Declining nutrient densities of crops in the past 50–70 years have been attributed to unsound agricultural practices and plant breeding focus on yield rather than quality. Few studies have quantified the soil and nutritional quality of grains in organic and conventional farms and reported results are scarce and inconsistent. The Rodale Institute's Farming Systems Trial (FST) was established in 1981 to quantify the effects of long-term organic and conventional grain cropping systems and tillage practices. A 2014 study to quantify effects on the nutrient density of oat grains was integrated into three systems within the long-term trial: organic manure-based (MNR), organic legume-based (LEG), and conventional synthetic input-based (CNV), split between tilled (T) and no-till (NT) practices. Oat grains with hulls removed were analyzed for minerals (n = 24), vitamins (n = 24), amino acids (n = 24) and proteins (n = 24), while soil samples to a depth of 10 cm were analyzed for elemental minerals, and total carbon (C), nitrogen (N) and sulfur (S). Organic systems increased six out ten soil minerals whose concentrations were influenced by cropping systems: aluminum (Al), iron (Fe), chromium (Cr), calcium (Ca), barium (B) and strontium (Sr). All essential amino acids were greater in oat grains under LEG systems compared with other systems except lysine, histidine and methionine. Both LEG systems also increased 12 out of 13 non-essential amino acids in oat grains. Total oat N, C and S required for amino acid synthesis tended to be greater in organic systems. Soil N, C and S were highly correlated with total oat amino acids under organic systems compared to CNV. Organic LEG had significantly greater vitamin B1 than MNR and CNV. These results suggest that nutrient concentrations of oat grains were greater in organic systems compared to CNV systems, and the increase could be partially explained by the long-term soil management differences between the systems.

Higher consumption of ‘ultra-processed’ (UP) foods has been linked to adverse health outcomes. The present paper aims to characterise percentage energy from UP foods by participant socio-economic status (SES), diet quality, self-reported food expenditure and energy-adjusted diet cost. Participants in the population-based Seattle Obesity Study III (n 755) conducted in WA in 2016–2017 completed socio-demographic and food expenditure surveys and the FFQ. Education and residential property values were measures of SES. Retail prices of FFQ component foods (n 378) were used to estimate individual-level diet cost. Healthy Eating Index (HEI-2015) and Nutrient Rich Food Index 9.3 (NRF9.3) were measures of diet quality. UP foods were identified following NOVA classification. Multivariable linear regressions were used to test associations between UP foods energy, socio-demographics, two estimates of food spending and diet quality measures. Higher percentage energy from UP foods was associated with higher energy density, lower HEI-2015 and NRF9.3 scores. The bottom decile of diet cost ($216·4/month) was associated with 67·5 % energy from UP foods; the top decile ($369·9/month) was associated with only 48·7 % energy from UP foods. Percentage energy from UP foods was inversely linked to lower food expenditures and diet cost. In multivariate analysis, percentage energy from UP foods was predicted by lower food expenditures, diet cost and education, adjusting for covariates. Percentage energy from UP foods was linked to lower food spending and lower SES. Efforts to reduce UP foods consumption, an increasingly common policy measure, need to take affordability, food expenditures and diet costs into account.

The NOVA food categorisation recommends ‘avoiding processed foods (PF), especially ultra-processed foods (UPF)’ and selecting minimally PF to address obesity and chronic disease. However, NOVA categories are drawn using non-traditional views of food processing with additional criteria including a number of ingredients, added sugars, and additives. Comparison of NOVA's definition and categorisation of PF with codified and published ones shows limited congruence with respect to either definition or food placement into categories. While NOVA studies associate PF with decreased nutrient density, other classifications find nutrient-dense foods at all levels of processing. Analyses of food intake data using NOVA show UPF provide much added sugars. Since added sugars are one criterion for designation as UPF, such a proof demonstrates a tautology. Avoidance of foods deemed as UPF, such as wholegrain/enriched bread and cereals or flavoured milk, may not address obesity but could decrease intakes of folate, calcium and dietary fibre. Consumer understanding and implementation of NOVA have not been tested. Neither have outcomes been compared with vetted patterns, such as Dietary Approaches to Stop Hypertension, which base food selection on food groups and nutrient contribution. NOVA fails to demonstrate the criteria required for dietary guidance: understandability, affordability, workability and practicality. Consumers’ confusion about definitions and food categorisations, inadequate cooking and meal planning skills and scarcity of resources (time, money), may impede adoption and success of NOVA. Research documenting that NOVA can be implemented by consumers and has nutrition and health outcomes equal to vetted patterns is needed.

