The NetScut Anthropometry Calculator
John J. Welch
Georgetown University Medical Center
Department of Pediatrics
Washington DC 20007
The Netscut Anthropometry Calculator (NAC) can be used to compare
individuals or groups
to a growth standard. These results can be useful in determining
the nutritional status of subject and aid in determining if the subject
has a growth abnormality. Data are entered via an HTML form on the
userís computer, submitted over the Internet to a UNIX server, processed
there by a PERL script, and results are returned to the user in an HTML
document in tabular format.
The primary application of anthropometry is assessment of nutritional status
by comparison of observed measurements to a standard. There have
been several standards for growth, but the most widely accepted is the
1977 data set from the NCHS/Fels Institute (1,2).
This data set, while not ideal, is the present international growth standard
(3). The data include measurements of length/stature,
weight, weight-for-length, and head circumference. The NetScut Anthropometry
Calculator (NAC) can be used to calculate these parameters when given the
height, weight, head circumference and age of a subject. When a new
set of standards is released by the NCHS,
the program will be modified to permit choice of the old or new data set
for use in calculations. The advantage of the NAC is that it can
be used from anywhere in the world and has a minimum hardware requirement
for the user. Its source code is freely
available and, although copyrighted, can
be used, modified, and incorporated into other software according to the
terms of the GNU Public License.
form and a plain HTML form. The
form, but the plain form is retained for universality of use. The
from the userís computer. Age can either be calculated from this
date or entered directly. The date-based method is preferred because
an exact date is calculated from the subjectís birthday and is later converted
to fractional months. The user-provided age will usually be based
on the calendar age provided by the subject, and may be rounded up or down.
This source of error can significantly distort the results (4).
units, but converts them to metric units prior to submission of the form.
The plain HTML form does not provide data-entry validation, cannot compute
the age from birth date, and accepts only metric units. A third form
exists for the processing of batched data, for instance, from an
epidemiological survey. This form accepts a comma delimited ASCII file
for input and outputs in similar format.
The heart of the program are the data sets which describe the length, weight,
weight-for-length and head circumference as coefficients to a cubic equations.
The coefficients for length, weight and weight-for-length were published
by Dibley et al (5) and the coefficients for head circumference
were calculated for the NAC using the same methods.
The original data were published by the NCHS as cubic spline-smoothed
percentile curves (1). Each percentile was actually
a composite of several segments, since a single spline would not describe
the entire curve well. Length as used in this program is a
combination of recumbent length for subjects less than 24 months and stature
for older subjects.
The height and weight curves were not normally distributed, making comparisons
at different ages difficult. Dibley et al (5) derived
normalized curves from the original curves and published the coefficients
for these curve. The coefficients for normalized head circumference
curves are available at the NetScut site. Using these normalized
curves, it is possible to calculate Z-scores (multiples of the standard
deviation) for any given observation. These scores are easily comparable
at different ages, and are more useful as the extremes of measurement,
as might be found in areas where malnutrition is present (6,7).
All other statistical parameters are based on the Z-scores.
For each observation, the median (50th percentile) value is calculated.
For instance, for a male subject of 15 months age, the median height is
about 50 cm. If the observation is greater than the 50th percentile,
a Z-score is generated based on a the relative distance between the Z-scores
for the 50th and 97th percentiles. If the observation were less than
the 50th percentile, the Z-score would be based on the 50th and 3rd percentile.
Both 97th and 3rd percentiles are about 1.88 standard deviations from the
median, and the distances from median are computed proportional to this
value. In deriving the 3rd and 97th percentile curves from the original
data, the 97th was based on the averaged standard deviations of the 75th,
90th and 95th percentiles, while the 3rd percentile curve was based on
the 5th, 10th and 25th percentiles to help counter the skew present in
the original curves.
If a Z-score cannot be calculated for a given observation, the program
is unable to calculate the derived values, but will attempt to determine
the value for which the observation is the median. For example, if
a male subject has a head circumference of 48.5 cm, but is four years old,
the Z-score cannot be calculated because it is undefined above 36 months
of age. However, the program can determine that the 48.5 cm is the
median value for a subject of about 18 months of age, hence this subject
has a small head for age.
