title: Predictive equations for stature in the elderly: a study in three Latin American cities.
abstract: OBJECTIVE
  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.
  
  
  METHODS
  Population-based cross-sectional study in three Latin American cities.
  
  
  METHODS
  Sample sizes were n=1657 (Sao Paulo, Brazil), n=1004 (Santiago, Chile) and n=995 (Mexico City, Mexico).
  
  
  METHODS
  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.affiliation: 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
authors.forename: Lydia
authors.initials: L
authors.lastname: Lera
authors.forename: José
authors.initials: J
authors.lastname: Luis Santos
authors.forename: Carola
authors.initials: C
authors.lastname: García
authors.forename: Patricia
authors.initials: P
authors.lastname: Arroyo
authors.forename: Cecilia
authors.initials: C
authors.lastname: Albala
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D001837:Body Weights and Measures / Q000706:statistics & numerical data*; D003430:Cross-Sectional Studies; D006801:Humans; D007843:Latin America; D016014:Linear Models; D008875:Middle Aged; D011237:Predictive Value of Tests; D012737:Sex Factors; D014505:Urban Population / Q000706:statistics & numerical data*