title: Predicting adult weight change in the real world: a systematic review and meta-analysis accounting for compensatory changes in energy intake or expenditure.
abstract: BACKGROUND
  Public health and clinical interventions for obesity in free-living adults may be diminished by individual compensation for the intervention. Approaches to predict weight outcomes do not account for all mechanisms of compensation, so they are not well suited to predict outcomes in free-living adults. Our objective was to quantify the range of compensation in energy intake or expenditure observed in human randomized controlled trials (RCTs).
  
  
  METHODS
  We searched multiple databases (PubMed, CINAHL, SCOPUS, Cochrane, ProQuest, PsycInfo) up to 1 August 2012 for RCTs evaluating the effect of dietary and/or physical activity interventions on body weight/composition.
  
  
  METHODS
  subjects per treatment arm ≥5; ≥1 week intervention; a reported outcome of body weight/body composition; the intervention was either a prescribed amount of over- or underfeeding and/or supervised or monitored physical activity was prescribed; ≥80% compliance; and an objective method was used to verify compliance with the intervention (for example, observation and electronic monitoring). Data were independently extracted and analyzed by multiple reviewers with consensus reached by discussion. We compared observed weight change with predicted weight change using two models that predict weight change accounting only for metabolic compensation.
  
  
  RESULTS
  Twenty-eight studies met inclusion criteria. Overfeeding studies indicate 96% less weight gain than expected if no compensation occurred. Dietary restriction and exercise studies may result in up to 12-44% and 55-64% less weight loss than expected, respectively, under an assumption of no behavioral compensation.
  
  
  CONCLUSIONS
  Compensation is substantial even in high-compliance conditions, resulting in far less weight change than would be expected. The simple algorithm we report allows for more realistic predictions of intervention effects in free-living populations by accounting for the significant compensation that occurs.
authors.affiliation: 1] Nutrition Obesity Research Center, University of Alabama at Birmingham, Birmingham, AL, USA [2] Department of Health Behavior, University of Alabama at Birmingham, Birmingham, AL, USA [3] Office of Energetics, University of Alabama at Birmingham, Birmingham, AL, USA.
authors.forename: E J
authors.initials: EJ
authors.lastname: Dhurandhar
authors.affiliation: 1] Nutrition Obesity Research Center, University of Alabama at Birmingham, Birmingham, AL, USA [2] Office of Energetics, University of Alabama at Birmingham, Birmingham, AL, USA [3] School of Public Health, Dean's Office, University of Alabama at Birmingham, Birmingham, AL, USA.
authors.forename: K A
authors.initials: KA
authors.lastname: Kaiser
authors.affiliation: Office of Energetics, University of Alabama at Birmingham, Birmingham, AL, USA.
authors.forename: J A
authors.initials: JA
authors.lastname: Dawson
authors.affiliation: Office of Energetics, University of Alabama at Birmingham, Birmingham, AL, USA.
authors.forename: A S
authors.initials: AS
authors.lastname: Alcorn
authors.affiliation: 1] Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA [2] Department of Statistics, Kansas State University, Manhattan, KS, USA.
authors.forename: K D
authors.initials: KD
authors.lastname: Keating
authors.affiliation: 1] Nutrition Obesity Research Center, University of Alabama at Birmingham, Birmingham, AL, USA [2] Office of Energetics, University of Alabama at Birmingham, Birmingham, AL, USA [3] School of Public Health, Dean's Office, University of Alabama at Birmingham, Birmingham, AL, USA.
authors.forename: D B
authors.initials: DB
authors.lastname: Allison
mesh_terms: D000328:Adult; D000465:Algorithms; D002149:Energy Intake / Q000502:physiology*; D004734:Energy Metabolism / Q000502:physiology*; D006801:Humans; D009765:Obesity / Q000517:prevention & control*; D011237:Predictive Value of Tests; D011634:Public Health; D016032:Randomized Controlled Trials as Topic; D015431:Weight Loss / Q000502:physiology*