OBJECTIVE: We present an updated method for identifying physiologically implausible dietary reports by comparing reported energy intake (rEI) with predicted energy requirements (pER), and we examine the impact of excluding these reports. RESEARCH METHODS AND PROCEDURES: Adult data from the Continuing Survey of Food Intakes by Individuals 1994 to 1996 were used. pER was calculated from the dietary reference intake equations. Within-subject variations and errors in rEI [coefficient of variation (CV) approximately 23%] over 2 days (d), pER (CV approximately 11%), and measured total energy expenditure (mTEE; doubly labeled water, CV approximately 8.2%) were propagated, where +/-1 SD = CV2(rEI)/d + CV2(pER) + CV2(mTEE) = +/-22%. Thus, a report was identified as implausible if rEI was not within 78% to 122% of pER. Multiple cut-offs between +/-1 and +/-2 SD were tested. RESULTS: %rEI/pER = 81% in the total sample (n = 6499) and progressively increased to 95% in the +/-1 SD sample (n = 2685). The +/-1 to 1.4 SD samples yielded rEI-weight associations closest to the theoretical relationship (mTEE to weight). Weak or spurious diet-BMI associations were present in the total sample; +/-1 to 1.4 SD samples showed the strongest set of associations and provided the maximum n while maintaining biological plausibility. DISCUSSION: Our methodology can be applied to different data sets to evaluate the impact of implausible rEIs on health outcomes. Implausible rEIs reduce the overall validity of a sample, and not excluding them may lead to inappropriate conclusions about potential dietary causes of health outcomes such as obesity.
OBJECTIVE: We present an updated method for identifying physiologically implausible dietary reports by comparing reported energy intake (rEI) with predicted energy requirements (pER), and we examine the impact of excluding these reports. RESEARCH METHODS AND PROCEDURES: Adult data from the Continuing Survey of Food Intakes by Individuals 1994 to 1996 were used. pER was calculated from the dietary reference intake equations. Within-subject variations and errors in rEI [coefficient of variation (CV) approximately 23%] over 2 days (d), pER (CV approximately 11%), and measured total energy expenditure (mTEE; doubly labeled water, CV approximately 8.2%) were propagated, where +/-1 SD = CV2(rEI)/d + CV2(pER) + CV2(mTEE) = +/-22%. Thus, a report was identified as implausible if rEI was not within 78% to 122% of pER. Multiple cut-offs between +/-1 and +/-2 SD were tested. RESULTS: %rEI/pER = 81% in the total sample (n = 6499) and progressively increased to 95% in the +/-1 SD sample (n = 2685). The +/-1 to 1.4 SD samples yielded rEI-weight associations closest to the theoretical relationship (mTEE to weight). Weak or spurious diet-BMI associations were present in the total sample; +/-1 to 1.4 SD samples showed the strongest set of associations and provided the maximum n while maintaining biological plausibility. DISCUSSION: Our methodology can be applied to different data sets to evaluate the impact of implausible rEIs on health outcomes. Implausible rEIs reduce the overall validity of a sample, and not excluding them may lead to inappropriate conclusions about potential dietary causes of health outcomes such as obesity.
Authors: Sabrina E Noel; Calum Mattocks; Pauline Emmett; Chris J Riddoch; Andrew R Ness; P K Newby Journal: Am J Clin Nutr Date: 2010-09-29 Impact factor: 7.045
Authors: Michelle A Mendez; Maria Isabel Covas; Jaume Marrugat; Joan Vila; Helmut Schröder Journal: Am J Clin Nutr Date: 2008-12-03 Impact factor: 7.045
Authors: Margaret Kurzius-Spencer; Mary K O'Rourke; Chiu-Hsieh Hsu; Vern Hartz; Robin B Harris; Jefferey L Burgess Journal: J Expo Sci Environ Epidemiol Date: 2013-01-16 Impact factor: 5.563