Beyond nutrient-based food indices: a data mining approach to search for a quantitative holistic index reflecting the degree of food processing and including physicochemical properties

Ultraprocessed foods and chronic kidney disease-double trouble

High energy intake combined with low physical activity generates positive energy balance, which, when maintained, favours obesity, a highly prevalent morbidity linked to development of non-communicable chronic diseases, including chronic kidney disease (CKD). Among many factors contributing to disproportionately high energy intakes, and thereby to the obesity epidemic, the type and degree of food processing play an important role. Ultraprocessed foods (UPFs) are industrialized and quite often high-energy-dense products with added sugar, salt, unhealthy fats and food additives formulated to be palatable or hyperpalatable. UPFs can trigger an addictive eating behaviour and is typically characterized by an increase in energy intake. Furthermore, high consumption of UPFs, a hallmark of a Western diet, results in diets with poor quality. A high UPF intake is associated with higher risk for CKD. In addition, UPF consumption by patients with CKD is likely to predispose and/or to exacerbate uraemic metabolic derangements, such as insulin resistance, metabolic acidosis, hypertension, dysbiosis, hyperkalaemia and hyperphosphatemia. Global sales of UPFs per capita increased in all continents in recent decades. This is an important factor responsible for the nutrition transition, with home-made meals being replaced by ready-to-eat products. In this review we discuss the potential risk of UPFs in activating hedonic eating and their main implications for health, especially for kidney health and metabolic complications of CKD. We also present various aspects of consequences of UPFs on planetary health and discuss future directions for research to bring awareness of the harms of UPFs within the CKD scenario.

Association between Consumption of Ultra-Processed Food and Body Composition of Adults in a Capital City of a Brazilian Region

The present study investigates the relationship between the consumption of ultra-processed foods (UPF) and anthropometric indices of body composition in adults and seniors living in Teresina, the state capital of an area in northeastern Brazil. The article seeks to address two questions: Is UPF consumption linked to worsening body composition in different age groups? Do anthropometric indicators of body composition change with the increasing consumption of UPF? The study is a cross-sectional, household, population study, carried out with 490 adults and seniors. The food consumption was obtained with a 24 h food recall, and the foods were classified using NOVA. Anthropometric indicators evaluated were waist-to-height ratio, triceps skinfold thickness, arm circumference, corrected arm muscle area, subscapular skinfold thickness, and calf circumference. The association between energy contribution of UPF with anthropometric indicators was verified with a simple and multiple linear regression analysis. Individuals aged 20 to 35 years showed a significant association between UPF consumption and skinfold thickness (ß: 0.04; CI: 0.03/0.09), demonstrating an increase in this subcutaneous body fat marker with higher UPF consumption. Moreover, in participants aged 36 to 59 years, an inverse correlation between UPF intake and muscle mass markers, arm circumference (ß: -0.02; confidence interval: -0.03/-0.01), and corrected arm muscle area (ß: -0.07; confidence interval: -0.12/-0.02) were observed. Such results suggest there is decreased muscle mass with increasing UPF consumption. This is the first study that verified an association between UPF consumption and low-cost body composition indicators in different age groups.

Ultraprocessed Foods and Obesity Risk: A Critical Review of Reported Mechanisms

Epidemiologic evidence supports a positive association between ultraprocessed food (UPF) consumption and body mass index. This has led to recommendations to avoid UPFs despite very limited evidence establishing causality. Many mechanisms have been proposed, and this review critically aimed to evaluate selected possibilities for specificity, clarity, and consistency related to food choice (i.e., low cost, shelf-life, food packaging, hyperpalatability, and stimulation of hunger/suppression of fullness); food composition (i.e., macronutrients, food texture, added sugar, fat and salt, energy density, low-calorie sweeteners, and additives); and digestive processes (i.e., oral processing/eating rate, gastric emptying time, gastrointestinal transit time, and microbiome). For some purported mechanisms (e.g., fiber content, texture, gastric emptying, and intestinal transit time), data directly contrasting the effects of UPF and non-UPF intake on the indices of appetite, food intake, and adiposity are available and do not support a unique contribution of UPFs. In other instances, data are not available (e.g., microbiome and food additives) or are insufficient (e.g., packaging, food cost, shelf-life, macronutrient intake, and appetite stimulation) to judge the benefits versus the risks of UPF avoidance. There are yet other evoked mechanisms in which the preponderance of evidence indicates ingredients in UPFs actually moderate body weight (e.g., low-calorie sweetener use for weight management; beverage consumption as it dilutes energy density; and higher fat content because it reduces glycemic responses). Because avoidance of UPFs holds potential adverse effects (e.g., reduced diet quality, increased risk of food poisoning, and food wastage), it is imprudent to make recommendations regarding their role in diets before causality and plausible mechanisms have been verified.

