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Associations Between Ultra-processed Foods Consumption and Indicators of Adiposity in US Adolescents: Cross-Sectional Analysis of the 2011-2016 National Health and Nutrition Examination Survey

  • Daniela Neri
    Correspondence
    Address correspondence to: Daniela Neri, PhD, Department of Nutrition, School of Public Health. Center for Epidemiological Research in Nutrition and Health, University of São Paulo, Av Dr Arnaldo 715, São Paulo SP, 01246-907, São Paulo, Brazil.
    Affiliations
    Department of Nutrition, School of Public Health, University of São Paulo, São Paulo, Brazil

    Center for Epidemiological Research in Nutrition and Health, School of Public Health, University of São Paulo, São Paulo, Brazil
    Search for articles by this author
  • Eurídice Martínez-Steele
    Affiliations
    Department of Nutrition, School of Public Health, University of São Paulo, São Paulo, Brazil

    Center for Epidemiological Research in Nutrition and Health, School of Public Health, University of São Paulo, São Paulo, Brazil
    Search for articles by this author
  • Neha Khandpur
    Affiliations
    Department of Nutrition, School of Public Health, University of São Paulo, São Paulo, Brazil

    Center for Epidemiological Research in Nutrition and Health, School of Public Health, University of São Paulo, São Paulo, Brazil

    Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, Massachusetts
    Search for articles by this author
  • Renata Levy
    Affiliations
    Center for Epidemiological Research in Nutrition and Health, School of Public Health, University of São Paulo, São Paulo, Brazil

    Department of Preventive Medicine, School of Medicine, University of São Paulo, São Paulo, Brazil
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Published:January 17, 2022DOI:https://doi.org/10.1016/j.jand.2022.01.005

      Abstract

      Background

      Ultra-processed foods represent a considerable part of the diet of US children and adolescents, yet their association with total, abdominal, and visceral overweight/obesity remains understudied.

      Objective

      To examine associations between dietary contribution of ultra-processed foods and total, abdominal, and visceral overweight/obesity in a nationally representative sample of US adolescents.

      Design

      Cross-sectional analyses were performed on data collected from adolescents participating in the 2011-2016 National Health and Nutrition Examination Survey.

      Participants/setting

      Participants included 3587 adolescents aged 12 to 19 years, who had data from at least 1 day of valid 24-hour dietary recall data.

      Main outcome measures

      Total overweight/obesity, abdominal overweight/obesity, and visceral overweight/obesity data were collected.

      Statistical analyses performed

      All food items (grams per day) recorded in the 24-hour recalls were classified according to Nova. Multiple logistic regressions were used to evaluate associations between the dietary contribution of ultra-processed foods (expressed in percentage of total grams per day) and outcomes. Multivariable models were adjusted for sociodemographic covariates, physical activity, total energy intake, whether the individual was following a special diet for weight loss, and indicators of the nutritional quality of the diet.

      Results

      In multivariable analyses, the highest consumption of ultra-processed food was associated with 45%, 52%, and 63% higher odds of total, abdominal, and visceral overweight/obesity, respectively (odds ratio [OR] 1.45, 95% CI 1.03-2.06, P for linear trend = .040; OR 1.52, 95% CI 1.06-2.18, P for linear trend = .026; OR 1.63, 95% CI 1.19-2.24, P for linear trend = .005, respectively), compared with the lowest consumption. A 10% increment in the proportion of ultra-processed foods in the diet was associated with an increased risk of both abdominal overweight/obesity (OR 1.07; 95% CI 1.01-1.13) and visceral overweight/obesity (OR 1.07; 95% CI 1.02-1.13).

      Conclusions

      Study findings support the growing evidence of cross-sectional and prospective associations between ultra-processed foods and increased adiposity and also with metabolically unhealthy phenotypes of obesity in adolescence. Timely action to reduce the consumption of ultra-processed foods among adolescents is needed.

