OBJECTIVE: To compare two approaches to analysing energy- and nutrient-converted data from dietary validation (and relative validation) studies - conventional analyses, in which the accuracy of reported items is not ascertained, and reporting-error-sensitive analyses, in which reported items are classified as matches (items actually eaten) or intrusions (items not actually eaten), and reported amounts are classified as corresponding or overreported. DESIGN: Subjects were observed eating school breakfast and lunch, and interviewed that evening about that day's intake. For conventional analyses, reference and reported information were converted to energy and macronutrients; then t-tests, correlation coefficients and report rates (reported/reference) were calculated. For reporting error-sensitive analyses, reported items were classified as matches or intrusions, reported amounts were classified as corresponding or overreported, and correspondence rates (corresponding amount/reference amount) and inflation ratios (overreported amount/reference amount) were calculated. SUBJECTS: Sixty-nine fourth-grade children (35 girls) from 10 elementary schools in Georgia (USA). RESULTS: For energy and each macronutrient, conventional analyses found that reported amounts were significantly less than reference amounts (every P < 0.021; paired t-tests); correlations between reported and reference amounts exceeded 0.52 (every P < 0.001); and median report rates ranged from 76% to 95%. Analyses sensitive to reporting errors found median correspondence rates between 67% and 79%, and that median inflation ratios, which ranged from 7% to 17%, differed significantly from 0 (every P < 0.0001; sign tests). CONCLUSIONS: Conventional analyses of energy and nutrient data from dietary reporting validation (and relative validation) studies may overestimate accuracy and mask the complexity of dietary reporting error.
OBJECTIVE: To compare two approaches to analysing energy- and nutrient-converted data from dietary validation (and relative validation) studies - conventional analyses, in which the accuracy of reported items is not ascertained, and reporting-error-sensitive analyses, in which reported items are classified as matches (items actually eaten) or intrusions (items not actually eaten), and reported amounts are classified as corresponding or overreported. DESIGN: Subjects were observed eating school breakfast and lunch, and interviewed that evening about that day's intake. For conventional analyses, reference and reported information were converted to energy and macronutrients; then t-tests, correlation coefficients and report rates (reported/reference) were calculated. For reporting error-sensitive analyses, reported items were classified as matches or intrusions, reported amounts were classified as corresponding or overreported, and correspondence rates (corresponding amount/reference amount) and inflation ratios (overreported amount/reference amount) were calculated. SUBJECTS: Sixty-nine fourth-grade children (35 girls) from 10 elementary schools in Georgia (USA). RESULTS: For energy and each macronutrient, conventional analyses found that reported amounts were significantly less than reference amounts (every P < 0.021; paired t-tests); correlations between reported and reference amounts exceeded 0.52 (every P < 0.001); and median report rates ranged from 76% to 95%. Analyses sensitive to reporting errors found median correspondence rates between 67% and 79%, and that median inflation ratios, which ranged from 7% to 17%, differed significantly from 0 (every P < 0.0001; sign tests). CONCLUSIONS: Conventional analyses of energy and nutrient data from dietary reporting validation (and relative validation) studies may overestimate accuracy and mask the complexity of dietary reporting error.
Authors: Suzanne Domel Baxter; William O Thompson; Albert F Smith; Mark S Litaker; Zenong Yin; Francesca H A Frye; Caroline H Guinn; Michelle L Baglio; Nicole M Shaffer Journal: Prev Med Date: 2003-05 Impact factor: 4.018
Authors: Nicole M Shaffer; Suzanne Domel Baxter; William O Thompson; Michelle L Baglio; Caroline H Guinn; Francesca H A Frye Journal: J Am Diet Assoc Date: 2004-10
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Authors: Suzanne Domel Baxter; William O Thompson; Mark S Litaker; Caroline H Guinn; Francesca H A Frye; Michelle L Baglio; Nicole M Shaffer Journal: J Nutr Educ Behav Date: 2003 May-Jun Impact factor: 3.045
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Authors: Suzanne D Baxter; David B Hitchcock; Caroline H Guinn; Kate K Vaadi; Megan P Puryear; Julie A Royer; Kerry L McIver; Marsha Dowda; Russell R Pate; Dawn K Wilson Journal: J Acad Nutr Diet Date: 2014-04-24 Impact factor: 4.910
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Authors: Caroline H Guinn; Suzanne D Baxter; Julie A Royer; James W Hardin; Alyssa J Mackelprang; Albert F Smith Journal: J Health Psychol Date: 2010-05
Authors: Suzanne Domel Baxter; Julie A Royer; Caroline H Guinn; James W Hardin; Albert F Smith Journal: Public Health Nutr Date: 2008-11-10 Impact factor: 4.022
Authors: Suzanne D Baxter; Albert F Smith; David B Hitchcock; Caroline H Guinn; Julie A Royer; Kathleen L Collins; Alyssa L Smith; Megan P Puryear; Kate K Vaadi; Christopher J Finney; Patricia H Miller Journal: J Nutr Date: 2015-07-29 Impact factor: 4.798
Authors: Suzanne Domel Baxter; James W Hardin; Caroline H Guinn; Julie A Royer; Alyssa J Mackelprang; Albert F Smith Journal: J Am Diet Assoc Date: 2009-05