Food Composition Databases: Considerations about Complex Food Matrices

FooDOxS: a database of oxidized sterols content in foods

Dietary oxidized sterols (DOxS) are cholesterol-like molecules known to exert pro-inflammatory, pro-oxidant, and pro-apoptotic effects, among others. We present the FooDOxS database, a comprehensive compilation of DOxS content in over 1680 food items from 120 publications across 25 countries, augmented by data generated by our group. This database reports DOxS content in foods classified under the NOVA and What We Eat in America (WWEIA) systems, allowing a comprehensive and statistically robust summary of DOxS content in foods. Notably, we evaluated the efficacy of using NOVA and WWEIA classifications in capturing DOxS variations across food categories. Our findings provide insights into the strengths and limitations of these classification systems, enhancing their utility for assessing dietary components. This research contributes to the understanding of DOxS in food processing and suggests refinements for classification systems, holding promise for improved food safety and public health assessments.

LIFANA - toward developing a meal recommender system as a dietary support app for the elderly

Background: Though a variety of eHealth/mHealth dietary solutions exist, many are ill-adapted to the target population and local eating habits. A specific need exists for the elderly, a growing vulnerable population with limited digital literacy. The LIFANA project aimed at developing a mobile nutrition solution, i.e. a dietary meal-recommender app for personalized meal planning useful for the elderly. Methods: In addition to considering age, gender, and physical activity, the app assured sufficient intake of calories and proteins. The solution was optimized to consider local eating culture in Portugal (PT)/The Netherlands (NL) where it was tested. Recipes (>300) were included and aligned with national food composition dietary databases (FCDBs) to analyse their nutritional values for meal planning. Individual dietary preferences, food restrictions (i.e., allergies), and budget considerations were included in the user profile. The development process involved user integration, including focus groups and usability evaluations, followed by longer field trials in Portugal (n=53 participants, age 60-81 y, 14 months) and the Netherlands (n=107, age 52-86 y, 3 months). Endpoints regarding acceptance/usage frequency, anthropometric measures and (in PT) blood pressure and body fat were collected. Results: 23/34 elderly finalized the trials in PT/NL. No significant changes in anthropometry or other assessed markers, including blood pressure, were observed. 9% (NL) and 47% (PT) of users reported that they would consider using the solution if it were on the market. Conclusions: Via an iterative adaptive process, a dietary app was developed and improved that demonstrated acceptance/user-friendliness comparable to other tools available on the market and allowed - despite the COVID crisis - for stable anthropometric markers and blood pressure. However, it was also observed that additional features, such as a link to an online shopping app, and closer personal follow-up was associated with increased usability and acceptance of the solution and thus further personalization and nudges are warranted to increase employment of such dietary apps.

Development of a Database of LanguaLTM and FoodEx2 Codes of 50 Ready-to-Eat Products

Ready-to-eat (RTE) and ready-to-heat (RTH) dishes are food items that help save time, physical energy, and mental effort in all food-related activities. Convenience of use, variability of supply, and adaptability to different consumption occasions have led to an increase of acceptance among consumers through the years. Specialized databases can help in this context, where food composition databases can provide information and data to create sustainable nutritional models by reducing the now growing number of chronic diseases. This paper aims at developing a database of LanguaLTM and FoodEx2 codes of 50 food preparations and ready-to-eat dishes designed for consumption outside the home. LanguaLTM, as well as FoodEx2, are classification and description systems for indexing, in the sense of a systematic description, of foods based on a hierarchical model (parent-child relationship), thus facilitating the international exchange of data on food composition, consumption, assessing chronic and/or acute exposure to a certain agent, and not least the assessment of nutrient intake. The database, here presented, consists of the codes of fifty ready-to-eat products present on the market in Italy, obtained by using the two mostly commonly used and widely recognized coding systems: LanguaLTM and FoodEx2. This database represents a tool and a guideline for other compilers and users to apply coding systems to ready-to-eat products. Moreover, it can be represented a resource for several applications, such as nutritional cards, nutritional facts, food labels, or booklet and brochures for promotion of food products, to be used at health and food nutrition interface, useful for consumers, dieticians, and food producers.