      Keywords

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      References

        • Umer A.
        • Kelley G.A.
        • Cottrell L.E.
        • Giacobbi P.
        • Innes K.E.
        • Lilly C.L.
        Childhood obesity and adult cardiovascular disease risk factors: A systematic review with meta-analysis.
        BMC Public Health. 2017; 17: 683https://doi.org/10.1186/s12889-017-4691-z
        • Van Gaal L.F.
        • Mertens I.L.
        • De Block C.E.
        Mechanisms linking obesity with cardiovascular disease.
        Nature. 2006; 444: 875-880https://doi.org/10.1038/nature05487
        • Freedman D.S.
        • Dietz W.H.
        • Srinivasan S.R.
        • Berenson G.S.
        The relation of overweight to cardiovascular risk factors among children and adolescents: The Bogalusa Heart Study.
        Pediatrics. 1999; 103: 1175-1182https://doi.org/10.1542/peds.103.6.1175
        • Fontana L.
        • Eagon J.C.
        • Trujillo M.E.
        • Scherer P.E.
        • Klein S.
        Visceral fat adipokine secretion is associated with systemic inflammation in obese humans.
        Diabetes. 2007; 56: 1010-1013https://doi.org/10.2337/db06-1656
        • Pischon T.
        • Boeing H.
        • Hoffmann K.
        • et al.
        General and abdominal adiposity and risk of death in Europe.
        N Engl J Med. 2008; 359: 2105-2120https://doi.org/10.1056/NEJMoa0801891
        • Kuk J.L.
        • Katzmarzyk P.T.
        • Nichaman M.Z.
        • Church T.S.
        • Blair S.N.
        • Ross R.
        Visceral fat is an independent predictor of all-cause mortality in men.
        Obesity (Silver Spring). 2006; 14: 336-341https://doi.org/10.1038/oby.2006.43
        • Janssen I.
        • Katzmarzyk P.T.
        • Ross R.
        Waist circumference and not body mass index explains obesity related health risk.
        Am J Clin Nutr. 2004; 79: 379-384https://doi.org/10.1093/ajcn/79.3.379
        • Gower B.A.
        • Nagy T.R.
        • Goran M.I.
        Visceral fat, insulin sensitivity, and lipids in prepubertal children.
        Diabetes. 1999; 48: 1515-1521https://doi.org/10.2337/diabetes.48.8.1515
        • Tchernof A.
        • Després J.P.
        Pathophysiology of human visceral obesity: An update.
        Physiol Rev. 2013; 93: 359-404https://doi.org/10.1152/physrev.00033.2011
        • Fryar C.D.
        • Carroll M.D.
        • Afful J.
        Prevalence of overweight, obesity, and severe obesity among children and adolescents aged 2–19 years: United States, 1963–1965 through 2017–2018.
        NCHS Health E-Stats. 2020;
        • Baker P.
        • Machado P.
        • Santos T.
        • et al.
        Ultra-processed foods and the nutrition transition: Global, regional and national trends, food systems transformations and political economy drivers.
        Obes Rev. 2020; 21: e13126https://doi.org/10.1111/obr.13126
        • Swinburn B.A.
        • Sacks G.
        • Hall K.D.
        • et al.
        The global obesity pandemic: Shaped by global drivers and local environments.
        Lancet. 2011; 378: 804-814https://doi.org/10.1016/S0140-6736(11)60813-1
        • NCD Risk Factor Collaboration (NCD-RisC)
        Worldwide trends in body-mass index, underweight, overweight, and obesity from 1975 to 2016: A pooled analysis of 2416 population-based measurement studies in 128·9 million children, adolescents, and adults.
        Lancet. 2017; 390: 2627-2642https://doi.org/10.1016/S0140-6736(17)32129-3
        • Monteiro C.A.
        • Cannon G.
        • Levy R.B.
        • et al.
        Ultra-processed foods: What they are and how to identify them.
        Public Health Nutr. 2019; 22: 936-941https://doi.org/10.1017/S1368980018003762
        • Neri D.
        • Steele E.M.
        • Khandpur N.
        • et al.
        Ultraprocessed food consumption and dietary nutrient profiles associated with obesity: A multicountry study of children and adolescents.
        Obes Rev. 2021; 23e13387https://doi.org/10.1111/obr.13387
        • Neri D.
