Composite index for aggregating nutrient density using food labels: ratio of recommended to restricted food components

What's On the Menu? Towards Predicting Nutritional Quality of Food Environments

Unhealthy diets are a leading cause of major chronic diseases including obesity, diabetes, cancer, and heart disease. Food environments-the physical spaces in which people access and consume food-have the potential to profoundly impact diet and related diseases. We take a step towards better understanding the nutritional quality of food environments by developing MINT: Menu Item to NutrienT model. This model utilizes under-studied data sources on recipes and generic food items, along with state-of-the-art word embedding and deep learning methods, to predict the nutrient density of never-before-seen food items using only their name as input. The model achieves an R 2 = 0.77 , a substantial improvement over comparable models. We illustrate the utility of MINT by applying it to the Los Angeles restaurant food environment, and discover close agreement between predicted and ground truth nutrient density of restaurant menu items. This model represents a significant step towards a policy toolkit needed to precisely identify and target food environments characterized by poor nutritional quality.

Evaluating the Nutritional Properties of Food: A Scoping Review

There are many methods or indicators used for evaluating the nutritional value of foods; however, it is difficult to accurately reflect the comprehensive nutritional value of a food with a single indicator, and a systematic evaluation system is lacking. In this article, we systematically summarize the common evaluation methods and indicators of the nutritional value of foods. The purpose of this review was to establish an evaluation procedure for nutritional properties of foodstuffs and to help scientists choose more direct and economical evaluation methods according to food types or relevant indicators. The procedure involves the selection of a three-level evaluation method that covers the whole spectrum of a food’s nutritional characteristics. It is applicable to scientific research in the fields of agricultural science, food science, nutrition, and so on.

Obesity and food away from home: What drives the socioeconomic gradient in excess body weight?

Rising obesity rates are one of the most challenging public health issues in many emerging economies. To what extent food away from home (FAFH) and its nutritional components are behind this rise is not yet well understood. To address the issue, this paper combines a representative restaurant survey that includes detailed information on the diet quality of the most widely consumed meals and their nutritional components from 1605 restaurants and a representative household survey with anthropometric measures of adult women living in 40 neighborhoods in the Lima Metropolitan Area. One important advantage of the dataset is the fact that nutrition professionals observed the preparation of the meals and that they were subject to a detailed laboratory analysis. Exploiting this data, we examine the differences in nutritional quality of FAFH among 40 neighborhoods of various socioeconomic groups and explore whether these differences can explain part of the observed socioeconomic gradient in excess body weight. The findings indicate that less healthy food in restaurants located in the food environment of the households is significantly associated with higher rates of obesity and overweight. In particular, the high supply and intake of sodium potentially drives higher excess body weight. The study also finds that up to 15 percent of the socioeconomic gradient in obesity is attributable to the restaurant food quality in the food environment of the households.

Towards a Water-Energy-Food (WEF) nexus index: A review of nutrient profile models as a fundamental pillar of food and nutrition security

The Water-Energy-Food (WEF) nexus approach should be promoted as a tool for sustainable management of resources through the interconnection of these three fundamental pillars. Particularly, food security must ensure healthy and balanced diets for everyone, but selecting individual indicators to assess all slants covered by this element is not an easy task. Hence, the objective of this paper is two-fold, to review nutrient profiling (NP) models that allow to categorize foods and evaluate diets based on their nutritional quality, and to choose the most appropriate model to be used within a WEF nexus index. To address this issue, a total of 159 documents were assessed, appraising the geographic distribution, and time evolution of the publications, as well as the characteristics and potential applications of the NP systems. The review concludes that the NRF9.3. model is the most liable option to be used in a WEF nexus index, presenting the best characteristics by means of the definition of scores and thresholds, and the use of an 'across-the-board' criteria and a reference quantity of 100 kcal, alongside offering higher ability to assess diets and foods than the other competitive model (HEI) through the evaluation of nutrients to encourage instead of foods. A secondary outcome of the review is the identification of the NP models as a useful tool to enable institutions with information to establish policies in the field of public health and facilitating the decision-making process according to the current healthy claims.

