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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.

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.

Background Limited information is available on added sugars consumption in US infants and toddlers. Objectives To present national estimates of added sugars intake among US infants and toddlers by sociodemographic characteristics, to identify top sources of added sugars, and to examine trends in added sugars intake. Design Cross-sectional analysis of 1 day of 24-hour dietary recall data. Participants/setting A nationally representative sample of US infants aged 0 to 11 months and toddlers aged 12 to 23 months (n=1,211) during the period from 2011 through 2016 from the National Health and Nutrition Examination Survey. Trends were assessed from 2005-2006 through 2015-2016 (n=2,795). Main outcome measures Among infants and toddlers, the proportion consuming any added sugars, the average amount of added sugars consumed, percent of total energy from added sugars, and top sources of added sugars intake. Statistical analysis Paired t tests were used to compare differences by age, sex, race/Hispanic origin, family income level, and head of household education level. Trends were tested using orthogonal polynomials. Significance was set at P Results During 2011 to 2016, 84.4% of infants and toddlers consumed added sugars on a given day. A greater proportion of toddlers (98.3%) consumed added sugars than infants (60.6%). The mean amount of added sugars toddlers consumed was also more compared with infants (5.8 vs 0.9 tsp). Non-Hispanic black toddlers (8.2 tsp) consumed more added sugars than non-Hispanic Asian (3.7 tsp), non-Hispanic white (5.3 tsp), and Hispanic (5.9 tsp) toddlers. A similar pattern was observed for percent energy from added sugars. For infants, top sources of added sugars were yogurt, baby food snacks/sweets, and sweet bakery products; top sources among toddlers were fruit drinks, sugars/sweets, and sweet bakery products. The mean amount of added sugars decreased from 2005-2006 through 2015-2016 for both age groups; however, percent energy from added sugars only decreased among infants. Conclusion Added sugars intake was observed among infants/toddlers and varied by age and race and Hispanic origin. Added sugars intake, as a percent of energy, decreased only among infants from 2005 to 2016.

Complementary foods and beverages (CFBs) are key components of an infant's diet in the second 6 months of life. This article summarizes nutrition and feeding practices examined by the 2020 Dietary Guidelines Advisory Committees during the CFB life stage. Breastfeeding initiation is high (84%), but exclusive breastfeeding at 6 months (26%) is below the Healthy People 2030 goal (42%). Most infants (51%) are introduced to CFBs sometime before 6 months. The primary mode of feeding (ie, human milk fed [HMF]; infant formula or mixed formula and human milk fed [FMF]) at the initiation of CFBs is associated with the timing of introduction and types of CFBs reported. FMF infants (42%) are more likely to be introduced to CFBs before 4 months compared with HMF infants (19%). Different dietary patterns, such as higher prevalence of consumption and mean amounts, were observed, including fruit, grains, dairy, proteins, and solid fats. Compared with HMF infants of the same age, FMF infants consume more total energy (845 vs 631 kcal) and protein (22 vs 12 g) from all sources, and more energy (345 vs 204 kcal) and protein (11 vs 6 g) from CFBs alone. HMF infants have a higher prevalence of risk of inadequate intakes of iron (77% vs 7%), zinc (54% vs3%), and protein (27% vs3%). FMF infants are more likely to have an early introduction (12 months) to fruit juice (45% vs 20%) and cow's milk (36% vs 24%). Registered dietitian nutritionists and nutritional professionals should consider tailoring their advice to caregivers on dietary and complementary feeding practices, taking into account the primary mode of milk feeding during this life stage to support infants' nutrient adequacy. National studies that address the limitations of this analysis, including small sample sizes and imputed breast milk volume, could refine findings from this analysis.

BACKGROUND: Standardized methods are needed to investigate intake patterns of processed meat subtypes, considering health concerns surrounding processed meat intake. OBJECTIVES: The objectives of this study were to create a standardized method of disaggregating processed meat into processed red meat and processed poultry and describe intake patterns of the US population aged ≥2 y. METHODS: Two researchers independently manually disaggregated processed meat from the Food Patterns Equivalents Database into processed red meat and processed poultry based on available information from the Foods and Nutrient Database for Dietary Studies. We created an SAS program (called Processed Meat Categories) to mimic the manual coding. We used the program to describe intake patterns and trends over time of processed red meat and processed poultry using 24-h recalls from 2007–2008 through 2017–2018 NHANES data with SAS survey-weighted procedures for complex surveys. RESULTS: The SAS program had high agreement with the manual code (Pearson concordance correlation ≥0.95). Of the US population aged ≥2 y, 46.8% (95% CI: 45.3, 48.2%) reported consuming any processed meat, 42.5% (95% CI: 41.0, 43.9%) reported consuming processed red meat, and 11.3% (95% CI: 10.2, 12.4%) reported consuming processed poultry. Most [74.1 ± 0.13% (SEM)] processed meat reported was red meat compared with poultry, and 32.1 ± 0.01% of total red meat and 13.7 ± 0.01% of total poultry reported were processed. Prevalence of processed poultry intake increased from 9.5% (95% CI: 8.9, 10.1%) in 2007–2010 to 11.3% (95% CI: 10.2, 12.4%) in 2015–2018 (P

