Predictive equations for stature in the elderly: A study in three Latin American cities

Abstract

Aim: The aim of this study was to develop predictive equations based on anthropometric data to estimate stature in people 60 years and older in Latin America. Design: Population-based cross-sectional study in three Latin American cities. Subjects: Sample sizes were n¼1657 (Sao Paulo, Brazil), n¼1004 (Santiago, Chile) and n¼995 (Mexico City, Mexico). Method: The prediction equations were fitted by stepwise linear regression analysis. For each country and sex, samples were randomly split into two sub-samples (training and validation sub-samples) using the cross-validation method. Results: Stepwise regression analysis in the training sample revealed that only knee-height and age had a significant effect on the prediction of height. The values of the shrinkage statistic were below 0.1 indicating the reliability of the prediction equations. The regression equations had standard errors of estimate ranging from 3.3cm (Chile), 3.6cm (Brazil) and 4.0 cm (Mexico) for women, and 3.7 cm (Mexico and Chile) and 3.8 cm (Brazil) for men. Conclusions: Sex-specific stature prediction equations based on knee-height and age were obtained from large representative samples from selected cities of Latin America.