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Objective To describe the data-based development of a short dietary assessment instrument, a 16-item screener; and to evaluate the performance of the screener, comparing its performance with a complete 120-item food frequency questionnaire (FFQ) in assessing percentage energy from fat intake. Design A subsample (n=404) of participants in the National Institutes of Health-AARP Diet and Health Study, who had completed an FFQ and two 24-hour dietary recalls, also completed the fat screener. Percentage energy from fat from the screener and from the FFQ were compared with estimated true usual intake using a measurement error model. Results For men, the mean percentage energy from fat estimates for the different methods were: recalls, 30.1%, screener, 29.9%; FFQ, 30.4%. For women, the results were: recalls, 31.3%, screener, 28.4%, FFQ, 30.0%. Estimated correlations between true intake and screener were 0.64 and 0.58 for men and women, respectively, and between true intake and FFQ were 0.67 for men and 0.72 for women. Estimated attenuation coefficients for the screener were 1.29 (men) and 0.98 (women) and for the FFQ were 0.56 (men) and 0.57 (women). Conclusions The percentage energy from fat screener, when used in conjunction with external reference data, may be useful to compare mean intakes of fat for different population subgroups, and to examine relationships between fat intake and other factors.

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.jada.2006.07.003 Byline: Janet A. Tooze, Douglas Midthune, Kevin W. Dodd, Laurence S. Freedman, Susan M. Krebs-Smith, Amy F. Subar, Patricia M. Guenther, Raymond J. Carroll, Victor Kipnis Abstract: We propose a new statistical method that uses information from two 24-hour recalls to estimate usual intake of episodically consumed foods.

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.jada.2006.07.002 Byline: Amy F. Subar, Kevin W. Dodd, Patricia M. Guenther, Victor Kipnis, Douglas Midthune, Margaret McDowell, Janet A. Tooze, Laurence S. Freedman, Susan M. Krebs-Smith Abstract: Twenty-four-hour recalls capture rich information on food consumption, but suffer from inadequately measuring usual intakes of episodically consumed foods. We explore using food frequency questionnaire (FFQ) data as covariates in a statistical model to estimate individual usual intakes of episodically consumed foods and their distributions and describe the development of the Food Propensity Questionnaire, an FFQ introduced in the 2003-2004 National Health and Nutrition Examination Survey.

Although 24-hour recalls are frequently used in dietary assessment, intake on a single day is a poor estimator of long-term usual intake. Statistical modeling mitigates this limitation more effectively than averaging multiple 24-hour recalls per respondent. In this article, we describe the statistical theory that underlies the four major modeling methods developed to date, then review the strengths and limitations of each method. We focus on the problem of estimating the distribution of usual intake for a population from 24-hour recall data, giving special attention to the problems inherent in modeling usual intake for foods or food groups that a proportion of the population does not consume every day (ie, episodically consumed foods). All four statistical methods share a common framework. Differences between the methods arise from different assumptions about the measurement characteristics of 24-hour recalls and from the fact that more recently developed methods build upon their predecessor(s). These differences can result in estimated usual intake distributions that differ from one another. We also demonstrate the need for an improved method for estimating usual intake distributions for episodically consumed foods.

Objective We propose a new statistical method that uses information from two 24-hour recalls 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 nonconsumption days that occur 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, may supplement the information from two or more 24-hour recalls using correlated mixed model regression. The model allows for correlation between the probability of consuming a food on a single day and the consumption-day amount. Percentiles of the distribution of usual intake are computed from the estimated model parameters. Results The Eating at America's Table Study 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. 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.

Objective Twenty-four-hour recalls capture rich information on food consumption, but suffer from inadequately measuring usual intakes of episodically consumed foods. We explore using food frequency questionnaire (FFQ) data as covariates in a statistical model to estimate individual usual intakes of episodically consumed foods and their distributions and describe the development of the Food Propensity Questionnaire, an FFQ introduced in the 2003-2004 National Health and Nutrition Examination Survey. Design We analyzed data from 965 adult participants in the Eating at America's Table Study who completed four 24-hour recalls and an FFQ. We assessed whether or not increasing FFQ-reported frequency was associated with both number of 24-hour recall consumption days and amounts reported. Results For 52 of 56 food groups (93%), and 218 of 230 individual foods (95%), there were significant monotonically increasing relationships between FFQ frequency and 24-hour recall probability of consumption. For 47 of 56 food groups (84%) and 55 of 230 (24%) individual foods, there were significant positive correlations between FFQ frequencies and consumption-day mean intake. Conclusions We found strong and consistent relationships between reported FFQ frequency of food and food-group consumption and probability of consumption on 24-hour recalls. This supports the premise that frequency data may offer important covariate information in supplementing multiple recalls for estimating usual intake of food groups.

