Food Compass is a nutrient profiling system using expanded characteristics for assessing healthfulness of foods

Switches in food and beverage product purchases can reduce greenhouse gas emissions in Australia

Switching between similar food and beverage products may reduce greenhouse gas emissions (GHGe). Here, using consumer data linked to 23,550 product-specific GHGe values, we estimated annual GHGe attributable to product purchases consumed at home in Australia and calculated reductions from specific switches. Potential changes to mean Health Star Rating, mean energy density and the proportion of ultraprocessed foods purchased were assessed. Approximately 31 million tonnes of GHGe were attributable to products consumed at home in 2019, the three highest contributors of GHGe being 'meat and meat products' (49%), 'dairy' (17%) and 'non-alcoholic beverages' (16%). Switching higher-emission products for 'very similar' lower-emission products could reduce total emissions by 26%. Switches to 'less similar' lower-emission products could lead to a 71% reduction. Switches had little impact on the average Health Star Rating, energy density of purchases and proportion of ultraprocessed foods purchased. Directing manufacturing and marketing towards lower-environmental-impact products and signposting such options to consumers are key.

Development and Validation of the Meiji Nutritional Profiling System (Meiji NPS) to Address Dietary Needs of Adults and Older Adults in Japan

This study introduces the Meiji Nutritional Profiling System (Meiji NPS), which was specifically designed to respond to age-related shifts in nutrient requirements among Japanese adults (<65 years old) and older adults (≥65 years old). Japan has one of the most aged societies in the world. The health issues of interest are malnutrition and lifestyle-related diseases among adults and frailty among older adults. Two versions of the NPS were developed based on nutrients to encourage (protein, dietary fibers, calcium, iron, and vitamin D), food groups to encourage (fruits, vegetables, nuts, legumes, and dairy), and nutrients to limit (energy, saturated fatty acids, sugars, and salt equivalents). The Meiji NPS for older adults did not include iron or saturated fatty acids. The algorithms were based on the Nutrient-Rich Foods Index (NRF). The convergent validity between the Meiji NPS and the existing NPSs for the same foods was confirmed using Spearman's correlation coefficients (NRF: r = 0.67 for adults and r = 0.60 for older adults; Health Star Rating: r = 0.64 for adults and r = 0.61 for older adults). The Meiji NPS may be useful for nutritional evaluation and reformulation of food products, tailored to adults and older adults to ameliorate health issues in Japan.

Food Compass and the challenge of sustainability on the route towards healthful diets

In order to tackle the global increase in overweight and obesity prevalence, several nutrient profiling systems have been developed; among others, Food Compass Score (FCS) has been designed to encompass multiple domains of food healthfulness. However, environmental sustainability of healthy diets is another crucial dimension which should not be overlooked in the context of human health. The aim of the present study is to assess the association between healthiness and environmental sustainability of food items, using the FCS and Agribalyse databases, respectively. A total of 806 matching food items were identified, grouped in 12 food categories; within each category, differences in median Z-scores between FCS and Single Environmental Footprint (EF) Score were assessed. While Fruits, Legumes and Nuts, Mixed foods, Meat Poultry and Eggs (MPE), Savory and Sweets, and Vegetables showed statistically significant differences (all p < 0.001), Beverages (p = 0.361), Dairy (p = 0.092), Fats and Oils (p = 0.594), Grains (p = 0.436), Sauce and Condiments (p = 0.093), and Seafood (p = 0.241) had similar Food Compass and Single EF Z-scores distributions. These findings underscore a relevant lack of difference between healthfulness and environmental impact of some prominent food categories, such as Grains and Seafood. Therefore, we suggest matching nutrient profiling systems with adequate environmental sustainability indices.

Dietary indices underpinning front-of-pack nutrition labels and health outcomes: a systematic review and meta-analysis of prospective cohort studies

BACKGROUND

Nutrient profiling systems are increasingly used to characterize the healthfulness of foods for front-of-package (FOP) labeling, which have been proposed as an effective public health strategy to help people make healthier food choices.

OBJECTIVE

This study aimed to review available evidence from cohort studies that evaluated the association of dietary indices underpinning FOP nutrition labels with all-cause mortality and incidence of cardiovascular diseases (CVDs) or cancer.

METHODS

PubMed, Web of Science, and Scopus were systematically searched up to October 2023. We included articles if they were prospective cohort studies, if the exposure was any dietary index underpinning FOP nutrition labels [e.g., the modified Food Standard Agency-Nutrient Profiling System (FSAm-NPS) and the Health Star Rating System], and if outcomes were all-cause mortality or incidence of or mortality due to CVD and cancer. Random-effects models were used to calculate the pooled hazard ratios (HRs) and 95% CIs.

RESULTS

We identified 11 records (7 unique prospective studies), which were included in the systematic review. The meta-analysis comprised 8 studies analyzing the FSAm-NPS dietary index (DI) as exposure. The pooled HRs associated with a 2-unit increase in the FSAm-NPS DI of all-cause mortality, CVD, and cancer risk were 1.06 (95% confidence interval [CI]: 0.99, 1.13; I2: 80%), 1.08 (95% CI: 1.00, 1.18; I2: 70%), and 1.09 (95% CI: 1.00, 1.19; I2: 77%), respectively. The Chilean Warning Label score and the Health Star Rating systems were examined by 1 study each and were significantly associated with the outcomes.

CONCLUSIONS

DIs underpinning most common FOP nutrition labels and reflecting nutrient-poor diets show a tendency toward an increased incidence of CVD and cancer, but the observed effects are quite modest in magnitude. Further studies at the population level are needed to support the widely shared hypothesis that FOP labels, possibly in conjunction with other interventions, may contribute to reduce noncommunicable disease risk. This meta-analysis was registered at PROSPERO as CRD42021292625.

Evaluating the water footprint and nutritional quality of takeaway dishes for selected large cities in China

The takeaway food and delivery market is developing rapidly in China, raising concerns about the impacts of takeaway dishes on both health and the environment. Here, we compare the environmental impact and nutritional performance of 32 popular takeaway dishes, which stem from the top 10 best-selling takeaway dishes in 10 large cities in China. We select water footprint and water scarcity footprint indicators to represent the environmental impact, and the Food Compass Score to measure nutritional quality. Our results show that 24 out of 32 takeaway dishes contains meat, which has a higher water footprint. The inhabitants of water stressed Chinese cities, mainly located in northern China, tend to favor meat dishes, resulting in a larger water scarcity footprint. The results also highlight the lower nutrition quality of the majority of takeaway dishes, with only three takeaway dishes meeting acceptable environmental and nutritional standards. Our study highlights the importance of analyzing dishes rather than individual foods, which can facilitate sustainable dietary choices for consumers.

