Perspective: Why Whole Grains Should Be Incorporated into Nutrient-Profile Models to Better Capture Nutrient Density

Sex differences in the relationships between macronutrients and all-cause mortality in individuals with metabolically unhealthy overweight/obesity

This study investigates sex differences in the effects of macronutrient quantity, quality, and timing on mortality in metabolically unhealthy overweight/obesity (MUO) populations. The study included 18,345 participants, including 9204 men and 9141 women. The Cox proportional risk model and isocaloric substitution effects were used to examine the association of macronutrient intake and subtype with all-cause mortality in the MUO populations. After adjusting for the potential covariates, The risk of all-cause mortality was elevated in men in the highest 25% percentile of poor-quality carbohydrates compared with men in the lowest quartile (odds ratio [OR]: 2.04; 95% confidence interval [CI], 1.40-2.98). Compared with women in the lowest quartile, the risk of all-cause mortality for women in the highest 25% percentile for high-quality carbohydrates (OR: 0.74; 95% CI, 0.55-0.99) and unsaturated fatty acids (OR: 0.54; 95% CI, 0.32-0.93) were decreased. In women, replacing low-quality carbohydrates with high-quality carbohydrates on an isocaloric basis reduces the risk of all-cause mortality by approximately 9%. We find that different macronutrient consumption subtypes are associated with all-cause mortality in MUO populations, with differential effects between men and women, and that the risk of all-cause mortality is influenced by macronutrient quality and meal timing.

Aligning front-of-pack labelling with dietary guidelines: including whole grains in the health star rating

PURPOSE

Front-of-pack labelling systems, such as the Health Star Rating (HSR), aim to aid healthy consumer dietary choices and complement national dietary guidelines. Dietary guidelines aim to be holistic by extending beyond the individual nutrients of food, including other food components that indicate diet quality, including whole grains. We aimed to test the feasibility of including whole grains in the HSR algorithm, to better inform dietary guidance in Australia coherent with existing dietary guidelines.

METHODS

We assigned whole-grain points as a favourable component of the HSR based on the whole-grain content of foods. We compared the original, and three modified HSR algorithms (including altered thresholds for star ratings) using independent-samples median tests. Finally, we used Spearman's correlation to measure the strength of association between an item's nutritional composition (all components of the HSR algorithm including all favourable and unfavourable components) and their HSR using each algorithm.

RESULTS

Up to 10 points were added for products with ≥ 50% whole-grain content, with no points for products with < 25%. Adjusting the HSR score cut-off by 3 points for grain products created the greatest difference in median HSR between refined and whole-grain items (up to 2 stars difference), compared to the original algorithm (a maximum of 1 star).

CONCLUSIONS

The addition of whole grains to the HSR algorithm improved the differentiation of refined and whole-grain items, and therefore better aligned with dietary guidelines. Holistic approaches to food guidance systems are required to provide consistent messaging and inform positive food choices.

Increasing fibre intake in the UK: lessons from the Danish Whole Grain Partnership

Diets deficient in fibre are reported globally. The associated health risks of insufficient dietary fibre are sufficiently grave to necessitate large-scale interventions to increase population intake levels. The Danish Whole Grain Partnership (DWP) is a public-private enterprise model that successfully augmented whole-grain intake in the Danish population. The potential transferability of the DWP model to Slovenia, Romania and Bosnia-Herzegovina has recently been explored. Here, we outline the feasibility of adopting the approach in the UK. Drawing on the collaborative experience of DWP partners, academics from the Healthy Soil, Healthy Food, Healthy People (H3) project and food industry representatives (Food and Drink Federation), this article examines the transferability of the DWP approach to increase whole grain and/or fibre intake in the UK. Specific consideration is given to the UK's political, regulatory and socio-economic context. We note key political, regulatory, social and cultural challenges to transferring the success of DWP to the UK, highlighting the particular challenge of increasing fibre consumption among low socio-economic status groups - which were also most resistant to interventions in Denmark. Wholesale transfer of the DWP model to the UK is considered unlikely given the absence of the key 'success factors' present in Denmark. However, the DWP provides a template against which a UK-centric approach can be developed. In the absence of a clear regulatory context for whole grain in the UK, fibre should be prioritised and public-private partnerships supported to increase the availability and acceptability of fibre-rich foods.

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.

Association of Whole Grain Consumption and Cognitive Decline: An Investigation From a Community-Based Biracial Cohort of Older Adults

BACKGROUND AND OBJECTIVES

To examine the association of whole grain consumption and longitudinal change in global cognition, perceptual speed, and episodic memory by different race/ethnicity.

