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The Canadian Food Intake Screener/Questionnaire court canadien sur les apports alimentaires was developed to rapidly assess alignment of adults' dietary intake over the past month with the 2019 Canada's Food Guide's healthy food choices recommendations. From July to December 2021, adults (n = 154) aged 18–65 years completed the screener and up to two 24 h dietary recalls. The screener scoring system was aligned with the Healthy Eating Food Index-2019 (HEFI-2019), to the extent possible. Analysis of variance compared screener scores among subgroups with known differences in diet quality. Using the recall data, the National Cancer Institute multivariate method was used to model HEFI-2019 components, with the screener score as a covariate, and the correlation coefficient between screener and total HEFI-2019 scores was estimated. The mean screener score was 35 points (SD = 4.7; maximum 65), ranging from 26 (1st percentile) to 45 (99th percentile). Differences in scores in hypothesized directions were evident by gender identity (p = 0.06), perceived income adequacy (p = 0.07), education (p = 0.02), and smoking status (p = 0.003). The correlation between screener and HEFI-2019 scores was 0.53 (SE = 0.12). The screener's moderate construct validity supports its use for rapid assessment of alignment of adults' intake with the healthy food choices recommendations when comprehensive dietary assessment is not possible. The Canadian Food Intake Screener was developed to rapidly assess alignment of dietary intake with the Canada's Food Guide-2019 healthy food choices recommendations. Scoring is aligned with the Healthy Eating Food Index-2019 to the extent possible. Among a sample of adults, reasonable variation in screener scores was noted, mean screener scores differed between some subgroups with known differences in diet quality, and a moderate correlation between screener scores and total Healthy Eating Food Index-2019 scores based on repeat 24 h dietary recalls was observed. The Canadian Food Intake Screener has moderate construct validity for rapid assessment of overall alignment of adults' dietary intake with the Canada's Food Guide-2019 healthy food choices recommendations. [ABSTRACT FROM AUTHOR]

The objective of this project was to develop a brief self-administered dietary screener, in English and French, to rapidly assess alignment of adults' dietary intake with the 2019 Canada's Food Guide healthy food choices recommendations. In consultation with Health Canada and external advisors (n = 15), guiding principles were defined. Existing screeners were scanned, and the healthy food choices recommendations were mapped to inform questions and response options. Cognitive interviews were conducted in English (n = 17) and French (n = 16) with adults aged 18–65 years from April to June 2021 to assess understanding of questions and face validity; recruitment emphasized variation in sociodemographic characteristics. Face and content validity were assessed with experts in nutrition, surveillance, and public health (n = 13 English, 3 French) from April to May 2021. The testing indicated that the screener was well understood overall but informed refinements to improve comprehension of the questions and their alignment with the healthy food choices recommendations. The resulting Canadian Food Intake Screener/Questionnaire court canadien sur les apports alimentaires includes 16 questions to rapidly assess alignment of intake with the 2019 Canada's Food Guide healthy food choices recommendations, including healthy foods and foods to limit, in situations in which comprehensive dietary assessment is not feasible. The Canadian Food Intake Screener was developed to rapidly assess alignment of adults' dietary intake over the past month with the Food Guide's healthy food choices recommendations. The screener was developed and evaluated through an iterative process that included three rounds of cognitive interviews in each of English and French, along with ongoing feedback from external advisors and face and content validity testing with a separate panel of content experts. The 16-question screener is intended for use with adults, aged 18–65 years, with marginal and higher health literacy in research and surveillance contexts in which comprehensive dietary assessment is not possible. [ABSTRACT FROM AUTHOR]