        • Martinez-Steele E.
        • Monteiro C.A.
        • Levy R.B.
        Consumption of ultra-processed foods and its association with added sugar content in the diets of US children, NHANES 2009-2014.
        Pediatr Obes. 2019; 14: e12563https://doi.org/10.1111/ijpo.12563
        • Marrón-Ponce J.A.
        • Sánchez-Pimienta T.G.
        • Louzada M.L.D.C.
        • Batis C.
        Energy contribution of NOVA food groups and sociodemographic determinants of ultra-processed food consumption in the Mexican population.
        Public Health Nutr. 2018; 21: 87-93https://doi.org/10.1017/S1368980017002129
        • Cediel G.
        • Reyes M.
        • da Costa Louzada M.L.
        • et al.
        Ultra-processed foods and added sugars in the Chilean diet (2010).
        Public Health Nutr. 2018; 21: 125-133https://doi.org/10.1017/S1368980017001161
        • Askari M.
        • Heshmati J.
        • Shahinfar H.
        • Tripathi N.
        • Daneshzad E.
        Ultra-processed food and the risk of overweight and obesity: A systematic review and meta-analysis of observational studies.
        Int J Obes (Lond). 2020; 44: 2080-2091https://doi.org/10.1038/s41366-020-00650-z
        • Rauber F.
        • Steele E.M.
        • Louzada M.L.D.C.
        • Millett C.
        • Monteiro C.A.
        • Levy R.B.
        Ultra-processed food consumption and indicators of obesity in the United Kingdom population (2008-2016).
        PLoS One. 2020; 15e0232676https://doi.org/10.1371/journal.pone.0232676
        • Canhada S.L.
        • Luft V.C.
        • Giatti L.
        • 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: 1076-1086https://doi.org/10.1017/S1368980019002854
        • Hall K.D.
        • Ayuketah A.
        • Brychta R.
        • 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.e3https://doi.org/10.1016/j.cmet.2019.05.008
        • Mendonça R.D.
        • Pimenta A.M.
        • Gea A.
        • 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: 1433-1440https://doi.org/10.3945/ajcn.116.135004
        • Konieczna J.
        • Morey M.
        • Abete I.
        • et al.
        Contribution of ultra-processed foods in visceral fat deposition and other adiposity indicators: Prospective analysis nested in the PREDIMED-Plus trial.
        Clin Nutr. 2021; 40 (S0261–5614(21)00029-7)
        • Chang K.
        • Khandpur N.
        • Neri D.
        • et al.
        Association between childhood consumption of ultraprocessed food and adiposity trajectories in the Avon Longitudinal Study of Parents and Children Birth Cohort.
        JAMA Pediatr. 2021; 14e211573https://doi.org/10.1001/jamapediatrics.2021.1573
        • Khandpur N.
        • Neri D.A.
        • Monteiro C.
        • et al.
        Ultra-processed food consumption among the paediatric population: An overview and call to action from the European Childhood Obesity Group.
        Ann Nutr Metab. 2020; 76: 109-113https://doi.org/10.1159/000507840
        • Costa C.S.
        • Rauber F.
        • Leffa P.S.
        • Sangalli C.N.
        • Campagnolo P.D.B.
        • Vitolo M.R.
        Ultra-processed food consumption and its effects on anthropometric and glucose profile: A longitudinal study during childhood.
        Nutr Metab Cardiovasc Dis. 2019; 29: 177-184https://doi.org/10.1016/j.numecd.2018.11.003
        • Costa C.S.
        • Del-Ponte B.
        • Assunção M.C.F.
        • Santos I.S.
        Consumption of ultra-processed foods and body fat during childhood and adolescence: A systematic review.
        Public Health Nutr. 2018; 21: 148-159https://doi.org/10.1017/S1368980017001331
        • Costa C.D.S.
        • Assunção M.C.F.
        • Loret de Mola C.
        • et al.
        Role of ultra-processed food in fat mass index between 6 and 11 years of age: A cohort study.
        Int J Epidemiol. 2021; 50: 256-265https://doi.org/10.1093/ije/dyaa141
        • Bawaked R.A.
        • Fernández-Barrés S.
        • Navarrete-Muñoz E.M.
        • et al.
