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

American Journal of Epidemiology

Volumn 175, Issue 4, 2012, Pages 340-347

  Carroll, Raymond J ^a   Midthune, Douglas ^c   Subar, Amy F ^c   Shumakovich, Marina ^c   Freedman, Laurence S ^b   Thompson, Frances E ^c   Kipnis, Victor ^c  

^a TEXAS A AND M UNIVERSITY   (United States)

^b GERTNER INSTITUTE FOR EPIDEMIOLOGY AND HEALTH POLICY RESEARCH   (Israel)

^c NATIONAL CANCER INSTITUTE   (United States)

Author keywords

combining dietary instruments; data collection; dietary assessment; energy adjustment; epidemiologic methods; measurement error; nutrient density; nutrient intake

Indexed keywords

ASCORBIC ACID;

ASSESSMENT METHOD; CALIBRATION; COHORT ANALYSIS; DIETARY SHIFT; ENERGY EFFICIENCY; EPIDEMIOLOGY; ESTIMATION METHOD; FOOD INTAKE; INSTRUMENTATION; MEASUREMENT METHOD; NUTRITIONAL STATUS;

24 HOUR DIETARY RECALL; ACCURACY; ARTICLE; CALIBRATION; CALORIC INTAKE; CARBOHYDRATE INTAKE; CLINICAL ASSESSMENT TOOL; COHORT ANALYSIS; CONTROLLED STUDY; DIET SUPPLEMENTATION; DIETARY INTAKE; DISEASE ASSOCIATION; FAT INTAKE; FIBER; FISH MEAT; FOOD FREQUENCY QUESTIONNAIRE; FOOD INTAKE; FRUIT; GRAIN; LEAFY VEGETABLE; MEASUREMENT ERROR; NUTRITIONAL ASSESSMENT; PROTEIN INTAKE; RED MEAT; SELF EVALUATION; VITAMIN INTAKE;

BIAS (EPIDEMIOLOGY); CALIBRATION; CAUSALITY; DATA INTERPRETATION, STATISTICAL; DIET SURVEYS; EATING; ENERGY INTAKE; EPIDEMIOLOGIC RESEARCH DESIGN; HUMANS; LOGISTIC MODELS; QUESTIONNAIRES; SAMPLE SIZE; SELF REPORT; SURVIVAL ANALYSIS;

EID: 84856746721     PISSN: 00029262     EISSN: 14766256     Source Type: Journal    
DOI: 10.1093/aje/kwr317     Document Type: Article

References (31)

