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.

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).

School-Age Children Can Recall Some Foods and Beverages Consumed the Prior Day Using the Automated Self-Administered 24-Hour Dietary Assessment Tool (ASA24) without Assistance.

BACKGROUND: Technological innovations allow for collection of 24-h recalls (24HRs) in a broader range of studies than previously possible. The web-based Automated Self-Administered 24-Hour Dietary Assessment Tool (ASA24) has been shown to be feasible and to perform well in capturing true intake among adults. However, data to inform use with children are limited. OBJECTIVE: This observational feeding study was conducted to evaluate children's ability to accurately report a lunchtime meal using ASA24 without assistance. METHODS: The study was conducted among children (n = 100) aged 10-13 y within a school setting. Students were served an individual cheese pizza, baby carrots, ranch dip, yogurt, a cookie, and 1 choice of water, juice, or milk. Plate waste was collected and weighed. The next day, participants completed ASA24 and a sociodemographic questionnaire. Descriptive statistics were generated to determine match rates by food item and age, and linear regression analyses were conducted to examine associations between sociodemographic characteristics and accuracy of reported energy and nutrient intake. Associations between true and reported energy and nutrient intakes and portion sizes were assessed with use of t tests. RESULTS: Just under half (49%) of children fully completed ASA24 (median time, 41 min). Children reported an exact, close, or far match for 58% of all foods and beverages consumed, ranging from 29% for dip to 76% for pizza, but also reported some items not consumed as part of the study meal. Older children completed the recall in a shorter time than younger children (mean 31 among 13 y compared with 52 min among 10 y). Intakes of energy (39%), protein (33%), and sodium (78%) were significantly overestimated, whereas portion sizes for cookies (53%) and juice (69%) were underestimated. CONCLUSIONS: Children can report some foods and drinks consumed using ASA24, but our findings suggest challenges with independent completion, necessitating research to examine strategies, such as training and resources, to support data quality.

Best Practices for Dietary Supplement Assessment and Estimation of Total Usual Nutrient Intakes in Population-Level Research and Monitoring.

The use of dietary supplements (DS) is pervasive and can provide substantial amounts of micronutrients to those who use them. Therefore when characterizing dietary intakes, describing the prevalence of inadequacy or excess, or assessing relations between nutrients and health outcomes, it is critical to incorporate DS intakes to improve exposure estimates. Unfortunately, little is known about the best methods to assess DS, and the structure of measurement error in DS reporting. Several characteristics of nutrients from DS are salient to understand when comparing to those in foods. First, DS can be consumed daily or episodically, in bolus form and can deliver discrete and often very high doses of nutrients that are not limited by energy intakes. These characteristics contribute to bimodal distributions and distributions severely skewed to the right. Labels on DS often provide nutrient forms that differ from those found in conventional foods, and underestimate analytically derived values. Finally, the bioavailability of many nutrient-containing DS is not known and it may not be the same as the nutrients in a food matrix. Current methods to estimate usual intakes are not designed specifically to handle DS. Two temporal procedures are described to refer to the order that nutrient intakes are combined relative to usual intake procedures, referred to as a "shrinking" the distribution to remove random error. The "shrink then add" approach is preferable to the "add then shrink" approach when users and nonusers are combined for most research questions. Stratifying by DS before usual intake methods is another defensible option. This review describes how to incorporate nutrient intakes from DS to usual intakes from foods, and describes the available methods and fit-for-purpose of different analytical strategies to address research questions where total usual intakes are of interest at the group level for use in nutrition research and to inform policy decisions. Clinical Trial Registry: NCT03400436.

The Provision of Assistance Does Not Substantially Impact the Accuracy of 24-Hour Dietary Recalls Completed Using the Automated Self-Administered 24-H Dietary Assessment Tool among Women with Low Incomes.

