30 research outputs found
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Cooking as part of a global sustainable food system - a 6 country pilot survey
The cooking of food is a nexus point for multiple issues. Cooking is intertwined with dietary choices, affects the nutrient content and environmental impacts of food, and is linked to time use and gender roles in the home. Due to its intersectionality, changing cooking practices can potentially impact upon multiple Sustainable Development Goals. However, cookery is seldom considered in the wider perspective of a sustainable food system - with only ethnographic studies examining how cooking is performed being the norm. Overall there is a limited evidence base at the population level of how different nations/populations currently cook, and how changing this would result in changes to the environment, consumer health, and economy. The current research aims to create a wider evidence base to demonstrate and quantify why cooking and food practices are important, and how they differ by geography. In this research we piloted a ~40 minute survey using the Qualtrics online survey panel in 6 countries (Nigeria, Ghana, India, Kenya, Brazil, and the UK). Participants were asked a series of questions about their: dietary preferences (e.g. vegetarian, omnivore, etc.), cooking habits (e.g frequency of cooking at home), food preparation (e.g. time taken), cooking methods used (e.g. boil, fry, roast), and perceptions of food waste, food safety, calorie and carbon footprints, as well as food security and demographic questions. 10-15 culturally appropriate/popular foods were accessed through a food frequency questionnaire, containing images of food portion size estimates, from food manuals developed by a research group from the Federal University of Paraná (http://gupea.ufpr.br/?page_id=19; Additional images of bread were sourced from the Food4Me project (DOI: 10.2196/jmir.3105). Figure 1 presents this list of foods. Recruitment used Qualtrics global recruitment services as well the Prolific panel (for the UK). Participants were potentially given financial compensation for taking part by Qualtrics, but this was outside the control of the research team. The surveys were deployed from the 25th of March, 2020. There were slight recruitment issues for some countries due to parts of the survey being carried out in Ramadan and during the COVID-19 lockdown, and so the recruitment window had to be extended until the 1st of June 2020. Participant rates, gender splits (Figure 2) and dietary patterns (figure 3) varied by country. Figure 4 to 10 compare Chicken food habits and perceptions across the 6 countries
Microencapsulação do Ăłleo de castanha-do-brasil com proteĂnas vegetais como material de parede.
SIAN. 17 e 18 de junho de 2019. PĂ´ster. R020
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Are we ready for sustainable cookery? Comparing current (and future) cooking and time use practices in UK, US and Australia
Cooking practices play a pivotal role in a healthy diet and lifestyle. Cooking is intertwined with dietary choices. To achieve a sustainable food system, we need to change how we cook and prepare food, along with the time we use to prepare and cook food. Cooking practices involve a variety of parameters such as cooking times, method of cooking (e.g. boiling, baking, steaming) and type of appliances (e.g. electric hobs, gas ovens, microwaves), which all influence the nutrition content and energy density of food and result in varying amounts of emitted greenhouse gases. Behavioural cooking choices are driven by factors such as convenience, taste, health and lifestyle and shape certain eating habits, but are also influenced by tradition and transfer of knowledge. This article presents the findings of three pilot surveys deployed in the United Kingdom, United States and Australia in 2019 (n = 385+ for each survey). These surveys asked about cooking and preparation time, methods and equipment for 30 common foods. Though based around similar food cultures, we find differences in cooking practices among the different countries’ populations. We then examine how food choices and cooking practices need to change differently in each country to be in line with current guidance on healthy, sustainable eating such as the guidelines provided by the EAT-Lancet report
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How home cooking methods and appliances affect the GHG emissions of food
Food is widely acknowledged as a significant contributor to climate change. Yet, estimates of food-related greenhouse gas emissions frequently consider supply chain stages only up to farm gate or regional distribution centres. Here, we estimate greenhouse gas emissions associated with different cooking methods and appliances in the UK. Data on current cooking practices were collected through a survey with more than 700 respondents. Results reveal that home cooking accounts for as much as 61% of total emissions associated with specific foods, and that this can be substantially reduced through alternative, readily available cooking practices
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Trends in the environmental impacts of unprocessed or minimally processed, processed, and ultra-processed animal products in Brazil over 30 years
Background: We aim to assess the trends in the consumption of unprocessed or minimally processed, processed, and ultra-processed animal products, and the environmental impacts associated with them.
Methods: We have used data from five Brazilian Household Budget Surveys (1987, 1996, 2003, 2009, 2017). Animal products (beef, pork, poultry, eggs, fish, milk, and cheese) were classified into NOVA food groups: unprocessed or minimally processed (G1), processed (G3), and ultra-processed (G4). We estimated the share (%) of each food group to daily kcal per capita, as well as carbon footprint (CF), water footprint (WF) and ecological footprint (EF) per 1000 kcal-day. Trends over the years were tested using linear regression considering the population size as a weighting factor.
