Two non-consecutive 24 h recalls using EPIC-Soft software are sufficiently valid for comparing protein and potassium intake between five European centres – results from the European Food Consumption Validation (EFCOVAL) study

Crispim, Sandra Patrícia; Vries, J.H.M. de; Geelen, Anouk; Souverein, Olga W.; Hulshof, P.J.M.; Lafay, Lionel; Rousseau, Anne-Sophie; Lillegaard, Inger Therese L.; Andersen, Lene Frost; Huybrechts, Inge; Keyzer, Willem De; Ruprich, Jiří; Dofková, Marcela; Ocké, Marga C.; Boer, Evelien de; Slimani, Nadia; Veer, Pieter van’t

doi:10.1017/s0007114510003648

Cited by 80 publications

(104 citation statements)

References 39 publications

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“…Detailed methods have been described before (8,9) . We collected two 24hR, one by telephone and one face-to-face, with at least 1 month in between, using EPIC-Soft software (10,11) .…”

Section: The European Food Consumption Validation Studymentioning

confidence: 99%

Comparison of approaches to correct intake–health associations for FFQ measurement error using a duplicate recovery biomarker and a duplicate 24 h dietary recall as reference method

Geelen

Souverein

Busstra

et al. 2014

Public Health Nutr.

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Objective: To illustrate the impact of intake-related bias in FFQ and 24 h recall (24hR), and correlated errors between these methods, on intake-health associations. Design: Dietary intake was assessed by a 180-item semi-quantitative FFQ and two 24hR. Urinary N and urinary K were estimated from two 24 h urine samples. We compared four scenarios to correct associations for errors in an FFQ estimating protein and K intakes. Setting: Wageningen, The Netherlands. Subjects: Fifty-nine men and fifty-eight women aged 45-65 years. Results: For this FFQ, measurement error weakened a true relative risk of 2?0 to 1?4 for protein and 1?5 for K. As compared with calibration to duplicate recovery biomarkers (i.e. the preferred scenario 1), estimating a validity coefficient using this duplicate biomarker resulted in overcorrected associations, caused by intakerelated bias in the FFQ (scenario 2). The correction factor based on a triad using biomarkers and 24hR was hampered by this intake-related bias and by correlated errors between FFQ and 24hR, and in this population resulted in a nearly perfect correction for protein but an overcorrection for K (scenario 3). When the 24hR was used for calibration, only a small correction was done, due to correlated errors between the methods and intake-related bias in the 24hR (scenario 4). Conclusions: Calibration to a gold standard reference method is the preferred approach to correct intake-health associations for FFQ measurement error. If it is not possible to do so, using the 24hR as reference method only partly removes the errors, but may result in improved intake-health associations.

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“…Detailed methods have been described before (8,9) . We collected two 24hR, one by telephone and one face-to-face, with at least 1 month in between, using EPIC-Soft software (10,11) .…”

Section: The European Food Consumption Validation Studymentioning

confidence: 99%

Comparison of approaches to correct intake–health associations for FFQ measurement error using a duplicate recovery biomarker and a duplicate 24 h dietary recall as reference method

Geelen

Souverein

Busstra

et al. 2014

Public Health Nutr.

Self Cite

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“…In addition, within the EFCOVAL Study, it was investigated whether two nonconsecutive standardized 24-HDRs using EPIC-Soft is a suitable method for future pan-European monitoring surveys, by assessing population means and distributions in the five participating EU countries (Crispim et al, 2011). Crispim et al (2011) concluded that the repeated 24-HDRs using EPIC-Soft appears to be suitable to describe the intake distribution of European populations, at least for their protein, potassium, fish, fruit and vegetable intake. Of note is the fact that the initial EPIC-Soft program was used in the validity study, as the adapted version was planned to be ready only at the end of EFCOVAL.…”

Section: S7mentioning

confidence: 99%

“…The advantages, limitations and requirements to use EPIC-Soft in the context of pan-European dietary monitoring and the results on the validity of EPIC-Soft for specific purposes of future pan-European monitoring surveys are reported elsewhere (Crispim et al, 2010(Crispim et al, , 2011Ocké et al, 2011;Huybrechts et al, 2011a, b).…”