Menu labeling, calories, and nutrient density: Evidence from chain restaurants

The Food and Drug Administration's menu labeling rule requires chain restaurants to prominently display calories, while leaving other nutritional information (e.g., fat, sodium, sugar) to the request of consumers. We use rich micronutrient data from 257 large chain brands and 24,076 menu items to examine whether calories are correlated with widely used "nutrient profile" scores that measure healthfulness based on nutrient density. We show that calories are indeed statistically significant predictors of nutrient density. However, as a substantive matter, the correlation is highly attenuated (partial R2 < 0.01). Our findings (a) suggest that the promise of calorie labeling to improve nutrient intake quality at restaurants is limited and (b) clarify the basis for transparency of nutrient composition beyond calories to promote healthy menu choices.

100% citrus juice: Nutritional contribution, dietary benefits, and association with anthropometric measures

Citrus juices such as 100% orange (OJ) and grapefruit juice (GJ) are commonly consumed throughout the world. This review examines the contributions of OJ and GJ to nutrient intake, diet quality, and fruit intake, and supports citrus juices as nutrient-dense beverages. This review also explores the research examining associations between OJ and GJ intake and anthropometric measures. Citrus juices are excellent sources of vitamin C and contribute other key nutrients such as potassium, folate, magnesium, and vitamin A. OJ intake has been associated with better diet quality in children and adults. OJ intake has not been associated with adverse effects on weight or other body measures in observational studies in children and adults. In adults, some observational studies report more favorable body mass index or body measure parameters in OJ consumers compared to nonconsumers. Intervention studies in adults report no negative impacts of OJ or GJ consumption on anthropometric measures, although these measures were typically not the primary outcomes examined in the studies. Moderate consumption of citrus juices may provide meaningful nutritional and dietary benefits and do not appear to negatively impact body weight, body composition, or other anthropometric measures in children and adults.

Development of a standardized measure to assess food quality: a proof of concept

Background

Food-based dietary guidelines are promoted to improve diet quality. In applying dietary recommendations, such as the MyPlate, the number of servings in a food group is the unit of measure used to make food selections. However, within each food group, different foods can vary greatly in their nutritional quality despite often having similar energy (caloric) values. This study aimed to develop a novel unit of measure that accounts for both the quantity of energy and the quality of nutrients, as defined by caloric and micronutrient density, respectively, in foods and to demonstrate its usability in identifying high quality foods within a food group.

Methods

A standardized unit of measure reflecting the quality of kilocalories for nutrition (qCaln) was developed through a mathematical function dependent on the energy content (kilocalories per 100 g) and micronutrient density of foods items within a food group. Nutrition composition of 1806 food items was extracted from the USDA nutrient database. For each food item analyzed, qCaln ratios were calculated to compare qCaln to its caloric content. Finally, a case example was developed comparing two plates adapted from the MyPlate.

Results

Examples of food items with highest and lowest qCaln ratios were displayed for five food groups: vegetables, fruits/fruit juices, milk/dairy products, meats/meat alternatives, and breads/cereals. Additionally, the applicability of the qCaln was presented through comparing two plates, adopted from the USDA MyPlate, to show differences in food quality.

Conclusions

The newly developed qCaln measure can be used to rank foods in terms of their nutrient density while accounting for their energy content. The proposed metric can provide consumers, public health professionals, researchers, and policy makers with an easy-to-understand measure of food quality and a practical tool to assess diet quality among individuals and population groups.

Electronic supplementary material

The online version of this article (doi:10.1186/s12937-016-0215-4) contains supplementary material, which is available to authorized users.