Dietary (poly)phenols and cardiometabolic health: from antioxidants to modulators of the gut microbiota

(Poly)phenols are plant secondary metabolites widely abundant in plant foods and beverages comprising a very large number of compounds with diverse structure and biological activities. Accumulating evidence indicates that these compounds exert beneficial effects against cardiometabolic diseases, and this review will provide a summary of current knowledge in this area. Epidemiological and clinical data collectively suggest that intake of flavonoids reduces the risk of cardiovascular disease (CVD), with the evidence being particularly strong for the flavan-3-ol subclass. However, to provide adequate dietary recommendations, a better understanding of their estimated content in foods and intake among the general public is needed. Regarding mechanisms of action, we now know that it is unlikely that (poly)phenols act as direct antioxidants in vivo, as it was hypothesised for decades with the popularity of in vitro antioxidant capacity assays. One of the reasons is that upon ingestion, (poly)phenols are extensively metabolised into a wide array of circulating metabolites with different bioactivities than their precursors. Well-conducted in vitro and in vivo studies and human nutrigenomic analysis have revealed new molecular targets that may be underlying the health benefits of (poly)phenols, such as the nitric oxide pathway. Recently, a bi-directional relationship was established between (poly)phenols and the gut microbiota, suggesting that individual gut microbial metabolising capacity may be a key factor explaining the variability in the cardiometabolic response to (poly)phenols. Future research is needed to elucidate which are the key factors affecting such capacity, and whether it can be modulated, along with the mechanisms of action.

How Do Brazilian Consumers Understand Food Groups in the Food-based Dietary Guidelines?

In the Food-based Dietary Guidelines (FBDGs), food classification is based on food groups and nutrient sources. Much research has already investigated multiple aspects of consumer understanding of the information described in these documents. However, no study has evaluated consumer understanding of all food items contained in the groups described in the FBDGs. This study aimed to assess Brazilian consumers' understanding of food classification according to food groups in the concepts of the FBDGs. Therefore, an instrument, Consumer Understanding of Food Groups (UFG), was constructed and validated to assess consumer understanding of food groups. The instrument comprised 44 items approved by experts (agreement > 80%). A total of 894 Brazilians from all regions participated in this study. The results suggest that 48.9% of the participants believe it is easier to classify food according to food groups. The classification of food groups is based on the origin of the food (animal and vegetable). Although consumers easily recognize foods according to their origin, we still identify asymmetries regarding including food items from the animal kingdom and species from the plant kingdom. This exploratory study highlights important information that can contribute to improving the FBDGs. It is essential to consider consumers' understanding and guide them regarding choices from a technical point of view.

Multi-omic approaches for host-microbiome data integration

The gut microbiome interacts with the host through complex networks that affect physiology and health outcomes. It is becoming clear that these interactions can be measured across many different omics layers, including the genome, transcriptome, epigenome, metabolome, and proteome, among others. Multi-omic studies of the microbiome can provide insight into the mechanisms underlying host-microbe interactions. As more omics layers are considered, increasingly sophisticated statistical methods are required to integrate them. In this review, we provide an overview of approaches currently used to characterize multi-omic interactions between host and microbiome data. While a large number of studies have generated a deeper understanding of host-microbiome interactions, there is still a need for standardization across approaches. Furthermore, microbiome studies would also benefit from the collection and curation of large, publicly available multi-omics datasets.

Is There a Convergence between the Food Classification Adopted by Food-Based Dietary Guidelines and Food Science and Technology?

The World Health Organization (WHO) proposed the dietary guidelines presented as the Food-based Dietary Guidelines (FBDG). The FBDG classify foods according to their origin, nature, nutrient source, food group, and processing level. Food science and technology (FST) ranks food according to its origin, perishability, nutrient source, processing, food group, and formulation. This paper aimed to compare the convergence points for food classification according to the FBDG and FST. This study was carried out in two phases. The first step was identifying the Food-Based Dietary Guidelines (FBDG). For each of the FBDG, food items were grouped as fruits, vegetables, cereals, sugars, fat and oils, legumes, foods from animals, dairy products, and others. The second step aimed to identify and describe the different food classification systems. The search was performed on PubMed®, Science Direct, and Web of Science and websites of international organizations such as the Food and Agriculture Organization of the United Nations (FAO), the World Health Organization (WHO), and the Codex Alimentarius. Our results show that the points of convergence between the classifications were the classification in terms of origin (animal and vegetable), nutrient sources, and food groups. However, inconsistencies were observed for the distribution of food items in each group in the 98 surveyed FBDG. As for nature, there was a convergence for in natura, minimally processed, and processed foods. However, the criteria adopted for minimally processed and processed foods described in the FBDG differ from those considered by the FST. FST also does not recognize the classification of foods concerning the level of processing.

