Variation in Osteon Circularity and Its Impact on Estimating Age at Death
Thesis
Presented in Partial Fulfillment of the Requirements for the Degree Master of Arts in the
Graduate School of The Ohio State University
By
Jesse Roberto Goliath, B.A.
Graduate Program in Anthropology
The Ohio State University
2010
Thesis Committee:
Dr. Sam D. Stout, Advisor
Dr. Douglas E. Crews
Dr. Clark Spencer Larsen
Copyright by
Jesse Roberto Goliath
2010
Abstract
Researchers have implemented many histomorphometric techniques to estimate
age at death for human skeletal remains. While previous studies have reported relations
between osteon size and age, few studies have focused on the shape of secondary osteons.
Osteon circularity (On.Cr) is a factor potentially affecting histological estimations.
Additionally, with age the numbers of observable osteons and osteon fragments increase
and an asymptotic value for osteon population density (OPD) is eventually achieved. The
cortex of bones reaches asymptote by 60 years of age, but it can occur as early as age 50.
Once asymptote is reached, histological methods can no longer produce reliable age at
death estimations. The purpose of this study is to establish if circularity differs between
young and old age groups, and whether observed On.Cr is due to the effects of increasing
OPD per unit area and osteon size (area; On.Ar) on the shape of osteons. To determine
circularity, osteons were measured from thin (~100µm) cross-sections of femora and ribs
of 29 individuals under and over the age of 50 from a modern cadaver sample of known
age at death. The observed results support the observations of Currey (1964) and Britz et
al. (2009) that osteon cross-sectional shape becomes more circular with age. With the
increase in the number of osteons and their fragments per unit area (OPD) with age, the
probability of eccentric and larger osteons surviving to be measured decreased
considerably. This finding may be useful to help identify if a bone has reached its OPD
asymptote, or even help refine our ability to estimate age for older individuals.
ii
Dedication
I dedicate this thesis to my family. Without their patience, understanding, support and
most of all love, the completion of this work would have not been possible. I also want to
dedicate this to my Notre Dame family for encouraging me and keeping me grounded.
iii
Acknowledgements
I would like to express my thanks to Dr. Sam Stout, my advisor, for all his direction and
guidance in this project. I acknowledge Dr. Douglas E. Crews and The Ohio State
Statistical Consulting Service of The Ohio State University for their assistance in the
statistical analysis of the research data. Additionally, special thanks go to Dr. Clark
Spencer Larsen for his suggestions and advice on earlier drafts of this thesis.
iv
Vita
May 2003…………………………………...Charleston Catholic High School
2006…………………………………………Induction into the Lambda
Alpha Honor Society
May 2007…………………………………...B.A., Anthropology Honors,
University of Notre Dame
2008…………………....................................The Ohio State University
Graduate Enrichment Fellow
2009 to present……………………………..Graduate Teaching Associate,
Department of Anthropology,
The Ohio State University
Fields of Study
Major Field: Anthropology
v
Table of Contents
Abstract…………………………………………………………………..…………..…..ii
Dedication………………………………………………………………………….….…iii
Acknowledgments………………………………………………..………………..…….iv
Vita………………………………………………………………………………………..v
List of Tables……………………………………………………………………………vii
List of Figures……………………………………………………………………….....viii
Chapter 1: Introduction…………………………………………………………………1
Chapter 2: Methodology…………………………………………………………………6
Chapter 3: Results………………………………………………………………………14
Chapter 4: Discussion…………………………………………………………………..21
Chapter 5: Conclusion………………………………………………………………….26
References……………………………………………………………………………….27
vi
List of Tables
Table 1. Summary of sample data..................................................................................7
Table 2. Descriptive Statistics for the sample data.......................................................12
Table 3. One-sample Kolmogorov-Smirnov Test for all histomorphometric
parameters........................................................................................................................13
Table 4. Summary of statistics from univariate analysis in relation to age................15
Table 5. Summary of statistics from univariate analysis in relation to sex…………19
Table 6. Summary of statistics from paired T-test and correlation............................20
vii
List of Figures
Figure 1. Example of the point at which OPD asymptote is reached……………..…..4
Figure 2. Examples of intact and fragmentary osteons………………………………..9
Figure 3. Images of osteons using programs Spot Basic 3.5.9.1 and ImageJ……….11
Figure 4. Osteon Circularity (On.Cr) for the sample data…………………………..16
Figure 5. Osteon Population Density (OPD) for the sample data……….…………...17
Figure 6. Mean Osteonal Area (On.Ar) for the sample data………………………...18
viii
Chapter 1: Introduction
Several histological methods have been developed for age estimation of
archaeological and forensic skeletal remains (Kerley, 1965; Kerley and Ubelaker, 1978;
Ahlqvist and Damsten, 1969; Thompson, 1980; Stout and Paine, 1992; Cho et al., 2002).