Nutri-Score 2023 update

In 2023, the algorithm underlying the Nutri-Score front-of-pack label was updated to better align with food-based dietary guidelines (FBDGs) across countries engaged in the system. On the basis of a comparison of FBDGs and literature reviews with the current Nutri-Score classification, modification scenarios were developed and tested in nutritional composition databases of branded products in four countries. The updated Nutri-Score nutrient profile model allows a better discrimination between products, in closer alignment with FBDGs, while the updated algorithm adopts a stricter approach for products that are high in components of concern (including non-nutritive sweeteners) and low in favourable dietary components. The updated Nutri-Score algorithm increases the alignment between the front-of-pack label system and FBDGs, strengthening its potential as a complementary public health tool in an international perspective.

Food Compass Score predicts incident cardiovascular disease: The ATTICA cohort study (2002-2022)

BACKGROUND

The Food Compass Score (FCS) is a novel nutrient profiling system, which evaluates food and diet quality. The present study aimed to prospectively assess the relationship of FCS with short-term (10 years) and long-term (20 years) cardiovascular disease (CVD) incidence and to explore whether this relationship is modified by long-term adherence to a Mediterranean type diet (MTD).

METHODS

Volunteers of the ATTICA cohort study, with complete data for the calculation of FCS and incident CVD were included (n = 759). Development of CVD was determined at 10 and 20 years after baseline. Dietary intake was assessed through a validated food frequency questionnaire. The FCS was calculated for each participant based on the published algorithm. Long-term adherence to a MTD was evaluated through MedDietScore.

RESULTS

FCS was inversely associated with CVD incidence (hazard ratio [HR] for 20-year follow-up = 0.97, 95% confidence interval [CI] = 0.95-0.99; HR for 10-year follow-up = 0.98, 95% CI = 0.96-1.01) in the total sample, as well as in those with a high baseline adherence to a MTD (HR for 20-year follow-up = 0.96, 95% CI = 0.93-0.99; HR for 10-year follow-up = 0.98, 95% CI = 0.95-1.02). FCS was also inversely associated with CVD risk in those who went away from the MTD (HR = 0.97, 95% CI = 0.96-0.99).

CONCLUSIONS

FCS, a novel tool for assessing overall diet quality, was also found to be useful in identifying potential CVD candidates in a long-term period, even in populations with good background dietary habits, such as those following a MTD.

Criterion validation of nutrient profiling systems: a systematic review and meta-analysis

BACKGROUND

Nutrient profiling systems (NPSs) use algorithms to evaluate the nutritional quality of foods and beverages. Criterion validation, which assesses the relationship between consuming foods rated as healthier by the NPS and objective measures of health, is essential to ensure the accuracy of NPSs.

OBJECTIVE

We examined and compared NPSs that have undergone criterion validity testing in relation to diet-related disease risk and risk markers.

METHODS

Academic databases were searched for prospective cohort and cross-sectional studies published before November, 2022. NPSs were eligible if they incorporated multiple nutrients or food components using an algorithm to determine an overall summary indicator (e.g., a score or rank) for individual foods. Studies were included if they assessed the criterion validity of an eligible NPS. Validation evidence was first summarized in narrative form by NPS, with random effects meta-analysis where ≥2 prospective cohort studies assessed the same NPS and outcomes.

RESULTS

Of 4519 publications identified, 29 describing 9 NPSs were included in the review. The Nutri-Score NPS was assessed as having substantial criterion validation evidence. Highest compared with lowest diet quality as defined by the Nutri-Score was associated with significantly lower risk of cardiovascular disease (hazard ratio [HR]: 0.74; 95% confidence interval [CI]: 0.59, 0.93; n = 6), cancer (HR: 0.75; 95% CI: 0.59, 0.94; n = 5), all-cause mortality (HR: 0.74; 95% CI; 0.59, 0.91; n = 4) and change in body mass index (HR: 0.68; 95% CI: 0.50, 0.92; n = 3). The Food Standards Agency NPS, Health Star Rating, Nutrient Profiling Scoring Criterion, Food Compass, Overall Nutrition Quality Index, and the Nutrient-Rich Food Index were determined as having intermediate criterion validation evidence. Two other NPSs were determined as having limited criterion validation evidence.

CONCLUSIONS

We found limited criterion validation studies compared with the number of NPSs estimated to exist. Greater emphasis on conducting and reporting on criterion validation studies across varied contexts may improve the confidence in existing NPSs.

Landscape analysis of environmental, social and governance (ESG) investing metrics for consumer nutrition and health in the food and beverage sector

Introduction

The private sector plays a critical role in influencing food choices and health outcomes of consumers. Among private sector actors, investors are a powerful yet underutilised stakeholder for driving scalable public health impact. There are systems to facilitate investors' involvement, notably environmental, social and governance (ESG) investing, which is well placed to include an assessment of business risks to social well-being. However, nutrition efforts within the ESG agenda (ESG-Nutrition) are nascent. We aimed to critically assess the strength of existing ESG-Nutrition metrics to advance the science of measuring business impacts on consumer nutrition and health.

Methods

ESG-Nutrition metrics were extracted from eight ESG frameworks and categorised across four domains: product portfolio healthfulness; product distribution and equity; product marketing and labelling; and nutrition-related governance. The strength of each metric was evaluated and scored 1-3 (best), independently by two researchers, based on six attributes: materiality, objectivity, alignment, activity, resolution and verifiability. The total score (range 6-18) and intercorrelation for each attribute was calculated.

Results

Across 529 metrics, most related to product marketing and labelling (n=230, 43.5%), followed by product healthfulness (n=126, 23.8%), nutrition-related governance (n=108, 20.4%) and product distribution and equity (n=65, 12.3%). Across all metrics, average total score was 10.94 (1.58), with average attribute scoring highest for verifiability (mean: 2.36 (SD: 0.57)), objectivity (2.11 (0.61)) and materiality (2.01 (0.68)) and lowest for activity (1.83 (0.74)), alignment (1.37 (0.67)) and resolution (1.26 (0.65)). Most intercorrelations were null, suggesting attributes were measuring distinct characteristics of each metric. Significant heterogeneity across domains and frameworks was also observed.

Conclusions

This research identifies a range of nutrition-related metrics used in ESG frameworks with respect to food companies, but with substantial heterogeneity in relevant nutrition domains covered and strength of each metric. Efforts are required to improve the quality of metrics across frameworks, establish standardised reporting and align these with investor priorities.

