Rasmus Køster-Rasmussen1, Volkert Siersma1, Thorhallur I Halldorsson2, Niels de Fine Olivarius1, Jan E Henriksen3, Berit L Heitmann4. 1. 1The Research Unit for General Practice and Section of General Practice,Department of Public Health,University of Copenhagen,Øster Farimagsgade 5,1014 Copenhagen,Denmark. 2. 3Faculty of Food Science and Nutrition,School of Health Sciences,University of Iceland,Reykjavik,Iceland. 3. 2Clinical Institute,University of Southern Denmark,Odense,Denmark. 4. 6Institute of Preventive Medicine,Capital Region,Bispebjerg and Frederiksberg Hospital,Copenhagen,Denmark.
Abstract
OBJECTIVE: Standard portions or substitution of missing portion sizes with medians may generate bias when quantifying the dietary intake from FFQ. The present study compared four different methods to include portion sizes in FFQ. DESIGN: We evaluated three stochastic methods for imputation of portion sizes based on information about anthropometry, sex, physical activity and age. Energy intakes computed with standard portion sizes, defined as sex-specific medians (median), or with portion sizes estimated with multinomial logistic regression (MLR), 'comparable categories' (Coca) or k-nearest neighbours (KNN) were compared with a reference based on self-reported portion sizes (quantified by a photographic food atlas embedded in the FFQ). SETTING: The Danish Health Examination Survey 2007-2008. SUBJECTS: The study included 3728 adults with complete portion size data. RESULTS: Compared with the reference, the root-mean-square errors of the mean daily total energy intake (in kJ) computed with portion sizes estimated by the four methods were (men; women): median (1118; 1061), MLR (1060; 1051), Coca (1230; 1146), KNN (1281; 1181). The equivalent biases (mean error) were (in kJ): median (579; 469), MLR (248; 178), Coca (234; 188), KNN (-340; 218). CONCLUSIONS: The methods MLR and Coca provided the best agreement with the reference. The stochastic methods allowed for estimation of meaningful portion sizes by conditioning on information about physiology and they were suitable for multiple imputation. We propose to use MLR or Coca to substitute missing portion size values or when portion sizes needs to be included in FFQ without portion size data.
OBJECTIVE: Standard portions or substitution of missing portion sizes with medians may generate bias when quantifying the dietary intake from FFQ. The present study compared four different methods to include portion sizes in FFQ. DESIGN: We evaluated three stochastic methods for imputation of portion sizes based on information about anthropometry, sex, physical activity and age. Energy intakes computed with standard portion sizes, defined as sex-specific medians (median), or with portion sizes estimated with multinomial logistic regression (MLR), 'comparable categories' (Coca) or k-nearest neighbours (KNN) were compared with a reference based on self-reported portion sizes (quantified by a photographic food atlas embedded in the FFQ). SETTING: The Danish Health Examination Survey 2007-2008. SUBJECTS: The study included 3728 adults with complete portion size data. RESULTS: Compared with the reference, the root-mean-square errors of the mean daily total energy intake (in kJ) computed with portion sizes estimated by the four methods were (men; women): median (1118; 1061), MLR (1060; 1051), Coca (1230; 1146), KNN (1281; 1181). The equivalent biases (mean error) were (in kJ): median (579; 469), MLR (248; 178), Coca (234; 188), KNN (-340; 218). CONCLUSIONS: The methods MLR and Coca provided the best agreement with the reference. The stochastic methods allowed for estimation of meaningful portion sizes by conditioning on information about physiology and they were suitable for multiple imputation. We propose to use MLR or Coca to substitute missing portion size values or when portion sizes needs to be included in FFQ without portion size data.
Authors: June Stevens; Fang-Shu Ou; Kimberly P Truesdale; Donglin Zeng; Amber E Vaughn; Charlotte Pratt; Dianne S Ward Journal: Food Nutr Res Date: 2015-12-17 Impact factor: 3.894
Authors: Robin Christensen; Berit L Heitmann; Karina Winther Andersen; Ole Haagen Nielsen; Signe Bek Sørensen; Mohamad Jawhara; Anette Bygum; Lone Hvid; Jakob Grauslund; Jimmi Wied; Henning Glerup; Ulrich Fredberg; Jan Alexander Villadsen; Søren Geill Kjær; Jan Fallingborg; Seyed A G R Moghadd; Torben Knudsen; Jacob Brodersen; Jesper Frøjk; Jens Frederik Dahlerup; Anders Bo Bojesen; Grith Lykke Sorensen; Steffen Thiel; Nils J Færgeman; Ivan Brandslund; Tue Bjerg Bennike; Allan Stensballe; Erik Berg Schmidt; Andre Franke; David Ellinghaus; Philip Rosenstiel; Jeroen Raes; Mette Boye; Lars Werner; Charlotte Lindgaard Nielsen; Heidi Lausten Munk; Anders Bathum Nexøe; Torkell Ellingsen; Uffe Holmskov; Jens Kjeldsen; Vibeke Andersen Journal: BMJ Open Date: 2018-02-08 Impact factor: 2.692