Several other values are based on the Z-score. These include the
percentile, the absolute value relative to the median, and the percent
of median. The percentile is calculated using an algorithm developed
by Hill (8). The weight and length curves are defined
only up to about 18 years, and head circumference curves are defined up
to 36 months. Above these ages, the script will generate error messages.
The weight-for-length curves are defined between a lower limit of 49 centimeters
and a gender-specific upper limit of about 140 cm. For very large
or small observed values may not correspond to any median value within
these ranges, and an error message will be generated.
An HTML document is returned to the user. It is prefaced by a summary
of the submitted values. All measures are converted to metric units,
and dates are converted to fractional months. These and other values
in the summary are limited to two decimal places, but were internally represented
at the default precision of the PERL script.
The program is designed so that errors will be trapped. Any value
which cannot be calculated is represented in the output as an asterisk,
and an error message appears below the entry.
Difference from similar programs
The program EPIANTH is part of the Epi
Info program which can be downloaded
from the CDC; this program supercedes
the previous program CASP. Excellent documentation
is available online which describes EPIANTH and some of the considerations
regarding computation of anthropometric indices (9).
This program can either calculate the indices from individual subjects
or from batched data. It provides many of features of the NAC, but
does not calculate the value for which the observations are median and
does not perform calculations related to head circumference. The
program ANTHRO, available from the CDC/WHO, performs similar calculations
on flat ASCII or dBase files. The program FORANTH
calculates some head circumference data, but relies on linear interpolation
between the most adjacent smoothed percentile curves. The NAC, however,
uses normalized growth curves for all of its calculations.
I am grateful to Jeffrey R. Backstrand, Ph.D. of New York University
who developed a similar Z-score
this project (10). I would also like to thank Kevin
Sullivan, Ph.D. at Emory University for his helpful comments and the program
and source code for the FORANTH programs. The coefficients of the
smoothed percentile curves describing head circumference are found in the
file. The coefficients for length, weight, and height are from the
Dibley et al. A formatted ASCII and
a Microsoft Excel-97 format file containing
all of the coefficients for the normalized 3rd, 50th and 97th percentile
curves (including the normalized head circumference curves derived for
this project) are available on NetScut.
An excellent discussion of anthropometry and its application is found online
at the Anthropometry Resource Center
National Center for Health Statistics. NCHS Growth Curves for Children
0-18 Years, United States. Vital and Health Statistics. Health Resources
Administration. Washington, D.C.: United States. Government
Printing Office. 1977; Series 11-no. 165.
Hammill PV, Drizd TA, Johnson CL, Reed RB, Roche AF, Moore WM. 1979.
Physical growth: National Center for Health Statistics percentiles.
Am J Clin Nutr 1979;32:607-626.
WHO working group. Use and interpretation of anthropometric indicators
of nutritional status. Bull WHO 1986;64:929-41.
Gorstein J. Assessment of nutritional status: effects of different methods
to determine age on the classification of undernutrition. Bull WHO 1989;67:143-50.
Dibley MJ, Goldsby JB, Staehling NW, Trowbridge FL. Development of normalized
curves for the international growth reference: historical and technical
considerations. Am J Clin Nutr 1987;46:736-48.
Dibley MJ, Staehling N, Nieburg P, Trowbridge FL. Interpretation of Z-score
anthropometric indicators derived from the international growth reference.
Am J Clin Nutr 1987;46:749-62.
Waterlow JC, Buzina R, Keller W, Lane JM, Nichaman, MZ, Tanner JM.
The presentation and use of height and weight data for comparing the nutritional
status of groups of children under the age of 10 years. Bull WHO
Hill ID. Algorithm AS 66. 1973;Appl Stat 22:424.
Sullivan K, Gorstein J, Coulombie D. Epi Info Online Manual. Chapter
23, Example: Programs for Nutritional Anthropometry. URL = "http://www.cdc.gov/epo/epi/intro/manual/manchp23.htm"
Backstrand, AR. Z-scores on the Internet. 1996;URL="http://www.nyu.edu/education/nutrition/software/zscore.htm"
Bender B, Remancus S. Anthropometry Resource Center. 1999;
Please direct all comments to:
Last modification: June 24, 1999