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Int J Obes (Lond). 2015 Aug;39(8):1181-7. doi: 10.1038/ijo.2014.184. Epub 2014 Oct 17.

Predicting adult weight change in the real world: a systematic review and meta-analysis accounting for compensatory changes in energy intake or expenditure.

Author information

  • 11] 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.
  • 21] 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.
  • 3Office of Energetics, University of Alabama at Birmingham, Birmingham, AL, USA.
  • 41] 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.

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.

INCLUSION CRITERIA:

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.

FINDINGS:

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.

INTERPRETATION:

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.

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