Evaluation of a mobile application for estimation of food intake
Keywords:
Diet, Diet sugens, Nutritional surveillanceAbstract
Objective
Evaluate the use of the Nutrabem (São Paulo, Brasil) mobile application as a tool for measurement of food intake among university students.
Methods
Cross-sectional study of a random sample of 40 undergraduate students at the Universidade Federal de São Paulo, Campus Baixada Santista. Food intake data were estimated using the Nutrabem app and the 24-hour dietary recall. Intakes of energy, carbohydrates, proteins, lipids, calcium, iron, and vitamin C were calculated. The intake of food groups and diet quality were evaluated by the Diet Quality Index associated with the Digital Food Guide. The agreement between the methods was assessed using the Pearson’s correlation coefficient and the Student’ t-test.
Results
Strong correlations were observed between energy (0.77), carbohydrates (0.82) and protein (0.83). The groups: poultry, fish, and eggs; beef and pork; refined grains and breads; and fruits and legumes showed strong correlations (between 0.76 and 0.85). There were moderate correlations (0.59 and 0.71) between the groups sugars and sweets; whole grains, tubers and roots, milk and dairy products, animal fats, and the Diet Quality Index associated with the Digital Food Guide scores. Vegetables and leafy greens, nuts, and vegetable oils showed weak correlations (0.31 and 0.43). Homogeneity assessment revealed similarity between the results
obtained by both methods (p>0.05).
Conclusion
The Nutrabem app can be used as a tool to assess dietary intake among university students since it produces results similar to those obtained by the 24-hour dietary recall method.
References
World Health Organization. Assessing national capacity for the prevention and control of noncommunicable diseases: Report of the 2010 global survey. Geneva: WHO; 2012.
Brasil. Ministério da Saúde. Guia alimentar para a população brasileira. Brasília: Ministério da Saúde; 2014.
Katz D, Meller S. Can we say what diet is best for health? Annu Rev Pub health. 2014;35:83-103.
Drewnowski A, Kawachi I. Diets and health: How food decisions are shaped by biology, economics, geography, and social interactions. Big Data. 2015;3(3):193-7.
Anjos LA, Souza DR, Rossato SL. Desafios na medição quantitativa de ingestão alimentar em estudos populacionais. Rev Nutr. 2009;22(1):151-61. https://doi.org/10.1590/51415-52732009000100014
Barbosa RMS, Colares LGT, Soares EA. Desenvolvimento de guias alimentares em diversos países. Rev Nutr. 2008;21(4):455-67. https://doi.org/10.1590/S1415-52732008000400010
Domene SMA. Avaliação do consumo alimentar. In: Taddei JA, Lang RMF, Longo-Silva G, Toloni MHA. Nutrição em saúde pública. Rio de Janeiro: Rubio; 2011. p.8-21.
Barbosa KB, Lima Rosado LE, Franceschini SDC, Priore SE. Instrumentos de inquérito dietético utilizados na avaliação do consumo alimentar em adolescentes: comparação entre métodos. Arch Latinoam Nutr. 2007;57(1):43-50.
Holzinger A, Dorner S, Födinger M, Valdez AC, Ziefle M. Chances of increasing youth health awareness through mobile wellness applications. LNCS. 2010;6389:71-81.
Caivano S, Domene SMA. Diet quality index for healthy food choices. Rev Nutr. 2013;26(6):693-9. https://doi.org/10.1590/S1415-52732013000600008
Thompson FE, Subar AF, Loria CM, Reedy JL, Baranowski T. Need for technological innovation in dietary assessment. J Am Diet Assoc. 2011;110(1):48-51. https://doi.org/10.1016/j.jada.2009.10.008
Fisberg RM, Marchioni DML, Colucci ACA. Avaliação do consumo alimentar e da ingestão de nutrientes na prática clínica. Arq Bras Endocrinol Metab. 2009;53(5):617-24.
Caivano S, Ferreira BJ, Domene SMA. Avaliação da usabilidade do Guia Alimentar Digital móvel segundo a percepção dos usuários. Rev Ciên Saúde Coletiva. 2014;19(5):1437-46 https://doi.org/10.1590/1413-81232014195.13932013
Liu C, Zhu Q, Holroyd KA, Seng EK. Status and trends of mobile-health applications for iOS devices: A developer’s perspective. J Syst Software. 2011;84(11):2022-33. https://doi.org/10.1016/j.jss.2011.06.049
Parker AG, Harper R, Grinter RE. Celebratory healthy technology. J Diab Science Techny. 2011;5(2):319-24.
