donated Skeletal Collection
(UTen) were seriated based on known ages and examined macroscopically to identify age-related trends.
3
AGE ESTIMATION OF ADULTS AND TRAITS OF THE ACETABULUM
TABLE 1. Sample sizes (n) for testing on the Tennessee and New Mexico collections
Sample Size (n)
Collection
Males
William M. Bass Donated Skeletal Collection (UTen; Knoxville, Tennessee)
Maxwell Museum of Anthropology (UNM; Albuquerque, New Mexico)
85
104c
Females
a
39
60c
Intraobserver error
sample size (n)
Males
Females
25
N/Ab
N/Ab
20
a
Females were seriated based on known chronological age to test for the trend of three contributing variables to expressions of
age-related traits as identified by the author. The three variables form the new revised nonsex specific technique, tested blind on
the skeletal collection in New Mexico (UNM).
b
Intraobserver error testing is not applicable (N/A) for this group.
c
Sample sizes were reduced due to poor preservation of remains.
Fig. 2. Orientation image for Variable 1, acetabular groove. To evaluate, hold the os coxae in anterio-lateral aspect and flip horizontally. The acetabular rim should be viewed close-up, under a light source, and at eye level. The area of inspection includes the
lunate surface where it meets the rim, as denoted by the dotted line.
Specimens were selected from each of the GRO and
UTen collections based on the number of usable skeletons (Table 1). The GRO and UTen were appropriate collections to evaluate the usefulness of acetabular criteria
to estimate age-at-death because they are made up of an
adequate number of male (n 5 147) and female (n 5 87)
specimens (Bedford et al., 1993; UTen Forensic Anthropology Centre, 2005). Seriation of the male GRO and
female UTen samples revealed similar age-related
changes at the acetabular rim, the anterior inferior iliac
spine, and at the apex of the posterior horn of the lunate
surface. Based on trait expression observed within the
GRO and UTen collections of individuals, broad defini-
tions of age were established: young adult (17–39 years),
middle adult (40–64 years), and old adult (651 years).
Variable descriptions for each broad category of age form
the new revised method by the author to estimate ageat-death from the acetabulum (Figs. 2–6). Figures 2 and
3 demonstrate: [1] how the os coxa was oriented for
inspection of variables and [2] point to anatomical locations where age-related characteristics were observed.
Figures 4–6 were used to estimate age for an unknown
individual. Left os coxae were examined, with the right
being substituted if poor preservation precluded analysis
of the left. The acetabulum was morphologically
inspected, focusing on the total pattern of observable
American Journal of Physical Anthropology
4
S.E. CALCE
Fig. 3. Orientation image for Variables 2 and 3, osteophyte development of the acetabular rim, and apex growth. To examine
age-related characteristics, hold os coxae in anterio-lateral position. An adequate light source is favorable to distinguish features of
age-related morphological variation. Areas of examination include the superior portion of the lunate surface below the anterior inferior iliac spine, and the posterior horn of the lunate surface, also known as the apex.
traits to determine whether the individual expressed
similarities associated with either the young, middle, or
older age phase. Based on analogous expressions of
young, middle, or older age qualities (Figs. 4–6), age-atdeath was estimated by reporting a range, 17–39 years,
40–64 years, or 651 years.
American Journal of Physical Anthropology
Testing the revised method
The revised method was tested blind on two contemporary North American skeletal populations (n 5 249). The
UTen collection (N 5 650), housed at the University of
Tennessee Forensic Anthropology Research Center, con-
AGE ESTIMATION OF ADULTS AND TRAITS OF THE ACETABULUM
5
Fig. 4. Line drawings and associated descriptions of Variables 1, 2, and 3 for the young adult age category, 17–39 years. To
assess age of an unknown individual, morphologically inspect the acetabulum and focus on the total pattern of observable traits to
determine whether the individual expresses similarities associated with the young adult age phase. Based on analogous expressions
of young adult age qualities, estimate age-at-death by reporting a range, 17–39 years.