Because these methods rely upon well-established increases in the number of intact and
fragmentary osteons within defined fields or per unit area with age, osteon size (On.Ar)
and circularity (On.Cr) potentially affect histological age estimates. The dimensions of
osteons have been reported to vary with age, notably an age-dependent decrease in osteon
size in humans (Jowsey, 1968; Singh and Gunberg, 1970; Ortner, 1975; Evans, 1976;
Stout and Simmons, 1979; Martin et al., 1980; Thompson, 1980; Thompson and Galvin,
1983; Pfeiffer, 1998; Watanabe et al., 1998; Streeter and Stout, 2003). This decrease has
been found in macaques as well (Burr, 1992; Havill, 2004). However, few studies have
focused on the relationship between age and shape of osteons. Moreover, when aspects of
On.Cr are examined the results are frequently limited to qualitative associations in
regards to strain mode (Skedros et al., 1994) and location with the cortex (Pfeiffer, 1998).
Some notable exceptions include Currey (1964) and Britz et al. (2009). Currey (1964)
reported that the osteons of older individuals are nearly circular whereas younger
individuals have more irregularly shaped osteons. Britz and colleagues (2009) found that
circularity increased with age in the femur. Because osteons are histomorphological
1
products of bone remodeling, a brief review of the remodeling process will be given
before the present study is discussed.
Bone Remodeling
During skeletal development, the processes of growth, modeling (shape change)
and remodeling (turnover) work together to adapt bone for its typical peak biomechanical
demands. After the completion of longitudinal and radial growth, a bone’s potential for
significant modeling activity is greatly reduced. Bone remodeling, however, is
continuous throughout the life of the individual. Remodeling is considered to exist in two
basic forms. Systemic remodeling is stochastic and most likely serves a metabolic
function, e.g., mineral homeostasis. Many authors have suggested a second form of bone
remodeling that is primarily biomechanical in function and targeted to repair
microdamage in bone (Parfitt 1983; Burr, 1993; Bentolila et al., 1998). The breakdown
and renewal of bone that occurs during remodeling aids in skeletal maintenance, and
helps alleviate mechanical stresses such as weight, posture, and physical activity (Wolff,
1892; Woo et al., 1981; Kumar et al., 2005). Bone is remodeled via a complex
multicellular unit that tunnels longitudinally through cortical bone. This basic
multicellular unit (BMU) consists of osteoclasts and osteoblasts. Osteoclasts resorb
existing bone, leaving a tunnel-like cutting cone or resorptive bay behind them. At the
edges of the resorptive bay, mononuclear cells lining the resorptive bay deposit a special
2
thin layer of matrix called a reversal (cement) line, which separates an osteon from the
surrounding cortex. Osteoblasts then move in and begin to lay down new matrix in
concentric lamellae, starting from the edges of the resorptive bay and moving to the
inside of the tunnel, where a central canal is left (Frost, 1969; Parfitt, 1990; 1994). These
canals are known as Haversian canals, and they house blood vessels. The entire structural
unit of reversal line, lamellae, and Haversian canal formed by this process is known as an
osteon or Haversian system (Cooper et al., 1966; Frost, 1969; Widmaier et al., 2001).
Based on its morphology, the osteon can be regarded as an independent bone unit
because it contains its own cellular and blood supply systems.