Holistic Framework to Contextualize Dietary Quality Assessment: A Critical Review

Numerous dietary quality indices exist to help quantify overall dietary intake and behaviors associated with positive health outcomes. Most indices focus solely on biomedical factors and nutrient or food intake, and exclude the influence of important social and environmental factors associated with dietary intake. Using the Diet Quality Index- International as one sample index to illustrate our proposed holistic conceptual framework, this critical review seeks to elucidate potential adaptations to dietary quality assessment by considering-in parallel-biomedical, environmental, and social factors. Considering these factors would add context to dietary quality assessment, influencing post-assessment recommendations for use across various populations and circumstances. Additionally, individual and population-level evidence-based practices could be informed by contextual social and environmental factors that influence dietary quality to provide more relevant, reasonable, and beneficial nutritional recommendations.

The intake of ultra-processed foods, all-cause, cancer and cardiovascular mortality in the Korean Genome and Epidemiology Study-Health Examinees (KoGES-HEXA) cohort

The relationship between ultra-processed food (UPF) intake and mortality is unknown in Asian countries, yet the intake of UPF is on the rise in these countries. This study examined the association of UPF intake with all-cause, cancer and cardiovascular disease (CVD) mortality. Participants were 113,576 adults who responded to a 106-item food frequency questionnaire during recruitment of the 2004-2013 Health Examinees (HEXA) study, a prospective cohort study in Korea. UPF were defined using the NOVA classification and evaluated as quartiles of the proportion of UPF in the diet (% total food weight). Multivariable Cox regression and restricted cubic spline models were used to examine the association of UPF intake with all-cause and cause specific mortality. A total of 3456 deaths were recorded during a median follow-up of 10.6 (interquartile range, 9.5-11.9) years. There was no evidence of an association of UPF intake with all-cause, cancer or CVD mortality comparing the highest with the lowest quartiles of UPF intake (all-cause mortality, men: hazard ratio [HR] 1.08, 95% confidence interval [CI] 0.95-1.22; women: HR 0.95, 95% CI 0.81-1.11; cancer mortality, men: HR 1.02, 95% confidence interval [CI] 0.84-1.22; women: HR 1.02, 95% CI 0.83-1.26; CVD mortality, men: HR 0.88, 95% CI 0.64-1.22; women: HR 0.80, 95% CI 0.53-1.19). However, the risk of all-cause mortality increased in both men and women with high consumption of ultra-processed red meat and fish (men, HR 1.26, 95% CI 1.11-1.43); women, HR 1.22 95% CI 1.05-1.43); and in men with high consumption of ultra-processed milk (HR 1.13, 95% CI 1.01-1.26); and soymilk drink (HR 1.12, 95% CI 1.00-1.25). We found no evidence of an association between total UPF intake and all-cause, cancer or CVD mortality, but ultra-processed red meat and fish in both sexes, and milk and soymilk drinks in men were positively associated with all-cause mortality.

The influence of dough kneading time and flour particle size distribution on white bread structure, glycemic response and aspects of appetite

BACKGROUND & AIMS

White bread is widely consumed in many countries despite being a high-glycemic index (GI) food. It has been shown that the "food matrix effect" may help with diabetes and obesity management through lowering GI and appetite. This study aimed at investigating the effects of dough kneading time and flour particle size on white bread structure, glycemic response, and aspects of appetite.

METHODS

A two-phase randomized cross-over design was used in 10 healthy subjects over the course of 2 h. In phase 1, Texture Profile Analysis (TPA) attributes, Scanning Electron Microscope (SEM) image, glycemic response, and appetite aspects of white bread made with a 15-min dough kneading time (K15) were compared with white bread made with a 10-min dough kneading time (K10). In phase 2, TPA, SEM image, glycemic response, and satiety score of white bread made with coarse flour (CF) were compared to white bread made with fine flour (FF).

