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Accurately estimating portion sizes remains a challenge in dietary assessment. Digital images used in online 24-hour dietary recalls may be conducive to accuracy. The current analyses were conducted to examine the accuracy of portion size estimation by women with low incomes who completed 24-hour dietary recalls using the online Automated Self-Administered 24-hour Dietary Assessment Tool (ASA24) in the Food and Eating Assessment Study II. True dietary intake was observed for 3 meals on 1 day through a controlled feeding study conducted from May through July 2016. The following day, participants completed an unannounced 24-hour dietary recall using ASA24, independently or with assistance in a small-group setting. Participants included 302 women aged 18 to 82 years living in the Washington, DC, area who met the income thresholds for the Supplemental Nutrition Assistance Program. The accuracy of portion size estimation was assessed by comparing the weight truly consumed (observed) and the weight reported for predetermined categories of foods and beverages. The differences between observed and reported portions were examined and linear regression tested differences by recall condition. Analyses were conducted by condition and repeated with stratification by racial/ethnic identity, education, and body mass index. On average across foods and beverages, reported portion sizes were 7.4 g (95% CI, 4.3-10.5) and 6.4 g (95% CI, 2.8-10.0) higher than observed portion sizes in the independent and assisted conditions, respectively. Portion sizes were overestimated for small pieces and shaped foods in both conditions, as well as for amorphous/soft foods in the assisted condition and underestimated for single-unit foods in both conditions. Misestimation was fairly consistent by participants' race/ethnicity, education, and body mass index, to varying magnitudes. Women with low incomes overestimated the amounts of foods and beverages consumed across several categories using online 24-hour dietary recalls with digital images to support portion size estimation. Assistance with ASA24 had little impact on accuracy. [ABSTRACT FROM AUTHOR]

Many research questions focused on characterizing usual, or long-term average, dietary intake of populations and subpopulations rely on short-term intake data. The objective of this paper is to review key assumptions, statistical techniques, and considerations underpinning the use of short-term dietary intake data to make inference about usual dietary intake. The focus is on measurement error and strategies to mitigate its effects on estimated characteristics of population-level usual intake, with attention to relevant analytic issues such as accounting for survey design. Key assumptions are that short-term assessments are subject to random error only (i.e., unbiased for individual usual intake) and that some aspects of the error structure apply to all respondents, allowing estimation of this error structure in data sets with only a few repeat measures per person. Under these assumptions, a single 24-hour dietary recall per person can be used to estimate group mean intake; and with as little as one repeat on a subsample and with more complex statistical techniques, other characteristics of distributions of usual intake, such as percentiles, can be estimated. Related considerations include the number of days of data available, skewness of intake distributions, whether the dietary components of interest are consumed nearly daily by nearly everyone or episodically, the number of correlated dietary components of interest, time-varying nuisance effects related to day of week and season, and variance estimation and inference. Appropriate application of assumptions and recommended statistical techniques allows researchers to address a range of research questions, though it is imperative to acknowledge systematic error (bias) in short-term data and its implications for conclusions. [ABSTRACT FROM AUTHOR]

Existing nutrition knowledge measures tend to be lengthy or tailored for specific contexts, making them unsuitable for population-based surveys. Given the growing emphasis within country-specific dietary guidelines on reducing consumption of highly processed foods, consumers' ability to understand and apply principles related to level of food processing could serve as a proxy measure of general nutrition knowledge. To examine the content validity of the Food Processing Knowledge (FoodProK) score based on subject matter expert consultation with Registered dietitian nutritionists (RDNs). RDNs in Canada (n = 64) completed an online survey, including the FoodProK, in January 2020. Participants rated the "healthiness" of 12 food products from four categories (fruit, meat, dairy, and grains) on a scale from 1 to 10. FoodProK scores were assigned based on concordance of ratings within each food category, with rankings according to the NOVA classification system, with less processed foods representing higher healthiness. For each category, one-way repeated-measures analysis of variance models tested whether the three product ratings were significantly different from one another. Descriptive statistics compared ratings and FoodProK scores across categories. Open-ended feedback was solicited to assess face validity of the score. RDNs' FoodProK scores were strongly associated with level of food processing. Almost one in three RDNs received perfect FoodProK scores, and the mean score was 7.0 of 8.0 possible points. Within each category, the three foods received significantly different healthiness ratings, in the same order as the NOVA system (P < 0.001 for all contrasts). Open-ended responses showed that RDNs did not perceive meaningful differences between the processed meat products, suggesting the need to change one of the products in the meat category. Overall, 80% of RDNs reported level of processing as an important indicator of the healthiness of foods. Level of food processing represents a promising framework for assessing general nutrition knowledge in population-based surveys. [ABSTRACT FROM AUTHOR]