Comparing product healthiness according to the Health Star Rating and the NOVA classification system and implications for food labelling systems: An analysis of 25 486 products in Australia

We investigated the extent of alignment between 'healthiness' defined by a food classification system that classifies foods and beverages primarily by their nutrient composition, the Health Star Rating (HSR) and a system that considers only the degree of processing of the product, the NOVA classification system. We used data for 25 486 products contained within the George Institute for Global Health's Australian 2022 FoodSwitch Dataset. Agreement between the two systems in the proportion of products classified as 'healthier' (HSR ≥3.5 or NOVA group 1-3) or 'less healthy' (HSR <3.5 or NOVA group 4) was assessed using the κ statistic. There was 'fair' agreement (κ = 0.30, 95%CI: 0.29-0.31) between both systems in the proportion of all products classified as healthier or less healthy. Approximately one-third (n = 8729) of all products were defined as 'discordant', including 34.3% (n = 5620) of NOVA group 4 products with HSR ≥3.5 (commonly convenience foods, sports/diet foods, meat alternatives, as well as products containing non-sugar sweeteners) and 34.1% (n = 3109) of NOVA group 1-3 products with HSR <3.5 (commonly single-ingredient foods such as sugars/syrups, full-fat dairy and products specially produced to contain no ultra-processed ingredients). Our analysis strengthens the evidence for the similarities and differences in product healthiness according to a nutrient-based classification system and a processing-based classification system. Although the systems' classifications align for the majority of food and beverage products, the discordance found for some product categories indicates potential for confusion if systems are deployed alongside each other within food policies.

Sustainable healthy diet modeling for a plant-based dietary transitioning in the United States

The potential environmental and nutritional benefits of plant-based dietary shifts require thorough investigation to outline suitable routes to achieve these benefits. Whereas dietary consumption is usually in composite forms, sustainable healthy diet assessments have not adequately addressed composite diets. In this study, we build on available data in the Food4HealthyLife calculator to develop 3 dietary concepts (M) containing 24 model composite diet scenarios (S) assessed for their environmental and nutritional performances. The Health Nutritional Index (HENI) and Food Compass scoring systems were used for nutritional quality profiling and estimates of environmental impact were derived from previously reported midpoint impact values for foods listed in the What We Eat in America database. The diets were ranked using the Kruskal‒Wallis nonparametric test, and a dual-scale data chart was employed for a trade-off analysis to identify the optimal composite diet scenario. The results showcased a distinct variation in ranks for each scenario on the environment and nutrition scales, describing an inherent nonlinear relationship between environmental and nutritional performances. However, trade-off analysis revealed a diet with 10% legumes, 0.11% red meat, 0.28% processed meat and 2.81% white meat could reduce global warming by 54.72% while yielding a diet quality of 74.13 on the Food Compass Scoring system. These observations provide an interesting forecast of the benefits of transitioning to an optimal plant- and animal-based dieting pattern, which advances global nutritional needs and environmental stewardship among consumers.

Food Compass Score and its association with inflammatory markers and homocysteine in cardiovascular disease-free adults: a cross-sectional analysis of the ATTICA epidemiological study

BACKGROUND/OBJECTIVES

Several nutrient profiling systems have been developed to assist in food choices and policy. Food Compass Score (FCS) is a novel holistic food score assessing 54 parameters. The aim was to assess the relation of FCS with inflammatory and lipid markers in cardiovascular disease-free volunteers.

SUBJECTS/METHODS

Information from the ATTICA epidemiological study participants, with complete data on lipid, inflammatory markers and dietary intake were studied (n = 1018). C-reactive protein (CRP) and amyloid A were determined by immunonephelometry, fibrinogen by nephelometry, homocysteine by fluorometry, while tumor necrosis factor-a (TNF-a), interleukin-6 (IL-6), adiponectin and leptin were determined by ELISA in fasting blood samples. Dietary intake was assessed through a semi-quantitative validated food frequency questionnaire. Each food was assigned a FCS value from the published values and then individual's FCS values were calculated.

RESULTS

Mean FCS was 56 (standard deviation: 5.7) and it was similar in men and women. FCS was inversely correlated with age (r = -0.06, p = 0.03). In multiple linear regression models, FCS was inversely associated with CRP (-0.03, 0.01), TNF-a (-0.04, 0.01), amyloid A (-0.10, 0.04) and homocysteine (-0.09, 0.04) (b coefficients, standard errors, all p < 0.05) and was not associated with IL-6, fibrinogen, adiponectin, leptin, or lipids levels (all p > 0.05).

CONCLUSIONS

The inverse correlations of the FCS with inflammatory markers suggest that a diet containing foods with high FCS might be protective against inflammation process. Our results support the usefulness of the FCS, but future studies should evaluate its relation to cardiovascular and other inflammation-related chronic diseases.

The Longitudinal Effect of Ultra-Processed Food on the Development of Dyslipidemia/Obesity as Assessed by the NOVA System and Food Compass Score

SCOPE

Ultra-processing food (UPF) has been a nutrition and health interest. This study is aimed to investigate the association between UPF consumption and the risk of obesity or dyslipidemia.

METHODS AND RESULTS

This study is performed using an ongoing cohort study including 17 310 individuals aged ≥40 years in South Korea. UPF is categorized by the NOVA system and FCS, respectively. After an average 5-year follow-up, there is a positive association between NOVA-defined UPF and dyslipidemia. The risk of the Q4 group is almost 20% higher than that of the Q1 group (men, adjusted HR = 1.209 [95% CI 1.039-1.407], women, adjusted HR = 1.195 [95% CI 1.096-1.303]). Consuming high-FCS foods (less processed and healthier foods) show a lower risk for dyslipidemia in both sexes and lower obesity risk in women compared to low-FCS consumption (men, dyslipidemia, adjusted HR = 0.857 [95% CI 0.744-0.988]; women, dyslipidemia, adjusted HR = 0.919 [95% CI 0.850-0.993], obesity, adjusted HR = 0.759 [95% CI 0.628-0.916]).

CONCLUSION

Higher UPF intakes assessed by the NOVA system and FCS are associated with increased incidences of dyslipidemia and obesity. Furthermore, NOVA-defined UPF shows a statistically significant negative association with AMED score, indicating poor diet quality.

Beyond ultra-processed: considering the future role of food processing in human health

Food-based dietary guidelines have been the basis of public health recommendations for over half a century, but more recently, there has been a trend to classify the health properties of food not by its nutrient composition, but by the degree to which it has been processed. This concept has been supported by many association studies, narrative reviews and the findings from one randomised controlled feeding trial, which demonstrated the sustained effect of ultra-processed diets on increasing both energy intake and body weight. This has led to widespread speculation as to specific features of ultra-processed foods that promote increased energy intakes. Rising interest in the ultra-processed topic has led to proposals to include guidance and restrictions on the consumption of processed foods in national dietary guidelines, with some countries encouraging consumers to avoid highly processed foods completely, and only choose minimally processed foods. However, there remains a lack of consensus on the role of processed foods in human health when faced with the challenges of securing the food supply for a growing global population, that is, healthy, affordable and sustainable. There has also been criticism of the subjective nature of definitions used to differentiate foods by their degree of processing, and there is currently a lack of empirical data to support a clear mechanism by which highly processed foods promote greater energy intakes. Recommendations to avoid all highly processed foods are potentially harmful if they remove affordable sources of nutrients and will be impractical for most when an estimated two-thirds of current energy purchased are from processed or ultra-processed foods. The current review highlights some considerations when interpreting the dietary association studies that link processed food intake to health and offers a critique on some of the mechanisms proposed to explain the link between ultra-processed food and poor health. Recent research suggests a combination of higher energy density and faster meal eating rates are likely to influence meal size and energy intakes from processed foods and offers new perspectives on how to manage this in the future. In going beyond the ultra-processed debate, the aim is to summarise some important considerations when interpreting existing data and identify the important gaps for future research on the role of processed food in health.

