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Measured Resting Energy Expenditure Using a Fixed Function Indirect Calorimeter in the Clinical Setting as a Predictor of Success with Weight Change in an Obese Pediatric Population

dc.contributor.advisorCollier, David N.en_US
dc.contributor.advisorHoumard, Joseph A.
dc.contributor.authorHenes, Sarah T.en_US
dc.contributor.departmentExercise and Sports Scienceen_US
dc.date.accessioned2010-09-16T13:22:41Zen_US
dc.date.accessioned2011-05-16T20:42:52Z
dc.date.available2010-09-16T13:22:41Zen_US
dc.date.available2011-05-16T20:42:52Z
dc.date.issued2010en_US
dc.description.abstractThe American Dietetic Association (ADA) standard of care for obese adults utilizes indirect calorimetry for calculating caloric targets for weight loss (1). Even though rates appear to be leveling off (2), childhood obesity is one of the major public health concerns of our time and much attention is currently being given to understanding the obese state. Resting energy expenditure (REE) makes up 60-70% of total energy expenditure and plays a major role in determining an individuals' daily energy needs and metabolism. In the clinical setting, indirect calorimetry is often unavailable, thus predictive equations are typically used to help set caloric goals for weight loss.   The first objective was to compare measured resting energy expenditure (MREE) using a portable indirect calorimeter with five predictive equations used to determine energy needs for children participating in the East Carolina University's Healthy Weight Clinic. The investigators also wanted to determine which of these equations are best to use in an obese pediatric population in the clinical setting. Results indicate that there is a significant (p< 0.05) and strong correlation between MREE and these five predictive equations; however, there are also significant discrepancies. Overall, the Harris Benedict equation demonstrates the lowest mean calorie difference when compared to MREE.   Secondly, it was hypothesized that those subjects with a higher baseline MREE would be more successful with weight loss, and that metabolic factors such as leptin may contribute to weight change in an obese pediatric population. It was also proposed that there may be validity in adjusting MREE to body weight and/or body composition to account for confounders such as age and gender. MREE does not appear to predict success with weight change in obese youth aged 7-18 years. In older obese youth (Tanner Stage 5) it appears that those with a lower baseline fat mass and higher adjusted MREE to fat mass, may have more success with decline in BMI z score. Also, leptin and fat mass significantly (p < 0.05) and negatively correlated with BMI z score change in older youth.  en_US
dc.description.degreePh.D.en_US
dc.format.extent105 p.en_US
dc.format.mediumdissertations, academicen_US
dc.identifier.urihttp://hdl.handle.net/10342/2948en_US
dc.publisherEast Carolina Universityen_US
dc.subjectBiology, Physiologyen_US
dc.subjectHealth sciencesen_US
dc.subjectHealth Sciences, Nutritionen_US
dc.subjectPhysiology
dc.subject.lcshObesity in childrenen_US
dc.subject.lcshIndirect calorimetryen_US
dc.subject.lcshEnergy metabolism in childrenen_US
dc.subject.lcshWeight lossen_US
dc.titleMeasured Resting Energy Expenditure Using a Fixed Function Indirect Calorimeter in the Clinical Setting as a Predictor of Success with Weight Change in an Obese Pediatric Populationen_US
dc.typeDoctoral Dissertationen_US

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