A Computational Model to Determine Energy Intake During Weight Loss

Information

  • Research Project
  • 8179656
  • ApplicationId
    8179656
  • Core Project Number
    R15DK090739
  • Full Project Number
    1R15DK090739-01A1
  • Serial Number
    90739
  • FOA Number
    PA-10-070
  • Sub Project Id
  • Project Start Date
    8/1/2011 - 13 years ago
  • Project End Date
    7/31/2014 - 10 years ago
  • Program Officer Name
    EVERHART, JAMES
  • Budget Start Date
    8/1/2011 - 13 years ago
  • Budget End Date
    7/31/2014 - 10 years ago
  • Fiscal Year
    2011
  • Support Year
    1
  • Suffix
    A1
  • Award Notice Date
    5/9/2011 - 13 years ago

A Computational Model to Determine Energy Intake During Weight Loss

DESCRIPTION (provided by applicant): Obesity and its resulting diseases are estimated to affect over twenty percent of the American population. While there are various strategies to lose excess weight, caloric restriction is considered the most effective natural weight loss intervention. However, the results of diet induced weight loss are modest and it is suspected that patient dietary adherence is largely responsible. To assess the role of adherence on weight loss, experimental study design should include methods to monitor dietary intake. Current valid methods for assessing dietary intake require extensive clinical visits or subject confinement. Both methods are expensive and not feasible for extended periods of time. Therefore, there is a critical need for an affordable, non-invasive, accurate method to monitor subject intake during weight loss. We propose to meet this need through application of a validated energy balance model. Three specific aims are proposed: (1) To rigorously develop a computational model that estimates individual ongoing energy intake during weight loss. (2) To validate the computational model through comparison with existing clinical measurements of dietary intake. (3) To determine markers of successful adherence from application of the model to existing weight loss datasets. To accomplish these aims, we have assembled an experienced multi-disciplinary team of obesity researchers and mathematicians. The proposed model is positioned to change current practices for determining patient dietary adherence and provide vital information for understanding the national obesity problem. PUBLIC HEALTH RELEVANCE: Caloric restriction is the most effective natural lifestyle intervention known to reduce weight and improve blood pressure, cholesterol levels, and other markers of health. Diet induced weight loss requires individuals to follow prescribed caloric restrictions;however, current methods to determine actual patient food consumption are either expensive or unreliable. The proposed mathematical approach will eliminate these challenges for determining dietary intake during weight loss.

IC Name
NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES
  • Activity
    R15
  • Administering IC
    DK
  • Application Type
    1
  • Direct Cost Amount
  • Indirect Cost Amount
  • Total Cost
    302860
  • Sub Project Total Cost
  • ARRA Funded
    False
  • CFDA Code
    847
  • Ed Inst. Type
    SCHOOLS OF ARTS AND SCIENCES
  • Funding ICs
    NIDDK:302860\
  • Funding Mechanism
    Research Projects
  • Study Section
    KNOD
  • Study Section Name
    Kidney, Nutrition, Obesity and Diabetes Study Section
  • Organization Name
    MONTCLAIR STATE UNIVERSITY
  • Organization Department
    BIOSTATISTICS &OTHER MATH SCI
  • Organization DUNS
    053506184
  • Organization City
    MONTCLAIR
  • Organization State
    NJ
  • Organization Country
    UNITED STATES
  • Organization Zip Code
    070431624
  • Organization District
    UNITED STATES