Can sodium and potassium measured in timed voids be used as reference instruments for validating self-report instruments? Results from a urine calibration study.

BACKGROUND: Sodium and potassium measured in 24-h urine collections are often used as reference measurements to validate self-reported dietary intake instruments. OBJECTIVES: To evaluate whether collection and analysis of a limited number of urine voids at specified times during the day ("timed voids") can provide alternative reference measurements, and to identify their optimal number and timing. METHODS: We used data from a urine calibration study among 441 adults aged 18-39 y. Participants collected each urine void in a separate container for 24 h and recorded the collection time. For the same day, they reported dietary intake using a 24-h recall. Urinary sodium and potassium were analyzed in a 24-h composite sample and in 4 timed voids (morning, afternoon, evening, and overnight). Linear regression models were used to develop equations predicting log-transformed 24-h urinary sodium or potassium levels using each of the 4 single timed voids, 6 pairs, and 4 triples. The equations also included age, sex, race, BMI (kg/m2), and log creatinine. Optimal combinations minimizing the mean squared prediction error were selected, and the observed and predicted 24-h levels were then used as reference measures to estimate the group bias and attenuation factors of the 24-h dietary recall. These estimates were compared. RESULTS: Optimal combinations found were as follows: single voids-evening; paired voids-afternoon + overnight (sodium) and morning + evening (potassium); and triple voids-morning + evening + overnight (sodium) and morning + afternoon + evening (potassium). Predicted 24-h urinary levels estimated 24-h recall group biases and attenuation factors without apparent bias, but with less precision than observed 24-h urinary levels. To recover lost precision, it was estimated that sample sizes need to be increased by ∼2.6-2.7 times for a single void, 1.7-2.1 times for paired voids, and 1.5-1.6 times for triple voids. CONCLUSIONS: Our results provide the basis for further development of new reference biomarkers based on timed voids. CLINICAL TRIAL REGISTRY: clinicaltrials.gov as NCT01631240.

Validation of Total Water Intake from the Automated Self-Administered 24-h Recall, 4-d Food Records, and a Food Frequency Questionnaire Using Doubly Labeled Water.

BACKGROUND: Although prior evidence indicates that water intake is important for health, the ability to accurately measure community-dwelling intake is limited. Only a few studies have evaluated self-reported water intake against an objective recovery biomarker. OBJECTIVES: The aim was to compare preformed water intakes (all sources including food) by multiple Automated Self-Administered 24-h recalls (ASA24s), food frequency questionnaires (FFQs), and 4-d food records (4DFRs) against a recovery biomarker, doubly labeled water (DLW), to assess measurement error. METHODS: Over 1 y, 1082 women and men (50%), aged 50 to 74 y, were asked to complete 6 ASA24s, 2 FFQs, 2 unweighted 4DFRs, and an administration of DLW (n = 686). Geometric means of water intake by self-report tools were compared with DLW. Attenuation factors and correlation coefficients between self-reported and the recovery biomarker (DLW) were estimated. RESULTS: Mean water intakes by DLW were 2777 mL/d (interquartile range, 2350 to 3331) in women and 3243 mL/d (interquartile range, 2720 to 3838) in men. Compared with DLW, water intake was underestimated by 18% to 31% on ASA24s and 43% to 44% on 4DFRs. Estimated geometric means from FFQs differed from DLW by -1% to +13%. For a single ASA24, FFQ, and 4DFR, attenuation factors were 0.28, 0.27, and 0.32 and correlation coefficients were 0.46, 0.48, and 0.49, respectively. Repeated use of 6 ASA24s, 2 FFQs, and 2 4DFRs improved attenuation factors to 0.43, 0.32, and 0.39 and correlation coefficients to 0.58, 0.53, and 0.54, respectively. CONCLUSIONS: FFQs may better estimate population means for usual water intake compared with ASA24 and 4DFR. Similar attenuation factors and correlation coefficients across all self-report tools indicate that researchers have 3 feasible options if the goal is understanding intake-disease relationships. The findings are useful for planning future nutrition studies that set policy priorities for populations and to understand the health impact of water. This trial was registered at clinicaltrials.gov as NCT03268577.

