Measurement error affecting web- and paper-based dietary assessment instruments: insights from the Multi-Cohort Eating and Activity Study for Understanding Reporting Error

Authors: KIRKPATRICK, SHARON - University Of Waterloo; TROIANO, RICHARD - National Cancer Institute (NCI, NIH); BARRETT, BRIAN - Information Management Services, Inc; CUNNINGHAM, CHRISTOPHER - Information Management Services, Inc; SUBAR, AMY - National Cancer Institute (NCI, NIH); PARK, YIKYUNG - Washington University; BOWLES, HEATHER - National Cancer Institute (NCI, NIH); FREEDMAN, LAURENCE - Information Management Services, Inc; KIPNIS, VICTOR - National Cancer Institute (NCI, NIH); MIDTHUNE, DOUGLAS - National Cancer Institute (NCI, NIH); RIMM, ERIC - Harvard School Of Public Health; STAMPFER, MEIR - Harvard School Of Public Health; WILLETT, WALTER - Harvard School Of Public Health; POTISCHMAN, NANCY - National Institutes Of Health (NIH); ROSNER, BERNARD - Harvard School Of Public Health; SPIELGELMAN, DONNA - Yale University; THOMPSON, FRANCES - National Cancer Institute (NCI, NIH); Baer, David; SCHOELLER, DALE - University Of Wisconsin; DODD, KEVIN - National Cancer Institute (NCI, NIH)

Submitted to: American Journal of Epidemiology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/2/2022
Publication Date: 6/1/2022
Citation: Kirkpatrick, S.I., Troiano, R.P., Barrett, B., Cunningham, C., Subar, A.F., Park, Y., Bowles, H.R., Freedman, L.S., Kipnis, V., Midthune, D., Rimm, E.B., Stampfer, M.J., Willett, W.C., Potischman, N., Rosner, B.A., Spielgelman, D., Thompson, F.E., Baer, D.J., Schoeller, D.A., Dodd, K.W. 2022. Measurement error affecting web- and paper-based dietary assessment instruments: insights from the Multi-Cohort Eating and Activity Study for Understanding Reporting Error. American Journal of Epidemiology. 191(6):1125-1139. https://doi.org/10.1093/aje/kwac026.
DOI: https://doi.org/10.1093/aje/kwac026

Interpretive Summary: Determining usual food intake in studies designed to link dietary habits and nutrient intakes with disease is important for nutrition research, particularly for large and long-term studies. The challenges measurement error poses to examining relationships between long-term dietary intake and health have been extensively described. Over the past few decades, validation studies leveraging recovery biomarkers have enhanced our understanding of the sources and extent of error in intake estimates of energy and a few nutrients based on self-report. Prior studies highlight that data from 24-hour recalls (24HRs) and food records (FRs) are affected by random error to a greater extent than food frequency questionnaire (FFQ) data, whereas the opposite is true for systematic error. This study was conducted to examine the error properties of multiple administrations of online 24HRs, online and paper-based FFQs, and paper-based FRs. The samples were drawn primarily from three cohorts and included women (n=1393) and men (n=1455), aged 45 to 80 years. Self-report instruments along with recovery biomarkers for energy, protein, sodium, and potassium were collected. The findings support prior research suggesting different instruments have unique strengths that should be leveraged in epidemiologic research.

Technical Abstract: Few biomarker-based validation studies have examined error in online self-report dietary assessment instruments, and food records (FRs) have been considered less than food frequency questionnaires (FFQs) and 24- hour recalls (24HRs). We investigated measurement error in online and paper-based FFQs, online 24HRs, and paper-based FRs in 3 samples drawn primarily from 3 cohorts, comprising 1,393 women and 1,455 men aged 45–86 years. Data collection occurred from January 2011 to October 2013. Attenuation factors and correlation coefficients between reported and true usual intake for energy, protein, sodium, potassium, and respective densities were estimated using recovery biomarkers. Across studies, average attenuation factors for energy were 0.07, 0.07, and 0.19 for a single FFQ, 24HR, and FR, respectively. Correlation coefficients for energy were 0.24, 0.23, and 0.40, respectively. Excluding energy, the average attenuation factors across nutrients and studies were 0.22 for a single FFQ, 0.22 for a single 24HR, and 0.51 for a single FR. Corresponding correlation coefficients were 0.31, 0.34, and 0.53, respectively. For densities (nutrient expressed relative to energy), the average attenuation factors across studies were 0.37, 0.17, and 0.50, respectively. The findings support prior research suggesting different instruments have unique strengths that should be leveraged in epidemiologic research.