Summary
Understanding the drivers and dynamics of global ultra‐processed food (UPF) consumption is essential, given the evidence linking these foods with adverse health outcomes. In this synthesis ...review, we take two steps. First, we quantify per capita volumes and trends in UPF sales, and ingredients (sweeteners, fats, sodium and cosmetic additives) supplied by these foods, in countries classified by income and region. Second, we review the literature on food systems and political economy factors that likely explain the observed changes. We find evidence for a substantial expansion in the types and quantities of UPFs sold worldwide, representing a transition towards a more processed global diet but with wide variations between regions and countries. As countries grow richer, higher volumes and a wider variety of UPFs are sold. Sales are highest in Australasia, North America, Europe and Latin America but growing rapidly in Asia, the Middle East and Africa. These developments are closely linked with the industrialization of food systems, technological change and globalization, including growth in the market and political activities of transnational food corporations and inadequate policies to protect nutrition in these new contexts. The scale of dietary change underway, especially in highly populated middle‐income countries, raises serious concern for global health.
Full text
Available for:
BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
•Food can be classified along a continuum of addictiveness potential.•Food addiction symptoms potentiate reactivity to Ultra-Processed and Processed foods.•Food addiction researchers may desegregate ...Ultra-Processed and Processed foods.•The addictive potential of Processed foods might be considered by nutrition experts.
The NOVA classification system categorizes foods according to their level of processing to differentiate between industrially prepared, or Ultra-Processed (UP), and home-prepared, or Processed (P) and Minimally Processed (MP), foods. Whereas P and MP are recommended as part of a healthy diet, UP foods are considered unhealthy and a contributing factor to global, rising obesity rates. However, food addiction investigators include examples of both UP and P foods within their nomenclature of Highly Processed, addictive foods. Our study is the first to compare the potential addictiveness of a priori classified foods into UP vs P vs MP categories. We presented 169 women with a collection of 45 UP, P, and MP food pictures and recorded their subjective motivational reactivity to each picture. Analyses of covariance (ANCOVA) revealed that Yale Food Addiction Scale 2.0 (YFAS 2.0; Gearhardt et al., 2016) scores potentiated reactivity to both UP and P pictures, but not MP pictures. In addition, although both UP and P foods produced greater motivational reactivity than MP foods, UP foods elicited significantly greater reactivity than P foods. Our findings concur with previous suggestions that foods can be classified along a continuum of addictiveness potential, but our findings are the first to demonstrate that such classification might be accomplished by following the NOVA classification system. The findings also imply that nutrition experts may need to refine their NOVA classification system and, perhaps, even their healthy diet recommendations.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Processed foods are typically praised/revered for their convenience, palatability, and novelty; however, their healthfulness has increasingly come under scrutiny. Classification systems that ...categorise foods according to their “level of processing” have been used to predict diet quality and health outcomes and inform dietary guidelines and product development. However, the classification criteria used are ambiguous, inconsistent and often give less weight to existing scientific evidence on nutrition and food processing effects; critical analysis of these criteria creates conflict amongst researchers.
We examine the underlying basis of food classification systems and provide a critical analysis of their purpose, scientific basis, and distinguishing features by thematic analysis of the category definitions.
These classification systems were mostly created to study the relationship between industrial products and health. There is no consensus on what factors determine the level of food processing. We identified four defining themes underlying the classification systems: 1. Extent of change (from natural state); 2. Nature of change (properties, adding ingredients); 3. Place of processing (where/by whom); and 4. Purpose of processing (why, essential/cosmetic). The classification systems embody socio-cultural elements and subjective terms, including home cooking and naturalness. Hence, “processing” is a chaotic conception, not only concerned with technical processes. Most classification systems do not include quantitative measures but, instead, imply correlation between “processing” and nutrition. The concept of “whole food” and the role of the food matrix in relation to healthy diets needs further clarification; the risk assessment/management of food additives also needs debate.
•Classifications were created to link processed foods to nutrition and health outcomes.•There is no consensus on what determines the level of food processing.•Classification includes the extent, nature of change, place and purpose of processing.•Processed food concepts relate to naturalness, additives, convenience, home cooking.•Food classifications embody social and cultural elements and subjective terms.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Although the consumer enjoys many benefits provided by the current food processing technology, some health professionals and digital influencers suggest that there is little benefit and serious harm ...that could be due to poor nutrition, which was caused by the consumption of processed foods (PF). A new classification, known as NOVA, which classified foods into four groups, according to the level of processing was proposed. However, this classification does not accurately categorize food products by the level of the processing. In contrast, it considers the quantity of ingredients contained in the food. Therefore, the NOVA classification can lead to a negative perception by many consumers, because it neglects well-established science concepts from the food science domain. NOVA is based on the erroneous assumption that all commercially manufactured foods have low nutritional value, promote weight gain and chronic diseases to consumers because they contain sugar, salt and additives. It dismisses the proven benefits of diets chosen with the right mix of foods at all levels of processing. Disagreeing with some scientific studies, the NOVA classification suggests with inadequate data, that food prepared from basic ingredients at home has superior nutritional qualities to those produced by processors. Thus, some concepts have emerged in the public health field with special highlights to the term “ultra-processed” foods (UPF).
