Literature DB >> 29036411

Relative Validity of Nutrient Intakes Assessed by Questionnaire, 24-Hour Recalls, and Diet Records as Compared With Urinary Recovery and Plasma Concentration Biomarkers: Findings for Women.

Changzheng Yuan1,2, Donna Spiegelman1,2,3, Eric B Rimm1,2,4, Bernard A Rosner3,4, Meir J Stampfer1,2,4, Junaidah B Barnett1,5, Jorge E Chavarro1,2,4, Jennifer C Rood6, Lisa J Harnack7, Laura K Sampson1,4, Walter C Willett1,2,4.   

Abstract

We evaluated the performance of a semiquantitative food frequency questionnaire (SFFQ), the Automated Self-Administered 24-Hour Dietary Recall (ASA24), and 7-day dietary records (7DDRs), in comparison with biomarkers, in the estimation of nutrient intakes among 627 women in the Women's Lifestyle Validation Study (United States, 2010-2012). Two paper SFFQs, 1 Web-based SFFQ, 4 ASA24s (beta version), 2 7DDRs, 4 24-hour urine samples, 1 doubly labeled water measurement (repeated among 76 participants), and 2 fasting blood samples were collected over a 15-month period. The dietary variables evaluated were energy, energy-adjusted intakes of protein, sodium, potassium, and specific fatty acids, carotenoids, α-tocopherol, retinol, and folate. In general, relative to biomarkers, averaged ASA24s had lower validity than the SFFQ completed at the end of the data-collection year (SFFQ2); SFFQ2 had slightly lower validity than 1 7DDR; the averaged SFFQs had validity similar to that of 1 7DDR; and the averaged 7DDRs had the highest validity. The deattenuated correlation of energy-adjusted protein intake assessed by SFFQ2 with its biomarker was 0.46, similar to its correlation with 7DDRs (deattenuated r = 0.54). These data indicate that the SFFQ2 provides reasonably valid measurements of energy-adjusted intake for most of the nutrients assessed in our study, consistent with earlier conclusions derived using 7DDRs as the comparison method. The ASA24 needs further evaluation for use in large population studies, but an average of 3 days of measurement will not be sufficient for some important nutrients.

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Year:  2018        PMID: 29036411      PMCID: PMC5928456          DOI: 10.1093/aje/kwx328

Source DB:  PubMed          Journal:  Am J Epidemiol        ISSN: 0002-9262            Impact factor:   4.897


  45 in total

1.  Taking advantage of the strengths of 2 different dietary assessment instruments to improve intake estimates for nutritional epidemiology.

Authors:  Raymond J Carroll; Douglas Midthune; Amy F Subar; Marina Shumakovich; Laurence S Freedman; Frances E Thompson; Victor Kipnis
Journal:  Am J Epidemiol       Date:  2012-01-24       Impact factor: 4.897

2.  Dietary evaluation and attenuation of relative risk: multiple comparisons between blood and urinary biomarkers, food frequency, and 24-hour recall questionnaires: the DEARR study.

Authors:  Iris Shai; Bernard A Rosner; Danit R Shahar; Hilel Vardi; Ayelet B Azrad; Ayala Kanfi; Dan Schwarzfuchs; Drora Fraser
Journal:  J Nutr       Date:  2005-03       Impact factor: 4.798

3.  Evaluation and comparison of food records, recalls, and frequencies for energy and protein assessment by using recovery biomarkers.

Authors:  Ross L Prentice; Yasmin Mossavar-Rahmani; Ying Huang; Linda Van Horn; Shirley A A Beresford; Bette Caan; Lesley Tinker; Dale Schoeller; Sheila Bingham; Charles B Eaton; Cynthia Thomson; Karen C Johnson; Judy Ockene; Gloria Sarto; Gerardo Heiss; Marian L Neuhouser
Journal:  Am J Epidemiol       Date:  2011-07-15       Impact factor: 4.897

4.  Validity of a Dietary Questionnaire Assessed by Comparison With Multiple Weighed Dietary Records or 24-Hour Recalls.

Authors:  Changzheng Yuan; Donna Spiegelman; Eric B Rimm; Bernard A Rosner; Meir J Stampfer; Junaidah B Barnett; Jorge E Chavarro; Amy F Subar; Laura K Sampson; Walter C Willett
Journal:  Am J Epidemiol       Date:  2017-04-01       Impact factor: 4.897

5.  Red meat intake and risk of breast cancer among premenopausal women.

Authors:  Eunyoung Cho; Wendy Y Chen; David J Hunter; Meir J Stampfer; Graham A Colditz; Susan E Hankinson; Walter C Willett
Journal:  Arch Intern Med       Date:  2006-11-13

6.  Eight self-administered 24-hour dietary recalls using the Internet are feasible in African Americans and Whites: the energetics study.

