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Dispersion dimorphism in human populations.

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AMERICAN JOURNAL OF PHYSICAL ANTHROPOLOGY 127:342–350 (2005)
Dispersion Dimorphism in Human Populations
Elisabetta Marini,1 Esther Rebato,2 Walter Racugno,3 Roberto Buffa,1 Itziar Salces,2 and
Silvana M. Borgognini Tarli4*
1
Sezione di Scienze Antropologiche, Dipartimento Biologia Sperimentale, Università di Cagliari, 09042 Monserrato
(Cagliari), Italy
2
Dipartamento de Genética, Antropologı́a Fı́sica y Fisiologı́a Animal, Facultad de Ciencias, Universidad del Paı́s
Vasco-Euskal Herriko Unibertsitatea, 48080 Bilbao, Spain
3
Dipartimento di Matematica, Università di Cagliari, 09124 Cagliari, Italy
4
Unità di Antropologia, Dipartimento di Etologia, Ecologia, e Evoluzione, Università di Pisa, 56126 Pisa, Italy
KEY WORDS
sexual dimorphism; living populations; bootstrap test; female canalization
ABSTRACT
The aim of this paper is to verify the
existence of dispersion (or variability) dimorphism in several anthropometric traits, i.e., some skeletal, muscular,
and adipose dimensions, and to provide an evaluation of
this scarcely considered aspect of sex differences. This
research focuses on two human samples from two different European regions, Sardinia (Italy) and the Basque
Country (Spain). Twenty-three anthropometric measurements were taken. A first qualitative analysis was carried
out comparing the profiles of the coefficients of variation of
each variable in both sexes. Secondly, the equality of variability was verified with different tests. In the normal
case, Student’s t-test, as proposed by Sokal and Braumann
([1980] Syst. Zool. 29:50 – 63), was applied. In the more
general case, it was necessary to resort to resampling
techniques. A suitable bootstrap test was constructed and
the results were compared, when possible, with those obtained by other methods. The measurements showed parallel trends in the two populations. In particular, subcutaneous skinfolds showed significant dispersion dimorphism, with the greatest coefficients of variation in men.
We suggest that this result was linked to stronger canalization in female dimensions related to the reproductive
function and influenced by sociocultural factors. We also
suggest defining dispersion dimorphism, whose existence
is confirmed by the results presented in this paper, as a
descriptive pattern of phenotype variability in both sexes
that can be specific of a given class of anthropometric
traits. Am J Phys Anthropol 127:342–350, 2005.
Intrasexual variability is a distinct level within
the hierarchical classification of variation, starting
with the ontogeny of individuals and going through
intrasexual, intersexual, interdemic, subspecific,
and interspecific levels (Albrecht and Miller, 1997).
As concerns the study of sexual dimorphism in primates, intrasexual variability has received sporadic
consideration (Cope and Lacy, 1992; Ipiña and
Durand, 2000; Kelley and Plavcan, 1998; LaVelle,
1995; Leutenegger and Cheverud, 1982, 1985;
Leutenegger and Larson, 1985; Marini et al., 1999;
Meindl et al., 1985; Oxnard, 1987; Plavcan, 2000,
2001; Plavcan and Cope, 2001; Plavcan and Kay,
1988; Tague, 1989, 1991, 1992, 1995; Wood, 1976).
However, intrasexual variability plays a double
role in the expression of sexual dimorphism: in case
of equal distance between mean values, a decreased
dispersion of measurements in both sexes produces
a decrease in the overlap of corresponding distributions and hence a higher degree of dimorphism;
moreover, intrasexual variability can be in itself a
component of dimorphism when sex differences in
the extent of variability of a given trait are significant (Marini et al., 1999). We propose here the new
label “dispersion dimorphism” which is more appropriate than the usual term “variance dimorphism”
(Marini et al., 1999; Plavcan, 2000), since variance
gives an absolute measure of variability that depends on the order of magnitude of the variables
considered.
The literature aimed at verifying the existence of
dispersion (or variability) dimorphism in primates is
characterized by divergent results. Application of
inadequate statistical methods, or violation of the
assumptions of the statistical model used, may be
possible explanations for such discrepancies.
