Estimating Usual Dietary Intake Distributions: Adjusting for Measurement Error and Nonnormality in 24‐Hour Food Intake Data

Nusser, Sarah M.; Fuller, Wayne A.; Guenther, Patricia M.

doi:10.1002/9781118490013.ch30

Cited by 62 publications

(71 citation statements)

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“…This part of the model also includes a person-specific effect as well as within-person variability due to dayto-day variation in an individual's intake and other sources of random error. The model for Part II is: [2] where subscript II indicates that these parameters are associated with Part II, and differ from those in Part I. Two or more 24HRs on a number of individuals with reports of the food of interest are required to distinguish between-and within-person variation.…”

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confidence: 99%

A New Statistical Method for Estimating the Usual Intake of Episodically Consumed Foods with Application to Their Distribution

Tooze¹,

Midthune²,

Dodd³

et al. 2006

Journal of the American Dietetic Association

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543

575

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Objective-We propose a new statistical method that uses information from two 24-hour recalls (24HRs) to estimate usual intake of episodically-consumed foods.Statistical Analyses Performed-The method developed at the National Cancer Institute (NCI) accommodates the large number of non-consumption days that arise with foods by separating the probability of consumption from the consumption-day amount, using a two-part model. Covariates, such as sex, age, race, or information from a food frequency questionnaire (FFQ), may supplement the information from two or more 24HRs using correlated mixed model regression. The model allows for correlation between the probability of consuming a food on a single day and the consumptionday amount. Percentiles of the distribution of usual intake are computed from the estimated model parameters. Results-TheEating at America's Table Study (EATS) data are used to illustrate the method to estimate the distribution of usual intake for whole grains and dark green vegetables for men and women and the distribution of usual intakes of whole grains by educational level among men. A simulation study indicates that the NCI method leads to substantial improvement over existing methods for estimating the distribution of usual intake of foods.Applications/Conclusions-The NCI method provides distinct advantages over previously proposed methods by accounting for the correlation between probability of consumption and amount consumed and by incorporating covariate information. Researchers interested in estimating the distribution of usual intakes of foods for a population or subpopulation are advised to work with a statistician and incorporate the NCI method in analyses. KeywordsUsual intake; Episodically-consumed foods; statistical methods When using dietary assessment among populations or individuals, investigators are often interested in capturing usual intakes -that is, long-term averages. The 24-hour dietary recall (24HR) provides rich details about dietary intake for a given day, but collecting more than two 24HRs per individual is impractical in large surveys such as the National Health and Nutrition Examination Survey (NHANES). Therefore, it is necessary to employ statistical methods to estimate usual dietary intake.Researchers are interested in estimating the usual intake of foods to assess compliance with food-based dietary recommendations and to relate food intake to health parameters. Unlike most nutrients, which are consumed daily, estimating usual intake of episodically-consumed foods presents the following unique challenges for statistical modeling (see the Glossary for a definition of "statistical modeling" and related terms):A. accounting for days without consumption of a particular food or food group; B. allowing for consumption-day amount data that are generally positively skewed and have extreme values in the upper tail of the intake distribution;C. distinguishing within-person variability, which consists of day-to-day variation in intake and random reporting errors, from between-...

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mentioning

confidence: 99%

A New Statistical Method for Estimating the Usual Intake of Episodically Consumed Foods with Application to Their Distribution

Tooze¹,

Midthune²,

Dodd³

et al. 2006

Journal of the American Dietetic Association

Self Cite

543

575

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“…The most flexible and efficient method is that of Nusser (Nusser et al, 1996(Nusser et al, , 1997Guenther et al, 1997). The transformation process guarantees in most cases that the distribution of the transformed data is near to normality.…”

Section: Methodsmentioning

confidence: 99%

“…These packages allow initial adjustments for nuisance effects (eg day of the week, month, interview mode, interview sequence), can incorporate sampling weights, and allow for correlation in the case of consecutive sampling days. Moreover, C-SIDE is also applicable for foods and food groups that are not consumed daily, assuming that the probability of consumption is independent of the amount consumed (Nusser et al, 1997). Although both packages are not expensive, the needed configuration (module SAS=IML for SIDE; UNIX and X Windows System for C-SIDE) impedes a widespread use.…”

Section: Methodsmentioning

confidence: 99%

“…For special foods or food groups that are consumed rarely or only by a part of the population, the expected number of reported days with zero intakes will be large. For such intake data, Nusser et al (1997) recommended a three-step procedure that was also implemented in C-SIDE (1996). Here, at first the distribution of food consumption probabilities is estimated from the observed numbers of zero and non-zero intakes.…”

