Literature DB >> 1877589

Estimating the relation between dietary intake obtained from a food frequency questionnaire and true average intake.

L S Freedman1, R J Carroll, Y Wax.   

Abstract

Knowledge of the regression relation between dietary intake reported on a food frequency questionnaire and true average intake is useful in interpreting results from nutritional epidemiologic studies and in planning such studies. Studies which validate a questionnaire against a food record may be used to estimate this regression relation provided the food record is completed by each subject on at least two occasions. Using data collected from women aged 45-69 years during 1985-1986 in the pilot study of the Women's Health Trial, the authors show how variation in diet over time and intraindividual correlation between a questionnaire and food record obtained close together in time affects the estimation of the regression. The authors' method provides estimates of the regression slope and the questionnaire "bias" that are corrected for these effects, together with standard errors. A computer program in the SAS language, for carrying out the analysis, is provided.

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Year:  1991        PMID: 1877589     DOI: 10.1093/oxfordjournals.aje.a116086

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


  16 in total

1.  Validating an FFQ for intake of episodically consumed foods: application to the National Institutes of Health-AARP Diet and Health Study.

Authors:  Douglas Midthune; Arthur Schatzkin; Amy F Subar; Frances E Thompson; Laurence S Freedman; Raymond J Carroll; Marina A Shumakovich; Victor Kipnis
Journal:  Public Health Nutr       Date:  2011-04-13       Impact factor: 4.022

2.  Performance of the quantitative food frequency questionnaire used in the Brazilian center of the prospective study Natural History of Human Papillomavirus Infection in Men: The HIM Study.

Authors:  Juliana Araujo Teixeira; Maria Luiza Baggio; Anna R Giuliano; Regina Mara Fisberg; Dirce Maria Lobo Marchioni
Journal:  J Am Diet Assoc       Date:  2011-07

3.  Relative validity and reliability of an FFQ in youth with type 1 diabetes.

Authors:  Angela D Liese; Jamie L Crandell; Janet A Tooze; Mary T Fangman; Sarah C Couch; Anwar T Merchant; Ronny A Bell; Elizabeth J Mayer-Davis
Journal:  Public Health Nutr       Date:  2014-03-28       Impact factor: 4.022

4.  Computerized portion-size estimation compared to multiple 24-hour dietary recalls for measurement of fat, fruit, and vegetable intake in overweight adults.

Authors:  Deborah J Toobert; Lisa A Strycker; Sarah E Hampson; Erika Westling; Steven M Christiansen; Thomas G Hurley; James R Hébert
Journal:  J Am Diet Assoc       Date:  2011-10

Review 5.  Comparison of dietary intake and physical activity between women with and without polycystic ovary syndrome: a review.

Authors:  Annie W Lin; Marla E Lujan
Journal:  Adv Nutr       Date:  2014-09       Impact factor: 8.701

Review 6.  STRATOS guidance document on measurement error and misclassification of variables in observational epidemiology: Part 1-Basic theory and simple methods of adjustment.

Authors:  Ruth H Keogh; Pamela A Shaw; Paul Gustafson; Raymond J Carroll; Veronika Deffner; Kevin W Dodd; Helmut Küchenhoff; Janet A Tooze; Michael P Wallace; Victor Kipnis; Laurence S Freedman
Journal:  Stat Med       Date:  2020-04-03       Impact factor: 2.373

7.  Methods to Assess Measurement Error in Questionnaires of Sedentary Behavior.

Authors:  Joshua N Sampson; Charles E Matthews; Laurence Freedman; Raymond J Carroll; Victor Kipnis
Journal:  J Appl Stat       Date:  2016-03-17       Impact factor: 1.404

8.  On the importance of using multiple methods of dietary assessment.

Authors:  Loki Natarajan; Cheryl L Rock; Jacqueline M Major; Cynthia A Thomson; Bette J Caan; Shirley W Flatt; Janice A Chilton; Kathryn A Hollenbach; Vicky A Newman; Susan Faerber; Cheryl K Ritenbaugh; Ellen Gold; Marcia L Stefanick; Lovell A Jones; James R Marshall; John P Pierce
Journal:  Epidemiology       Date:  2004-11       Impact factor: 4.822

9.  Robust best linear estimator for Cox regression with instrumental variables in whole cohort and surrogates with additive measurement error in calibration sample.

Authors:  Ching-Yun Wang; Xiao Song
Journal:  Biom J       Date:  2016-08-22       Impact factor: 2.207

10.  Validation of a food frequency questionnaire for children and adolescents aged 4 to 11 years living in Salvador, Bahia.

Authors:  S M A Matos; M S Prado; C A S T Santos; S D'Innocenzo; A M O Assis; L S Dourado; N S Oliveira; L C Rodrigues; M L Barreto
Journal:  Nutr Hosp       Date:  2012 Jul-Aug       Impact factor: 1.169

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