Objectives To describe the implementation of the Multifactor Screener in the 2000 National Health Interview Survey (NHIS); to provide intake estimates for fruits and vegetables, fiber, and percentage of energy from fat by various demographic and behavioral characteristics; and to discuss the strengths and weaknesses of the method. Design/Subjects The 2000 NHIS was conducted in 38,632 households in a clustered sample representative of the 48 contiguous states in the United States. The Cancer Control Module was administered to adults (18 years and older) and included 17 dietary intake questions. Analyses After excluding individuals with missing data or unlikely values on the diet questions, we computed individual intake of servings of fruits and vegetables, percentage of energy from fat, and grams of fiber. We estimated median intakes and distributions of intakes using adjusted variance estimates. We present bivariate relationships between diet and demographics and diet and behavioral characteristics in almost 30,000 adults in the United States. Results In general, intakes of these dietary factors were closer to recommendations among well-educated individuals, those engaged in other healthful behaviors, and underweight and normal weight individuals. Latinos had higher intakes of fruits and vegetables (men: 6 servings; women: 4.8 servings) and fiber (men: 23 g; women: 17 g), and generally a lower percentage of energy intake from fat (men: 33.7%; women: 32.1%) than did non-Latino whites (men: 5.4 servings; women: 4.5 servings; men: 19 g; women: 14 g; men: 33.9%; women: 32.0%) and non-Latino blacks (men: 5.4 servings; women: 4.4 servings; men: 19 g; women: 13 g; men: 34.7%; women: 33.5%). The strengths and limitations of the short dietary assessment method are discussed. Conclusions The Multifactor Screener in NHIS, when used in conjunction with external reference data, provides reasonable estimates for three dietary factors and suggests relationships between intakes and other characteristics that are consistent with other data. Thus, these NHIS estimates could provide useful national benchmarks for local surveys using the same instrument. J Am Diet Assoc. 2005;105:352-363.

Objective The aim of this study was to examine whether estimated net acid excretion (NAE) from two dietary assessment instruments can predict urine pH in healthy volunteers. Design The Observing Protein and Energy Nutrition (OPEN) study, which was designed to assess dietary measurement error, included men and women aged 40 to 69 years. Participants were asked to complete two food frequency questionnaires (FFQs) and two 24-hour recalls at approximately three-month intervals, and to return two 24-hour urine samples during the same period. NAE was estimated using a previously described equation. The estimates obtained from the different dietary assessment measures were correlated with actual urine pH. Subjects/setting Four hundred eighty-four subjects were enrolled in the OPEN study. All participants were included in this study on urine pH, given that they had all completed at least one dietary assessment and one urine sample. The study took place in Montgomery County, MD, between September 1999 and March 2000. Results Correlation coefficients between NAE estimates using the FFQ data and the average of two urine pH measures were -0.34 and -0.39 for women and men, respectively. Removing within-person variance in the urine pH levels resulted in a deattenuated overall correlation of -0.50 for the FFQ. Correlations between the 24-hour recall estimates of NAE were -0.41 and -0.32 for women and men, respectively. For the 24-hour recalls, the deattenuated overall correlation was -0.50. Application/conclusions Our findings suggest that FFQs provide adequate dietary data to estimate renal NAE and could be used as a surrogate for urinary pH levels in large epidemiologic studies. J Am Diet Assoc. 2003; 103: 1001-1007., In animal and human studies, low pH of the urine has been directly related to elevated levels of arylamine-DNA adducts in the bladder urothelium (1-3). Experimental data show that low [...]

Objective To evaluate the ability of 2 new short assessment instruments and a food frequency questionnaire (FFQ) to measure intake of fruit and vegetables. The 'All-Day' screener asks frequency and portion size questions about 9 food items. The 'By-Meal' screener is similar, except that it asks about 2 of those 9 food items in terms of mealtime. Design Survey participants completed 4 telephone-administered 24-hour dietary recalls over 1 year, a self-administered FFQ 1 to 2 months later, and 1 of 2 self-administered screeners after an additional 7 months. Subjects/setting Participating were 202 men and 260 women aged 20 to 70 years living throughout the United States. Statistical analyses Fruit and vegetable intakes measured by each screener and the FFQ were compared with true usual intake based on a measurement error model with 24hour dietary recalls as the reference instrument. Results Estimates of median daily servings of fruit and vegetables were as follows: For men: True intake (5.8) vs All-Day screener (5.0), By-Meal screener (5.5), and FFQ (6.6); for women: true intake (4.2) vs All-Day screener (5.0), By-Meal screener (5.4), and FFQ (6.2). Estimated correlations between the test instruments and true intake were as follows: For men: All-Day screener (0.66), By-Meal screener (0.67), FFQ (0.68); for women: All-Day screener (0.51), By-Meal screener (0.53), and FFQ (0.54). Applications/conclusions Both screeners might be useful to estimate median intakes of fruit and vegetable servings in US populations, but they might be less useful in accurately ranking individuals. More research is needed before using the screeners in ethnic or low-literacy populations. J Am Diet Assoc. 2002; 02:1764-1772., The ability to measure fruit and vegetable intake accurately is important for nutritional surveillance, intervention research, and epidemiology. Those pursuing surveillance and intervention research are most interested in accurate estimates [...]

