Kirkpatrick discusses the study by Steele et al which detailed a process for application of the NOVA classification system to data from NHANES. The "What We Eat in America" component of NHANES ...collects dietary intake data using interviewer-administered 24-hour dietary recalls (24HDR). Challenges to standardized application of the NOVA system noted by Steele et al. included lack of information about food preparation and level of processing in the 24HDR data and the lack of brand-specific data in food composition databases. The process required linking food codes from the Food and Nutrient Database for Dietary Surveys, which are used to estimate the intake of energy and nutrients based on 24HDRs, to those from the underlying National Nutrient Database for Standard Reference to disaggregate recipes and mixed dishes into ingredients.
Update of the Healthy Eating Index: HEI-2015 Krebs-Smith, Susan M.; Pannucci, TusaRebecca E.; Subar, Amy F. ...
Journal of the Academy of Nutrition and Dietetics,
September 2018, 2018-09-00, 20180901, Letnik:
118, Številka:
9
Journal Article
Recenzirano
Odprti dostop
The Healthy Eating Index (HEI) is a measure for assessing whether a set of foods aligns with the Dietary Guidelines for Americans (DGA). An updated HEI is released to correspond to each new edition ...of the DGA, and this article introduces the latest version, which reflects the 2015-2020 DGA. The HEI-2015 components are the same as in the HEI-2010, except Saturated Fat and Added Sugars replace Empty Calories, with the result being 13 components. The 2015-2020 DGA include explicit recommendations to limit intakes of both Added Sugars and Saturated Fats to <10% of energy. HEI-2015 does not account for excessive energy from alcohol within a separate component, but continues to account for all energy from alcohol within total energy (the denominator for most components). All other components remain the same as for HEI-2010, except for a change in the allocation of legumes. Previous versions of the HEI accounted for legumes in either the two vegetable or the two protein foods components, whereas HEI-2015 counts legumes toward all four components. Weighting approaches are similar to those of previous versions, and scoring standards were maintained, refined, or developed to increase consistency across components; better ensure face validity; follow precedent; cover a range of intakes; and, when applicable, ensure the DGA level corresponds to a score >7 out of 10. HEI-2015 component scores can be examined collectively using radar graphs to reveal a pattern of diet quality and summed to represent overall diet quality.
Evaluation of the Healthy Eating Index-2015 Reedy, Jill; Lerman, Jennifer L.; Krebs-Smith, Susan M. ...
Journal of the Academy of Nutrition and Dietetics,
September 2018, 2018-09-00, 20180901, Letnik:
118, Številka:
9
Journal Article
Recenzirano
Odprti dostop
The Healthy Eating Index (HEI), a diet quality index that measures alignment with the Dietary Guidelines for Americans, was updated with the 2015-2020 Dietary Guidelines for Americans.
To evaluate ...the psychometric properties of the HEI-2015, eight questions were examined: five relevant to construct validity, two related to reliability, and one to assess criterion validity.
Three data sources were used: exemplary menus (n=4), National Health and Nutrition Examination Survey 2011-2012 (N=7,935), and the National Institutes of Health-AARP (formally known as the American Association of Retired Persons) Diet and Health Study (N=422,928).
Exemplary menus: Scores were calculated using the population ratio method. National Health and Nutrition Examination Survey 2011-2012: Means and standard errors were estimated using the Markov Chain Monte Carlo approach. Analyses were stratified to compare groups (with t tests and analysis of variance). Principal components analysis examined the number of dimensions. Pearson correlations were estimated between components, energy, and Cronbach’s coefficient alpha. National Institutes of Health-AARP Diet and Health Study: Adjusted Cox proportional hazards models were used to examine scores and mortality outcomes.
For construct validity, the HEI-2015 yielded high scores for exemplary menus as four menus received high scores (87.8 to 100). The mean score for National Health and Nutrition Examination Survey was 56.6, and the first to 99th percentile were 32.6 to 81.2, respectively, supporting sufficient variation. Among smokers, the mean score was significantly lower than among nonsmokers (53.3 and 59.7, respectively) (P<0.01), demonstrating differentiation between groups. The correlation between diet quality and diet quantity was low (all <0.25) supporting these elements being independent. The components demonstrated multidimensionality when examined with a scree plot (at least four dimensions). For reliability, most of the intercorrelations among the components were low to moderate (0.01 to 0.49) with a few exceptions, and the standardized Cronbach’s alpha was .67. For criterion validity, the highest vs the lowest quintile of HEI-2015 scores were associated with a 13% to 23% decreased risk of all-cause, cancer, and cardiovascular disease mortality.