American Journal of Physical Anthropology
6
S.E. CALCE
Fig. 5. Line drawings and associated descriptions of Variables 1, 2, and 3 for the middle adult age category, 40–64 years. Morphologically inspect the acetabulum and focus on the total pattern of observable traits to determine whether the individual
expresses similarities associated with the middle adult age phase. Based on analogous expressions of middle adult age qualities,
estimate age-at-death by reporting a range, 40–64 years.
tains donated complete skeletons predominantly made
up of European-derived (White) or African-derived
(Black) persons (UTen Forensic Anthropology Centre,
2005). The UNM Documented Collection, housed at the
Maxwell Museum of Anthropology at the UNM (N 5
257), contains complete skeletons from donated persons
and positively identified forensic cases with documented
demographic information, representing diverse socioeconomic classes and ethnic affinities (Komar and Lathrop,
2006). Age-at-death is known for 77% of individuals (n 5
698), and 79% of persons (n 5 716) are over 40 years of
age; both robust samples, the UTen and UNM collections
are appropriate models to test age estimation for older
adults (UNM Maxwell Museum of Anthropology, 2003;
UTen Forensic Anthropology Centre, 2005; Komar and
Lathrop, 2006; Grivas and Komar, 2008).
American Journal of Physical Anthropology
Males were tested using both the UTen and UNM
documented collections. Because the test for females was
developed on the UTen sample, age estimation of female
specimens was tested on individuals belonging only to
the UNM collection. The samples were chosen on the basis of high-quality preservation of skeletal elements;
however, of 100 female and 200 male ossa coxae only 60
and 189 respectively were in a condition suitable for
evaluation. In total, 51 specimens were not evaluated
because they were either: poorly preserved; altered by
surgical implant at the site of the acetabular–joint; missing from storage box; or damaged at the rim /apex due
to mishandling. Eighty-five individuals were tested from
the UTen Collection, 164 from the UNM Collection. They
range in age from 19 to 101 years, and died between
1984 and 2006 (UNM Maxwell Museum of Anthropology,
AGE ESTIMATION OF ADULTS AND TRAITS OF THE ACETABULUM
7
Fig. 6. Line drawings and associated descriptions of variables 1, 2, and 3 for the old adult age category, 651 years. Morphologically inspect the acetabulum and focus on the total pattern of observable traits to determine whether the individual expresses similarities associated with the older adult age phase. Based on analogous expressions of older adult age qualities, estimate age-atdeath by reporting a range, 651 years.
American Journal of Physical Anthropology
8
S.E. CALCE
2003; UTen Forensic Anthropology Centre, 2005). Sample sizes are displayed in Table 1, and the age distribution of the sample is presented in Figure 7.
Specimens were chosen randomly from each age category but resulted in a test population made up of largely
‘‘American Whites’’ (n 5 207, males and females combined). Asian descent is not represented in this sample
and ‘‘American Blacks’’ only make up 7% of the total
sample population, whereas ‘‘Hispanic’’ persons are represented by 6%. Of the 249 individuals studied, 11 persons were not identified as belonging to any ancestral
group; reasons for this may include failure to collect relevant information on intake of body donation. Males and
females were examined separately to identify sex-specific
differences or problems with the technique. Individuals
with noninflammatory osteoarthritis were not excluded
because such manifestations are related to age and/or activity. Known ages for each individual were not documented until each specimen was examined, to eliminate
observer bias. If the individual’s known age fell within
the estimated age class (young, middle, or old), the ageat-death calculation was recorded as correct. A measure
of accuracy (how close a measured value is to the actual
Fig. 7. The sample age distribution for both UTen and UNM
collections of individuals (males and females combined) based
on known chronological ages. Across all age classes, age was
estimated for 249 persons. Fewer numbers of individuals are
represented by the young adult age category, likely because
older aged persons have an increased susceptibility to mortality.
A bell shaped curve symmetrical about the mean (60.5 years)
represents the frequency distribution of the test population displayed in 10-year age classes; the sample population is normally
distributed. Above each bar, the number of individuals in each
10-year age class (n) is also reported.
or true value) was calculated by dividing the number of
correct calculations by the total number of specimens. To
test for intraobserver error, 45 individuals were selected
from the UTen and UNM samples (UTen males, n 5 25;
UNM females, n 5 20) and subjected to re-examination
by the author (Table 1). Intraobserver error was calculated by the difference in categorical assignment
between the first and second age estimates. To quantify
interobserver constancy and evaluate the utility of acetabular descriptions with associated line drawings, 55
ossa coxae were observed under identical conditions by
three additional independent observers with varied
osteological experience.