Because bone remodeling begins at or before birth and continues until death, the
number of secondary osteons increases per unit area with age (Stout and Gehlert, 1979).
However, as the numbers of observable osteons and osteon fragments increase with age,
an asymptotic value for osteon population density (OPD) is eventually achieved (Fig. 1).
OPD is the sum of the observed intact and fragmentary osteons per unit area for a bone
sample (Wu et al., 1970; Stout and Teitelbaum, 1976). The OPD asymptote is the number
of osteons/mm2 at which new osteons begin to remove the evidence of preexisting ones
(Frost, 1987). The cortex of bones usually reaches asymptote by 60 years of age, but it
can occur as early as age 50 (Wu et al., 1970; Frost, 1987). Robling and Stout (2000)
point out that once asymptote is reached, histological methods can no longer produce
accurate age estimations.
3
Figure 1. Image showing the point at which OPD asymptote is reached (Robling and
Stout, 2000)
There are many factors affecting bone-remodeling rates. It is well established that
bone-remodeling rate increases in both males and females in their seventh decade, and
then declines during the next two decades (Martin et al., 2004). Heavy mechanical
loading, for example can accelerate remodeling rates in certain bones and thus potentially
yield estimates above actual age (Wolff, 1892; Woo et al., 1981, Kumar et al., 2005).
Additionally, remodeling rates can be altered through decreased levels of physical
activity or decreased responsiveness to loading (Kohrt, 2001; Pearson and Lieberman,
2004). Diet may also be a factor affecting remodeling rates. Cao and colleagues (2010)
suggest that obesity induced by a high fat diet increases bone resorption that may dampen
any positive effects of increased body weight on bone. Numerous pathological conditions
can also affect remodeling rates and, in turn, age estimations. Diabetes tends to slow
remodeling, and hyperparathyroidism tends to accelerate it (Robling and Stout, 2000).
These factors have received considerable attention in the literature, and a number of
4
researchers have attempted to account for pathological conditions in age estimations
(Ericksen, 1991; Robling and Stout, 2000; Paine and Brenton, 2006).
Hypothesis
Osteon circularity is a variable potentially affecting age at death estimation that is
still not well understood. This is one of the first studies quantitatively examining osteon
shape using a circularity index in both femoral and rib bone. The purpose of this study is
to evaluate the impact osteon shape (circularity) has on age at death estimations. More
specifically, I hypothesize that osteon circularity will increase with age in both femur and
rib cross-sections, and that because OPD increases and osteon area decreases, smaller
more circular osteons are more prevalent as age increases and OPD asymptote is reached.
This is due to the greater likelihood of smaller more circular osteons surviving intact for
measurement.
5
Chapter 2: Methodology
Sample Material
The study sample includes 12 males and 17 females, ages 17-82 years (with a
mean age of 60.4 years). The 29 individuals are a subset of a dissecting room cadaver
collection obtained from Washington University, St. Louis, Missouri. The slides of bone
cross-sections were previously prepared for another study comparing cortical bone
remodeling rates among three archaeological populations and a modern autopsy sample
(Stout and Lueck, 1995). Undecalcified sections were dehydrated and embedded in
methylmethacrylate. Transverse sections, approximately 200µm in thickness,
were cut with a high-speed rotary saw, ground manually to a thickness of approximately
100 µm, and mounted on glass slides (Frost, 1958). Age at death, sex, and cause of death
are known for the individuals (Table 1). The subset contained only individuals of
European ancestry. Each individual was represented by femur and rib sections. All rib
samples were taken from the middle-third of the rib and all femur samples were taken
from the mid-shaft of the femur. These two sampling sites were chosen because they
represent bones of different size and biomechanical loading histories (Robling and Stout,
2000), both factors that affect bone remodeling rate, and therefore age at which OPD
asymptote is reached.