1. Subar AF, Kipnis V, Troiano RP, et al. Using intake biomarkers to evaluate the extent of dietary misreporting in a large sample of adults: The OPEN Study. Am J Epidemiol. 2003;158(1): 1-13. (Pubitemid 36745325)
2. Kipnis V, Subar AF, Midthune D, et al. Structure of dietary measurement error: results of the OPEN biomarker study. Am J Epidemiol. 2003;158(1):14-21. (Pubitemid 36745326)
3. Neuhouser ML, Tinker L, Shaw PA, et al. Use of recovery biomarkers to calibrate nutrient consumption self-reports in theWomen's Health Initiative. Am J Epidemiol. 2008;167(10): 1247-1259. (Pubitemid 351670635)
4. Schatzkin A, Kipnis V, Carroll RJ, et al. A comparison of a food frequency questionnaire with a 24-hour recall for use in an epidemiological cohort study: results from the biomarkerbased Observing Protein and Energy Nutrition (OPEN) Study. Int J Epidemiol. 2003;32(6):1054-1062. (Pubitemid 38072695)
5. Freedman LS, Schatzkin A, Midthune D, et al. Dealing with dietary measurement error in nutritional cohort studies. J Natl Cancer Inst. 2011;103(14):1086-1092.
6. Kolar AS, Patterson RE, White E, et al. A practical method for collecting 3-day food records in a large cohort. Epidemiology. 2005;16(4):579-583. (Pubitemid 40847847)
7. Kwan ML, Kushi LH, Song J, et al. A practical method for collecting food record data in a prospective cohort study of breast cancer survivors. Am J Epidemiol. 2010;172(11):1315-1323.
8. Bingham SA, Luben R,Welch A, et al. Are imprecise methods obscuring a relation between fat and breast cancer? Lancet. 2003;362(9379):212-214. (Pubitemid 36859940)
9. Freedman LS, Potischman N, Kipnis V, et al. A comparison of two dietary instruments for evaluating the fat-breast cancer relationship. Int J Epidemiol. 2006;35(4):1011-1021. (Pubitemid 44540756)
10. Six BL, Schap TE, Zhu FM, et al. Evidence-based development of a mobile telephone food record. JAmDietAssoc. 2010;110(1): 74-79.
11. Weiss R, Stumbo PJ, Divakaran A. Automatic food documentation and volume computation using digital imaging and electronic transmission. J Am Diet Assoc. 2010;110(1):42-44.
12. Sun M, Fernstrom JD, Jia W, et al. A wearable electronic system for objective dietary assessment. J Am Diet Assoc. 2010;110(1):45-47.
13. Subar AF, Thompson FE, Potischman N, et al. Formative research of a quick list for an automated self-administered 24-hour dietary recall. JAmDietAssoc. 2007;107(6):1002-1007. (Pubitemid 46764586)
14. Subar AF, Crafts J, Zimmerman TP, et al. Assessment of the accuracy of portion size reports using computer-based food photographs aids in the development of an automated selfadministered 24-hour recall. J Am Diet Assoc. 2010;110(1): 55-64.
15. Zimmerman TP, Hull SG, McNutt S, et al. Challenges in converting an interviewer-administered food probe database to self-administration in the National Cancer Institute Automated Self-administered 24-Hour Recall (ASA24). J Food Compost Anal. 2009;22(suppl 1):S48-S51.
16. Arab L, Wesseling-Perry K, Jardack P, et al. Eight selfadministered 24-hour dietary recalls using the Internet are feasible in African Americans and whites: the Energetics Study. J Am Diet Assoc. 2010;110(6):857-864.
17. Baranowski T, Beltran A, Martin S, et al. Tests of the accuracy and speed of categorizing foods into child vs professional categories using two methods of browsing with children. J Am Diet Assoc. 2010;110(1):91-94.
18. Subar AF, Thompson FE, Kipnis V, et al. Comparative validation of the Block,Willett, and National Cancer Institute food frequency questionnaires: the Eating at America's Table Study. Am J Epidemiol. 2001;154(12):1089-1099. (Pubitemid 33140629)
19. Agricultural Research Service, US Department of Agriculture. Design and Operation: the Continuing Survey of Food Intakes by Individuals and the Diet and Health Knowledge Survey, 1994-1996. Washington, DC: US Department of Agriculture; 1997.
20. Bowman SA, Friday JE, Moshfegh A. MyPyramid Equivalents Database, 2.0 for USDA Survey Foods, 2003-2004: Documentation and User Guide. Beltsville, MD: Beltsville Human Nutrition Research Center, Agricultural Research Service, US Department of Agriculture; 2008. (http://www.ars.usda.gov/SP2UserFiles/Place/ 12355000/pdf/mped/mped2-doc.pdf). (Accessed December 20, 2011).
21. Subar AF, Midthune D, Kulldorff M, et al. Evaluation of alternative approaches to assign nutrient values to food groups in food frequency questionnaires. Am J Epidemiol. 2000;152(3): 279-286. (Pubitemid 30640251)
22. Prentice RL. Covariate measurement errors and parameter estimation in a failure time regression model. Biometrika. 1982;69(2):331-342.
23. Rosner B, Willett WC, Spiegelman D. Correction of logistic regression relative risk estimates and confidence intervals for systematic within-person measurement error. Stat Med. 1989; 8(9):1051-1069. (Pubitemid 19233679)
24. Carroll RJ, Stefanski LA. Approximate quasilikelihood estimation in models with surrogate predictors. J Am Stat Assoc. 1990;85(411):652-663.
25. Carroll RJ, Ruppert D, Stefanski LA, et al. Measurement Error in Nonlinear Models: A Modern Perspective. New York, NY: Chapman & Hall, Inc; 2006.
26. Kipnis V, Midthune D, Buckman DW, et al. Modeling data with excess zeros and measurement error: application to evaluating relationships between episodically consumed foods and health outcomes. Biometrics. 2009;65(4):1003-1010.
27. Freedman LS, Guenther PM, Dodd KW, et al. The population distribution of ratios of usual intakes of dietary components that are consumed every day can be estimated from repeated 24-hour recalls. J Nutr. 2010;140(1):111-116.
28. Freedman LS, Guenther PM, Krebs-Smith SM, et al. A population's distribution of Healthy Eating Index-2005 component scores can be estimated when more than one 24-hour recall is available. J Nutr. 2010;140(8):1529-1534.
29. Dodd KW, Guenther PM, Freedman LS, et al. Statistical methods for estimating usual intake of nutrients and foods: a review of the theory. J Am Diet Assoc. 2006;106(10): 1640-1650. (Pubitemid 44415594)
30. Gersovitz M, Madden JP, Smiciklas-Wright H. Validity of the 24-hr. dietary recall and seven-day record for group comparisons. J Am Diet Assoc. 1978;73(1):48-55.
31. Rebro SM, Patterson RE, Kristal AR, et al. The effect of keeping food records on eating patterns. J Am Diet Assoc. 1998;98(10):1163-1165.