Energy Balance Teens: A Measurement Error Approach to Estimating Energy Balance in Free-Living Adolescents
Condition: Childhood Obesity
MeSH terms: Pediatric Obesity
Study type: Observational

Summary: 
      There is a critical need to develop an affordable, valid, and reliable techniques to assess
      free-living energy expenditure (EE), energy storage (ES), and energy intake (EI). The purpose
      of this project is to develop and evaluate statistical procedures to model, quantify and
      adjust for the measurement error of and consumer (e.g., Garmin) activity monitors and body
      composition scales to estimate EE and ES, and use the 'calibrated' values to estimate
      free-living EI.
    

Detailed description: 
      Dietary intake and physical activity are important lifestyle behaviors that have a profound
      role in the development of my many chronic diseases, including heart disease, diabetes,
      kidney disease, certain cancers, and overweight/obesity. It is clear that there are a
      multitude of physiological, environmental, and behavioral factors that influence obesity
      risk, but at the most basic level body weight is determined by the energy balance of energy
      intake (EI) and energy expenditure (EE). Standard assessment techniques of EI in
      population-based studies rely on individuals to self-report the foods they eat, but these
      estimates are typically 12-31% below expected values. This has led expert dieticians and
      nutritional epidemiologists to declare 'EI is inaccurately measured by self-report' and
      'wholly unacceptable for scientific research.' Thus, there is a critical need to develop an
      affordable, valid, and reliable techniques to assess free-living EE, energy storage (ES), and
      EI. The investigator's long-term goal is to assess the components of energy balance to better
      inform obesity prevention and treatment. The short-term goal, and the purpose of this
      application, is to develop and evaluate statistical procedures to model, quantify and adjust
      for the measurement error of and consumer (e.g., Fitbit) activity monitors and body
      composition scales to estimate EE and ES, and use the 'calibrated' values to estimate
      free-living EI. The status quo as it relates to the use of non-gold standard devices is that
      there exists large variability compared to criterion measures that may produce erroneous
      estimates, particularly in mean EE, making their use at a population-level ill-advised. In
      contrast, the investigator's working hypothesis is that the error inherent in consumer
      devices can be quantified and adjusted for, allowing for the accurate assessment of EE and
      ES. The purpose of this project is to apply measurement error techniques to a pilot sample
      (N=24) of free-living adolescents to improve energy balance estimates. The investigators will
      use a consumer physical activity monitor (Garmin Vivofit 4), and a consumer body composition
      analyzer (Garmin Smartscale) to estimate daily EE and change in ES over two consecutive
      14-day periods, separated by a 14-day washout period. The investigators will develop
      calibration models using simultaneously collected gold-standard techniques including doubly
      labeled water for EE and duel-energy x-ray absorptiometry for ES as references. The
      investigators will use the calibrated EE and ES to calculate EI using the intake-balance
      technique. Lastly, the investigators will evaluate the feasibility and acceptability of the
      protocols and methodology. At the completion of the proposed study, it is the investigators
      expectation that they will have generated important pilot data and assessed project
      feasibility in adolescents for a large-scale NIH R01 application. A fully powered study will
      improve the assessment of EE and ES in free-living conditions using research grade and
      consumer devices, allowing for the estimation of EI with greater accuracy than currently
      available techniques. This project will make significant advancements on the assessment of
      energy balance in free-living settings.
    

Observational model: Cohort
Time perspective: Prospective
Sampling method: Non-Probability Sample
Study population: 
        Participants will be healthy boys and girls.