6
Table 1. Summary of sample data
Individual
1
Bones Examined
Femur, Rib
Age
17
Sex
M
2
Femur, Rib
35
F
3
Femur, Rib
39
F
4
Femur, Rib
47
F
5
6
7
8
Femur, Rib
Femur, Rib
Femur, Rib
Femur, Rib
52
53
53
54
M
M
M
F
9
Femur, Rib
55
F
10
11
12
13
Femur, Rib
Femur, Rib
Femur, Rib
Femur, Rib
57
59
59
60
F
F
F
M
14
15
Femur, Rib
Femur, Rib
60
61
F
F
16
17
Femur, Rib
Femur, Rib
62
65
F
F
18
19
20
21
22
Femur, Rib
Femur, Rib
Femur, Rib
Femur, Rib
Femur, Rib
66
66
67
68
68
M
F
M
M
M
23
24
25
Femur, Rib
Femur, Rib
Femur, Rib
70
72
72
M
F
F
26
27
Femur, Rib
Femur, Rib
75
77
M
F
28
Femur, Rib
81
F
29
Femur, Rib
82
M
7
Cause of Death
Aspiration of gastric
contents
Seizure disorder
Diabetes mellitus
(Liver failure)
Hemorrhage
Metastatic Breast
Cancer
Suicide (Drug
overdose)
Carcinomatosis
Pending
Carcinomatosis
Intracerebral
hemorrhage
Metastatic Colon
Cancer
Liver Failure
Ovarian Cancer
Breast Cancer
Cardiac Arrest
Bladder Cancer
Cerebral
Hemorrhage
Cardiac Arrest
Metastatic Breast
Cancer
Lung Cancer
Carcinomatosis
Heart Attack
Pneumonia
Chronic Congestive
Heart Failure
Lung Cancer
Pending
Metastic Breast
Cancer
Gastric Carcinoma
Cerebrovascular
Accident
Cerebral
Hemorrhage
Ventricular
Fibulation
Histomorphometric Variables
Intact and fragmentary osteons (Fig. 2) were defined and counted following a
point-count grid method in order to determine osteon population density (OPD,
osteons/mm2). Half or more of an osteon’s area had to fall within the counting field
(square grid) of the eyepiece reticule to be counted (Pirok et al., 1966; Wu et al., 1970;
Stout and Teitelbaum, 1976). Osteon population density is defined as the number of
intact and fragmentary osteons per unit area (Wu et al., 1970; Stout and Teitelbaum,
1976). An intact osteon is an osteon in which at least 90% of the Haversian canal
exhibits no evidence of remodeling by subsequent osteon generations. Fragmentary
osteons are those in which the evidence of formation or resorption is present in more than
10% of its Haversian canal (Cho et al., 2002). For determining osteon circularity (On.Cr,
unitless), only structurally complete intact osteons with round haversian canals were
measured. On.Cr was measured using circularity index (4*pi*area/square root of
perimeter) the shape factor that indicates to what extent a measured object is similar to a
true circle. One represents a true circle and values approaching zero represent
increasingly elongated shapes (Russ, 1990). Osteon area represented the total area
contained within the cement lines of structurally complete osteons for each specimen. For
determining mean osteonal area (On.Ar, mm2) the average area of 30-35 osteons per
individual/per bone (femur/rib) was calculated. Histomorphometric analyses were
8
performed according to standard criteria (Parfitt et al., 1987) and all abbreviations are
according to the standard nomenclature described by Parfitt et al. (1987).
Figure 2. Intact and fragmentary osteons. Photomicrograph of an unstained
nondecalcified transverse section of a tibia. Thin arrows point to the cement line of
an intact osteon (i) that has partially eliminated an earlier formed osteon to create
an osteon fragment (f). Open arrow indicates a Haversian canal. Heavy arrows
point to the cement line of the osteon fragment. At a 10x magnification (Stout, 1982).
9
Image Analysis
Thirty to thirty-five osteons were measured for each of the femur and rib thin
sections. As osteon size tends to vary in different areas of the bone cortex, perhaps
relating to regional differences in strain levels (van Oers et al., 2008a, b), osteons were
sampled from throughout the entire thin section to obtain representation from all regions.