Rodrigues AGM, Proença RPDC. Use of food images for evaluating food intake. Rev Nutr. 2011;24(5):765-76. https://doi.org/10.1590/S1415-52732011000500009
Instituto Brasileiro de Geografia e Estatística. Pesquisa de orçamentos familiares 2008-2009: análise do consumo alimentar pessoal no Brasil. Rio de Janeiro: IBGE; 2011.
Moshfegh AJ, Rhodes DG, Baer DJ, Murayi T, Clemens JC, Rumpler WV, et al. The US department of agriculture automated multiple-pass method reduces bias in the collection of energy intakes. Am J Clin Nutr. 2008;88(2):324-32.
Caivano S, Domene SMA, Anunciato T. Nutrabem Pro. São Paulo: NutraBem Consultoria; 2009 [acesso 20 fev 2016]. Disponível em: http://Nutrabem.com.br/site/instituto-nutra-bem
Universidade Estadual de Campinas. Tabela Brasileira de Composição de Alimentos – Taco. 4ª ed. Campinas: Unicamp; 2011 [acesso 20 fev 2016]. Disponível em: http://www.unicamp.br/nepa/taco/contar/taco_4_edicao_ampliada_e_revisada
United State Department of Agriculture. National nutrient database for standard reference release, nº 27. Washington (DC): USDA; 2001 [cited 20 Fev 2016]. Available from: http://ndb.nal.usda.gov/ndb/search/list
Touvier M, Kesse-Guyot E, Méjean C, Pollet C, Malon A, Castetbon K, et al. Comparison between an interactive web-based self-administered 24h dietary record and an interview by a dietitian for large-scale epidemiological studies. Br J Nutr. 2011;105(7):1055-64. https://doi.org/10.1017/S0007114510004617
Vereecken CA, Covents M, Sichert-Hellert W, Alvira JMF, Le Donne C, De Henauw S, et al. Development and evaluation of a self-administered computerized 24-h dietary recall method for adolescents in Europe. Int J Obes. 2008;32(Supl.5):S26-S34. https://doi.org/10.1038/ijo.2008.180
Vance VA, Woodruff SJ, McCargar LJ, Husted J, Hanning RM. Self-reported dietary energy intake of normal weight, overweight and obese adolescents. Public Health Nutr. 2009;12(2):222-7. https://doi.org/10.1017/S1368980008003108
Universidade Federal de São Paulo. Análise do perfil de estudantes ingressantes da Universidade Federal de São Paulo. São Paulo: Unifesp; 2016 [acesso 5 set 2016]. Disponível em: http://www.unifesp.br/reitoria/prae/images/prae/Informativo/Analise_perfil_estudantes_executiva.pdf
Klovning A, Sandvik H, Hunskaar S. Web-based survey attracted age-biased sample with more severe illness than paper-based survey. J Clin Epidemiol. 2009;62(10):1068-74. https://doi.org/10.1016/j.jclinepi.2008.10.015
Touvier M, Mejean C, Kesse-Guyot E, Pollet C, Malon A, Castetbon K, et al. Comparison between web-based and paper versions of a self-administered anthropometric questionnaire. Eur J Epidemiol 2010;25(5):287-96. https://doi.org/10.1007/s10654-010-9433-9
Castell GS, Serra-Majem L, Ribas-Barba, L. What and how much do we eat? 24-hour dietary recall method. Nutr Hosp. 2015;31(Supl.3):46-8. https://doi.org/10.3305/nh.2015.31.sup3.8750
Baldo C, Zanchim MC, Kirsten VR, De Marchi, ACB. Diabetes Food Control: um aplicativo móvel para avaliação do consumo alimentar de pacientes diabéticos. Rev Eletron Comun Inf Inov Saúde. 2015;9(3):1-12.
Selem SSC, Carvalho AM, Verly-Junior E, Carlos JV, Teixeira JA, Marchioni DML, et al. Validade e reprodutibilidade de um questionário de frequência alimentar para adultos de São Paulo, Brasil. Rev Bras Epidemiol. 2014;17(4):852-9. https://doi.org/10.1590/1809-4503201400040005
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Copyright (c) 2023 Samantha Bittencourt MESCOLOTO, Simone CAIVANO, Semíramis Martins Álvares DOMENE
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