Background: Evidence is lacking informing the use of the Automated Self-Administered 24-h Dietary Assessment Tool (ASA24) with populations characterized by low income. Objective: This study was conducted among women with low incomes to evaluate the accuracy of ASA24 recalls completed independently and with assistance. Methods: Three hundred and two women, aged ≥18 y and with incomes below the Supplemental Nutrition Assistance Program thresholds, served themselves from a buffet; amounts taken as well as plate waste were unobtrusively weighed to enable calculation of true intake for 3 meals. The following day, women completed ASA24-2016 independently (n = 148) or with assistance from a trained paraprofessional in a small group (n = 154). Regression modeling examined differences by condition in agreement between true and reported foods; energy, nutrient, and food group intakes; and portion sizes. Results: Participants who completed ASA24 independently and those who received assistance reported matches for 71.9% and 73.5% (P = 0.56) of items truly consumed, respectively. Exclusions (consumed but not reported) were highest for lunch (at which participants consumed approximately 2 times the number of distinct foods and beverages compared with breakfast and dinner). Commonly excluded foods were additions to main dishes (e.g., tomatoes in salad). On average, excluded foods contributed 43.6 g (46.2 kcal) and 40.1 g (43.2 kcal) among those in the independent and assisted conditions, respectively. Gaps between true and reported intake were different between conditions for folate and iron. Within conditions, significant gaps were observed for protein, vitamin D, and meat (both conditions); vitamin A, iron, and magnesium (independent); and folate, calcium, and vegetables (assisted). For foods and beverages for which matches were reported, no difference in the gap between true and reported portion sizes was observed by condition (P = 0.22). Conclusions: ASA24 performed relatively well among women with low incomes; however, accuracy was somewhat lower than previously observed among adults with a range of incomes. The provision of assistance did not significantly impact accuracy.

Dietary Supplement Use among U.S. Children by Family Income, Food Security Level, and Nutrition Assistance Program Participation Status in 2011⁻2014.

This analysis characterizes use of dietary supplements (DS) and motivations for DS use among U.S. children (≤18 years) by family income level, food security status, and federal nutrition assistance program participation using the 2011⁻2014 National Health and Nutrition Examination Survey data. About one-third (32%) of children used DS, mostly multivitamin-minerals (MVM; 24%). DS and MVM use were associated with higher family income and higher household food security level. DS use was lowest among children in households participating in the Supplemental Nutrition Assistance Program (SNAP; 20%) and those participating in the Special Supplemental Nutrition Assistance Program for Women, Infants, and Children (WIC; 26%) compared to both income-eligible and income-ineligible nonparticipants. Most children who used DS took only one (83%) or two (12%) products; although children in low-income families took fewer products than those in higher income families. The most common motivations for DS and MVM use were to "improve (42% or 46%)" or "maintain (34 or 38%)" health, followed by "to supplement the diet (23 or 24%)" for DS or MVM, respectively. High-income children were more likely to use DS and MVM "to supplement the diet" than middle- or low-income children. Only 18% of child DS users took DS based on a health practitioner's recommendation. In conclusion, DS use was lower among children who were in low-income or food-insecure families, or families participating in nutrition assistance programs.

Dietary Supplement Use Differs by Socioeconomic and Health-Related Characteristics among U.S. Adults, NHANES 2011⁻2014.

The objective of this study was to estimate the prevalence of use and types of dietary supplements (DS) used by U.S. adults (≥19 years) by sociodemographic characteristics: family income-to-poverty ratio (PIR), food security status, and Supplemental Nutrition Assistance Program (SNAP) participation using NHANES 2011⁻2014 data (n = 11,024). DS use was ascertained via a home inventory and a retrospective 30-day questionnaire. Demographic and socioeconomic differences related to DS use were evaluated using a univariate t statistic. Half of U.S. adults (52%) took at least one DS during a 30-day period; multivitamin-mineral (MVM) products were the most commonly used (31%). DS and MVM use was significantly higher among those with a household income of ≥ 350% of the poverty level, those who were food secure, and SNAP income-ineligible nonparticipants across all sex, age, and race/ethnic groups. Among women, prevalence of use significantly differed between SNAP participants (39%) and SNAP income-eligible nonparticipants (54%). Older adults (71+ years) remained the highest consumers of DS, specifically among the highest income group (82%), while younger adults (19⁻30 years), predominantly in the lowest income group (28%), were the lowest consumers. Among U.S. adults, DS use and the types of products consumed varied with income, food security, and SNAP participation.