Construct and criterion-related validation of nutrient profiling models: A systematic review of the literature

Nutrient profiling (NP) is defined as the science of ranking foods according to their nutritional composition for the purpose of preventing disease or promoting health. The application of NP is ultimately to assist consumers to make healthier food choices, and thus provide a cost effective public health strategy to reduce the incidence of diet-related chronic disease. To our knowledge, no review has assessed the evidence to confirm the validity of NP models. We conducted a systematic review to investigate the construct and criterion-related validity of NP models in ranking food according to their nutritional composition for the purpose of preventing disease and promoting health. We searched peer-reviewed research published to 30 June 2015 and used PUBMED, Global Health (CABI), and SCOPUS databases. Within study bias was assessed using an adapted version of the QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies -2) tool for all diagnostic studies and the Cochrane Collaboration's Risk of Bias tool for all non-diagnostic studies. The GRADE (Grades of Recommendation, Assessment, Development, and Evaluation) approach was used to guide our judgement of the quality of the body of evidence for each outcome measure. From a total of 83 studies, 69 confirmed the construct validity of NP models; however most of these studies contained methodological weaknesses. Six studies used objective external measures to confirm the criterion-related validity of NP models; which inherently improved quality. The overall quality of evidence on the accuracy of NP models was judged to be very low to moderate using the GRADE approach. Many carefully designed studies to establish both construct and criterion-related validity are necessary to authenticate the application of NP models and provide the evidence to support the current definition of NP.

The nutrient density approach to healthy eating: challenges and opportunities

The term 'nutrient density' for foods/beverages has been used loosely to promote the Dietary Guidelines for Americans. The 2010 Dietary Guidelines for Americans defined 'all vegetables, fruits, whole grains, fat-free or low-fat milk and milk products, seafood, lean meats and poultry, eggs, beans and peas (legumes), and nuts and seeds that are prepared without added solid fats, added sugars, and sodium' as nutrient dense. The 2010 Dietary Guidelines for Americans further states that nutrient-dense foods and beverages provide vitamins, minerals and other substances that may have positive health effects with relatively few (kilo)calories or kilojoules. Finally, the definition states nutrients and other beneficial substances have not been 'diluted' by the addition of energy from added solid fats, added sugars or by the solid fats naturally present in the food. However, the Dietary Guidelines Advisory Committee and other scientists have failed to clearly define 'nutrient density' or to provide criteria or indices that specify cut-offs for foods that are nutrient dense. Today, 'nutrient density' is a ubiquitous term used in the scientific literature, policy documents, marketing strategies and consumer messaging. However, the term remains ambiguous without a definitive or universal definition. Classifying or ranking foods according to their nutritional content is known as nutrient profiling. The goal of the present commentary is to address the research gaps that still exist before there can be a consensus on how best to define nutrient density, highlight the situation in the USA and relate this to wider, international efforts in nutrient profiling.

Nutrient density: principles and evaluation tools

Nutrient profiling is the technique of rating or classifying foods on the basis of their nutritional value. Foods that supply relatively more nutrients than calories are defined as nutrient dense. Nutrient profile models calculate the content of key nutrients per 100 g, 100 kcal, or per serving size of food. For maximum effectiveness, nutrient profile models need to be transparent, based on publicly accessible nutrient composition data, and validated against independent measures of a healthy diet. These rigorous scientific standards were applied to the development of the Nutrient-Rich Foods (NRF) family of nutrient profile models. First, the NRF models included nutrients to encourage as well as nutrients to limit. Second, NRF model performance was repeatedly tested against the Healthy Eating Index (HEI), an independent measure of a healthy diet. HEI values were calculated for participants in the 1999-2002 NHANES. Models based on 100 kcal and serving sizes performed better than those based on 100 g. Formulas based on sums and means performed better than those based on ratios. The final NRF9.3 index was based on 9 beneficial nutrients (protein; fiber; vitamins A, C, and E; calcium; iron; potassium; and magnesium) and on 3 nutrients to limit (saturated fat, added sugar, and sodium). Higher NRF9.3 scores were associated with lower energy density and more nutrient-rich diets. The nutrient density of foods, paired with a comprehensive program of consumer education, can become the foundation of dietary recommendations and guidelines.