A series of papers published during the 1980s,
building on research by Schultz (1926), pointed to a
©
2005 WILEY-LISS, INC.
©
2005 Wiley-Liss, Inc.
Grant sponsors: Ministero Istrucione Universitá Ricria (Italy) and
Univirsidad Paı́s Vasco-Euskal Herriko Universitatea (Spain). Grant
number: 1/UPV 00154.310-E-13972/2001.
*Correspondence to: Silvana M. Borgognini Tarli, Unità di Antropologia, Dipartimento di Etologia, Ecologia, e Evoluzione, Università
di Pisa, via S. Maria 55, 56126 Pisa, Italy.
E-mail: borgognini@discau.unipi.it
Received 3 December 2003; accepted 25 June 2004.
DOI 10.1002/ajpa.20134
Published online 6 December 2004 in Wiley InterScience (www.
interscience.wiley.com).
343
DISPERSION DIMORPHISM IN HUMANS
greater male than female variance in body weight,
skeletal, and dental dimensions in several primate species (Leutenegger and Cheverud, 1985;
Leutenegger and Larson, 1985; Wood, 1976) including humans, where a smaller variability of female
pelvic traits was also noticed (Meindl et al., 1985).
On the other hand, Plavcan and Kay (1988), analyzing dental dimensions in several platyrrhine species, found that trait variance in males was less or
greater than that in females in an equal number of
cases. Tague (1989, 1995), studying intrasexual
variability in pelvic traits of humans and nine species of nonhuman anthropoids, did not find significant variability dimorphism. Plavcan (2000) reported a greater male within-sex coefficient of
variation only in 54% of all comparisons performed
with craniometric data in 35 primate species.
On the whole, investigations aimed at verifying
the significance of sex differences refer to a finite set
of variables, mostly represented by body weight and
dental or cranial dimensions. As yet, a systematic
analysis of dispersion dimorphism of different metric traits that can be referred to the various body
compartments (e.g., skeletal, muscular, or adipose)
is not available. These components vary in their
ecosensitivity, and in their expression in the two
sexes (Waddington, 1942). Moreover, it is likely that
various dimensions are differently affected by possible causal mechanisms of variability dimorphism,
such as natural and sexual selection, canalization,
and sociocultural factors.
The aim of the present study was to evaluate the
expression of dispersion dimorphism in anthropometric traits. The investigation was carried out on a
range of variable categories and on two different
human populations, characterized by diverse environments and history, and devoid of appreciable reciprocal gene flow. The study was directed toward
young adults exclusively, in order to avoid possible
confounding sex-by-age interaction effects.
The relevance of the study of dispersion dimorphism lies in the fact that it expands our knowledge
of human variability and sex differences. Moreover,
since most proximate and ultimate factors affect
phenotype variability, the evaluation of dispersion
dimorphism is a necessary step toward the identification of mechanisms working differently on the two
sexes and, therefore, toward the understanding of
causes and correlates of sexual dimorphism. In particular, the study of dispersion dimorphism is a direct way of testing the better female canalization
hypothesis (Hamilton, 1982; Stini, 1972, 1982;
Stinson, 1985), which postulates that males are
more sensitive to the environment than females and
hence generally more variable.
MATERIALS
Basque sample
The sample from the Basque Country consisted of
200 individuals of both sexes (100 males and 100
females) aged 20 –25 years (21.48 ⫾ 1.20 years in
males, and 21.93 ⫾ 1.44 years in females). This
sample came from a broad cross-sectional study on
university students from the Basque Autonomous
Community started in 2001. Most individuals
(89.6% males and 87.5% females) came from urban
areas in one of the three Basque provinces. On the
basis of a preliminary interview used to define socioeconomic status, the sample can be considered
middle class.
Sardinian sample
The Sardinian sample consisted of 280 individuals
of both sexes (140 males and 140 females) aged
20 –25 years (22.01 ⫾ 1.51 years in males, and
22.05 ⫾ 1.38 years in females). The sample came
from a large database collected between 1995–1998
containing personal, social, and anthropometric
data of the Sardinian population. Individuals were
randomly selected from the population born in the
town of Cagliari. On the basis of socioeconomic characteristics, the sample can be considered middle
class.
