title: Estimation of energy expenditure using prediction equations in overweight and obese adults: a systematic review.
abstract: Estimates of energy requirements are needed in weight management and are usually determined using prediction equations. The objective of these two systematic reviews was to identify which equations based on simple anthropometric and demographic variables provide the most accurate and precise estimates of (1) resting energy expenditure (REE) and (2) total energy expenditure (TEE) in healthy obese adults.
  
  
  
  Systematic searches for relevant studies in healthy adults with body mass index (BMI) ≥25 kg m(-2) and published in English were undertaken using Cinahl, Cochrane Library, OpenGrey, PubMed and Web of Science (completed March 2014). Search terms included metabolism, calorimetry, obesity and prediction equations. Data extraction, study appraisal and synthesis followed guidelines from PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses).
  
  
  
  From 243 REE papers and 254 TEE papers identified, 21 and four studies, respectively, met the inclusion criteria. (1) The most accurate REE predictions varied with BMI subgroup: WHO (weight and height) ≥25 and ≥30 kg m(-2) ; Mifflin 30-39.9 kg m(-2) ; Henry ≥40 kg m(-2) . The most precise REE predictions were obtained using Mifflin in BMI 30-39.9 and ≥40 kg m(-2) , where approximately 75% of predictions were within 10% of measured REE. (2) No accurate or precise predictions of TEE were identified.
  
  
  
  No single prediction equation provides accurate and precise REE estimates in all obese adults. Mifflin equations are recommended in this population, although errors exceed 10% in 25% of those assessed. There is no evidence to support the use of prediction equations in estimating TEE in obesity.
authors.affiliation: School of Life and Medical Sciences, University of Hertfordshire, Hatfield, UK.
authors.forename: A M
authors.initials: AM
authors.lastname: Madden
authors.affiliation: School of Life Sciences, Faculty of Science, Engineering and Computing, University of Kingston, Kingston Upon Thames, UK.
authors.forename: H M
authors.initials: HM
authors.lastname: Mulrooney
authors.affiliation: School of Life and Medical Sciences, University of Hertfordshire, Hatfield, UK.
authors.forename: S
authors.initials: S
authors.lastname: Shah
mesh_terms: D000328:Adult; D000465:Algorithms; D001481:Basal Metabolism; D015992:Body Mass Index; D000068959:Body Weight Maintenance; D003131:Combined Modality Therapy; D002149:Energy Intake; D004734:Energy Metabolism; D005260:Female; D006801:Humans; D008297:Male; D015201:Meta-Analysis as Topic; D008875:Middle Aged; D008954:Models, Biological; D009765:Obesity / Q000378:metabolism* / Q000628:therapy; D000067329:Obesity, Metabolically Benign / Q000378:metabolism* / Q000628:therapy; D050177:Overweight / Q000378:metabolism* / Q000628:therapy; D015203:Reproducibility of Results; D012196:Review Literature as Topic; D012727:Sex Characteristics
keywords: energy; obesity; systematic review