An integrative analytical framework to identify healthy, impactful, and equitable foods: a case study on 100% orange juice

To identify healthy, impactful, and equitable foods, we combined health scores from six diverse nutrient profiling systems (NPS) into a meta-framework (meta-NPS) and paired this with dietary guideline adherence assessment via multilevel regression and poststratification. In a case-study format, a commonly debated beverage formulation - 100% orange juice (OJ) - was chosen to showcase the utility and depth of our framework, systematically scoring high across multiple food systems (i.e. a Meta-Score percentile = 93rd and Stability percentile = 75th) and leading to an expected increase of US dietary fruit guideline adherence by ∼10%. Moreover, the increased adherence varies across the 300 sociodemographic strata, with the benefit patterns being sensitive to absolute or relative quantification of the difference of adherence affected by OJ. In sum, the adaptable, integrative framework we established deepens the science of nutrient profiling and dietary guideline adherence assessment while shedding light on the nuances of defining equitable health effects.

Scoping review of the association of plant-based diet quality with health outcomes

Introduction

The association of plant-based dietary patterns with health outcomes has traditionally been assessed without considering nutritional value. The plant-based dietary index (PDI), first published in 2016, overcomes this limitation with both a healthful PDI (hPDI) and an unhealthful PDI (uPDI), based on the quality of plant foods consumed plus the frequency of animal foods. We sought to summarize the breadth of research using the hPDI and uPDI to gain insight into how the quality of plant-based dietary patterns might be associated with health outcomes.

Methods

Scoping review of studies that used the PDI, hPDI, or uPDI to report associations with health outcomes. Multiple databases were searched from 2010 through April 2023 with 2 authors independently assessing eligibility and extracting data. In addition to assessing the association of the indices to health outcomes, we determined the frequency of concordant or discordant findings for hPDI versus PDI and for hPDI versus uPDI.

Results

We included 95 articles (54% longitudinal, 37% cross-sectional, and 9% case-control) with a median sample size of 3,646. Higher hPDI levels were associated with favorable health outcomes in 36% of comparisons (most often for obesity, mortality, diabetes, cardiovascular disease, and psychiatric disorders), compared to 25% for the PDI and only 2% for the uPDI. Conversely, higher levels of the uPDI were associated with unfavorable health outcomes in 33% of comparisons, in contrast to under 1% for the hPDI and 2% for the PDI. When the hPDI association to an outcome was discordant with the uPDI or PDI, the significance and directionality always favored the hPDI over the uPDI, and nearly always favored the hPDI over the PDI.

Discussion

Dietary indices that account for the quality of plant foods can show health benefits that might be missed by a generic plant-based index. A greater focus on the quality of plant foods could improve nutrition guidelines, raise awareness about the benefits of adding unrefined plant foods to the diet, and empower consumers to make incremental additions of such foods to displace unhealthy foods. We anticipate increasing use of indices that address food quality in future research.

Are single global warming potential impact assessments adequate for carbon footprints of agri-food systems?

The vast majority of agri-food climate-based sustainability analyses use global warming potential (GWP100) as an impact assessment, usually in isolation; however, in recent years, discussions have criticised the 'across-the-board' application of GWP100 in Life Cycle Assessments (LCAs), particularly of food systems which generate large amounts of methane (CH4) and considered whether reporting additional and/or alternative metrics may be more applicable to certain circumstances or research questions (e.g. Global Temperature Change Potential (GTP)). This paper reports a largescale sensitivity analysis using a pasture-based beef production system (a high producer of CH4 emissions) as an exemplar to compare various climatatic impact assessments: CO2-equivalents using GWP100 and GTP100, and 'CO2-warming-equivalents' using 'GWP Star', or GWP*. The inventory for this system was compiled using data from the UK Research and Innovation National Capability, the North Wyke Farm Platform, in Devon, SW England. LCAs can have an important bearing on: (i) policymakers' decisions; (ii) farmer management decisions; (iii) consumers' purchasing habits; and (iv) wider perceptions of whether certain activities can be considered 'sustainable' or not; it is, therefore, the responsibility of LCA practitioners and scientists to ensure that subjective decisions are tested as robustly as possible through appropriate sensitivity and uncertainty analyses. We demonstrate herein that the choice of climate impact assessment has dramatic effects on interpretation, with GWP100 and GTP100 producing substantially different results due to their different treatments of CH4 in the context of carbon dioxide (CO2) equivalents. Given its dynamic nature and previously proven strong correspondence with climate models, out of the three assessments covered, GWP* provides the most complete coverage of the temporal evolution of temperature change for different greenhouse gas emissions. We extend previous discussions on the limitations of static emission metrics and encourage LCA practitioners to consider due care and attention where additional information or dynamic approaches may prove superior, scientifically speaking, particularly in cases of decision support.

A Little Bird Told Me… Nutri-Score Panoramas from a Flight over Europe, Connecting Science and Society

Within the Farm to Fork Strategy, the European Commission ask for a unified Front Of Pack nutritional label for food to be used at the European level. The scientific debate identified the Nutri-Score (NS) as the most promising candidate, but within the political discussion, some Member States brought to attention several issues related to its introduction. This misalignment led to a postponement of the final decision. With the aim to shed some light on the current stances and contribute to the forthcoming debate, the objective of the present work is to understand to what extent scientific research addresses the issues raised by the general public. We applied a structural topic model to tweets from four European countries (France, Germany, Italy, Spain) and to abstracts of scientific papers, all dealing with the NS topic. Different aspects of the NS debate are discussed in different countries, but scientific research, while addressing some of them (e.g., the comparison between NS and other labels), disregards others (e.g., relations between NS and traditional products). It is advisable, therefore, to widen the scope of NS research to properly address the concerns of European society and to provide policymakers with robust evidence to support their decisions.

US Policies That Define Foods for Junk Food Taxes, 1991-2021

Policy Points Suboptimal diet is a leading cause of mortality and morbidity in the United States. Excise taxes on junk food are not widely utilized in the United States. The development of a workable definition of the food to be taxed is a substantial barrier to implementation. Three decades of legislative and regulatory definitions of food for taxes and related purposes provide insight into methods to characterize food to advance new policies. Defining policies through Product Categories combined with Nutrients or Processing may be a method to identify foods for health-related goals.