METHODS
Body measurements
In both samples, 20 measurements were taken:
weight (kg); stature, sitting height, and iliospinal
height (cm); biacromial, biiliac, elbow, and knee
breadths (cm); relaxed and tensed midarm circumferences, and waist, thigh, and calf circumferences
(cm); and biceps, triceps, subscapular, suprailiac,
abdominal, midthigh, and calf skinfolds (mm). In
addition, in the Sardinian sample alone, three cephalic/facial measurements were taken: cephalic length and breadth (cm), and bizygomatic
breadth (cm).
In each sample, measurements were taken by the
same experienced observer (E.M. or E.R.), following
standard international criteria (Weiner and Lourie,
1981; Lohman et al., 1988).
Statistical analysis
The tests more widely used for the comparison of
variability in two populations require assumptions
of the variables under study. Such assumptions are
not always justifiable. In particular, F statistics for
comparison between variances assume the normality and stochastic independence of the two variables.
Moreover, when the variables have different scales,
the significance of the difference between the variances may not be indicative of the different dispersion of the distributions.
The use of an index of relative variability, such as
the coefficient of variation CV⫽␴/␮ removes this
last difficulty, but it does not permit reference to the
F-Fisher probability law, because the ratio of variation coefficients does not follow that distribution
(except in the obvious case of equality between the
two means).
344
E. MARINI ET AL.
TABLE 1. Descriptive statistics and t-test results of sample from Basque Country1
Men
Weight
Stature
Sitting height
Iliospinal height
Breadths
Biacromial
Bi-iliac
Elbow
Knee
Circumferences
Midarm relaxed
Midarm tensed
Waist
Thigh
Calf
Skinfolds
Biceps
Triceps
Subscapular
Suprailiac
Abdominal
Midthigh
Calf
Women
Mean
SD
N
Normality
Mean
SD
N
73.15
175.72
91.46
103.65
10.66
6.63
3.72
5.98
39.20
29.03
6.59
9.51
100
100
100
100
n.s.
n.s.
n.s.
n.s.
58.96
162.10
85.86
95.72
9.50
6.89
3.36
5.25
100
100
100
100
P ⬍ 0.01
n.s.
n.s.
n.s.
3.70
2.44
0.41
0.47
100
100
100
100
P ⬍ 0.01
P ⬍ 0.01
P ⬍ 0.01
n.s.
35.60
27.05
5.79
8.89
2.03
2.15
0.36
0.49
100
100
100
100
n.s.
P ⬍ 0.01
P ⬍ 0.01
P ⬍ 0.01
28.48
30.71
79.65
52.39
36.95
2.80
2.95
8.62
4.48
2.81
100
100
100
100
100
n.s.
n.s.
P ⬍ 0.01
n.s.
n.s.
25.79
26.60
70.71
49.30
35.28
2.70
2.75
8.14
4.41
2.70
100
100
100
100
100
n.s.
P ⬍ 0.01
P ⬍ 0.01
n.s.
P ⬍ 0.01
6.13
9.59
12.21
13.56
16.30
15.21
10.08
3.33
4.99
6.15
7.43
8.55
6.18
5.03
85
85
85
85
85
85
85
P⬍
P⬍
P⬍
P⬍
P⬍
n.s.
P⬍
8.87
16.44
13.32
14.89
16.37
23.99
17.75
3.33
4.99
5.52
6.20
5.88
6.05
5.15
98
98
98
98
98
98
98
n.s.
n.s.
P ⬍ 0.01
n.s.
n.s.
P ⬍ 0.01
n.s.
0.01
0.01
0.01
0.01
0.01
0.01
Normality
t-test
P ⬍ 0.01
P ⬍ 0.01
P ⬍ 0.01
P ⬍ 0.01
P ⬍ 0.01
1
Weight is expressed in kg; skinfolds in mm; all other measurements in cm. Under “Normality” results of Lilliefors test are reported.
Variables above significant level cannot be considered as normally distributed. Results of t-test are shown only when variables were
normally distributed in both sexes. n.s., not significant.
Neither is it possible to bypass the obstacle assuming any functional link between variables, such
as their proportionality for example (Lewontin,
1966), because it would contradict the hypothesis of
variable independence.