METHODS

We included 3,326 participants from the Chicago Health and Aging Project who responded to a Food Frequency Questionnaire (FFQ), with 2 or more cognitive assessments. Global cognition was assessed using a composite score of episodic memory, perceptual speed, and the Mini Mental State Examination (MMSE). Diet was assessed by a 144-item FFQ. Linear mixed-effects models were used to estimate the association of intakes of whole grains and cognitive decline.

RESULTS

This study involved 3,326 participants (60.1% African American [AA], 63.7% female) with a mean age of 75 years at baseline and a mean follow-up of 6.1 years. Higher consumption of whole grains was associated with a slower rate of global cognitive decline. Among AA participants, those in the highest quintile of whole grain consumption had a slower rate of decline in global cognition (β = 0.024, 95% CI [0.008-0.039], p = 0.004), perceptual speed (β = 0.023, 95% CI [0.007-0.040], p = 0.005), and episodic memory (β = 0.028, 95% CI [0.005-0.050], p = 0.01) compared with those on the lowest quintile. Regarding the amount consumed, in AA participants, those who consumed >3 servings/d vs those who consumed <1 serving/d had a slower rate of decline in global cognition (β = 0.021, 95% CI [0.005-0.036], p = 0.0093). In White participants, with >3 servings/d, we found a suggestive association of whole grains with global cognitive decline when compared with those who consumed <1 serving/d (β = 0.025, 95% CI [-0.003 to 0.053], p = 0.08).

DISCUSSION

Among AA participants, individuals with higher consumption of whole grains and more frequent consumption of whole grain had slower decline in global cognition, perceptual speed, and episodic memory. We did not see a similar trend in White adults.

Ultra-processed foods in a rural Ecuadorian community: associations with child anthropometry and bone maturation

Frequent ultra-processed food (UPF) consumption is consistently associated with poor health outcomes. Little is known about UPF intake during early childhood and its effects on growth. We assessed UPF in relation to child anthropometry, bone maturation, and their nutrition profiles in a rural Ecuadorian community. Covariate-adjusted regression models estimated relationships between UPF intake from a 24-hour Food Frequency Questionnaire and three outcomes: linear growth, weight status and bone maturation. Nutrient Profiling Models (NPM) evaluated a convenience sample of UPF (n 28) consumed by children in the community. In this cohort (n 125; mean age = 33·92 (sd 1·75) months), 92·8 % consumed some form of UPF the previous day. On average, children consuming UPF four to twelve times per day (highest tertile) had lower height-for-age z-scores than those with none or a single instance of UPF intake (lowest tertile) (β = -0·43 [se 0·18]; P = 0·02). Adjusted stunting odds were significantly higher in the highest tertile relative to the lowest tertile (OR: 3·07, 95 % CI 1·11, 9·09). Children in the highest tertile had significantly higher bone age z-scores (BAZ) on average compared with the lowest tertile (β = 0·58 [se 0·25]; P = 0·03). Intake of savoury UPF was negatively associated with weight-for-height z-scores (β = -0·30 [se 0·14]; P = 0·04) but positively associated with BAZ (β = 0·77 [se 0·23]; P < 0·001). NPM indicated the availability of unhealthy UPF to children, with excessive amounts of saturated fats, free sugars and sodium. Findings suggest that frequent UPF intake during early childhood may be linked to stunted growth (after controlling for bone age and additional covariates), despite paradoxical associations with bone maturation.

A Diet Profiling Algorithm (DPA) to Rank Diet Quality Suitable to Implement in Digital Tools—A Test Study in a Cohort of Lactating Women

Although nutrient profiling systems can empower consumers towards healthier food choices, there is still a need to assess diet quality to obtain an overall perspective. The purpose of this study was to develop a diet profiling algorithm (DPA) to evaluate nutritional diet quality, which gives a final score from 1 to 3 with an associated color (green-yellow-orange). It ranks the total carbohydrate/total fiber ratio, and energy from saturated fats and sodium as potentially negative inputs, while fiber and protein are assumed as positive items. Then, the total fat/total carbohydrate ratio is calculated to evaluate the macronutrient distribution, as well as a food group analysis. To test the DPA performance, diets of a lactating women cohort were analyzed, and a correlation analysis between DPA and breast milk leptin levels was performed. Diets classified as low quality showed a higher intake of negative inputs, along with higher energy and fat intakes. This was reflected in body mass index (BMI) and food groups, indicating that women with the worst scores tended to choose tastier and less satiating foods. In conclusion, the DPA was developed and tested in a sample population. This tool can be easily implemented in digital nutrition platforms, contributing to real-time dietary follow-up of patients and progress monitoring, leading to further dietary adjustment.