        Impact of lifestyle behaviors in early childhood on obesity and cardiometabolic risk in children: Results from the Spanish INMA birth cohort study.
        Pediatr Obes. 2020; 15: e12590https://doi.org/10.1111/ijpo.12590
        • Vedovato G.M.
        • Vilela S.
        • Severo M.
        • Rodrigues S.
        • Lopes C.
        • Oliveira A.
        Ultra-processed food consumption, appetitive traits and BMI in children: A prospective study.
        Br J Nutr. 2021; 125: 1427-1436https://doi.org/10.1017/S0007114520003712
        • Cunha D.B.
        • da Costa T.H.M.
        • da Veiga G.V.
        • Pereira R.A.
        • Sichieri R.
        Ultra-processed food consumption and adiposity trajectories in a Brazilian cohort of adolescents: ELANA study.
        Nutr Diabetes. 2018; 8: 28https://doi.org/10.1038/s41387-018-0043-z
        • Loomba-Albrecht L.A.
        • Styne D.M.
        Effect of puberty on body composition.
        Curr Opin Endocrinol Diabetes Obes. 2009; 16: 10-15https://doi.org/10.1097/med.0b013e328320d54c
        • Diwadkar R.
        • Neri D.
        • Miller T.L.
        Nutritional evaluation and intervention.
        in: Lipshultz S.E. Messiah S.E. Miller T.L. Pediatric Metabolic Syndrome. 1st ed. Springer-Verlag London, 2012: 283-309
        • Fox C.S.
        • Massaro J.M.
        • Hoffmann U.
        • et al.
        Abdominal, visceral and subcutaneous adipose tissue compartments: Association with metabolic risk factors in the Framingham Heart Study.
        Circulation. 2007; 116: 39-48https://doi.org/10.1161/CIRCULATIONAHA.106.675355
        • Møller G.
        • Ritz C.
        • Kjølbæk L.
        • et al.
        Sagittal abdominal diameter and waist circumference appear to be equally good as identifiers of cardiometabolic risk.
        Nutr Metab Cardiovasc Dis. 2021; 31: 518-527https://doi.org/10.1016/j.numecd.2020.09.032
        • Weber D.R.
        • Levitt Katz L.E.
        • Zemel B.S.
        • et al.
        Anthropometric measures of abdominal adiposity for the identification of cardiometabolic risk factors in adolescents.
        Diabetes Res Clin Pract. 2014; 103: e14-e17https://doi.org/10.1016/j.diabres.2013.12.050
        • National Health and Nutrition Examination Survey (NHANES) 2011
        Anthropometry Procedures Manual.
        • Zipf G.
        • Chiappa M.
        • Porter K.S.
        • Ostchega Y.
        • Lewis B.G.
        • Dostal J.
        National health and nutrition examination survey: Plan and operations, 1999-2010.
        Vital Health Stat 1. 2013; (PMID: 25078429): 1-37
        • Banna J.C.
        • McCrory M.A.
        • Fialkowski M.K.
        • Boushey C.
        Examining plausibility of self-reported energy intake data: Considerations for method selection.
        Front Nutr. 2017; 4: 45https://doi.org/10.3389/fnut.2017.00045
        • Nielsen S.J.
        • Adair L.
        An alternative to dietary data exclusions.
        J Am Diet Assoc. 2007; 107: 792-799https://doi.org/10.1016/j.jada.2007.02.003
        • Fryar C.D.
        • Gu Q.
        • Ogden C.L.
        • Flegal K.M.
        Anthropometric reference data for children and adults: United States, 2011–2014. National Center for Health Statistics.
        Vital Health Stat 3. 2016; : 1-46
        • Ahluwalia N.
        • Dwyer J.
        • Terry A.
        • Moshfegh A.
        • Johnson C.
        Update on NHANES dietary data: Focus on collection, release, analytical considerations, and uses to inform public policy.
        Adv Nutr. 2016; 7: 121-134https://doi.org/10.3945/an.115.009258
        • Fitt E.
        • Mak T.N.
        • Stephen A.M.
        • et al.
        Disaggregating composite food codes in the UK National Diet and Nutrition Survey food composition databank.
        Eur J Clin Nutr. 2010; 64: S32-S36https://doi.org/10.1038/ejcn.2010.207
        • Juul F.
        • Martinez-Steele E.
        • Parekh N.
        • Monteiro C.A.
        • Chang V.W.
        Ultra-processed food consumption and excess weight among US adults.
        Br J Nutr. 2018; 120: 90-100https://doi.org/10.1017/S0007114518001046
