Sociodemographic disparities in the consumption of ultra-processed food and drink products in Southern Brazil: a population-based study
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This study aims to describe the distribution of ultra-processed food and drink products (UPP) consumption according to sociodemographic characteristics in adults from southern Brazil, and to investigate which are the most-consumed UPP subtypes in the different social strata.
Cross-sectional analysis of the second wave of a population-based cohort of 1720 adults. The usual caloric intake and the caloric contribution of UPP to total energy intake (%CTEI) were estimated by the application of two 24-h dietary recalls (adjusted by intra- and inter-individual variability). Data were analyzed according to gender, age, marital status, schooling, and family income. Linear regression models were used to estimate the adjusted means.
Consumption data were obtained from 1206 adults (70.1% of the original cohort). Mean UPP consumption was higher in males than females (829.6 kcal vs 694.3 kcal, p value < 0.001), but the %CTEI from UPP increased in females (34.7% vs 39.3%, p value < 0.001), even after adjusting for sociodemographic variables. In the full model, which included all sociodemographic variables, %CTEI from UPP was inversely associated with age (difference between extreme categories 7.1 pp., 95 CI% 7.7–6.5) and directly associated with schooling (difference between extreme categories 6.3 pp., 95 CI% 5.5–7.1). The subtypes of UPP that contributed most to the observed differences were processed breads, fast food, and ultra-processed pies and sweets.
UPP account for a third of the calories normally consumed, with women, young people, and better educated individuals being the most vulnerable groups. These results can help when planning public policies to reduce UPP consumption.
KeywordsFood habits Nutrition Risk factors Population characteristics Nutrition survey Nutritional epidemiology
We would like to express our gratitude to Dr. Nilza Nunes da Silva, Department of Epidemiology, School of Public Health of the University of São Paulo, São Paulo, Brazil, for her advice on sample procedures. We would also like to thank the Brazilian Institute of Geography and Statistics (IBGE) and Florianópolis Health Authority staff for their valuable help with the practical aspects of this study. We are also grateful to Dr. Carlos Augusto Monteiro and his research group “Núcleo de Pesquisas Epidemiológicas em Nutrição e Saúde” (NUPENS), for their advice and assistance regarding food group classification. We appreciate the cooperation of Dr. Regina Mara Fisberg and her research group “Grupo de Pesquisa de Avaliação do Consumo Alimentar” (GAC), for facilitating the use of Nutrition Data Software for Research (NDSR) software. The authors conceived and designed this study, performed the experiments, analyzed the data, and wrote the paper jointly.
Author Silvia Giselle Ibarra Ozcariz has participated in the research planning process, field and data entry supervision, conducted the statistical analyses, written, and led this article. Katia Jakovljevic Pudla has participated in the study design and data entry and contributed in revising this article. Ana Paula Bortoletto Martins has contributed to classifying the food groups and revising this article. Marco Peres led the EpiFloripa research and contributed to the revision of this article. David González-Chica contributed to the study design, statistical analysis, writing, and revision of the article.
Compliance with ethical standards
The EpiFloripa Adults 2009 project was approved by the Ethics Committee on Human Research of the Federal University of Santa Catarina (UFSC), under protocol number 351 / 08. The subjects were informed about the objectives of the study and were requested to sign an Informed Consent Form.
The Project was sponsored by the Brazilian National Council for Scientific and Technological Development (CNPq), grant number 485327/2007–4.
Conflict of interest
The authors declare that they have no conflict of interest.