A study was conducted to evaluate productive performance in laying hens fed diets with reduced nutrient density based on the nutritional contribution of a Buttiauxella phytase in laying-hen diets from 21-57 weeks of age. A commercial laying hen diet was offered ad libitum to the 480 ISA Brown laying hens from 18-21 weeks of age. From 21 weeks onwards, the hens received one of four dietary treatments: a positive control (PC) diet, a down specified diet (DS1) + phytase at 300 FTU/kg, a second down-specified diet (DS2) + phytase at 600 FTU/kg and a third test diet formulated as per DS1 + phytase at 1,200 FTU/kg feed. The PC was formulated based on ISA breeder recommendations. DS1 was formulated with reduction of 0.149% available P, 0.134% Ca, 55 kcal/kg AME, 0.33% CP, digestible amino acids (up to 0.015%) and 0.013% Na based on the contribution of Buttiauxella phytase at 300 FTU/kg. DS2 was formulated with reduction of 0.177% available P, 0.159% Ca, 60 kcal/kg AME, 0.61% CP, digestible amino acids (up to 0.028%) and 0.02% Na based on the contribution of Buttiauxella phytase at 600 FTU/kg. Every dietary treatment was fed to 12 cages containing 10 hens each. The trial treatments did not include a full, DS negative control, as ethical considerations regarding birds' welfare when feeding such diets over such an extended period of time did not permit this. No significant differences were seen in hen-day egg production, feed intake, egg weight, feed to egg mass ratio, shell, yolk or albumen proportion, unsaleable eggs or shell breaking strength in laying hens fed the PC diet or the DS diets with added phytase. Yolk colour increased significantly with phytase supplementation. Supplementing the DS1 diet with 300 FTU and the DS2 diet with 600 FTU resulted in non-significant differences in tibia ash, Ca and P, compared to the PC diet. The data from this study indicated that applying the nutrient contributions for Buttiauxella phytase at 300 and 600 FTU/kg maintained the egg production, BW and egg quality parameters compared to PC. The best economic efficiency value during the whole experimental period was recorded with phytase at 600 FTU/kg when full matrix values are used. When commercial diets are formulated based on ISA breeder recommendations, lowering diet nutrient density while supplementing with phytase reduced the overall diet cost, which should contribute to the profitability of egg production.

Obesity rates are increasing worldwide. Potential reasons include excessive consumption of sugary beverages and energy-dense foods instead of more nutrient-rich options. On a per kJ basis, energy-dense grains, added sugars and fats cost less, whereas lean meats, seafood, leafy greens and whole fruit generally cost more. Given that consumer food choices are often driven by price, the observed social inequities in diet quality and health can be explained, in part, by nutrition economics. Achieving a nutrient-rich diet at an affordable cost has become progressively more difficult within the constraints of global food supply. However, given the necessary metrics and educational tools, it may be possible to eat better for less. New metrics of nutrient density help consumers identify foods, processed and unprocessed, that are nutrient-rich, affordable and appealing. Affordability metrics, created by adding food prices to food composition data, permit calculations of both kJ and nutrients per penny, allowing for new studies on the economic drivers of food choice. Merging dietary intake data with local or national food prices permits the estimation of individual-level diet costs. New metrics of nutrient balance can help identify those food patterns that provide optimal nutritional value. Behavioural factors, including cooking at home, have been associated with nutrition resilience, defined as healthier diets at lower cost. Studies of the energy and nutrient costs of the global food supply and diverse food patterns will permit a better understanding of the socioeconomic determinants of health. Dietary advice ought to be accompanied by economic feasibility studies.

A study was conducted to examine the effects of a multi-carbohydrase enzyme complex on the nutritive value of wheat in diets differing in nutrient density. It was hypothesised that response to enzyme inclusion would be greater in diets with lower nutrient density. The study was conducted using 1008 Ross 308 male broiler chicks (four treatments with seven replicate pens of 36 chicks). A 2 × 2 factorial arrangement of treatments was employed. Factors were adequate or low nutrient density with or without enzyme supplementation. The wheat-soybean meal based positive control (PC) diet was formulated to be nutritionally adequate in energy and digestible amino acids according to local industry recommendations. A negative control (NC) was formulated to have 80 kcal/kg less ME and 1.5% less digestible amino acids as compared to the PC. A multi-carbohydrase complex containing 19 carbohydrase activities derived from Penicillium funiculosum was added in both the PC and NC diets (Rovabio® Excel LC, Adisseo Asia Pacific Pte Ltd., Singapore). Birds fed the NC had 3.7 points (P < 0.05) poorer FCR than the PC. Across the diet type, enzyme supplementation increased body weight by 3.2% (P < 0.05) and improved FCR by 5.2 points (P < 0.01). There was no nutrient density x enzyme interaction (P > 0.05), indicating that performance improvement was independent of nutrient density. Apparent ileal digestibility of crude protein followed a similar trend, showing a 4.9% enhancement (P < 0.01) with the inclusion of the enzyme product in either diet. Enzyme supplementation reduced ileal viscosity by 39.0% (P < 0.05). It was concluded that multi-carbohydrase could overcome the negative effect in broiler performance brought by nutrient reduction, however, there was no indication that nutrient density affected bird response to supplementation of multi-carbohydrase.

