Lydia Lera1, José Luis Santos, Carola García, Patricia Arroyo, Cecilia Albala. 1. Public Health Nutrition Unit, Chronic Diseases and Genetic Epidemiology Research Laboratory, Institute of Nutrition and Food Technology (INTA), University of Chile, Casilla 138-11, Santiago, Chile. llera@inta.cl
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 n=1657 (Sao Paulo, Brazil), n=1004 (Santiago, Chile) and n=995 (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 3.3 cm (Chile), 3.6 cm (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.
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 n=1657 (Sao Paulo, Brazil), n=1004 (Santiago, Chile) and n=995 (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 3.3 cm (Chile), 3.6 cm (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.
Authors: Arnulfo Ramos-Jiménez; Rosa P Hernández-Torres; Isaac A Chávez-Guevara; José A Alvarez-Sanchez; Marco A García-Villalvazo; Miguel Murguía-Romero Journal: Int J Environ Res Public Health Date: 2022-04-21 Impact factor: 4.614
Authors: Marcos Felipe Silva de Lima; Larissa Praça de Oliveira; Natália Louise de Araújo Cabral; Laura Camila Pereira Liberalino; Ursula Viana Bagni; Kenio Costa de Lima; Clélia de Oliveira Lyra Journal: PLoS One Date: 2018-10-23 Impact factor: 3.240