        • Martínez Steele E.
        • Baraldi L.G.
        • Louzada M.L.
        • Moubarac J.C.
        • Mozaffarian D.
        • Monteiro C.A.
        Ultra-processed foods and added sugars in the US diet: Evidence from a nationally representative cross-sectional study.
        BMJ Open. 2016; 6e009892https://doi.org/10.1136/bmjopen-2015-009892
        • Kuczmarski R.J.
        • Ogden C.L.
        • Guo S.S.
        • et al.
        2000 CDC growth charts for the United States: Methods and development.
        Vital Health Stat. 2002; 11 (PMID: 12043359): 1-190
        • Ogden C.L.
        • Carroll M.D.
        • Fakhouri T.H.
        • et al.
        Prevalence of obesity among youths by household income and education level of head of household—United States 2011-2014.
        MMWR Morb Mortal Wkly Rep. 2018; 67: 186-189https://doi.org/10.15585/mmwr.mm6706a3
        • US Department of Health and Human Services
        Physical activity guidelines for Americans. 2nd ed.
        (Published 2018)
      1. Stata Statistical Software. StataCorp LP, 2015
        Version: Release 14
        • Juonala M.
        • Magnussen C.G.
        • Berenson G.S.
        • et al.
        Childhood adiposity, adult adiposity, and cardiovascular risk factors.
        N Engl J Med. 2011; (17;365(20):1876–1885. https://doi.org/10.1056/NEJMoa1010112)
        • Freedman D.S.
        • Katzmarzyk P.T.
        • Dietz W.H.
        • et al.
        Relation of body mass index and skinfold thicknesses to cardiovascular disease risk factors in children: The Bogalusa Heart Study.
        Am J Clin Nutr. 2009; 90: 210-216https://doi.org/10.3945/ajcn.2009.27525
        • Pagliai G.
        • Dinu M.
        • Madarena M.P.
        • Bonaccio M.
        • Iacoviello L.
        • Sofi F.
        Consumption of ultra-processed foods and health status: A systematic review and meta-analysis.
        Br J Nutr. 2021; 125: 308-318https://doi.org/10.1017/S0007114520002688
        • Lane M.M.
        • Davis J.A.
        • Beattie S.
        • et al.
        Ultraprocessed food and chronic noncommunicable diseases: A systematic review and meta-analysis of 43 observational studies.
        Obes Rev. 2021; 22: e13146https://doi.org/10.1111/obr.13146
        • Louzada M.L.
        • Baraldi L.G.
        • Steele E.M.
        • et al.
        Consumption of ultra-processed foods and obesity in Brazilian adolescents and adults.
        Prev Med. 2015; 81: 9-15https://doi.org/10.1016/j.ypmed.2015.07.018
        • Nardocci M.
        • Leclerc B.S.
        • da Costa Louzada M.L.
        • Monteiro C.A.
        • Batal M.
        • Moubarac J.C.
        Consumption of ultra-processed foods and obesity in Canada.
        Can J Public Health. 2019; (20;110(1):4e14. https://doi.org/10.17269/s41997-018-0142-6)
        • Hall K.D.
        A review of the carbohydrate-insulin model of obesity.
        Eur J Clin Nutr. 2017; 71: 323-326https://doi.org/10.1038/ejcn.2017.21
        • Bleich S.N.
        • Vercammen K.A.
        The negative impact of sugar-sweetened beverages on children’s health: An update of the literature.
        BMC Obes. 2018; 5: 6https://doi.org/10.1186/s40608-017-0178-9
        • Malik V.S.
        • Popkin B.M.
        • Bray G.A.
        • Després J.P.
        • Hu F.B.
        Sugar-sweetened beverages, obesity, type 2 diabetes mellitus, and cardiovascular disease risk.
        Circulation. 2010; 121: 1356-1364https://doi.org/10.1161/CIRCULATIONAHA.109.876185
        • Jenkins D.J.
        • Jenkins A.L.
        • Wolever T.M.
        • Rao A.V.
        • Thompson L.U.
        Fiber and starchy foods: Gut function and implications in disease.
        Am J Gastroenterol. 1986; 81 (PMID: 3020970): 920-930
        • Kaczmarczyk M.M.
        • Miller M.J.
        • Freund G.G.
        The health benefits of dietary fiber: Beyond the usual suspects of type 2 diabetes mellitus, cardiovascular disease and colon cancer.
        Metabolism. 2012; 61: 1058-1066https://doi.org/10.1016/j.metabol.2012.01.017
