Hall et al. 1919. Hall KD, Ayuketah A, Brychta R, Cai H, Cassimatis T, Chen KY, et al. Ultra-processed diets cause excess calorie intake and weight gain: an inpatient randomized controlled trial of ad libitum food intake. Cell Metab 2019; 30:67-77.e3. (2019) |
Randomized clinical trial |
Adults from the United States aged between 18 to 50 years old in 2018 (n = 20) (NIH Study). |
Ad libitum offer for two weeks of diets made with, on average, 83% of calories from ultra-processed foods or diets without ultra-processed foods. |
Daily energy intake and change in weight and body fat in two weeks. |
The ultra-processed and non-ultra-processed diets were paired for calories, energy density, macronutrients, sugar, sodium and fiber. |
When exposed to an ultra-processed diet, participants consumed, on average, 508 ± 106Kcal more per day than when exposed to diets without ultra-processed foods. At the end of two weeks, the participants increased 0.9kg ± 0.3kg in weight and 0.4kg ± 0.1kg in body fat consuming the ultra-processed diet and decreased 0.9kg ± 0.3kg in weight and 0.3kg ± 0.1kg of body fat consuming the non-ultra-processed diet (p-value < 0.001). |
High |
Canhada et al. 2020. Canhada SL, Luft VC, Giatti L, Duncan BB, Chor D, Fonseca MJM, et al. Ultra-processed foods, incident overweight and obesity, and longitudinal changes in weight and waist circumference: the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). Public Health Nutr 2020; 23:1076-86. (2019) |
Cohort |
Brazilian adults aged 35 years old or older with a mean follow-up of 3.8 years between 2008/2010-2012/2014 (n = 11,827) (ELSA-Brasil). |
Participation of ultra-processed foods in the food’s total energy. |
Incidence of overweight and obesity and weight gain and waist circumference. |
Age, sex, race/color, family income, education, physical activity and smoking status. |
Participants in the largest quartile of consumption of ultra-processed foods had a higher risk of weight gain (adjusted RR = 1.27; 95%CI: 1.07; 1.50) and waist circumference (adjusted RR = 1.33; 95%CI: 1.12; 1.58), excessive and higher incidence of overweight and obesity (adjusted RR = 1.20; 95%CI 1.03; 1.40) when compared to those in the lowest quartile. |
High |
Mendonça et al. 2121. Mendonça RD, Pimenta AM, Gea A, de la Fuente-Arrillaga C, Martínez-González MA, Lopes AC, et al. Ultraprocessed food consumption and risk of overweight and obesity: the University of Navarra Follow-Up (SUN) cohort study. Am J Clin Nutr 2016; 104:1433-40. (2016) |
Cohort |
Spanish middle-aged adults with a mean follow-up of 8.9 years between 1999-2012 (n = 8,541) (The Sun). |
Consumption of ultra-processed foods servings/day. |
Incidence of overweight and obesity. |
Age, sex, education, marital status, physical activity, smoking status, hours watching television, nap times, BMI at baseline, following a special diet at baseline, snacking between meals and consumption of fruits and vegetables. |
Participants in the largest quartile of consumption of ultra-processed foods had a higher risk of overweight/obesity (adjusted HR = 1.26; 95%CI: 1.10; 1.45) when compared to those in the lowest quartile. |
High |
Rauber et al. 2222. Rauber F, Chang K, Vamos EP, Louzada MLC, Monteiro CA, Millett CJ, et al. Ultra-processed food consumption and risk of adiposity: a prospective cohort study of UK Biobank. Eur J Nutr 2021; 60:2169-80. (2020) |
Cohort |
British adults aged between 40 to 69 years old with a mean follow-up of 5 years between 2006-2019 (n = 22,659) (UK Biobank). |
Participation of ultra-processed foods in the food’s total energy. |
Incidence of obesity and abdominal obesity and gain of BMI, waist circumference and body fat. |
Sex, socioeconomic deprivation index, physical activity, smoking status and hours of sleep. |
Participants in the highest quartile of consumption of ultra-processed foods had a higher risk of obesity (adjusted HR = 1.58; 95%CI: 1.32; 1.90) and high waist circumference (adjusted HR = 1.38; 95%CI: 1.21; 1.57) and to experience an increase of ≥ 5% in BMI (adjusted HR = 1.30; 95%CI: 1.19; 1.42), in waist circumference (adjusted HR = 1.30; 95%CI: 1.21; 1.40) and in the percentage of body fat (adjusted HR = 1.14; 95%CI: 1.04; 1.26) when compared to those with the lowest consumption quartile. |
High |
