Development of the Healthy Eating Index-2005.
ABSTRACT The Healthy Eating Index (HEI) is a measure of diet quality as specified by Federal dietary guidance, and publication of the Dietary Guidelines for Americans 2005 necessitated its revision. An interagency working group based the HEI-2005 on the food patterns found in My-Pyramid. Diets that meet the least restrictive of the food-group recommendations, expressed on a per 1,000 calorie basis, receive maximum scores for the nine adequacy components of the index: total fruit (5 points), whole fruit (5 points), total vegetables (5 points), dark green and orange vegetables and legumes (5 points), total grains (5 points), whole grains (5 points), milk (10 points), meat and beans (10 points), and oils (10 points). Lesser amounts are pro-rated linearly. Population probability densities were examined when setting the standards for minimum and maximum scores for the three moderation components: saturated fat (10 points), sodium (10 points), and calories from solid fats, alcoholic beverages (ie, beer, wine, and distilled spirits), and added sugars (20 points). Calories from solid fats, alcoholic beverages, and added sugars is a proxy for the discretionary calorie allowance. The 2005 Dietary Guideline for saturated fat and the Adequate Intake and Tolerable Upper Intake Level for sodium, expressed per 1,000 calories, were used when setting the standards for those components. Intakes between the maximum and minimum standards are pro-rated. The HEI-2005 is a measure of diet quality as described by the key diet-related recommendations of the 2005 Dietary Guidelines. It has a variety of potential uses, including monitoring the diet quality of the US population and subpopulations, evaluation of interventions, and research.
Full-textDOI: · Available from: Patricia M. Guenther, Apr 14, 2015
SourceAvailable from: Diewertje Sluik[Show abstract] [Hide abstract]
ABSTRACT: Nutrient-rich food (NRF) index scores are dietary quality indices based on nutrient density. We studied the design aspects involved in the development and validation of NRF index scores, using the Dutch consumption data and guidelines as an example. We evaluated fifteen NRF index scores against the Dutch Healthy Diet Index (DHD-index), a measure of adherence to the Dutch dietary guidelines, and against energy density. The study population included 2106 adults from the Dutch National Food Consumption Survey 2007–2010. The index scores were composed of beneficial nutrients (protein, fibre, fatty acids, vitamins, minerals), nutrients to limit (saturated fat, sugar, Na) or a combination. Moreover, the influence of methodological decisions was studied, such as the choice of calculation basis (100 g or 100 kcal (418 kJ)). No large differences existed in the prediction of the DHD-index by the fifteen NRF index scores. The score that best predicted the DHD-index included nine beneficial nutrients and three nutrients to limit on a 100-kcal basis, the NRF9.3 with a model R2 of 0·34. The scores were quite robust with respect to sex, BMI and differences in calculation methods. The NRF index scores were correlated with energy density, but nutrient density better predicted the DHD-index than energy density. Consumption of vegetables, cereals and cereal products, and dairy products contributed most to the individual NRF9.3 scores. In conclusion, many methodological considerations underlie the development and evaluation of nutrient density models. These decisions may depend upon the purpose of the model, but should always be based upon scientific, objective and transparent criteria.04/2015; 4(e14):1-9. DOI:10.1017/jns.2015.4
[Show abstract] [Hide abstract]
ABSTRACT: Examine whether use of a grocery list is associated with healthier diet and weight among food desert residents. Cross-sectional analysis of in-person interview data from randomly selected household food shoppers in 2 low-income, primarily African American urban neighborhoods in Pittsburgh, PA with limited access to healthy foods. Multivariate ordinary least-square regressions conducted among 1,372 participants and controlling for sociodemographic factors and other potential confounding variables indicated that although most of the sample (78%) was overweight or obese, consistently using a list was associated with lower body mass index (based on measured height and weight) (adjusted multivariant coefficient = 0.095) and higher dietary quality (based on the Healthy Eating Index-2005) (adjusted multivariant coefficient = 0.103) (P < .05). Shopping with a list may be a useful tool for low-income individuals to improve diet or decrease body mass index. Copyright © 2015 Society for Nutrition Education and Behavior. Published by Elsevier Inc. All rights reserved.05/2015; 47(3):259-264.e1. DOI:10.1016/j.jneb.2015.01.005
[Show abstract] [Hide abstract]
ABSTRACT: The food environment in markets constrains and signals consumers what to purchase. It encompasses availability , affordability, convenience, and desirability of various foods. The effect of income on dietary consumption is always modified by the food environment. Many agricultural interventions aim to improve incomes, increase food availability and reduce food prices. Their effects on nutrition could be better understood if food environment measures helped to explain how additional income is likely to be spent, and how food availability and prices change as a result of large-scale interventions. Additionally, measurement of the food environment could elucidate food access gaps and inform the design of nutrition-sensitive interventions. This paper reviews existing measures of the food environment, and then draws from these tools to suggest ways the food environment could be measured in future studies and monitoring.Food Security 05/2015; DOI:10.1007/s12571-015-0455-8 · 1.64 Impact Factor