Associations between dietary variety, portion size and body weight: prospective evidence from UK Biobank participants

'Dietary variety' has been identified as a factor associated with food intake. Whilst this relationship may have longer-term benefits for body weight management when eating low-energy, nutrient-dense foods, it may increase the risk of overconsumption (and body adiposity) when foods are high energy density. This study sought to further explore pathways underpinning the relationship between dietary variety and body weight, by considering energy density as a moderating factor and portion size as a mediating factor in this relationship. Using prospective data from the UK Biobank, dietary variety scores (DVS), cumulative portion size and energy density were derived from 24-h dietary recall questionnaires at baseline and follow-up. BMI, whole-body fat percentage and fat-free mass were included as outcomes. Contrary to predictions, linear multiple regression models found some evidence of a negative, direct association between DVS and body weight outcomes at baseline (b = -0·13). Though dietary variety was significantly associated with larger portions across time points (b = 41·86-82·64), a moderated mediation effect was not supported at baseline or follow-up (Index ≤ 0·035). Taken together, these findings provide population-level evidence to support a positive association between variety and food intake, which in turn has potential implications for body weight management, both in terms of moderating food intake and benefitting diet quality.

Food Composition Databases (FCDBs): A Bibliometric Analysis

Food composition databases (FCDBs) are important tools that provide information on the nutritional content of foods. Previously, it was largely unclear what nutritional contents and which FCDBs were involved in highly cited papers. The bibliometric study aimed to identify the most productive authors, institutions, and journals. The chemicals/chemical compounds with high averaged citations and FCDBs used by highly cited papers were identified. In July 2023, the online database Web of Science Core Collection (WoSCC) was queried to identify papers related to FCDBs. A total of 803 papers were identified and analyzed. The first paper indexed in WoSCC was published in 1992 by Pennington, which described the usefulness of FCDB for researchers to identify core foods for their own studies. In that paper, the FCDB described was the USDA 1987-88 NFCS (the United States Department of Agriculture 1987-88 Nationwide Food Consumption Survey). The most productive author was Dr. Paul M. Finglas, the Head of the Food Databanks National Capability at the Quadram Institute (Norwich, UK) and the Managing Director of EuroFIR. His most cited paper among this dataset was about the development of an online Irish food composition database together with EuroFIR. The most productive institutions were the USDA and the World Health Organization (WHO) instead of universities. Flavonoid was the most recurring chemical class among the highly cited ones. The anti-oxidative properties and protective effects against heart disease and cancer of flavonoids might be some of the reasons for their popularity in research. Among the highly cited papers, the most heavily used FCDBs were the USDA database for the flavonoid content of selected foods, Fineli, the USDA National Nutrient Database for Standard Reference (USNDB), EuroFIR eBASIS-Bioactive Substances in Food Information Systems, and Phenol-Explorer. High-quality national and international FCDBs should be promoted and made more accessible to the research and public communities to promote better nutrition and public health on a global scale.

Machine learning accurately predicts food exchange list and the exchangeable portion

Introduction

Food Exchange Lists (FELs) are a user-friendly tool developed to help individuals aid healthy eating habits and follow a specific diet plan. Given the rapidly increasing number of new products or access to new foods, one of the biggest challenges for FELs is being outdated. Supervised machine learning algorithms could be a tool that facilitates this process and allows for updated FELs-the present study aimed to generate an algorithm to predict food classification and calculate the equivalent portion.

Methods

Data mining techniques were used to generate the algorithm, which consists of processing and analyzing the information to find patterns, trends, or repetitive rules that explain the behavior of the data in a food database after performing this task. It was decided to approach the problem from a vector formulation (through 9 nutrient dimensions) that led to proposals for classifiers such as Spherical K-Means (SKM), and by developing this idea, it was possible to smooth the limits of the classifier with the help of a Multilayer Perceptron (MLP) which were compared with two other algorithms of machine learning, these being Random Forest and XGBoost.