CONTEXT

Suboptimal diet is a substantial contributor to weight gain, cardiometabolic diseases, and certain cancers. Junk food taxes can raise the price of the taxed product to reduce consumption and the revenue can be used to invest in low-resource communities. Taxes on junk food are administratively and legally feasible but no definition of "junk food" has been established.

METHODS

To identify legislative and regulatory definitions characterizing food for tax and other related purposes, this research used Lexis+ and the NOURISHING policy database to identify federal, state, territorial, and Washington DC statutes, regulations, and bills (collectively denoted as "policies") defining and characterizing food for tax and related policies, 1991-2021.

FINDINGS

This research identified and evaluated 47 unique laws and bills that defined food through one or more of the following criteria: Product Category (20 definitions), Processing (4 definitions), Product intertwined with Processing (19 definitions), Place (12 definitions), Nutrients (9 definitions), and Serving Size (7 definitions). Of the 47 policies, 26 used more than one criterion to define food categories, especially those with nutrition-related goals. Policy goals included taxing foods (snack, healthy, unhealthy, or processed foods), exempting foods from taxation (snack, healthy, unhealthy, or unprocessed foods), exempting homemade or farm-made foods from state and local retail regulations, and supporting federal nutrition assistance objectives. Policies based on Product Categories alone differentiated between necessity/staple foods on the one hand and nonnecessity/nonstaple foods on the other.

CONCLUSIONS

In order to specifically identify unhealthy food, policies commonly included a combination of Product Category, Processing, and/or Nutrient criteria. Explanations for repealed state sales tax laws on snack foods identified retailers' difficulty pinpointing which specific foods were subject to the tax as a barrier to implementation. An excise tax assessed on manufacturers or distributors of junk food is a method to overcome this barrier and may be warranted.

Innovative financing for nutrition

Given the constraints of both overseas development aid and domestic financing for nutrition, innovative financing is critical-yet nutrition lags behind other sectors in catalysing it. Here, we argue that the framing for nutrition must evolve and critical actions must be taken to generate more money for nutrition and more nutrition for money. Food systems hold some of the most powerful opportunities to improve human and planetary health while increasing productivity-and the private sector has a key role to play in this.

Perspective: Nutrition’s Next Chapter – Bioactive Gaps & the Microbiome-Mitochondria Axis

Food has the power to heal. Our bodies transform and are transformed by the elements in food and the adage that we are what we eat is figuratively and literally true. Twentieth century nutrition science focused on decoding the processes and building blocks of this transformation -- the proteins, fats, carbohydrates, vitamins, and minerals. Twenty-first century nutrition science is aimed at better understanding the increasingly appreciated bioactives within the food matrix that help regulate this transformation - fibers, phytonutrients, bioactive fats, and ferments. Our microbiome and the mitochondria play a key function in orchestrating the role of bioactives in health and are inspiring next-generation nutritional approaches for addressing over- and undernutrition.

The Metabolic Matrix: Re-engineering ultraprocessed foods to feed the gut, protect the liver, and support the brain

Ultraprocessed food is established as a metabolic disruptor acting to increase adiposity, reduce mitochondrial efficiency, drive insulin resistance, alter growth, and contribute to human morbidity and mortality. Consumer packaged goods (CPG) companies are beginning to understand the detrimental impact of the food they market, and have employed substitution strategies to reduce salt, sugar, and fat. However, the harms of ultraprocessed foods are far more complex than any single component, and are not ameliorated by such simple substitutions. Over the past 2 years, the authors have worked with the Kuwaiti Danish Dairy Company (KDD) to conduct a comprehensive scientific evaluation of their entire commercial food and beverage portfolio. Assay of the macronutrients, micronutrients, additives, and toxins contained in each of their products was undertaken to determine the precise nature of each product’s ingredients as well as the health impacts of processing. The authors formed a Scientific Advisory Team (SAT) and developed a tiered “Metabolic Matrix” founded in three science-based principles: (1) protect the liver, (2) feed the gut, and (3) support the brain. The Metabolic Matrix categorizes each product and provides the criteria, metrics, and recommendations for improvement or reformulation. Real-time consultation with the KDD Executive and Operations teams was vital to see these procedures through to fruition. This scientific exercise has enabled KDD to lay the groundwork for improving the health, well-being, and sustainability of their entire product line, while maintaining flavor, economic, and fiscal viability. This process is easily transferrable, and we are sharing this effort and its approaches as a proof-of-concept. The key aim of our work is to not only make ultraprocessed food healthier but to urge other food companies to implement similar analysis and reformulation of their product lines to improve the metabolic health and well-being of consumers worldwide.

Plant-Based Meat Alternatives Can Help Facilitate and Maintain a Lower Animal to Plant Protein Intake Ratio

The health and environmental advantages of plant-predominant diets will likely lead to increasing numbers of consumers reducing their reliance on animal products. Consequently, health organizations and professionals will need to provide guidance on how best to make this change. In many developed countries, nearly twice as much protein is derived from animal versus plant sources. Potential benefits could result from consuming a higher share of plant protein. Advice to consume equal amounts from each source is more likely to be embraced than advice to eschew all or most animal products. However, much of the plant protein currently consumed comes from refined grains, which is unlikely to provide the benefits associated with plant-predominant diets. In contrast, legumes provide ample amounts of protein as well other components such as fiber, resistant starch, and polyphenolics, which are collectively thougt to exert health benefits. But despite their many accolades and endorsement by the nutrition community, legumes make a negligible contribution to global protein intake, especially in developed countries. Furthermore, evidence suggests the consumption of cooked legumes will not substantially increase over the next several decades. We argue here that plant-based meat alternatives (PBMAs) made from legumes are a viable alternative, or a complement, to consuming legumes in the traditional manner. These products may be accepted by meat eaters because they can emulate the orosensory properties and functionality of the foods they are intended to replace. PBMAs can be both transition foods and maintenance foods in that they can facilitate the transition to a plant-predominant diet and make it easier to maintain. PBMAs also have a distinct advantage of being able to be fortified with shortfall nutrients in plant-predominant diets. Whether existing PBMAs provide similar health benefits as whole legumes, or can be formulated to do so, remains to be established. Adv Nutr 2023;xx:xx-xx.

Limitations of the Food Compass Nutrient Profiling System

Nutrient Profiling Systems provide frameworks to assess the healthfulness of foods based on food composition and are intended as inputs into strategies to improve diets. Many Nutrient Profiling Systems are founded on a reductionist assumption that the healthfulness of foods is determined by the sum of their individual nutrients, with no consideration for the extent and purpose of processing and its health implications. A novel Nutrient Profiling System called Food Compass attempted to address existing gaps and provide a more holistic assessment of the healthfulness of foods. We propose that the chosen algorithm is not well justified and produces results that fail to discriminate for common shortfall nutrients, exaggerate the risks associated with animal-source foods, and underestimate the risks associated with ultraprocessed foods. We caution against the use of Food Compass in its current form to inform consumer choices, policies, programs, industry reformulations, and investment decisions.