Comparing Reported Dietary Supplement Intakes between Two 24-Hour Recall Methods: The Automated Self-Administered 24-Hour Dietary Assessment Tool and the Interview-Administered Automated Multiple Pass Method.

BACKGROUND: The Automated Self-Administered 24-hour Dietary Assessment Tool (ASA24) includes a highly standardized multipass web-based recall that, like the Automated Multiple Pass Method (AMPM), captures detailed information about dietary intake using multiple probes and reminders to enhance recall of intakes. The primary distinction between ASA24 and AMPM is that the ASA24 user interface guides participants, thus removing the need for interviewers. OBJECTIVE: The objective of this study was to compare dietary supplement use reported on self-administered (ASA24-2011) vs interviewer-administered (AMPM) 24-hour recalls. DESIGN: The Food Reporting Comparison Study was an evaluation study designed to compare self-reported intakes captured using the self-administered ASA24 vs data collected via interviewer-administered AMPM recalls. Between 2010 and 2011, 1081 women and men were enrolled from three integrated health care systems that belong to the National Cancer Institute-funded Cancer Research Network: Security Health Plan Marshfield Clinic, Wisconsin; Henry Ford Health System, Michigan; and Kaiser Permanente Northern California, California. Quota sampling was used to ensure a balance of age, sex, and race/ethnicity. Participants were randomly assigned to four groups, and each group was asked to complete two dietary recalls: group 1, two ASA24s; group 2, two AMPMs; group 3, ASA24 first and AMPM second; and group 4, AMPM first and ASA24 second. Dietary supplements were coded using the 2007-2008 National Health and Nutrition Examination Survey Dietary Supplement Database. Analyses used the two one-sided tests, known as TOST, to assess equivalence of reported supplement use between methods. RESULTS: Complete 24-hour dietary recalls that included both dietary and supplement intake data were available for 1076 participants (507 men and 569 women). The proportions reporting supplement use via ASA24 and AMPM were 46% and 43%, respectively. These proportions were equivalent, with a small effect size of less than 20%. There were two exceptions in subgroup analyses: reported use among those 40 to 59 years of age and reported use by non-Hispanic black subjects were higher for ASA24 than AMPM. CONCLUSIONS: This study provides evidence that there is little difference in reported supplement use by mode of administration (ie, interview-administered vs self-administered recall).

Whole Grains Contribute Only a Small Proportion of Dietary Fiber to the U.S. Diet.

Dietary fiber (DF), found in whole fruits, vegetables, and whole grains (WG), is considered a nutrient of concern in the US diet and increased consumption is recommended. The present study was designed to highlight this critical importance of the difference between WG, high-fiber WG, and sources of fiber that are not from WG. The study is based on the two-day diets reported consumed by the nationally representative sample of Americans participating in What We Eat In America, the dietary component of the National Health and Nutrition Examination Survey from 2003-2010. Foods consumed were classified into tertiles of DF and WG and the contribution of fiber by differing levels of WG content were examined. Foods containing high amounts of WG and DF only contributed about 7% of total fiber intake. Overall, grain-based foods contributed 54.5% of all DF consumed. Approximately 39% of DF came from grain foods that contained no WG, rather these foods contained refined grains, which contain only small amounts of DF but are consumed in large quantities. All WG-containing foods combined contributed a total of 15.3% of DF in the American diet. Thus, public health messaging needs to be changed to specifically encourage consumption of WG foods with high levels of DF to address both recommendations.

Using 2 Assessment Methods May Better Describe Dietary Supplement Intakes in the United States.