Careful consideration of the validity and reliability of methods intended to assess dietary intake is central to the robustness of nutrition research. A dietary assessment method with high validity is capable of providing useful measurement for a given purpose and context. More specifically, a method with high validity is well grounded in theory; its performance is consistent with that theory; and it is precise, dependable, and accurate within specified performance standards. Assessing the extent to which dietary assessment methods possess these characteristics can be difficult due to the complexity of dietary intake, as well as difficulties capturing true intake. We identified challenges and best practices related to the validation of self-report dietary assessment methods. The term validation is used to encompass various dimensions that must be assessed and considered to determine whether a given method is suitable for a specific purpose. Evidence on the varied concepts of validity and reliability should be interpreted in combination to inform judgments about the suitability of a method for a specified purpose. Self-report methods are the focus because they are used in most studies seeking to measure dietary intake. Biomarkers are important reference measures to validate self-report methods and are also discussed. A checklist is proposed to contribute to strengthening the literature on the validation of dietary assessment methods and ultimately, the nutrition literature more broadly. [ABSTRACT FROM AUTHOR]

This monograph describes the National Cancer Institute’s Dietary Assessment Primer, a web resource developed to help researchers choose the best available dietary assessment approach to achieve their research objective. All self-report instruments have error, but understanding the nature of that error can lead to better assessment, analysis, and interpretation of results. The Primer includes profiles of the major self-report dietary assessment instruments, including guidance on the best uses of each instrument; discussion of validation and measurement error generally and with respect to each instrument; guidance for choosing a dietary assessment approach for different research questions; and additional resources, such as a glossary, references, and overviews of specific/important issues in the field. This monograph also describes some future research needs in the field of dietary assessment. [ABSTRACT FROM AUTHOR]

Characterizing relationships between diet, body weight, and health is complicated by reporting errors in dietary intake data that are associated with body weight. The objectives of this study were to assess changes in reporting across days (reactivity) on food checklists and associations between reactivity and body mass index (BMI) using data from two cross-sectional studies: (a) the Recontacting Participants in the Observing Protein and Energy Nutrition study (n=297), which was conducted in 2003-2004 and included a 7-day checklist and a 4-day food record, and (b) the America''s Menu Daily Food Report Study (n=530), which was conducted in 1996 and included a 30-day checklist. Zero-inflated Poisson regression was used to assess effects of reporting day on frequency of consumption for the checklists and number of items reported for the food record. Interactions between day and BMI were tested using contrast statements. Frequency of reported consumption decreased across days among males and females for total items and many of the eight food groups on the 7-day checklist; among females, the effect of reporting day differed by BMI category for the meat, fish, and poultry group. Smaller declines across days were observed for some of the 22 food groups on the 30-day checklist; no interactions with BMI were apparent. No reporting day effects were observed in the food record data. The results suggest inconsistent reactivity across days, possibly reflecting changes in reporting or consumption behavior. However, the effects are generally small and independent of body weight, suggesting that checklists are potentially useful for the study of body weight and diet. [Copyright &y& Elsevier]