Results

The algorithm proposed in this study could classify and calculate the equivalent portion of a single or a list of foods. The algorithm allows the categorization of more than one thousand foods with a confidence level of 97% at the first three places. Also, the algorithm indicates which foods exceed the limits established in sodium, sugar, and/or fat content and show their equivalents.

Discussion

Accurate and robust FELs could improve implementation and adherence to the recommended diet. Compared with manual categorization and calculation, machine learning approaches have several advantages. Machine learning reduces the time needed for manual food categorization and equivalent portion calculation of many food products. Since it is possible to access food composition databases of various populations, our algorithm could be adapted and applied in other databases, offering an even greater diversity of regional products and foods. In conclusion, machine learning is a promising method for automation in generating FELs. This study provides evidence of a large-scale, accurate real-time processing algorithm that can be useful for designing meal plans tailored to the foods consumed by the population. Our model allowed us not only to distinguish and classify foods within a group or subgroup but also to perform the calculation of an equivalent food. As a neural network, this model could be trained with other food bases and thus improve its predictive capacity. Although the performance of the SKM model was lower compared to other types of classifiers, our model allows selecting an equivalent food not from a group previously classified by machine learning but with a fully interpretable algorithm such as cosine similarity for comparing food.

Food exchange list based on macronutrients: adapted for the Ecuadorian population

Background

Food exchange lists allow health professionals to generate healthy eating plans adapted to individual or population needs. The objective of this study was to develop the first food exchange list based on the macronutrients and energy provided by the various food groups of the Ecuadorian diet.

Methods

The list of Ecuadorian food exchanges was constructed by going through the following phases: (1) Selection of household measurements; (2) Selection of tables and databases of the nutritional composition of food items; (3) Definition of food groups and quantities; (4) Determination of the average energy and macronutrient values of each group; and (5) Photographic record. For the definition of food quantities, statistical criteria were applied according to a standard deviation of ±2SD; thus, for carbohydrates: ±5 g, total fat: ±2 g, and protein: ±3 g. To ensure the inclusion of the food items in the groups, a coefficient of variation of less than 30% and a Z value of ±2 were also considered.

Results

The list of food exchanges is presented with eight general groups according to the predominant nutrient (carbohydrates, proteins, or fats), and, where necessary, subgroups are included according to the second predominant nutrient. The list includes 404 food items with their photographic record, represented by their net weights and corresponding household measurement. All food items met the statistical criteria that help to reduce the variability of the nutritional composition of the food items in each group.

Conclusion

This is the first list of Ecuadorian food exchanges based on statistical criteria. It represents a novel tool for public health professionals as well as researchers. Resulting healthier eating plans may improve daily dietetic practice, facilitate better clinical trial designs and help establish guidelines according to Ecuador's cultural and dietary patterns. The described methodology can further be used to develop other food exchanges lists for patients with specific nutritional requirements.

Effects of Different Heating Treatments on the Antioxidant Activity and Phenolic Compounds of Ecuadorian Red Dacca Banana

The banana is a tropical fruit characterized by its composition of healthy and nutritional compounds. This fruit is part of traditional Ecuadorian gastronomy, being consumed in a wide variety of ways. In this context, unripe Red Dacca banana samples and those submitted to different traditional Ecuadorian heating treatments (boiling, roasting, and baking) were evaluated to profile their phenolic content by ultra-high-performance liquid chromatography coupled to high-resolution mass spectrometry (UHPLC-HRMS) and the antioxidant activity by ORAC, ABTS, and DPPH assays. A total of sixty-eight phenolic compounds were identified or tentatively identified in raw banana and treated samples, highlighting the content in flavonoids (flavan-3-ols with 88.33% and flavonols with 3.24%) followed by the hydroxybenzoic acid family (5.44%) in raw banana samples. The total phenolic compound content significantly decreased for all the elaborations evaluated, specifically from 442.12 mg/100 g DW in fresh bananas to 338.60 mg/100 g DW in boiled (23.41%), 243.63 mg/100 g DW in roasted (44.90%), and 109.85 mg/100 g DW in baked samples (75.15%). Flavan-3-ols and flavonols were the phenolic groups most affected by the heating treatments, while flavanones and hydroxybenzoic acids showed higher stability against the heating treatments, especially the boiled and roasted samples. In general, the decrease in phenolic compounds corresponded with a decline in antioxidant activity, evaluated by different methods, especially in baked samples. The results obtained from PCA studies confirmed that the impact of heating on the composition of some phenolic compounds was different depending on the technique used. In general, the heating processes applied to the banana samples induced phytochemical modifications. Even so, they remain an important source of bioactive compounds for consumers.