OBJECTIVES: The Healthy Eating Index (HEI) is a measure of diet quality, independent of quantity, that can be used to assess alignment with the Dietary Guidelines for Americans (DGAs), which are the basis of nutrition policy for the United States (US) government and the foundation of all federal nutrition guidance. The recently released 2020–2025 DGAs include recommendations for infants and toddlers for the first time, and necessitate a review, update, and development process of the HEI to reflect healthy eating across the lifespan. METHODS: Since 2005, researchers at the HHS National Cancer Institute (NCI) and the USDA Center for Nutrition Policy and Promotion have collaborated to revise the HEI based on updates to the DGAs, and the HEI-2015 is the most recent iteration. The process includes: 1) gathering information from dietary guidelines, experts, and federal stakeholders; 2) considering substantive changes and needs for new development; and 3) completing validation analyses. RESULTS: Updates to the HEI have aimed to maintain stability, reflecting the consistency of recommendations over time. A guiding principle is to only make changes to the HEI that have a strong rationale. With no significant changes in the USDA Dietary Patterns, few changes are anticipated for the HEI for 2 years and older; instead, the emphasis for the update process is focusing on considerations for an index for infants and toddlers under 2 years. Additionally, the Scientific Report of the 2020 Dietary Guidelines Advisory Committee identified the development of a scoring system (such as the HEI) for infants and toddlers as a research recommendation, because comparisons of diet quality using the HEI have thus far only been possible for Americans 2 years and older. The HEI review, update, and development process aims to consider analyses with distributions of HEI scores across the lifespan with nationally representative data and diverse cohorts. CONCLUSIONS: The HEI is a valuable tool for research that can be used in nutrition interventions, epidemiology, and consumer nutrition education programs. The timely release of a new HEI will enable application across the lifespan and support additional methodological research to examine needs specific to each life stage and how to model optimal trajectories of healthy dietary patterns. FUNDING SOURCES: None.

OBJECTIVES: To develop a tool for researchers to augment the ASA24 database and include novel foods, beverages, and supplements for use in their study. METHODS: ASA24 uses nutrient values for foods and beverages from USDA's Food and Nutrient Database for Dietary Studies (FNDDS) and supplement values from the National Health and Nutrition Examination Survey Dietary Supplement Database (NHANES DSD). Novel items, such as medical food products, regional or international foods, and proprietary supplement blends may not be present in FNDDS and NHANES DSD, causing researchers to decide not to use ASA24. The ASA24 software engineering and dietary assessment teams analyzed system components including the hierarchal structured database and software code to determine how researcher-provided data for novel items could be incrementally integrated into the complex, “big data” system. The staff evaluated several approaches and technologies to allow researchers to define specific foods, beverages, and supplements against a set of defined evaluation criteria that addressed usability and technical requirements. RESULTS: The ASA24 new foods tool is an Excel workbook comprised of 19 worksheets. Excel macros validate data and facilitate navigation through the workbook. The worksheets are comprised of instructions, data entry templates, completed data entry templates for example purposes, and reference data. Researchers specify food, beverage, and supplement terms, portion amount probes and associated images, nutrient and Food Pattern Equivalents Database values, allowing the novel item to be added to the ASA24 system, and ultimately available to respondents using ASA24 to report dietary intake. The tool has undergone multiple rounds of usability testing and refinements to address issues. The integration process includes the maintenance of a master copy of foods, beverages, and supplements that will be available to researchers interested in adding these items to their own studies. CONCLUSIONS: The ASA24 new foods tool provides researchers with a cost-effective means to add novel foods, beverages, and supplements to their study. This tool can expand the utility of ASA24 to previously understudied groups. FUNDING SOURCES: This project has been funded in whole or in part by the NIH.

