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      Reproducibility and Relative Validity of the Healthy Eating Index-2015 and Nutrient-Rich Food Index 9.3 Estimated by Comprehensive and Brief Diet History Questionnaires in Japanese Adults

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          Abstract

          We examined the reproducibility and relative validity of two measures of overall diet quality, the Healthy Eating Index-2015 (HEI-2015) and Nutrient-Rich Food Index 9.3 (NRF9.3), as estimated by well-established self-administered dietary assessment questionnaires for the Japanese, namely the comprehensive diet history questionnaire (DHQ) and the brief diet history questionnaire (BDHQ). Diet was assessed separately by two DHQs and two BDHQs at a 1-year interval and by 16-day weighed dietary records (DRs) in 121 women and 121 men aged 31–81 years. HEI-2015 and NRF9.3 were calculated from each method. The reproducibility correlation for the two questionnaires (intraclass correlation) ranged from 0.53 (HEI-2015 from BDHQ in men) to 0.77 (NRF9.3 from BDHQ in women). The validity correlation between the first questionnaires and DR (Pearson correlation) ranged from 0.37 (NRF9.3 from BDHQ in men) to 0.61 (NRF9.3 from DHQ and BDHQ in women). Bland–Altman plots showed poor agreement between the DHQ or BDHQ and DR, as well as the presence of weak proportional bias. Overall, these data indicate reasonable reproducibility and ranking ability of the DHQ and BDHQ for assessing the HEI-2015 and NRF9.3 and support their usefulness in future epidemiological research on the overall effects of Japanese diets on various health outcomes.

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          Development, validation and utilisation of food-frequency questionnaires - a review.

          The purpose of this review is to provide guidance on the development, validation and use of food-frequency questionnaires (FFQs) for different study designs. It does not include any recommendations about the most appropriate method for dietary assessment (e.g. food-frequency questionnaire versus weighed record). A comprehensive search of electronic databases was carried out for publications from 1980 to 1999. Findings from the review were then commented upon and added to by a group of international experts. Recommendations have been developed to aid in the design, validation and use of FFQs. Specific details of each of these areas are discussed in the text. FFQs are being used in a variety of ways and different study designs. There is no gold standard for directly assessing the validity of FFQs. Nevertheless, the outcome of this review should help those wishing to develop or adapt an FFQ to validate it for its intended use.
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            Development and validation of the nutrient-rich foods index: a tool to measure nutritional quality of foods.

            Ranking and/or classifying foods based on their nutrient composition is known as nutrient profiling. Nutrition quality indices need to be tested and validated against quality of the total diet. A family of nutrient-rich foods (NRF) indices were validated against the Healthy Eating Index (HEI), an accepted measure of diet quality. All foods consumed by participants in NHANES 1999-2002 studies were scored using NRFn.3 (where n = 6-15) indices based on unweighted sums, means, and ratios of percent daily values (DV) for nutrients to encourage (n) and for nutrients to limit (LIM) (3). Individual food scores were calculated based on 100 kcal (418 kJ) and FDA serving sizes [reference amounts customarily consumed (RACC)]. Energy-weighted food-based scores per person were then regressed against HEI, adjusting for gender, age, and ethnicity. The measure of index performance was the percentage of variation in HEI (R2) explained by each NRF score. NRF indices based on both nutrients to encourage and LIM performed better than indices based on LIM only. Maximum variance in HEI was explained using 6 or 9 nutrients to encourage; index performance actually declined with the inclusion of additional vitamins and minerals. NRF indices based on 100 kcal (418 kJ) performed similarly to indices based on RACC. Algorithms based on sums or means of nutrient DV performed better than ratio-based scores. The NRF9.3 index, based on 9 nutrients to encourage and 3 LIM per RACC and per 100 kcal, explained the highest percentage of variation from HEI and could be readily expected to rank foods based on nutrient density.
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              The Nutrient Rich Foods Index helps to identify healthy, affordable foods.

              The Nutrient Rich Foods (NRF) Index is a formal scoring system that ranks foods on the basis of their nutrient content. When used in conjunction with a food prices database, it can help identify foods that are both nutritious and affordable. Our aim was to identify healthy, affordable foods and food groups by using the NRF index and US Department of Agriculture (USDA) nutrient composition and food prices data sets. Foods in the USDA Food and Nutrition Database for Dietary Studies 1.0 were scored by using the NRF index. This NRF algorithm was represented by the sum of the percentage of the daily values of 9 nutrients to encourage (protein, fiber, vitamin A, vitamin C, vitamin E, calcium, iron, magnesium, and potassium) minus the sum of the percentage of the maximum recommended values for 3 nutrients to limit (saturated fat, added sugar, and sodium). NRF scores and mean national food prices were calculated per calorie and per US Food and Drug Administration-defined serving. Each of the 9 USDA food groups offered foods of diverse nutritive value and cost. Eggs, dry beans and legumes, and meat and milk products were the lowest-cost sources of protein. Milk and milk products were the lowest-cost sources of calcium, whereas vegetables and fruit were the lowest-cost sources of vitamin C. Milk, potatoes, citrus juices, cereals, and beans had more favorable overall nutrient-to-price ratios than did many vegetables and fruit. Energy-dense grains, sweets, and fats provided most of the calories but fewer nutrients per dollar. One important application of nutrient profile models is to help consumers identify foods that provide optimal nutrition at an affordable cost.
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                Author and article information

                Journal
                Nutrients
                Nutrients
                nutrients
                Nutrients
                MDPI
                2072-6643
                21 October 2019
                October 2019
                : 11
                : 10
                : 2540
                Affiliations
                [1 ]Department of Social and Preventive Epidemiology, School of Public Health, University of Tokyo, Tokyo 113-0033, Japan; fujiwaraay-tky@ 123456umin.ac.jp (A.F.); stssasak@ 123456m.u-tokyo.ac.jp (S.S.)
                [2 ]Nutrition Innovation Centre for Food and Health (NICHE), School of Biomedical Sciences, Ulster University, Coleraine BT52 1SA, UK; mbe.livingstone@ 123456ulster.ac.uk
                Author notes
                [* ]Correspondence: kenmrkm@ 123456m.u-tokyo.ac.jp ; Tel.: +81-3-5841-7872
                Author information
                https://orcid.org/0000-0002-4189-7753
                https://orcid.org/0000-0001-5687-4530
                https://orcid.org/0000-0001-9928-1946
                Article
                nutrients-11-02540
                10.3390/nu11102540
                6836176
                31640242
                52282d9d-e7e7-4b41-84f8-1266887ef7ae
                © 2019 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 19 September 2019
                : 13 October 2019
                Categories
                Article

                Nutrition & Dietetics
                diet quality,hei-2015,nrf9.3,japan,dietary assessment questionnaire
                Nutrition & Dietetics
                diet quality, hei-2015, nrf9.3, japan, dietary assessment questionnaire

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