This commentary addresses the NOVA classification system from the perspective of food science, which is responsible for the safety and reliability of virtually all the foods we eat. NOVA has classified food into four groups based on the type of processing: 1) Unprocessed and minimally processed foods, 2) Processed culinary ingredients, 3) Processed foods, and 4) “Ultra-processed” foods.
The NOVA system is confusing and controversial. Knowledge of food engineering and/or science must be taken into consideration if food processing is the key for food classification. NOVA could be acceptable if it were based only on health concerns, but this was not the case.
•The NOVA classification system is analyzed in the field of Food Science.•The NOVA classification does not truly consider only food processing levels.•Clarifications are needed to avoid pejorative connotations to industrialized foods.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Since previous meta-analyses, which were limited only to depression and by a small number of studies available for inclusion at the time of publication, several additional studies have been published ...assessing the link between ultra-processed food consumption and depression as well as other mental disorders. We aimed to build on previously conducted reviews to synthesise and meta-analyse the contemporary evidence base and clarify the associations between the consumption of ultra-processed food and mental disorders. A total of 17 observational studies were included (n = 385,541); 15 cross-sectional and 2 prospective. Greater ultra-processed food consumption was cross-sectionally associated with increased odds of depressive and anxiety symptoms, both when these outcomes were assessed together (common mental disorder symptoms odds ratio: 1.53, 95%CI 1.43 to 1.63) as well as separately (depressive symptoms odds ratio: 1.44, 95%CI 1.14 to 1.82; and, anxiety symptoms odds ratio: 1.48, 95%CI 1.37 to 1.59). Furthermore, a meta-analysis of prospective studies demonstrated that greater ultra-processed food intake was associated with increased risk of subsequent depression (hazard ratio: 1.22, 95%CI 1.16 to 1.28). While we found evidence for associations between ultra-processed food consumption and adverse mental health, further rigorously designed prospective and experimental studies are needed to better understand causal pathways.
We performed a systematic review and dose-response meta-analysis of observational studies assessing the association between UPF consumption and adult mortality risk. A systematic search was conducted ...using ISI Web of Science, PubMed/MEDLINE, and Scopus electronic databases from inception to August 2021. Data were extracted from seven cohort studies (totaling 207,291 adults from four countries). Using a random-effects model, hazard ratios (HR) of pooled outcomes were estimated. Our results showed that UPF consumption was related to an enhanced risk of all-cause mortality (HR = 1.21; 95% CI: 1.13, 1.30; I
= 21.9%;
< 0.001), cardiovascular diseases (CVDs)-cause mortality (HR = 1.50; 95% CI: 1.37, 1.63; I
= 0.0%;
< 0.001), and heart-cause mortality (HR = 1.66; 95% CI: 1.50, 1.85; I
= 0.0%;
= 0.022), but not cancer-cause mortality. Furthermore, our findings revealed that each 10% increase in UPF consumption in daily calorie intake was associated with a 15% higher risk of all-cause mortality (OR = 1.15; 95% CI: 1.09, 1.21; I
= 0.0%;
< 0.001). The dose-response analysis revealed a positive linear association between UPF consumption and all-cause mortality (
= 0.879,
=
< 0.001), CVDs-cause mortality (
= 0.868,
=
< 0.001), and heart-cause mortality (
= 0.774,
=
< 0.001). It seems that higher consumption of UPF is significantly associated with an enhanced risk of adult mortality. Despite this, further experimental studies are necessary to draw a more definite conclusion.
Higher intake of ultra-processed foods (UPFs) has been associated with increased risk of CVD and mortality in observational studies from Western countries but data from non-Western countries are ...limited.
We aimed to assess the association between consumption of UPFs and risk of mortality and major CVD in a cohort from multiple world regions.
This analysis includes 138,076 participants without a history of CVD between the ages of 35 and 70 y living on 5 continents, with a median follow-up of 10.2 y. We used country-specific validated food-frequency questionnaires to determine individuals’ food intake. We classified foods and beverages based on the NOVA classification into UPFs. The primary outcome was total mortality (CV and non-CV mortality) and secondary outcomes were incident major cardiovascular events. We calculated hazard ratios using multivariable Cox frailty models and evaluated the association of UPFs with total mortality, CV mortality, non-CV mortality, and major CVD events.