OBJECTIVES: To develop a sleep assessment module in ASA24 to capture self-reported sleep behavior as an optional enhancement to the ASA24 Dietary Assessment Tool for adults. METHODS: Multiple self-reported sleep assessment tools were considered in module development, including the National Sleep Foundation Sleep Diary, the Activities Completed over Time in 24-hours (ACT24), Munich Chronotype Questionnaire (MCTQ), and the Consensus Sleep Diary (CSD) Core. Priority was given to minimal need for adaptation, questionnaire length to reduce survey fatigue, incorporating plain language, and optimizing for implementation in 24 hour recalls (24HR) and food records. Researchers with expertise in meal timing and sleep were consulted for feedback on content and utility and programmers with expertise in survey design were consulted on implementation. Lastly, the online data collection process and ASA24 System's output data files were tested for accuracy. RESULTS: The ASA24 sleep module contains ten questions and can be administered immediately following dietary assessment. Eight CSD Core questions were adapted to assess time in bed, time trying to go to sleep, and length of time to fall asleep; number and duration of nocturnal awakenings; wake time and time out of bed for the day; and perceived sleep quality. Two questions were added to capture sleep quality and comparability of reported sleep to a usual night's sleep. For users completing a 24HR, the module includes two questions on time of awakening and sleep quality immediately preceding the first reported meal; all 10 sleep questions are asked for the sleep period immediately following the last meal (i.e., 12 questions total), allowing for assessment of the impact of diet on sleep. In contrast, a food record is completed on the same day users consume the food, and thus all sleep questions address the sleep window prior to the first meal; a single record can be used to assess the impact of sleep on diet. Consecutive days of records can also be collected to capture sleep pre- and post-eating windows. CONCLUSIONS: The ASA24 sleep module can assess sleep timing and quality and will be available in Fall 2021. Researchers can soon leverage this novel resource to examine the association of sleep with timing of eating and other chrononutrition variables. FUNDING SOURCES: This project has been funded by the NIH.

Background & Aims Public interest in pre-, pro-, and synbiotic products is increasing because of interactions between gut microbiota and human health. Our aim was to describe nonfood (from dietary supplements or medication) pre-, pro-, and synbiotic use by US adults and children and reported reasons. Methods Using data from the National Health and Nutrition Examination Survey (NHANES), we text-mined dietary supplement and prescription medication labels and ingredients to identify pre-, pro-, and synbiotic products used in the past 30 days. We describe trends in use from 1999 to 2018 (n = 101,199) and prevalence in 2015–2016 and 2017–2018 (n = 19,215) by age groups, sex, ethnicity/race, education, income, self-reported diet and health quality, and prescription gastrointestinal medication use stratified by children ( Results Nonfood pre-, pro-, and synbiotic use increased up to 3-fold in recent cycles. Prevalence of use for all ages for prebiotics was 2.4% (95% confidence interval [CI], 2.0–2.9), for probiotics was 4.5% (95% CI, 3.5–5.6), and for synbiotics was 1.1% (95% CI, 0.8–1.5). Use was highest among older adults (8.8% [95% CI, 5.4–13.3] among those aged 60–69 years for probiotics), non-Hispanic Whites, those with higher educational attainment and income, those with more favorable self-reported diet or health quality, and those with concurrent prescription gastrointestinal medication use. The top reasons for use were for digestive health and to promote/maintain general health. Less than 30% reported using these products based on a health care provider's recommendation. Conclusions One in 20 US adults or children use nonfood pre-, pro-, or synbiotic products, and use has sharply increased in recent years. Most individuals voluntarily take these products for general digestive or overall health reasons.

OBJECTIVES: Providing nutrition feedback and advice to research participants based on reported dietary intake is feasible, but has not traditionally been undertaken in all settings. However, it is unclear how such feedback is received and understood by participants or the general public absent the guidance of a clinician or professional. We conducted usability testing to assess understanding of a report with personalized nutrition information to respondents who provided dietary data via the National Cancer Institute's Automated Self-Administered 24-hour (ASA24) Dietary Assessment tool. METHODS: Two rounds of usability testing (6 participants per round) were conducted in a laboratory equipped with an eye tracker, as well as audio and computer recording. Participants were recruited from the general population and represented a range of race/ethnicities, education levels, and ages. Trained moderators asked participants to freely explore a newly designed Respondent Nutrition Report (RNR) and then guided them through a series of questions designed to elicit information about whether nutrition information was understood and gather feedback on areas of confusion or misunderstanding. In addition to verbal feedback, participant interaction with the RNR was captured via gaze plots and heat maps. RESULTS: Participants requested additional informational text during round 1 of testing, and read text explanations when present in round 2. Participants preferred a narrow vs. wide design such that it would display easily on mobile devices. They focused on numbers enclosed by graphics and lingered on terminology that was unfamiliar or confusing. When large amounts of information were presented in graphs, attention was focused on the first few items presented but then decreased towards the end of rows and the bottom of the page. Highlighted text was not always attended to by participants. Verbal results indicated that choice of words for labels and explanatory text was critical and that participants desired links to more detailed external information when possible. CONCLUSIONS: It is possible to design a personalized nutrition feedback report that is well understood by participants. Care should be taken with wording choices, extraneous information should be limited, and testing within the target population is advisable. FUNDING SOURCES: None.

