Submitted:
09 February 2024
Posted:
12 February 2024
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Abstract
Keywords:
1. Introduction
2. Materials and Methods
2.1. Study design and settings
2.2. Subjects and Sample Size
2.3. Dietary intake assessment
2.4. Sociodemographic and anthropometric measurements
2.5. Statistical analysis
3. Results
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- WHO. World Health Organization. Bulletin of the World Health Organization. v 90, n 2. 2012.
- Felisbino-Mendes, M.S.; Cousin, E.; Malta, D.C.; et al. The burden of non-communicable diseases attributable to high BMI in Brazil, 1990–2017: findings from the Global Burden of Disease Study. Popul Health Metr. 2020 Sep 30;18(S1):18. [CrossRef]
- Afshin, A.; Sur, P.J.; Fay, K.A.; et al. Health effects of dietary risks in 195 countries, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. The Lancet. 2019 May;393(10184):1958–72. [CrossRef]
- Oikonomou, E.; Psaltopoulou, T.; Georgiopoulos, G.; et al. Western Dietary Pattern Is Associated With Severe Coronary Artery Disease. Angiology. 2018 Apr 21;69(4):339–46. [CrossRef]
- Mujica-Coopman, M.F.; Brito, A.; López de Romaña, D.; et al. Prevalence of Anemia in Latin America and the Caribbean. Food Nutr Bull. 2015 Jun 1;36(2_suppl):S119–28. [CrossRef]
- Black, R.E.; Allen, L.H.; Bhutta, Z.A.; et al. Maternal and child undernutrition: global and regional exposures and health consequences. The Lancet. 2008 Jan;371(9608):243–60. [CrossRef]
- Bailey, R.L.; Pac, S.G.; Fulgoni, V.L.; et al. Estimation of Total Usual Dietary Intakes of Pregnant Women in the United States. JAMA Netw Open. 2019 Jun 21;2(6):e195967. [CrossRef]
- Bai, Y.; Herforth, A.; Masters, W.A. Global variation in the cost of a nutrient-adequate diet by population group: an observational study. Lancet Planet Health. 2022 Jan;6(1):e19–28. [CrossRef]
- Perez-Escamilla, R.; Bermudez, O.; Buccini, G.S.; et al. Nutrition disparities and the global burden of malnutrition. BMJ. 2018 Jun 13;k2252. [CrossRef]
- Jura, M.; Kozak, L.P. Obesity and related consequences to ageing. Age (Omaha). 2016 Feb 4;38(1):23. [CrossRef]
- Wegmüller, R.; Bentil, H.; Wirth, J.P.; et al. Anemia, micronutrient deficiencies, malaria, hemoglobinopathies and malnutrition in young children and non-pregnant women in Ghana: Findings from a national survey. PLoS One. 2020 Jan 30;15(1):e0228258. [CrossRef]
- Jones, A.D.; Acharya, Y.; Galway, L.P. Urbanicity Gradients Are Associated with the Household- and Individual-Level Double Burden of Malnutrition in Sub-Saharan Africa. J Nutr. 2016 Jun 1;146(6):1257–67. [CrossRef]
- Verly-Junior, E.; Marchioni, D.M.; Araujo, M.C.; et al. Evolução da ingestão de energia e nutrientes no Brasil entre 2008–2009 e 2017–2018. Rev Saude Publica. 2021 Dec 8;55(Supl.1):1–22. [CrossRef]
- Micha, R.; Coates, J.; Leclercq, C.; et al. Global Dietary Surveillance: Data Gaps and Challenges. Food Nutr Bull. 2018 Jun 25;39(2):175–205. [CrossRef]
- Miller, V.; Singh, G.M.; Onopa, J.; et al. Global Dietary Database 2017: data availability and gaps on 54 major foods, beverages, and nutrients among 5.6 million children and adults from 1220 surveys worldwide. BMJ Glob Health. 2021 Feb 5;6(2):e003585. [CrossRef]
- Passarelli, S.; Free, C.M.; Allen, L.H.; et al. Estimating national and subnational nutrient intake distributions of global diets. Am J Clin Nutr. 2022 Aug 4;116(2):551–60. [CrossRef]
- Fisberg, M.; Kovalskys, I.; Previdelli, A.N.; et al. Brazilian Study of Nutrition and Health (EBANS) - Brazilian data of ELANS: methodological opportunities and challenges. Rev Assoc Med Bras. 2019 May;65(5):669–77. [CrossRef]
- Fisberg, M.; Kovalskys, I.; Gómez, G.; et al. Latin American Study of Nutrition and Health (ELANS): rationale and study design. BMC Public Health. 2015 Dec 30;16(1):93. [CrossRef]
- Moshfegh, A.J.; Rhodes, D.G.; Baer, D.J.; et al. The US Department of Agriculture Automated Multiple-Pass Method reduces bias in the collection of energy intakes. Am J Clin Nutr. 2008 Aug 1;88(2):324–32. [CrossRef]
- Universidade de São Paulo (USP). Food Research Center (FoRC). Versão 6.0. 2017. Tabela Brasileira de Composição de Alimentos (TBCA).