A New Technique for Determining Micronutrient Nutritional Quality in Fruits and Vegetables Based on the Entropy Weight Method and Fuzzy Recognition Method

The human body needs nutrients to maintain its regular physiological activity. It requires 40 essential nutrients, including macronutrients (carbohydrates, protein, and fat) and micronutrients (vitamins and minerals). Although macronutrient intake has been improved in China due to people's increased social awareness, the population's micronutrient intake remains insufficient.

OBJECTIVE

The current food evaluation system is primarily used to assess macronutrients, while an effective assessment method for micronutrients is still lacking. Fruits and vegetables are low-energy food sources that mainly provide vitamins and minerals and supply the human body with various micronutrients.

METHODS

In this paper, the entropy and fuzzy recognition methods were used to construct the Vitamin Index (Vitamin Index = Vitamin A Index + Vitamin Comprehensive Index + Vitamin Matching Index) and Mineral Index (Mineral Index = Calcium Index + Mineral Comprehensive Index + Mineral Matching Index) and to evaluate the micronutrient quality of 24 vegetables and 20 fruits.

RESULTS

The assessment results showed that Chinese dates displayed the highest Vitamin and Mineral Index among fruits (Vitamin Index = 2.62 and Mineral Index = 2.63), while collard greens had the highest Vitamin Index of the vegetables, at 2.73, and red amaranth had the highest Mineral Index, at 2.74.

CONCLUSIONS

The study introduces a new method for assessing the nutritional quality of micronutrients, which provides a new idea for assessing the nutrient quality of agricultural products.

Dietary Intakes and Eating Behavior between Metabolically Healthy and Unhealthy Obesity Phenotypes in Asian Children and Adolescents

Diet plays a critical role in the development of obesity and obesity-related morbidities. Our study aimed to evaluate the dietary food groups, nutrient intakes and eating behaviors of metabolically healthy and unhealthy obesity phenotypes in an Asian cohort of children and adolescents. Participants (n = 52) were asked to record their diet using a 3-day food diary and intakes were analyzed using a nutrient software. Eating behavior was assessed using a validated questionnaire. Metabolically healthy obesity (MHO) or metabolically unhealthy obesity (MUO) were defined based on criteria of metabolic syndrome. Children/adolescents with MUO consumed fewer whole grains (median: 0.00 (interquartile range: 0.00-0.00 g) vs. 18.5 g (0.00-69.8 g)) and less polyunsaturated fat (6.26% kcal (5.17-7.45% kcal) vs. 6.92% kcal (5.85-9.02% kcal)), and had lower cognitive dietary restraint (15.0 (13.0-17.0) vs. 16.0 (14.0-19.0)) compared to children/adolescents with MHO. Deep fried food, fast food and processed convenience food were positively associated with both systolic (β: 2.84, 95%CI: 0.95-6.62) and diastolic blood pressure (β: 4.83, 95%CI: 0.61-9.04). Higher polyunsaturated fat intake (OR: 0.529, 95%CI: 0.284-0.986) and cognitive dietary restraint (OR: 0.681, 95%CI: 0.472-0.984) were associated with a lower risk of the MUO phenotype. A healthier diet composition and positive eating behavior may contribute to favorable metabolic outcomes in children and adolescents with obesity.

Performance and discriminatory capacity of Nutri-Score in branded foods in Greece

Background

The harmonization of front-of-pack nutritional declaration is in the heart of food and nutrition policy discussions in Europe. The Nutri-Score system has been proposed by many countries as a potential candidate but its suitability for use across Europe is still under consideration. The current study aimed to evaluate the performance and discriminatory capacity of Nutri-Score in Greece and to test its alignment with the national food-based dietary guidelines.

Materials and methods

Data on the energy, saturated fat, total sugars, sodium, protein, and fiber content per 100°g or ml were extracted for all foods available (n = 4,002) in the Greek branded food composition database HelTH. Each food content in fruits, vegetables, pulses, nuts and oils was manually estimated from the ingredients list. The Nutri-Score algorithm was used both as a continuous (FSAm-NPS Score) and a categorical variable [Grades (A)–(E)].