A priori dietary indices provide a standardized, reproducible way to evaluate adherence to dietary recommendations across different populations. Existing nutrient-based indices were developed to reflect food/beverage intake; however, given the high prevalence of dietary supplement (DS) use and its potentially large contribution to nutrient intakes for those that use them, exposure classification without accounting for DS is incomplete. The purpose of this article is to review existing nutrient-based indices and describe the development of the Total Nutrient Index (TNI), an index developed to capture usual intakes from all sources of under-consumed micronutrients among the U.S. population. The TNI assesses U.S. adults' total nutrient intakes relative to recommended nutrient standards for eight under-consumed micronutrients identified by the Dietary Guidelines for Americans: calcium, magnesium, potassium, choline, and vitamins A, C, D, E. The TNI is scored from 0 to 100 (truncated at 100). The mean TNI score of U.S. adults (≥19 y; n = 9,954) based on dietary data from NHANES 2011-2014, was 75.4; the mean score for the index ignoring DS contributions was only 69.0 (t-test; p < 0.001). The TNI extends existing measures of diet quality by including nutrient intakes from all sources and was developed for research, monitoring, and policy purposes. Supplemental data for this article is available online at https://doi.org/10.1080/10408398.2021.1967872. [ABSTRACT FROM AUTHOR]

Background: The National Cancer Institute (NCI) method has been used widely by researchers to make inferences about usual dietary intake distributions of foods and nutrients based on a limited number of 24-hour dietary recalls (24HRs). Although the NCI method does not provide individual estimates of usual intake, it can be used to address many research questions, including modeling effects of nutrition interventions on population distributions of usual intake. Software for implementing the NCI method and corresponding code examples is publicly available in the form of SAS macros, but little formal guidance exists for conducting advanced analyses.Objectives: We aim to present advanced techniques for working with NCI macros to conduct both basic and advanced dietary analyses and modeling.Method: We first present the three basic building blocks of analyses using the NCI method: 1) dataset preparation; 2) application of the MIXTRAN macro to estimate parameters of the usual intake distribution, including effects of covariates, after transformation of 24HRs to approximate normality; and 3) application of the DISTRIB macro to estimate the distribution of usual nutrient intake. Then, we illustrate how researchers can employ these building blocks to answer questions beyond typical descriptive analyses.Results: Researchers can adapt the building blocks to 1) account for factors such as demographic changes or nutrition interventions such as food fortification, 2) estimate the prevalence of dietary inadequacy via the full probability method, 3) incorporate nutrient intake from sources not always captured by 24HRs, such as dietary supplements and human milk, and 4) carry out multiple subgroup analyses. This paper describes the theoretical basis and operational guidance for these techniques.Conclusion: With this paper as a detailed resource, researchers can leverage the basic NCI building blocks to investigate a wide range of questions about usual dietary intake distribution. [ABSTRACT FROM AUTHOR]

A Longstanding goal of dietary surveillance has been to estimate the proportion of the population with intakes above or below a target, such as a recommended level of intake. However, until now, statistical methods for assessing the alignment of food intakes with recommendations have been lacking. The purposes of this study were to demonstrate the National Cancer Institute's method of estimating the distribution of usual intake of foods and determine the proportion of the U.S. population who does not meet federal dietary recommendations. Data were obtained from the 2001-2004 NHANES for 16,338 persons, aged 2 y and older. Quantities of foods reported on 24-h recalls were translated into amounts of various food groups using the MyPyramid Equivalents Database. Usual dietary intake distributions were modeled, accounting for sequence effect, weekend/weekday effect, sex, age, poverty income ratio, and race/ethnicity. The majority of the population did not meet recommendations for all of the nutrient-rich food groups, except total grains and meat and beans. Concomitantly, overconsumption of energy from solid fats, added sugars, and alcoholic beverages ('empty calories') was ubiquitous. Over 80% of persons age [greater than or equal to] 71 y and over 90% of all other sex-age groups had intakes of empty calories that exceeded the discretionary calorie allowances. In conclusion, nearly the entire U.S. population consumes a diet that is not on par with recommendations. These findings add another piece to the rather disturbing picture that is emerging of a nation's diet in crisis. doi: 10.3945/jn.110.124826.