The Canadian Food Intake Screener for assessing alignment of adults' dietary intake with the 2019 Canada's Food Guide healthy food choices recommendations: scoring system and construct validity.

NOVELTY: 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.

Development of the Canadian Food Intake Screener to assess alignment of adults' dietary intake with the 2019 Canada's Food Guide healthy food choices recommendations.

NOVELTY: 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.

Prevalence and Severity of Food Insecurity Before and During the Coronavirus Disease 2019 Pandemic Among Adults and Youth in Australia, Canada, Chile, Mexico, the United Kingdom, and the United States.

BACKGROUND: Disruptions from the coronavirus disease 2019 (COVID-19) pandemic potentially exacerbated food insecurity among adults and youth. OBJECTIVES: The objective was to examine changes in the prevalence and severity of food insecurity among adults and youth from before (2019) to during (2020) the pandemic in multiple countries. METHODS: Repeated cross-sectional data were collected among adults aged 18-100 y (n = 63,278) in 5 countries in November to December in 2018-2020 and among youth aged 10-17 y (n = 23,107) in 6 countries in November to December in 2019 and 2020. Food insecurity in the past year was captured using the Household Food Security Survey Module and the Child Food Insecurity Experiences Scale. Changes in the prevalence and severity of food insecurity were examined using logistic and generalized logit regression models, respectively. Models included age, gender, racial-ethnic identity, and other sociodemographic characteristics associated with food insecurity to adjust for possible sample differences across waves. Models were weighted to reflect each country's population. RESULTS: Adults [adjusted OR (AOR): 1.15; 95% CI: 1.02, 1.31] and youth (AOR: 1.43; 95% CI: 1.19, 1.71) in Mexico were more likely to live in food-insecure households in 2020 compared to 2019. Adults in Australia (AOR: 0.81; 95% CI: 0.72, 0.92) and Canada (AOR: 0.87; 95% CI: 0.77, 0.99) were less likely to live in food-insecure households in 2020. Trends in severity aligned with changes in prevalence, with some exceptions. Youth in Australia (AOR: 2.24; 95% CI: 1.65, 3.02) and the United States (AOR: 1.39; 95% CI: 1.04, 1.86) were more likely to have many compared with no experiences of food insecurity in 2020 compared to 2019. There was no evidence of change among adults and youth in the remaining countries. CONCLUSIONS: Except for Mexico, few changes in food insecurity among adults and youth were observed from before to during the COVID-19 pandemic. Action is needed to support households at risk of food insecurity.

A narrative review of nutrient based indexes to assess diet quality and the proposed total nutrient index that reflects total dietary exposures.

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.

The Accuracy of Portion Size Reporting on Self-Administered Online 24-Hour Dietary Recalls Among Women With Low Incomes.

BACKGROUND: Accurately estimating portion sizes remains a challenge in dietary assessment. Digital images used in online 24-hour dietary recalls may be conducive to accuracy. OBJECTIVE: 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. DESIGN: 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/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. MAIN OUTCOME MEASURES: 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. STATISTICAL ANALYSES PERFORMED: 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. RESULTS: 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. CONCLUSIONS: 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.

Using Short-Term Dietary Intake Data to Address Research Questions Related to Usual Dietary Intake among Populations and Subpopulations: Assumptions, Statistical Techniques, and Considerations.

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.

Measurement Error Affecting Web- and Paper-Based Dietary Assessment Instruments: Insights From the Multi-Cohort Eating and Activity Study for Understanding Reporting Error.

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.

The Total Nutrient Index is a Useful Measure for Assessing Total Micronutrient Exposures Among US Adults.

