Literature DB >> 25667947

Reply to Schoeller et al.

Michelle A Mendez, Daniela Sotres-Alvarez, Donna R Miles, Meghan M Slining, Barry M Popkin.   

Abstract

Mesh：

Year:  2015        PMID： 25667947      PMCID： PMC4264020          DOI： 10.3945/jn.114.202770

Source DB:  PubMed          Journal:  J Nutr        ISSN： 0022-3166            Impact factor:   4.798


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  9 in total

1.  Effect of screening out implausible energy intake reports on relationships between diet and BMI.

Authors:  Terry T-K Huang; Susan B Roberts; Nancy C Howarth; Megan A McCrory
Journal:  Obes Res       Date:  2005-07

Review 2.  Considering the value of dietary assessment data in informing nutrition-related health policy.

Authors:  James R Hébert; Thomas G Hurley; Susan E Steck; Donald R Miller; Fred K Tabung; Karen E Peterson; Lawrence H Kushi; Edward A Frongillo
Journal:  Adv Nutr       Date:  2014-07-14       Impact factor: 8.701

3.  Pooled results from 5 validation studies of dietary self-report instruments using recovery biomarkers for energy and protein intake.

Authors:  Laurence S Freedman; John M Commins; James E Moler; Lenore Arab; David J Baer; Victor Kipnis; Douglas Midthune; Alanna J Moshfegh; Marian L Neuhouser; Ross L Prentice; Arthur Schatzkin; Donna Spiegelman; Amy F Subar; Lesley F Tinker; Walter Willett
Journal:  Am J Epidemiol       Date:  2014-06-10       Impact factor: 4.897

4.  A mixed-effects model approach for estimating the distribution of usual intake of nutrients: the NCI method.

Authors:  Janet A Tooze; Victor Kipnis; Dennis W Buckman; Raymond J Carroll; Laurence S Freedman; Patricia M Guenther; Susan M Krebs-Smith; Amy F Subar; Kevin W Dodd
Journal:  Stat Med       Date:  2010-11-30       Impact factor: 2.373

Review 5.  A systematic review of the validity of dietary assessment methods in children when compared with the method of doubly labeled water.

Authors:  Tracy L Burrows; Rebecca J Martin; Clare E Collins
Journal:  J Am Diet Assoc       Date:  2010-10

6.  Prevalence of childhood and adult obesity in the United States, 2011-2012.

Authors:  Cynthia L Ogden; Margaret D Carroll; Brian K Kit; Katherine M Flegal
Journal:  JAMA       Date:  2014-02-26       Impact factor: 56.272

7.  The US Department of Agriculture Automated Multiple-Pass Method reduces bias in the collection of energy intakes.

Authors:  Alanna J Moshfegh; Donna G Rhodes; David J Baer; Theophile Murayi; John C Clemens; William V Rumpler; David R Paul; Rhonda S Sebastian; Kevin J Kuczynski; Linda A Ingwersen; Robert C Staples; Linda E Cleveland
Journal:  Am J Clin Nutr       Date:  2008-08       Impact factor: 7.045

8.  Shifts in the recent distribution of energy intake among U.S. children aged 2-18 years reflect potential abatement of earlier declining trends.

Authors:  Michelle A Mendez; Daniela Sotres-Alvarez; Donna R Miles; Meghan M Slining; Barry M Popkin
Journal:  J Nutr       Date:  2014-06-11       Impact factor: 4.798

9.  Dynamics of childhood growth and obesity: development and validation of a quantitative mathematical model.

Authors:  Kevin D Hall; Nancy F Butte; Boyd A Swinburn; Carson C Chow
Journal:  Lancet Diabetes Endocrinol       Date:  2013-10       Impact factor: 32.069
  9 in total

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