An inter-rater reliability analysis using the weighted
Kappa statistic was performed to determine consistency
among raters (Fleiss and Cohen, 1973; Landis and Koch,
1977). Kappa assesses the proportion of agreement
between observers corrected for chance and the standard
measure of interobserver reliability with nominal data
(e.g., young, middle, and old). Scaled on a range from 21
to 11, a negative kappa value indicates a poorer than
chance agreement, zero indicates agreement totally
by chance alone, a positive value indicates a better than
chance agreement, and 11 indicates perfect agreement
(Fleiss and Cohen, 1973; Walrath et al., 2004). Kappa
does not take into account the degree of disagreement
between observers and all disagreement is treated
equally as total disagreement. Therefore when the categories are ordered, it is preferable to use weighted
Kappa, and assign different weights wi to subjects for
whom the raters differ by i categories, so that different
levels of agreement can contribute to the value of Kappa.
Based on the assessment criteria of Landis and Koch
(1977) for the adequacy of Kappa, a weighted Kappa
score of 0.41–0.60 indicated a ‘‘moderate agreement,’’
and 0.61–0.79 was used as an indicator of ‘‘substantial
agreement’’ between observers for all traits to estimate
age (Landis and Koch, 1977). The Intraclass Correlation
Coefficient (ICC) was used to measure the reliability of
ratings and absolute agreement between three observers
(Shrout and Fleiss, 1979). ICC is useful when two or
more raters are used to rate the same study subjects; in
this study, the measurement of absolute agreement is
valid because systematic differences are relevant to
show consistencies (or irregularities) in scoring (Bartko,
1976). ICC ranges from 21 to 11 where 11 indicates
identical ratings for a subject, or perfect agreement.
Four separate scores for weighted Kappa and ICC were
generated to assess interobserver reliability: (1) the overall ability to estimate age-at-death based on the combi-
TABLE 2. Results of stepwise-multiple-regression for seven variables as defined by Rissech et al. (2006)
In
Yes
Yes
Yes
No
No
No
No
Variable
v1
v3
v4
v2
v5
v6
v7
(groove)
(rim porosity)
(apex activity)
(rim shape)
(outer edge of fossa)
(fossa activity)
(fossa porosity)
Standard
coefficient
R2
increment
R2 other
X’s
T-Value
Probability
level
Pct change
Sqrt (MSE)
0.2523
0.2790
0.2444
0.041516
0.036181
0.037373
0.004172
0.002102
0.004254
0.005560
0.348036
0.535084
0.374115
0.659325
0.309018
0.256713
0.340952
2.6006
2.4278
2.4674
0.8231
0.5831
0.8311
0.9513
0.010776
0.017056
0.015379
0.412540
0.561199
0.408011
0.343878
2.9279
2.4916
2.5893
0.1684
0.3455
0.1615
0.0496
R2 5 0.410699 Sqrt (MSE) 5 12.82071.
List of variables selected v1, v3, and v4.
Note that v3 (rim porosity) as described here as one of the original variables by Rissech et al. (2006) is referred to as Variable 2,
Osteophyte development of the acetabular rim in the revised method.
American Journal of Physical Anthropology
9
AGE ESTIMATION OF ADULTS AND TRAITS OF THE ACETABULUM
TABLE 3. Interobserver reliability using the weighted Kappa statistic (P < 0.001) for (1) the overall age-at-death estimate and (2)
for each individually assessed trait
Observer
comparison
Weighted
Kappaa
Standard
error
95% confidence
interval
3
3
3
3
3
3
3
3
3
3
3
3
0.631
0.585
0.492
0.663
0.506
0.653
0.449
0.486
0.337
0.659
0.698
0.624
0.080
0.081
0.088
0.078
0.080
0.078
0.093
0.091
0.096
0.075
0.074
0.080
0.474–0.788
0.426–0.743
0.319–0.665
0.511–0.815
0.348–0.664
0.501–0.805
0.268–0.631
0.307–0.665
0.148–0.525
0.511–0.806
0.554–0.843
0.467–0.782
Age-at-death estimate
1
2
1
1
2
1
1
2
1
1
2
1
Trait 1 (acetabular groove)
Trait 2 (osteophyte development of the acetabular rim)
Trait 3 (apex growth)
2
3
3
2
3
3
2
3
3
2
3
3
a
Kappa: 0.41–0.60 5 moderate inter-rater agreement; 0.61–0.80 5 substantial inter-rater agreement; 0.81–1.00 5 almost perfect
agreement (Landis and Koch, 1977).
