Standardising anthropometric measures in children and adolescents with new extensions to egen

Comparing crude anthropometric data from children of different ages is complicated by the fact that children are still growing (we do not expect the height of a 5-year-old to be the same as the height of a 10-year-old!). Clinicians and researchers are often interested in the question ``is this child taller, shorter, or about average compared to other children their age?''. Two sets of population-based reference data are now widely used to address this question: the 1990 British Growth Reference and the Centers for Disease Control and Prevention (CDC) Growth Reference in the U.S. Both references tabulate values obtained by the LMS method (Cole, Eur. J. Clin. Nutr., 1990; Cole and Green, Statistics in Medicine, 1992) that can be used to transform crude data to standard deviation (z) scores, which are standardised to the reference population. The LMS transformation reduces right skew and adjusts for physiological changes in anthropometric measures that occur with age. Stata provides a convenient environment in which to apply the age-specific (or height-specific) LMS values and generate z-scores for each child in a dataset, using the egen command. New functions of egen have been developed to allow transformation of crude child anthropometric data to z-scores using the LMS method and the reference data available from the British Growth Reference and the CDC Growth Reference. Recently the Childhood Obesity Working Group of the International Obesity Taskforce recommended use of BMI cut-off points to categorise children as normal weight, overweight or obese based on age, gender and BMI. An additional function of egen allows for children to be categorised according to these international cut-off points. This talk will provide brief background on growth standards and the LMS method, and describe in detail how the new egen commands were created, with examples of their application.