Comparison of Nutri-Score and Health Star Rating Nutrient Profiling Models Using Large Branded Foods Composition Database and Sales Data

Front-of-package nutrition labelling (FOPNL) is known as an effective tool that can encourage healthier food choices and food reformulation. A very interesting type of FOPNL is grading schemes. Our objective was to compare two market-implemented grading schemes-European Nutri-Score (NS) and Australian Health Star Rating (HSR), using large Slovenian branded foods database. NS and HSR were used for profiling 17,226 pre-packed foods and drinks, available in Slovenian food supply dataset (2020). Alignment between models was evaluated with agreement (% of agreement and Cohen's Kappa) and correlation (Spearman rho). The 12-month nationwide sales-data were used for sale-weighing, to address market-share differences. Study results indicated that both models have good discriminatory ability between products based on their nutritional composition. NS and HSR ranked 22% and 33% of Slovenian food supply as healthy, respectively. Agreement between NS and HSR was strong (70%, κ = 0.62) with a very strong correlation (rho = 0.87). Observed profiling models were most aligned within food categories Beverages and Bread and bakery products, while less aligned for Dairy and imitates and Edible oils and emulsions. Notable disagreements were particularly observed in subcategories of Cheese and processed cheeses (8%, κ = 0.01, rho = 0.38) and Cooking oils (27%, κ = 0.11, rho = 0.40). Further analysis showed that the main differences in Cooking oils were due to olive oil and walnut oil, which are favoured by NS and grapeseed, flaxseed and sunflower oil that are favoured by HSR. For Cheeses and cheese products, we observed that HSR graded products across the whole scale, with majority (63%) being classified as healthy (≥3.5 *), while NS mostly graded lower scores. Sale-weighting analyses showed that offer in the food supply does not always reflect the sales. Sale-weighting increased overall agreement between profiles from 70% to 81%, with notable differences between food categories. In conclusion, NS and HSR were shown as highly compliant FOPNLs with few divergences in some subcategories. Even these models do not always grade products equally high, very similar ranking trends were observed. However, the observed differences highlight the challenges of FOPNL ranking schemes, which are tailored to address somewhat different public health priorities in different countries. International harmonization can support further development of grading type nutrient profiling models for the use in FOPNL, and make those acceptable for more stake-holders, which will be crucial for their successful regulatory implementation.

A novel food processing-based nutrition classification scheme for guiding policy actions applied to the Australian food supply

Unhealthy diets are a leading risk factor for non-communicable diseases and negatively impact environmental sustainability. Policy actions recommended to address dietary risk factors, such as restrictions on marketing and front-of-pack labelling, are informed by nutrition classification schemes (NCSs). Ultra-processed foods are associated with adverse population and planetary health outcomes, yet the concept is rarely incorporated in nutrition classification schemes for policy actions. This study aims to develop a novel food processing-based nutrition classification scheme for guiding policy actions. A secondary aim is to validate the scheme by classifying food and beverage items in the Australian food supply (face validity) and comparing them to the classifications of existing NCSs (convergent validity). Two versions of a model were developed, classifying foods and beverages in two steps, first using the NOVA classification system and secondly by applying upper thresholds for added free sugars and sodium, producing a binary output of either healthy or unhealthy. All food and beverage items (n = 7,322) in a dataset combining the Australian Food Composition Database (AUSNUT 2011-2013) and Mintel's Global New Product Database (2014-2019) were classified using the two models. The same dataset was also classified by the Health Star Rating system (HSR), The Australian Dietary Guidelines (ADGs), The Pan American Health Organization's Nutrient Profile Model (PAHO NPM), and the NOVA classification scheme, and pairwise agreement between all NCSs and the two models was determined (using Cohen's Kappa coefficient). A higher proportion of food categories consistent with dietary patterns that are associated with positive health outcomes, such and fruits, vegetables, and eggs were classified as healthy. And the clear majority of food categories consistent with dietary patterns associated with adverse health outcomes, such as confectionery, snack foods, and convenience foods were classified as unhealthy. The two versions of the model showed substantial agreement with NOVA and the PAHO NPM, fair agreement with the ADGs and slight to moderate agreement with the HSR system. A model NCS combining level of processing and nutrient criteria presents a valid alternative to existing methods to classify the health potential of individual foods for policy purposes.

Validation of Food Compass with a healthy diet, cardiometabolic health, and mortality among U.S. adults, 1999-2018

The Food Compass is a nutrient profiling system (NPS) to characterize the healthfulness of diverse foods, beverages and meals. In a nationally representative cohort of 47,999 U.S. adults, we validated a person's individual Food Compass Score (i.FCS), ranging from 1 (least healthful) to 100 (most healthful) based on cumulative scores of items consumed, against: (a) the Healthy Eating Index (HEI) 2015; (b) clinical risk factors and health conditions; and (c) all-cause mortality. Nationally, the mean (SD) of i.FCS was 35.5 (10.9). i.FCS correlated highly with HEI-2015 (R = 0.81). After multivariable-adjustment, each one SD (10.9 point) higher i.FCS associated with more favorable BMI (-0.60 kg/m² [-0.70,-0.51]), systolic blood pressure (-0.69 mmHg [-0.91,-0.48]), diastolic blood pressure (-0.49 mmHg [-0.66,-0.32]), LDL-C (-2.01 mg/dl [-2.63,-1.40]), HDL-C (1.65 mg/d [1.44,1.85]), HbA1c (-0.02% [-0.03,-0.01]), and fasting plasma glucose (-0.44 mg/dL [-0.74,-0.15]); lower prevalence of metabolic syndrome (OR = 0.85 [0.82,0.88]), CVD (0.92 [0.88,0.96]), cancer (0.95 [0.91,0.99]), and lung disease (0.92 [0.88,0.96]); and higher prevalence of optimal cardiometabolic health (1.24 [1.16,1.32]). i.FCS also associated with lower all-cause mortality (HR = 0.93 [0.89,0.96]). Findings were similar by age, sex, race/ethnicity, education, income, and BMI. These findings support validity of Food Compass as a tool to guide public health and private sector strategies to identify and encourage healthier eating.

Is food compass score useful for menu planning in the hospital setting?

Background: The novel food compass score (FCS) may ease food choices and policy actions. Aim: To assess the correlations of FCS with key nutrients in hospital meals. Methods: A 14-day hospital menu was recorded and analyzed with the USDA database and published FCS values. Results: The menu FCS was 40.6 ± 3.7 (mean ± standard deviation). Fish, vegetable, chicken, and egg-based meals had the highest FCS, while pork/beef meals had the lowest FCS. The FCS was positively related to vitamins (vitamin C, thiamine, B6, folate, pantothenic acid, vitamin E, vitamin D, vitamin A, carotenoids), choline and minerals (calcium, magnesium, phosphorus, potassium, sodium, copper, and manganese) and negatively associated with zinc, niacin, and animal protein. Moreover, the FCS was positively related to portions of cheese, fish, vegetables, and eggs and negatively to portions of poultry, refined grains, and margarine. Conclusion: The FCS may help in designing healthier nutrient-dense hospital menus.