Beslay et al. 2323. Beslay M, Srour B, Méjean C, Allès B, Fiolet T, Debras C, et al. Ultra-processed food intake in association with BMI change and risk of overweight and obesity; a prospective analysis of the French NutriNet-Santé cohort. PLoS Med 2020; 17:e1003256. (2020) |
Cohort |
French adults aged 18 years old or over and a mean follow-up of 4.1 years (n = 110,260) |
Participation of ultra-processed foods in the total of food grams. |
Incidence of overweight and obesity and BMI gain. |
Sex, age, marital status, education, physical activity, smoking status, number of dietary records, alcohol intake, energy intake. |
The consumption of ultra-processed foods was positively associated with a higher risk of overweight (adjusted HR associated with a 10% increase in the consumption of ultra-processed foods = 1.11; 95%CI: 1.08; 1.14), obesity (adjusted HR associated with a 10% increase in the consumption of ultra-processed foods = 1.09; 95%CI: 1.05; 1.13) and BMI gain (adjusted B associated with a 10% increase in the consumption of ultra-processed foods: 0.02; 95%CI: 0.01; 0.02) |
High |
Adams & White 2424. Adams J, White M. Characterisation of UK diets according to degree of food processing and associations with socio-demographics and obesity: cross-sectional analysis of UK National Diet and Nutrition Survey (2008-12). Int J Behav Nutr Phys Act 2015; 12:160. (2015) |
Cross-sectional |
British adults aged 18 years old or older in 2008-2012 (n = 2,174). |
Participation of ultra-processed foods in the food’s total energy. |
BMI, overweight and obesity. |
Age, sex, social class and alcohol consumption. |
The consumption of ultra-processed foods was not significantly associated with the outcomes. |
Mean |
Louzada et al. 2525. Louzada ML, Baraldi LG, Steele EM, Martins AP, Canella DS, Moubarac JC, et al. Consumption of ultra-processed foods and obesity in Brazilian adolescents and adults. Prev Med 2015; 81:9-15. (2015) |
Cross-sectional |
Brazilians aged 10 years old or older in 2008/2009 (n = 32,898). |
Participation of ultra-processed foods in the food’s total energy. |
BMI, overweight and obesity. |
Age, sex, race/color, income, education, region, urbanity, physical activity, smoking status, intake of fruits, vegetables and beans. |
Participants in the largest quintile of consumption of ultra-processed foods had a higher mean BMI (adjusted coefficient: 0.94; 95%CI: 0.42; 1.42) and a greater chance of being overweight (adjusted OR = 1.26; 95%CI: 0.95; 1.69) and obesity (adjusted OR = 1.98; 95%CI: 1.26; 3.12) when compared to those in the lowest quintile. |
Mean |
Juul et al. 2626. Juul F, Martínez-Steele E, Parekh N, Monteiro CA, Chang VW. Ultra-processed food consumption and excess weight among US adults. Br J Nutr 2018; 120:90-100. (2018) |
Cross-sectional |
Adults from the United States aged between 20 to 64 years old in 2005-2014 (n = 15,977). |
Participation of ultra-processed foods in the food’s total energy. |
BMI, waist circumference, overweight and obesity. |
Age, sex, ethnicity, socioeconomic status, education, marital status, physical activity and smoking status. |
Participants in the largest quintile of consumption of ultra-processed foods had a higher mean BMI (adjusted coefficient: 1.61; 95%CI: 1.11; 2.10) and waist circumference (adjusted coefficient: 4.07; 95%CI: 2.94; 5.19), greater chance of having obesity (adjusted OR = 1.53; 95%CI 1.29; 1.81), overweight (adjusted OR = 1.48; 95%CI: 1.25; 1.76) and abdominal obesity (adjusted OR = 1.62; 95%CI: 1.39; 1.89) when compared to those in the lowest quintile. |
Mean |
Machado et al. 2727. Machado PP, Martínez-Steele E, Levy RB, Louzada MLC, Rangan A, Woods J, et al. Ultra-processed food consumption and obesity in the Australian adult population. Nutr Diabetes 2020; 10:39. (2020) |
Cross-sectional |
Australian adults aged 20 years old or older between 2011-2012 (n = 7,411). |
Participation of ultra-processed foods in the food’s total energy. |
BMI, waist circumference, obesity and abdominal obesity. |
Age, sex, income, education, area of residence, country of birth, physical activity and smoking status. |
Participants in the largest quintile of consumption of ultra-processed foods had a higher mean BMI (adjusted coefficient: 0.97; 95%CI: 0.42; 1.51), and waist circumference (adjusted coefficient: 1.92cm; 95%CI: 0.57; 3.27) and greater chance of having obesity (adjusted OR = 1.61; 95%CI: 1.27; 2.04) and abdominal obesity (adjusted OR = 1.38; 95%CI: 1.10; 1.72) when compared to those in the lowest quintile. |