Section: Distribution Of Usual Dietary Intake K Hoffmann Et Almentioning

confidence: 99%

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Estimating the distribution of usual dietary intake by short-term measurements

et al. 2002

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Objective: To estimate the habitual dietary intake distribution in a population on the basis of repeated short-term measurements, especially of multiple 24 h diet recalls. Methods: Six different statistical methods were evaluated and compared. The comparison referred to theoretical assumptions, admitted data transformations, statistical foundations, available software packages, and applications to real data of dietary intake. Results: The Nusser method and a simplified version of it proposed in the paper have proved to be universally applicable methods for estimating the usual intake distribution for food groups and nutrients. Also, the Buck method seemed to be a robust estimation procedure suitable for the description of food consumption data, whereas the other considered methods were only applicable for log -normally distributed intake data or required a comprehensive data simulation. Characteristics of the estimated usual intake distribution were a decreased standard deviation, increased lower percentiles, and decreased upper percentiles compared to the observed sample distribution of individual means. Empirical results concerning total fat and vegetable intake in three different European consumption surveys showed that the estimated percentiles of the usual intake distribution did not depend markedly on the number of sampling days. Conclusions: Repeated short-term measurements like 24 h diet recalls can be used to describe the habitual dietary intake distribution in food consumption surveys. Recommended is a sampling design of two non-consecutive sampling days. The sampling days of all participants should be selected in such a way that they cover all seasons and days of the week.

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“…The EFSA Journal (2007) (2006), and a discrete/semi-parametric approach following the basic ideas of Nusser et al (1996Nusser et al ( , 1997.…”

Section: Arfdsmentioning

confidence: 99%

Opinion of the Scientific Panel on Plant protection products and their Residues on acute dietary intake assessment of pesticide residues in fruit and vegetables

2007

EFSA Journal

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SUMMARY OF OPINIONAcute dietary intake is one of the factors considered by Member States, the European Commission and international authorities when setting Maximum Residue Levels (MRLs) for pesticides. The MRL is the maximum concentration of a pesticide residue (expressed as mg/kg) that is legally permitted in or on a food or agricultural commodity or animal feedstuff.The measure of acute dietary exposure that is used in MRL-setting is the International Estimate of Short Term Intake (IESTI). The IESTI is calculated using one of 4 standard equations, depending on the type of commodity involved. An MRL above the limit of detection is set for a commodity only if its IESTI does not exceed the Acute Reference Dose (ARfD) of the pesticide concerned.There are discussions at international level about whether to change the way that IESTI equations are calculated. Therefore the European Commission asked the EFSA Scientific Panel on Plant protection products and their Residues (PPR Panel) for an Opinion on how conservative the IESTI equation is, with respect to the percentage of the total European population protected from intakes above the ARfD, and how much this would be altered by changes to the way the IESTI is calculated. However, the Panel is aware that risk managers are also interested in the special case of people who consume a commodity containing residues at the MRL. Therefore the Panel undertook two types of assessment: "total population assessments", estimating the level of protection for the total population based on the levels of pesticides observed in monitoring programs, and "MRL-level assessments" for the special case of people who consume one commodity containing residues at the MRL and other commodities at monitoring levels.The Panel estimated acute dietary intakes by probabilistic modelling. This used data on food consumption and body weight from national surveys, and took account of unit-to-unit variability of residues using variability factors. The probabilistic estimates of intakes were higher than measured intakes from a duplicate diet study, suggesting the Panel's results are conservative (i.e. overestimating intakes and underestimating levels of protection). However, this comparison was possible for only 6 pesticides in one country and one age group, and extrapolation to others countries and age groups is uncertain.It was not possible to conduct probabilistic modelling for the entire population of the EU, or for all pesticides. The Panel conducted total population assessments for a number of scenarios representing different combinations of 13 pesticides, 8 countries and a range of age groups from babies to seniors. For practical reasons, the MRL-level assessments were based on a reduced range of scenarios, representing only two countries (Germany and The Netherlands) and 11 pesticides.For the total population, the Panel's estimates suggested that the level of protection (LoP) provided by the IESTI equation as currently used in the EU (including variability factors of 5 & 7) varies quite widely be...

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Estimating Usual Dietary Intake Distributions: Adjusting for Measurement Error and Nonnormality in 24‐Hour Food Intake Data

Cited by 62 publications

References 10 publications

A New Statistical Method for Estimating the Usual Intake of Episodically Consumed Foods with Application to Their Distribution

A New Statistical Method for Estimating the Usual Intake of Episodically Consumed Foods with Application to Their Distribution

Estimating the distribution of usual dietary intake by short-term measurements

Opinion of the Scientific Panel on Plant protection products and their Residues on acute dietary intake assessment of pesticide residues in fruit and vegetables

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