Finally, for some anthropometric variables, the
normality assumption is not verified, and therefore
tests of the Student kind cannot be applied. All
things considered, the more general case refers to
variables whose probabilistic model is unknown, so
that the only available information is contained in
the data. In such circumstances, the use of empirical
methods, generally based on resampling techniques,
is suggested.
For this purpose, a bootstrap test for the null
hypothesis H0: CVX1 ⫽ CVX2 vs. the alternative
H1: CVX1 ⫽ CVX2 was designed by using the following
test statistic
冉
兩CV X 1⫺CV X 2兩
冊
CV X2 1
CV X2 2
⫹
2n 1
2n 2
1/2
,
which is asymptotically normal (Sachs, 1984), where
CVXi ⫽ SXi/x៮ i, SXi denotes the standard deviation and
SXi and ni is the size of sample from Xi, I ⫽ 1,2. In
order to evaluate the significance of the test conditional on Ho, i.e., in order to obtain the “bootstrap
distribution” on which the test is based, the following transformation of the original variables was
used:
៮ T ⫹ n 2X
៮ 2T
nX
៮ iT ⫹ 1 1
X⬘i ⫽ X iT ⫺X
, i ⫽ 1,2,
n 1⫹n 2
冉
冊
n1S12 ⫹ n2S22 1/2
៮ iT is the mean
and X
niSi2
value of XiT (more detailed information on the mathematical/statistical properties of the test can be
found in Cabras et al., 2004).
It is easy to show that CVX⬘1⫽CVX⬘2.
The behavior of the test in various anthropological
situations and in comparison with other tests was
considered by Borgognini Tarli, Marini, and
Racugno (unpublished results).
Here, as an example, we will show some comparisons permitted by the assumptions on the variables: in particular, in the case of normally distributed variables, with Student’s t-test as suggested by
Sokal and Braumann (1980), and with the usual
F-test, when the two means are not significantly
different. The inferential analysis of the coefficients
of variation will be preceded by a short descriptive study of the variability profiles (Sokal and
Braumann, 1980) for the comparison of the two
sexes in each population.
We employed the test of Lilliefors (1967), a modified Kolmogorov-Smirnov test that permits using
the sample mean and the sample standard deviation
in place of mu and sigma, in order to identify variables departing from normality.
where XiT ⫽ Xi
RESULTS
Tables 1 (Basque Country) and 2 (Sardinia)
show the results of the test of Lilliefors (1967) on
the normality of intrasexual distribution and of
the comparison between male and female means
(t-test). The first two columns also show means
345
DISPERSION DIMORPHISM IN HUMANS
TABLE 2. Descriptive statistics and t-test results of sample from Sardinia1
Men
Weight
Cephalic length
Cephalic breadth
Bizigomatic breadth
Stature
Sitting height
Iliospinal height
Breadths
Biacromial
Bi-iliac
Elbow
Knee
Circumferences
Midarm relaxed
Midarm tensed
Waist
Thigh
Calf
Skinfolds
Biceps
Triceps
Subscapular
Suprailiac
Abdominal
Midthigh
Calf
1
Women
Mean
SD
N
Normality
Mean
SD
N
67.22
19.26
15.10
13.26
169.89
87.96
101.45
8.46
0.70
0.64
0.75
6.36
3.82
4.68
39.42
27.31
7.02
9.73
140
141
141
137
140
139
93
n.s.
n.s.
n.s.
P ⬍ 0.01
n.s.
n.s.
n.s.
53.71
18.33
14.53
12.46
156.70
83.17
93.50
7.59
0.62
0.58
0.61
6.14
3.63
4.65
140
172
172
159
140
140
101
P ⬍ 0.01
n.s.
P ⬍ 0.01
n.s.
n.s.
n.s.
n.s.
2.42
1.54
0.39
0.55
138
138
103
101
n.s.
n.s.
n.s.
n.s.
35.14
26.37
6.01
8.88
2.01
2.04
0.35
0.51
139
139
117
110
n.s.
n.s.
P ⬍ 0.01
n.s.
P ⬍ 0.01
26.91
30.83
74.90
50.21
34.08
2.60
2.74
6.17
4.70
3.11
139
139
139
97
93
n.s.
n.s.
n.s.
n.s.
n.s.