Authors:  Lenore Arab; Kate Wesseling-Perry; Patricia Jardack; Judith Henry; Ashley Winter
Journal:  J Am Diet Assoc       Date:  2010-06

7.  Validity of adolescent diet recall 48 years later.

Authors:  Jorge E Chavarro; Bernard A Rosner; Laura Sampson; Carol Willey; Paula Tocco; Walter C Willett; Wm Cameron Chumlea; Karin B Michels
Journal:  Am J Epidemiol       Date:  2009-11-18       Impact factor: 4.897

8.  Sodium and potassium intake and balance in adults consuming self-selected diets.

Authors:  J T Holbrook; K Y Patterson; J E Bodner; L W Douglas; C Veillon; J L Kelsay; W Mertz; J C Smith
Journal:  Am J Clin Nutr       Date:  1984-10       Impact factor: 7.045

9.  Comparison between plasma and erythrocyte fatty acid content as biomarkers of fatty acid intake in US women.

Authors:  Qi Sun; Jing Ma; Hannia Campos; Susan E Hankinson; Frank B Hu
Journal:  Am J Clin Nutr       Date:  2007-07       Impact factor: 7.045

10.  Urine nitrogen as an independent validatory measure of dietary intake: a study of nitrogen balance in individuals consuming their normal diet.

Authors:  S A Bingham; J H Cummings
Journal:  Am J Clin Nutr       Date:  1985-12       Impact factor: 7.045

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  109 in total

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Authors:  Ana B Maldonado-Cárceles; Lidia Mínguez-Alarcón; Irene Souter; Audrey J Gaskins; Mariel Arvizu; Paige L Williams; Jennifer B Ford; Jorge E Chavarro
Journal:  Fertil Steril       Date:  2020-07-22       Impact factor: 7.329

2.  Association Between Risk Factors for Colorectal Cancer and Risk of Serrated Polyps and Conventional Adenomas.

Authors:  Xiaosheng He; Kana Wu; Shuji Ogino; Edward L Giovannucci; Andrew T Chan; Mingyang Song
Journal:  Gastroenterology       Date:  2018-04-24       Impact factor: 22.682

3.  Nutritional epidemiology: forest, trees and leaves.

Authors:  Edward Giovannucci
Journal:  Eur J Epidemiol       Date:  2019-02-06       Impact factor: 8.082

4.  Dietary intake of fiber, whole grains and risk of colorectal cancer: An updated analysis according to food sources, tumor location and molecular subtypes in two large US cohorts.

Authors:  Xiaosheng He; Kana Wu; Xuehong Zhang; Reiko Nishihara; Yin Cao; Charlie S Fuchs; Edward L Giovannucci; Shuji Ogino; Andrew T Chan; Mingyang Song
Journal:  Int J Cancer       Date:  2019-05-21       Impact factor: 7.396

5.  Intake of protein-rich foods in relation to outcomes of infertility treatment with assisted reproductive technologies.

Authors:  Feiby L Nassan; Yu-Han Chiu; Jose C Vanegas; Audrey J Gaskins; Paige L Williams; Jennifer B Ford; Jill Attaman; Russ Hauser; Jorge E Chavarro
Journal:  Am J Clin Nutr       Date:  2018-11-01       Impact factor: 7.045

6.  Paternal preconception folate intake in relation to gestational age at delivery and birthweight of newborns conceived through assisted reproduction.

Authors:  Nerea Martín-Calvo; Lidia Mínguez-Alarcón; Audrey J Gaskins; Feiby L Nassan; Paige L Williams; Irene Souter; Russ Hauser; Jorge E Chavarro
Journal:  Reprod Biomed Online       Date:  2019-07-12       Impact factor: 3.828

7.  One-Carbon Cofactor Intake and Risk of Neural Tube Defects Among Women Who Meet Folic Acid Recommendations: A Multicenter Case-Control Study.

Authors:  Julie M Petersen; Samantha E Parker; Krista S Crider; Sarah C Tinker; Allen A Mitchell; Martha M Werler
Journal:  Am J Epidemiol       Date:  2019-06-01       Impact factor: 4.897

8.  Association between intake of fruits and vegetables by pesticide residue status and coronary heart disease risk.

Authors:  Yu-Han Chiu; Helena Sandoval-Insausti; Sylvia H Ley; Shilpa N Bhupathiraju; Russ Hauser; Eric B Rimm; JoAnn E Manson; Qi Sun; Jorge E Chavarro
Journal:  Environ Int       Date:  2019-08-29       Impact factor: 9.621

9.  Diet and health-finding a path to Veritas.

Authors:  Walter C Willett
Journal:  Eur J Epidemiol       Date:  2018-02       Impact factor: 8.082

10.  Additive and Multiplicative Interactions Between Genetic Risk Score and Family History and Lifestyle in Relation to Risk of Type 2 Diabetes.

Authors:  Ming Ding; Shafqat Ahmad; Lu Qi; Yang Hu; Shilpa N Bhupathiraju; Marta Guasch-Ferré; Majken K Jensen; Jorge E Chavarro; Paul M Ridker; Walter C Willett; Daniel I Chasman; Frank B Hu; Peter Kraft
Journal:  Am J Epidemiol       Date:  2020-05-05       Impact factor: 4.897

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