Nutrition and Cost Comparisons of Select Canned, Frozen, and Fresh Fruits and Vegetables

A common call to action for addressing public health concerns of both obesity and hunger is improving access to and consumption of fruits and vegetables. Previous research has examined the nutritional merits of fresh, frozen, and canned fruits and vegetables. However, there are limited data on the cost-effectiveness of fresh compared with processed—that is, canned and frozen—food. This study examined the nutrition delivered in 8 common vegetables and 10 common fruits across multiple packaging options (fresh, frozen, and canned) relative to average costs. A method of scoring based on nutrient intake recommendations was used to calculate the nutrients per calorie, and average costs were obtained from the US Department of Agriculture’s Economic Research Service. Nutrient scores for the vegetables were similar across the 3 packaging options, whereas canned vegetables had a lower cost per edible cup compared with frozen and fresh. Nutrient scores were variable for the fruits across the 3 packaging options, and canned fruits were either lower or comparably priced per edible cup. The evidence from this study suggests that fruits and vegetables packaged as frozen or canned are cost-effective and nutritious options for meeting daily vegetable and fruit recommendations in the context of a healthy diet.

A content analysis of food references in television programming specifically targeting viewing audiences aged 11 to 14 years

OBJECTIVE

Examine food in cable television programming specifically targeting 11- to 14-year-olds ("tweens").

DESIGN

Content analysis of food-related scenes (FRS)-in which food was shown, mentioned, and/or consumed-in 880 minutes of programming was conducted.

SETTING

Five days of afternoon/early evening television programs on the Disney Channel.

MAIN OUTCOME MEASURES AND ANALYSIS

Food references were compared with USDA MyPlate and classified according to modified Ratio of Recommended to Restricted Food Components.

RESULTS

The authors found 331 FRS, averaging 16.6 scenes/h. Preponderance of FRS was physiological needs (40.7%), followed by display (10%), party (8.5%), social event (8%), and retail store (6.6%). Snacks dominated 41% of FRS, and breakfast, lunch, and dinner were much lower in frequency. Half of FRS was visual only, followed by verbal only. Food references were not congruent with MyPlate recommendations; 42% of food items did not fit into MyPlate food groups. Only 24% of food items were fruit or vegetables, which is considerably less than recommended by MyPlate guidelines. Using modified Ratio of Recommended to Restricted Food Components, 66% of food items scored < 1.0, signifying less nutritious.

CONCLUSIONS AND IMPLICATIONS

Tween television programming regularly includes non-nutritious food, which likely influences tweens' attitudes and behaviors. Television programming may consider past approaches to tobacco smoking and health messages on television. More attention is warranted regarding television programming by nutrition educators, researchers, health professionals, and industry specialists.

Sweet and salty. An assessment of the snacks and beverages sold in vending machines on US post-secondary institution campuses

This study assessed the nutritional quality of snacks and beverages sold in vending machines. The contents of snack and beverage vending machines in 78 buildings on 11 US post-secondary education campuses were surveyed. Of the 2607 snack machine slots surveyed, the most common snacks vended were salty snacks (e.g., chips, pretzels) and sweets (i.e., candy and candy bars). The 1650 beverage machine slots assessed contained twice as many sugar-sweetened beverages as non-calorie-containing beverages. Only two institutions sold both milk and 100% juice in vending machines. The portion of snacks and beverages sold averaged more than 200 cal. Neither snacks nor beverages were nutrient dense. The majority of snacks were low in fiber and high in calories and fat and almost half were high in sugar. Most beverages were high in calories and sugar. This study's findings suggest that vending machines provide limited healthful choices. Findings from benchmark assessments of components of the food environment, like the vending options reported here, can provide valuable input to campus administrators, health services, food service, and students who want to establish campus policies to promote healthful eating.

Nutrient analysis of varying socioeconomic status home food environments in New Jersey