Results

The average FSAm-NPS Score in Greece was 8.52 ± 9.4. More than half of the solid foods (53.8%) were graded from (A) to (C), while most beverages (59.2%) were graded (E). More than 50% of food categories were populated with foods in all Nutri-Score grades, indicative of a good discriminatory capacity. The system scores favorably vegetables, pulses, and low-fat dairy products and unfavourablly sweets and processed meats showing in this way good alignment with the national guidelines. Eggs and seafood scored preferably compared to meat products. Animal fats received less favorable scores and so did cereal products that were highly processed.

Discussion

Nutri-Score showed good capacity to inform consumers toward better food choices in line with the national guidelines. It showed a potential to guide consumers and manufacturers toward less energy dense and more nutrient dense options and highlighted areas of improvement in the food supply.

Multiple Metrics of Carbohydrate Quality Place Starchy Vegetables Alongside Non-starchy Vegetables, Legumes, and Whole Fruit

Background

Starchy vegetables, including white potatoes, are often categorized as “lower-quality” carbohydrate foods, along with refined grains, 100% fruit juices, sweetened beverages, and sugars, snacks and sweets. Among “higher-quality” carbohydrates are whole grains, non-starchy vegetables, legumes, and whole fruits.

Objective

To apply multiple nutrient profiling (NP) models of carbohydrate quality to foods containing &gt;40% carbohydrate by dry weight in the USDA Food and Nutrient Database for Dietary Studies (FNDDS 2017-18).

Methods

Carbohydrate foods in the FNDDS (n = 2423) were screened using four recent Carbohydrate Quality Indices (CQI) and a new Carbohydrate Food Quality Score (CFQS-4). Cereal products containing &gt;25% whole grains by dry weight were classified as whole grain foods.

Results

Based on percent items meeting the criteria for 4 CQI scores, legumes, non-starchy and starchy vegetables, whole fruit, and whole grain foods qualified as “high quality” carbohydrate foods. Distribution of mean CFQS-4 values showed that starchy vegetables, including white potatoes placed closer to non-starchy vegetables and fruit than to candy and soda.

Conclusion

Published a priori determinations of carbohydrate quality do not always correspond to published carbohydrate quality metrics. Based on CQI metrics, specifically designed to assess carbohydrate quality, starchy vegetables, including white potatoes, merit a category reassignment and a more prominent place in dietary guidance.

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.

Defining Energy-Dense, Nutrient-Poor Food and Drinks and Estimating the Amount of Discretionary Energy

Overconsumption of energy provided by energy-dense, nutrient-poor (EDNP) food and drinks increases the risk of unhealthy weight gain and of obesity-related health outcomes. The aim of this study was to develop a nutrient profiling model for classifying EDNP food and drinks and to estimate the amount of discretionary energy for EDNP food and drinks in a recommended diet. A stepwise approach was used first to develop a nutrient profiling model for classifying EDNP food and drinks and then to estimate the amount of discretionary energy in a recommended diet using diet modeling. The nutrition profiling model comprised 24 macro- and micronutrients and energy density. The model classified 67% of 1482 foods and 73% of 161 drinks correctly as EDNP food and drinks compared with an expert-adjusted model. Sweets, chocolate, cake, cookies and biscuits, sweet and salty snacks, sugar-sweetened and artificially sweetened drinks, and alcoholic drinks were classified as EDNP food and drinks. The estimated amount of discretionary energy for EDNP food and drinks was 4–6% of the energy requirements for 4–75-year-old Danes. It seems prudent to have special attention on EDNP food and drinks in dietary guidelines and future public health initiatives to avoid overconsumption of energy.

“Even We Are Confused”: A Thematic Analysis of Professionals' Perceptions of Processed Foods and Challenges for Communication

Processed foods are increasingly under the spotlight since the development of classification systems based on proxies for food processing. Published critical reviews and commentaries suggest different views among professional disciplines about the definition and classification of processed food. There is a need to further understand perspectives of professionals on the conceptualisation of processed food and the agreements and disagreements among experts, to encourage interdisciplinary dialogue and aid communication to the public. The aim of this research was to elicit views and understandings of professionals on processed food, their perceptions of lay people's perceptions of the same, and their perspectives on the challenges of communicating about processed foods to the public. The online discussion groups brought together a range of professionals (n = 27), covering the fields of nutrition, food technology, policy making, industry, and civil society, mixed in 5 heterogenous groups. Through thematic analysis the following themes relating to the conceptualisation of processed food and challenges for communication were identified: (1) Broad concepts that need differentiation; (2) Disagreements on scope and degree of processing; (3) The role of food processing within the food system: the challenges in framing risks and benefits; and (4) The challenge of different perspectives and interests for risk communication. Throughout the discussions blurred lines in the characterisation of processing, processed foods, and unhealthy foods were observed. Participants agreed that consensus is important, but difficult. Participants identified a need for further interdisciplinary dialogue, including public engagement, to break down the observed issues, and work towards a mutual understanding and develop clear communication messages.