Mean |
Rauber et al. 2828. Rauber F, Martínez-Steele E, Louzada MLC, Millett C, Monteiro CA, Levy RB. Ultra-processed food consumption and indicators of obesity in the United Kingdom population (2008-2016). PLoS One 2020; 15:e0232676. (2020) |
Cross-sectional |
British adults aged 19 years old or older in 2008-2016 (n = 6,143). |
Participation of ultra-processed foods in the food’s total energy. |
BMI, waist circumference, obesity and abdominal obesity. |
Age, sex, ethnicity, region, occupation, physical activity, smoking status, hours of sleep, year of research and whether they were on a diet for weight loss. |
Participants in the largest quartile of consumption of ultra-processed foods had a higher mean BMI (adjusted coefficient: 1.66; 95%CI: 0.96; 2.36) and waist circumference (adjusted coefficient: 3.56; 95%CI: 1.79; 5.33), and a greater chance of having obesity (adjusted O =: 1.90; 95%CI: 1.39; 2.61) when compared to those in the lowest quartile. |
Mean |
Nardocci et al. 2929. Nardocci M, Leclerc BS, Louzada ML, Monteiro CA, Batal M, Moubarac JC. Consumption of ultra-processed foods and obesity in Canada. Can J Public Health 2019; 110:4-14. (2018) |
Cross-sectional |
Canadian adults aged 18 years old or older in 2004 (n = 19,363). |
Participation of ultra-processed foods in the food’s total energy. |
Overweight and obesity. |
Age, sex, income, education, immigration, area of residence, physical activity, smoking status, group's total energy intake and type of weight and height measurement (self-reported or directly measured). |
Participants in the largest quintile of consumption of ultra-processed foods were more likely to have obesity (adjusted OR = 1.32; 95%CI: 1.05; 1.57) when compared to those in the lowest quintile. |
Low |
Seale et al. 3030. Seale E, Greene-Finestone LS, de Groh M. Examining the diversity of ultra-processed food consumption and associated factors in Canadian adults. Appl Physiol Nutr Metab 2020; 45:857-64. (2020) |
Cross-sectional |
Canadian adults aged 18 years old or older in 2014/2015 (n = 10,942). |
Number of different types of ultra-processed foods consumed in the previous seven days. |
BMI. |
Age, sex, income and region. |
The consumption of ultra-processed foods was positively associated with BMI (adjusted coefficient: 0.04; 95%CI: 0.02; 0.07). |
Low |
Julia et al. 3131. Julia C, Martinez L, Allès B, Touvier M, Hercberg S, Méjean C, et al. Contribution of ultra-processed foods in the diet of adults from the French NutriNet-Santé study. Public Health Nutr 2018; 21:27-37. (2018) |
Cross-sectional |
French adults aged 18 years old or older between 2009-2014 (n = 74,470). |
Participation of ultra-processed foods in the total of food grams. |
Overweight and obesity. |
Age, sex, income, education, marital status, smoking status, BMI and energy intake. |
Higher consumption of ultra-processed foods was significantly associated with overweight and obesity (p-value < 0.0001). |
Mean |
Silva et al. 3232. Silva FM, Giatti L, Figueiredo RC, Molina MDB, Cardoso LD, Duncan BB, et al. Consumption of ultra-processed food and obesity: cross sectional results from the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) cohort (2008-2010). Public Health Nutr 2018; 21:2271-9. (2018) |
Cross-sectional |
Brazilian adults aged between 35 and 74 years in 2008-2010 (n = 8,977). |
Participation of ultra-processed foods in the food’s total energy. |
BMI, waist circumference, overweight, obesity, high waist circumference and significantly high waist circumference. |
Age, sex, race/color, family income per capita, physical activity, smoking status, hypertension, diabetes, consumption of fresh and minimally processed foods added to culinary ingredients and energy intake. |
Participants in the largest quartile of consumption of ultra-processed foods had a higher mean BMI (adjusted coefficient: 0.64; 95%CI: 0.33; 0.95) and waist circumference (adjusted coefficient: 0.95; 95%CI: 0.17; 1.74) and greater chance of overweight (adjusted OR = 1.32; 95%CI: 1.15; 1.53), obesity (adjusted OR: 1.43, 95%CI: 1.20; 1.72) and high waist circumference (OR = 1.21; 95%CI: 1.01; 1.46) when compared to those in the lowest quartile. |
Mean |
Djupegot et al. 3333. Djupegot IL, Nenseth CB, Bere E, Bjørnarå HBT, Helland SH, Øverby NC, et al. The association between time scarcity, sociodemographic correlates and consumption of ultra-processed foods among parents in Norway: a cross-sectional study. BMC Public Health 2017; 17:447. (2017) |
