Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 414321
Title Predicting urinary creatinine excretion and its usefulness to identify incomplete 24h urine collections
Author(s) Keyzer, W. de; Huybrechts, I.; Dekkers, A.L.M.; Geelen, A.; Crispim, S.P.; Hulshof, P.J.M.; Andersen, L.F.; Rehurkova, I.; Ruprich, J.; Volatier, J.L.; Maele, G. van; Slimani, N.; Veer, P. van 't; Boer, E. de; Henauw, S. de
Source British Journal of Nutrition 108 (2012)6. - ISSN 0007-1145 - p. 1118 - 1125.
DOI http://dx.doi.org/10.1017/S0007114511006295
Department(s) Chair Nutrition and Disease
Chair Nutrition and Health over the Lifecourse
VLAG
Publication type Refereed Article in a scientific journal
Publication year 2012
Keyword(s) 4-aminobenzoic acid - european centers - completeness - potassium - diet - validation - stability - recalls - protein - sodium
Abstract Studies using 24 h urine collections need to incorporate ways to validate the completeness of the urine samples. Models to predict urinary creatinine excretion (UCE) have been developed for this purpose; however, information on their usefulness to identify incomplete urine collections is limited. We aimed to develop a model for predicting UCE and to assess the performance of a creatinine index using para-aminobenzoic acid (PABA) as a reference. Data were taken from the European Food Consumption Validation study comprising two non-consecutive 24 h urine collections from 600 subjects in five European countries. Data from one collection were used to build a multiple linear regression model to predict UCE, and data from the other collection were used for performance testing of a creatinine index-based strategy to identify incomplete collections. Multiple linear regression (n 458) of UCE showed a significant positive association for body weight (ß = 0·07), the interaction term sex × weight (ß = 0·09, reference women) and protein intake (ß = 0·02). A significant negative association was found for age (ß = - 0·09) and sex (ß = - 3·14, reference women). An index of observed-to-predicted creatinine resulted in a sensitivity to identify incomplete collections of 0·06 (95 % CI 0·01, 0·20) and 0·11 (95 % CI 0·03, 0·22) in men and women, respectively. Specificity was 0·97 (95 % CI 0·97, 0·98) in men and 0·98 (95 % CI 0·98, 0·99) in women. The present study shows that UCE can be predicted from weight, age and sex. However, the results revealed that a creatinine index based on these predictions is not sufficiently sensitive to exclude incomplete 24 h urine collections.
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