Applying and comparing various nutrient profiling models against the packaged food supply in South Africa

OBJECTIVE

This study aimed to apply the newly developed Chile Adjusted Model (CAM) nutrient profiling model (NPM) to the food supply in South Africa (SA) and compare its performance against existing NPMs as an indication of suitability for use to underpin food policies targeted at discouraging consumption of products high in nutrients associated with poor health.

DESIGN

Cross-sectional analysis of the SA packaged food supply comparing the CAM to three other NPMs: SA health and nutrition claims (SA HNC), Chilean warning octagon (CWO) 2019, and Pan-American Health Organization (PAHO) NPM.

SETTING

The SA packaged food supply based on products stocked by supermarkets in Cape Town, SA.

PARTICIPANTS

Packaged foods and beverages (N=6474) available in 2018 were analyzed.

RESULTS

49% of products contained excessive amounts of nutrients of concern (considered non-compliant) according to the criteria of all four models. Only 10.9% of products were not excessive in any nutrients of concern (considered compliant) according to all NPMs evaluated. The CAM had an overall non-compliance level of 73.2%, and was comparable to the CWO 2019 for foods (71.2% and 71.1% respectively). The CAM was the strictest NPM for beverages (80.4%) due to the criteria of non-sugar sweeteners and free sugars. The SA HNC was the most lenient with non-compliance at 52.9%. This was largely due to the inclusion of nutrients to encourage, which is a criterion for this NPM.

CONCLUSION

For the purpose of discouraging products high in nutrients associated with poor health in SA, the CAM is a suitable NPM.

Aligning nutrient profiling with dietary guidelines: modifying the Nutri-Score algorithm to include whole grains

Purpose

Whole grains, generally recognised as healthy choices, are not included in most nutrient profiling systems. We tested modifications to the Nutri-Score algorithm to determine whether including whole grains would provide an improved measure of food, and overall diet quality.

Methods

The whole-grain content of food, with a minimum cut-point of 25%, was added to the algorithm, following similar methods used to score other health-promoting components such as fibre. We applied and compared the original and the modified Nutri-Score to food composition and dietary intake data from Australia, France, the United Kingdom, and the United States.

Results

At the food level, correlations between whole-grain content and food nutritional score were strengthened using the modified algorithm in Australian data, but less so for the other countries. Improvements were greater in grain-specific food groups. The largest shift in Nutri-Score class was from B to A (best score). At the dietary intake level, whole-diet nutritional scores for individuals were calculated and compared against population-specific diet-quality scores. With modifications, correlations with diet-quality scores were improved slightly, suggesting that the modified score better aligns with national dietary guidelines. An inverse linear relationship between whole-diet nutritional score and whole-grain intake was evident, particularly with modifications (lower whole-diet nutritional score indicative of better diet quality).

Conclusion

Including a whole-grain component in the Nutri-Score algorithm is justified to align with dietary guidelines and better reflect whole grain as a contributor to improved dietary quality. Further research is required to test alternative algorithms and potentially other nutrient profiling systems.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00394-021-02718-6.

Healthcare Cost Savings Associated with Increased Whole Grain Consumption among Australian Adults