Cross-sectional |
Norwegian parents of 2-year-old children in 2014/2015 (n = 497). |
Frequency score of the consumption of ultra-processed foods. |
Overweight and obesity. |
Age, sex, education, shortage of time and number of children in the household. |
Overweight/obese people were more likely to have a high consumption of ultra-processed foods at dinner (adjusted OR = 1.54; 95%CI: 1.04; 2.30) when compared to those with normal weight. |
Low |
Pan-American Health Organization 3434. Pan American Health Organization. Ultra-processed food and drink products in Latin America: trends, impact on obesity, policy implications. Washington DC: Pan American Health Organization; 2015. (2015) |
Ecological |
Latin American countries between 2000-2013 (n = 13). |
Total volume, in kg/per capita, of sales of ultra-processed foods. |
BMI trajectories. |
Population size, urbanization and gross national income. |
The increase in the per capita volume of sales of ultra-processed foods was significantly and positively associated with the average increase in the countries’ BMI (p-value < 0.001). |
Mean |
Vandevijvere et al. 3535. Vandevijvere S, Jaacks LM, Monteiro CA, Moubarac JC, Girling-Butcher M, Lee AC, et al. Global trends in ultraprocessed food and drink product sales and their association with adult body mass index trajectories. Obes Rev 2019; 20 Suppl 2:10-9. (2019) |
Ecological |
Countries of the Euromonitor food sales database between 2002-2014 (n = 80). |
Total volume, in kg/per capita, of sales of ultra-processed foods. |
BMI trajectories. |
National income per capita, education, urbanization, average consumption of fruits and vegetables in 2005, GINI index and, indirectly, physical activity. |
Increases in the per capita volume of sales of ultra-processed foods were significantly and positively associated with the BMI trajectories in the population (p-value < 0.001). |
Mean |
Monteiro et al. 3636. Monteiro CA, Moubarac J-C, Levy RB, Canella DS, Louzada MLC, Cannon G. Household availability of ultra-processed foods and obesity in nineteen European countries. Public Health Nutr 2018; 21:18-26. (2018) |
Ecological |
European countries between 1991-2008 (n =19). |
Participation of ultra-processed foods in the total energy available for consumption in households (national per capita). |
Prevalence of obesity in adults. |
GDP per capita, GDP2 per capita, years of difference between the estimates of obesity and availability of ultra-processed foods, obesity measurement method (self-reported or direct measurement), prevalence of physical inactivity and smoking status. |
The national household availability of ultra-processed foods was positive and significantly associated with the national prevalence of obesity among adults. The increase of a percentage in the availability of ultra-processed foods at home was associated with an increase of 0.25 percentage points in the prevalence of obesity. |
Low |
Mendonça et al. 3737. Mendonça RD, Lopes ACS, Pimenta AM, Gea A, Martínez-González MA, Bes-Rastrollo M. Ultra-processed food consumption and the incidence of hypertension in a Mediterranean cohort: The Seguimiento Universidad de Navarra Project. Am J Hypertens 2017; 30:358-66. (2017) |
Cohort |
Spanish middle-aged adults with an average follow-up of 9.1 years between 1999-2012 (n = 14,790) (The Sun). |
Consumption of ultra-processed foods servings/day. |
Hypertension incidence. |
Age, sex, physical activity, smoking status, time watching TV, use of analgesics, family history of hypertension and hypercholesterolemia, following a special baseline diet, baseline BMI, energy intake, alcohol consumption, oil and fruit and vegetable intake. |
Participants in the highest tertile of consumption of ultra-processed foods had a higher risk of hypertension (adjusted HR = 1.21; 95%CI: 1.06; 1.37) when compared to those in the lowest tertile. |
High |
Martínez Steele et al. 3838. Martínez Steele E, Juul F, Neri D, Rauber F, Monteiro CA. Dietary share of ultra-processed foods and metabolic syndrome in the US adult population. Prev Med 2019; 125:40-8. (2019) |
Cross-sectional |
American adults aged 20 years old or older between 2009-2014 (n = 6,385). |
Participation of ultra-processed foods in the food’s total energy. |