23.47
25.28
64.41
50.20
32.55
2.01
2.15
5.54
4.47
2.68
134
133
140
99
98
P ⬍ 0.01
P ⬍ 0.01
n.s.
n.s.
n.s.
P ⬍ 0.01
n.s.
P ⬍ 0.01
4.10
7.76
10.34
9.23
12.15
12.35
11.50
1.79
3.76
3.78
4.34
6.52
6.09
5.07
137
140
137
140
97
98
93
P
P
P
P
P
P
P
6.08
13.33
12.71
10.21
12.77
24.65
18.63
2.51
4.78
4.53
4.48
5.74
7.33
6.02
133
140
140
140
111
118
100
P⬍
P⬍
P⬍
P⬍
P⬍
n.s.
n.s.
⬍
⬍
⬍
⬍
⬍
⬍
⬍
0.01
0.01
0.01
0.01
0.01
0.01
0.01
Normality
t-test
P ⬍ 0.01
P ⬍ 0.01
P ⬍ 0.01
P ⬍ 0.01
P ⬍ 0.01
P ⬍ 0.01
0.01
0.01
0.01
0.01
0.01
Legend as in Table 1.
and standard deviations of all metric traits under
study.
At first glance, in both samples, men showed
greater mean values than women in variables related to the skeletal component (heights, breadths,
and cephalic dimensions) and to the muscular component (circumferences). On the other hand, women
had a subcutaneous adipose component more developed than that of men. A similar picture fits well
with general knowledge on the patterns of human
sexual dimorphism in metric traits.
The results of the test of Lilliefors (1967) indicate
that in the Basque Country, many variables do not
meet the normality condition (10 out of 20 in men,
and 9 out of 20 in women). In general, longitudinal
dimensions were more often normally distributed,
whereas skinfolds showed an opposite tendency. The
only five variables with normal distribution in both
sexes (stature, sitting height, iliospinal height, midarm relaxed circumference, and thigh circumference) were examined by t-test to verify the hypothesis of equality between means. As shown in Table 1,
such a hypothesis must be rejected in all cases at the
1% level. Thus, in spite of the assumption of normality, it will be not legitimate to apply the F-test, and
it will be necessary to resort to coefficients of variation for the comparison of dispersion in males and
females.
In the Sardinian sample, variables not normally
distributed were 8 out of 23 in men and 10 out of 23
in women. The t-test was applied to 10 variables.
The difference between male and female means was
always significant, with thigh circumference the
only exception. In this last case only was it possible
to use the F-test to verify the equality of intrasexual
variances, and to adopt this variable as a case for the
comparison by the bootstrap method.
Intrasexual variability profiles
The amount of variation in a range of anthropometric dimensions can be analyzed by means of variability profiles, which are line graphs coefficient of
variation (of CV) values (Sokal and Braumann,
1980). Figures 1 and 2 show the variability profiles
relative to all variables examined in the two samples. It can be noted that variability profiles show
very similar trends in both samples and in the two
sexes.
In the sample from the Basque Country, the variables with a smaller CV were those of longitudinal
dimensions (in the two sexes, coefficients ranged
between 0.038 – 0.058), followed in order of increasing value by transverse breadths (coefficients ranging between 0.050 – 0.094), circumferences (coefficients between 0.076 – 0.115), weight (men CV ⫽
0.146; women CV ⫽ 0.161), and skinfolds, which
showed the greatest CV values (ranging between
0.252– 0.548).
In the Sardinian sample, the CV profiles almost
overlap with those of the Basque sample. The variables with the lowest CV were dimensions of
height, followed in order of increasing value by
transverse measurements, circumferences, body
weight, and finally skinfolds. It must be noted that
CV values of cephalic measurements, taken only
in this sample, were close to those of the other
skeletal dimensions.
346
E. MARINI ET AL.
Fig. 1. Variability profiles in sample from Basque Country.
Fig. 2. Variability profiles in Sardinian sample.
Dispersion dimorphism
Tables 3 and 4 show the intrasexual CV values,
and the results of tests for comparisons between
coefficients, for the populations of the Basque Country and Sardinia, respectively.
In both samples, trait CVs had a slight tendency
toward being greater in males than in females overall. This was due to the consistently higher trait CVs
in males in the skinfold measurements.