RESULT

With increasing hardness (force required to compress a food between the molars to a given deformation), total blood glucose IAUC in K15 (IAUC = 119 ± 12; GI = 66) was significantly (p < 0.05) lower than in K10 (IAUC = 154 ± 10; GI = 81). No marked difference was observed between K15 and K10 on aspects of appetite except for hunger. There was no significant (p > 0.05) difference in glycemic response between CF (IAUC = 126 ± 18; GI = 64) and FF (IAUC = 147 ± 12; GI = 81). Similarly, no discernible difference in satiety between CF and FF.

CONCLUSION

Changes in processing conditions can improve blood glucose response relalated to white bread consumption.

Macronutrient (im)balance drives energy intake in an obesogenic food environment: An ecological analysis

OBJECTIVE

The protein leverage hypothesis (PLH) postulates that strong regulation of protein intake drives energy overconsumption and obesity when human diets are diluted by fat and carbohydrates. The two predictions of the PLH are that humans (i) regulate intake to maintain protein within a narrow range and that (ii) energy intake is an inverse function of percentage energy from protein because absolute protein intake is maintained within narrow limits.

METHODS

Multidimensional nutritional geometry was used to test the predictions of the PLH using dietary data from the Australian National Nutrition and Physical Activity Survey.

RESULTS

Both predictions of the PLH were confirmed in a population setting: the mean protein intake was 18.4%, and energy intake decreased with increasing energy from protein (L = -0.18, p &lt; 0.0001). It was demonstrated that highly processed discretionary foods are a significant diluent of protein and associated with increased energy but not increased protein intake.

CONCLUSIONS

These results support an integrated ecological and mechanistic explanation for obesity, in which low-protein highly processed foods lead to higher energy intake because of the biological response to macronutrient imbalance driven by a dominant appetite for protein. This study supports a central role for protein in the obesity epidemic, with significant implications for global health.

A Comparison of the Australian Dietary Guidelines to the NOVA Classification System in Classifying Foods to Predict Energy Intakes and Body Mass Index

NOVA classification distinguishes foods by level of processing, with evidence suggesting that a high intake of ultra-processed foods (UPFs, NOVA category 4) leads to obesity. The Australian Dietary Guidelines, in contrast, discourage excess consumption of “discretionary foods” (DFs), defined according to their composition. Here, we (i) compare the classification of Australian foods under the two systems, (ii) evaluate their performance in predicting energy intakes and body mass index (BMI) in free-living Australians, and (iii) relate these outcomes to the protein leverage hypothesis of obesity. Secondary analysis of the Australian National Nutrition and Physical Activity Survey was conducted. Non-protein energy intake increased by 2.1 MJ (p < 0.001) between lowest and highest tertiles of DF intake, which was significantly higher than UPF (0.6 MJ, p < 0.001). This demonstrates that, for Australia, the DF classification better distinguishes foods associated with high energy intakes than does the NOVA system. BMI was positively associated with both DFs (−1. 0, p = 0.0001) and UPFs (−1.1, p = 0.0001) consumption, with no difference in strength of association. For both classifications, macronutrient and energy intakes conformed closely to the predictions of protein leverage. We account for the similarities and differences in performance of the two systems in an analysis of Australian foods.

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

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

Empirico-inductive and/or hypothetico-deductive methods in food science and nutrition research: which one to favor for a better global health?

Scientific research generally follows two main methods: empirico-inductive (EI), gathering scattered, real-world qualitative/quantitative data to elaborate holistic theories, and the hypothetico-deductive (HD) approach, testing the validity of hypothesized theory in specific conditions, generally according to reductionist methodologies or designs, with the risk of over simplifying the initial complexity empirically perceived in its holistic view. However, in current food and nutrition research, new hypotheses are often elaborated from reductionist data obtained with the HD approach, and aggregated to form (ultra)reductionist theories, with no application of EI observations, limiting the applicability of these hypotheses in real life. This trend and the application of the EI method are illustrated as regards with the global health issue through the examples of food classifications/scoring, clinical studies, the definition of a sustainable diet, the "matrix effect"-related hypothesis, the concept of healthy core metabolism, and obesity prevention within the perspective of social sciences. To be efficient for producing food and nutritional data appropriable by the society, it finally appears that not only both approaches are necessary, starting with the EI method then the HD one, but also a back and forth between the two, this being not always realized, potentially leading to confusion and misunderstanding in society.