BACKGROUND: One-half of US adults report using a dietary supplement. NHANES has traditionally assessed dietary supplement use via a 30-d questionnaire but in 2007 added a supplement module to the 24-h dietary recall (24HR). OBJECTIVE: We compared these 2 dietary assessment methods, examined potential biases in the methods, and determined the effect that instrument choice had on estimates of prevalence of multivitamin/multimineral dietary supplement (MVMM) use. METHODS: We described prevalence of dietary supplement use by age, sex, and assessment instrument in 12,285 adults in the United States (>19 y of age) from NHANES 2007-2010. RESULTS: When using data from the questionnaire alone, 29.3% ± 1.0% of men and 35.5% ± 1.0% of women were users of MVMMs, whereas data from the 24HR only produced prevalence estimates of 26.3% ± 1.1% for men and 33.2% ± 1.0% for women. When using data from both instruments combined, 32.3% ± 1.2% of men and 39.5% ± 1.1% of women were classified as MVMM users. Prevalence estimates were significantly higher by 2-9% in all age-sex groups when using information from both instruments combined than when using data from either instrument individually. A digit preference bias and flattened slope phenomenon were observed in responses to the dietary supplement questionnaire. A majority (67%) of MVMMs were captured on both instruments, whereas 19% additional MVMMs were captured on the questionnaire and 14% additional on the 24HR. Of those captured only on the 24HR, 26% had missing label information, whereas only 12% and 9% of those captured on the questionnaire or both, respectively, had missing information. CONCLUSIONS: Use of both the dietary supplement questionnaire and the 24HR can provide advantages to researchers over the use of a single instrument and potentially capture a larger fraction of dietary supplement users.

Dietary assessment in food environment research: a systematic review.

CONTEXT: The existing evidence on food environments and diet is inconsistent, potentially because of heterogeneity in measures used to assess diet. The objective of this review, conducted in 2012-2013, was to examine measures of dietary intake utilized in food environment research. EVIDENCE ACQUISITION: Included studies were published from January 2007 through June 2012 and assessed relationships between at least one food environment exposure and at least one dietary outcome. Fifty-one articles were identified using PubMed, SCOPUS, Web of Knowledge, and PsycINFO; references listed in the papers reviewed and relevant review articles; and the National Cancer Institute's Measures of the Food Environment website. The frequency of the use of dietary intake measures and assessment of specific dietary outcomes were examined, as were patterns of results among studies using different dietary measures. EVIDENCE SYNTHESIS: The majority of studies used brief instruments, such as screeners or one or two questions, to assess intake. Food frequency questionnaires were used in about a quarter of studies, one in ten used 24-hour recalls, and fewer than one in 20 used diaries. Little consideration of dietary measurement error was evident. Associations between the food environment and diet were more consistently in the expected direction in studies using less error-prone measures. CONCLUSIONS: There is a tendency toward the use of brief dietary assessment instruments with low cost and burden rather than more detailed instruments that capture intake with less bias. Use of error-prone dietary measures may lead to spurious findings and reduced power to detect associations.

Chapter 2: Birth-cohort-specific estimates of smoking behaviors for the U.S. population.

We present methods for estimating five-year birth-cohort-specific trends in smoking behavior for individuals born between 1910 and 1984. We combine cross-sectional survey data on smoking behavior from the National Health Interview Surveys (NHIS) conducted between 1965 and 2001 into a single data set. The cumulative incidence of smoking by year of age and calendar year is constructed for each birth cohort from this data set and the effect of differential mortality on ever smoking prevalence is adjusted by modeling the ever smoking prevalence of each cohort for each survey year and back extrapolating that effect to age 30. Cumulative incidence is then scaled to match the ever smoking prevalence at age 30. Survival analyses generate the cumulative cessation among ever smokers across year of age and calendar year and are used to estimate current smoking prevalence. Data from Substance Abuse and Mental Health Services Administration (SAMHSA) National Survey on Drug Use and Health is used to divide those initiating smoking into quintiles of number of cigarettes smoked per day (CPD) and the mean CPD for each quintile in each calendar year is estimated from the NHIS data. For five-year birth cohorts of white, african-american, Hispanic and all race/ethnicity groupings of males and females born between 1910 and 1984, estimates are provided for prevalence of current and ever smoking, incidence of cessation, incidence of initiation, and the distribution of smoking duration and CPD for each calendar year and each single year of age through the year 1999. We believe that we are the first to provide birth-cohort-specific estimates of smoking behaviors for the U.S. population that include distributions of duration of smoking and number of cigarettes per day. These additional elements substantively enhance the utility of these estimates for estimating lung cancer risks.