OBJECTIVES: To compare five Healthy Eating Index-2015 (HEI-2015) scoring methods using 24-hour recalls (24HRs), 4-day food records (4DFRs), and food frequency questionnaires (FFQs). METHODS: Over 12 months, Interactive Diet and Activity Tracking in AARP (IDATA) study participants (N = 1021) aged 50–74 years completed up to six Automated Self-Administered 24-Hour Dietary Assessment Tool (ASA24) recalls, 2 4DFRs, and 2 FFQs. Mean HEI-2015 total and component scores were estimated using five methods – two estimating usual intake: the multivariate Markov Chain Monte Carlo (MCMC) and bivariate; and three not estimating usual intake: per day, per person, and population ratio. Sums of squared differences (SSD) were calculated to compare differences among component scores. RESULTS: MCMC and bivariate methods estimated similar total mean HEI-2015 scores for men with 24HRs (60 points) and 4DFRs (61 points). The population ratio scores were comparable (63 points), but higher, and the per day was most different for both 24HRs and 4DFRs (57 points). This pattern was similar for women. With 24HR and 4DFRs, the population ratio method had higher component scores compared with MCMC and bivariate for Total Fruits, Whole Fruits, and Seafood and Plant Proteins. For example, among men, in 24HRs (comparing MCMC and population ratio), the SSD for Whole Fruit were 1.44 and those of Seafood and Plant Proteins were 0.49, compared to SSDs for other components which only ranged from 0.01 to 0.16. With FFQs, estimation of mean HEI scores is not recommended due to biases. However, when applying all methods, the total and component scores for FFQs were higher for Total Fruits, Whole Fruits, Greens and Beans, Dairy, Fatty Acids, Refined Grains, Sodium, and Saturated Fats. CONCLUSIONS: Overall, the two usual intake methods (MCMC and bivariate) yield comparable total and component scores. The population ratio method adjusts for day-to-day variation by averaging data across populations, thus arrives at scores closer to the MCMC and bivariate, hence is the preferred method of estimating a population's mean usual HEI scores on the basis of a single day of data. When distributions are needed, the MCMC and bivariate methods are recommended to adjust for measurement error, consider episodic consumption and skewness, and account for correlation between each and or all constituents and energy. FUNDING SOURCES: N/A.

Objective To describe the history, key features, recent enhancements, and common applications of the Dietary Supplement Label Database (DSLD). Background and history Although many Americans use dietary supplements, databases of dietary supplements sold in the United States have not been widely available. The DSLD, an easily accessible public-use database was created in 2008 to provide information on dietary supplement composition for use by researchers and consumers. Rationale Accessing current information easily and quickly is crucial for documenting exposures to dietary supplements because they contain nutrients and other bioactive ingredients that may have beneficial or adverse effects on human health. This manuscript details recent developments with the DSLD to achieve this goal and provides examples of how the DSLD has been used. Recent developments With periodic updates to track changes in product composition and capture new products entering the market, the DSLD currently contains more than 71,000 dietary supplement labels. Following usability testing with consumer and researcher user groups completed in 2016, improvements to the DSLD interface were made. As of 2017, both a desktop and mobile device version are now available. Since its inception in 2008, the use of the DSLD has included research, exposure monitoring, and other purposes by users in the public and private sectors. Future directions Further refinement of the user interface and search features to facilitate ease of use for stakeholders is planned. Conclusions The DSLD can be used to track changes in product composition and capture new products entering the market. With over 71,000 DS labels it is a unique resource that policymakers, researchers, clinicians, and consumers may find valuable for multiple applications.

Objective This review summarizes the current and previous data on dietary supplement (DS) use collected from participants in the National Health and Nutrition Examination Survey (NHANES), describes the NHANES dietary supplement database used to compute nutrient intakes from DSs, discussed recent developments and future direction, and describes many examples to demonstrate the utility of these data in informing nutrition research and policy. Background and history Since 1971, NHANES, has been collecting information on the use of DSs from participants. These data are critical to national nutrition surveillance and have been used to characterize usage patterns, examine trends over time, assess the percentage of the population meeting or exceeding nutrient recommendations, and to help elucidate the sources contributing nutrients to the diet of the US population. Rationale Over half of adults and about one-third of children in the United States use at least one dietary supplement in the past 30 days. Dietary supplements contribute to the dietary intake of nutrients and bioactive compounds in the US and therefore need to be assessed when monitoring nutritional status of the population and when studying diet-health associations. Recent developments With the recent development and availability of the Dietary Supplement Label Database (DSLD), a comprehensive DS database that will eventually contain labels for all products marketed in the US, NHANES DS data will be more easily linked to product information to estimate nutrient intake from DS. Future directions Over time, NHANES has both expanded and improved collection methods. The continued understanding of sources of error in collection methods will continue to be explored and is critical to improved accuracy. Conclusions NHANES provides a rich source of nationally representative data on the usage of dietary supplements in the US.