Section: Introductionmentioning

confidence: 99%

The standardized computerized 24-h dietary recall method EPIC-Soft adapted for pan-European dietary monitoring

et al. 2011

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Background/Objectives: The EPIC-Soft program (the software initially developed to conduct 24-h dietary recalls (24-HDRs) in the European Prospective Investigation into Cancer and Nutrition (EPIC) Study) was recommended as the best way to standardize 24-HDRs for future pan-European dietary monitoring. Within European Food Consumption Validation (EFCOVAL), EPIC-Soft was adapted and further developed on various aspects that were required to optimize its use. In this paper, we present the structure and main interview steps of the EPIC-Soft program, after implementation of a series of new specifications deemed to satisfy specific requirements of pan-European monitoring surveys and other international studies. Subjects/Methods: Updates to optimize the EPIC-Soft program were ascertained according to the following stepwise approach: (1) identification of requested specifications to be potentially implemented through an ad hoc 'EPIC-Soft specifications questionnaire' sent to past, current and possible future users of the software; (2) evaluation of the specifications in collaboration with two ad hoc task force groups and through a workshop; (3) development of a technical solution for each retained specification; (4) implementation of the specifications by software developers; (5) testing and amendment of bugs. Results: A number of new specifications and facilities were implemented to EPIC-Soft program. In addition, the software underwent a full reprogramming and migration to a modern Windows environment, including changes in its internal architecture and user interface. Although the overall concept and structure of the initial software were not changed substantially, these improvements ease the current and future use of EPIC-Soft and increase further its adaptation to other countries and study contexts. Conclusions: EPIC-Soft is enriched with further functions and facilities expected to fulfil specific needs of pan-European dietary monitoring and risk assessment purposes. The validity, feasibility and relevance of this software for different national and international study designs, and the logistical aspects related to its implementation are reported elsewhere.

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“…To illustrate the different methods in a real-life setting, the usual intake distributions of several nutrients and foods were calculated using data from the male participants of the EFCOVAL Study (Crispim et al, 2011). This study was designed to evaluate the validity of two independent days of 24-HDRs using EPIC-Soft for assessing food and nutrient intake within countries in Europe, and for comparisons between these countries.…”

Section: Data Of the Efcoval Studymentioning

confidence: 99%

Comparing four methods to estimate usual intake distributions

et al. 2011

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Background/Objectives: The aim of this paper was to compare methods to estimate usual intake distributions of nutrients and foods. As 'true' usual intake distributions are not known in practice, the comparison was carried out through a simulation study, as well as empirically, by application to data from the European Food Consumption Validation (EFCOVAL) Study in which two 24-h dietary recalls (24-HDRs) and food frequency data were collected. The methods being compared were the Iowa State University Method (ISU), National Cancer Institute Method (NCI), Multiple Source Method (MSM) and Statistical Program for Age-adjusted Dietary Assessment (SPADE). Subjects/Methods: Simulation data were constructed with varying numbers of subjects (n), different values for the Box-Cox transformation parameter (l BC ) and different values for the ratio of the within-and between-person variance (r var ). All data were analyzed with the four different methods and the estimated usual mean intake and selected percentiles were obtained. Moreover, the 2-day within-person mean was estimated as an additional 'method'. These five methods were compared in terms of the mean bias, which was calculated as the mean of the differences between the estimated value and the known true value. The application of data from the EFCOVAL Project included calculations of nutrients (that is, protein, potassium, protein density) and foods (that is, vegetables, fruit and fish). Results: Overall, the mean bias of the ISU, NCI, MSM and SPADE Methods was small. However, for all methods, the mean bias and the variation of the bias increased with smaller sample size, higher variance ratios and with more pronounced departures from normality. Serious mean bias (especially in the 95th percentile) was seen using the NCI Method when r var ¼ 9, l BC ¼ 0 and n ¼ 1000. The ISU Method and MSM showed a somewhat higher s.d. of the bias compared with NCI and SPADE Methods, indicating a larger method uncertainty. Furthermore, whereas the ISU, NCI and SPADE Methods produced unimodal density functions by definition, MSM produced distributions with 'peaks', when sample size was small, because of the fact that the population's usual intake distribution was based on estimated individual usual intakes. The application to the EFCOVAL data showed that all estimates of the percentiles and mean were within 5% of each other for the three nutrients analyzed. For vegetables, fruit and fish, the differences were larger than that for nutrients, but overall the sample mean was estimated reasonably. Conclusions: The four methods that were compared seem to provide good estimates of the usual intake distribution of nutrients. Nevertheless, care needs to be taken when a nutrient has a high within-person variation or has a highly skewed distribution, and when the sample size is small. As the methods offer different features, practical reasons may exist to prefer one method over the other.

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Two non-consecutive 24 h recalls using EPIC-Soft software are sufficiently valid for comparing protein and potassium intake between five European centres – results from the European Food Consumption Validation (EFCOVAL) study

Cited by 80 publications

References 39 publications

Comparison of approaches to correct intake–health associations for FFQ measurement error using a duplicate recovery biomarker and a duplicate 24 h dietary recall as reference method

Comparison of approaches to correct intake–health associations for FFQ measurement error using a duplicate recovery biomarker and a duplicate 24 h dietary recall as reference method

The standardized computerized 24-h dietary recall method EPIC-Soft adapted for pan-European dietary monitoring

Comparing four methods to estimate usual intake distributions

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