Nature of the evidence base and strengths, challenges and recommendations in the area of nutrition and health claims: a position paper from the Academy of Nutrition Sciences

The regulation of health claims for foods by the Nutrition and Health Claims Regulation is intended, primarily, to protect consumers from unscrupulous claims by ensuring claims are accurate and substantiated with high quality scientific evidence. In this position paper, the Academy of Nutrition Sciences uniquely recognises the strengths of the transparent, rigorous scientific assessment by independent scientists of the evidence underpinning claims in Europe, an approach now independently adopted in UK. Further strengths are the separation of risk assessment from risk management, and the extensive guidance for those submitting claims. Nevertheless, four main challenges in assessing the scientific evidence and context remain: (i) defining a healthy population, (ii) undertaking efficacy trials for foods, (iii) developing clearly defined biomarkers for some trial outcomes and (iv) ensuring the composition of a food bearing a health claim is consistent with generally accepted nutrition principles. Although the Regulation aims to protect the consumer from harm, we identify some challenges from consumer research: (i) making the wording of some health claims more easily understood and (ii) understanding the implications of the misperceptions around products bearing nutrition or health claims. Recommendations are made to overcome these challenges. Further, the Academy recommends that a dialogue is developed with the relevant national bodies about Article 12(c) in the Regulation. This should further clarify the GB Guidance to avoid the current non-level playing field between health professionals and untrained ‘influencers’ who are not covered by this Article about the communication of authorised claims within commercial communications.

Ultra-processed Foods and Cardiometabolic Health Outcomes: from Evidence to Practice

PURPOSE OF REVIEW

Poor diet quality is the leading risk factor related to the overall cardiometabolic disease burden in the USA and globally. We review the current evidence linking ultra-processed foods and cardiometabolic health risk and provide recommendations for action at the clinical and public health levels.

RECENT FINDINGS

A growing body of evidence conducted in a variety of study populations supports an association between ultra-processed food intake and increased risk of metabolic syndrome, hypertension, type 2 diabetes, overweight and obesity trajectories, and cardiovascular disease. The strongest evidence is observed in relation to weight gain and obesity among adults, as this association is supported by high-quality epidemiological and experimental evidence. Accumulating epidemiologic evidence and putative biological mechanisms link ultra-processed foods to cardiometabolic health outcomes. The high intake of ultra-processed foods in all population groups and its associated risks make ultra-processed foods an ideal target for intensive health promotion messaging and interventions.

Estimating the environmental impacts of 57,000 food products

Understanding and communicating the environmental impacts of food products is key to enabling transitions to environmentally sustainable food systems [El Bilali and Allahyari, Inf. Process. Agric. 5, 456-464 (2018)]. While previous analyses compared the impacts of food commodities such as fruits, wheat, and beef [Poore and Nemecek, Science 360, 987-992 (2018)], most food products contain numerous ingredients. However, because the amount of each ingredient in a product is often known only by the manufacturer, it has been difficult to assess their environmental impacts. Here, we develop an approach to overcome this limitation. It uses prior knowledge from ingredient lists to infer the composition of each ingredient, and then pairs this with environmental databases [Poore and Nemecek Science 360, 987-992 (2018); Gephart et al., Nature 597, 360-365 (2021)] to derive estimates of a food product's environmental impact across four indicators: greenhouse gas emissions, land use, water stress, and eutrophication potential. Using the approach on 57,000 products in the United Kingdom and Ireland shows food types have low (e.g., sugary beverages, fruits, breads), to intermediate (e.g., many desserts, pastries), to high environmental impacts (e.g., meat, fish, cheese). Incorporating NutriScore reveals more nutritious products are often more environmentally sustainable but there are exceptions to this trend, and foods consumers may view as substitutable can have markedly different impacts. Sensitivity analyses indicate the approach is robust to uncertainty in ingredient composition and in most cases sourcing. This approach provides a step toward enabling consumers, retailers, and policy makers to make informed decisions on the environmental impacts of food products.

Nutrition Classification Schemes for Informing Nutrition Policy in Australia: Nutrient-Based, Food-Based, or Dietary-Based?

Background

Policy makers are increasingly using nutrition classification schemes (NCSs) to assess a food's health potential for informing nutrition policy actions. However, there is wide variability among the NCSs implemented and no standard benchmark against which their contrasting assessments can be validated.

Objectives

This study aimed to compare the agreement of nutrient-, food-, and dietary-based NCSs in their assessment of a food's health potential within the Australian food supply, and examine the conceptual underpinnings and technical characteristics that explain differences in performance.

Methods

A dataset combining food compositional data from the Mintel Global New Products Database and the Australian Food Composition Database (AUSNUT 2011-2012) (n = 7322) was assembled. Products were classified by 7 prominent NCSs that were selected as representative of one or other of 1) nutrient-based NCSs [the Chilean nutrient profile model (NPM), Health Star Rating (HSR), Nutri-Score, the WHO European Region's NPM (WHO-Euro NPM), and the Pan American Health Organization's (PAHO) NPM]; 2) food-based NCS (NOVA), and 3) dietary-based NCS [Australian Dietary Guidelines (ADGs)].

Results

The PAHO NPM classified the lowest proportion (22%) of products as "healthy", and the HSR the highest (63%). The PAHO NPM, NOVA, WHO-Euro NPM, and the Chilean NPM classified >50% of products as "unhealthy," and the ADGs, HSR, and Nutri-Score classified <50% of products as "unhealthy." The HSR and Nutri-Score had the highest pairwise agreement (κ = 0.7809, 89.70%), and the PAHO NPM and HSR the lowest (κ = 0.1793, 53.22%). Characteristics of NCSs that more effectively identified ultraprocessed and discretionary foods were: category-specific assessment, the classification of categories as always "healthy" or "unhealthy," consideration of level of food processing, thresholds for "risk" nutrients that do not penalize whole foods; and no allowance for the substitution of ingredients.

Conclusions

Wide variation was observed in agreement of the assessment of a food's health potential among the NCSs analyzed due to differing conceptual underpinnings and technical characteristics.