Front-of-package (FOP) nutrition labeling systems differ in how they rate food and beverage products. There is a need to examine the implications of these differences, including their focus on nutrients of public health concern. Our aim was to examine the impacts of 4 common FOP labels on consumers' purchases of products that received conflicting ratings across FOP systems. In an experimental marketplace, participants were randomized to complete a series of purchases under 1 of 5 FOP conditions: no label, "high in" nutrient labels, multiple traffic light, Health Star Rating, or a 5-color nutrition grade. A final sample of 3,584 Canadians (13 years and older) were recruited from shopping centers in March to May 2018. Probability of purchasing was assessed for 5 product categories (100% fruit juice, plain milk, chocolate milk, cheese snacks, and diet beverages), which received conflicting ratings across the FOP conditions. Separate generalized linear mixed models estimated the influence of FOP condition on 5 binary outcomes (1 = purchased, 0 = not purchased) corresponding to the product categories. Few differences were observed among the full sample. Among participants who noticed the labels (n = 1,993), those in the Health Star Rating condition were 4.5 percentage points (95% CI –7.0 to –1.9) more likely to purchase 100% fruit juice (compared to multiple traffic light) and 3.3 (95% CI 0.4 to 6.2) and 3.0 percentage points (95% CI 0.1 to 6.1) more likely to purchase cheese snacks (compared to no label and "high in"). "High in" labels produced fewer purchases of chocolate milk than no label. Despite some similarities, existing FOP systems differ in the extent to which they promote or dissuade purchases of common product categories. Although the Health Star Rating might encourage purchases of products with certain positive nutritional attributes, "high in" and multiple traffic light systems might more effectively discourage purchases of products contributing nutrients of public health concern. [ABSTRACT FROM AUTHOR]

The construct and predictive validity of the Healthy Eating Index (HEI) have been demonstrated, but how error in reported dietary intake may affect scores is unclear. These analyses examined concordance between HEI-2015 scores based on observed vs reported intake among adults. Data were from two feeding studies (Food and Eating Assessment STudy, or FEAST, I and II) in which true intake was observed for three meals on 1 day. The following day, participants completed an unannounced 24-hour dietary recall. FEAST I (2012) included 81 men and women, aged 20 to 70 years, living in the Washington, DC, area. FEAST II (2016) included 302 women, aged 18 years or older, with low household incomes and living in the Washington, DC, area. In FEAST I, recalls were completed independently using the Automated Self-Administered 24-hour Dietary Assessment Tool (ASA24-2011) or interviewer-administered using the Automated Multiple-Pass Method. In FEAST II, recalls were completed using ASA24-2016, independently or in a small group setting with assistance. HEI-2015 scores were calculated using the population ratio method. T -tests determined whether differences between scores based on observed and reported intake were different from zero. FEAST I data were stratified by sex, and in FEAST II, analyses were repeated by education and body mass index (BMI). Differences in total HEI-2015 scores between observed and reported intake ranged from −1.3 to 5.8 points among those completing ASA24 independently in both studies, compared with −2.5 points in the small group setting. For interviewer-administered recalls, the differences were −1.1 for men and 2.3 for women. In FEAST II, total HEI-2015 scores derived from observed intake were lower than scores derived from reported intake among those who had completed high school or less (−3.2, SE 1.1, P <0.01) and those with BMI ≥ 30 (−2.8, SE 1.1, P = 0.01). HEI-2015 scores based on 24-hour dietary recall data are generally well estimated. [ABSTRACT FROM AUTHOR]

Abstract: Background: Income and race/ethnicity are associated with differences in dietary intakes that may contribute to health disparities among members of the US population. Objective: To examine alignment of intakes of food groups and energy from solid fats, added sugars, and alcohol with the 2005 Dietary Guidelines for Americans and MyPyramid, by family income and race/ethnicity. Design: Data from the National Health and Nutrition Examination Survey, a cross-sectional, nationally representative survey, for 2001-2004. Participants/setting: Persons aged ≥2 years for whom reliable dietary intake data were available (n=16,338) were categorized by income (lowest, middle, and highest) and race/ethnicity (non-Hispanic white, non-Hispanic black, and Mexican American). Statistical analyses performed: The National Cancer Institute method was used to estimate the proportions of adults and children in each income and race/ethnic group whose usual intakes met the recommendations. Results: Higher income was associated with greater adherence to recommendations for most food groups; the proportions meeting minimum recommendations among adults in the highest income group were double that observed for the lowest income group for total vegetables, milk, and oils. Fewer differences by income were apparent among children. Among the race/ethnic groups, the proportions meeting recommendations were generally lowest among non-Hispanic blacks. Marked differences were observed for milk—15% of non-Hispanic black children met the minimum recommendations compared with 42% of non-Hispanic white children and 35% of Mexican-American children; a similar pattern was evident for adults. One in five Mexican-American adults met the dry beans and peas recommendations compared with approximately 2% of non-Hispanic whites and non-Hispanic blacks. Most adults and children consumed excess energy from solid fats and added sugars irrespective of income and race/ethnicity. Conclusions: The diets of some subpopulations, particularly individuals in lower-income households and non-Hispanic blacks, are especially poor in relation to dietary recommendations, supporting the need for comprehensive strategies to enable healthier dietary intake patterns. [Copyright &y& Elsevier]