Income and race/ethnicity are associated with adherence to food-based dietary guidance among US adults and children.

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.

A NEW MULTIVARIATE MEASUREMENT ERROR MODEL WITH ZERO-INFLATED DIETARY DATA, AND ITS APPLICATION TO DIETARY ASSESSMENT.

In the United States the preferred method of obtaining dietary intake data is the 24-hour dietary recall, yet the measure of most interest is usual or long-term average daily intake, which is impossible to measure. Thus, usual dietary intake is assessed with considerable measurement error. Also, diet represents numerous foods, nutrients and other components, each of which have distinctive attributes. Sometimes, it is useful to examine intake of these components separately, but increasingly nutritionists are interested in exploring them collectively to capture overall dietary patterns. Consumption of these components varies widely: some are consumed daily by almost everyone on every day, while others are episodically consumed so that 24-hour recall data are zero-inflated. In addition, they are often correlated with each other. Finally, it is often preferable to analyze the amount of a dietary component relative to the amount of energy (calories) in a diet because dietary recommendations often vary with energy level. The quest to understand overall dietary patterns of usual intake has to this point reached a standstill. There are no statistical methods or models available to model such complex multivariate data with its measurement error and zero inflation. This paper proposes the first such model, and it proposes the first workable solution to fit such a model. After describing the model, we use survey-weighted MCMC computations to fit the model, with uncertainty estimation coming from balanced repeated replication.The methodology is illustrated through an application to estimating the population distribution of the Healthy Eating Index-2005 (HEI-2005), a multi-component dietary quality index involving ratios of interrelated dietary components to energy, among children aged 2-8 in the United States. We pose a number of interesting questions about the HEI-2005 and provide answers that were not previously within the realm of possibility, and we indicate ways that our approach can be used to answer other questions of importance to nutritional science and public health.

Fitting a bivariate measurement error model for episodically consumed dietary components.

There has been great public health interest in estimating usual, i.e., long-term average, intake of episodically consumed dietary components that are not consumed daily by everyone, e.g., fish, red meat and whole grains. Short-term measurements of episodically consumed dietary components have zero-inflated skewed distributions. So-called two-part models have been developed for such data in order to correct for measurement error due to within-person variation and to estimate the distribution of usual intake of the dietary component in the univariate case. However, there is arguably much greater public health interest in the usual intake of an episodically consumed dietary component adjusted for energy (caloric) intake, e.g., ounces of whole grains per 1000 kilo-calories, which reflects usual dietary composition and adjusts for different total amounts of caloric intake. Because of this public health interest, it is important to have models to fit such data, and it is important that the model-fitting methods can be applied to all episodically consumed dietary components.We have recently developed a nonlinear mixed effects model (Kipnis, et al., 2010), and have fit it by maximum likelihood using nonlinear mixed effects programs and methodology (the SAS NLMIXED procedure). Maximum likelihood fitting of such a nonlinear mixed model is generally slow because of 3-dimensional adaptive Gaussian quadrature, and there are times when the programs either fail to converge or converge to models with a singular covariance matrix. For these reasons, we develop a Monte-Carlo (MCMC) computation of fitting this model, which allows for both frequentist and Bayesian inference. There are technical challenges to developing this solution because one of the covariance matrices in the model is patterned. Our main application is to the National Institutes of Health (NIH)-AARP Diet and Health Study, where we illustrate our methods for modeling the energy-adjusted usual intake of fish and whole grains. We demonstrate numerically that our methods lead to increased speed of computation, converge to reasonable solutions, and have the flexibility to be used in either a frequentist or a Bayesian manner.