The childhood obesity rate has been steadily rising among US youths during the past 2 decades. Increasing evidence links consumption of ultraprocessed foods to excessive calorie consumption and weight gain, but trends in the consumption of ultraprocessed foods among US youths have not been well characterized.To characterize trends in the consumption of ultraprocessed foods among US youths.Serial cross-sectional analysis using 24-hour dietary recall data from a nationally representative sample of US youths aged 2-19 years (n = 33 795) from 10 cycles of the National Health and Nutrition Examination Survey (NHANES) from 1999-2000 to 2017-2018.Secular time.Percentage of total energy consumed from ultraprocessed foods as defined by NOVA, an established food classification system that categorizes food according to the degree of food processing.Dietary intake from youths were analyzed (weighted mean age, 10.7 years; 49.1% were girls). From 1999 to 2018, the estimated percentage of total energy from consumption of ultraprocessed foods increased from 61.4% to 67.0% (difference, 5.6% [95% CI, 3.5% to 7.7%]; P .001 for trend), whereas the percentage of total energy from consumption of unprocessed or minimally processed foods decreased from 28.8% to 23.5% (difference, -5.3% [95% CI, -7.5% to -3.2%]; P .001 for trend). Among the subgroups of ultraprocessed foods, the estimated percentage of energy from consumption of ready-to-heat and -eat mixed dishes increased from 2.2% to 11.2% (difference, 8.9% [95% CI, 7.7% to 10.2%]) and from consumption of sweet snacks and sweets increased from 10.7% to 12.9% (difference, 2.3% [95% CI, 1.0% to 3.6%]), but the estimated percentage of energy decreased for sugar-sweetened beverages from 10.8% to 5.3% (difference, -5.5% [95% CI, -6.5% to -4.5%]) and for processed fats and oils, condiments, and sauces from 7.1% to 4.0% (difference, -3.1% [95% CI, -3.7% to -2.6%]) (all P .05 for trend). There was a significantly larger increase in the estimated percentage of energy from consumption of ultraprocessed foods among non-Hispanic Black youths (from 62.2% to 72.5%; difference, 10.3% [95% CI, 6.8% to 13.8%]) and Mexican American youths (from 55.8% to 63.5%; difference, 7.6% [95% CI, 4.4% to 10.9%]) than the increase among non-Hispanic White youths (from 63.4% to 68.6%; difference, 5.2% [95% CI, 2.1% to 8.3%]) (P = .04 for trends).Based on the NHANES cycles from 1999 to 2018, the estimated proportion of energy intake from consumption of ultraprocessed foods has increased among youths in the US and has consistently comprised the majority of their total energy intake.

Diet quality in the United States is improving over time but remains poor. Food outlets influence diet quality and represent the environments in which individuals make choices about food purchases and intake. The objective of this study was to use the Healthy Eating Index-2015 (HEI-2015) to evaluate the quality of foods consumed from the four major outlets where food is obtained—stores, full-service restaurants, quick-services restaurants, and schools—and to assess changes over time. This cross-sectional study used 24 h dietary recall data from eight cycles (2003–2004 to 2017–2018) of the National Health and Nutrition Examination Survey (NHANES). Linear trend estimation was used to test for changes in HEI scores over time, and balanced repeated replicate weighted linear regression was used to test for differences in total and component scores between types of food outlets. Overall, Americans are not consuming a mix of foods from any major category of food outlet that aligns with dietary guidelines. The total score for schools (65/100 points) and stores (62/100 points) was significantly higher than full-service (51/100 points) and quick-service (39/100 points) restaurants (p &lt, 0.0001). HEI scores significantly improved over time for schools (p &lt, 0.001), including an increase in whole grains from less than 1 point in 2003–2004 to 7 out of 10 points in 2017–2018. In 2017–2018, schools received the maximum score for total fruits, whole fruits, and dairy. Continued research on strategies for improving the quality of foods consumed from restaurants and stores is warranted.

OBJECTIVES: To describe differences in dietary intake of select foods and nutrients by level of urbanization in U.S. youth ages 2–19 years. METHODS: Data from 8301 youth in the National Health and Nutrition Examination Survey, 2013–2018 were used. Mean ratios were estimated for % of fruit consumed as whole fruit (WF) and grains as whole grains (WG), % of energy from added sugars (AS) and saturated fats (SF), and mean intake of fiber, potassium, and sodium on a given day. Proportions consuming >50% (fruit as WF and grains as WG), 50% of fruit as WF increased significantly from 43.7% in non-MSAs to 51.0% in large MSAs, and a significant increase was seen among males. The % of energy from AS decreased significantly from 15.5% in non-MSAs to 13.2% in large MSAs, and significant declines were also seen among males and among lower income youth, and the percentage of males who consumed 50% of fruit as WF