As shown in Table 3, containing the data of the
sample from the Basque Country, the bootstrap test
highlighted significant differences, due to greater coefficients of variation in men, in seven characters: all
subcutaneous skinfolds (with the exception of the subscapular), and biacromial breadth.
Also in the Sardinian sample (Table 4), the bootstrap test found significantly dimorphic variables,
with greater male CVs: the triceps, midthigh, and
calf skinfolds, the abdominal skinfold excepted,
which is close to the limit of statistical significance.
The biiliac breadth had a greater CV in women than
in men.
DISPERSION DIMORPHISM IN HUMANS
TABLE 3. Coefficients of variation (CV) in two sexes and
relative statistical comparisons in sample from Basque Country1
Men Women
(CVW)
(CVM)
Weight
Stature
Sitting height
Iliospinal height
Biacromial breadth
Bi-iliac breadth
Elbow breadth
Knee breadth
Midarm relaxed circumference
Midarm tensed circumference
Waist circumference
Thigh circumference
Calf circumference
Biceps skinfold
Triceps skinfold
Subscapular skinfold
Suprailiac skinfold
Abdominal skinfold
Midthigh skinfold
Calf skinfold
0.146
0.038
0.041
0.058
0.094
0.084
0.062
0.050
0.098
0.096
0.108
0.085
0.076
0.543
0.521
0.504
0.548
0.525
0.406
0.499
0.161
0.042
0.039
0.055
0.057
0.079
0.062
0.055
0.105
0.103
0.115
0.089
0.077
0.375
0.304
0.415
0.416
0.359
0.252
0.290
B
tSB
n.s.
n.s.
n.s.
n.s.
n.s.
B, bootstrap test; tSB, t-test proposed by Sokal and Braumann
(1980), only for normally distributed variables. n.s., not significant.
* P ⬍ 0.05.
** P ⬍ 0.001.
TABLE 4. Coefficients of variation (CV) in two sexes and
relative statistical comparisons in sample from Sardinia1
Weight
Cephalic length
Cephalic breadth
Bizigomatic breadth
Stature
Sitting height
Iliospinal height
Biacromial breadth
Bi-iliac breadth
Elbow breadth
Knee breadth
Midarm relaxed
circumference
Midarm tensed
circumference
Waist circumference
Thigh circumference
Calf circumference
Biceps skinfold
Triceps skinfold
Subscapular skinfold
Suprailiac skinfold
Abdominal skinfold
Midthigh skinfold
Calf skinfold
B
0.126
0.036
0.042
0.057
0.037
0.043
0.046
0.061
0.056
0.056
0.057
0.097
0.141
0.034
0.040
0.049
0.039
0.044
0.050
0.057
0.077
0.058
0.058
0.086
n.s.
n.s.
n.s.
n.s.
n.s.
n.s.
n.s.
n.s.
*
n.s.
n.s.
n.s.
0.089
0.085
n.s.
0.082
0.094
0.091
0.435
0.484
0.366
0.470
0.536
0.493
0.441
0.086
0.089
0.082
0.413
0.358
0.357
0.439
0.449
0.297
0.323
n.s.
n.s.
n.s.
n.s.
**
n.s.
n.s.
n.s.
***
**
tSB
F
n.s.
n.s.
n.s.
***
n.s.
n.s.
n.s.
n.s.
and 4. They are always in accordance with those
obtained by the bootstrap test.
DISCUSSION
Intrasexual variability profiles
n.s.
n.s.
n.s.
n.s.
**
n.s.
n.s.
n.s.
n.s.
n.s.
n.s.
n.s.
n.s.
*
**
n.s.
*
**
**
**
1
Men Women
(CVM) (CVW)
347
Intrasexual variability profiles of the anthropometric phenotypes observed in the two population
samples (Basque Country and Sardinia) showed
consistent parallelism (Figs. 1, 2). The more evident
phenomenon was an appreciable divergence in the
variability levels of skinfolds as compared to all
other dimensions, especially skeletal measurements. This pattern of “skinfold phenotype” could be
due to the hereditary and/or environmental component, but it might also be influenced by intra- and
interobserver and instrumental error.