The US food system is primarily an economic enterprise, with far-reaching health, environmental, and social effects. A key data source for evaluating the many effects of the food system, including the overall quality and extent to which it provides the basic elements of a healthful diet, is the Food Availability Data System. The objective of the present study was to update earlier research that evaluated the extent to which the US food supply aligns with the most recent federal dietary guidance, using the current Healthy Eating Index-2010 (HEI-2010) and food supply data extending through 2010. The HEI-2010 was applied to 40 years of food supply data (1970-2010) to examine trends in the overall food supply as well as specific components related to a healthy diet, such as fruits and vegetables. The HEI-2010 overall summary score hovered around half of optimal for all years evaluated, with an increase from 48 points in 1970 to 55 points (out of a possible 100 points) in 2010. Fluctuations in scores for most individual components did not lead to sustained trends. Our study continues to demonstrate sizable gaps between federal dietary guidance and the food supply. This disconnect is troublesome within a context of high rates of diet-related chronic diseases among the population and suggests the need for continual monitoring of the quality of the food supply. Moving toward a food system that is more conducive to healthy eating requires consideration of a range of factors that influence food supply and demand. [ABSTRACT FROM AUTHOR]

Psychosocial stress and diet quality individually mediate associations between socioeconomic position (SEP) and health; however, it is not known whether they jointly mediate these associations. This is an important question because stress-related unhealthy eating is often invoked as an explanation for diet-related health inequities, particularly among women, seemingly with no empirical justification. This study examined whether psychosocial stress and diet quality jointly mediated associations between SEP and self-rated health in women and men. Multiple mediating pathways were modeled using data from the cross-sectional International Food Policy Study. Data were collected from 5,645 adults (aged 18 years or older) in Canada during 2018 and 2019. Participants reported SEP using indicators of materialist (educational attainment and perceived income adequacy) and psychosocial pathways (subjective social status), along with psychosocial stress, dietary intake (to assess overall diet quality via Healthy Eating Index-2015 scores), and self-rated health. Structural equation modeling modeled pathways linking SEP (ie, educational attainment, perceived income adequacy, and subjective social status) with self-rated health mediated by psychosocial stress and diet quality, stratified by gender. There was no evidence that psychosocial stress and diet quality jointly mediated associations between SEP and self-rated health in women or men. Diet quality mediated associations between educational attainment and self-rated health in women and men, with some evidence that it mediated associations between subjective social status and self-rated health in men (P = 0.051). Psychosocial stress mediated associations between perceived income adequacy and self-rated health in women and men, and between subjective social status and self-rated health in women. Although often invoked as an explanation for diet-related health inequities, stress-related poor diet quality did not mediate associations between SEP and self-rated health in women or men. Psychosocial stress and diet quality individually mediated some of these associations, with some differences by gender. [ABSTRACT FROM AUTHOR]