Clinical Application of the Food Compass Score: Positive Association to Mediterranean Diet Score, Health Star Rating System and an Early Eating Pattern in University Students

Nutrient profiling systems (NPS) assist consumers in food choices. Several scores based on NPS have been proposed, but data on their clinical application are lacking. The food compass score (FCS) is a newly developed NPS per 100 kcal (from 1 “least healthy” to 100 “most healthy”). We examined the correlations of FCS with other indices, food groups, and meal patterns. A total of 346 students of the University of the Peloponnese (269 women and 77 men) participated. Dietary habits were evaluated with a food frequency questionnaire, and FCS, health star rating score (HSR), and MedDietScore were computed. Meal and snack frequency consumption was reported. Principal component analysis revealed three meal patterns: “early eater” (breakfast, morning snack and afternoon snack), “medium eater” (lunch and dinner), and “late eater” (bedtime snack). Pearson partial correlations between ranked variables were used to test the correlation coefficients between FCS, other scores, and meal patterns, after adjustment for age, sex, BMI, and underreporting. FCS was positively correlated to HSR (rho = 0.761, p ≤ 0.001) in a multi-adjusted analysis. In the highest tertile of MedDietScore FCS was also positively correlated to MedDietScore (rho = 0.379, p < 0.001). The FCS was positively correlated with juices, high-fat dairy, vegetables, legumes, fruits, and olive oil and negatively correlated with sodas, alcoholic drinks, red meat, refined grains, sweets, fats other than olive oil, fast foods, and coffee. In addition, it related positively to the “early eater” pattern (rho = 0.207, p < 0.001). The FCS was associated with other quality indices and better nutritional habits, such as being an early eater.

Balanced Hybrid Nutrient Density Score Compared to Nutri-Score and Health Star Rating Using Receiver Operating Characteristic Curve Analyses

Background

Nutrient profiling (NP) models that are used to assess the nutrient density of foods can be based on a combination of key nutrients and desirable food groups.

Objective

To compare the diagnostic accuracy of a new balanced hybrid nutrient density score (bHNDS) to Nutri-Score and Health Star Rating (HSR) front-of-pack systems using receiver operating characteristic (ROC) curve analyses. The diet-level bHNDS was first validated against Healthy Eating Index (HEI-2015) using data from the 2017–18 National Health and Nutrition Examination Survey (2017–18 NHANES). Food-level bHNDS values were then compared to both the Nutri-Score and HSR using ROC curve analyses.

Results

The bHNDS was based on 6 nutrients to encourage (protein, fiber, calcium, iron, potassium, and vitamin D); 5 food groups to encourage (whole grains, nuts and seeds, dairy, vegetables, and fruit), and 3 nutrients (saturated fat, added sugar, and sodium) to limit. The algorithm balanced components to encourage against those to limit. Diet-level bHNDS values correlated well with HEI-2015 (r = 0.67; p &lt; 0.001). Food-level correlations with both Nutri-Score (r = 0.60) and with HSR (r = 0.58) were significant (both p &lt; 0.001). ROC estimates of the Area Under the Curve (AUC) showed high agreement between bHNDS values and optimal Nutri-Score and HSR ratings (&gt;0.90 in most cases). ROC analysis identified those bHNDS cut-off points that were predictive of A-grade Nutri-Score or 5-star HSR. Those cut-off points were highly category-specific.

Conclusion

The new bHNDS model showed high agreement with two front-of-pack labeling systems. Cross-model comparisons based on ROC curve analyses are the first step toward harmonization of proliferating NP methods that aim to “diagnose” high nutrient-density foods.

A New Carbohydrate Food Quality Scoring System to Reflect Dietary Guidelines: An Expert Panel Report

Existing metrics of carbohydrate food quality have been based, for the most part, on favorable fiber- and free sugar-to-carbohydrate ratios. In these metrics, higher nutritional quality carbohydrate foods are defined as those with >10% fiber and <10% free sugar per 100 g carbohydrate. Although fiber- and sugar-based metrics may help to differentiate the nutritional quality of various types of grain products, they may not aptly capture the nutritional quality of other healthy carbohydrate foods, including beans, legumes, vegetables, and fruits. Carbohydrate food quality metrics need to be applicable across these diverse food groups. This report introduces a new carbohydrate food scoring system known as a Carbohydrate Food Quality Score (CFQS), which supplements the fiber and free sugar components of previous metrics with additional dietary components of public health concern (e.g., sodium, potassium, and whole grains) as identified by the Dietary Guidelines for Americans. Two CFQS models are developed and tested in this study: one that includes four dietary components (CFQS-4: fiber, free sugars, sodium, potassium) and one that considers five dietary components (CFQS-5: fiber, free sugars, sodium, potassium, and whole grains). These models are applied to 2596 carbohydrate foods in the Food and Nutrient Database for Dietary Studies (FNDDS) 2017−2018. Consistent with past studies, the new carbohydrate food scoring system places large percentages of beans, vegetables, and fruits among the top scoring carbohydrate foods. The whole grain component, which only applies to grain foods (N = 1561), identifies ready-to-eat cereals, oatmeal, other cooked cereals, and selected whole grain breads and crackers as higher-quality carbohydrate foods. The new carbohydrate food scoring system shows a high correlation with the Nutrient Rich Food (NRF9.3) index and the Nutri-Score. Metrics of carbohydrate food quality that incorporate whole grains, potassium, and sodium, in addition to sugar and fiber, are strategically aligned with multiple 2020−2025 dietary recommendations and may therefore help with the implementation of present and future dietary guidelines.

Interrelations Between Food Form, Texture, and Matrix Influence Energy Intake and Metabolic Responses

Purpose of Review

Nutrition often focuses on food composition, yet differences in food form, texture, and matrix influence energy intake and metabolism. This review outlines how these attributes of food impact oral processing, energy intake, and metabolism.

Recent Findings

Food form has a well-established impact on intake, where liquids are consumed more than solids and semi-solids. For solids, texture properties like thickness, hardness, and lubrication, and geometrical properties like size and shape influence oral processing, eating rate, and intake. Food matrix integrity can influence nutrient and energy absorption and is strongly influenced by food processing.

Summary

Food texture and matrix play important roles in modulating energy intake and absorption. Future research needs to consider the often overlooked role of texture and matrix effects on energy and metabolic responses to composite foods and meals. Research is needed to understand how processing impacts macro- and micro-structure of food and its long-term impact on energy balance and health.

Nutrition research challenges for processed food and health

Existing highly processed food (HPF) classification systems show large differences in the impact of these foods on biochemical risk factors for disease. If public health nutrition is to consider the degree of food processing as an important element of the link between food and health, certain gaps in research must be acknowledged. Quantifying the food additive exposure derived from HPFs is a task made challenging by the lack of data available on the occurrence and concentration of additives in food and the degree to which the natural occurrence of additives in unprocessed foods confounds exposure estimates. The proposed role of HPFs in health outcomes could also be associated with altered nutrient profiles. Differences exist within and between HPF classification systems in this regard and there are conflicting data on the impact of controlling for nutrient intake. Furthermore, research is needed on how the sensory aspects of HPFs contribute to energy intake. Current data suggest that high energy intake rate may be the mechanism linking HPFs and increased energy intake. A high priority now is to clarify the basis of definitions used to categorize foods as highly processed and, in a constructive sense, to distinguish between the contributions of nutrients, additives and sensory properties to health.