The prepared slides of bone thin (~100µm) sections were all examined under transmitted
light with an Olympus BX51 research microscope with integrated eyepiece grid to allow
microscopic field delineation and perform area measurements (Kimmel and Jee, 1983). A
camera mounted on the microscope captured polarized and semi-polarized images of the
slides and transmitted them to a computer. Using SPOT Basic 3.5.9.1 software
(Diagnostic Instrument Inc.) and ImageJ software platform (v 1.42; National Institutes of
Health), an outline of each osteon was manually drawn, from which the computer
calculated osteon circularity and area (Fig. 3). A drawing pen tablet (Intuos3, Wacom Co.
Ltd., Japan) was employed for manual outlining of osteon boundaries. Each individual
osteon was outlined separately and served the basis for the calculation of osteon
geometric properties. All osteons which had well defined boundaries were outlined. This
included osteons with ‘classic’ circular shapes and more ‘irregular’ elongated shapes.
Where the majority of an osteon outline (≥ 75%) was visible and the remainder could be
inferred, it was also included. This inclusive approach was taken because it avoided
10
subjective judgment regarding circularity. Calibration at 10x was established with a stage
micrometer. All histomorphometric variables are measured using a 10x magnification.
Figure 3. Spot Basic images from the cortex of the rib of a 17 yr old male at a
magnification of 10x. The second image shows two examples of manually drawn
outlines used to calculate area and circularity.
Statistics
Statistical analyses were performed using SPSS 17.0 (SPSS Inc., Chicago, IL,
USA). Mean values for On.Cr, On.Ar, and OPD were calculated for each individual and
these were employed in subsequent analyses. Summary descriptive statistics for the
sample are provided in Table 2. Komolgorov-Smirnov 1-sample tests confirmed that the
11
collection of mean values was distributed normally for all histomorphometric variables
(Table 3). Univariate analysis of variance was conducted to evaluate the relationship
between osteon geometry and age (fixed factor). The same analysis was done using sex
as a factor. Additionally, a paired T-test and paired correlations were utilized to evaluate
relationships between femur osteon geometry and rib osteon geometry. For all analyses,
significance level was set at p < 0.05 and log-transformed age was used to improve the
linearity of the relationship with the histomorphometric variables.
Table 2. Descriptive Statistics for the sample data
Descriptive Statistics
Std.
N
Minimum
Maximum
Statistic
Statistic
Statistic
Mean
Statistic
Std. Error
Deviation
Variance
Statistic
Statistic
Age (yrs)
29
17
82
60.41
2.583
13.912
193.537
Femur On.Cr
29
.8327
.9272
.902286
.0048094
.0258996
.001
29
.0138
.0653
.034074
.0022828
.0122934
.000
29
9.718
41.100
23.43614
1.173137
6.317534
39.911
29
.857
.924
.90268
.003111
.016753
.000
Rib On.Ar (mm2)
29
.01230
.04255
.0248192
.00178163
.00959435
.000
Rib OPD
29
12.59
42.33
22.9106
1.16426
6.26971
39.309
(unitless)
Femur On.Ar
2
(mm )
Femur OPD
2
(osteons/mm )
Rib On.Cr
(unitless)
2
(osteons/mm )
Valid N
29
12
Table 3. One-sample Kolmogorov-Smirnov Test for all histomorphometric
parameters
One-Sample Kolmogorov-Smirnov Test
N
Normal Parameters
a
Mean
Std.
Femur
Femur
Femur
On.Cr
On.Ar
OPD
Rib On.Cr
Rib On.Ar
Rib OPD
29
29
29
29
29
29
.902286
.034074
23.43614
.90268
.0248192
22.9106
.0258996
.0122934
6.317534
.016753
.00959435
6.26971
Deviation
Most Extreme
Absolute
.223
.158
.091
.172
.155
.131
Differences
Positive
.168
.158
.091
.101
.155
.131
Negative
-.223
-.063
-.067
-.172
-.096
-.074
1.201
.851
.492
.924
.837
.708
.112
.464
.969
.360
.486
.699
Kolmogorov-Smirnov Z
Asymp. Sig. (2-tailed)
a. Test distribution is Normal.