Many dietary guidelines emphasise "mostly" whole grain food choices as part of an overall healthy eating pattern based on evidence for enhancing nutritional status and reducing chronic disease. Still, countries including Australia fall short of their consumption targets. Furthermore, healthcare cost savings associated with increasing the consumption of whole grains in alignment with the Daily Target Intake (DTI) recommendation of 48 g are unknown. The aim of this study was to assess the potential savings in costs of healthcare and lost productivity associated with a reduction in the incidence of Type 2 Diabetes Mellitus (T2DM) and cardiovascular disease (CVD) through meeting the 48 g DTI recommendation for whole grains among the Australian adult population (>20 years). A three-step cost-of-illness analysis was conducted using input parameters from: 1) estimates of proportions of consumers (5%, 15%, 50%, and 100%) who would increase their current intake of whole grains to meet the recommended DTI in Australia; 2) relative reductions in risk of T2DM and CVD associated with specific whole grain consumption, as reported in meta-analysis studies; and 3) data on costs of healthcare and productivity loss based on monetary figures by national healthcare authorities. A very pessimistic (5% of the population) through to universal (100% of the population) adoption of the recommended DTI was shown to potentially yield AUD 37.5 (95% CI 22.3-49.3) to AUD 750.7 (95% CI 445.7-985.2) million, and AUD 35.9 (95% CI 8.3-60.7) to AUD 717.4 (95% CI 165.5-1214.1) million in savings on annual healthcare and lost productivity costs for T2DM and CVD, respectively. Given such economic benefits of the recommended consumption of whole grains, in exchange for refined grains, there is a real opportunity to facilitate relevant socioeconomic cost-savings for Australia and reductions in disease. These results are suggestive of a much greater opportunity to communicate the need for dietary change at all levels, but particularly through food-based dietary guidelines and front-of-pack labelling initiatives.

The New Hybrid Nutrient Density Score NRFh 4:3:3 Tested in Relation to Affordable Nutrient Density and Healthy Eating Index 2015: Analyses of NHANES Data 2013-16

Background: Hybrid nutrient density scores are based on both nutrients and selected food groups. Objective: To compare the new hybrid nutrient-rich food NRFh 4:3:3 score to other nutrient-rich food (NRF) scores, energy density, and energy cost and to model the impact on the Healthy Eating Index (HEI-2015) of partially replacing less nutrient-rich with more nutrient-rich foods. Methods: Analyses were based on 5870 foods and beverages in the Food and Nutrient Database for Dietary Studies and on 24 h dietary recalls from the National Health and Nutrition Examination Survey (NHANES 2013–16). The NRFh 4:3:3 model was based on four nutrients to encourage (protein fiber, potassium, MUFA + PUFA); three food groups to encourage (dairy, fruit, whole grains); and three nutrients to limit (saturated fat, added sugar, sodium). Ratings generated by NRFh 4:3:3 and by other NRF models were correlated with score components, energy density (kcal/100 g), and energy cost (USD/100 kcal). The impact on HEI-2015 of replacing foods in the lowest nutrient density tertile (T1) with top tertile (T3) foods at 10%, 20%, 30%, and 100% equicaloric replacement was modeled using NHANES 2013–16 dietary data by population subgroups. Results: The NRFh 4:3:3 model awarded higher scores to foods containing dairy, fruit, and whole grains and proportionately lower scores to vegetables when compared to the NRF 9.3 model. Higher NRF and NRFh nutrient density scores were linked to lower energy density and higher energy cost; however, both correlations were lower for the NRFh 4:3:3. Isocaloric replacement of bottom tertile with top tertile foods as rated by both models led to significantly higher HEI-2105 values, based on complete (100%) and on partial (10–30%) replacement. Conclusion: The new NRFh 4:3:3 model provides the basis for developing new metrics of affordable nutrient density. The model identified “best value” food categories that were both affordable and nutrient-rich. Total and partial replacement of low nutrient density with high nutrient density foods was associated with higher HEI-2015 scores, suggesting that even partial inclusion of more nutrient dense foods in the diet may have an important impact on total diet quality.

Diet-Derived Antioxidants and Their Role in Inflammation, Obesity and Gut Microbiota Modulation

It is generally accepted that gut microbiota, inflammation and obesity are linked to the development of cardiovascular diseases and other chronic/non-communicable pathological conditions, including cancer, neurodegenerative diseases and ageing-related disorders. In this scenario, oxidative stress plays a pivotal role. Evidence suggests that the global dietary patterns may represent a tool in counteracting oxidative stress, thus preventing the onset of diseases related to oxidative stress. More specifically, dietary patterns based on the regular consumption of fruits and vegetables (i.e., Mediterranean diet) have been licensed by various national nutritional guidelines in many countries for their health-promoting effects. Such patterns, indeed, result in being rich in specific components, such as fiber, minerals, vitamins and antioxidants, whose beneficial effects on human health have been widely reported. This suggests a potential nutraceutical power of specific dietary components. In this manuscript, we summarize the most relevant evidence reporting the impact of dietary antioxidants on gut microbiota composition, inflammation and obesity, and we underline that antioxidants are implicated in a complex interplay between gut microbiota, inflammation and obesity, thus suggesting their possible role in the development and modulation of chronic diseases related to oxidative stress and in the maintenance of wellness. Do all roads lead to Rome?