When Machine Learning and Deep Learning Come to the Big Data in Food Chemistry

Since the first food database was released over one hundred years ago, food databases have become more diversified, including food composition databases, food flavor databases, and food chemical compound databases. These databases provide detailed information about the nutritional compositions, flavor molecules, and chemical properties of various food compounds. As artificial intelligence (AI) is becoming popular in every field, AI methods can also be applied to food industry research and molecular chemistry. Machine learning and deep learning are valuable tools for analyzing big data sources such as food databases. Studies investigating food compositions, flavors, and chemical compounds with AI concepts and learning methods have emerged in the past few years. This review illustrates several well-known food databases, focusing on their primary contents, interfaces, and other essential features. We also introduce some of the most common machine learning and deep learning methods. Furthermore, a few studies related to food databases are given as examples, demonstrating their applications in food pairing, food-drug interactions, and molecular modeling. Based on the results of these applications, it is expected that the combination of food databases and AI will play an essential role in food science and food chemistry.

Review on retention of long-chain omega-3 polyunsaturated fatty acids (EPA and DHA) in fish as affected by cooking methods

Fatty acids are essential building blocks for the structural components of the cells, tissues, organs, and certain biologically active substances synthesis. Omega-3 polyunsaturated fatty acids are long-chain fatty acids essential for several biological functions including oxidative stress reduction and cardiovascular safety. Diet rich in omega-3 fatty acids is well acknowledged as beneficial to one's health and well-being. For the development of balanced diets, the nutrient content of raw and cooked foods is crucial. However, cooking method, animal age, and carcass characteristics might affect nutrient retention during cooking, and these factors are often unique to specific countries. This review thus provides a general overview of several cooking effects on long-chain omega-3 retention in fish. It can be concluded that the DHA and EPA's true retention values are correlated to the impact of different cooking treatments.

Dietary Intakes of Slovenian Adults and Elderly: Design and Results of the National Dietary Study SI.Menu 2017/18

Incomparable and insufficiently detailed information on dietary intakes are common challenges associated with dietary assessment methods. Being a European Union country, Slovenia is expected to conduct national food consumption studies in line with harmonised EU Menu methodology. The present study aimed to describe the methodology and protocols in the Slovenian nationally representative dietary survey SI.Menu 2017/18, and to assess population dietary habits with respect to food consumption and energy and macronutrient intakes. While the study targeted various population groups, this report is focused on adults. A representative sample of participants was randomly selected from the Central Register of Population according to sex, age classes and place of residency, following a two-stage stratified sampling procedure. Information on food consumption was collected with two non-consecutive 24-h dietary recalls using a web-based Open Platform for Clinical Nutrition (OPEN) software. Data were complemented with a food propensity questionnaire to adjust for usual intake distribution. Altogether, 364 adults (18–64 years) and 416 elderlies (65–74 years) were included in the data analyses. Study results highlighted that observed dietary patterns notably differ from food-based dietary guidelines. Typical diets are unbalanced due to high amounts of consumed meat and meat products, foods high in sugar, fat and salt, and low intake of fruits and vegetables and milk and dairy products. Consequently, the energy proportion of carbohydrates, proteins, and to some extent, free sugars and total fats, as well as intake of dietary fibre and total water deviates from the reference values. Age and sex were significantly marked by differences in dietary intakes, with particularly unfavourable trends in adults and men. Study results call for adoption of prevention and public health intervention strategies to improve dietary patterns, taking into account population group differences. In addition, all developed protocols and tools will be useful for further data collection, supporting regular dietary monitoring systems and trend analyses.

