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Estimating changes in free-living energy intake and its confidence interval
1Laboratory of Biological Modeling, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD 20892, USA. kevinh@niddk.nih.gov
The American Journal of Clinical Nutrition
|May 13, 2011
Summary
Estimating free-living energy intake changes in individuals requires frequent body weight measurements over extended periods. This method, using an energy balance equation, is feasible for assessing weight management programs.
Area of Science:
- Human Metabolism
- Nutritional Science
- Weight Management
Background:
- Accurate measurement of free-living energy intake is crucial for evaluating outpatient weight-control interventions.
- Current methods for assessing dietary intake in free-living individuals are often challenging and imprecise.
Purpose of the Study:
- To develop a simple methodology for estimating changes in free-living energy intake using longitudinal body weight measurements.
- To establish a method for calculating the 95% confidence interval (CI) of estimated energy intake changes in individual subjects.
Main Methods:
- Derived a two-parameter energy balance equation from human metabolism models.
- Solved the equation to express changes in energy intake as a function of body weight and its rate of change.
- Validated the method using inpatient feeding studies and simulated free-living data with body water fluctuations and daily energy intake variations.
Main Results:
- The methodology accurately predicted individual energy intake changes based on controlled inpatient weight-loss data.
- Simulations indicated that daily weight measurements over more than 28 days are necessary for accurate energy intake change estimates (95% CI <300 kcal/d).
- Estimates demonstrated relative insensitivity to initial body composition and physical activity levels.
Conclusions:
- Precise estimation of energy intake changes in free-living individuals necessitates frequent body weight monitoring over extended durations.
- This approach is practical, cost-effective, and can be utilized to monitor diet adherence in clinical weight management programs.
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