TABLE 4. Interobserver reliability using the Intraclass Correlation Coefficient (ICC) (P < 0.001) for (1) the overall age-at-death estimate and (2) for each individually assessed trait
# of subjects
# of raters
Single measure of ICCa
95% confidence interval
55
55
55
55
3
3
3
3
0.701
0.725
0.543
0.760
0.569–0.796
0.583–0.826
0.388–0.681
0.654–0.843
Age-at-death estimate
Trait 1 (acetabular groove)
Trait 2 (osteophyte development at rim)
Trait 3 (apex growth)
Intraclass correlation coefficient, ICC: 0.5–0.6 5 moderate agreement; 0.7–0.8 5 strong agreement; and [0.8 5 almost perfect
agreement (Portney and Watkins, 2000).
a
nation of three observable traits, i.e., which individuals
were classified as young, middle, or old adults and (2)
how each of the three individual traits (acetabular
groove, osteophyte development of the acetabular rim,
and apical growth) were scored by independent observers
as being young, middle or old.
Box plots, Spearman’s Rank correlation, and the Kruskal–Wallis test were used to compare and analyze population distributions between young, middle, and older
age categories to detect differences and associations
between trait expression and known chronological age.
Statistical analyses were performed using SPSS for Windows release 19.0.0 (1 August 2010) and MedCalc for
Windows, version 11.6.1.0 (MedCalc Software, Mariakerke, Belgium).
RESULTS
Stepwise multiple regression analysis of data using
Rissech et al.’s (2006) original variables on 100 male
skeletons from the GRO (Calce and Rogers, 2011) indicates that there are three statistically significant variables highly correlated with age: Variable 1, acetabular
groove (P-value 0.01); Variable 3, acetabular rim porosity
(P-value 0.017); and Variable 4, apex activity (P-value
0.015). Note that Variable 3, as defined by Rissech et al.
(2006) becomes Variable 2 (osteophyte development
of the acetabular rim) in the revised method. R2 and
P-value coefficients for data collected on the GRO for
each of Rissech et al.’s (2006) seven variables are provided in Table 2.
Testing the revised method
Each observer was able to score traits effectively using
only the information given in the descriptions of varia-
bles (Figs. 2–6). Forty-three out of 45 individuals were
aged the same when subjected to re-examination by the
author (error in scoring 5 4.4%). When estimating age,
the average inter-rater reliability was Kappa 5 0.569
(95% CI 0.407–0.732, SE 0.08) and ICC 5 0.701 (95% CI
0.569–0.796), indicating a moderate to substantial agreement between observers (Tables 3 and 4). Despite their
varied osteological experience, observers were able to
identify acetabular variables consistently and use them
to accurately estimate age. Among all traits, apical activity was the easiest to differentiate (Kappa 5 0.660; ICC
5 0.905); osteophyte development of the acetabular rim
proved the most difficult (K 5 0.424; ICC 5 0.780;
Tables 3 and 4). Age dependence of individual traits is
presented in Table 5 where the correlation between estimated trait scoring and actual age is given by three
independent observers. Experience of the observer and
familiarity with defined character traits can improve
interobserver reliability. Results of both intra- and interobserver error testing demonstrate a reasonable degree
of reproducibility indicating that only a modest amount
of error exists when estimating the degree of development of features. Investigators should be aware that delicate features of the acetabulum are more difficult to distinguish on greasy bone, and specimens may appear
younger in these cases.