        • Davy B.M.
        • Melby C.L.
        The effect of fiber-rich carbohydrates on features of syndrome X.
        J Am Diet Assoc. 2003; 103: 86-96https://doi.org/10.1053/jada.2003.50005
        • Delzenne N.M.
        • Cani P.D.
        A place for dietary fibre in the management of the metabolic syndrome.
        Curr Opin Clin Nutr Metab Care. 2005; 8: 636-640https://doi.org/10.1097/01.mco.0000171124.06408.71
        • Davis J.N.
        • Alexander K.E.
        • Ventura E.E.
        • Toledo-Corral C.M.
        • Goran M.I.
        Inverse relation between dietary fiber intake and visceral adiposity in overweight Latino youth.
        Am J Clin Nutr. 2009; 90: 1160-1166https://doi.org/10.3945/ajcn.2009.28133
        • Parikh S.
        • Pollock N.K.
        • Bhagatwala J.
        • Guo D.H.
        • Gutin B.
        • Zhu H.
        • Dong Y.
        Adolescent fiber consumption is associated with visceral fat and inflammatory markers.
        J Clin Endocrinol Metab. 2012; 97: E1451-E1457https://doi.org/10.1210/jc.2012-1784
        • Hairston K.G.
        • Vitolins M.Z.
        • Norris J.M.
        • Anderson A.M.
        • Hanley A.J.
        • Wagenknecht L.E.
        Lifestyle factors and 5-year abdominal fat accumulation in a minority cohort: The IRAS Family Study.
        Obesity (Silver Spring). 2012; 20: 421-427https://doi.org/10.1038/oby.2011.171
        • Fischer K.
        • Pick J.A.
        • Moewes D.
        • Nöthlings U.
        Qualitative aspects of diet affecting visceral and subcutaneous abdominal adipose tissue: A systematic review of observational and controlled intervention studies.
        Nutr Rev. 2015; 73: 191-215https://doi.org/10.1093/nutrit/nuu006
        • Beslay M.
        • Srour B.
        • Méjean 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; (27;17(8):e1003256. https://doi.org/10.1371/journal.pmed.1003256)
        • Chassaing B.
        • Koren O.
        • Goodrich J.K.
        • et al.
        Dietary emulsifiers impact the mouse gut microbiota promoting colitis and metabolic syndrome.
        Nature. 2015; 519: 92-96https://doi.org/10.1038/nature14232
        • Ciardi C.
        • Jenny M.
        • Tschoner A.
        • et al.
        Food additives such as sodium sulphite, sodium benzoate and curcumin inhibit leptin release in lipopolysaccharide-treated murine adipocytes in vitro.
        Br J Nutr. 2012; 107: 826-833https://doi.org/10.1017/S0007114511003680
        • Ayton A.
        • Ibrahim A.
        The Western diet: A blind spot of eating disorder research? A narrative review and recommendations for treatment and research.
        Nutr Rev. 2020; 78: 579-596https://doi.org/10.1093/nutrit/nuz089
        • Pearlman M.
        • Obert J.
        • Casey L.
        The association between artificial sweeteners and obesity.
        Curr Gastroenterol Rep. 2017; (21;19(12):64. https://doi.org/10.1007/s11894-017-0602-9)
        • Simmons A.L.
        • Schlezinger J.J.
        • Corkey B.E.
        What are we putting in our food that is making us fat? Food additives, contaminants, and other putative contributors to obesity.
        Curr Obes Rep. 2014; 3: 273-285https://doi.org/10.1007/s13679-014-0094-y
        • Lopes A.E.D.S.C.
        • Araújo L.F.
        • Levy R.B.
        • Barreto S.M.
        • Giatti L.
        Association between consumption of ultra-processed foods and serum C-reactive protein levels: Cross sectional results from the ELSA-Brasil study.
        Sao Paulo Med J. 2019; 137: 169-176https://doi.org/10.1590/1516-3180.2018.0363070219
        • Miclotte L.
        • Van de Wiele T.
        Food processing, gut microbiota and the globesity problem.
        Crit Rev Food Sci Nutr. 2020; 60: 1769-1782https://doi.org/10.1080/10408398.2019.1596878
        • Mims T.S.
        • Abdallah Q.A.
        • Stewart J.D.
        • et al.
        The gut mycobiome of healthy mice is shaped by the environment and correlates with metabolic outcomes in response to diet.
        Commun Biol. 2021; 4: 281https://doi.org/10.1038/s42003-021-01820-z