Metabolic syndrome. |
Age, sex, race/ethnicity, socioeconomic status, education, physical activity and smoking status. |
Participants in the largest quintile of consumption of ultra-processed foods had a higher prevalence of metabolic syndrome (adjusted PR = 1.28; 95%CI: 1.09; 1.50) when compared to those in the lowest quintile. |
Mean |
Lavigne-Robichaud et al. 3838. Martínez Steele E, Juul F, Neri D, Rauber F, Monteiro CA. Dietary share of ultra-processed foods and metabolic syndrome in the US adult population. Prev Med 2019; 125:40-8. (2018) |
Cross-sectional |
Canadian indigenous people aged 18 years old or older (n = 811). |
Participation of ultra-processed foods in the food’s total energy, sodium and added sugar. |
Metabolic syndrome. |
Age, sex, area of residence, smoking status, energy intake and alcohol consumption. |
Participants in the largest quintile of consumption of ultra-processed foods were more likely to have metabolic syndrome (adjusted OR = 1.90; 95%CI: 1.14; 3.17) when compared to those in the lowest quintile. |
Low |
Nasreddine et al. 4040. Nasreddine L, Tamim H, Itani L, Nasrallah MP, Isma'eel H, Nakhoul NF, et al. A minimally processed dietary pattern is associated with lower odds of metabolic syndrome among Lebanese adults. Public Health Nutr 2018; 21:160-71. (2018) |
Cross-sectional |
Lebanese adults aged 18 years old or older (n = 302). |
Participation of ultra-processed foods in the food’s total energy. |
Metabolic syndrome. |
Age, sex, income, education, marital status, area of residence, physical activity, smoking status, BMI and energy intake. |
The consumption of ultra-processed foods was not significantly associated with metabolic syndrome. |
Low |
Lopes et al. 4141. Lopes A, Araújo LF. Association between consumption of ultra-processed foods and serum C-reactive protein levels: cross-sectional results from the ELSA-Brasil study. São Paulo Med J 2019; 137:169-76. (2019) |
Cross-sectional |
Brazilian adults aged between 35 to 74 years old in 2008-2010 (n = 8,468). |
Participation of ultra-processed foods in the food’s total energy. |
Serum levels of C-reactive protein. |
Age, race/color, education, physical activity, smoking status and BMI. |
Women in the highest tertile of consumption of ultra-processed foods had higher serum levels of C-reactive protein (adjusted coefficient: 1.14; 95%CI: 1.04; 1.24) when compared to those in the lowest tertile in the model adjusted for age, race/color, education, physical activity, smoking status. The association lost significance when adjusted in the model additionally adjusted for BMI (adjusted coefficient: 1.00; 95%CI: 0.92; 1.08). No association was found between men. |
Mean |
Montero-Salazar et al. 4242. Montero-Salazar H, Donat-Vargas C, Moreno-Franco B, Sandoval-Insausti H, Civeira F, Laclaustra M, et al. High consumption of ultra-processed food may double the risk of subclinical coronary atherosclerosis: the Aragon Workers' Health Study (AWHS). BMC Med 2020; 18:235. (2020) |
Cross-sectional |
Spanish adult men aged between 40 to 60 years old (n = 1,876) |
Grams of ultra-processed food. |
Coronary calcium score. |
Age, marital status, education, smoking status, physical activity, sleep duration, serum cholesterol, blood pressure, diabetes, BMI, alcohol intake, fiber intake, cholesterol and total energy. |
Men in the highest quartile of consumption of ultra-processed foods had a greater chance of high coronary calcium score (≥ 100) (adjusted OR = 2.0; 95%CI: 1.26; 3.16) when compared to those in the first quartile. |
Mean |
Alonso-Pedrero et al. 4343. Alonso-Pedrero L, Ojeda-Rodríguez A, Martínez-González MA, Zalba G, Bes-Rastrollo M, Marti A. Ultra-processed food consumption and the risk of short telomeres in an elderly population of the Seguimiento Universidad de Navarra (SUN) Project. Am J Clin Nutr 2020; 111:1259-66. (2020) |
Cross-sectional |
Spanish adults aged between 57 and 91 years old (n = 886) |
Ultra-processed food portions. |
Short telomeres. |
Age, sex, education, smoking status, physical activity, television time, family history of diabetes and cardiovascular diseases, prevalence of cancer, diabetes and dyslipidemia, BMI, energy intake. |
Participants in the largest quartile of consumption of ultra-processed foods were more likely to have short telomeres (adjusted OR = 1.82; 95%CI: 1.05; 3.22) when compared to those in the lowest quartile. |
Low |