Results: From 1987 to 2017, the dietary share of G1 animal products decreased 2% (15.5-15.2%, p-trend < 0.001), while the share of G3 and G4 products increased by 88% (1.6-3.0%, p-trend < 0.001) and 340% (4.3-1.1%, p-trend < 0.001), respectively. CF in g CO2 eq per 1000 kcal remained the same for G1 products (921.4-946.2, p-trend = 0.278) and increased by 124% (30.9-69.3, p-trend < 0.001) and 319% (50.7-212.5, p-trend < 0.001) for G3 and G4 products, respectively. WF in litres per 1000 kcal decreased by 11% for G1 products (846.7-752.5, p-trend < 0.001), and increased by 130% for G3 (24.3-55.9, p-trend < 0.001) and 323% for G4 products (42.5-179.8, p-trend < 0.001). Similarly, EF in m2 per 1000 kcal decreased by 5% for G1 products (6.06-5.73, p-trend < 0.001), and increased by 67% for G3 (0.24-0.40, p-trend < 0.001) and by 305% for G4 products (0.21-0.85, p-trend < 0.001).
Conclusion: The consumption of processed and ultra-processed animal products has been increasing along with their environmental impact, suggesting that the reduction of their consumption would be beneficial for both human and planet health
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The impact of ultra-processed food on carbon, water and ecological footprints of food in Brazil
Background
Ultra-processed foods (UPF) have been associated with major diet-related public health issues that share underlying drivers with climate change. Both challenges require major changes to the food system and so the potential benefits to health and the environment present a double motivation for transformation. Our aim is to assess the impacts of UPF on total greenhouse gas emissions (GHGE), water and ecological footprints in Brazil food purchases.
Methods
We have used data from 4 Brazilian Household Budget Surveys (1987, 1996, 2003, 2009). Each food item was classified into NOVA food groups (unprocessed/minimally processed, culinary ingredients, processed and ultra-processed). The information was linked to nutrition and footprint data. Purchases were converted into grams per capita per day to estimate total energy (kcal), percentage of energy from UPF, as well as total GHGE, water and ecological footprints. We performed linear regression to calculate year-adjusted means of footprints per 1000 Kcal by year-specific quintiles of UPF participation in the total energy. The data were analysed in R v.3.6.1 and STATA SE 14.1.
Results
The mean UPF participation in total energy varied from 13% (SD 2.4) in the 1st UPF quintile to 29% (SD 5.1) in the 5th quintile. The footprints increased linearly across quintiles: the mean g CO2eq varied from 1312 in the 1st to 1721 in the 5th UPF quintile (p-trend<0.001); the mean litres of water varied from 1420 in the 1st to 1830 in the 5th quintile (p-trend<0.001); the mean m2 varied from 9.4 in the 1st to 12.3 in the 5th quintile (p < 0.001).
Conclusions
The environmental impacts were higher for Brazilian diets with a larger fraction of energy from UPF. Specifically, low UPF diets seem to have lower GHGE, water and ecological footprints. Our findings offer new motivators for dietary change to simultaneously healthier and more sustainable eating patterns and will be of relevance to consumers and policymakers.
Key messages
Diets high in UPF cause more climate impact than diets with lower levels of UPF.
Healthy and sustainable dietary patterns should be low in ultra-processed foods
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Comparison of Greenhouse Gas databases using FoodEx2 codes
Introduction
FoodEx2 consists of a vocabulary of foods with assigned codes, allowing the classification and description of foods reported in different types of data (food consumption, composition, or production method) [1]. At least 56 food consumption databases have been coded with FoodEx2 [2]. The linkage of greenhouse gas emissions (GHGE) databases to FoodEx2 codes would allow rapid matching of GHGE data to any food database previously harmonised with FoodEx2. We have linked 4558 FoodEx2 codes to GHGE data [3]. In this work, we aim to assess the reliability of the linkage, by comparing it to similar databases.
Methods or approach
The main database (“City”) was developed by matching 43 food categories from Poore and Nemecek (2018) [4] to the 4558 FoodEx2 codes, adjusting for edibility. The items were matched by hand, using the closest raw product; if it was a product with multiple ingredients, we took the largest ingredient by weight. The reliability of the matching was assessed by comparing “City” to three GHGE databases: 1) SHARP (Mertens et al 2019) [5] has linked GHGE to FoodEx1 (an initial version of FoodEx); 2) Rose et al (2019) [6] and Heller et al (2018) [7] have GHGE data linked to National Health and Nutrition Examination Survey (NHANES), which is coded with FoodEx2; 3) Garzillo et al (2019) [8] have GHGE data linked to the Brazilian Food Consumption Survey. We have compared “City” with the three databases by calculating Spearman correlation coefficients. The food items with GHGE in both “City” and SHARP were ranked and split into quintiles. We checked quintile rankings of agreement between “City” and SHARP by calculating weighted kappa statistics. For food items not ranked in the same quintile, we checked whether values from SHARP were within the p5 and p95 from “City”.