The results demonstrated evidence supportive of construct validity, reliability, and criterion validity. The HEI-2015 can be used to examine diet quality relative to the 2015-2020 Dietary Guidelines for Americans.
Update of the Healthy Eating Index: HEI-2010 Guenther, Patricia M., PhD, RD; Casavale, Kellie O., PhD, RD; Reedy, Jill, PhD, RD ...
Journal of the Academy of Nutrition and Dietetics,
04/2013, Letnik:
113, Številka:
4
Journal Article
Recenzirano
Odprti dostop
Abstract The Healthy Eating Index (HEI) is a measure of diet quality in terms of conformance with federal dietary guidance. Publication of the 2010 Dietary Guidelines for Americans prompted an ...interagency working group to update the HEI. The HEI-2010 retains several features of the 2005 version: (a) it has 12 components, many unchanged, including nine adequacy and three moderation components; (b) it uses a density approach to set standards, eg, per 1,000 calories or as a percentage of calories; and (c) it employs least-restrictive standards; ie, those that are easiest to achieve among recommendations that vary by energy level, sex, and/or age. Changes to the index include: (a) the Greens and Beans component replaces Dark Green and Orange Vegetables and Legumes; (b) Seafood and Plant Proteins has been added to capture specific choices from the protein group; (c) Fatty Acids, a ratio of polyunsaturated and monounsaturated to saturated fatty acids, replaces Oils and Saturated Fat to acknowledge the recommendation to replace saturated fat with monounsaturated and polyunsaturated fatty acids; and (d) a moderation component, Refined Grains, replaces the adequacy component, Total Grains, to assess overconsumption. The HEI-2010 captures the key recommendations of the 2010 Dietary Guidelines and, like earlier versions, will be used to assess the diet quality of the US population and subpopulations, evaluate interventions, research dietary patterns, and evaluate various aspects of the food environment.
Abstract This monograph describes the National Cancer Institute’s Dietary Assessment Primer, a web resource developed to help researchers choose the best available dietary assessment approach to ...achieve their research objective. All self-report instruments have error, but understanding the nature of that error can lead to better assessment, analysis, and interpretation of results. The Primer includes profiles of the major self-report dietary assessment instruments, including guidance on the best uses of each instrument; discussion of validation and measurement error generally and with respect to each instrument; guidance for choosing a dietary assessment approach for different research questions; and additional resources, such as a glossary, references, and overviews of specific/important issues in the field. This monograph also describes some future research needs in the field of dietary assessment.
Household food insecurity constrains food selection, but whether the dietary compromises associated with this problem heighten the risk of nutrient inadequacies is unclear. The objectives of this ...study were to examine the relationship between household food security status and adults' and children's dietary intakes and to estimate the prevalence of nutrient inadequacies among adults and children, differentiating by household food security status. We analyzed 24-h recall and household food security data for persons aged 1-70 y from the 2004 Canadian Community Health Survey (cycle 2.2). The relationship between adults' and children's nutrient and food intakes and household food security status was assessed using regression analysis. Estimates of the prevalence of inadequate nutrient intakes by food security status and age/sex group were calculated using probability assessment methods. Poorer dietary intakes were observed among adolescents and adults in food-insecure households and many of the differences by food security status persisted after accounting for potential confounders in multivariate analyses. Higher estimated prevalences of nutrient inadequacy were apparent among adolescents and adults in food-insecure households, with the differences most marked for protein, vitamin A, thiamin, riboflavin, vitamin B-6, folate, vitamin B-12, magnesium, phosphorus, and zinc. Among children, few differences in dietary intakes by household food security status were apparent and there was little indication of nutrient inadequacy. This study indicates that for adults and, to some degree, adolescents, food insecurity is associated with inadequate nutrient intakes. These findings highlight the need for concerted public policy responses to ameliorate household food insecurity.