Introducing Plant-Based Mediterranean Diet as a Lifestyle Medicine Approach in Latin America: Opportunities Within the Chilean Context

Latin America is experiencing a significant epidemiological and nutritional transition, with a trend toward higher incidence of food-related chronic diseases. In this context, Lifestyle Medicine (LM) is a growing field focused on assisting individuals in adopting healthy behaviors for the prevention and treatment of these chronic diseases, including, among other pillars, a great emphasis on healthy eating. There is also a growing interest worldwide in environmental sustainability of dietary patterns, with increasing concern about their effects on planetary health. In this context, whole-food, plant-based diets -such as the Mediterranean diet (MD)- have emerged as a solution for both healthier eating and lowering environmental impact. Yet in order to be effective at these goals and achieve a high adherence to any nutritional prescription, the sociocultural reality of the community or population where we aim to practice must also be taken into account. In this review, we specifically highlight the plant-based MD as a LM-contextualized dietary pattern that is adaptable, applicable, and sustainable within the Chilean context and has the potential to address the current trend of chronic diseases in our country.

Ultra-processed food consumption is associated with increased risk of all-cause and cardiovascular mortality in the Moli-sani Study

BACKGROUND

Consumption of ultra-processed food (UPF) is gaining growing attention in relation to disease/mortality risk, but less is known on the main nutritional factors or biological mechanisms potentially underlying such associations.

OBJECTIVES

We aimed to assess the association between UPF and mortality risk in a large sample of the Italian adult population and test which nutritional factors were on the pathway of this relation. Established risk factors for cardiovascular disease (CVD) were analyzed as potential biological mechanisms linking UPF to mortality.

METHODS

Longitudinal analysis was conducted on 22,475 men and women (mean ± SD age: 55 ± 12 y) recruited in the Moli-sani Study (2005-2010, Italy) and followed for 8.2 y. Food intake was assessed using a semiquantitative FFQ. UPF was defined using the NOVA classification according to degree of processing, and UPF intakes were categorized as quartiles of the ratio (%) of UPF (g/d) to total food consumed (g/d).

RESULTS

Individuals reporting the highest intake of UPF (Q4, >14.6% of total food), as opposed to the lowest (Q1, UPF < 6.6%), experienced increased risks of CVD mortality (HR: 1.58; 95% CI: 1.23, 2.03), death from ischemic heart disease (IHD)/cerebrovascular disease (HR: 1.52; 95% CI: 1.10, 2.09), and all-cause mortality (HR: 1.26; 95% CI: 1.09, 1.46). High sugar content explained 36.3% of the relation of UPF with IHD/cerebrovascular mortality, whereas other nutritional factors (e.g., saturated fats) were unlikely to be on the pathway. Biomarkers of renal function accounted for 20.1% of the association of UPF with all-cause mortality, and 12.0% for that of UPF with CVD mortality.

CONCLUSIONS

A high proportion of UPF in the diet was associated with increased risk of CVD and all-cause mortality, partly through its high dietary content of sugar. Some established biomarkers of CVD risk were likely to be on the pathway of such associations. These findings should serve as an incentive for limiting consumption of UPF, and encouraging natural or minimally processed foods, as several national nutritional policies recommend.

Approaches to Defining Healthy Diets: A Background Paper for the International Expert Consultation on Sustainable Healthy Diets

Background:

Healthy diets promote optimal growth and development and prevent malnutrition in all its forms, including undernutrition, obesity, and diet-related noncommunicable diseases (NCDs).

Objective:

This background paper for the International Expert Consultation on Sustainable Healthy Diets characterizes healthy diets and their implications for food system sustainability.

Methods:

Three complementary approaches to defining healthy diets are compared: World Health Organization (WHO) guidelines or recommendations developed between 1996 and 2019; 2017 Global Burden of Disease (GBD) risk factor study estimates of diet-related risk–outcome associations; and analyses associating indices of whole dietary patterns with health outcomes in population studies and clinical trials.

Results:

World Health Organization dietary recommendations are global reference points for preventing undernutrition and reducing NCD risks; they emphasize increasing intakes of fruits, vegetables (excepting starchy root vegetables), legumes, nuts, and whole grains; limiting energy intake from free sugars and total fats; consuming unsaturated rather than saturated or trans fats; and limiting salt intake. Global Burden of Disease findings align well with WHO recommendations but include some additional risk factors such as high consumption of processed meat; this approach quantifies contributions of diet-related risks to the NCD burden. Evidence on whole dietary patterns supports WHO and GBD findings and raises concerns about potential adverse health effects of foods with high levels of industrial processing.