BACKGROUND: Most dietary indices reflect foods and beverages and do not include exposures from dietary supplements (DS) that provide substantial amounts of micronutrients. A nutrient-based approach that captures total intake inclusive of DS can strengthen exposure assessment. OBJECTIVES: We examined the construct and criterion validity of the Total Nutrient Index (TNI) among US adults (≥19 years; nonpregnant or lactating). METHODS: The TNI includes 8 underconsumed micronutrients identified by the Dietary Guidelines for Americans: calcium; magnesium; potassium; choline; and vitamins A, C, D, and E. The TNI is expressed as a percentage of the RDA or Adequate Intake to compute micronutrient component scores; the mean of the component scores yields the TNI score, ranging from 0-100. Data from exemplary menus and the 2003-2006 (≥19 years; n = 8861) and 2011-2014 NHANES (≥19 years; n = 9954) were employed. Exemplary menus were used to determine whether the TNI yielded high scores from dietary sources (women, 31-50 years; men ≥ 70 years). TNI scores were correlated with Healthy Eating Index (HEI) 2015 overall and component scores for dairy, fruits, and vegetables; TNI component scores for vitamins A, C, D, and E were correlated with respective biomarker data. TNI scores were compared between groups with known differences in nutrient intake based on the literature. RESULTS: The TNI yielded high scores on exemplary menus (84.8-93.3/100) and was moderately correlated (r = 0.48) with the HEI-2015. Mean TNI scores were significantly different for DS users (83.5) compared with nonusers (67.1); nonsmokers (76.8) compared with smokers (70.3); and those living with food security (76.6) compared with food insecurity (69.1). Correlations of TNI vitamin component scores with available biomarkers ranged from 0.12 (α-tocopherol) to 0.36 (serum 25-hydroxyvitamin D), and were significantly higher than correlations obtained from the diet alone. CONCLUSIONS: The evaluation of validity supports that the TNI is a useful construct to assess total micronutrient exposures of underconsumed micronutrients among US adults.

Advanced Dietary Analysis and Modeling: A Deep Dive into the National Cancer Institute Method.

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-h dietary recalls (24-HRs). 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 3 basic building blocks of analyses using the NCI method: 1) data set preparation, 2) application of the MIXTRAN macro to estimate parameters of the usual intake distribution, including effects of covariates, after transformation of 24-HRs 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 24-HRs, such as dietary supplements and human milk, and 4) carry out multiple subgroup analyses. This article describes the theoretical basis and operational guidance for these techniques. CONCLUSION: With this article as a detailed resource, researchers can leverage the basic NCI building blocks to investigate a wide range of questions about usual dietary intake distribution.

Healthy Eating Index-2015 Scores Among Adults Based on Observed vs Recalled Dietary Intake.

BACKGROUND: 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. OBJECTIVE: These analyses examined concordance between HEI-2015 scores based on observed vs reported intake among adults. DESIGN: 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. PARTICIPANTS/SETTING: 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. MAIN OUTCOME MEASURES: HEI-2015 scores were calculated using the population ratio method. STATISTICAL ANALYSES PERFORMED: 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). RESULTS: 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). CONCLUSIONS: HEI-2015 scores based on 24-hour dietary recall data are generally well estimated.

Association of food insecurity with dietary intakes and nutritional biomarkers among US children, National Health and Nutrition Examination Survey (NHANES) 2011-2016.

BACKGROUND: Food insecurity is associated with poorer nutrient intakes from food sources and lower dietary supplement use. However, its association with total usual nutrient intakes, inclusive of dietary supplements, and biomarkers of nutritional status among US children remains unknown. OBJECTIVE: The objective was to assess total usual nutrient intakes, Healthy Eating Index-2015 (HEI-2015) scores, and nutritional biomarkers by food security status, sex, and age among US children. METHODS: Cross-sectional data from 9147 children aged 1-18 y from the 2011-2016 NHANES were analyzed. Usual energy and total nutrient intakes and HEI-2015 scores were estimated using the National Cancer Institute method from 24-h dietary recalls. RESULTS: Overall diet quality was poor, and intakes of sodium, added sugars, and saturated fat were higher than recommended limits, regardless of food security status. Food-insecure girls and boys were at higher risk of inadequate intakes for vitamin D and magnesium, and girls also had higher risk for inadequate calcium intakes compared with their food-secure counterparts, when total intakes were examined. Choline intakes of food-insecure children were less likely to meet the adequate intake than those of their food-secure peers. No differences by food security status were noted for folate, vitamin C, iron, zinc, potassium, and sodium intakes. Food-insecure adolescent girls aged 14-18 y were at higher risk of micronutrient inadequacies than any other subgroup, with 92.8% (SE: 3.6%) at risk of inadequate intakes for vitamin D. No differences in biomarkers for vitamin D, folate, iron, and zinc were observed by food security status. The prevalence of iron deficiency was 12.7% in food-secure and 12.0% in food-insecure adolescent girls. CONCLUSIONS: Food insecurity was associated with compromised intake of some micronutrients, especially among adolescent girls. These results highlight a need for targeted interventions to improve children's overall diet quality, including the reduction of specific nutrient inadequacies, especially among food-insecure children. This study was registered at clinicaltrials.gov as NCT03400436.

