Greenhouse gas emissions, water footprint, and ecological footprint of food purchases according to their degree of processing in Brazilian metropolitan areas: a time-series study from 1987 to 2018

Copyright © 2021 The Author(s). Background The consumption of ultra-processed foods has increased worldwide and has been related to the occurrence of obesity and other non-communicable diseases. However, little is known about the environmental effects of ultra-processed foods. We aimed to assess the temporal trends in greenhouse gas emissions (GHGE), water footprint, and ecological footprint of food purchases in Brazilian metropolitan areas, and how these are affected by the amount of food processing. Methods In this time-series study, we used data from five Brazilian Household Budget Surveys (1987–88, 1995–96, 2002–03, 2008–09, 2017–18) to calculate GHGE, water footprint, and ecological footprint per 1000 kcal of food and beverages purchased. Food items were classified into NOVA food groups: unprocessed or minimally processed foods (G1); processed culinary ingredients (G2); processed foods (G3); and ultra-processed foods (G4). We calculated the proportion each NOVA food group contributes to daily kcal per person. Linear regression was performed to evaluate trends of the environmental impacts across the years. Findings Between 1987–88 and 2017–18, diet-related GHGE increased by 21% (from 1538·6 g CO2 equivalent [CO2e] per 1000 kcal [95% CI 1473·3–1604·0] to 1866·0 g CO2e per 1000 kcal [1788·0–1944·0]; ptrend<0·0001), diet-related water footprint increased by 22% (from 1447·2 L/1000 kcal [95% CI 1400·7–1493·8] to 1769·1 L/1000 kcal [1714·5–1823·7]; ptrend<0·0001), and diet-related ecological footprint increased by 17% (from 9·69 m2/1000 kcal [95% CI 9·33–10·05] to 11·36 m2/1000 kcal [10·91–11·81]; ptrend<0·0001). We found that the change in the environmental indicators over time varied between NOVA food groups. We did not find evidence of a change in the environmental indicators for G1 foods over time. GHGE from G2 foods decreased by 18% (ptrend<0·0001), whereas GHGE from G4 foods increased by 245% (ptrend<0·0001). The water footprint from G2 foods decreased by 17% (ptrend<0·0001) whereas the water footprint from G4 foods increased by 233% (ptrend<0·0001). The ecological footprint from G2 foods decreased by 13% (ptrend<0·0001), whereas the ecological footprint from G3 foods increased by 49% (ptrend<0·0001) and from G4 foods increased by 183% (ptrend<0·0001). We found no significant change in contribution by any other NOVA food groups to any of the three environmental indicators over the study period. Interpretation The environmental effects of the Brazilian diet have increased over the past three decades along with increased effects from ultra-processed foods. This means that dietary patterns in Brazil are becoming potentially more harmful to human and planetary health. Therefore, a shift in the current trend would be needed to enhance sustainable healthy food systems.Science and Technologies Facilities Council—Global Challenges Research Fund

Food insecurity, food waste, food behaviours and cooking confidence of UK citizens at the start of the COVID-19 lockdown

Purpose The current pilot study explored food insecurity, food waste, food related behaviours and cooking confidence of UK consumers following the COVID-19 lockdown. Design/methodology/approach Data were collected from 473 UK-based consumers (63% female) in March 2020. A cross-sectional online survey measured variables including food insecurity prevalence, self-reported food waste, food management behaviours, confidence and frequency of use of a range of cooking methods, type of food eaten (ultra-processed, semi-finished, unprocessed) and packaging type foods are purchased in. Findings 39% of participants have experienced some food insecurity in the last 12 months. Being younger, having a greater BMI and living in a smaller household were associated with food insecurity. Green leaves, carrots, potatoes and sliced bread are the most wasted of purchased foods. Polenta, green leaves and white rice are the most wasted cooked foods. Food secure participants reported wasting a smaller percentage of purchased and cooked foods compared to food insecure participants. Overall, participants were most confident about boiling, microwaving and stir-frying and least confident with using a pressure cooker or sous vide. Food secure participants were more confident with boiling, stir-frying, grilling and roasting than insecure food participants. Practical implications This has implications for post lockdown policy, including food policies and guidance for public-facing communications. Originality/value We identified novel differences in self-report food waste behaviours and cooking confidence between the food secure and insecure consumers and observed demographics associated with food insecurity

Characterization of the degree of food processing in the European Prospective Investigation into Cancer and Nutrition: Application of the Nova classification and validation using selected biomarkers of food processing