Conclusions:

Implied shifts toward plant foods and away from animal foods (excepting fish and seafood), and for changes in food production systems have direct relevance to the sustainability agenda.

How to protect both health and food system sustainability? A holistic 'global health'-based approach via the 3V rule proposal

OBJECTIVE

To define a generic diet to protect human health and food system sustainability based on three dimensions: animal:plant ratio, degree of food processing and food diversity.

DESIGN/SETTING

The percentages of maximum animal and ultra-processed energy content were evaluated from scientific papers (Web of Science database) and reports from international scientific institutions. Then, a weekly French standard diet, including these percentages and food diversity (≥42 different foods), was designed to calculate adequacy to nutritional needs.

RESULTS

Based on traditional and scientifically based healthy diets, and on foresight scenarios for sustainable diets at horizon 2050, a median daily animal energy content intake of 15 % was found to be protective towards both human health and environment. Based on epidemiological studies associating ultra-processed energy consumption with increased overweight/obesity risk, a precautionary threshold of approximately 15 % ultra-processed energy content was observed. The French diet allows addressing all nutritional needs and other nutritional indicators such as maximum salt and simple sugar consumption, α-linolenic acid:linoleic acid ratio and essential amino acids. This diet was named the '3V rule' for Végétal (plant), Vrai (real) and Varié (varied, if possible organic, local and seasonal). This generic diet can be adapted according to regional traditions and environmental characteristics. Excluding only one dimension of it would threaten both health and food system sustainability.

CONCLUSIONS

Tending towards a 3V-based diet, while respecting local constraints, should allow preserving human health, environment (greenhouse gas emissions, pollution, deforestation, etc.), small farmers, animal welfare and biodiversity, culinary traditions and socioeconomics (including an alleviation of public health cost).

Evaluating the impact of soy compounds on breast cancer using the data mining approach

Accumulating evidence has shown that soy intake is associated with the promotion of health and prevention of cancers. However, the relationship between the intake of soy compounds and the risk of breast cancer is still debatable. In this study, we use mathematical models for assessing the impact of soy phytoestrogens and protein/peptide intervention on breast cancer development using the datasets acquired from a large number of published studies. We used data mining models, including the decision tree classification and association rule methods, to analyze 478 data collected from 201 research papers. The results indicated that the intervention of soy proteins and peptides, especially lunasin (LUN) and bowman-birk protease inhibitor (BBI), has a positive impact on different types of breast cancer, while the effects of soy phytoestrogens are inconsistent in breast cancer development. Among soy phytoestrogens, daidzein (DAI) exhibited the highest negative impact on breast cancer, followed by coumestrol (COU), soysapogenol (SAP), genistein (GEN), and equol (EQ). With regard to the type of cancer, phytoestrogens should be carefully considered in estrogen receptor (ER)+ or progesterone receptor (PR)+ breast cancer. In the case of ER-, PR- or triple negative type, both soy categories can be used as auxiliary interventions. In summary, this is the first study to use data mining to explore the relationship between the intake of soy phytoestrogens or proteins/peptides and breast cancer development. Our findings indicate that soy intervention might reduce breast cancer development. However, the specific soy compound and cancer type should be considered before allocating a precise nutrient intervention.

Utilization of text mining as a big data analysis tool for food science and nutrition

Big data analysis has found applications in many industries due to its ability to turn huge amounts of data into insights for informed business and operational decisions. Advanced data mining techniques have been applied in many sectors of supply chains in the food industry. However, the previous work has mainly focused on the analysis of instrument-generated data such as those from hyperspectral imaging, spectroscopy, and biometric receptors. The importance of digital text data in the food and nutrition has only recently gained attention due to advancements in big data analytics. The purpose of this review is to provide an overview of the data sources, computational methods, and applications of text data in the food industry. Text mining techniques such as word-level analysis (e.g., frequency analysis), word association analysis (e.g., network analysis), and advanced techniques (e.g., text classification, text clustering, topic modeling, information retrieval, and sentiment analysis) will be discussed. Applications of text data analysis will be illustrated with respect to food safety and food fraud surveillance, dietary pattern characterization, consumer-opinion mining, new-product development, food knowledge discovery, food supply-chain management, and online food services. The goal is to provide insights for intelligent decision-making to improve food production, food safety, and human nutrition.