The USDA's Healthy Eating Index-2005 (HEI-2005) is a tool to quantify the quality of diet consumed by individuals in the U.S. It comprises 12 components expressed as ratios of a food group or nutrient intake to energy intake. Components are scored on a scale from 0 to M, where M is 5, 10, or 20. Ideally, the HEI-2005 is calculated on the basis of the usual, or long-term average, dietary intake of an individual. In recent cycles of the NHANES, intake data have been collected via 24-h recalls for more than 1 d on most participants. We present here a statistical method to estimate a population's distribution of usual HEI-2005 component scores when [greater than or equal to] 2 d of dietary information is available for a sample of individuals from the population. Distributions for the total population and for age-gender subgroups may be estimated. The method also yields an estimate of the population's mean total HEI-2005 score. Application of the method to NHANES data for 2001-2004 yielded estimated distributions for all 12 components; those of total vegetables (range 0-5), whole grains (range 0-5), and energy from solid fats, alcoholic beverages, and added sugars (range 0-20) are presented. The total population mean scores for these components were 3.21, 1.00, and 8.41, respectively. An estimated 30% of the total population had a score of doi: 10.3945/jn.110.124594.

Our objective in this study was to estimate calcium intakes from food, water, dietary supplements, and antacids for U.S. citizens aged [greater than or equal to] 1 y using NHANES 2003-2006 data and the Dietary Reference Intake panel age groupings. Similar estimates were calculated for vitamin D intake from food and dietary supplements using NHANES 2005-2006. Diet was assessed with 2 24-h recalls; dietary supplement and antacid use were determined by questionnaire. The National Cancer Institute method was used to estimate usual nutrient intake from dietary sources. The mean daily nutrient intake from supplemental sources was added to the adjusted dietary intake estimates to produce total usual nutrient intakes for calcium and vitamin D. A total of 53% of the U.S. population reported using any dietary supplement (2003-2006), 43% used calcium (2003-2006), and 37% used vitamin D (2005-2006). For users, dietary supplements provided the adequate intake (Al) recommendation for calcium intake for ~12% of those [greater than or equal to] 71 y. Males and females aged 1-3 y had the highest prevalence of meeting the AI from dietary and total calcium intakes. For total vitamin D intake, males and females [greater than or equal to] 71, and females 14-18 y had the lowest prevalence of meeting the Al. Dietary supplement use is associated with higher prevalence of groups meeting the AI for calcium and vitamin D. Monitoring usual total nutrient intake is necessary to adequately characterize and evaluate the population's nutritional status and adherence to recommendations for nutrient intake. doi: 10.3945/jn.109.118539

Estimating the population distribution of the usual intake of a nutrient relative to that of another nutrient requires determination of individual-level ratios, if intake data are available on a per-day basis, as with 24-h dietary recalls, those ratios can be determined in 1 of 2 ways: as the usual ratio of intakes or the ratio of usual intakes. Each of these ratios has its own meaning and determination; the ratio of usual intakes is conceptually consistent with determinations obtained from FFQ data. We present a method for estimating the ratio of usual intakes that uses bivariate modeling of the 2 nutrient intakes in question. Application of the method to the NHANES data for the years 2001-2004 yielded estimated distributions for percent of usual energy intake from total fat, percent of usual energy intake from saturated fat, and usual sodium intake per 1000 kcal (4184 kJ) of usual energy intake. Distributions for both the total population and for age- gender subgroups were estimated. Approximately 60% of adults (>19 y) had a usual total fat intake that was within the recommended range of 20-35% of total energy, but only ~34% had a usual saturated fat intake doi: 10.3945/jn.109.110254.

Few biomarker-based validation studies have examined error in online self-report dietary assessment instruments, and food records (FRs) have been considered less than food frequency questionnaires (FFQs) and 24-hour recalls (24HRs). We investigated measurement error in online and paper-based FFQs, online 24HRs, and paper-based FRs in 3 samples drawn primarily from 3 cohorts, comprising 1,393 women and 1,455 men aged 45–86 years. Data collection occurred from January 2011 to October 2013. Attenuation factors and correlation coefficients between reported and true usual intake for energy, protein, sodium, potassium, and respective densities were estimated using recovery biomarkers. Across studies, average attenuation factors for energy were 0.07, 0.07, and 0.19 for a single FFQ, 24HR, and FR, respectively. Correlation coefficients for energy were 0.24, 0.23, and 0.40, respectively. Excluding energy, the average attenuation factors across nutrients and studies were 0.22 for a single FFQ, 0.22 for a single 24HR, and 0.51 for a single FR. Corresponding correlation coefficients were 0.31, 0.34, and 0.53, respectively. For densities (nutrient expressed relative to energy), the average attenuation factors across studies were 0.37, 0.17, and 0.50, respectively. The findings support prior research suggesting different instruments have unique strengths that should be leveraged in epidemiologic research. [ABSTRACT FROM AUTHOR]