- Benzecry E, Pinheiro A, Lacerda E (2001) Tabela para avaliação de consumo alimentar em medidas caseiras. Editora Atheneu, Rio de JaneiroGoogle Scholar
- Bombem KCM, Bandoni DH, Canella DS, Jaime PC (2012) Manual de medidas caseiras e receitas para cálculos dietéticos. M. Books, São PauloGoogle Scholar
- IBGE (2010) Pesquisa de orçamentos familiares: 2008–2009. Antropometria e estado nutricional de crianças, adolescentes e adultos no Brasil. IBGE, Rio de JaneiroGoogle Scholar
- Djupegot IL, Nenseth CB, Bere E, Bjørnarå HBT, Helland SH, Øverby NC, Torstveit MK, Stea TH (2017) The association between time scarcity, sociodemographic correlates and consumption of ultra-processed foods among parents in Norway: a cross-sectional study. BMC Public Health 17:447. https://doi.org/10.1186/s12889-017-4408-3 CrossRefGoogle Scholar
- Dodd KW, Guenther PM, Freedman LS, Subar AF, Kipnis V, Midthune D, Tooze JA, Krebs-Smith SM (2006) Statistical methods for estimating usual intake of nutrients and foods: a review of the theory.see comment. J Am Diet Assoc 106:1640–1650. https://doi.org/10.1016/j.jada.2006.07.011 CrossRefGoogle Scholar
- Fisberg RM, Marchioni DML (2012) Manual de avaliação do consumo alimentar em estudos populacionais: a experiência do inquérito de saúde em São Paulo (ISA). Universidade de São Paulo, São PauloGoogle Scholar
- IBGE (2011) Taxa de analfabetismo da população de 15 anos ou mais de idade, por grupos de idade, segundo as Unidades da Federação e os municípios das capitais 2000/2010. IBGE, Rio de JaneiroGoogle Scholar
- Louzada ML da C, Baraldi LG, Steele EM, Martins APB, Canella DS, Moubarac JC, Levy RB, Cannon G, Afshin A, Imamura F, Mozaffarian D, Monteiro CA (2015) Consumption of ultra-processed foods and obesity in Brazilian adolescents and adults. Prev Med (Baltim) 81:9–15. https://doi.org/10.1016/j.ypmed.2015.07.018 CrossRefGoogle Scholar
- Martínez Steele E, Popkin BM, Swinburn B, Monteiro CA (2017) The share of ultra-processed foods and the overall nutritional quality of diets in the US: evidence from a nationally representative cross-sectional study. Popul Health Metrics 15:6. https://doi.org/10.1186/s12963-017-0119-3 CrossRefGoogle Scholar
- Monteiro CA, Cannon G, Moubarac J-C, Martins APB, Martins CA, Garzillo J, Canella DS, Baraldi LG, Barciotte M, Louzada ML da C, Levy RB, Claro RM, Jaime PC (2015) Dietary guidelines to nourish humanity and the planet in the twenty-first century. A blueprint from Brazil. Public Health Nutr 18:2311–2322. https://doi.org/10.1017/S1368980015002165 CrossRefGoogle Scholar
- Moubarac J-C, Claro RM, Baraldi LG, Levy RB, Martins APB, Cannon G, Monteiro CA (2013) International differences in cost and consumption of ready-to-consume food and drink products: United Kingdom and Brazil, 2008–2009. Glob Public Health 8:845–856. https://doi.org/10.1080/17441692.2013.796401 CrossRefGoogle Scholar
- Moubarac J-C, Pan American Health Organization, World Health Organization (2015) Ultra-processed food and drink products in Latin America: Trends, impact on obesity, policy implications. In: http://iris.paho.org/xmlui/bitstream/handle/123456789/7699/9789275118641_eng.pdf. Accessed 26 June 2017
- NEPA - Núcleo de Estudos e Pesquisas em Alimentação (2011) Tabela brasileira de composição de alimentos. NEPA - Unicamp:161. https://doi.org/10.1007/s10298-005-0086-x
- Ozcariz SGI, Bernardo C de O, Cembranel F, Peres MA, González-Chica DA (2015) Dietary practices among individuals with diabetes and hypertension are similar to those of healthy people: a population-based study. BMC Public Health 15:479. https://doi.org/10.1186/s12889-015-1801-7 CrossRefGoogle Scholar
- Stevens GA, Singh GM, Lu Y, Danaei G, Lin JK, Finucane MM, Bahalim AN, McIntire RK, Gutierrez HR, Cowan M, Paciorek CJ, Farzadfar F, Riley L, Ezzati M (2012) National, regional, and global trends in adult overweight and obesity prevalences. Popul Health Metrics 10:22. https://doi.org/10.1186/1478-7954-10-22 CrossRefGoogle Scholar
- WHO (2013) Global action plan for the prevention and control of noncommunicable diseases 2013–2020. World Heal Organ 102Google Scholar
- Willett W (2013) Nutritional epidemiology, 3rd edn. Oxford University Press, New YorkGoogle Scholar