13
Chapter 3: Results
As predicted, there is an age related increase in circularity in both femoral and rib
bones. In addition, osteon circularity was significantly related to age (p=0.000), as were
OPD (p=0.002) and On.Ar (p=0.056) (Table 4). This relation was positive for On.Cr and
OPD and negative for On.Ar. That is circularity and density increased with age while
osteonal area decreased with age.
Scatter plots of the relationships among all variables with age (untransformed) are
provided in Figures 4-6. As reported by Britz et al. (2009), this study found no significant
relationship between sex and circularity (p=.735). Moreover, there was no statistically
significant relationship between sex and On.Ar (p=0.142) nor between sex and OPD
(p=0.841) (Table 5).
A comparison between femur and rib osteon geometry found all three
histomorphometric variables significantly correlated (p= < 0.05), and a paired T-test
showed no significant difference in means for On.Cr (p=0.845) or OPD (p=0.631).
However, there was a significant difference for On.Ar (p=0.000), with the femur having
larger osteons. Results of the paired T-test and correlations are provided in Table 6.
14
Table 4. Summary of statistics from univariate analysis in relation to age
Tests of Between-Subjects Effects
Dependent
Type III Sum of
Source
Variable
Corrected Model
On.Cr
.024a
22
.001
13.853
.000
On.Ar
.004b
22
.000
1.813
.056
1433.672c
22
65.167
2.893
.002
On.Cr
42.935
1
42.935
547528.801
.000
On.Ar
.047
1
.047
438.325
.000
26757.808
1
26757.808
1187.716
.000
On.Cr
.024
22
.001
13.853
.000
On.Ar
.004
22
.000
1.813
.056
1433.672
22
65.167
2.893
.002
On.Cr
.003
35
7.842E-5
On.Ar
.004
35
.000
OPD
788.508
35
22.529
On.Cr
47.266
58
On.Ar
.058
58
33368.407
58
On.Cr
.027
57
On.Ar
.008
57
2222.180
57
OPD
Intercept
OPD
LogAge
OPD
Error
Total
OPD
Corrected Total
OPD
Squares
df
a. R Squared = .897 (Adjusted R Squared = .832)
b. R Squared = .533 (Adjusted R Squared = .239)
c. R Squared = .645 (Adjusted R Squared = .422)
15
Mean Square
F
Sig.
Figure 4. Osteon Circularity Index (unitless). As age increased, there was an
increase in circularity index for both rib and femoral bones.
16
Figure 5. Osteon Population Density (osteons/mm2). As age increased, there was an
increase in the osteon population density for both rib and femoral bones.
17
Figure 6. Osteonal Area (mm2). As age increased, there was a decrease in mean
osteonal area for both rib and femoral bones.
18
Table 5. Summary of statistics from univariate analysis in relation to sex
Tests of Between-Subjects Effects
Dependent
Type III Sum of
Source
Variable
Corrected Model
On.Cr
5.502E-5a
1
5.502E-5
.116
.735
On.Ar
.000b
1
.000
2.220
.142
OPD
1.603c
1
1.603
.040
.841
On.Cr
45.818
1
45.818
96504.877
.000
On.Ar
.050
1
.050
362.587
.000
30144.521
1
30144.521
760.205
.000
On.Cr
5.502E-5
1
5.502E-5
.116
.735
On.Ar
.000
1
.000
2.220
.142
OPD
1.603
1
1.603
.040
.841
On.Cr
.027
56
.000
On.Ar
.008
56
.000
2220.577
56
39.653
On.Cr
47.266
58
On.Ar
.058
58
33368.407
58
On.Cr
.027
57
On.Ar
.008
57
2222.180
57
Intercept
OPD
Sex
Error
OPD
Total
OPD
Corrected Total
OPD
Squares
df
Mean Square
a. R Squared = .002 (Adjusted R Squared = -.016)
b. R Squared = .038 (Adjusted R Squared = .021)
c. R Squared = .001 (Adjusted R Squared = -.017)
19
F
Sig.
Table 6. Summary of statistics from paired T-test and paired correlation
Paired Samples Correlations
N
Correlation
Sig.
