Anthropometric measurement error and the assessment of nutritional status

Anthropometry involves the external measurement of morphological traits of human beings. It has a widespread and important place in nutritional assess ment, and while the literature on anthropometric measurement and its interp retation is enormous, the extent to which measurement error can influence b oth measurement and interpretation of nutritional status is little consider ed. In this article, different types of anthropometric measurement error ar e reviewed, ways of estimating measurement error are critically evaluated, guidelines for acceptable error presented, and ways in which measures of er ror can be used to improve the interpretation of anthropometric nutritional status discussed. Possible errors are of two sorts; those that are associa ted with: (1) repeated measures giving the same value (unreliability, impre cision, undependability); and (2) measurements departing from true values ( inaccuracy, bias). Imprecision is due largely to observer error, and is the most commonly used measure of anthropometric measurement error. This can b e estimated by carrying out repeated anthropometric measures on the same su bjects and calculating one or more of the following: technical error of mea surement (TEM); percentage TEM, coefficient of reliability (R), and intracl ass correlation coefficient. The first three of these measures are mathemat ically interrelated. Targets for training in anthropometry are at present f ar from perfect, and further work is needed in developing appropriate proto cols for nutritional anthropometry training. Acceptable levels of measureme nt error are difficult to ascertain because TEM is age dependent, and the v alue is also related to the anthropometric characteristics of the group or population under investigation. R > 0.95 should be sought where possible, a nd reference values of maximum acceptable TEM at set levels of R using publ ished data from the combined National Health and Nutrition Examination Surv eys I and II (Frisancho, 1990) are given. There is a clear hierarchy in the precision of different nutritional anthropometric measures, with weight an d height being most precise. Waist and hip circumference show strong betwee n-observer differences, and should, where possible, be carried out by one o bserver. Skinfolds can be associated with such large measurement error that interpretation is problematic. Ways are described in which measurement err or can be used to assess the probability that differences in anthropometric measures across time within individuals are due to factors other than impr ecision. Anthropometry is an important tool for nutritional assessment, and the techniques reported here should allow increased precision of measureme nt, and improved interpretation of anthropometric data.