A mixed-effects model approach for estimating the distribution of usual intake of nutrients: the NCI method.

It is of interest to estimate the distribution of usual nutrient intake for a population from repeat 24-h dietary recall assessments. A mixed effects model and quantile estimation procedure, developed at the National Cancer Institute (NCI), may be used for this purpose. The model incorporates a Box-Cox parameter and covariates to estimate usual daily intake of nutrients; model parameters are estimated via quasi-Newton optimization of a likelihood approximated by the adaptive Gaussian quadrature. The parameter estimates are used in a Monte Carlo approach to generate empirical quantiles; standard errors are estimated by bootstrap. The NCI method is illustrated and compared with current estimation methods, including the individual mean and the semi-parametric method developed at the Iowa State University (ISU), using data from a random sample and computer simulations. Both the NCI and ISU methods for nutrients are superior to the distribution of individual means. For simple (no covariate) models, quantile estimates are similar between the NCI and ISU methods. The bootstrap approach used by the NCI method to estimate standard errors of quantiles appears preferable to Taylor linearization. One major advantage of the NCI method is its ability to provide estimates for subpopulations through the incorporation of covariates into the model. The NCI method may be used for estimating the distribution of usual nutrient intake for populations and subpopulations as part of a unified framework of estimation of usual intake of dietary constituents.

A population's distribution of Healthy Eating Index-2005 component scores can be estimated when more than one 24-hour recall is available.

The USDA's Healthy Eating Index-2005 (HEI-2005) is a tool to quantify the quality of diet consumed by individuals in the U.S. It comprises 12 components expressed as ratios of a food group or nutrient intake to energy intake. Components are scored on a scale from 0 to M, where M is 5, 10, or 20. Ideally, the HEI-2005 is calculated on the basis of the usual, or long-term average, dietary intake of an individual. In recent cycles of the NHANES, intake data have been collected via 24-h recalls for more than 1 d on most participants. We present here a statistical method to estimate a population's distribution of usual HEI-2005 component scores when >or=2 d of dietary information is available for a sample of individuals from the population. Distributions for the total population and for age-gender subgroups may be estimated. The method also yields an estimate of the population's mean total HEI-2005 score. Application of the method to NHANES data for 2001-2004 yielded estimated distributions for all 12 components; those of total vegetables (range 0-5), whole grains (range 0-5), and energy from solid fats, alcoholic beverages, and added sugars (range 0-20) are presented. The total population mean scores for these components were 3.21, 1.00, and 8.41, respectively. An estimated 30% of the total population had a score of <2.5 for total vegetables. This is the first time, to our knowledge, that estimated distributions of usual HEI-2005 component scores have been published.

Are patterns of health behavior associated with cancer screening?

PURPOSE: This study investigates the relationship between patterns of health behaviors and the use of cancer-screening tests while controlling for sociodemographic and health system factors. DESIGN: Cross-sectional analysis of the 2000 National Health Interview (NHIS). SETTING: Nationally representative sample. SUBJECTS: Adults 50 years and older. MEASURES: Use of cancer-screening tests, health behaviors, sociodemographic factors, and health system factors from self-reported responses from the NHIS. Sixteen health behavior patterns were identified based on lifestyle recommendations for physical activity, tobacco use, alcohol consumption, and fruit and vegetable consumption. RESULTS: Health behavior patterns, age, educational attainment, usual source of care, and health insurance were significantly associated with the use of breast, cervical, and colorectal cancer screening (p < .05). Approximate R2 for the four models ranged from .067 for colorectal cancer screening in women to .122 for cervical cancer screening. Having a usual source of care was the strongest correlate of screening; the magnitude of associations for health behavior patterns and demographic variables and screening was similar and much smaller than those for usual source of care. CONCLUSION: These findings demonstrate relationships between patterns of multiple health behaviors and use of recommended cancer-screening tests, even when accounting for factors known to influence test use. This suggests potential for addressing cancer screening in the context of multiple behavior change interventions once barriers to health care access are removed.

Most Americans eat much less than recommended amounts of fruits and vegetables.

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