ood consumption according to the degree of industrial food processing in Brazilian graduates (CUME Project)
A hierarchical analysis of associated factors
Keywords:
Eating, Nutrition policy, Regression analysis, Social determinants of healthAbstract
Objective
Evaluate the food consumption of the participants of the Cohort of Universities of Minas Gerais, according to the degree of processing, and its relationship with socioeconomic, behavioral, and individual factors.
Methods
A total of 4,124 individuals from the baseline of the Cohort of Universities of Minas Gerais (2016 and 2018) participated in this study. Food consumption was self-reported by completing an online Food Frequency Questionnaire. The foods were divided into 3 groups: Group 1, in natura, minimally processed foods, culinary ingredients and culinary preparations; Group 2, processed foods; Group 3, ultra-processed foods. A hierarchical multiple linear regression model was used to verify the associated factors.
Results
Regarding the factors associated with food consumption, it is noteworthy that Group 1 was positively associated with the practice of physical activity, female gender, age, “non-white” skin color, and the presence of diabetes Mellitus; and negatively with “not married/without stable union” marital status, alcohol abuse, tobacco use, obesity, and depression. Considering Group 2, it was positively associated with alcohol abuse, tobacco use, and age; and negatively with physical activity, female gender, and “non-white” skin color. As for Group 3 it was positively associated with a marital status of “not married/without stable union”, obesity, and depression; and negatively with physical activity, age, “non-white” skin color, and presence of diabetes Mellitus.
Conclusion
The factors that are in at least one of the final hierarchical linear regression models stand out: marital status, physical activity, alcohol abuse, tobacco use, sex, age, skin color, obesity, diabetes mellitus, and depression.
References
World Health Organization. Assessing national capacity for the prevention and control of noncommunicable diseases: Report of the 2019 global survey [Internet]. Geneva: Organization; 2020 [cited 2021 Oct 10]. Available from: https://www.who.int/publications/i/item/9789240002319
Malta DC, Silva Jr JB. Brazilian Strategic Action Plan to Combat Chronic Non-communicable Diseases and the global targets set to confront these diseases by 2025: A review. Epidemiol Serv Saude. 2013;22(1):15164. https://doi.org/10.5123/S1679-49742013000100016
Ministério da Saúde (Brasil). Guia alimentar para a população brasileira [Internet]. 2nd ed. Brasília: Ministério; 2014 [cited 2021 Oct 10]. Available from: https://bvsms.saude.gov.br/bvs/publicacoes/guia_alimentar_ populacao_brasileira_2ed.pdf
Food and Agriculture Organization. Guidelines on the collection of information on food processing through food consumption surveys [Internet]. Rome: Organization; 2015 [cited 2021 Oct 10]. Available from: https://www.fao.org/documents/card/fr/c/a7e19774-1170-4891-b4ae-b7477514ab4e/
Elizabeth L, Machado P, Zinöcker M, Baker P, Lawrence M. Ultra-processed foods and health outcomes: A narrative review. Nutrients. 2020;12(7):1955. https://doi.org/10.3390/nu12071955
Pagliai G, Dinu M, Madarena MP, 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(3):308-18. https://doi. org/10.1017/S0007114520002688
Santos FS, Dias MS, Mintem GC, Oliveira IO, Gigante DP. Food processing and cardiometabolic risk factors: A systematic review. Rev Saude Publica. 2020;54:70. https://doi.org/10.11606/s1518-8787.2020054001704
Berti TL, Rocha TFD, Curioni CC, Verly Junior E, Bezerra FF, Canella DS, et al. Food consumption according to degree of processing and sociodemographic characteristics: Estudo Pró-Saúde, Brazil. Rev Bras Epidemiol. 2019;26(22):e190046. https://doi.org/10.1590/1980-549720190046