Nutrient-rich food (NRF) index scores are dietary quality indices based on nutrient density. We studied the design aspects involved in the development and validation of NRF index scores, using the Dutch consumption data and guidelines as an example. We evaluated fifteen NRF index scores against the Dutch Healthy Diet Index (DHD-index), a measure of adherence to the Dutch dietary guidelines, and against energy density. The study population included 2106 adults from the Dutch National Food Consumption Survey 2007–2010. The index scores were composed of beneficial nutrients (protein, fibre, fatty acids, vitamins, minerals), nutrients to limit (saturated fat, sugar, Na) or a combination. Moreover, the influence of methodological decisions was studied, such as the choice of calculation basis (100 g or 100 kcal (418 kJ)). No large differences existed in the prediction of the DHD-index by the fifteen NRF index scores. The score that best predicted the DHD-index included nine beneficial nutrients and three nutrients to limit on a 100-kcal basis, the NRF9.3 with a model R2 of 0·34. The scores were quite robust with respect to sex, BMI and differences in calculation methods. The NRF index scores were correlated with energy density, but nutrient density better predicted the DHD-index than energy density. Consumption of vegetables, cereals and cereal products, and dairy products contributed most to the individual NRF9.3 scores. In conclusion, many methodological considerations underlie the development and evaluation of nutrient density models. These decisions may depend upon the purpose of the model, but should always be based upon scientific, objective and transparent criteria.

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

There is increasing concern that high intakes of added sugars might compromise intakes of micronutrients. The objectives of this systematic review were (1) to determine whether dietary added sugar intake was associated with micronutrient intakes, and if so, whether there was evidence of micronutrient dilution as a result of higher dietary added sugar intake and (2) if micronutrient dilution was present, to determine whether there was sufficiently robust evidence to support a threshold effect above which there was a significant decline in micronutrient intake or status relative to the recommended intakes. A systematic computerised literature search was undertaken, limited to studies written in English published from 1980 onwards and further studies identified through hand searching papers. Fifteen studies that assessed associations between intakes of added sugars or non-milk extrinsic sugars and micronutrients were included. Overall, there are insufficient data and inconsistency between studies in relationships between added sugars and micronutrient intakes, with no clear evidence of micronutrient dilution or a threshold for a quantitative amount of added sugar intake for any of the micronutrients investigated. The current evidence base is considerably constrained by methodological issues. Further research is required to determine which food products high in added sugars might adversely affect micronutrient intakes by displacing other food items from the diet. Analyses should take into account the magnitude of any observed associations to determine their true biological significance.

Nutrient density, the vitamin or mineral content of a food or diet per unit energy, has long been a useful concept in the nutritional sciences. However, few nutritionists have applied the idea in quantitative, population-based nutrition planning and assessment. This paper discusses the conceptual issues related to the calculation of a nutrient density value that, if consumed, should meet the nutrient needs of most individuals in a population or sub-population, and outlines several methods for estimating this value. The paper also discusses the potential influence on the estimate's validity of factors such as skewed distributions and correlated energy intake and nutrient requirement.

When formulating least-cost poultry diets, ME concentration should be optimised by an iterative procedure, not entered as a fixed value. This iteration must calculate profit margins by taking into account the way in which feed intake and saleable outputs vary with ME concentration.

In the case of broilers, adjustment of critical amino acid contents in direct proportion to ME concentration does not result in birds of equal fatness. To avoid an increase in fat deposition at higher energy levels, it is proposed that amino acid specifications should be adjusted in proportion to changes in the net energy supplied by the feed. A model is available which will both interpret responses to amino acids in laying trials and give economically optimal estimates of amino acid inputs for practical feed formulation. Flocks coming into lay and flocks nearing the end of the pullet year have bimodal distributions of rates of lay, with the result that calculations of requirement based on mean output will underestimate the optimal amino acid input for the flock.

Chick diets containing surplus protein can lead to impaired utilisation of the first-limiting amino acid. This difficulty can be avoided by stating amino acid requirements as a proportion of the protein.

This study evaluated the tracking of energy and nutrient intakes, assessed by diet history, in a random sample of adolescents (boys n 225, girls n 230) at baseline (age 12 years), and subsequently at age 15 years. Median energy (MJ/d) and macronutrient (g/d) intakes increased significantly (all P<0·001) with increasing age in the boys. The girls' reported energy intake (MJ/d) remained stable over time, despite significant increases in BMI, weight and % body fat. Age-related changes in the girls' macronutrient intakes were inconsistent. When expressed in terms of nutrient density, the diets of both sexes became significantly richer, over time, in total folate (both sexes, P<0·01), but poorer in Ca (boys P<0·01, girls P<0·001) and riboflavin (both sexes P<0·001). Vitamin B6 (P<0·001) and Fe (P<0·05) densities increased in the boys, while the thiamin density of the girls' diets decreased (P<0·001). Tracking, defined as maintenance of rank over time, was summarised using weighted kappa statistics (κ). There were some significant changes in intakes at the group level; however, tracking of energy and nutrients in both sexes was only poor to fair (κ<0·40), indicating substantial drift of individuals between classes of intake over time. Particularly poor tracking was evident for % energy from sugars (κ 0·09) and total fat (κ 0·09) in the girls' diets. In conclusion, the poor to fair tracking observed in this cohort suggests that individual dietary patterns exhibited at 12 years of age are unlikely to be predictive of energy and nutrient intake at age 15 years.