Evidence suggests that combining tools that gather short- and long-term dietary data may be the optimal approach for the assessment of diet–disease associations in epidemiologic studies. Online technology can reduce the associated burdens for researchers and participants, but feasibility must be demonstrated in real-world settings before wide-scale implementation. The objective of this study was to determine the feasibility and acceptability of combining web-based tools (the Automated Self-Administered 24-hour Dietary Assessment Tool [ASA24-2016] and the past-year Diet History Questionnaire II [DHQ-II]) in a subset of participants in Alberta's Tomorrow Project, a prospective cohort. For this feasibility study, invitations were mailed to 550 randomly selected individuals enrolled in Alberta's Tomorrow Project. Consented participants (n = 331) were asked to complete a brief sociodemographic and health questionnaire, four ASA24-2016 recalls, the DHQ-II, and an evaluation survey. The study was conducted from March 2016 to December 2016 in Alberta, Canada. The majority of participants, mean age (SD) = 57.4 (9.8) years, were women (70.7%), urban residents (85.5%), and nonsmokers (95.7%). Primary outcomes were number of ASA24-2016 recalls completed, response rate of DHQ-II completion, and time to complete each assessment. The Wilcoxon signed rank sum test was used to assess differences in completion time. One-third (n = 102) of consenting participants did not complete any ASA24-2016 recalls. The primary reason to withdraw from the feasibility study was a lack of time. Among consenting participants, 51.9% (n = 172), 41.1% (n = 136), and 36.5% (n = 121) completed at least two ASA24-2016 recalls, the DHQ-II, and at least two ASA24-2016 recalls plus the DHQ-II, respectively. Median (25th to 75th percentile) completion times for participants who completed all recalls were 39 minutes (25 to 53 minutes) for the first ASA24-2016 recall and 60 minutes (40 to 90 minutes) for the DHQ-II. Findings indicate combining multiple ASA24-2016 recalls and the DHQ-II is feasible in this subset of Alberta's Tomorrow Project participants. However, optimal response rates may be contingent on providing participant support. Completion may also be sensitive to timing and frequency of recall administration. [ABSTRACT FROM AUTHOR]

Efforts to lose, gain, or maintain weight are prevalent among youth and young adults, but little is known about the relationship between weight management efforts and dietary quality. Attempts to manage weight are typically driven by weight perceptions, which may also uniquely affect overall diet. The objective was to explore sex-stratified associations between weight management efforts and perceptions with dietary quality among youth and young adults. Cross-sectional online survey data were drawn from Wave 1 (2016) of the Canada Food Study. Youth and young adults (n = 3,000), aged 16 to 30 years, were recruited from community settings in five Canadian cities and completed the online survey. The analytic sample consisted of 2,040 participants. The Healthy Eating Index-2015 (HEI-2015) was used to characterize dietary quality among participants who completed a 24-hour recall. Respondents reported their weight change efforts over the past year and their weight perception. Sex-stratified multiple linear regression analyses were conducted to investigate relationships between each of weight management efforts and perceptions, separately, and dietary quality, controlling for known covariates. The HEI-2015 mean score was 52 of 100 possible points. Nearly one quarter of male and female respondents reported not trying to do anything about their weight, whereas 16% reported trying to maintain, 28% and 5% trying to gain, and 33% and 55% trying to lose weight, respectively. Most respondents (63% of males and 66% of females) perceived their weight as just about right. Among males, trying to gain or maintain weight were each significantly associated with higher HEI-2015 mean scores compared with not trying to manage weight (P <.01 and <.001, respectively), whereas this relationship existed only for weight maintenance among female respondents (P <.01). Weight perceptions and HEI-2015 mean scores were not significantly related. Efforts to manage weight, which are commonplace among youth and young adults, are associated with dietary quality. Future behavioral research may provide insights into strategies used by youth to manage weight, guiding interventions that recognize links among weight-related behaviors, dietary quality, and other determinants of health. [ABSTRACT FROM AUTHOR]

