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Member Research & Reports

Member Research & Reports

UAB Develops Algorithm for Making Realistic Predictions of Adult Weight Change

Public health and clinical interventions for obesity in free-living adults may be diminished by individual compensation for the intervention. For example, even if someone starts exercising, they may also experience hunger and eat more calories to make up for those burned during exercise. Current approaches to predict weight outcomes account for metabolic compensation, such as compensation by the body through changes in resting energy expenditure; however, they do not account for behavioral compensation, such as adjustments in activity or food intake, making them not well suited to predict outcomes. In a study conducted by Dr. Emily J. Dhurandhar, assistant professor in the department of health behavior, and Dr. Kathryn Kaiser, instructor in the office of energetics, at the University of Alabama at Birmingham, the objective was to quantify the range of compensation in energy intake or expenditure observed in human randomized controlled trials (RCTs). Co-investigators include Dr. John Dawson, postdoctoral trainee in the department of biostatistics, section on statistical genetics; Ms. Amy S. Alcorn, Program Manager I in the office of energetics; Dr. Karen Keating, at Kansas State University; and Dr. David B. Allison, distinguished professor and director of UAB’s office of energetics and Nutrition Obesity Research Center (NORC).


[Photo: Dr. Emily J. Dhurandhar (above) and Dr. Kathryn Kaiser]

Researchers searched multiple databases to August 1, 2012, for RCTs evaluating the effect dietary and/or physical activity interventions have on body weight/composition. Twenty-eight studies met the inclusion criteria: subjects per five or more treatment arm; a week or more intervention; a reported outcome of weight /body composition; the intervention was either a prescribed amount of over- or underfeeding and/or supervised or monitored physical activity was prescribed; 80 percent or greater compliance with the intervention; and an objective method was used to verify compliance (e.g., direct observation, electronic monitoring). Data were independently extracted and analyzed by multiple reviewers with consensus reached by discussion. The team compared observed weight change from the included studies to weight change predicted by two models that account only for metabolic compensation. The difference between observed and predicted weight change indicated the degree of behavioral compensation for the intervention. Overfeeding studies indicated 96 percent less weight gain than expected had no behavioral compensation occurred. Dietary restriction and exercise studies showed the potential to result in up to 12 to 44 percent and 55 to 64 percent less weight loss than expected, respectively, under assumption of no behavioral compensation.

Results indicate that compensation is substantial even in high-compliance conditions, resulting in far less weight change than would be expected. The simple algorithm this study reports allows for more realistic predictions of intervention effects in free-living populations by accounting for the significant compensation that occurs. “The significance of this study is that there are now better data to project population level effects of different types of interventions on body weight. Policy makers can be better informed,” said Dr. Kaiser.

“Predicting Adult Weight Change in the Real World: A Systematic Review and Meta-analysis Accounting for Compensatory Changes in Energy Intake or Expenditure” was published in October in the International Journal of Obesity.

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