Oliveira RR, Peter NB, Muniz LC. Consumo alimentar segundo grau de processamento entre adolescentes da zona rural de um município do sul do Brasil. Cien Saude Colet. 2021;26(3):1105-14. https://doi.org/10.1590/1413-81232021263.06502019
Naspolini NF, Machado PP, Fróes-Asmus CIR, Câmara VM, Moreira JC, Meyer A. Food consumption according to the degree of processing, dietary diversity and socio-demographic factors among pregnant women in Rio de Janeiro, Brazil: The Rio Birth Cohort Study of Environmental Exposure and Childhood Development (PIPA project). Nutr Health. 2021;27(1):79-88. https://doi.org/10.1177/0260106020960881
Dahlgren G, Whitehead M. Policies and Strategies to promote social equity in health Stockholm [Internet]. Bryghuspladsen: Institute for Future Studies; 1991 [cited 2021 Oct 10]. Available from: https://core.ac.uk/ download/pdf/6472456.pdf
Souza DO, Silva SEV, Silva NO. Determinantes Sociais da Saúde: reflexões a partir das raízes da “questão social”. Saude Soc. 2013;22(1):44-56. https://doi.org/10.1590/S0104-12902013000100006
Silva I, Pais-Ribeiro JL, Cardoso H. Por que comemos o que comemos? Determinantes psicossociais da seleção alimentar. Psic Saude & Doenças. 2008 [cited 2021 Oct 10];9(2):189-208. Available from: https:// www.redalyc.org/pdf/362/36219057002.pdf
Alexandre VP, Peixoto MRG, Schmitz BAS, Moura EC. Factors associated with the feeding practices of the adult population of Goiânia, Goiás, Brazil. Rev Bras Epidemiol. 2014;17(1):267-80. https://doi. org/10.1590/1415-790X201400010021ENG
Gomes Domingos AL, Miranda AEDS, Pimenta AM, Hermsdorff HHM, Oliveira FLP, Dos Santos LC, et al. Cohort Profile: The Cohort of Universities of Minas Gerais (CUME). Int J Epidemiol. 2018;47(6):1743-54. https://doi.org/10.1093/ije/dyy152
Schmidt MI, Duncan BB, Mill JG, Lotufo PA, Chor D, Barreto SM, et al. Cohort Profile: Longitudinal Study of Adult Health (ELSA-Brasil). Int J Epidemiol. 2015;44(1):68-75. https://doi.org/10.1093/ije/dyu027
Azarias H, Marques-Rocha JL, Miranda A, Santos LC, Gomes-Domingos AL, Hermsdorff HHM, et al. Online food frequency questionnaire from Cohort of Universities of Minas Gerais (CUME project, Brazil): Construction, validity and reproducibility. Front Nutr. 2021;8:709915. https://doi.org/10.3389/ fnut.2021.709915 18. Universidade Estadual de Campinas. Tabela Brasileira de Composição de Alimentos (TACO). [Internet]. 4th ed. Campinas: NEPA/UNICAMP; 2011 [cited 2021 Oct 10]. Available from: https://www.nepa.unicamp. br/taco/tabela.php?ativo=tabela
United States Department of Agriculture. Composition of Foods Raw, Processed, Prepared USDA National Nutrient Database for Standard Reference, Release 25 [Internet]. Maryland: Department of Agriculture; 2012 [cited 2021 Oct 10]. Available from: https://www.ars.usda.gov/ARSUserFiles/80400525/Data/SR25/ sr25_doc.pdf
Martins APB, Levy RB, Claro RM, Moubarac JC, Monteiro CA. Increased contribution of ultra-processed food products in the Brazilian diet (1987-2009). Rev Saude Publica. 2013;47(4):656-65. https://doi.org/10.1590/S0034-8910.2013047004968
World Health Organization. Who guidelines on physical activity and sedentary behaviour [Internet]. Geneva: Organization; 2020 [cited 2021 Oct 10]. Available from: https://www.who.int/publications/i/ item/9789240015128
National Institute on Alcohol Abuse and Alcoholism. Drinking Levels Defined [Internet]. Bethesda: Institute; 2015 [cited 2021 Oct 10]. Available from: https://www.niaaa.nih.gov/alcohol-health/overview-alcoholconsumption/moderate-binge-drinking
World Health Organization. Obesity: Preventing and managing the global epidemic [Internet]. Geneva: Report of a WHO Consultation on Obesity; 1998. (WHO technical report series; nº 894) [cited 2021 Oct 10]. Available from: https://apps.who.int/iris/handle/10665/42330
