RESUMO
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.
Assuntos
Dieta , Avaliação Nutricional , Biomarcadores , Estudos de Coortes , Inquéritos sobre Dietas , Ingestão de Energia , Feminino , Humanos , Masculino , Rememoração Mental , Reprodutibilidade dos Testes , Inquéritos e QuestionáriosRESUMO
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).
Assuntos
Registros de Dieta , Inquéritos sobre Dietas/estatística & dados numéricos , Dieta Saudável/estatística & dados numéricos , Avaliação Nutricional , Autorrelato/estatística & dados numéricos , Idoso , Biomarcadores/urina , Inquéritos sobre Dietas/métodos , Ingestão de Alimentos , Metabolismo Energético , Estudos de Viabilidade , Feminino , Humanos , Masculino , Rememoração Mental , Pessoa de Meia-Idade , Nitrogênio/urina , Nutrientes/análise , Potássio/urina , Reprodutibilidade dos Testes , Sódio/urinaRESUMO
BACKGROUND: Measurement error in self-reported sugars intake may be obscuring the association between sugars and cancer risk in nutritional epidemiologic studies. METHODS: We used 24-hour urinary sucrose and fructose as a predictive biomarker for total sugars, to assess measurement error in self-reported sugars intake. The Nutrition and Physical Activity Assessment Study (NPAAS) is a biomarker study within the Women's Health Initiative (WHI) Observational Study that includes 450 postmenopausal women ages 60 to 91 years. Food Frequency Questionnaires (FFQ), four-day food records (4DFR), and three 24-hour dietary recalls (24HRs) were collected along with sugars and energy dietary biomarkers. RESULTS: Using the biomarker, we found self-reported sugars to be substantially and roughly equally misreported across the FFQ, 4DFR, and 24HR. All instruments were associated with considerable intake- and person-specific bias. Three 24HRs would provide the least attenuated risk estimate for sugars (attenuation factor, AF = 0.57), followed by FFQ (AF = 0.48) and 4DFR (AF = 0.32), in studies of energy-adjusted sugars and disease risk. In calibration models, self-reports explained little variation in true intake (5%-6% for absolute sugars and 7%-18% for sugars density). Adding participants' characteristics somewhat improved the percentage variation explained (16%-18% for absolute sugars and 29%-40% for sugars density). CONCLUSIONS: None of the self-report instruments provided a good estimate of sugars intake, although overall 24HRs seemed to perform the best. IMPACT: Assuming the calibrated sugars biomarker is unbiased, this analysis suggests that measuring the biomarker in a subsample of the study population for calibration purposes may be necessary for obtaining unbiased risk estimates in cancer association studies.
Assuntos
Carboidratos/urina , Ingestão de Energia/fisiologia , Idoso , Inquéritos sobre Dietas , Feminino , Humanos , Pessoa de Meia-Idade , Atividade Motora , Estado Nutricional , Estudos Prospectivos , Autorrelato , Inquéritos e QuestionáriosRESUMO
With the advent of Internet-based 24-hour recall (24HR) instruments, it is now possible to envision their use in cohort studies investigating the relation between nutrition and disease. Understanding that all dietary assessment instruments are subject to measurement errors and correcting for them under the assumption that the 24HR is unbiased for usual intake, here the authors simultaneously address precision, power, and sample size under the following 3 conditions: 1) 1-12 24HRs; 2) a single calibrated food frequency questionnaire (FFQ); and 3) a combination of 24HR and FFQ data. Using data from the Eating at America's Table Study (1997-1998), the authors found that 4-6 administrations of the 24HR is optimal for most nutrients and food groups and that combined use of multiple 24HR and FFQ data sometimes provides data superior to use of either method alone, especially for foods that are not regularly consumed. For all food groups but the most rarely consumed, use of 2-4 recalls alone, with or without additional FFQ data, was superior to use of FFQ data alone. Thus, if self-administered automated 24HRs are to be used in cohort studies, 4-6 administrations of the 24HR should be considered along with administration of an FFQ.
Assuntos
Inquéritos sobre Dietas/métodos , Projetos de Pesquisa Epidemiológica , Inquéritos e Questionários , Viés , Calibragem , Causalidade , Interpretação Estatística de Dados , Inquéritos sobre Dietas/normas , Inquéritos sobre Dietas/estatística & dados numéricos , Ingestão de Alimentos , Ingestão de Energia , Humanos , Modelos Logísticos , Tamanho da Amostra , Autorrelato , Análise de SobrevidaRESUMO
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.
RESUMO
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.
Assuntos
Dieta , Ingestão de Energia , Modelos Estatísticos , Animais , Teorema de Bayes , Grão Comestível , Peixes , Humanos , Cadeias de Markov , Método de Monte CarloRESUMO
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.