Males (n 5 189) and females (n 5 60) were examined
separately; no significant sex-specific differences were
found. In this early stage, it appears the method is not
dependent on sex, although further testing on a larger
female sample is favorable to support these preliminary
results. The three traits identified in this analysis are
highly correlated with age (P \ 0.05), and together are
capable of estimating age-at-death with 81% accuracy,
both sexes combined. Of the percentage wrong (19%),
the tendency was to underestimate age by one age cateAmerican Journal of Physical Anthropology
10
S.E. CALCE
TABLE 5. Correspondence between trait scores and actual age for three independent observers
Young (n 5 15)
Trait 1
Trait 2
Trait 3
Middle (n 5 20)
Old (n 5 20)
Obs 1
Obs 2
Obs 3
Obs 1
Obs 2
Obs 3
Obs 1
Obs 2
Obs 3
10
11
9
9
15
15
10
15
12
10
13
13
14
14
8
9
14
12
14
6
9
10
6
11
16
4
15
TABLE 6. Cross tabulation between actual and
estimated age category
Estimated age category
Actual age category
(n)
Young
Middle
Old
Young
Middle
Old
34
105
110
29
4
2
5
87
22
0
14
86
gory. Overall, errors in assigning an incorrect age grouping were low accounting for 15%, 17%, and 22% of ageat-death estimates for young, middle, and older aged
persons respectively (Table 6).
Population statistics and nonparametric tests
Using Spearman’s Rank correlation (for three variables combined and across all age classes) a positive association between trait expression and known chronological age is occurring within the data set (rs 5 0.7551; P \
0.001). Results demonstrate that variables are correlated
with age in such a way that as trait expression changes
from young to middle to older adult phases, chronological age increases. Because a component system of scoring was not used by the author on the UTen and UNM
test samples, data for each variable was not collected independently, so there is no way to determine whether
correlation between age and trait expression is weaker
when Variables 1, 2, and 3 are analyzed separately.
A Kruskal–Wallis (K–W) test was conducted to compare three groupings of ordinal data: young (n 5 34),
middle (n 5 105), and older (n 5 110) aged categories.
Robust differences were detected among them (P-value
\0.001), indicating that samples are from dissimilar populations and all medians are distinct (Fig. 8). The K–W
test demonstrates that it is possible to detect differences
between broad categories of age through morphological
inspection of three variables: acetabular groove, osteophyte development of the acetabular rim, and apex
growth. Standard deviation representing the sample
spread of individuals around the means for categories of
actual age in young, middle, and old age classes are
found in Table 7. Based on the revised morphological
descriptions of three acetabular variables that form the
basis of this analysis, the probability that young, middle,
and older aged adults display similar characteristics is
nil (0.000).
DISCUSSION AND CONCLUSIONS
Methods to accurately estimate age-at-death for the
adult skeleton are a challenging, but worthwhile investigation. Precise definitions of fewer, more encompassing
variables reduce subjectivity in scoring and increase the
utility of the method, particularly for older aged individuals where joint surfaces are complicated by extrinsic
factors such as weight, infection, and physical activity.
American Journal of Physical Anthropology
Fig. 8. Data is summarized using a box plot to display and
compare sample population distributions between three age categories. Medians for young (32.5), middle (54), and older (76)
aged adults differ. Distributions do not overlap indicating that
it is possible to discern changes in trait expression between
these three age groups.
Low error rate, consistency in scoring and reduction in
data collection time are considerable advantages to using
the author’s technique, but it is important to investigate
bone remodeling and biomechanics to explain behavioral
changes in bone structure relative to the effects of genetics and the environment. Because skeletal morphology is
influenced by a combination of mechanical forces (or
loadings), activity is an important variable to consider,
the effects of which may potentially be a major limitation of the method in general. Teasing apart whether the
observed changes reflect age or activity at the weightbearing site of the acetabulum requires further study.
