Ultra-processed food consumption and risk of obesity: a prospective cohort study of UK Biobank

Objective: To examine the associations between ultra-processed food consumption and risk of obesity among UK adults. Methods: Participants aged 40-69 years at recruitment in the UK Biobank (2006-2019) with dietary intakes collected using 24-hour recall and repeated measures of adiposity - body mass index (BMI), waist circumference (WC) and percentage of body fat (% BF) - were included (N=22,659; median follow-up: 5 years). Ultra-processed foods were identified using the NOVA classification and their consumption was expressed as a percentage of total energy intake. Multivariable Cox proportional hazards regression models were used to estimate hazard ratios (HR) of several indicators of obesity according to ultra-processed food consumption. Models were adjusted for sociodemographic and lifestyle characteristics. Results: 947 incident cases of overall obesity (BMI≥30 kg/m2) and 1,900 incident cases of abdominal obesity (men: WC≥102cm, women: WC≥88cm) were identified during follow-up. Participants in the highest quartile of ultra-processed food consumption had significantly higher risk of developing overall obesity (HR: 1.79; 95%CI: 1.06─3.03) and abdominal obesity (HR: 1.30; 95%CI: 1.14─1.48). They had higher risk of experiencing a ≥5% increase in BMI (HR: 1.31; 95%CI: 1.20─1.43), WC (HR: 1.35; 95%CI: 1.25─1.45) and %BF (HR: 1.14; 95%CI: 1.03─1.25), than those in the lowest quartile of consumption. Conclusions: Our findings provide evidence that higher consumption of ultra-processed food is strongly associated with a higher risk of multiple indicators of obesity in the UK adult population. Policy makers should consider actions that promote consumption of fresh or minimally processed foods and reduce consumption of ultra-processed foods

Ultra-processed food consumption and obesity in the Australian adult population

Background: Rapid simultaneous increases in ultra-processed food sales and obesity prevalence have been observed worldwide, including in Australia. Consumption of ultra-processed foods by the Australian population was previously shown to be systematically associated with increased risk of intakes of nutrients outside levels recommended for the prevention of obesity. This study aims to explore the association between ultra-processed food consumption and obesity among the Australian adult population and stratifying by age group, sex and physical activity level. Methods: A cross-sectional analysis of anthropometric and dietary data from 7411 Australians aged ≥20 years from the National Nutrition and Physical Activity Survey 2011–2012 was performed. Food consumption was evaluated through 24-h recall. The NOVA system was used to identify ultra-processed foods, i.e. industrial formulations manufactured from substances derived from foods and typically added of flavours, colours and other cosmetic additives, such as soft drinks, confectionery, sweet or savoury packaged snacks, microwaveable frozen meals and fast food dishes. Measured weight, height and waist circumference (WC) data were used to calculate the body mass index (BMI) and diagnosis of obesity and abdominal obesity. Regression models were used to evaluate the association of dietary share of ultra-processed foods (quintiles) and obesity indicators, adjusting for socio-demographic variables, physical activity and smoking. Results: Significant (P-trend ≤ 0.001) direct dose–response associations between the dietary share of ultra-processed foods and indicators of obesity were found after adjustment. In the multivariable regression analysis, those in the highest quintile of ultra-processed food consumption had significantly higher BMI (0.97 kg/m2; 95% CI 0.42, 1.51) and WC (1.92 cm; 95% CI 0.57, 3.27) and higher odds of having obesity (OR = 1.61; 95% CI 1.27, 2.04) and abdominal obesity (OR = 1.38; 95% CI 1.10, 1.72) compared with those in the lowest quintile of consumption. Subgroup analyses showed that the trend towards positive associations for all obesity indicators remained in all age groups, sex and physical activity level. Conclusion: The findings add to the growing evidence that ultra-processed food consumption is associated with obesity and support the potential role of ultra-processed foods in contributing to obesity in Australia

The environmental impact of beef and ultra-processed food consumption in Brazil

Copyright © The Author(s), 2024. Objective: This study evaluated the independent and combined environmental impacts of the consumption of beef and ultra-processed foods in Brazil. Design: Cross-sectional study. Setting: Brazil. Participants: We used food purchases data from a national household budget survey conducted between July 2017 and July 2018, representing all Brazilian households. Food purchases were converted into energy, carbon footprints and water footprints. Multiple linear regression models were used to assess the association between quintiles of beef and ultra-processed foods in total energy purchases and the environmental footprints, controlling for sociodemographic variables. Results: Both beef and ultra-processed foods had a significant linear association with carbon and water footprints (P < 0·01) in crude and adjusted models. In the crude upper quintile of beef purchases, carbon and water footprints were 47·7 % and 30·8 % higher, respectively, compared to the lower quintile. The upper quintile of ultra-processed food purchases showed carbon and water footprints 14·4 % and 22·8 % higher, respectively, than the lower quintile. The greatest reduction in environmental footprints would occur when both beef and ultra-processed food purchases are decreased, resulting in a 21·1 % reduction in carbon footprint and a 20·0 % reduction in water footprint. Conclusions: Although the environmental footprints associated with beef consumption are higher, dietary patterns with lower consumption of beef and ultra-processed foods combined showed the greatest reduction in carbon and water footprints in Brazil. The high consumption of beef and ultra-processed foods is harmful to human health, as well as to the environment; thus, their reduction is beneficial to both.Science and Technology Facilities Council Global Challenges Research Fund; the Fundação de Amparo à Pesquisa do Estado de São Paulo – FAPESP (G.L.C., grant number (2022/11009-8)), and F.R. is a beneficiary of a research fellowship of the World Cancer Research Fund

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

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