Development of a nutrition management software based on selected Middle Eastern and Mediterranean dishes to support personalized diet and weight management

The nutrient composition of 50 commonly consumed Jordanian food dishes was determined to support the development of a novel nutrition management system designed to assist with dietary intake assessment and diet management. Composite dishes were selected by interviewing households located in the northern region of Jordan. For each dish, five different recipes were collected from experienced chefs and the typical recipe was formulated based on the average weights of ingredients and net weight of the dish. Proximate composition as well as vitamin and mineral contents were determined and related to ingredient composition and cooking conditions. The newly created food composition database was used to develop a user-centric nutrition management software tailored to reflect the characteristics of the Jordanian diet with representative items from this diet. This novel nutrition management system is customizable, enabling users to build daily meal plans in accordance with personalized dietary needs and goals.

Assessments of risk of bias in systematic reviews of observational nutritional epidemiologic studies are often not appropriate or comprehensive: a methodological study

BACKGROUND

An essential component of systematic reviews is the assessment of risk of bias. To date, there has been no investigation of how reviews of non-randomised studies of nutritional exposures (called 'nutritional epidemiologic studies') assess risk of bias.

OBJECTIVE

To describe methods for the assessment of risk of bias in reviews of nutritional epidemiologic studies.

METHODS

We searched MEDLINE, EMBASE and the Cochrane Database of Systematic Reviews (Jan 2018-Aug 2019) and sampled 150 systematic reviews of nutritional epidemiologic studies.

RESULTS

Most reviews (n=131/150; 87.3%) attempted to assess risk of bias. Commonly used tools neglected to address all important sources of bias, such as selective reporting (n=25/28; 89.3%), and frequently included constructs unrelated to risk of bias, such as reporting (n=14/28; 50.0%). Most reviews (n=66/101; 65.3%) did not incorporate risk of bias in the synthesis. While more than half of reviews considered biases due to confounding and misclassification of the exposure in their interpretation of findings, other biases, such as selective reporting, were rarely considered (n=1/150; 0.7%).

CONCLUSION

Reviews of nutritional epidemiologic studies have important limitations in their assessment of risk of bias.

Development of an Unified Food Composition Database for the European Project "Stance4Health"

The European Commission funded project Stance4Health (S4H) aims to develop a complete personalised nutrition service. In order to succeed, sources of information on nutritional composition and other characteristics of foods need to be as comprehensive as possible. Food composition tables or databases (FCT/FCDB) are the most commonly used tools for this purpose. The aim of this study is to describe the harmonisation efforts carried out to obtain the Stance4Health FCDB. A total of 10 FCT/FCDB were selected from different countries and organizations. Data were classified using FoodEx2 and INFOODS tagnames to harmonise the information. Hazard analysis and critical control points analysis was applied as the quality control method. Data were processed by spreadsheets and MySQL. S4H’s FCDB is composed of 880 elements, including nutrients and bioactive compounds. A total of 2648 unified foods were used to complete the missing values of the national FCDB used. Recipes and dishes were estimated following EuroFIR standards via linked tables. S4H’s FCDB will be part of the smartphone app developed in the framework of the Stance4Health European project, which will be used in different personalized nutrition intervention studies. S4H FCDB has great perspectives, being one of the most complete in terms of number of harmonized foods, nutrients and bioactive compounds included.

Ethnomycological Knowledge of Three Ethnic Groups in Ethiopia

Ethnomycological information was gathered by conducting semi-structured interviews with members of the Amhara, Agew, and Sidama ethnic groups in Ethiopia. A total of 300 individuals were involved in this study. Forest excursions were also undertaken to investigate the habitat and to identify useful wild mushroom species present in the study areas. A total of 24 useful wild mushroom species were identified. Among the three ethnic groups, the Sidama have the most extensive ethnomycological knowledge and over seven vernacular names for useful fungal species were recorded for this group. Collecting mushrooms is common practice among the Sidama and usually carried out by women and children during the main rainy season from June to September. Useful mushrooms are collected in natural forests, plantation forests, grazing areas, home gardens, and swampy areas. In terms of medicinal uses, Lycoperdon perlatum Pers. and Calvatia rubroflava (Cragin) Lloyd. are well-known treatments for wounds and skin disease. Harvest storage of wild mushroom species is unknown. Respondents in the Amhara and Agew ethnic groups were similar in terms of their use and knowledge of mushrooms. Both ethnic groups reported that although wild mushroom species were consumed by their grandparents, they do not eat mushrooms themselves, which could eventually represent a loss of mycological knowledge in these two ethnic groups. Such inconsistency between ethnic groups in terms of their knowledge may also be linked to the social valuation of mushroom resources, which could easily be mitigated by raising awareness. Thus, the baseline information obtained in this study could be useful for further investigations and documentation, and to promote ethnomycological benefits to different ethnic groups in countries with similar settings.