        • Barrea L.
        • Arnone A.
        • Annunziata G.
        • et al.
        Adherence to the Mediterranean diet, dietary patterns and body composition in women with polycystic ovary syndrome (PCOS).
        Nutrients. 2019; 11: 2278https://doi.org/10.3390/nu11102278
        • Cavallo D.N.
        • Horino M.
        • McCarthy W.J.
        Adult intake of minimally processed fruits and vegetables: Associations with cardiometabolic disease risk factors.
        J Acad Nutr Diet. 2016; 116: 1387-1394https://doi.org/10.1016/j.jand.2016.03.019
        • Aguilera J.M.
        The food matrix: Implications in processing, nutrition and health.
        Crit Rev Food Sci Nutr. 2019; 59: 3612e29https://doi.org/10.1080/10408398.2018
        • Fardet A.
        Minimally processed foods are more satiating and less hyperglycemic than ultra-processed foods: A preliminary study with 98 ready-to-eat foods.
        Food Funct. 2016; 7: 2338-2346https://doi.org/10.1039/c6fo00107f
        • Anne Moorhead S.
        • Welch R.W.
        • Barbara M.
        • et al.
        The effects of the fibre content and physical structure of carrots on satiety and subsequent intakes when eaten as part of a mixed meal.
        Br J Nutr. 2006; 96: 587-595https://doi.org/10.1079/bjn20061790
        • Martínez Steele E.
        • Raubenheimer D.
        • Simpson S.J.
        • Baraldi L.G.
        • Monteiro C.A.
        Ultra-processed foods, protein leverage and energy intake in the USA.
        Public Health Nutr. 2018; 21: 114-124https://doi.org/10.1017/S1368980017001574
        • Forde C.G.
        • Mars M.
        • de Graaf K.
        Ultra-processing or oral processing? A role for energy density and eating rate in moderating energy intake from processed foods.
        Curr Dev Nutr. 2020; 4: nzaa019https://doi.org/10.1093/cdn/nzaa019
        • Payne A.N.
        • Chassard C.
        • Lacroix C.
        Gut microbial adaptation to dietary consumption of fructose, artificial sweeteners and sugar alcohols: Implications for host-microbe interactions contributing to obesity.
        Obes Rev. 2012; 13: 799-809https://doi.org/10.1111/j.1467-789X.2012.01009.x
        • Livingston A.S.
        • Cudhea F.
        • Wang L.
        • et al.
        Effect of reducing ultraprocessed food consumption on obesity among US children and adolescents aged 7-18 years: Evidence from a simulation model.
        BMJ Nutr Prev Health. 2021; 4: 397-404https://doi.org/10.1136/bmjnph-2021-000303
        • Poll F.A.
        • Miraglia F.
        • D’avila H.F.
        • Reuter C.P.
        • Mello E.D.
        Impact of intervention on nutritional status, consumption of processed foods, and quality of life of adolescents with excess weight.
        J Pediatr (Rio J). 2020; 96: 621-629https://doi.org/10.1016/j.jped.2019.05.007
        • Ostfeld R.J.
        • Allen K.E.
        Ultra-processed foods and cardiovascular disease: Where do we go from here?.
        J Am Coll Cardiol. 2021; 77: 1532-1534https://doi.org/10.1016/j.jacc.2021.02.003
        • Healthy Voices
        EU action plan on childhood obesity 2014-2020. 2014.
        • World Cancer Research Fund International
        NOURISHING policy database: Restrict food advertising and other forms of commercial promotion.
        (Published 2021)
        • US Department of Agriculture and US Department of Health and Human Services
        Dietary Guidelines for Americans, 2020-2025. 9th ed.
        (Published December 2020. Accessed March 1, 2019. Accessed January 12, 2021)
        • Pan American Health Organization
        Ultra-processed Food and Drink Products in Latin America: Trends, Impact on Obesity, Policy Implications.
        Pan American Health Organization, 2015
      2. Ministry of Health of Brazil. Secretariat of Health Care. Primary Health Care Department. Dietary guidelines for the Brazilian population, 2015. Accessed March 1, 2019. https://bvsms.saude.gov.br/bvs/publicacoes/dietary_guidelines_brazilian_population.pdf