A holistic approach to scoring age-related traits
Hoppa and Vaupel (2002), Rissech et al. (2006), and
more recently Konigsberg et al. (2008) describe the
promise of a more rigorous and intuitive statistical explanation of estimating age-at-death using the Bayesian
approach. Rissech et al.’s (2006) method relies on the use
of a known comparative collection to generate age ranges
each time an investigator scores an unknown skeleton,
therefore there are no fixed age categories in the original
method. Regrettably, age-at-death estimates using Rissech’s method are biased in the direction of the knownage reference sample, used as a standard of calibration
to estimate age for unknown persons (Boldsen et al.,
2002; Ross and Kimmerle, 2009). To date, many age estimation studies report on the problem of test populations
mimicking age distributions of the original sample (Bocquet-Appel and Masset, 1982; Lucy et al., 1996; Boldsen
et al., 2002; Hoppa and Vaupel, 2002; Ross and Kimmerle, 2009), and although the benefit of computing a
likelihood function for the combination of individually
11
AGE ESTIMATION OF ADULTS AND TRAITS OF THE ACETABULUM
TABLE 7. Descriptive statistics for each age phase young, middle, and old adults representing males and females of the test sample
(n 5 249) from the UTen and UNM collections of individuals
Young adult 17–39 years
Middle adult 40–64 years
Old adult 651 years
Count
Mean
Standard
deviation
Standard
error
Minimum
Median
Maximum
Range
IQR
34
105
110
31.79
52.97
76.74
5.772
7.324
8.388
0.991
0.718
0.803
19
40
65
32.5
54
76
39
64
101
20
24
36
9.5
13
14
age related traits is propitious, so far, methods using the
acetabulum to estimate age have not employed Bayes’
theorem to correct this problem.
A component system was not used because numerical
scoring of qualitative variables requires more rigid
descriptions of progressive biological phenomena (Meindl
et al., 1985). Component scoring systems fail to capture
age-related variability and can be problematic if the investigator does not understand descriptions distinguishing key features. For example, differentiating between
what classifies a trait as ‘‘1’’ from ‘‘2’’ or ‘‘2’’ from ‘‘3,’’ etc.
For these reasons, biological assessment is based on a
basic sequence of modal changes that allows for full integration of all age-related variables and reduces intraand interobserver error (Lovejoy et al., 1985; Brooks and
Suchey, 1990; Meindl et al., 1990). To employ the
author’s new method effectively, all three traits of the
acetabulum for each individual must be in good condition for evaluation: that is, not altered by surgical
implant at the site of the acetabular–joint or damaged at
the rim /apex. Additional research is necessary to determine which trait (1, 2, or 3) is most accurate to estimate
age in adult samples. For now, investigators should
examine the total pattern of observable traits and select
the age category that most closely resembles the acetabular region of the unknown specimen (Lovejoy et al.,
1985; Meindl et al., 1990; Suchey and Katz, 1998; Rogers, 2009). For use with ordinal categorical variables,
modal phase analysis is favorable over the more complicated component scoring system because it incorporates
both early and late phases of development into one age
class (Rogers, 2009). A more robust age class, as is used
in this study, is necessary to provide a more accurate
representation of the variation associated with acetabular morphology (Franklin, 2010). Doing so in a forensic
context avoids excluding decedents based on chronological age and instead, preserves attributes of physiology
(Suchey and Katz, 1998; Cunha et al., 2009). In comparison to the pubic symphyseal and auricular surface aging
methods, the acetabulum technique performs better at
reducing broad categories of age for estimates of
unknown individuals, particularly for those over 50
years (Suchey and Katz, 1998; Buckberry and Chamberlain, 2002). Unlike other areas of the skeleton, continued
age-related changes are observed in the acetabulum
beyond the sixth decade; ‘‘the acetabulum in the future,
may in the end be the most reliable for 60-year-old or
older individuals’’ (Cunha et al., 2009: 5). The next (and
ongoing) step of this research is to develop more narrow
age categories from morphological descriptions particularly for individuals over 65 years.