Background: Epidemiological studies have demonstrated an association between the degree of food processing in our diet and the risk of various chronic diseases. Much of this evidence is based on the international Nova classification system, which classifies 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 (UPF). The ability of the Nova classification to accurately characterise the degree of food processing across consumption patterns in various European populations has not been investigated so far. Therefore, we applied the Nova coding to data from the European Prospective Investigation into Cancer and Nutrition (EPIC) in order to characterize the degree of food processing in our diet across European populations with diverse cultural and socio-economic backgrounds and to validate this Nova classification through comparison with objective biomarker measurements. Methods: After grouping foods in the EPIC dataset according to the Nova classification, a total of 476,768 participants in the EPIC cohort (71.5% women; mean age 51 [standard deviation (SD) 9.93]; median age 52 [percentile (p)25–p75: 58–66] years) were included in the cross-sectional analysis that characterised consumption patterns based on the Nova classification. The consumption of food products classified as different Nova categories were compared to relevant circulating biomarkers denoting food processing, measured in various subsamples (N between 417 and 9,460) within the EPIC cohort via (partial) correlation analyses (unadjusted and adjusted by sex, age, BMI and country). These biomarkers included an industrial transfatty acid (ITFA) isomer (elaidic acid; exogenous fatty acid generated during oil hydrogenation and heating) and urinary 4-methyl syringol sulfate (an indicator for the consumption of smoked food and a component of liquid smoke used in UPF). Results: Contributions of UPF intake to the overall diet in % grams/day varied across countries from 7% (France) to 23% (Norway) and their contributions to overall % energy intake from 16% (Spain and Italy) to >45% (in the UK and Norway). Differences were also found between sociodemographic groups; participants in the highest fourth of UPF consumption tended to be younger, taller, less educated, current smokers, more physically active, have a higher reported intake of energy and lower reported intake of alcohol. The UPF pattern as defined based on the Nova classification (group 4;% kcal/day) was positively associated with blood levels of industrial elaidic acid (r = 0.54) and 4-methyl syringol sulfate (r = 0.43). Associations for the other 3 Nova groups with these food processing biomarkers were either inverse or non-significant (e.g., for unprocessed and minimally processed foods these correlations were –0.07 and –0.37 for elaidic acid and 4-methyl syringol sulfate, respectively). Conclusion: These results, based on a large pan-European cohort, demonstrate sociodemographic and geographical differences in the consumption of UPF. Furthermore, these results suggest that the Nova classification can accurately capture consumption of UPF, reflected by stronger correlations with circulating levels of industrial elaidic acid and a syringol metabolite compared to diets high in minimally processed foods

Using Natural Language Processing and Artificial Intelligence to Explore the Nutrition and Sustainability of Recipes and Food

Copyright © 2021 van Erp, Reynolds, Maynard, Starke, Ibáñez Martín, Andres, Leite, Alvarez de Toledo, Schmidt Rivera, Trattner, Brewer, Adriano Martins, Kluczkovski, Frankowska, Bridle, Levy, Rauber, Tereza da Silva and Bosma. In this paper, we discuss the use of natural language processing and artificial intelligence to analyze nutritional and sustainability aspects of recipes and food. We present the state-of-the-art and some use cases, followed by a discussion of challenges. Our perspective on addressing these is that while they typically have a technical nature, they nevertheless require an interdisciplinary approach combining natural language processing and artificial intelligence with expert domain knowledge to create practical tools and comprehensive analysis for the food domain.Research Councils UK, the University of Manchester, the University of Sheffield, the STFC Food Network+ and the HEFCE Catalyst-funded N8 AgriFood Resilience Programme with matched funding from the N8 group of Universities; AHRC funded AHRC US-UK Food Digital Scholarship Network (Grant Reference: AH/S012591/1), STFC GCRF funded project “Trends in greenhouse gas emissions from Brazilian foods using GGDOT” (ST/S003320/1), the STFC funded project “Piloting Zooniverse for food, health and sustainability citizen science” (ST/T001410/1), and the STFC Food Network+ Awarded Scoping Project “Piloting Zooniverse to help us understand citizen food perceptions”; ESRC via the University of Sheffield Social Sciences Partnerships, Impact and Knowledge Exchange fund for “Recipe environmental impact calculator”; and through Research England via the University of Sheffield QR Strategic Priorities Fund projects “Cooking as part of a Sustainable Food System – creating an wider evidence base for policy makers”, and “Food based citizen science in the UK as a policy tool”; N8 AgriFood-funded project “Greenhouse Gas and Dietary choices Open-source Toolkit (GGDOT) hacknights.’; Brunel University internal Research England GCRF QR Fund; The University of Manchester GCRF QR Visiting Researcher Fellowship; National Institute of Informatics, Japan

Ultra-processed food consumption and type 2 diabetes incidence: A prospective cohort study.

