A limitation of the present study is that mostly lean
persons (BMI%25) were measured (151 women and
101 men), who might not have an increased risk of
cardiovascular diseases because of their weight.
However, people with a BMI in the normal weight
range can still be at increased risk of metabolic
disturbances if their WHR or waist circumference is
increased. To obtain an impression as to whether the
results could be applicable to an overweight population,
the analyses were done on a subset of individuals (BMI
between 25 and 30, n Z99 (36 women)). Just as in the
entire cohort, in overweight women, DXA CFM was
highly correlated with central skinfolds (SSCSI;
rZ0.84). Peripheral skinfolds were correlated slightly
less with DXA PFM (BICTRI; rZ0.69), whereas the
skinfolds ratios were correlated slightly higher with
DXA ratio ((SSCSI)/(TRICLEG); rZ0.72). In over-
weight men, DXA CFM was highly correlated with waist
circumference (rZ0.83). Of the skinfold measurements,
SSCSI had the highest correlation rZ 0.69. The
waist/length ratio in men was again the best anthro-
pometric alternative for CFM-to-PFM ratio (rZ0.69). As
in the entire cohort, WHR does not seem appropriate for
the measurement of body fat mass distribution (r%0.4).
Since our study was underrepresented for the purpose
of the prediction of body fat distribution in an obese
population (BMI O30), this needs further investigation.
Another limitation of the study is that the study group
was Caucasian. Ethnic variation of body fat distribution is
well known. Black women, for example, have more bone
and muscle mass, but less fat as a percentage of body
weight than white women, after controlling for ethnic
differences in age, body weight and height (43).Therefore,
heterogeneity of waist circumference (44) and skinfold
(45) cut-off points have been reported. Conclusions
derived from the present study should only be used in
It should be noticed that our results are applicable on
a population level. Since DXA is expressed in kilograms
and skinfolds in millimetres, the Bland–Altman analysis
S.D. of DXA and anthropometrics, to
circumvent problems with different units of the
measurements, will not gain more information than
Pearson’s correlation (46). In conclusion, our study
suggests that for predicting central and peripheral body
fat mass, anthropometric measurements such as waist
circumference and skinfolds are good alternatives in
large epidemiological studies that do not allow appli-
cation of DXA or CT. In daily practice, for the
assessment of CFM-to-PFM ratio, the ratio (SSCSI)/
BMI in women and the waist/length in men are the best
alternatives. According to our study, WHR should not
be used to determine fat distribution. These ﬁndings
might improve the prediction of diabetes and cardio-
vascular risk in men and women in future studies.
Therefore, longitudinal data must be collected to
establish the value of waist circumference and skinfold
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