Findings and interpretations
The “City” dataset was strongly correlated to all three comparator databases. However, the number of directly comparable food items between all datasets were low. The number of food items compared, the Spearman correlation coefficients, and p-values are as follows: 1) “City” versus SHARP: n=945, r = 0.699, p < 0.001; 2) “City” versus Rose/Heller: n=608, r = 0.572, p < 0.001; 2) “City” versus Garzillo: n=329, r = 0.610, p < 0.001. Of the 945 food items with GHGE in “City” and SHARP, 50% (n = 476) were ranked in the same quintile. The kappa statistics was 0.536 (p < 0.001). Of the 469 food items not ranked into the same quintiles, 44% (n=206) were within p5 and p95, while 31% (n=144) were lower than the p5, and 25% (n= 119) were higher than p95. The food items with the biggest differences between “City” and SHARP are into the following food categories: wheat and rye; fish and seafood; pig meat; fruits; nuts and pulses. These food items will be further investigated in the next update of the data, aiming to increase reliability to estimate GHGE from food consumption.
Conclusions
The FoodEx2 database linked to GHGE by City presented a strong correlation with other GHGE databases and therefore could be considered as a tool to estimate the environmental impacts from food. However, further work is still needed to refine the data, in particular checking values categorised in opposite quintiles and that do not fall within p5 and p95. This database allows for a quick link between GHGE and multiple dietary databases harmonised with FoodEx2.
References
EFSA (European Food Safety Authority), Nikolic, M and Ioannidou, S, 2021. FoodEx2 maintenance 2020. EFSA supporting publication 2021: 18( 3):EN-6507. 19 pp. doi: 10.2903/sp.efsa.2020.EN-6507
Karageorgou, Dimitra and Lara-Castor, Laura and de Quadros, Victoria Padula and de Sousa, Rita Ferreira and Holmes, Bridget Anna and Ioannidou, Sofia and Mozaffarian, Dariush and Micha, Renata, Harmonizing Dietary Datasets for Global Surveillance: Methods and Findings From the Global Dietary Database. Under review.
Livestock, Environment And People (LEAP) Conference, Oxford, November 2019. C.J. Reynolds , X. Schmidt Rivera, , A. Frankowska, A Kluczkovski, J. T. da Silva S. L. Bridle,R. Levy, F. Rauber, V. P. Quadros, A. Balcerzak, R. F. Sousa, M. Ferrari, C. Leclercq, B. Koroušić Seljak, Tome Eftimov "A pilot method linking greenhouse gas emission databases to the FoodEx2 classification"
Poore, J., & Nemecek, T. (2018). Reducing food’s environmental impacts through producers and consumers. Science, 360(6392), 987–992.
Mertens, E., Kaptijn, G., Kuijsten, A., van Zanten, H., Geleijnse, J.M. and van't Veer, P., 2019. SHARP-Indicators Database towards a public database for environmental sustainability. Data in brief, 27, p.104617.https://doi.org/10.1016/j.dib.2019.104617
Rose D, Heller MC, Willits-Smith AM, Meyer RJ. "Carbon footprint of self-selected US diets: nutritional, demographic, and behavioral correlates," American Journal of Clinical Nutrition 2019;109:526-534. DOI:10.1093/ajcn/nqy327.
Heller MC, Willits-Smith A, Meyer R, Keoleian G, Rose D. "Greenhouse gas emissions and energy use associated with production of US self-selected diets," Environmental Research Letters 2018;13 044004. DOI: 10.1088/1748-9326/aab0ac.
Garzillo JMF, Machado PP, Costa Louzada ML, Levy RB, Monteiro CA. Footprints of foods and culinary preparations consumed in Brazil. https://doi.org/10.11606/9788588848405 (accessed Dec 7, 2020
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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
Ultrasound-Assisted Preparation of Brazil Nut Oil-in-Water Emulsions Stabilized by Arabic Gum
The objective of this work is to evaluate the stability of Brazil nut oil emulsions with gum Arabic using ultrasound-assisted homogenization. The emulsions were prepared in a completely randomized design varying the time (2 and 4 min) and the ultrasound power (30 and 40%). The physicochemical properties of the emulsions (pH, conductivity, turbidity, zeta potential, surface tension, rheology and optical microscopy) were evaluated after the homogenization process and 4 hours later. The results showed that more energetic homogenization processes (longer duration and higher ultrasound power) favored the physicochemical properties, keeping the emulsions more stable. Thus, Brazil nut oil emulsions prepared with ultrasound-assisted showed good physic-chemical characteristics that can guarantee good emulsion stability during spray drying, guaranteeing efficiency and protection of the physical and chemical properties of the Brazil nut oil
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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