Pair 1
Femur On.Cr & Rib On.Cr
29
.961
.000
Pair 2
Femur On.Ar & Rib On.Ar
29
.557
.002
Pair 3
Femur OPD & Rib OPD
29
.572
.001
Paired Samples T-Test
Paired Differences
Sig. (2Mean
Std. Deviation Std. Error Mean
t
df
tailed)
Pair 1
Femur On.Cr - Rib On.Cr
-.0003969
.0108261
.0020104
-.197
28
.845
Pair 2
Femur On.Ar - Rib On.Ar
.00925528
.01056866
.00196255
4.716
28
.000
Pair 3
Femur OPD - Rib OPD
.525586
5.821087
1.080949
.486
28
.631
20
Chapter 4: Discussion
These results support the hypothesis that age is significantly associated with
osteon shape in both rib and femoral bone. Observed results support the observations of
Currey (1964) and Britz et al. (2009) that osteon cross-sectional shape becomes more
circular with age. Additionally, increase is continuous in this sample and continues
beyond the point at which cortical bone reaches OPD asymptote. Further, the observed
increase in circularity with age is consistent with a suggestion by Takahashi and
colleagues (1965) that the decreasing osteon area with age is because larger osteons are
more likely to be overlapped by subsequent remodeling events. Moreover, an increase in
osteon population density in both femur and rib bone cross-sections with age is observed.
An increase in OPD per unit area with age, decreases the probability that eccentric and
larger osteons survive to be measured. More secondary osteons appear with age, creating
more and more osteon fragments. The largest osteons are therefore the most vulnerable to
having part of their area removed by new osteons and are the least likely to survive intact
as the individual ages (Robling and Stout, 2000).
Conversely, the osteonal area decreased with age in both rib and femoral bones
sampled. As previously stated, a decrease in osteon size with age is well documented in
the literature. In this study, there was a significant difference in rib and femoral osteonal
area. Ribs have a relatively thin cortex, are less affected by physical activity than are
load-bearing long bones, like the femur (Raab et al., 1991; Tomerrup et al., 1993). As
21
reported in this study, Pfeiffer (1998) found that the mean osteonal area of ribs was
significantly smaller than the mean osteonal area of femora. Pfeiffer argues that osteon
size is correlated with bone size, for example, smaller bones have smaller osteons.
The increase in OPD and a decrease in On.Ar with age appears to result in
symmetrical, more circular shaped osteons. Additionally, it is important to consider the
effect of mechanical loading, especially when dealing with a load-bearing bone, such as
the femur. Compression or tensile loading increases cross-sectional circularity while
torsion resistance forms osteon shapes that are less resistant to bending (e.g. ellipse)
(Alexander, 1968; Rothschild and Panza, 2007). Also, van Oers and colleagues (2008a,
2008b) found that smaller osteons were located in areas of higher strains. Furthermore,
the presence of reversal lines permits them to act as 'crack stoppers'. Smaller, more
circular osteons may improve the fatigue life of cortical bone as it relates to
microdamage. As age increases, the density of microcrack damage increases in both
males and females (Schaffler et al., 1995). Microcrack propagation will tend to follow
cement lines and lamellar boundaries along the tensile side of a strained element (Martin
and Burr, 1982). It has been suggested that the concentric organization of Haversian
lamellae also acts to limit the progression of a microcrack (Currey, 1962; Saha and
Hayes, 1977; Martin and Burr, 1982; O’Brien et al., 2005; Gibson et al., 2006).
Extending fatigue life through Haversian remodeling is considerably more efficient
metabolically than the alternative of dramatically increasing cross-sectional area (i.e.,
22
bone thickness) (Lipson and Katz 1984). In biomechanics, circularity implies optimum
resistance to "all strain-inducing modes" (Lovejoy et al., 1976: 505).