Home food inventories of Oaxacan Mexican-American and African-American families of low-socioeconomic status living in an urban area in New Jersey with at least one child under the age of 12 were conducted using Universal Product Code scanning. The African-American and Oaxacan household food supplies were compared with a sample of White households, also with at least one child under the age of 12, not of low-socioeconomic status. Nutrient Adequacy Ratios for total fat, saturated fat, cholesterol, sodium, total carbohydrate, sugar, dietary fiber, protein, vitamin A, vitamin C, calcium, and iron were used to quantify the adequacy of household food supplies per 2000 cal. The food supplies of the White households had significantly more calcium, vitamin A, and sugar and less total fat than the other two samples. The home food supplies of African-American households contained significantly less vitamin C than White and Oaxacan households. Compared to both other samples, Oaxacan household food supplies were lower in protein, sodium, and iron. Per 2000 cal, African-American households had the lowest supply of nutrients recommended to be maximized (i.e., vitamin A, vitamin C, calcium, iron, protein, and dietary fiber) and highest supply of nutrients to be minimized (i.e., total fat, cholesterol, sodium, and sugar). Overall household food quality scores were lowest for the African-American sample with no differences between Oaxacan and White household food supply quality scores.

Should nutrient profiles be based on 100 g, 100 kcal or serving size?

BACKGROUND/OBJECTIVES

Nutrient profiling of foods is defined as the science of ranking or classifying foods based on their nutrient content. Nutrient profiles can be calculated based on 100 g or 100 kcal of food or on standard serving sizes. The objective of this study was to compare the performance of nutrient profiles based on 100 g, 100 kcal and government-mandated serving sizes, and to identify the optimal base of calculation.

SUBJECTS/METHODS

Nutrient profiles tested were composed of positive subscores based on nutrients to encourage and negative subscores based on nutrients to limit. Alternative profiles, computed using different bases of calculation, were used to rank order 378 commonly consumed foods from a food frequency instrument. Profile performance was tested with respect to the foods' energy density.

RESULTS

Serving sizes, defined by the US Food and Drug Administration as reference amounts customarily consumed (RACC), were inversely linked to energy density of foods. Positive subscores based on 100 kcal were equivalent to those calculated using RACC values. Negative subscores performed better when based on 100 g as opposed to 100 kcal.

CONCLUSIONS

Models based on serving sizes and on 100 kcal were preferable for positive subscores and models based on 100 g of food were preferable for negative subscores. RACC-based profiles may represent an attractive option for the US consumer.

A comparison of nutrient density scores for 100% fruit juices

The 2005 Dietary Guidelines for Americans recommend that consumers choose a variety of nutrient-dense foods. Nutrient density is usually defined as the quantity of nutrients per calorie. Food and nutrition professionals should be aware of the concept of nutrient density, how it might be quantified, and its potential application in food labeling and dietary guidance. This article presents the concept of a nutrient density score and compares nutrient density scores for various 100% fruit juices. One hundred percent fruit juices are popular beverages in the United States, and although they can provide concentrated sources of a variety of nutrients, they can differ considerably in their nutrient profiles. Six methodologies were used to quantify nutrient density and 7 100% fruit juices were included in the analysis: apple, grape, pink grapefruit, white grapefruit, orange, pineapple, and prune. Food composition data were obtained from the USDA National Nutrient Database for Standard Reference, Release 18. Application of the methods resulted in nutrient density scores with a range of values and magnitudes. The relative scores indicated that citrus juices, particularly pink grapefruit and orange juice, were more nutrient dense compared to the other nonfortified 100% juices included in the analysis. Although the methods differed, the relative ranking of the juices based on nutrient density score was similar for each method. Issues to be addressed regarding the development and application of a nutrient density score include those related to food fortification, nutrient bioavailability, and consumer education and behavior.

Developing nutrient profile models: a systematic approach

Objective

Nutrient profiling can be defined as the ‘the science of categorising foods according to their nutritional composition’. The purpose of the present paper is to describe a systematic and logical approach to nutrient profiling.

Design

A seven-stage decision-making process is proposed and, as an illustration of how the approach might operate in practice, the development of a nutrient profiling model for the purpose of highlighting breakfast cereals that are ‘high in fat, sugar or salt’ is described.

Results

The nutrient profile model developed for this paper calculates scores for foods using a simple equation. It enables breakfast cereals to be compared with each other and with other foods eaten at breakfast.

Conclusion

Nutrient profiling is not new, but hitherto most nutrient profiling models have been developed in an unsystematic and illogical fashion. Different nutrient profiling models are needed for different purposes but a key requirement should be that they are developed using a systematic, transparent and logical process. This paper provides an example of such a process; approaches to validating nutrient profiling models are described elsewhere.