Indirect information on the proportion of phenotype variability that can be attributed to the genetic
or environmental component comes from research
on heritability coefficients. Although heritability estimates are affected by some theoretical limitations
(e.g., they are specific for the population and environment analyzed), there is a general consensus on
the assumption that skeletal measurements have
greater heritability than muscular or adipose dimensions (Mueller, 1977; Salces, 2002; Susanne,
1975). In the case of skinfolds, a substantial influence of the environment (ecosensitivity) is also indicated by their appreciable individual variability during life.
As to residual variability due to technical error,
the reliability values of different anthropometric dimensions are available (Lohman et al., 1988; Marks
et al., 1989; Ulijaszek et al., 1998). Since the reliability of skinfolds is on the same order of magnitude as that of skeletal diameters (R ⫽ 0.81– 0.95),
technical error cannot be the only reason for the
observed differences in variability.
Therefore, the greater phenotype variability of
skinfolds as compared to other measurements might
be mainly ascribed to a stronger environmental influence.
n.s.
1
B, bootstrap test; tSB, t-test proposed by Sokal and Braumann
(1980), only for normally distributed variables; F, F-test, for normally distributed variables with equal means. n.s., not significant.
* P ⬍ 0.05.
** P ⬍ 0.01.
*** P ⬍ 0.001.
In order to confirm the adequacy of the bootstrap
test used, t- and F-tests were also applied whenever
possible. The relative results are shown in Tables 3
Dispersion dimorphism
The range of anthropometric traits analyzed in
the present paper allowed us to show the different
manifestations of dispersion dimorphism in soft-tissue vs. skeletal traits.
As already demonstrated (Plavcan and Kay, 1988;
Plavcan, 2000; Tague, 1989, 1995), cranial and postcranial skeletal dimensions did not show significant
dispersion dimorphism or a noticeably higher frequency of CV values greater in men than in women.
Body circumferences and breadths also did not
show significant differences in variability between
the sexes. The only exceptions were biacromial
breadth in the sample from the Basque Country (CV
value greater in men) and bi-iliac breadth in the
sample from Sardinia (CV greater in women). Since
the last two results had opposite directions in the
348
E. MARINI ET AL.
two samples, it is difficult to assign a specific significance to these results. More focused analysis might
help in better assessing the role of these differences.
The main results of this research clearly indicate
that in both samples, the dimensions of subcutaneous fat showed significant dispersion dimorphism,
with greater variability in men. Although variations
of the phenomenon during the life-course may be
hypothesized, a preliminary analysis of a larger database including individuals aged 6 –75 years from
both countries showed that the trend of dispersion
dimorphism was similar in all age classes (Marini,
Rebato, Buffa, Salces, Floris, and Borgognini Tarli,
unpublished results).
As already discussed in the case of variability
profiles, the different degree of dispersion observed
in the two sexes could be related to the environmental component, to the genetic component, and/or to a
combination between observer and instrumental error. However, we think it reasonable to exclude the
last factor, because it is unlikely that instrument or
observer error would be systematically different between the sexes.
The environmental component could decrease female phenotype variability in case of a reduced sensitivity of the character to macroenvironmental factors (environmental canalization; Wagner et al.,
1997), or in case of lower environmental variation
for women. This last circumstance could be due to
cultural factors, in cases of a more homogenous female lifestyle. In this connection, it was hypothesized that women are more concerned in coping with
body mass and fatness than men (Dornbusch et al.,
1984; Rocandio et al., 2003). Sociocultural factors
might also affect intrasexual variability by influencing mate choice.
As to the genetic component, a lower variability in
females could be due to greater intensity of stabilizing selection, a mechanism that acts predominantly
on quantitative traits (Johnson, 1976; Phillips and
Arnold, 1989; Via and Lande, 1985), or to epistatic
interactions among genes (canalizing selection;
Waddington, 1957). Traits related to fertility can
also be subjected to the action of sexual selection
(Darwin, 1871), and the combination of the two
types of selection would again reduce variability
(Via and Lande, 1985). In fact, Gaulin and Sailer
(1985) showed that female variability in body weight
is lower in cases of sexual selection, asymmetric
parental investment, and nutritional constraints.