Objective: To evaluate, through study- and individual-level analyses of data from 7 studies, the effectiveness of school-based nutrition interventions on child fruit and vegetable (FV) consumption. Design: To find original studies on school-based nutrition interventions, the authors searched electronic databases from 1990 to 2002. First authors of the 13 eligible studies were contacted to request their data. Data from 7 studies were received for inclusion in this pooled analysis. Setting: Schools. Participants: 8156 children were matched from pretest to posttest. Participants were primarily elementary school-aged (75.5%) and white (66%), and 50.4% were males. Main Outcome Measures: Net FV difference and net FV relative change (%). Analysis: Data were analyzed at both the study and individual levels. A fitted multivariable fixed-effects model was used to analyze the role of potential covariates on FV intake. Statistical significance was set at [alpha] = .05. Results: At the individual level, the net difference in FV consumption was 0.45 (95% CI 0.33-0.59) servings; the net relative change was 19% (95% CI 0.15-0.23) servings. Conclusions and Implications: School-based nutrition interventions produced a moderate increase in FV intake among children. These results may have implications for chronic disease prevention efforts, including cardiovascular disease and cancer. Key Words: child, adolescent, schools, interventions, fruit and vegetable, pooled analysis, nutrition, diet, meta-analysis

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.

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.jada.2006.06.002 Byline: Patricia M. Guenther, Kevin W. Dodd, Jill Reedy, Susan M. Krebs-Smith Abstract: To estimate the proportions of the population meeting recommendations for fruit and vegetable intake, we first estimated the usual intake distributions of total fruits and vegetables and then compared the results to the 5 A Day recommendation and to the recommendations for fruits and vegetables combined, found in the new US Department of Agriculture food guide, MyPyramid.

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.jada.2006.06.002 Byline: Patricia M. Guenther, Kevin W. Dodd, Jill Reedy, Susan M. Krebs-Smith Abstract: To estimate the proportions of the population meeting recommendations for fruit and vegetable intake, we first estimated the usual intake distributions of total fruits and vegetables and then compared the results to the 5 A Day recommendation and to the recommendations for fruits and vegetables combined, found in the new US Department of Agriculture food guide, MyPyramid.

Objective To estimate the proportions of the population meeting recommendations for fruit and vegetable intake, we first estimated the usual intake distributions of total fruits and vegetables and then compared the results to the 5 A Day recommendation and to the recommendations for fruits and vegetables combined, found in the new US Department of Agriculture food guide, MyPyramid. Design/subjects The primary dataset was created from one 24-hour recall from each of 8,070 respondents in the 1999-2000 National Health and Nutrition Examination Survey. Variances were estimated using one or two 24-hour recalls from 14,963 respondents in the 1994-1996 Continuing Survey of Food Intakes by Individuals. Statistical analysis The statistical method developed at Iowa State University was used for estimating distributions of usual intake of dietary components that are consumed daily. It was modified to allow the adjustment of heterogeneous within-person variances using an external estimate of heterogeneity. Results In 1999-2000, only 40% of Americans ate an average of five or more 1/2-cup servings of fruits and vegetables per day. The proportions of sex-age groups meeting the new US Department of Agriculture recommendations ranged from 0.7% of boys aged 14 to 18 years, whose combined recommendation is 5 cups, to 48% of children aged 2 to 3 years, whose combined recommendation is 2 cups. Conclusions Americans need to consume more fruits and vegetables, especially dark green and orange vegetables and legumes. Nutritionists must help consumers realize that, for everyone older than age 3 years, the new recommendations for fruit and vegetable intakes are greater than the familiar five servings a day. J Am Diet Assoc. 2006;106:1371-1379.