title: Use of recovery biomarkers to calibrate nutrient consumption self-reports in the Women's Health Initiative.
abstract: Underreporting of energy consumption by self-report is well-recognized, but previous studies using recovery biomarkers have not been sufficiently large to establish whether participant characteristics predict misreporting. In 2004-2005, 544 participants in the Women's Health Initiative Dietary Modification Trial completed a doubly labeled water protocol (energy biomarker), 24-hour urine collection (protein biomarker), and self-reports of diet (assessed by food frequency questionnaire (FFQ)), exercise, and lifestyle habits; 111 women repeated all procedures after 6 months. Using linear regression, the authors estimated associations of participant characteristics with misreporting, defined as the extent to which the log ratio (self-reported FFQ/nutritional biomarker) was less than zero. Intervention women in the trial underreported energy intake by 32% (vs. 27% in the comparison arm) and protein intake by 15% (vs. 10%). Younger women had more underreporting of energy (p = 0.02) and protein (p = 0.001), while increasing body mass index predicted increased underreporting of energy and overreporting of percentage of energy derived from protein (p = 0.001 and p = 0.004, respectively). Blacks and Hispanics underreported more than did Caucasians. Correlations of initial measures with repeat measures (n = 111) were 0.72, 0.70, 0.46, and 0.64 for biomarker energy, FFQ energy, biomarker protein, and FFQ protein, respectively. Recovery biomarker data were used in regression equations to calibrate self-reports; the potential application of these equations to disease risk modeling is presented. The authors confirm the existence of systematic bias in dietary self-reports and provide methods of correcting for measurement error.
authors.affiliation: Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109-1024, USA. mneuhous@fhcrc.org
authors.forename: Marian L
authors.initials: ML
authors.lastname: Neuhouser
authors.forename: Lesley
authors.initials: L
authors.lastname: Tinker
authors.forename: Pamela A
authors.initials: PA
authors.lastname: Shaw
authors.forename: Dale
authors.initials: D
authors.lastname: Schoeller
authors.forename: Sheila A
authors.initials: SA
authors.lastname: Bingham
authors.forename: Linda Van
authors.initials: LV
authors.lastname: Horn
authors.forename: Shirley A A
authors.initials: SA
authors.lastname: Beresford
authors.forename: Bette
authors.initials: B
authors.lastname: Caan
authors.forename: Cynthia
authors.initials: C
authors.lastname: Thomson
authors.forename: Suzanne
authors.initials: S
authors.lastname: Satterfield
authors.forename: Lew
authors.initials: L
authors.lastname: Kuller
authors.forename: Gerardo
authors.initials: G
authors.lastname: Heiss
authors.forename: Ellen
authors.initials: E
authors.lastname: Smit
authors.forename: Gloria
authors.initials: G
authors.lastname: Sarto
authors.forename: Judith
authors.initials: J
authors.lastname: Ockene
authors.forename: Marcia L
authors.initials: ML
authors.lastname: Stefanick
authors.forename: Annlouise
authors.initials: A
authors.lastname: Assaf
authors.forename: Shirley
authors.initials: S
authors.lastname: Runswick
authors.forename: Ross L
authors.initials: RL
authors.lastname: Prentice
mesh_terms: D000368:Aged; D015415:Biomarkers / Q000032:analysis*; D015992:Body Mass Index; D015930:Diet Records; D004044:Dietary Proteins / Q000008:administration & dosage; D002149:Energy Intake; D005247:Feeding Behavior; D005260:Female; D006801:Humans; D016014:Linear Models; D008875:Middle Aged; D015596:Nutrition Assessment; D017698:Postmenopause; D011795:Surveys and Questionnaires; D016387:Women's Health
chemical_list: D015415:Biomarkers; D004044:Dietary Proteins