Ortopedická protetika Praha sro - Společnost pro pojivové tkáně

mixed effects’ (2, 6, 7, 20). This model
is able to give an accurate description of
straight-line dependence as well as the
dependence of a bent curve type if we
choose a polynomial of sufficiently high
degrees. The model that we have chosen
takes into consideration various sources of
variability in observed traits and decomposes
their overall variability into two types:
on one hand the variability due to random
errors of measurement and on the other
hand fluctuation associated with an individual
variability of every proband’s parameters
(18). This model enables us to make
a combined use of both data measured in
individuals with a complete line-up of measurements
and data obtained from individuals
who passed only a lower number of
examinations (2, 3, 4).
growth velocity [units/year]
1,5
1,4
1,3
1,2
1,1
1,0
0,9
0,8
0,7
0,6
0,5
0,4
T1
T2 T3 T4
By means of the model described it
was possible to establish characteristics
of average growth curves of somatic traits
with an even growth dynamic, that show
significant pubertal spurt (PS) and variability
partial growth acceleration in prepubertal
period, mid-growth spurt (MGS)
(13, 17, 21). The dynamics of both spurts
may be described by means of points of
local maximums and minimums of growth
velocity and points, where growth velocity
begins to bend down or up in the sense of
maximal acceleration or deceleration. This
is how it is possible to get for every spurt 4
points labelled as T1–T4 for MGS and T6–
T9 for PS (8, 9, 10, 11, 22, 23). T1 and T6
are points of minimal growth velocity before
a given spurt, T3 and T8 are points of
maximal growth velocity in a given spurt.
0,3 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Figure 1: Model of growth velocity curve (according to Sheehy et al., 1999)
T6
T7
age [years]
POHYBOVÉ ÚSTROJÍ, ročník 14, 2007, č. 3+4 175
T8
T9