Examining the association between meal context and diet quality: an observational study of meal context in older adults.

BACKGROUND: Though a healthy diet is widely associated with reduced risks for chronic disease and mortality, older adults in the U.S. on average do not meet dietary recommendations. Given that few studies have examined the association between meal context on older adult diet quality, the aims of this study were (1) to compare the dietary quality of foods consumed in different meal contexts, as measured by the Healthy Eating Index 2015 (HEI-2015): meal location, the presence of others, and the use of electronic screens; and (2) to examine which components of the HEI-2015 drove differences in HEI-2015 total scores by meal context. METHODS: Interactive Diet and Activity Tracking in AARP study participants (50-74 years) completed the Automated Self-Administered 24-h Dietary Assessment tool (ASA24, version 2011) that included foods and beverages consumed and three meal contexts: "at home" versus "away from home," "alone" versus "with company," and "with screen time" versus "without screen time." A population ratio approach was used to estimate HEI-2015 total and component scores for all food items consumed by meal context. Mean HEI-2015 scores (range: 0-100) for the three meal context variables were compared using t-tests. Where there were significant differences in total scores, additional t-tests were used to explore which HEI-2015 components were the primary drivers. All tests were stratified by sex and adjusted for multiple comparisons. RESULTS: HEI-2015 scores were lower for meals consumed away vs. at home (mean difference (SE), males: - 8.23 (1.02); females: - 7.29 (0.93); both p < 0.0001) and for meals eaten with vs. without company (mean difference (SE), males: - 6.61 (1.06); females: - 7.34 (1.18); both p < 0.0001). There was no difference comparing with vs. without screen time. When HEI-2015 component scores were examined, fewer total fruits, whole grains, and dairy were consumed away from home or with company; more total vegetables and greens and beans, and less added sugars were consumed with company. CONCLUSIONS: Our findings suggest an association between the behavior cues of meal location and companions and dietary choices among older adults. Future studies can explore the individual and interactive effects of meal context on diet quality and subsequent health outcomes.

Introduction to the SIMPLE Macro, a Tool to Increase the Accessibility of 24-Hour Dietary Recall Analysis and Modeling.

BACKGROUND: Information on long-term dietary intake is often required for research or program planning, but surveys routinely use short-term assessments such as 24-h recalls (24HRs). Methods to reduce the impact of within-person variation in 24HRs, such as the National Cancer Institute (NCI) method, typically require extensive training and skill. OBJECTIVES: We introduce the Simulating Intake of Micronutrients for Policy Learning and Engagement (SIMPLE) macro, a new tool to increase the accessibility of 24HR analysis. We explain the underlying theory behind the tool and provide examples of potential applications. METHODS: The SIMPLE macro connects the core NCI statistical code to estimate usual intake distributions and includes additional code to enable advanced analyses such as predictive modeling. The related SIMPLE-Iron macro applies the full probability method to estimate inadequate iron intake, and the SIMPLE-1D macro is used for descriptive or modeling analyses of data with a single 24HR per person. The macros and associated documentations are freely available. We analyzed data from the US National Health and Nutrition Examination Survey (NHANES) and the Cameroon National Micronutrient Survey to compare the SIMPLE macro to 1) the core NCI code using the Estimated Average Requirement cut point method, and 2) the IMAPP software for iron only, and to demonstrate the applications of the SIMPLE macro for estimating usual intake and predictive modeling. RESULTS: The SIMPLE macro generates identical results to the core NCI code. The SIMPLE-Iron macro also produces estimates of inadequate iron intake comparable to the IMAPP software. The examples demonstrate application of the SIMPLE macro to 1) descriptive analyses of nutrient intake from food and supplements (NHANES), and 2) analyses accounting for breast-milk nutrient intake and modeling fortification and supplementation programs (Cameroon). CONCLUSIONS: The SIMPLE macros may facilitate the analysis and modeling of dietary data to inform nutrition research, programs, and policy.

