Literature DB >> 21414246

The number of 24 h dietary recalls using the US Department of Agriculture's automated multiple-pass method required to estimate nutrient intake in overweight and obese adults.

Kim S Stote1, Steven V Radecki, Alanna J Moshfegh, Linda A Ingwersen, David J Baer.   

Abstract

OBJECTIVE: To determine the number of 24 h dietary recalls required to adequately estimate nutrient intake in overweight and obese adults using the US Department of Agriculture's (USDA) automated multiple-pass method (AMPM). In addition, the study quantified sources of variation in dietary intake, such as day of the week, season, sequence of diet interviews (training effect), diet interviewer, body weight and within- and between-subject variances in the intake of selected nutrients.
DESIGN: Adults having a BMI of ≥ 28 but <38 kg/m2 were included in the study. The USDA's AMPM was used to obtain 24 h dietary recalls every 10 d for 6 months. Dietary intake data were analysed to adequately estimate the number of 24 h recalls necessary to assess nutrient intake. Variance component estimates were made by using a mixed-model procedure.
SETTING: The greater Washington, DC, metropolitan area.
SUBJECTS: Adults (34 men and 39 women) aged 35-65 years.
RESULTS: Overweight and obese adults completed fourteen 24 h dietary recalls. Utilizing within- and between-subject variances requires 5-10 and 12-15 d of 24 h dietary recalls in men and women, respectively, to estimate energy and macronutrient intakes in a 6-month period. Within- and between-subject variances were the major contributors to variance in nutrient intakes. Day of the week, season, sequence, diet interviewer and body weight had little impact on variance.
CONCLUSIONS: This information is valuable for researchers planning to conduct studies on free-living individuals that include the collection of dietary intake data.

Entities:  

Mesh:

Substances:

Year:  2011        PMID: 21414246     DOI: 10.1017/S1368980011000358

Source DB:  PubMed          Journal:  Public Health Nutr        ISSN: 1368-9800            Impact factor:   4.022


  17 in total

Review 1.  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

2.  ω-3 fatty acid intakes are inversely related to elevated depressive symptoms among United States women.

Authors:  May A Beydoun; Marie T Fanelli Kuczmarski; Hind A Beydoun; Joseph R Hibbeln; Michele K Evans; Alan B Zonderman
Journal:  J Nutr       Date:  2013-09-04       Impact factor: 4.798

3.  Intensive nutrition counseling as part of a multi-component weight loss intervention improves diet quality and anthropometrics in older adults with obesity.

Authors:  Rima Itani Al-Nimr; K C S Wright; Christina L Aquila; Curtis L Petersen; Tyler L Gooding; John A Batsis
Journal:  Clin Nutr ESPEN       Date:  2020-09-19

4.  Talking health, a pragmatic randomized-controlled health literacy trial targeting sugar-sweetened beverage consumption among adults: rationale, design & methods.

Authors:  Jamie Zoellner; Yvonnes Chen; Brenda Davy; Wen You; Valisa Hedrick; Terri Corsi; Paul Estabrooks
Journal:  Contemp Clin Trials       Date:  2013-11-15       Impact factor: 2.226

5.  Within-Person Variation in Nutrient Intakes across Populations and Settings: Implications for the Use of External Estimates in Modeling Usual Nutrient Intake Distributions.

Authors:  Caitlin D French; Joanne E Arsenault; Charles D Arnold; Demewoz Haile; Hanqi Luo; Kevin W Dodd; Stephen A Vosti; Carolyn M Slupsky; Reina Engle-Stone
Journal:  Adv Nutr       Date:  2021-03-31       Impact factor: 8.701

6.  Comparison of the Diet ID Platform to the Automated Self-administered 24-hour (ASA24) Dietary Assessment Tool for Assessment of Dietary Intake.

Authors:  Gabrielle Turner-McGrievy; Brent Hutto; John A Bernhart; Mary J Wilson
Journal:  J Am Nutr Assoc       Date:  2021-03-11

7.  Comparison of the 24 h Dietary Recall of Two Consecutive Days, Two Non-Consecutive Days, Three Consecutive Days, and Three Non-Consecutive Days for Estimating Dietary Intake of Chinese Adult.

Authors:  Kun Huang; Liyun Zhao; Qiya Guo; Dongmei Yu; Yuxiang Yang; Qiuye Cao; Xiaolin Yuan; Lahong Ju; Shujuan Li; Xue Cheng; Xiaoli Xu; Hongyun Fang
Journal:  Nutrients       Date:  2022-05-07       Impact factor: 5.717

8.  Examination of food reward and energy intake under laboratory and free-living conditions in a trait binge eating subtype of obesity.

Authors:  Michelle Dalton; John Blundell; Graham S Finlayson
Journal:  Front Psychol       Date:  2013-10-21

9.  The Impact of Health Literacy Status on the Comparative Validity and Sensitivity of an Interactive Multimedia Beverage Intake Questionnaire.

Authors:  Lucy P Hooper; Emily A Myers; Jamie M Zoellner; Brenda M Davy; Valisa E Hedrick
Journal:  Nutrients       Date:  2016-12-23       Impact factor: 5.717

10.  Effects of a behavioral and health literacy intervention to reduce sugar-sweetened beverages: a randomized-controlled trial.

Authors:  Jamie M Zoellner; Valisa E Hedrick; Wen You; Yvonnes Chen; Brenda M Davy; Kathleen J Porter; Angela Bailey; Hannah Lane; Ramine Alexander; Paul A Estabrooks
Journal:  Int J Behav Nutr Phys Act       Date:  2016-03-22       Impact factor: 6.457

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.