Directions for future research
Assignment to an incorrect age group was low (19%
across all age classes; Table 6). Percentage wrong estimates for each age category varied with the smallest
error occurring for younger persons (15%), likely because
TABLE 8. Sample age distribution for males and females
in the UTen and UNM collections
Age class
16–20
21–30
31–40
41–50
51–60
61–70
71–80
81–90
91–99
100–109
TOTAL
Young adult (19–39)
Middle adult (40–64)
Old adult (651)
TOTAL
Males (n)
Females (n)
2
8
23
31
42
34
28
18
3
0
189
30
91
68
189
0
2
2
3
8
13
15
12
4
1
60
4
14
42
60
the smallest number of individuals belong to this age
category (n 5 34; Table 6), but may also reflect less variation and absolute change to pristine morphology commonly observed in early adulthood. Larger error was
observed for middle and older aged adults (17% and 22%
respectively). The author considers two explanations for
this result. First, large inaccuracies are merely a statistical artifact of the sample, because the largest proportion of UTen and UNM individuals for whom age was
estimated (86% of total sample) belong to these age
classes (Tables 6 and 8). Second, age-related morphological changes are highly variable for individuals 401
years, where further research into specific degenerative
modifications targeting middle-aged and elderly persons
is required (Calce and Rogers, 2011).
Issues of donor-based and forensic skeletal collections
are a current topic of debate in physical anthropology.
Multiple biases of sample distributions must be considered to determine whether these populations are representative of normal variation both in living and decedent
groups (Usher, 2002; Grivas and Komar, 2008). The
research design of this project focused on maximizing
the sample size to include as many usable specimens as
was possible. With respect to sex ratio, males are overrepresented in the test sample accounting for 76% of all
age estimates. Due to the limited number of females
comprised in the entire UNM collection (38.2%), this
result is not considered unusual (Grivas and Komar,
2008). Although no significant sex-specific differences
were found, the sample of female specimens used in this
investigation was small and should be increased. The
author suggests expanding the research to focus more
specifically on the female expression of age-related acetabular traits to determine whether differences in carrying capacity at the femoroacetabular joint produce variable morphology between sexes.
Although the number of individuals in the middle and
older age categories are consistent (Table 8), younger
American Journal of Physical Anthropology
12
S.E. CALCE
adults (17–39 years) are underrepresented (n 5 34, 14%
of total sample; Table 6). As a person ages, they become
more susceptible to mortality which explains the large
number of individuals in the documented UTen and
UNM skeletal collections over 40 years of age, resulting
in an inevitably smaller sample size for persons less
than 39 years. Even though the sample size for young
adults (males and females combined) is not as sizeable
as the middle and older age categories, young traits of
the acetabulum are more easily discernible due to the
density, general smoothness, robusticity, and minimal
porosity. Young adult females (n 5 4) are largely underrepresented in the test sample (Table 8), which is attributed to a general lack in available female specimens for
study in modern late 20th century samples (Marks,
1995; Grivas and Komar, 2008). That said, skeletal collections with a large percentage of female specimens,
such as Hamann-Todd or Robert J. Terry would also be
appropriate.
Applicability of this method to nonwhite populations
must be explored. The investigator plans to test this
method on available collections of various geographical
origins and encourages other researchers to do the same.
Figures 1–6 may serve as datasheets in the estimation
of age for an unknown individual. Morphological features of the acetabulum can be used as an effective age
indicator. The acetabulum is a durable part of skeleton,
which survives well in postdepositional environments
(Haglund, 1997), making the os coxae an important
region of study for methods of personal identification. Investigator confidence using the author’s method is high,
but whenever possible should be combined with multiple
age indicators for the most precise estimation of age-atdeath. The present technique produces encouraging
results, can be completed on a small budget, and within
a reasonable amount of time. Consistency in scoring,
reduction in data collection time, and low error rates are
significant advantages to using the technique, which is
flexible and useful in forensic and bioarchaeological analyses of human remains.
ACKNOWLEDGMENTS
The author thanks the following people: Drs. Helen K.
Kurki, Tracy L. Rogers, and Michael Schillaci for critical
review of the study proposal and/or editorial suggestions
of the manuscript; Joyce Hui, biomedical communications
artist, for producing acetabular renderings; Drs. Heather
J. Edgar and Lee Meadows Jantz for granting access to
skeletal collections; graduate students Catherine Merritt,
Lelia Watamaniuk, and Johanna Kelly for collaborating in
testing observational consistency of the variables; and Dr.
Christopher Ruff as well as three anonymous reviewers
for helpful comments on the manuscript.
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