Assuntos
Ingestão de Alimentos , Modelos Estatísticos , National Cancer Institute (U.S.) , Avaliação Nutricional , Distribuições Estatísticas , Adulto , Fatores Etários , Idoso , Algoritmos , Cálcio da Dieta/administração & dosagem , Simulação por Computador , Inquéritos sobre Dietas , Feminino , Humanos , Entrevistas como Assunto , Ferro da Dieta/administração & dosagem , Funções Verossimilhança , Masculino , Pessoa de Meia-Idade , Método de Monte Carlo , Fatores Sexuais , Inquéritos e Questionários , Estados Unidos , Vitamina A/administração & dosagem , Adulto JovemRESUMO
BACKGROUND: Few large doubly labeled water (DLW) studies have provided an objective measure of total energy expenditure (TEE) in free-living men and women. The committee that developed the 2002 Dietary Reference Intake (DRI) estimated energy requirements (EER) noted that DLW studies in adults aged 40 to 60 y were limited. OBJECTIVE: We aimed to describe TEE and physical activity energy expenditure in middle-aged men and women by sex, age, menopausal status, and level of obesity, and to compare TEE to the DRI EER. DESIGN: TEE was measured by the DLW method in 450 men and women aged 40-69 y from the Observing Protein and Energy Nutrition Study. Resting metabolic rate was estimated by use of the Mifflin equation. RESULTS: Unadjusted TEE was lower in women than in men (591 kcal/d); however, when the analysis was adjusted for fat-free mass, women had significantly higher TEE than did men (182 kcal/d). This difference appeared to be due to higher physical activity levels in women (physical activity energy expenditure adjusted for FFM was 188 kcal/d greater in women than in men). Mean TEE was lowest in the seventh decade. TEE from DLW was highly correlated (r = 0.93) with EER from the DRI equations. CONCLUSION: In this population, TEE was higher in women than in men when adjusted for FFM, apparently because of higher physical activity levels in women. There were no significant differences in TEE, FFM, or physical activity levels in women by menopausal status. TEE was inversely associated with age and increased linearly with body mass index. This study corroborates the use of the DRI equations for EER.
Assuntos
Metabolismo Energético , Necessidades Nutricionais , Adulto , Índice de Massa Corporal , Calorimetria , Óxido de Deutério/metabolismo , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Seleção de PacientesRESUMO
OBJECTIVES: To describe the implementation of the Multifactor Screener in the 2000 National Health Interview Survey (NHIS); to provide intake estimates for fruits and vegetables, fiber, and percentage of energy from fat by various demographic and behavioral characteristics; and to discuss the strengths and weaknesses of the method. DESIGN/SUBJECTS: The 2000 NHIS was conducted in 38,632 households in a clustered sample representative of the 48 contiguous states in the United States. The Cancer Control Module was administered to adults (18 years and older) and included 17 dietary intake questions. ANALYSES: After excluding individuals with missing data or unlikely values on the diet questions, we computed individual intake of servings of fruits and vegetables, percentage of energy from fat, and grams of fiber. We estimated median intakes and distributions of intakes using adjusted variance estimates. We present bivariate relationships between diet and demographics and diet and behavioral characteristics in almost 30,000 adults in the United States. RESULTS: In general, intakes of these dietary factors were closer to recommendations among well-educated individuals, those engaged in other healthful behaviors, and underweight and normal weight individuals. Latinos had higher intakes of fruits and vegetables (men: 6 servings; women: 4.8 servings) and fiber (men: 23 g; women: 17 g), and generally a lower percentage of energy intake from fat (men: 33.7%; women: 32.1%) than did non-Latino whites (men: 5.4 servings; women: 4.5 servings; men: 19 g; women: 14 g; men: 33.9%; women: 32.0%) and non-Latino blacks (men: 5.4 servings; women: 4.4 servings; men: 19 g; women: 13 g; men: 34.7%; women: 33.5%). The strengths and limitations of the short dietary assessment method are discussed. CONCLUSIONS: The Multifactor Screener in NHIS, when used in conjunction with external reference data, provides reasonable estimates for three dietary factors and suggests relationships between intakes and other characteristics that are consistent with other data. Thus, these NHIS estimates could provide useful national benchmarks for local surveys using the same instrument.
Assuntos
Inquéritos sobre Dietas , Gorduras na Dieta/administração & dosagem , Fibras na Dieta/administração & dosagem , Frutas , Verduras , Adolescente , Adulto , Algoritmos , Análise por Conglomerados , Escolaridade , Ingestão de Energia , Feminino , Comportamentos Relacionados com a Saúde , Inquéritos Epidemiológicos , Hispânico ou Latino , Humanos , Entrevistas como Assunto , Masculino , Pessoa de Meia-Idade , Inquéritos e Questionários , Estados Unidos , População BrancaAssuntos
Inquéritos sobre Dietas , Comportamento Alimentar , Frutas , Neoplasias/prevenção & controle , Prevenção Primária , Verduras , Análise de Variância , Estudos de Casos e Controles , Humanos , Análise Multivariada , Prevenção Primária/métodos , Medição de Risco , Fatores de Risco , Inquéritos e QuestionáriosRESUMO
OBJECTIVE: To evaluate the ability of 2 new short assessment instruments and a food frequency questionnaire (FFQ) to measure intake of fruit and vegetables. The "All-Day" screener asks frequency and portion size questions about 9 food items. The "By-Meal" screener is similar, except that it asks about 2 of those 9 food items in terms of mealtime. DESIGN: Survey participants completed 4 telephone-administered 24-hour dietary recalls over 1 year, a self-administered FFQ 1 to 2 months later, and 1 of 2 self-administered screeners after an additional 7 months. SUBJECTS/SETTING: Participating were 202 men and 260 women aged 20 to 70 years living throughout the United States. STATISTICAL ANALYSES: Fruit and vegetable intakes measured by each screener and the FFQ were compared with true usual intake based on a measurement error model with 24-hour dietary recalls as the reference instrument. RESULTS: Estimates of median daily servings of fruit and vegetables were as follows: For men: True intake (5.8) vs All-Day screener (5.0), By-Meal screener (5.5), and FFQ (6.6); for women: true intake (4.2) vs All-Day screener (5.0), By-Meal screener (5.4), and FFQ (6.2). Estimated correlations between the test instruments and true intake were as follows: For men: All-Day screener (0.66), By-Meal screener (0.67), FFQ (0.68); for women: All-Day screener (0.51), By-Meal screener (0.53), and FFQ (0.54). APPLICATIONS/CONCLUSIONS: Both screeners might be useful to estimate median intakes of fruit and vegetable servings in US populations, but they might be less useful in accurately ranking individuals. More research is needed before using the screeners in ethnic or low-literacy populations.