Careful consideration of the validity and reliability of methods intended to assess dietary intake is central to the robustness of nutrition research. A dietary assessment method with high validity ...is capable of providing useful measurement for a given purpose and context. More specifically, a method with high validity is well grounded in theory; its performance is consistent with that theory; and it is precise, dependable, and accurate within specified performance standards. Assessing the extent to which dietary assessment methods possess these characteristics can be difficult due to the complexity of dietary intake, as well as difficulties capturing true intake. We identified challenges and best practices related to the validation of self-report dietary assessment methods. The term validation is used to encompass various dimensions that must be assessed and considered to determine whether a given method is suitable for a specific purpose. Evidence on the varied concepts of validity and reliability should be interpreted in combination to inform judgments about the suitability of a method for a specified purpose. Self-report methods are the focus because they are used in most studies seeking to measure dietary intake. Biomarkers are important reference measures to validate self-report methods and are also discussed. A checklist is proposed to contribute to strengthening the literature on the validation of dietary assessment methods and ultimately, the nutrition literature more broadly.
Recent reports have asserted that, because of energy underreporting, dietary self-report data suffer from measurement error so great that findings that rely on them are of no value. This commentary ...considers the amassed evidence that shows that self-report dietary intake data can successfully be used to inform dietary guidance and public health policy. Topics discussed include what is known and what can be done about the measurement error inherent in data collected by using self-report dietary assessment instruments and the extent and magnitude of underreporting energy compared with other nutrients and food groups. Also discussed is the overall impact of energy underreporting on dietary surveillance and nutritional epidemiology. In conclusion, 7 specific recommendations for collecting, analyzing, and interpreting self-report dietary data are provided: (1) continue to collect self-report dietary intake data because they contain valuable, rich, and critical information about foods and beverages consumed by populations that can be used to inform nutrition policy and assess diet-disease associations; (2) do not use self-reported energy intake as a measure of true energy intake; (3) do use self-reported energy intake for energy adjustment of other self-reported dietary constituents to improve risk estimation in studies of diet-health associations; (4) acknowledge the limitations of self-report dietary data and analyze and interpret them appropriately; (5) design studies and conduct analyses that allow adjustment for measurement error; (6) design new epidemiologic studies to collect dietary data from both short-term (recalls or food records) and long-term (food-frequency questionnaires) instruments on the entire study population to allow for maximizing the strengths of each instrument; and (7) continue to develop, evaluate, and further expand methods of dietary assessment, including dietary biomarkers and methods using new technologies.
The Healthy Eating Index (HEI), a measure of diet quality, was updated to reflect the 2010 Dietary Guidelines for Americans and the accompanying USDA Food Patterns. To assess the validity and ...reliability of the HEI-2010, exemplary menus were scored and 2 24-h dietary recalls from individuals aged ≥2 y from the 2003-2004 NHANES were used to estimate multivariate usual intake distributions and assess whether the HEI-2010 1) has a distribution wide enough to detect meaningful differences in diet quality among individuals, 2) distinguishes between groups with known differences in diet quality by using t tests, 3) measures diet quality independently of energy intake by using Pearson correlation coefficients, 4) has >1 underlying dimension by using principal components analysis (PCA), and 5) is internally consistent by calculating Cronbach's coefficient α. HEI-2010 scores were at or near the maximum levels for the exemplary menus. The distribution of scores among the population was wide (5th percentile = 31.7; 95th percentile = 70.4). As predicted, men's diet quality (mean HEI-2010 total score = 49.8) was poorer than women's (52.7), younger adults' diet quality (45.4) was poorer than older adults' (56.1), and smokers' diet quality (45.7) was poorer than nonsmokers' (53.3) (P < 0.01). Low correlations with energy were observed for HEI-2010 total and component scores (|r| ≤ 0.21). Cronbach's coefficient α was 0.68, supporting the reliability of the HEI-2010 total score as an indicator of overall diet quality. Nonetheless, PCA indicated multiple underlying dimensions, highlighting the fact that the component scores are equally as important as the total. A comparable reevaluation of the HEI-2005 yielded similar results. This study supports the validity and the reliability of both versions of the HEI.
PDF