Abstract: Objective: To describe the data-based development of a short dietary assessment instrument, a 16-item screener; and to evaluate the performance of the screener, comparing its performance with a complete 120-item food frequency questionnaire (FFQ) in assessing percentage energy from fat intake. Design: A subsample (n=404) of participants in the National Institutes of Health-AARP Diet and Health Study, who had completed an FFQ and two 24-hour dietary recalls, also completed the fat screener. Percentage energy from fat from the screener and from the FFQ were compared with estimated true usual intake using a measurement error model. Results: For men, the mean percentage energy from fat estimates for the different methods were: recalls, 30.1%, screener, 29.9%; FFQ, 30.4%. For women, the results were: recalls, 31.3%, screener, 28.4%, FFQ, 30.0%. Estimated correlations between true intake and screener were 0.64 and 0.58 for men and women, respectively, and between true intake and FFQ were 0.67 for men and 0.72 for women. Estimated attenuation coefficients for the screener were 1.29 (men) and 0.98 (women) and for the FFQ were 0.56 (men) and 0.57 (women). Conclusions: The percentage energy from fat screener, when used in conjunction with external reference data, may be useful to compare mean intakes of fat for different population subgroups, and to examine relationships between fat intake and other factors. [Copyright &y& Elsevier]

Abstract: Although 24-hour recalls are frequently used in dietary assessment, intake on a single day is a poor estimator of long-term usual intake. Statistical modeling mitigates this limitation more effectively than averaging multiple 24-hour recalls per respondent. In this article, we describe the statistical theory that underlies the four major modeling methods developed to date, then review the strengths and limitations of each method. We focus on the problem of estimating the distribution of usual intake for a population from 24-hour recall data, giving special attention to the problems inherent in modeling usual intake for foods or food groups that a proportion of the population does not consume every day (ie, episodically consumed foods). All four statistical methods share a common framework. Differences between the methods arise from different assumptions about the measurement characteristics of 24-hour recalls and from the fact that more recently developed methods build upon their predecessor(s). These differences can result in estimated usual intake distributions that differ from one another. We also demonstrate the need for an improved method for estimating usual intake distributions for episodically consumed foods. [Copyright &y& Elsevier]

Abstract: Objective: We propose a new statistical method that uses information from two 24-hour recalls 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 nonconsumption days that occur 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, may supplement the information from two or more 24-hour recalls using correlated mixed model regression. The model allows for correlation between the probability of consuming a food on a single day and the consumption-day amount. Percentiles of the distribution of usual intake are computed from the estimated model parameters. Results: The Eating at America’s Table Study 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. 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. [Copyright &y& Elsevier]

Abstract: Objective: Twenty-four–hour recalls capture rich information on food consumption, but suffer from inadequately measuring usual intakes of episodically consumed foods. We explore using food frequency questionnaire (FFQ) data as covariates in a statistical model to estimate individual usual intakes of episodically consumed foods and their distributions and describe the development of the Food Propensity Questionnaire, an FFQ introduced in the 2003-2004 National Health and Nutrition Examination Survey. Design: We analyzed data from 965 adult participants in the Eating at America’s Table Study who completed four 24-hour recalls and an FFQ. We assessed whether or not increasing FFQ-reported frequency was associated with both number of 24-hour recall consumption days and amounts reported. Results: For 52 of 56 food groups (93%), and 218 of 230 individual foods (95%), there were significant monotonically increasing relationships between FFQ frequency and 24-hour recall probability of consumption. For 47 of 56 food groups (84%) and 55 of 230 (24%) individual foods, there were significant positive correlations between FFQ frequencies and consumption-day mean intake. Conclusions: We found strong and consistent relationships between reported FFQ frequency of food and food-group consumption and probability of consumption on 24-hour recalls. This supports the premise that frequency data may offer important covariate information in supplementing multiple recalls for estimating usual intake of food groups. [Copyright &y& Elsevier]

Objective: It is now well-established that individuals misreport their dietary intake. We propose a new method (National Research Council-Biomarker [NRC-B]) for estimating population distributions of usual dietary intake from national survey 24-hour recall data, using additional biomarker data from an external study to adjust for such dietary misreporting., Statistical Analyses Performed: NRC-B is an extension of the NRC method, and is based upon two developed assumptions: the ratio of the mean of true intake to that of reported intake is equal in the survey and external biomarker study; and the ratio of the variance of true intake to that of reported intake is equal in these two studies. NRC-B adjusts the usual intake distribution both for within-person variation and for bias (underreporting) that occur with 24-hour recall reports. Using doubly labeled water ((2)H(2)(18)O) measurements from the Observing Protein and Energy Nutrition study, we applied NRC-B to data on energy intake for adults aged 40 to 69 years from two national surveys, the Continuing Survey of Food Intakes by Individuals and National Health and Nutrition Examination Survey. We compared the results with the NRC and traditional methods that used only the survey data to estimate dietary intake distributions., Results: Estimated distributions from NRC-B and NRC were much narrower and less skewed than from the traditional method. However, unlike NRC, the median of the NRC-B based distribution was higher by 8% to 16% than the traditional method in our examples., Conclusions: The proposed method adjusts for the well-documented problem of underreporting of energy intake.