This and previous studies show that osteons in cortical bone vary in size, even
between two adjacent osteons (Landeros and Frost, 1964; Martin and Burr, 1989; Qiu et
al., 2003). The mechanism(s) for the formation of different sized osteons remains
unclear. It has been suggested that osteon size is determined by the quantity of bone
removed by osteoclasts in one resportive tunnel (Landeros and Frost, 1964; Takahashi
and Frost, 1965). However, a change in osteon size may be considered a desirable
adaptive response. For example, while Moyle and colleagues (1978) found no significant
relation between osteon diameter and toughness in canine femoral bone, specimens that
failed testing had significantly larger osteons. Additionally, a decrease in osteoclastic
activity may contribute to this trend (van Oers et al., 2008a). Van Oers et al. (2008a,
2008b) propose that strain-induced osteocyte signals inhibit osteoclast activity and
therefore affect osteon size. If there is a decreased responsiveness to loading (Kohrt,
2001; Pearson and Lieberman, 2004) with age, one might expect an increase in osteon
size. However, Martin and colleagues (1980) have linked a decrease in osteon size to a
decrease in osteoclastic activity, and Tappen (1977) observed that resorption events do
not always occupy all the space (e.g. highly mineralized older bone) available to them.
Finally, another potential benefit of decreased osteon size may be that, as bone density
23
increases, the introduction of smaller spaces reduces the size of temporary defects, which
might contribute to bone failure.
To eliminate the potential effects of ancestry on the results, I restricted the
examination to only individuals of European ancestry. There is evidence that ancestral
differences exist for bone mass and structure (Ericksen, 1979; Pollitzer and Anderson,
1989; Parfitt, 1997; Cho et al., 2002). In looking at the bone samples themselves there
were some assumptions made. Since autopsies had been performed, it is assumed that the
listed cause of death correctly reflects the state of health for each individual. It is also
assumed that the accident victims represent typical bone turnover rates for their cohort.
Chronically ill individuals probably do not represent typical bone turnover rates, but they
were retained in this sample to insure the broadest data set. This seemed appropriate as
these findings are meant to be applied to unidentified modern skeletal remains or to
archaeological skeletal specimens, which are not necessarily healthy populations. This
data set is particularly well suited to forensic anthropology, since forensic cases would be
from a population similar in age and health distribution to the sample individuals.
In examining the data, there were also some contributing factors that may have
affected the results of this study. Osteon accumulation is limited by the fact that osteons
soon begin to overlap one another as more and more are added (Martin et al., 2004). As
osteons overlap each other it is more difficult to accurately measure circularity. An earlier
generation of osteon may appear to be a fragment but may in fact be a circular intact
24
osteon that has been partially covered. The impact of menopause is another confounding
factor. Older females in the sample were post-menopause. Bone loss associated with an
imbalance in remodeling and cortical thinning (which increases with menopause) is
accelerated in females (Kaptoge et al., 2003; Russo et al., 2006). With an increase in
remodeling, younger menopausal females may have a higher circularity index at an
earlier age. Finally, it is unclear whether the BMUs themselves actually form smaller
osteons as age increases or whether the observed smaller osteons are merely a factor of
osteon crowding with age. Further research should continue to address the study of
osteon shape and its potential applications using circularity index as an additional
variable to examine with current aging methods. For example, in this study, a circularity
index of 0.89 and greater was a clear indication mark for identifying an individual over
the age of 60.
25
Chapter 5: Conclusion
In summary, it was found that with age there is a decrease in osteon size and an
increase in circularity and osteon density. Additional research is needed to better clarify
the underlying cause of the link between age and osteon shape as well as changing osteon
size with age. The present study suggests that the observed increase in osteon circularity
with age can be explained by the effects of increasing osteon population density and/or
decreased osteon size on the shape of osteons. With the increase in osteon population
density (OPD) per unit area with age, the probability of eccentric and larger osteons
surviving to be measured decreases. Those left to measure are smaller and more circular
in shape. It is proposed that including On.Cr, along with other variables, including
osteonal area and OPD, with other known aging methods may enhance our ability to
estimate age at death for older individuals, especially after OPD asymptote is reached. A
better understanding of how osteon shape and size changes with aging would be helpful
in refining forensic and bioarchaeological techniques in which size and shape are a factor.
26
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