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

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

E J Dhurandhar et al. Int J Obes (Lond). 2015 Aug.

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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Conflict of interest statement

Conflict of Interest: No other authors have any information to disclose pertinent to conflict of interest.

Figures

Figure 1

Figure 1

PRISMA Diagram - Literature search and study selection process

Figure 2

Figure 2

NIDDK and Pennington calculator predictions for caloric restriction (D, squares) and overfeeding (F, triangles) interventions. NIDDK (A) and Pennington (B) model predictions (x-axis) versus actual observed weight changes for all studies (y-axis) Each individual point represents a control vs. treatment comparison; the solid lines are lines of best fit for slope and black dashed lines are 95% confidence intervals. Gray dashed lines are axes and lines of identity. Overall, predictions are an overestimate of observed weight change.

Figure 3

Figure 3

NIDDK and Pennington calculator predictions for exercise interventions (E). NIDDK (A) and Pennington (B) model predictions (x-axis) versus actual observed weight changes for all studies (y-axis). Each individual point represents a treatment vs. control comparison; the solid lines are lines of best fit for slope and black dashed lines are 95% confidence intervals. Gray dashed lines are axes and lines of identity. Overall, predictions are an overestimate of observed weight change.

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