High risk groups and disease markers Professor Bruce Duncan Federal University of Rio Grande do Sul
Professor Bruce Duncan Federal University of Rio Grande do Sul
Ultraprocessed Foods What They Are and What We Know About Their Risks Bruce B. Duncan, MD, PhD Postgraduate Program in Epidemiology Federal University of Rio Grande do Sul, Brazil 18 July 2018 Thanks to Carlos Monteiro for several of the slides presented
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Brasilia DF 2014 http://dab.saude.gov.br/portaldab/biblioteca.php?conteudo=publicacoes/guia_alimentar2014
NOVA: A food classification based on extent and purpose of industrial processing NOVA Food groups Examples 1) Unprocessed or minimally processed foods Edible parts of plants and animals after separation from nature or modified/preserved by minimal processes (no substances added) 2) Processed culinary ingredients Substances extracted from foods or nature and used to prepare, cook and season Group 1 foods such as salt, sugar, oils or fats 3) Processed foods Group 1 foods modified with the addition of salt, sugar, oils or fats to preserve and enhance their sensory qualities 4) Ultra-processed foods Formulations of substances derived from foods plus cosmetic additives, and designed to be durable, convenient, hyper-palatable, irresistible and highly profitable Source: Monteiro CA et al Public Health Nutrition 2017
Distribution (%) of total daily energy intake according to Nova classification US population aged 1 + years (NHANES 2009-2010) Minimally processed foods Processed culinary ingredients Processed foods Ultra-processed foods 1 Meat 8% Oils 1% Cheese 4% Pizza, sandwich, other fast meals 10% 2 Fruits 5% Sugar 1% Salted meat products 1% Breads 9% 3 Milk 5% All other < 1% All other 2% Soft drinks, fruit and milk drinks 8% 4 Grains 3% Sweet snacks, ice cream, desserts 6% 5 Potatoes 2% Cakes, cookies, pies, pastries 5% 6 Eggs 1% Salty snacks 4% 7 Pasta 1% Breakfast cereals 3% 8 Fish < 1% Sauces, dressings, gravies 3% 9 Legumes<1% Reconstituted meat/fish products 2% 10 Vegetables < 1% All other 8% All other 1% All 30.1% 2.9% 7,1% 59.9% Source: Martinez Steele, Baraldi, Louzada, Moubarac, Mozaffarian and Monteiro 2015 BMJ Open 5
India Kenya Cameroon Nigeria Indonesia Uzbekistan Egypt Morocco Vietnam Azerbaijan China Peru Philippines Malaysia Iran Algeria Georgia Bosnia Ukraine Thailand Turkey Tunisia South Pakistan Belarus Kazakhst Greece Ecuador Romania Colombia Slovenia Russia United South Singapore Dominica Lithuania Croatia Hungary Venezuela Latvia Bolivia Macedon Portugal Taiwan Czech Brazil Italy Guatemala Bulgaria Costa Rica Slovakia Estonia serbia France Hong Kong Poland Uruguay Saudi Denmark Sweden Spain Israel Austria Finland New Argentina Ireland Netherla Switzerla Japan United Norway Chile Australia Belgium Mexico Germany Canada United Kg/person 350 300 250 200 150 100 50 Annual retail sales of ultra-processed food and drink products in 80 countries (2013) India 6.7 China Nige 50.5 Thailand 75.2 South Korea South Africa 82.5 95.6 Brazil 113 Canada Mexico 231.5 Australia214 Argentina 208.3 185 Saudi Arabia Italy 149.6 113.3 USA 308 0 Source : PAHO 2015. Ultra-processed food and drinks products in Latin America. Washington, PAHO.