In this study, 9227 deaths and 7934 major cardiovascular events were recorded during the follow-up period. We found a diet high in UPFs (≥2 servings/d compared with 0 intake) was associated with higher risk of mortality (HR: 1.28; 95% CI: 1.15, 1.42; P-trend < 0.001), CV mortality (HR: 1.17; 95% CI: 0.98, 1.41; P-trend = 0.04), and non-CV mortality (HR: 1.32; 95% CI 1.17, 1.50; P-trend < 0.001). We did not find a significant association between UPF intake and risk of major CVD.
A diet with a high intake of UPFs was associated with a higher risk of mortality in a diverse multinational study. Globally, limiting the consumption of UPFs should be encouraged.
Full text
Available for:
CMK, GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
There is limited evidence regarding the association between consumption of highly processed foods (HPFs) and overall diet quality in children and adolescents from Asian countries.
This study aimed to ...examine the association between HPF consumption and overall diet quality in Japanese children and adolescents.
A cross-sectional analysis was conducted based on 8-day dietary record data collected from volunteers in 32 of 47 prefectures throughout Japan in 2016 to 2020. Foods were categorized into 1 of 4 processing levels using the framework developed by the University of North Carolina at Chapel Hill. Food classification was performed under a low-estimate scenario (classifying mixed dishes consumed outside the home after disaggregation into ingredients) and high-estimate scenario (classifying them into HPFs without food disaggregation).
A total of 1,318 Japanese children and adolescents aged 3 to 17 years participated in the study.
Diet quality was assessed using the Healthy Eating Index-2020 and Nutrient-Rich Food Index 9.3.
Multiple regression models adjusted for sociodemographic and anthropometric characteristics and the survey cycle were used to examine the association between tertiles of the energy contribution of HPFs and diet quality.
The mean energy contribution of HPFs was 27.3% and 44.3% in the low- and high-estimate scenarios, respectively. The top contributors to total energy intake from HPFs were confectionaries in the low-estimate scenario and cereals and starchy foods in the high-estimate scenario. Irrespective of the scenarios, participants in higher tertiles of energy contribution of HPFs had lower total scores for Healthy Eating Index-2020 and Nutrient-Rich Food Index 9.3 (P for trend < .0001).
HPFs accounted for more than one-quarter of the energy intake of Japanese children and adolescents surveyed, and higher consumption of HPFs was associated with lower diet quality. Therefore, reducing HPF consumption may increase overall diet quality among Japanese children and adolescents. Further research is needed to explore the causal nature of this association.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ
Ultra-processed foods provide 58 % of energy intake and 89 % of added sugars in the American diet. Nevertheless, the association between ultra-processed foods and excess weight has not been ...investigated in a US sample. The present investigation therefore aims to examine the association between ultra-processed foods and excess weight in a nationally representative sample of US adults. We performed a cross-sectional analysis of anthropometric and dietary data from 15 977 adults (20–64 years) participating in the National Health and Nutrition Examination Survey 2005–2014. Dietary data were collected by 24-h recall. Height, weight and waist circumference (WC) were measured. Foods were classified as ultra-processed/non-ultra-processed according to the NOVA classification. Multivariable linear and logistic regression was used to evaluate the association between ultra-processed food consumption (% energy) and BMI, WC and odds of BMI≥25 kg/m2, BMI≥30 kg/m2 and abdominal obesity (men: WC≥102 cm, women: WC≥88 cm). Prevalence of BMI≥25 kg/m2, BMI≥30 kg/m2 and abdominal obesity was 69·2, 36·1 and 53·0 %, respectively. Consuming ≥74·2 v. ≤36·5 % of total energy from ultra-processed foods was associated with 1·61 units higher BMI (95 % CI 1·11, 2·10), 4·07 cm greater WC (95 % CI 2·94, 5·19) and 48, 53 and 62 % higher odds of BMI≥25 kg/m2, BMI≥30 kg/m2 and abdominal obesity, respectively (OR 1·48; 95 % CI 1·25, 1·76; OR 1·53; 95 % CI 1·29, 1·81; OR 1·62; 95 % CI 1·39, 1·89, respectively; P
for trend<0·001 for all). A significant interaction between being female and ultra-processed food consumption was found for BMI (F
4,79=4·89, P=0·002), WC (F
4,79=3·71, P=0·008) and BMI≥25 kg/m2 (F
4,79=5·35, P<0·001). As the first study in a US population, our findings support that higher consumption of ultra-processed food is associated with excess weight, and that the association is more pronounced among women.
PDF