Organización Panamericana de la Salud. XXXVI Reunióndel Comitê Asesor de Ivestigaciones en Salud – Encuestra Multicêntrica – Salud Beinestar y Envejecimeiento (SABE) en América Latina e el Caribe [Internet]. México: Organización; 2002 [cited 2021 oct 10] Available from: https://iris.paho.org/handle/10665.2/38968
Barroso WKS, Rodrigues CIS, Bortolotto LA, Mota-Gomes MA, Brandão AA, Feitosa ADM, et al. Diretrizes Brasileiras de Hipertensão Arterial – 2020. Arq Bras Cardiol. 2021;116(3):516-658. https://doi.org/10.36660/abc.20201238
Sociedade Brasileira de Diabetes. Diretrizes Sociedade Brasileira de Diabetes 2019-2020 [Internet]. Clanad: São Paulo; 2019 [cited 2021 Oct 10]. Available from: http://www.saude.ba.gov.br/wp-content/ uploads/2020/02/Diretrizes-Sociedade-Brasileira-de-Diabetes-2019-2020.pdf
Miranda AES, Ferreira AVM, Oliveira FLP, Hermsdorff HHM, Bressan J, Pimenta AM. Validation of metabolic syndrome and its self reported components in the CUME Study. REME. 2017;21:e-10691. https://www.doi.org/10.5935/1415-2762.20170079 28. Victora CG, Huttly SR, Fuchs SC, Olinto MT. The role of conceptual frameworks in epidemiological analysis: A hierarchical approach. Int J Epidemiol. 1997;26(1):224-7. https://doi.org/10.1093/ije/26.1.224
Victora CG, Huttly SR, Fuchs SC, Olinto MT. The role of conceptual frameworks in epidemiological analysis: A hierarchical approach. Int J Epidemiol. 1997;26(1):224-7. https://doi.org/10.1093/ije/26.1.224
Louzada ML, Baraldi LG, Steele EM, Martins AP, Canella DS, Moubarac JC, et al. Consumption of ultraprocessed foods and obesity in Brazilian adolescents and adults. Prev Med. 2015;81:9-15. https://doi.org/10.1016/j.ypmed.2015.07.018
Instituto Brasileiro de Geografia e Estatística. Pesquisa de Orçamentos Familiares – POF: 2017-2018: Avaliação Nutricional da Disponibilidade Domiciliar de Alimentos no Brasil [Internet]. Rio de Janeiro: Instituto; 2020 [cited 2021 Oct 10]. Available from: https://biblioteca.ibge.gov.br/visualizacao/livros/liv101704.pdf
Chen X, Zhang Z, Yang H, Qiu P, Wang H, Wang F, et al. Consumption of ultra-processed foods and health outcomes: A systematic review of epidemiological studies. Nutr J. 2020;19(1):86. https://doi.org/10.1186/s12937-020-00604-1
Baker P, Machado P, Santos T, Sievert K, Backholer K, Hadjikakou M, 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(12):1-22. https://doi.org/10.1111/obr.13126
Baraldi LG, Martinez Steele E, Canella DS, Monteiro CA. Consumption of ultra-processed foods and associated sociodemographic factors in the USA between 2007 and 2012: Evidence from a nationally representative cross-sectional study. BMJ Open. 2018;8(3):1-9. https://doi.org/10.1136/bmjopen-2017-020574
Nardocci M, Polsky JY, Moubarac JC. Consumption of ultra-processed foods is associated with obesity, diabetes and hypertension in Canadian adults. Can J Public Health. 2021;112(3):421-9. https://doi.org/10.17269/s41997-020-00429-9
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. https://doi.org/10.1186/s12966-015-0317-y
Damiani TF, Pereira LP, Ferreira MG. Consumo de frutas, legumes e verduras na Região Centro-Oeste do Brasil: prevalência e fatores associados. Cien Saude Colet. 2017;22(2):369-82. https://doi.org/10.1590/141381232017222.12202015
Silva DCGD, Segheto W, Amaral FCDS, Reis NA, Veloso GSS, Pessoa MC, et al. Consumo de bebidas açucaradas e fatores associados em adultos. Cien Saude Colet. 2019;24(3):899-906. https://doi.org/10.1590/1413-81232018243.05432017
Bezerra IN, Moreira TM, Cavalcante JB, Souza AM, Sichieri R. Food consumed outside the home in Brazil according to places of purchase. Rev Saude Publica. 2017;51(0):15. https://doi.org/10.1590/S15188787.2017051006750
Matos RA, Adams M, Sabaté J. Review: The Consumption of Ultra-Processed Foods and Non-communicable Diseases in Latin America. Front Nutr. 2021;8:622714. https://doi.org/10.3389/fnut.2021.622714