Bridging the food security gap: an information-led approach to connect dietary nutrition, food composition and crop production

BACKGROUND

Food security is recognized as a major global challenge, yet human food-chain systems are inherently not geared towards nutrition, with decisions on crop and cultivar choice not informed by dietary composition. Currently, food compositional tables and databases (FCT/FCDB) are the primary information sources for decisions relating to dietary intake. However, these only present single mean values representing major components. Establishment of a systematic controlled vocabulary to fill this gap requires representation of a more complex set of semantic relationships between terms used to describe nutritional composition and dietary function.

RESULTS

We carried out a survey of 11 FCT/FCDB and 177 peer-reviewed papers describing variation in nutritional composition and dietary function for food crops to identify a comprehensive set of terms to construct a controlled vocabulary. We used this information to generate a Crop Dietary Nutrition Data Framework (CDN-DF), which incorporates controlled vocabularies systematically organized into major classes representing nutritional components and dietary functions. We demonstrate the value of the CDN-DF for comparison of equivalent components between crop species or cultivars, for identifying data gaps and potential for formal meta-analysis. The CDN-DF also enabled us to explore relationships between nutritional components and the functional attributes of food.

CONCLUSION

We have generated a structured crop dietary nutrition data framework, which is generally applicable to the collation and comparison of data relevant to crop researchers, breeders, and other stakeholders, and will facilitate dialogue with nutritionists. It is currently guiding the establishment of a more robust formal ontology. © 2019 Society of Chemical Industry.

From carbohydrates to fat: Trends in food intake among Swedish nutrition students from 2002 to 2017

Earlier studies have implied a change in dietary habits of the Swedish population towards a low carbohydrate, high fat diet. Questions have been raised about the development in recent years and potential health effects. We have investigated the dietary intake of Swedish female students enrolled in a university nutrition course between 2002 and 2017. The students carried out self-reporting of all food and drink intake over one weekday and one weekend day. Intake of macronutrients (E%) and micronutrients were calculated for the whole period while statistical analysis was performed for changes between 2009 and 2017 (729 women). Results showed significant changes in carbohydrate intake (from 47.0 to 41.4 E%) and fat intake (from 31.7 to 37.5 E%). Carbohydrate intake was significantly lower than the Nordic Nutrition Recommendations (45–60 E%). However, daily fiber intake remains high (3.0 g/MJ) in a national context, and intake of vitamin D and folate appears to increase during the period. The results suggest that the observed national transition from carbohydrate to fat intake persists, and that it might be especially evident among individuals interested in food and nutrition. Considering the fiber and micronutrient intake, the change is not necessarily unfavorable for this particular group.

MIGHT: Statistical Methodology for Missing-Data Imputation in Food Composition Databases

This paper addresses the problem of missing data in food composition databases (FCDBs). The missing data can be either for selected foods or for specific components only. Most often, the problem is solved by human experts subjectively borrowing data from other FCDBs, for data estimation or imputation. Such an approach is not only time-consuming but may also lead to wrong decisions as the value of certain components in certain foods may vary from database to database due to differences in analytical methods. To ease missing-data borrowing and increase the quality of missing-data selection, we propose a new computer-based methodology, named MIGHT - Missing Nutrient Value Imputation UsinG Null Hypothesis Testing, that enables optimal selection of missing data from different FCDBs. The evaluation on a subset of European FCDBs, available through EuroFIR and complied with the Food data structure and format standard BS EN 16104 published in 2012, proves that, in more than 80% of selected cases, MIGHT gives more accurate results than techniques currently applied for missing value imputation in FCDBs. MIGHT deals with missing data in FCDBs by introducing rules for missing data imputation based on the idea that proper statistical analysis can decrease the error of data borrowing.