BACKGROUND: Ultra-processed foods account for more than 50% of daily calories consumed in several high-income countries, with sales of ultra-processed foods soaring globally, especially in middle-income countries. The objective of this study is to investigate the association between ultra-processed food (UPF) consumption and risk of type 2 diabetes (T2D) in a UK-based prospective cohort study. METHODS: Participants of the UK Biobank (2007-2019) aged 40-69 years without diabetes at recruitment who provided 24-h dietary recall and follow-up data were included. UPFs were defined using the NOVA food classification. Multivariable Cox proportional hazards regression models were used to evaluate the association between UPF consumption and the risk of T2D adjusting for socio-demographic, anthropometric and lifestyle characteristics. RESULTS: A total of 21,730 participants with a mean age of 55.8 years and mean UPF intake of 22.1% at baseline were included. During a mean follow-up of 5.4 years (116,956 person-years), 305 incident T2D cases were identified. In the fully adjusted model, compared with the group in the lowest quartile of UPF intake, the hazard ratio for T2D was 1.44, 1.04-2.02 in the group with the highest quartile of UPF consumption. A gradient of elevated risk of T2D associated with increasing quartiles of UPF intake was consistently observed (p value for trend < 0.028). A significantly increased risk of T2D was observed per 10 percentage points increment in UPF consumption ([adjusted HR]: 1.12, 95% confidence interval [CI]: 1.04-1.20). CONCLUSIONS: Our findings demonstrate that a diet high in UPFs is associated with a clinically important increased risk of T2D. Identifying and implementing effective public health actions to reduce UPF consumption in the UK and globally are urgently required

Ultra-processed food consumption and chronic non-communicable diseases-related dietary nutrient profile in the UK (2008⁻2014)

We described the contribution of ultra-processed foods in the U.K. diet and its association with the overall dietary content of nutrients known to affect the risk of chronic non-communicable diseases (NCDs). Cross-sectional data from the U.K. National Diet and Nutrition Survey (2008⁻2014) were analysed. Food items collected using a four-day food diary were classified according to the NOVA system. The average energy intake was 1764 kcal/day, with 30.1% of calories coming from unprocessed or minimally processed foods, 4.2% from culinary ingredients, 8.8% from processed foods, and 56.8% from ultra-processed foods. As the ultra-processed food consumption increased, the dietary content of carbohydrates, free sugars, total fats, saturated fats, and sodium increased significantly while the content of protein, fibre, and potassium decreased. Increased ultra-processed food consumption had a remarkable effect on average content of free sugars, which increased from 9.9% to 15.4% of total energy from the first to the last quintile. The prevalence of people exceeding the upper limits recommended for free sugars and sodium increased by 85% and 55%, respectively, from the lowest to the highest ultra-processed food quintile. Decreasing the dietary share of ultra-processed foods may substantially improve the nutritional quality of diets and contribute to the prevention of diet-related NCDs

The ultra-processed food content of school meals and packed lunches in the United Kingdom

British children have the highest levels of ultra-processed food (UPF) consumption in Europe. Schools are posited as a positive setting for impacting dietary intake but the level of UPFs consumed at schools is currently unknown. This study determined the UPF content of school food in the UK. We conducted a pooled cross-sectional analysis of primary (4-11 years, n=1,895) and secondary schoolchildren (11-18 years, n=1,408) from the UK’s National Diet and Nutrition Survey (2008-2017). Multivariable quantile regression models determined the association between meal-type (school meal or packed lunch) and lunchtime UPF intake (NOVA food classification system). We showed that on average UPF intake was high in both primary (72.6% total lunch Kcal) and secondary schoolchildren (77.8 % total lunch Kcal). Higher UPF intakes were observed in packed lunch consumers, secondary schoolchildren, and those in lower income households. This study highlights the need for a renewed focus on school food. Better guidance and policies which consider levels of industrial processing in food served in schools is needed to ensure the dual benefit of encouraging school meal uptake and equitably improving children’s diet