OBJECTIVES: Limitations in dietary assessment methodology lead to broad and inconsistent red meat intake categories. For example, red meat is often combined with processed meat, which includes processed poultry. Our objective was to quantitatively assess how these limitations influence red meat intake estimates of the U.S. population. METHODS: Three distinct red meat categories were identified from a series of systematic literature reviews. By systematically disaggregating and reaggregating meat variables (lean meat oz-eq) from the USDA's Food Pattern Equivalents Database, the following categories were created: 1) ‘unprocessed red meat’, 2) ‘total red meat’ [unprocessed red meat + processed red meat], and 3) ‘mixed red and processed meat’ [unprocessed red meat + total processed meat which includes processed poultry]. The 2015–16 and 2017–18 cycles of NHANES (n = 15,039) were combined to estimate and compare mean intakes across these three categories as well as the proportion of the population that exceeded age- and sex-specific red meat allotments in the Dietary Guidelines for Americans recommended eating patterns for those aged 2 + years. The two-part correlated model of the NCI Usual Intake method in SAS was used. Estimates were adjusted for age, sex, race, and ethnicity and pairwise comparisons were made across categories; P

Approximately 24% of U.S. adolescents attempted to lose weight during 2009-2010, and studies show that girls are more likely than boys to attempt weight loss (1,2). Adolescents are known to use multiple weight loss and weight control practices (3). This report describes the percentage of U.S. adolescents who tried to lose weight in the past year from 2013 through 2016 by sex, race and Hispanic origin, and weight status. Methods of intentional weight loss are also reported.

Total grains intake comes from whole grains and refined grains. Whole grains contain the entire grain kernel (bran, germ, and endosperm) (1). A higher intake of whole grains is linked with a lower risk of cardiovascular disease, cancer, and mortality (2). The "2015-2020 Dietary Guidelines for Americans" recommend that at least one-half of total grains intake be from whole grains (3). This report provides estimates of the percentage of total grains intake consumed from whole grains sources, for adults aged 20 and over who reported consumption of grains (98.6%) on a given day during 2013-2016.

BACKGROUND: Vitamin D is important for bone health; in 2014 it was the fifth most commonly ordered laboratory test among Medicare Part B payments. OBJECTIVES: The aim of this study was to describe vitamin D status in the US population in 2011–2014 and trends from 2003 to 2014. METHODS: We used serum 25-hydroxyvitamin D data from NHANES 2011–2014 (n = 16,180), and estimated the prevalence at risk of deficiency (

Background: To our knowledge, few studies have described the usual nutrient intakes of US children aged

OBJECTIVES: Cured animal protein foods are not often differentiated by animal source in dietary data, e.g., cured poultry is commonly grouped with cured red meat. Using the USDA's Food Patterns Equivalents Database (FPED), our objective was to disaggregate the ‘cured meat’ FPED variable into cured red meat (CRM) and cured poultry (CP) to describe mean intakes in the U.S. population. METHODS: Two researchers independently manually disaggregated the ‘cured meat’ FPED variable into CRM or CP based on food code description, ingredients, and What We Eat in America category. We then developed a SAS program to mimic the manual coding. We estimated consumption prevalence and mean intake of CRM and CP using 1-day dietary recalls for individuals aged 2+ years in NHANES 2011–2016 (n = 23,917). Additionally, we assessed differences by age, sex, self-identified Hispanic origin and race, education, and income (Tukey adjusted P

OBJECTIVES: To identify top dietary sources of energy, empty calories, added sugars, and solid fats among 2–18 year old children and adolescents in the U.S. and describe trends. METHODS: Day 1 24-hour dietary recalls from the NHANES Survey were categorized according to the What We Eat in America Food categories and used to examine food sources (percentage contribution and mean intake) of total energy and energy from added sugars and solid fats (collectively, empty calories). Trends over time between 2007–2016 were examined in 2–18-year-olds. Significance was set at P 25% of total energy intake came from empty calories: 2–3-year-olds (26.1%–30.0%), 4–8-year-olds (30.0%–33.6%), 9–13-year-olds (30.2%–34.4%), and 14–18-year-olds (30.5%–35.5%). Over time the top sources of energy and empty calories did not vary greatly within each age group, but with increasing age, there was a shift from beverages to solid foods, and in types of beverages. For example, of the top five energy sources among 2–3 year-olds, four were beverages (flavored milk, 3.9–5.7%; whole milk, 3.4–5.4%; reduced fat milk, 4.2–5.3%, and fruit drinks, 2.9–3.1%), among 4–8 year-olds, two were beverages (flavored milk, 3.2–4.7% and fruit drinks, 3.1–3.3%), and among 9–13 year-olds and 14–18 year-olds, mainly soft drinks (3.4–4.7% and 4.1–6.3%, respectively), and in some years, fruit drinks (2.7% and 2.9%, respectively). CONCLUSIONS: There is an overlap in top sources of energy and empty calories: flavored milk, fruit drinks, whole milk, reduced fat milk, soft drinks, pizza, cookies and brownies, and other sandwiches. Continued research on how the sources of empty calories transition from early childhood into adolescence can inform how to modify the food landscape to include fewer empty calorie foods and potentially address excess energy intake. FUNDING SOURCES: N/A.

