title: Predictive equations for estimating regional body composition: a validation study using DXA as criterion and associations with cardiometabolic risk factors.
abstract: BACKGROUND
  Regional body composition can influence disease risk and simple screening methods to identify individuals at risk are still needed.
  
  
  OBJECTIVE
  To develop equations for estimating fat and lean mass distribution, using DXA as a criterion, and to compare their performance by the association with cardiometabolic risk factors (systolic and diastolic blood pressure, high-density lipoprotein cholesterol, triacylglycerides and fasting glucose).
  
  
  METHODS
  The study was conducted among 391 adults (52% female; aged 24-64 years), randomly selected from the EPIPorto cohort, with anthropometric (skin-folds and circumferences) and DXA measures. Multiple linear regression models, by sex, were used to derive predictive equations and to investigate their performance by the associations with cardiometabolic risk factors.
  
  
  RESULTS
  The best predicting models included circumferences and skin-folds. The final equations standard error (SEEs) ranged between 1.7-3.2% in men and 2.0-3.7% in women. Similar associations were found between regional body composition, measured by DXA or estimated by anthropometric equations, with traditional cardiometabolic risk factors, supporting the convergent validity of the equations. Additionally, it was found that central fat was associated adversely, whereas peripheral fat was favourably associated with cardiometabolic risk factors and their clustering.
  
  
  CONCLUSIONS
  Equations combining both circumferences and skin-folds met the necessary standards for predicting regional body composition accurately, being an important tool to identify individuals with cardiometabolic risk.
authors.affiliation: a EPI Unit - Institute of Public Health, University of Porto , Portugal .|b Department of Clinical Epidemiology , Predictive Medicine and Public Health, University of Porto Medical School , Porto , Portugal .|c School of Sports and Leisure, Polytechnic Institute of Viana do Castelo , Portugal , and.
authors.forename: Mário
authors.initials: M
authors.lastname: Simões
authors.affiliation: a EPI Unit - Institute of Public Health, University of Porto , Portugal .|b Department of Clinical Epidemiology , Predictive Medicine and Public Health, University of Porto Medical School , Porto , Portugal .
authors.forename: Milton
authors.initials: M
authors.lastname: Severo
authors.affiliation: a EPI Unit - Institute of Public Health, University of Porto , Portugal .|b Department of Clinical Epidemiology , Predictive Medicine and Public Health, University of Porto Medical School , Porto , Portugal .
authors.forename: Andreia
authors.initials: A
authors.lastname: Oliveira
authors.affiliation: d Department of Clinical Epidemiology and Medical Technology Assessment & CARIM School for Cardiovascular Diseases , Maastricht University Medical Centre , Maastricht , The Netherlands.
authors.forename: Isabel
authors.initials: I
authors.lastname: Ferreira
authors.affiliation: a EPI Unit - Institute of Public Health, University of Porto , Portugal .|b Department of Clinical Epidemiology , Predictive Medicine and Public Health, University of Porto Medical School , Porto , Portugal .
authors.forename: Carla
authors.initials: C
authors.lastname: Lopes
mesh_terms: D015502:Absorptiometry, Photon / Q000379:methods*; D000328:Adult; D000886:Anthropometry; D001823:Body Composition; D002318:Cardiovascular Diseases / Q000453:epidemiology*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D015203:Reproducibility of Results; D012307:Risk Factors; D055815:Young Adult
keywords: Anthropometry; DXA; body composition; cardiovascular health