Automated Self-Administered 24-Hour Dietary Assessment Tool (ASA24) is a self-administered web-based tool designed to collect detailed dietary data at low cost in observational studies. The objectives of this study were to describe, overall and by demographic groups, the performance and feasibility of ASA24-2011 recalls and compare Healthy Eating Index-2015 (HEI-2015) total and component scores to 4-day food records (4DFRs) and food frequency questionnaires (FFQs). Over 12 months, participants completed up to 6 ASA24 recalls, 2 web-based FFQs, and 2 unweighed paper-and-pencil 4DFRs. Up to 3 attempts were made to obtain each ASA24 recall. Participants were administered doubly-labeled water to provide a measure of total energy expenditure and collected two 24-hour urine samples to assess concentrations of nitrogen, sodium, and potassium. From January through September 2012, 1,110 adult members of AARP, 50 to 74 years of age, were recruited from the Pittsburgh, PA, area to participate in the Interactive Diet and Activity Tracking in AARP (IDATA) study. After excluding 33 participants who had not completed any dietary assessments, 531 men and 546 women remained. Response rates, nutrient intakes compared to recovery biomarkers across each ASA24 administration day, and HEI-2015 total and component scores were measured. Means, medians, standard deviations, interquartile ranges, and HEI-2015 total and component scores computed using a multivariate measurement error model are presented. Ninety-one percent of men and 86% of women completed 3 ASA24 recalls. Approximately three-quarters completed 5 or more, higher than the completion rates for 2 4DFRs and 2 FFQs. Approximately, three-quarters of men and 70% of women completed ASA24 on the first attempt; 1 in 5 completed it on the second. Completion rates varied slightly by age and body mass index. Median time to complete ASA24-2011 (current version: ASA24-2020) declined with subsequent recalls from 55 to 41 minutes in men and from 58 to 42 minutes in women and was lowest in those younger than 60 years. Mean nutrient intakes were similar across recalls. For each recording day, energy intakes estimated by ASA24 were lower than energy expenditure. Reported intakes for protein, potassium, and sodium were closer to recovery biomarkers for women, but not for men. Geometric means of reported intakes of these nutrients did not systematically vary across ASA24 administrations, but differences between reported intakes and biomarkers differed by nutrient. Of 100 possible points, HEI-2015 total scores were nearly identical for 4DFRs and ASA24 recalls and higher for FFQs (men: 61, 60, and 68; women: 64, 64, and 72, respectively). ASA24, a freely available dietary assessment tool for use in large-scale nutrition research, was found to be highly feasible. Similar to previously reported data for nutrient intakes, HEI-2015 total and component scores for ASA24 recalls were comparable to those for 4DFRs, but not FFQs. ClinicalTrials.gov identifier: NCT03268577 (http://www.clinicaltrials.gov). [ABSTRACT FROM AUTHOR]

Quantitative research depends on using measures to collect data that are valid (ie, reflect well the phenomena of interest) and perform equivalently across contexts. Demonstrating validity and cross-context equivalence requires specifically designed studies, but many such studies have problems that have limited their usefulness. This article explains validity and cross-context equivalence of measures (and important related concepts) and clarifies how to establish them. Validation is the process of determining whether a measure or indicator is suitable for providing useful analytical measurement for a given purpose and context. Cross-context equivalence means that a measure performs comparably across contexts. Four types of equivalence are construct, item, measurement, and scalar. Establishing validity and cross-context equivalence requires representing mathematically the errors (ie, imprecision, undependability, and inaccuracy) of a measure and using appropriate statistical methods to quantify these errors. Studies aiming to provide evidence about the validity of a measure need to clarify the purpose and context for use of that measure. Choose one of the two conceptual systems for validation; obtain data to establish the extent to which the measure is well constructed, reliable, and accurate; and use analytic methods beyond simple correlations to provide a basis for making reasoned judgment about whether the measure provides useful analytic measurement for the particular purpose(s) and context. Establishing accuracy of a measure requires having available other measures known to be accurate as comparators; in the case that no other measure understood to be more accurate is available, then the study will be able to establish agreement rather than validity. [ABSTRACT FROM AUTHOR]

Abstract: The Healthy Eating Index (HEI) is a measure of diet quality in terms of conformance with federal dietary guidance. Publication of the 2010 Dietary Guidelines for Americans prompted an interagency working group to update the HEI. The HEI-2010 retains several features of the 2005 version: (a) it has 12 components, many unchanged, including nine adequacy and three moderation components; (b) it uses a density approach to set standards, eg, per 1,000 calories or as a percentage of calories; and (c) it employs least-restrictive standards; ie, those that are easiest to achieve among recommendations that vary by energy level, sex, and/or age. Changes to the index include: (a) the Greens and Beans component replaces Dark Green and Orange Vegetables and Legumes; (b) Seafood and Plant Proteins has been added to capture specific choices from the protein group; (c) Fatty Acids, a ratio of polyunsaturated and monounsaturated to saturated fatty acids, replaces Oils and Saturated Fat to acknowledge the recommendation to replace saturated fat with monounsaturated and polyunsaturated fatty acids; and (d) a moderation component, Refined Grains, replaces the adequacy component, Total Grains, to assess overconsumption. The HEI-2010 captures the key recommendations of the 2010 Dietary Guidelines and, like earlier versions, will be used to assess the diet quality of the US population and subpopulations, evaluate interventions, research dietary patterns, and evaluate various aspects of the food environment. [Copyright &y& Elsevier]