title: Anthropometric measures are simple and accurate paediatric weight-prediction proxies in resource-poor settings with a high HIV prevalence.
abstract: BACKGROUND
  Accurate weight measurements are essential for both growth monitoring and drug dose calculations in children. Weight can be accurately measured using calibrated scales in resource-rich settings; however, reliable scales are often not available in resource-poor regions or emergency situations. Current age and/or length/height-based weight-prediction equations tend to overestimate weight because they were developed from Western children's measures.
  
  
  OBJECTIVE
  To determine the accuracy of several proxy measures for children's weight among a predominately HIV-positive group of children aged 18 months to 12 years in Botswana.
  
  
  METHODS
  Weight, length/height, ulna and tibia lengths, mid-upper arm circumference (MUAC) and triceps skinfold were measured on 775 children recruited from Gaborone, Botswana, between 6 July and 24 August 2011.
  
  
  RESULTS
  Mean (95% CI) age and weight were 7.8 years (7.5 to 8.4) and 21.7 kg (21.2 to 22.2), respectively. The majority of children were HIV-positive (n=625, 81%) and on antiretroviral treatment (n=594, 95%). The sample was randomly divided; a general linear model was used to develop weight-prediction equations for one half of the sample (n=387), which were then used to predict the weight of the other half (n=388). MUAC and length/height, MUAC and tibia length and MUAC and ulna length most accurately predicted weight, with an adjusted R2of 0.96, 0.95 and 0.93, respectively. Using MUAC and length/height, MUAC and tibia length and MUAC and ulna length equations, ≥92% of predicted weight fell within 15% of actual weight, compared with <55% using current equations.
  
  
  CONCLUSIONS
  The development of nomograms using these equations is warranted to allow for rapid and accurate weight prediction from these simple anthropometric measures in HIV-endemic, resource-constrained settings.
authors.affiliation: Food, Nutrition and Health, University of British Columbia, Vancouver, British Columbia, Canada.
authors.forename: Kyly C
authors.initials: KC
authors.lastname: Whitfield
authors.affiliation: Food, Nutrition and Health, University of British Columbia, Vancouver, British Columbia, Canada.
authors.forename: Roberta
authors.initials: R
authors.lastname: Wozniak
authors.affiliation: Department of Pediatrics, University of British Columbia, Vancouver, British Columbia, Canada.
authors.forename: Mia
authors.initials: M
authors.lastname: Pradinuk
authors.affiliation: Food, Nutrition and Health, University of British Columbia, Vancouver, British Columbia, Canada.
authors.forename: Crystal D
authors.initials: CD
authors.lastname: Karakochuk
authors.affiliation: Botswana-Baylor Children's Clinical Centre of Excellence, Gaborone, Botswana.
authors.forename: Gabriel
authors.initials: G
authors.lastname: Anabwani
authors.affiliation: Food, Nutrition and Health, University of British Columbia, Vancouver, British Columbia, Canada.
authors.forename: Zachary
authors.initials: Z
authors.lastname: Daly
authors.affiliation: Department of Pediatrics, University of British Columbia, Vancouver, British Columbia, Canada.
authors.forename: Stuart M
authors.initials: SM
authors.lastname: MacLeod
authors.affiliation: Department of Pediatrics, University of British Columbia, Vancouver, British Columbia, Canada.
authors.forename: Charles P
authors.initials: CP
authors.lastname: Larson
authors.affiliation: Food, Nutrition and Health, University of British Columbia, Vancouver, British Columbia, Canada.|South Australian Health and Medical Research Institute, and the Women's and Children's Health Research Institute, Adelaide, South Australia, Australia.
authors.forename: Timothy J
authors.initials: TJ
authors.lastname: Green
mesh_terms: D000886:Anthropometry / Q000379:methods; D001827:Body Height / Q000502:physiology; D001835:Body Weight / Q000502:physiology*; D001902:Botswana / Q000453:epidemiology; D002648:Child; D002675:Child, Preschool; D003430:Cross-Sectional Studies; D005260:Female; D015658:HIV Infections / Q000453:epidemiology / Q000503:physiopathology*; D006801:Humans; D007223:Infant; D008297:Male; D008507:Medically Underserved Area; D015588:Observer Variation; D011237:Predictive Value of Tests; D015995:Prevalence; D013977:Tibia / Q000033:anatomy & histology; D014457:Ulna / Q000033:anatomy & histology
keywords: anthropometry; long bone length; mid-upper arm circumference; paediatric; weight prediction