      Biography

      Daniela Neri, PhD, is a postdoctoral research fellow, Department of Nutrition, School of Public Health, University of São Paulo, São Paulo, Brazil. She is also from Center for Epidemiological Research in Nutrition and Health, School of Public Health, University of São Paulo, São Paulo, Brazil.

      Biography

      Eurídice Martínez-Steele is a postdoctoral research fellow, Department of Nutrition, School of Public Health, University of São Paulo, São Paulo, Brazil. She is also from Center for Epidemiological Research in Nutrition and Health, School of Public Health, University of São Paulo, São Paulo, Brazil.

      Biography

      Neha Khandpur is a research scientist, Department of Nutrition, School of Public Health, University of São Paulo, São Paulo, Brazil. She is also from Center for Epidemiological Research in Nutrition and Health, School of Public Health, University of São Paulo, São Paulo, Brazil. She is also a research scientist, Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, MA. Neha Khandpur is a researcher scientist, Department of Nutrition, School of Public Health, University of São Paulo, São Paulo, Brazil. She is also from the Center for Epidemiological Research in Nutrition and Health, School of Public Health, University of São Paulo, São Paulo, Brazil. She is also a senior research scientist, Department of Preventive Medicine, School of Medicine, University of São Paulo, São Paulo, Brazil.

      Biography

      R. Levy is a postdoctoral research fellow, Department of Nutrition, School of Public Health, University of São Paulo, São Paulo, Brazil. She is also from Center for Epidemiological Research in Nutrition and Health, School of Public Health, University of São Paulo, São Paulo, Brazil. She is also a research scientist, Department of Preventive Medicine, School of Medicine, University of São Paulo, São Paulo, Brazil.