Canuto R, Fanton M, Lira PIC. Iniquidades sociais no consumo alimentar no Brasil: uma revisão crítica dos inquéritos nacionais. Cien Saude Colet. 2019;24(9):3193-212. https://doi.org/10.1590/141381232018249.26202017
Juul F, Martinez-Steele E, Parekh N, Monteiro CA, Chang VW. Ultra-processed food consumption and excess weight among US adults. Br J Nutr. 2018;120(1):90-100. https://doi.org/10.1017/S0007114518001046
Silva JA, Silva KS, Matias TS, Leal DB, Oliveira ESA, Nahas MV. Food consumption and its association with leisure-time physical activity and active commuting in Brazilian workers. Eur J Clin Nutr. 2020;74(2):314-21. https://doi.org/10.1038/s41430-019-0454-5
Castilhos CB, Schneider BC, Muniz LC, Assunção MC. Qualidade da dieta de jovens aos 18 anos de idade, pertencentes à coorte de nascimentos de 1993 da cidade de Pelotas (RS), Brasil. Cien Saude Colet. 2015;20(11):3309-18. https://doi.org/10.1590/1413-812320152011.17822014
French S, Rosenberg M, Knuiman M. The clustering of health risk behaviours in a Western Australian adult population. Health Promot J Austr. 2008;19(3):203-9. https://doi.org/10.1071/he08203
Marin-Leon L, Francisco PM, Segall-Corrêa AM, Panigassi G. Household appliances and food insecurity: gender, referred skin color and socioeconomic differences. Rev Bras Epidemiol. 2011;14(3):398-410. https://doi.org/10.1590/S1415-790X2011000300005
Simões BDS, Barreto SM, Molina MDCB, Luft VC, Duncan BB, Schmidt MI, et al. Consumption of ultraprocessed foods and socioeconomic position: A cross-sectional analysis of the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). Cad Saude Publica. 2018;34(3):e00019717. https://doi.org/10.1590/0102311X00019717
Rezende-Alves K, Hermsdorff HHM, Miranda AES, Lopes ACS, Bressan J, Pimenta AM. Food processing and risk of hypertension: Cohort of Universities of Minas Gerais, Brazil (CUME Project). Public Health Nutr. 2020;6:1-9. https://doi.org/10.1017/S1368980020002074
Silva FM, Giatti L, Figueiredo RC, Molina MDCB, Oliveira Cardoso L, 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(12):2271-79. https://doi.org/10.1017/S1368980018000861
Canhada SL, Luft VC, Giatti L, Duncan BB, Chor D, Fonseca MJMD, 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(6):1076-86. https://doi.org/10.1017/S1368980019002854
Machado PP, Steele EM, Levy RB, Sui Z, Rangan A, Woods J, et al. Ultra-processed foods and recommended intake levels of nutrients linked to non-communicable diseases in Australia: Evidence from a nationally representative cross-sectional study. BMJ Open. 2019;9(8):e029544. https://doi.org/10.1136/bmjopen-2019-029544
Mendonça RD, Lopes AC, Pimenta AM, Gea A, Martinez-Gonzalez 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(4):358-66. https://doi.org/10.1093/ajh/hpw137
Mendonça RD, Pimenta AM, Gea A, de la Fuente-Arrillaga C, Martinez-Gonzalez 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(5):1433-40. https://doi.org/10.3945/ajcn.116.135004
Adjibade M, Julia C, Allès B, Touvier M, Lemogne C, Srour B, et al. Prospective association between ultraprocessed food consumption and incident depressive symptoms in the French NutriNet-Santé cohort. BMC Medicine. 2019;17:78. https://doi.org/10.1186/s12916-019-1312-y
Gómez-Donoso C, Sánchez-Villegas A, Martínez-González MA, Gea A, Mendonça RD, Lahortiga-Ramos F, et al. Ultra-processed food consumption and the incidence of depression in a Mediterranean cohort: The SUN Project. Eur J Nutr. 2020;59(3):1093-1103. https://doi.org/10.1007/s00394-019-01970-1
Zanchim MC, Kirsten VR, Marchi ACB. Consumption of dietary intake markers by patients with diabetes assessed using a mobile application. Cien Saude Colet. 2018;23(12):4199-208. https://doi.org/10.1590/1413812320182312.01412017