Sexual selection, with male choice preferentially directed toward women with particular amounts and
distributions of subcutaneous fat (Morris, 1967),
which is an important determinant of body shape,
might therefore also reduce female variability.
From a theoretical standpoint, each of these potential correlates of dispersion dimorphism might be
influential. At present it is difficult to select the most
effective one(s). The measurements of soft tissues
showing dispersion dimorphism are more phenotypically flexible and ecosensitive, and therefore more
susceptible to the influence of cultural factors. However, they are also very relevant in reproduction and
lactation, and for this reason they might be subjected to environmental canalization and maybe stabilizing or canalizing selection.
The hypothesis that females express greater canalization in growth and body composition traits
than do males was previously advanced (Hamilton,
1982; Stini, 1972, 1982; Stinson, 1985). It predicts
that women are less variable in traits related to
reproduction. Experimental evidence supporting the
above theory is based on comparisons of the degree
of sexual dimorphism in populations experiencing
different levels of environmental stress (Hamilton,
1975; Stini, 1969, 1972; Stinson, 1985; Pucciarelli
et al., 1993). In this case, weaker male canalization
would cause a greater effect on male average dimensions, while females would remain relatively stable.
Other less direct information comes from comparisons of sex-specific morbility and mortality levels,
and from studies on sex differences in secular
trends, or in growth under conditions of environmental stress. Of particular interest are the results
obtained in Guatemalan children, showing greater
environmental influence on boys (Bogin and
McVean, 1982) and on the adipose tissue (Bogin and
McVean, 1981).
The adipose tissue is an active endocrine organ
that influences many aspects of human metabolism
and contributes to adaptation to physiological and
environmental challenges (Mohamed-Ali et al.,
1998). Humans are unique among primates in having major sex-specific fat stores and patterns of fat
distribution (Norgan, 1997; Pond, 1997). Humans
also show sex differences in the mechanisms that
regulate nutrient utilization and energy homeostasis, showing a stronger propensity toward the retention of fat mass during times of energy surfeit in
females than in males (Cortright and Koves, 2000).
Adipose reserves guarantee women the energetic
surplus required during pregnancy and lactation,
and are crucial in case of starvation (McFarland,
1997; Pond, 1997). In this connection, in morphologically complex organisms such as humans, the
power of stabilizing selection may be strong enough
to include environmental canalization in characters
with protective effects for early developmental
stages (Wagner et al., 1997).
CONCLUSIONS
The literature on dispersion dimorphism (Cope
and Lacy, 1992; Ipiña and Durand, 2000; Kelley and
Plavcan, 1998; LaVelle, 1995; Leutenegger and
Cheverud, 1982, 1985; Leutenegger and Larson,
1985; Marini et al., 1999; Meindl et al., 1985;
Oxnard, 1987; Plavcan, 2000, 2001; Plavcan and
Cope, 2001; Plavcan and Kay, 1988; Tague, 1989,
1991, 1992, 1995; Wood, 1976), directed toward the
study of skeletal and dental traits in nonhuman
primates and in humans, is characterized by discor-
DISPERSION DIMORPHISM IN HUMANS
dant results sometimes obtained by inadequate statistical methods.
The present paper tackles this problem using a
range of metric traits sampled in two different human populations: one from the Basque Country and
one from Sardinia. The results were very similar in
the two samples examined.
In agreement with results in the literature
(Plavcan and Kay, 1988; Plavcan, 2000; Tague,
1989, 1995), dispersion dimorphism was absent in
some anthropometric variable categories (such as
breadths and circumferences) that are substantially
related to the skeletal and muscular compartments.
On the other hand, dispersion dimorphism was significantly present, with greater male variability, in
the case of skinfolds. We first excluded instrumental
and/or observer error as a cause. The possible influential factors (environmental canalization, sociocultural pressure, stabilizing selection, and sexual
selection) were discussed. The adipose body compartment would be especially subject to environmental canalization and stabilizing selection because of its role in pregnancy and lactation. The role
of cultural factors that affect most human behavioral traits might be relevant in reducing female
environmental variation by means of direct effects
and by indirect influence on male choice.
ACKNOWLEDGMENTS
We thank the anonymous referees for their comments and observations, which contributed to substantial improvement of this paper.
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