in parentheses correspond to the numbered references in my publication
From 1990 to 1993, I worked
one day a week for the Department of Community Health in the School of
Medicine. I worked at a unit which at that time was called the Division
of Human Biology; now it's called the Lifespan
Health Research Center (LHRC). The LHRC maintains the massive database
for the Fels Longitudinal Study. The Fels Longitudinal Study is the largest
and longest running (started in 1929) longitudinal study of human growth
and development in the world. See Roche, 1992 for
a full description of the Study.
Although I worked on many
projects at LHRC, the focus of my work involved the prediction of adult
(age 18) stature in children, and most of my work was done in collaboration
with Alex Roche, M.D., Ph.D., D.Sc., now retired. Some of the research
was contract work for Genentech pharmaceuticals and some was independent
Let me first motivate this
work by answering the question, "Why predict adult stature?" Of course,
there is always the anxious curiosity of doting parents, but that by itself
might not justify the effort we make in predicting adult stature. Other
important reasons include the following.
In the mid-1970s, researchers
at the Division of Human Biology used the Fels Longitudinal Study data
to conduct an exhaustive investigation in an attempt to determine the most
important predictors of adult stature. Their conclusion: the most important
predictors of adult stature for a child of a given age and gender are (i)
current stature (big surprise!), (ii) current weight, (iii) midparent stature
(another no-brainer), and (iv) skeletal age (a measurement of bone age
based on a skeletal X-ray of the hand and wrist). They then proceeded to
develop a prediction model based on these four predictors from which the
adult stature of a given child could be predicted with a high degree of
accuracy; see Roche et al. (1975) for details.
It is used in medical and psychological
management of child growth. Many children experience erratic growth behavior
near the age of puberty which may lead to adverse psychological effects.
We may be able to avoid therapeutic intervention if we can determine that
the child will achieve a normal stature despite the erratic growth behavior.
Shortness has been correlated
with hyperactivity, poor concentration, low attainment in reading, seriously
elevated blood pressure, and increased risk of heart disease. Hence the
desire by many for therapeutic intervention to avoid short adult stature.
Adult stature prediction is
an important part of treatments involving regulation of dosages for human
growth hormone or anabolic steroids.
It plays an important role in
studying the effects of surgery for congenital heart disease and for the
surgical management of anisomelic children.
It is an important part of intervention
programs involving nutrition and incidence of disease.
Improvements in the methodology
described above have since been incorporated - see (34).
The new method is called MCS**2(1); this stands
for "multivariate cubic spline smoothing with one knot." In an attempt
to make the method more accessible to everyone, the skeletal age predictor
(which requires a hand X-ray to obtain) was omitted. The remaining three
predictors, the child's stature, the child's weight, and the average stature
of the two parents, can be measured by anyone (e.g., the parents themselves).
And interestingly, the deterioration in prediction accuracy after dropping
the skeletal age predictor is not serious; see (39).
The resulting method is called the Khamis-Roche Method and can now be accessed
through the world-wide web (see the end of this article). Be aware, however,
that the height predictor on the web, based on the tables in (39),
are valid only for White Americans who are free from any growth-related
condition or disease. The 90% error margin of such individuals is 2.1 inches
for boys and 1.7 inches for girls on the average - somewhat higher during
the puberty years, and lower for other years. Unfortunately, there is not
a sufficient number of African-American participants, or other ethnic groups,
in the Fels Longitudinal Study data set from which to produce reliable
stature prediction equations.
A very rough rule of thumb
that many parents have used to predict their child's adult stature in inches
is to double their child's stature (in inches) at age two:
Adult stature =
2 x (stature at age 2).
This prediction can be improved
substantially by using simple linear regressions, separately for boys and
girls, of adult stature on stature at age two. These regressions, based
on the Fels Longitudinal Study data, are:
Adult stature =
22.7 + 1.37 x (stature at age 2) for boys, and
The prediction is improved further
by using the Khamis-Roche method, based on three predictors: the child's
stature, the child's weight, and the midparent stature, and can be done
at any age, years 4 - 17.
Adult stature = 25.0 + 1.17
x (stature at age 2) for girls.
Finally, the best prediction
is obtained by using MCS**2(1), which
uses the three predictors listed above in addition to the child's skeletal
age. For comparison purposes, the median absolute deviation (MAD) for each
of these cases is given below (MAD is the median deviation, in absolute
value, between the predicted adult stature and the observed adult stature):
|2 x stature at
Note that doubling the child's
stature at age two is a very unreliable method for girls. Separate simple
linear regressions not only produce more reliable (lower MAD) predictions,
but also predictions that have about the same reliability for boys and
girls. The Khamis-Roche method produces a substantial improvement, and
is only slightly inferior to MCS**2(1).
To calculate the predicted
adult stature of a White, American child using the Khamis-Roche method,
A.F. (1992). Growth, Maturation and Body Composition, The Fels Longitudinal
Study, 1929 - 1991. Cambridge University Press.
A.F., Wainer, H., and Thissen, D. (1975). Predicting Adult Stature for
Individuals. Monogr. Pediatr. 3: 1 - 115.