Testing nutrient profile models using data from a survey of nutrition professionals

Objective

To compare nutrient profile models with a standard ranking of 120 foods.

Design

Over 700 nutrition professionals were asked to categorise 120 foods into one of six positions on the basis of their healthiness. These categorisations were used to produce a standard ranking of the 120 foods. The standard ranking was compared with the results of applying eight different nutrient profile models to the 120 foods: Models SSCg3d and WXYfm developed for the UK Food Standards Agency, the Nutritious Food Index, the Ratio of Recommended to Restricted nutrients, the Naturally Nutrient Rich score, the Australian Heart Foundation's Tick scheme, the American Heart Association's heart-check mark and the Netherlands tripartite classification model for foods. Rank correlation was assessed for continuous models, and dependence was assessed for categorical models.

Results

The continuous models each showed good correlation with the standard ranking (Spearman's ρ = 0.6–0.8). The categorical models achieved high χ2 results, indicating a high level of dependence between the nutrition professionals' and the models' categorisations (P < 0.001). Models SSCg3d and WXYfm achieved higher scores than the other models, implying a greater agreement with the standard ranking of foods.

Conclusions

The results suggest that Models SSCg3d and WXYfm rank and categorise foods in accordance with the views of nutrition professionals.

Nutrient profiling: comparison and critical analysis of existing systems

Background

Nutrient profiling systems aim at positioning foodstuffs relative to each other according to their contribution to a balanced diet. The accuracy and performance of methodologies are still debated. We present here a critical analysis of the structure and efficiency of the current schemes.

Methods

The literature survey detected only four systems addressing the issue on an ‘across the board’ approach and with enough detail to enable analysis. The building principles of these systems were compared and their performance was estimated via their classification of a series of 125 foodstuffs on the basis of nutritional composition. These classifications were compared with one another and with an empirical classification by expert nutritionists.

Results

All systems gave a similar overview, with fruits and vegetables ranked as the most favourable foods and fatty and sugary foods as the least favourable ones, but numerous discrepancies existed in every system, mainly related to their choice of nutrients and thresholds. The FSA scoring system seemed the most consistent approach, although it still generated some questionable rankings. Expert classification did not clearly validate any scheme, and cannot be considered as a true reference.

Conclusion

Nutrient profiling systems are confirmed to be powerful tools to translate nutritional information related to the whole diet into the level of individual foods. However, the performance of the existing schemes remains moderate. Alternative approaches, such as considering food categories or introducing more stringent validation steps by a panel of expert nutritionists, could be ways to reach more efficient and consensual tools.

Concept of a nutritious food: toward a nutrient density score

The American diet is said to be increasingly energy-rich but nutrient-poor. To help improve the nutrient-to-energy ratio, the 2005 Dietary Guidelines for Americans recommend that consumers replace some foods in their diets with more nutrient-dense options. Such dietary guidance presupposes the existence of a nutrient density standard. However, a review of the literature shows that the concept of a nutritious food is not based on any consistent standards or criteria. In many cases, healthful foods are defined by the absence of problematic ingredients-fat, sugar, and sodium-rather than by the presence of any beneficial nutrients they might contain. Past attempts to quantify the nutrient density of foods have been based on a variety of calories-to-nutrient scores, nutrients-per-calorie indexes, and nutrient-to-nutrient ratios. The naturally nutrient rich (NNR) score, which is based on mean percentage daily values (DVs) for 14 nutrients in 2000 kcal food, can be used to assign nutrient density values to foods within and across food groups. Use of the NNR score allows consumers to identify and select nutrient-dense foods while permitting some flexibility where the discretionary calories are concerned. This approach has implications for food labeling, nutritional policy making, and consumer education. The Food and Drug Administration has considered approving nutrient claims based on the ratio of a beneficial nutrient to the food's energy content, as opposed to a specified minimum amount of a nutrient per serving size. Given the current dietary trends, the nutrient density approach can be a valuable tool for nutrition education and dietary guidance.