Fuente: Alimentos y bebidas ultraprocesados en América Latina: tendencias, efectos sobre la obesidade y implicaciones para las políticas públicas. Washington, PAHO, 2015. Evolution of sales of UPFs in 12 Latin American countries, 1999-2013 Kg/pessoa/ano Brazil
Critical nutrients in the overall diet according to the share of ultra-processed foods (quintiles). Brasil 2008-9 Energy (kcal/g) 2 Q5 1.5 Q1 1 0 10 20 30 40 50 Dietary share of ultra-processed foods (% energy) Source: Adapted from Louzada ML 2015 et al Rev Saude Pub 49
Protective nutrients in the overall diet according to the share of ultra-processed foods (quintiles) Brasil 2008-9 Vitamin C (mg/1000 kcal) 95 90 85 Q1 80 75 0 10 20 30 40 50 Dietary share of ultra-processed foods (% energy) Q5 Source: Adapted from Louzada ML 2015 et al Rev Saude Pub 49
The Evidence that UPFs Are Harmful Ecological Studies: Share of ultra-processed foods in national food baskets and obesity in 19 European countries (1991-2008) y = a + 0,25x + E (R² = 0,63) Fonte: Monteiro et al Public Health Nutrition 2018 doi:10.1017/s13689 80017001379
Annual adult population mean BMI Evidence of Harm: Multiple Time Series: Annual sales of ultra-processed foods versus annual estimated adult mean BMI in 12 Latin American countries in the period 2000 2009 30.0 29.0 BMI= 15.5 + 0.014 (ULTRAPROCESSED)+ +e R²= 0.79; P<0.0001 Mexico Chile Venezuela 28.0 27.0 26.0 25.0 24.0 20 40 60 80 100 120 140 160 180 200 220 Annual sales of ultra-processed foods (kg/person) Costa Rica Uruguay Guatemala Brazil Ecuador Dominican Republic Colombia Bolivia
Cross-Sectional Studies of Individuals: Obesity according to quintiles of the dietary share of ultra-processed foods Brazilian population 10y+ (2008/9) Adjusted RR for being obese 2 1 Q1 Q2 Q3 Q4 Q5 Dietary share of ultra-processed foods (quintiles) * Adjustment for age, sex, income, education, ethnicity, region, setting, tobacco, and physical activity Source: Louzada et al., 2015 Consumption of ultra-processed foods and obesity in Brazilian adolescents and adults. Prev Med 81:9-15
Prospective Cohort Studies Incidence of Overweight/Obesity by UPF consumption (quartiles) Nine year incidence* in The University of Navarra Follow-up (SUN) cohort study 21% risk of hypertension for 4th (vs. 1st) quartile consumption of UPFs University of Navarra Follow-up (SUN) Cohort Study Mendonça RD et al. Am J Hypertens 2017;30(4):358-366 *Adjusted for sex, age, marital status, education level, physical activity, hours of TV watching, sleeping/siesta, smoking status, snacking between meals, following a special diet at baseline, baseline body mass index,and consumption of fruits and vegetables. 12% risk of cancer for each 10% in UPF consumption French NutriNet-Santé cohort (2009-17) Fiolet T et al. BMJ 2018;360:k322 Mendonça et al. Am J Clin Nut October 12, 2016 doi: 10.3945/ajcn.116.135004
Paper 47 Risk of large weight gain (> 90th percentile: 1.68 kg/year), ELSA-Brasil (n=11827) Crude RR (IC95%) Adjusted* RR (IC95%) For each 15% point increase 1.36 (1.26-1.47) 1.12 (1.03-1.22) Q1 1 1 Q2 1.35 (1.14-1.61) 1.15 (0.97-1.37) Q3 1.51 (1.28-1.78) 1.20 (1.02-1.42) Q4 1.79 (1.52-2.10) 1.27 (1.07-1.50) 0.6 0.8 1 1.2 1.4 1.6 *Through Poisson regression with robust variance for: age, sex, color/race, center, school achievement, smoking, physical activity, baseline BMI. Canhada S et al. WCPD10
Paper 47 Risk of large waist circumference gain (> 90th percentile: 2.42 cm/year), ELSA-Brasil (n=11827) Crude RR (IC95%) Adjusted RR (IC95%) For each 15% point increase 1.42 (1.31-1.53) 1.15 (1.06-1.25) Q1 1 1 Q2 1.29 (1.08-1.54) 1.11 (0.94-1.33) Q3 1.56 (1.32-1.84) 1.23 (1.04-1.46) Q4 1.92 (1.64-2.26) 1.33 (1.12-1.58) *Through Poisson regression with robust variance for: age, sex, color/race, center, school achievement, smoking, physical activity, and waist circumference at baseline. 0.6 0.8 1 1.2 1.4 1.6 Canhada S et al. WCPD10
Conclusion Ultra-processed foods and the NOVA classification provide a conceptual framework for investigating the role of food production and comercialization in the obesity epidemic Intervening to control one important cause of the current obesity and diabetes pandemics
Thank You bbduncan@ufrgs.br
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