Effects of Industrial Boiling on the Nutritional Profile of Common Octopus (Octopus vulgaris)

Industrial cooking of common octopus (Octopus vulgaris) under well-established procedures is advantageous for current consumers, which demand healthy and convenient food. This work aimed to evaluate the effect of industrial water boiling, without the addition of salt, on the nutritional profile of common octopus. True retentions (TRs) were calculated for essential nutrients and toxic elements. After boiling, the moisture content decreased, resulting in a concentration of other constituents (protein, fat, fatty acids, majority of amino acids, phosphorus, zinc, and iodine). High TRs were obtained for some essential nutrients: 90.2% (eicosapentaenoic acid, EPA), 89.1% (docosahexaenoic acid, DHA), ≥74.6% (indispensable amino acids, IAA), and 86.8% (iodine). In both raw and boiled octopus, polyunsaturated fatty acids (252.2 and 425.1 mg/100 g), leucine (940.1 and 1613.4 mg/100 g), glutamate (1971.5 and 3257.1 mg/100 g), sodium (393.3 and 332.5 mg/100 g), and zinc (12.6 and 16.6 mg/kg) were, respectively, the most abundant fatty acids, IAA, dispensable amino acids, macro, and micro elements. Cadmium, lead, and mercury levels found in boiled octopus were 0.02, 0.10, and 0.08 mg/kg, respectively. The consumption of 150 g (usual portion) of boiled octopus is advisable because it contributes to significant daily intakes of EPA+DHA (>100%), selenium (75.6%), and iodine (12.4%), and 25% of the daily adequate intake of sodium for adults.

The Close Linkage between Nutrition and Environment through Biodiversity and Sustainability: Local Foods, Traditional Recipes, and Sustainable Diets

This special issue, “The Close Linkage between Nutrition and Environment through Biodiversity and Sustainability: Local Foods, Traditional Recipes, and Sustainable Diets” is focused on the close correlation between the potential benefits and “functional role” of a food and the territory, including papers on the characterization of local foods and traditional recipes, on the promotion of traditional dietary patterns and sustainable diets.

Evaluation of the Recipe Function in Popular Dietary Smartphone Applications, with Emphasize on Features Relevant for Nutrition Assessment in Large-Scale Studies

Nutrient estimations from mixed dishes require detailed information collection and should account for nutrient loss during cooking. This study aims to make an inventory of recipe creating features in popular food diary apps from a research perspective and to evaluate their nutrient calculation. A total of 12 out of 57 screened popular dietary assessment apps included a recipe function and were scored based on a pre-defined criteria list. Energy and nutrient content of three recipes calculated by the apps were compared with a reference procedure, which takes nutrient retention due to cooking into account. The quality of the recipe function varies across selected apps with a mean score of 3.0 (out of 5). More relevant differences (larger than 5% of the Daily Reference Intake) between apps and the reference were observed in micronutrients (49%) than in energy and macronutrients (20%). The primary source of these differences lies in the variation in food composition databases underlying each app. Applying retention factors decreased the micronutrient contents from 0% for calcium in all recipes to more than 45% for vitamins B6, B12, and folate in one recipe. Overall, recipe features and their ability to capture true nutrient intake are limited in current apps.

A Disaggregation Methodology to Estimate Intake of Added Sugars and Free Sugars: An Illustration from the UK National Diet and Nutrition Survey

Various and inconsistent definitions for free and added sugars are used in the consideration and assessment of dietary intakes across public health, presenting challenges for nutritional surveillance, research, and policy. Furthermore, analytical methods to identify those sugars which are not naturally incorporated into the cellular structure of foods are lacking, thus free and added sugars are difficult to estimate in an efficient and accurate way. We aimed to establish a feasible and accurate method that can be applied flexibly to different definitions. Based on recipe disaggregation, our method involved five steps and showed good repeatability and validity. The resulting Free Sugars Database provided data for seven components of sugars; (1) table sugar; (2) other sugars; (3) honey; (4) fruit juice; (5) fruit puree; (6) dried fruit; and (7) stewed fruit, for ~9000 foods. Our approach facilitates a standardized and efficient assessment of added and free sugars, offering benefit and potential for nutrition research and surveillance, and for the food industry, for example to support sugar reduction and reformulation agendas.