The 2015-2020 Dietary Guidelines for Americans (1) recommend consuming two servings of seafood, including fish and shellfish, per week. Consuming approximately 8 ounces of a variety of seafood weekly is associated with reduced cardiac deaths (2). This report describes the percentage of U.S. adults and youth who reported consuming seafood at least two times per week by sex, age, and race and Hispanic origin during 2013-2016. Trends in the percentage of adults and youth who consumed seafood at least twice weekly, from 2005-2006 through 2015-2016, are also presented.

Fast food is a part of the American diet and has been associated with high caloric intake (1), and poor diet quality (2). Time, financial resources, price, and availability influence fast food consumption (3). This report presents data on the percentage of adults who consumed fast food on a given day in the United States during 2013-2016.

BACKGROUND: Limited nationally representative data are available on dietary supplement (DS) use and resulting nutrient exposures among infants and toddlers. OBJECTIVE: This study evaluated DS use among US infants and toddlers to characterize DS use, estimate nutrient intake from DSs, and assess trends in DS use over time. METHODS: Using nationally representative data from NHANES (2007–2014) and trends over time (1999–2014), we estimated prevalence of DS use and types of products used for US infants and toddlers aged

Almost 40% of adults in the United States had obesity in 2015-2016 (1). Obesity is associated with a range of serious health risks (2). Individuals may have multiple motivations for trying to losing weight, including health and appearance reasons (3). This report describes the percentage of U.S. adults who tried to lose weight in the past year by sex, age, race and Hispanic origin, family income, and weight status, based on data collected in the National Health and Nutrition Examination Survey (NHANES) from 2013 -2016.

ObjectiveDifferences in bottled v. tap water intake may provide insights into health disparities, like risk of dental caries and inadequate hydration. We examined differences in plain, tap and bottled water consumption among US adults by sociodemographic characteristics.DesignCross-sectional analysis. We used 24 h dietary recall data to test differences in percentage consuming the water sources and mean intake between groups using Wald tests and multiple logistic and linear regression models.SettingNational Health and Nutrition Examination Survey (NHANES), 2007–2014.SubjectsA nationally representative sample of 20 676 adults aged ≥20 years.ResultsIn 2011–2014, 81·4 (se 0·6) % of adults drank plain water (sum of tap and bottled), 55·2 (se 1·4) % drank tap water and 33·4 (se 1·4) % drank bottled water on a given day. Adjusting for covariates, non-Hispanic (NH) Black and Hispanic adults had 0·44 (95 % CI 0·37, 0·53) and 0·55 (95 % CI 0·45, 0·66) times the odds of consuming tap water, and consumed B=−330 (se 45) ml and B=−180 (se 45) ml less tap water than NH White adults, respectively. NH Black, Hispanic and adults born outside the fifty US states or Washington, DC had 2·20 (95 % CI 1·79, 2·69), 2·37 (95 % CI 1·91, 2·94) and 1·46 (95 % CI 1·19, 1·79) times the odds of consuming bottled water than their NH White and US-born counterparts. In 2007–2010, water filtration was associated with higher odds of drinking plain and tap water.ConclusionsWhile most US adults consumed plain water, the source (i.e. tap or bottled) and amount differed by race/Hispanic origin, nativity status and education. Water filters may increase tap water consumption.

We examined consumption of different types of infant formula (eg, cow’s milk, soy, gentle/lactose-reduced, and specialty) and regular milk among a nationally representative sample of 1864 infants, 0 to 12 months old, from the National Health and Nutrition Examination Survey, 2003-2010. Among the 81% of infants who were fed formula or regular milk, 69% consumed cow’s milk formula, 12% consumed soy formula, 5% consumed gentle/ lactose-reduced formulas, 6% consumed specialty formulas, and 13% consumed regular milk products. There were differences by household education and income in the percentage of infants consuming cow’s milk formula and regular milk products. The majority of infants in the United States who were fed formula or regular milk consumed cow’s milk formula (69%), with lower percentages receiving soy, specialty, gentle/sensitive, or lactose-free/reduced formulas. Contrary to national recommendations, 13% of infants younger than 1 year consumed regular milk, and the percentage varied by household education and income levels.