The holistico-reductionist Siga classification according to the degree of food processing: an evaluation of ultra-processed foods in French supermarkets

The Siga classification of foods according to degree of processing showed that two-thirds of 24 932 packaged foods collected in French supermarkets are ultra-processed at various degrees.

An integrated look at the effect of structure on nutrient bioavailability in plant foods

The true bioavailability of a nutrient being intrinsically coupled to the specific food matrix in which it occurs remains poorly considered in nutrition science. During digestion, the food matrix and, in particular, the structure of food modulate the extent and kinetics to which nutrients and bioactive compounds make themselves available for absorption. In this perspective, we describe an integrated look at the effect of structure on nutrient bioavailability in plant foods. Based on this integrated look, cell wall integrity and the particle size of the plant material during its transit in the small intestine determine the bioavailability of plant nutrients; in turn, cell wall integrity and particle size are determined by the level of oral processing and, accordingly, what subsequently escapes digestion in the upper intestine and is utilized by colon microbiota. Ultimately, the effect on nutrient digestion is linked to food structure through each step of digestion. A consideration of the structure rather than just the composition of foods opens up possibilities for the design of healthier foods. © 2018 Society of Chemical Industry.

Perspective: Reductionist Nutrition Research Has Meaning Only within the Framework of Holistic and Ethical Thinking

Today, it seems that nutrition is in a state of great confusion, especially for the general public. For decades, some nutrients (e.g., cholesterol, saturated fats, sugars, gluten, salt) and food groups (e.g., dairy, cereals, meats) have been regularly denigrated. In this position paper, we hypothesize that such a state of confusion is mainly the result of the reductionist paradigm applied to nutrition research for more than a century, and by being pushed to its extreme, this perspective has led to accusations about some nutrients and foods. However, the real issue is about foods taken as a whole and therefore about their degree of processing, which affects both the food matrix and composition. Indeed, we eat whole foods, not nutrients. Therefore, the objectives of this article are to emphasize the need for more holistic approaches in nutrition to preserve our health, animal welfare, and planet. We propose to first redefine the food health potential on a holistic basis and then to show that reductionism and holism are interconnected approaches that should coexist. Then, we try to explain how extreme reductionism has been disconnected from reality and ethical considerations and has ultimately led to environmental degradation and loss of biodiversity, notably through very specific crops, and to an increased prevalence of chronic diseases. Furthermore, to address the confusion of the general public and to simplify nutritional messages, we propose 3 holistic golden rules based on scientific evidence to protect human health, animal welfare, and the environment (climate and biodiversity). Finally, we try to show how these 3 rules can be easily applied worldwide while respecting the environment, cultural traditions, and heritage.

Characterization of the Degree of Food Processing in Relation With Its Health Potential and Effects

Up today technological processes are intended to produce safe and palatable food products. Yet, it is also expected that processing produces healthy and sustainable foods. However, due to the dramatic increase of chronic diseases prevalence worldwide, i.e., obesity, type 2 diabetes, cardiovascular diseases, and some cancers, ultraprocessing has been pointed out as producing unhealthy foods, rich in energy and poor in protective micronutrients and fiber, i.e., "empty" calories. Indeed the 1980s saw massive arrivals of ultraprocessed foods in supermarkets, i.e., fractionated-recombined foods with added ingredients and/or additives. Epidemiological studies clearly emphasized that populations adhering the most to ultraprocessed foods, e.g., processed meat, refined grains, ultraprocessed plant-based foods, and/or sweetened beverages, exhibited the higher prevalence of chronic diseases. This prompted researchers to classify foods according to their degree of processing as with the international NOVA classification (i.e., un/minimally processed, processed, and ultraprocessed foods). More and more studies showed that such a classification makes sense for health. Overall one distinguishes three categories of processes: mechanical, thermal, and fermentative treatments, this latter being the more favorable to food health potential. This chapter has therefore several ambitions: (1) to review association between degree of food processing and chronic disease risk prevalence; (2) to explore the impact of technological processes on food health potential considering both matrix and compositional effects; (3) to discuss the need for classifying food according to their degree of processing in future epidemiological studies; and (4) to analyze consequences of adhering to a more holistic paradigm in both food processing and nutrition.