Within-Person Variation in Nutrient Intakes across Populations and Settings: Implications for the Use of External Estimates in Modeling Usual Nutrient Intake Distributions.

Determining the proportion of a population at risk of inadequate or excessive nutrient intake is a crucial step in planning and managing nutrition intervention programs. Multiple days of 24-h dietary intake data per subject allow for adjustment of modeled usual nutrient intake distributions for the proportion of total variance in intake attributable to within-individual variation (WIV:total). When only single-day dietary data are available, an external adjustment factor can be used; however, WIV:total may vary by population, and use of incorrect WIV:total ratios may influence the accuracy of prevalence estimates and subsequent program impacts. WIV:total values were compiled from publications and from reanalyses of existing datasets to describe variation in WIV:total across populations and settings. The potential impact of variation in external WIV:total on estimates of prevalence of inadequacy was assessed through simulation analyses using the National Cancer Institute 1-d method. WIV:total values were extracted from 40 publications from 24 countries, and additional values were calculated from 15 datasets from 12 nations. Wide variation in WIV:total (from 0.02 to 1.00) was observed in publications and reanalyses. Few patterns by population characteristics were apparent, but WIV:total varied by age in children (< vs. >1 y) and between rural and urban settings. Simulation analyses indicated that estimates of the prevalence of inadequate intake are sensitive to the selected ratio in some cases. Selection of an external WIV:total estimate should consider comparability between the reference and primary studies with regard to population characteristics, study design, and statistical methods. Given wide variation in observed ratios with few discernible patterns, the collection of ≥2 days of intake data in at least a representative subsample in population dietary studies is strongly encouraged. In the case of single-day dietary studies, sensitivity analyses are recommended to determine the robustness of prevalence estimates to changes in the variance ratio.

Micronutrient Fortification of Commercially Available Biscuits Is Predicted to Have Minimal Impact on Prevalence of Inadequate Micronutrient Intakes: Modeling of National Dietary Data From Cameroon.

BACKGROUND: Voluntarily fortified snack products are increasingly available but are not necessarily formulated to meet known dietary nutrient gaps, so potential impacts on population micronutrient intake adequacy are uncertain. OBJECTIVES: We modeled the impacts of hypothetical micronutrient-fortified biscuits on inadequate micronutrient intake in children and women of reproductive age (WRA) in Cameroon. METHODS: In a nationally representative survey stratified by macro-region (North, South, and Yaoundé/Douala), 24-h dietary recall data were collected from 883 children aged 12-59 mo and from 912 WRA. We estimated usual nutrient intake by the National Cancer Institute method for vitamin A, folate, vitamin B-12, zinc, and iron. We simulated the impact of biscuit fortification on prevalence of micronutrient intake below the estimated average requirement, given observed biscuit consumption, in the presence and absence of large-scale food fortification (LSFF) programs. RESULTS: Biscuit consumption in the prior 24-h by children and WRA, respectively, ranged from 4.5% and 1.5% in the South, to 20.7% and 5.9% in Yaoundé/Douala. In the absence of LSFF programs, biscuits fortified with retinol (600 µg/100 g), folic acid (300 µg/100 g), and zinc (8 mg/100 g) were predicted to reduce the prevalence of inadequacy among children by 10.3 ± 4.4, 13.2 ± 4.2, and 12.0 ± 6.1 percentage points, respectively, in Yaoundé/Douala. However, when existing vitamin A-fortified oil, and folic acid-fortified and zinc-fortified wheat flour programs were considered, the additional impacts of fortified biscuits were reduced substantially. Micronutrient-fortified biscuits were predicted to have minimal impact on dietary inadequacy in WRA, with or without LSFF programs. CONCLUSIONS: Given observed patterns of biscuit consumption in Cameroon, biscuit fortification is unlikely to reduce dietary inadequacy of studied micronutrients, except possibly for selected nutrients in children in urban areas in the absence of LSFF programs. As voluntary fortification becomes increasingly common, modeling studies could help guide efforts to ensure that fortified products align with public health goals.