BACKGROUND: In light of increasing concern of potential adverse effects of caffeine intake in children, recent estimates of caffeine consumption among a representative sample of young children are needed. OBJECTIVE: To provide estimates of caffeine intake in children, in absolute amount (mg) and in relation to body weight (mg/kg), examine the association of caffeine consumption with socio-demographic factors, and describe trends in caffeine intake among children in the United States. DESIGN: We analyzed caffeine intake among 3280 children aged 2–19 y who participated in a 24-h dietary recall as part of NHANES, a nationally representative sample of the US population with a cross-sectional design, in 2009–2010. The association of caffeine consumption with socio-demographic factors was also determined. Trends over time were examined in 18,530 children aged 2–19 y, between 2001 and 2010. Analyses were conducted for all children, and repeated for caffeine consumers. RESULTS: Seventy one percent of US children consumed caffeine on a given day. Median caffeine intakes (mg) for 2–5, 6–11, and 12–19 y olds were 1.3, 4.5, and 13.6, respectively; and 4.7, 9.1 and 40.6, respectively among children who consumed caffeine. Non-Hispanic black children had lower caffeine intake compared to non-Hispanic white counterparts. Caffeine intake correlated positively with age; this association was independent of body weight. On a given day, 10% and

The period from birth to 24 mo (B-24) is a critical phase in which nutrient requirements for growth and development are high and several transitions in food consumption practices occur. A few large-scale national studies (eg, the Feeding Infants and Toddlers Study and Infant Feeding Practices Study) offer important insights into infant feeding practices and food consumption patterns in young children in the United States. The NHANES collects comprehensive cross-sectional data on the nutrition and health of Americans including infants and toddlers. This article describes the NHANES program and data from NHANES 1999–2010 on young children that are relevant for the B-24 Project. NHANES is a nationally representative survey of the noninstitutionalized US population that combines personal interviews with standardized physical examination and measurements via mobile examination centers. Data on infant feeding practices (breastfeeding and timing of introduction and nature of complementary foods), dietary intake (two 24-h recalls), and nutrient supplements are collected. Data on demographic characteristics, anthropometric measurements, biomarkers of nutrient status, food security, and participation in federal nutrition programs are also available. Data can be accessed online, downloaded, and pooled over several survey cycles, allowing examination of infant feeding practices, food and nutrient intakes, and nutritional status of Americans

OBJECTIVES: Rural populations are generally older, sicker, and poorer than their urban counterparts. Few studies have examined differences in dietary patterns by urbanization that may mirror differences in health by urbanization. Our objective is provide national estimates of dietary patterns among adults by urbanization level. METHODS: Using a single 24 hour recall from NHANES 2013–2016, we estimated the mean consumption of fruits, vegetables, % of calories from added sugars and % of calories from saturated fats, by age, sex, education, race and Hispanic origin, and urbanization level among US adults aged 20 and over (n = 9939). We used SUDAAN to conduct all analyses and we evaluated differences between groups using a t statistic and tests of trend across ordinal variables using orthogonal contrast matrices. RESULTS: During 2013–2016, the average fruit intake (cup equivalence) was 0.9 (SE 0.03) for both men and women. After adjustment by age, education level, and race and Hispanic origin, fruit intake increased with higher level of urbanization, from 0.6 (SE 0.07) in rural areas, to 0.9 (SE 0.05) in medium or small urban areas, to 1.0 (SE 0.04) in large urban areas among men. After adjustment, differences by urbanization were not significant for women. The average % of calories from added sugars on a given day was 12% (SE 0.2) for both men and women. After adjustment, added sugars intake decreased with higher level of urbanization, from 14.0% (SE 0.9) in rural areas, to 12.6% (SE 0.3) in medium to small urban areas, to 12.0% (SE 0.2) in large urban areas among women. A similar pattern was also observed among men. There were no differences in vegetable consumption or % of energy from saturated fat by level of urbanization. CONCLUSIONS: Disparities in dietary patterns exist by urbanization. Additional research may show how these differences impact health and identify opportunities to improve health in rural communities. FUNDING SOURCES: The National Center for Health Statistics and the US Centers for Disease Control and Prevention funded this study.

In the United States, the American Thyroid Association recommends that women take a dietary supplement containing 150 µg of iodine 3 months prior to conception and while pregnant and lactating to support fetal growth and neurological development. We used data from the National Health and Nutrition Examination Survey 2011–2014 to describe the use of dietary supplements with and without iodine in the past 30 days among 2155 non-pregnant, non-lactating (NPNL) women; 122 pregnant women; and 61 lactating women. Among NPNL women, 45.3% (95% Confidence Interval [CI]: 42.0, 48.6) used any dietary supplement and 14.8% (95% CI: 12.7, 16.8) used a dietary supplement with iodine in the past 30 days. Non-Hispanic black and Hispanic women were less likely to use any dietary supplement as well as one with iodine, than non-Hispanic white or non-Hispanic Asian women (p < 0.05). Among pregnant women, 72.2% (95% CI: 65.8, 78.6) used any dietary supplement; however, only 17.8% (95% CI: 11.4, 24.3) used a dietary supplement with iodine. Among lactating women, 75.0% (95% CI: 63.0, 87.0) used a dietary supplement; however, only 19.0% (95% CI: 8.8, 29.2) used a dietary supplement with iodine. Among NPNL women using a supplement with iodine, median daily iodine intake was 75.0 µg. Self-reported data suggests that the use of iodine containing dietary supplements among pregnant and lactating women remains low in contrast with current recommendations.