Literature DB >> 19386746

Comparison of self-reported, measured, metabolizable energy intake with total energy expenditure in overweight teens.

Rajni Singh1, Berdine R Martin, Yvonne Hickey, Dorothy Teegarden, Wayne W Campbell, Bruce A Craig, Dale A Schoeller, Deborah Anne Kerr, Connie M Weaver.   

Abstract

BACKGROUND: The accuracy of dietary energy assessment tools is critical to understanding the role of diet in the increasing rate of obesity.
OBJECTIVES: The purposes of our study in overweight adolescent boys and girls were 1) to assess the energy reporting bias of diet records against the referent of total energy expenditure (TEE) and 2) to compare the methods of determining energy needs by using measured metabolizable energy intake (MEI) and TEE.
DESIGN: Twenty girls [12-15 y, body mass index (in kg/m2) = 33.0 +/- 5] and 14 boys (12-14 y, body mass index = 27.4 +/- 4) participated in 2- to 3-wk metabolic balance studies. TEE was measured by using doubly labeled water (TEE(DLW)), and MEI was measured by bomb calorimetry of composite daily diet, urine, and fecal collections. Food records were collected before each study.
RESULTS: Food records underreported TEE(DLW) by 35 +/- 20%. Underreporting of energy intake was correlated with all macronutrient intake concentrations (g or kcal) (P < 0.0001). A multiple regression model showed that 86.4% of the variance in underreporting error was explained by dietary fat (g), BMI, and sex. The intrasubject CV was 3.9% for TEE(DLW) and 9.9% for MEI. MEI for weight stability (MEI(wtstb)) averaged 99 +/- 11% of TEE.
CONCLUSIONS: The increased underreporting of dietary intake with increasing body weight in teens may explain in part previous reports noting that there has been an increased incidence of obesity, although energy intakes have not appeared to increase. MEI(wtstb) and TEE(DLW) gave similar estimates of energy needs. This trial was registered at clinicaltrials.gov as NCT 00592137.

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Year:  2009        PMID: 19386746      PMCID: PMC2682993          DOI: 10.3945/ajcn.2008.26752

Source DB:  PubMed          Journal:  Am J Clin Nutr        ISSN: 0002-9165            Impact factor:   7.045


  34 in total

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Authors:  Paula Trumbo; Sandra Schlicker; Allison A Yates; Mary Poos
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2.  Validation of estimates of energy intake by weighed dietary record and diet history in children and adolescents.

Authors:  M B Livingstone; A M Prentice; W A Coward; J J Strain; A E Black; P S Davies; C M Stewart; P G McKenna; R G Whitehead
Journal:  Am J Clin Nutr       Date:  1992-07       Impact factor: 7.045

3.  Energy expenditure by doubly labeled water: validation in humans and proposed calculation.

Authors:  D A Schoeller; E Ravussin; Y Schutz; K J Acheson; P Baertschi; E Jéquier
Journal:  Am J Physiol       Date:  1986-05

Review 4.  Limitations in the assessment of dietary energy intake by self-report.

Authors:  D A Schoeller
Journal:  Metabolism       Date:  1995-02       Impact factor: 8.694

5.  Energy and fat intakes of children and adolescents in the united states: data from the national health and nutrition examination surveys.

Authors:  R P Troiano; R R Briefel; M D Carroll; K Bialostosky
Journal:  Am J Clin Nutr       Date:  2000-11       Impact factor: 7.045

6.  Doubly labeled water method: in vivo oxygen and hydrogen isotope fractionation.

Authors:  D A Schoeller; C A Leitch; C Brown
Journal:  Am J Physiol       Date:  1986-12

7.  Measurements of total energy expenditure provide insights into the validity of dietary measurements of energy intake.

Authors:  A E Black; A M Prentice; G R Goldberg; S A Jebb; S A Bingham; M B Livingstone; W A Coward
Journal:  J Am Diet Assoc       Date:  1993-05

8.  Relative dilution spaces of 2H- and 18O-labeled water in humans.

Authors:  S B Racette; D A Schoeller; A H Luke; K Shay; J Hnilicka; R F Kushner
Journal:  Am J Physiol       Date:  1994-10

9.  Total energy expenditure and energy intake in the pre-school child: a comparison.

Authors:  P S Davies; W A Coward; J Gregory; A White; A Mills
Journal:  Br J Nutr       Date:  1994-07       Impact factor: 3.718

10.  The predictive value of childhood body mass index values for overweight at age 35 y.

Authors:  S S Guo; A F Roche; W C Chumlea; J D Gardner; R M Siervogel
Journal:  Am J Clin Nutr       Date:  1994-04       Impact factor: 7.045

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  37 in total

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Authors:  Peter Manu; Constantin Ionescu-Tirgoviste; James Tsang; Barbara A Napolitano; Martin L Lesser; Christoph U Correll
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2.  Use of accelerometer data in prediction equations for capturing implausible dietary intakes in adolescents.

Authors:  Sabrina E Noel; Calum Mattocks; Pauline Emmett; Chris J Riddoch; Andrew R Ness; P K Newby
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3.  Underreporting in obese inpatients undergoing a psycho-nutritional rehabilitative program.

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4.  Relatively Low β-Cell Responsiveness Contributes to the Association of BMI with Circulating Glucose Concentrations Measured under Free-Living Conditions among Pregnant African American Women.

Authors:  Paula C Chandler-Laney; Desti N Shepard; Camille R Schneider; Lee Anne Flagg; Wesley M Granger; Melissa S Mancuso; Joseph R Biggio; Barbara A Gower
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5.  Associations of youth and parent weight status with reported versus predicted daily energy intake and hemoglobin A1c in youth with type 1 diabetes mellitus.

Authors:  Amanda L P Sands; Laurie A Higgins; Sanjeev N Mehta; Tonja R Nansel; Leah M Lipsky; Lori M B Laffel
Journal:  J Diabetes Sci Technol       Date:  2013-01-01

6.  Dietary calcium intake recommendations for children: are they too high?

Authors:  Babette S Zemel
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7.  A randomized trial of sugar-sweetened beverages and adolescent body weight.

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8.  Adolescent girls' most common source of junk food away from home.

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9.  Nutritional profile and obesity: results from a random-sample population-based study in Córdoba, Argentina.

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Review 10.  Working toward precision medicine approaches to treat severe obesity in adolescents: report of an NIH workshop.

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