Performance and Feasibility of Recalls Completed Using the Automated Self-Administered 24-Hour Dietary Assessment Tool in Relation to Other Self-Report Tools and Biomarkers in the Interactive Diet and Activity Tracking in AARP (IDATA) Study.

BACKGROUND: 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. OBJECTIVE: 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). DESIGN: 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. PARTICIPANTS/SETTING: 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. MAIN OUTCOME MEASURES: Response rates, nutrient intakes compared to recovery biomarkers across each ASA24 administration day, and HEI-2015 total and component scores were measured. STATISTICAL ANALYSES PERFORMED: Means, medians, standard deviations, interquartile ranges, and HEI-2015 total and component scores computed using a multivariate measurement error model are presented. RESULTS: 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). CONCLUSIONS: 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. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT03268577 (http://www.clinicaltrials.gov).

Older adults with obesity have higher risks of some micronutrient inadequacies and lower overall dietary quality compared to peers with a healthy weight, National Health and Nutrition Examination Surveys (NHANES), 2011-2014.

OBJECTIVE: To evaluate total usual intakes and biomarkers of micronutrients, overall dietary quality and related health characteristics of US older adults who were overweight or obese compared with a healthy weight. DESIGN: Cross-sectional study. SETTING: Two 24-h dietary recalls, nutritional biomarkers and objective and subjective health characteristic data were analysed from the National Health and Nutrition Examination Survey 2011-2014. We used the National Cancer Institute method to estimate distributions of total usual intakes from foods and dietary supplements for eleven micronutrients of potential concern and the Healthy Eating Index (HEI)-2015 score. PARTICIPANTS: Older adults aged ≥60 years (n 2969) were categorised by sex and body weight status, using standard BMI categories. Underweight individuals (n 47) were excluded due to small sample size. RESULTS: A greater percentage of obese older adults compared with their healthy-weight counterparts was at risk of inadequate Mg (both sexes), Ca, vitamin B6 and vitamin D (women only) intakes. The proportion of those with serum 25-hydroxyvitamin D < 40 nmol/l was higher in obese (12 %) than in healthy-weight older women (6 %). Mean overall HEI-2015 scores were 8·6 (men) and 7·1 (women) points lower in obese than in healthy-weight older adults. In addition, compared with healthy-weight counterparts, obese older adults were more likely to self-report fair/poor health, use ≥ 5 medications and have limitations in activities of daily living and cardio-metabolic risk factors; and obese older women were more likely to be food-insecure and have depression. CONCLUSIONS: Our findings suggest that obesity may coexist with micronutrient inadequacy in older adults, especially among women.

STRATOS guidance document on measurement error and misclassification of variables in observational epidemiology: Part 2-More complex methods of adjustment and advanced topics.

We continue our review of issues related to measurement error and misclassification in epidemiology. We further describe methods of adjusting for biased estimation caused by measurement error in continuous covariates, covering likelihood methods, Bayesian methods, moment reconstruction, moment-adjusted imputation, and multiple imputation. We then describe which methods can also be used with misclassification of categorical covariates. Methods of adjusting estimation of distributions of continuous variables for measurement error are then reviewed. Illustrative examples are provided throughout these sections. We provide lists of available software for implementing these methods and also provide the code for implementing our examples in the Supporting Information. Next, we present several advanced topics, including data subject to both classical and Berkson error, modeling continuous exposures with measurement error, and categorical exposures with misclassification in the same model, variable selection when some of the variables are measured with error, adjusting analyses or design for error in an outcome variable, and categorizing continuous variables measured with error. Finally, we provide some advice for the often met situations where variables are known to be measured with substantial error, but there is only an external reference standard or partial (or no) information about the type or magnitude of the error.