- Kovalskys, I.; Fisberg, M.; Gómez, G.; et al. Standardization of the Food Composition Database Used in the Latin American Nutrition and Health Study (ELANS). Nutrients. 2015 Sep 16;7(9):7914–24. [CrossRef]
- Harttig, U.; Haubrock, J.; Knüppel, S.; et al. The MSM program: web-based statistics package for estimating usual dietary intake using the Multiple Source Method. Eur J Clin Nutr. 2011 Jul 6;65(S1):S87–91. [CrossRef]
- IOM/ Food and Nutrition Board. Dietary Reference Intakes for Energy, Carbohydrate, Fiber, Fat Fatty Acids, Cholesterol, Protein, and Amino Acids (Macronutrients). 2005.
- World Health Organization. Saturated fatty acid and trans-fatty acid intake for adults and children WHO guideline. Geneva; 2023.
- World Health Organization. Carbohydrate intake for adults and children WHO guideline. Geneva; 2023.
- U.S. Department of Agriculture and U.S. Department of Health and Human Services. Dietary Guidelines for Americans, 2020-2025. 9th edition. 2020.
- WHO. World Health Organization. Guideline: Sugars intake for adults and children. Geneva; 2015.
- Marchioni, D.M.L.; Slater, B.; Fisberg, R.M. Aplicação das Dietary Reference Intakes na avaliação da ingestão de nutrientes para indivíduos. Revista de Nutrição. 2004 Jun;17(2):207–16. [CrossRef]
- WHO – World Health Organization. WHO Consultation on Obesity: preventing and managing the global epidemic. Geneva; 1998.
- Associação Brasileira de Empresas de Pesquisa (ABEP). Critério padrão de classificação econômica Brasil. 2013.
- Matsudo, S.; Araújo, T.; Matsudo, V.; et al. Questionário Internacional de Atividade Física (IPAQ): Estudo de validade e reprodutibilidade no Brasil. Rev Bras Ativ Fís Saúde. 2012 Oct;6(2):5–18. [CrossRef]
- Craig, C.L.; Marshall, A.L.; Sjöström, M.; et al. International Physical Activity Questionnaire: 12-Country Reliability and Validity. Med Sci Sports Exerc. 2003 Aug;35(8):1381–95. [CrossRef]
- Bull, F.C.; Al-Ansari, S.S.; Biddle, S.; et al. World Health Organization 2020 guidelines on physical activity and sedentary behaviour. Br J Sports Med. 2020 Dec;54(24):1451–62. [CrossRef]
- Ferrari, G.L.M.; Kovalskys, I.; Fisberg, M.; et al. Socio-demographic patterning of objectively measured physical activity and sedentary behaviours in eight Latin American countries: Findings from the ELANS study. Eur J Sport Sci. 2020 May 27;20(5):670–81. [CrossRef]
- Ferrari, G.L.M.; Kovalskys, I.; Fisberg, M.; et al. Methodological design for the assessment of physical activity and sedentary time in eight Latin American countries - The ELANS study. MethodsX. 2020;7:100843. [CrossRef]
- Slater, B.; Marchioni, D.L.; Fisberg, R.M. Estimando a prevalência da ingestão inadequada de nutrientes. Rev Saúde Pública. 2004;38(4). [CrossRef]
- Mendes, A.; Gavioli, L.; Previdelli, A.N.; et al. The diet quality index evaluates the adequacy of energy provided by dietary macronutrients. Revista de Nutrição. 2015 Aug;28(4):341–8. [CrossRef]
- Araujo, M.C.; Bezerra, I.N.; Barbosa, F.S.; et al. Consumo de macronutrientes e ingestão inadequada de micronutrientes em adultos. Rev Saude Publica. 2013 Feb;47(suppl 1):177s–89s. [CrossRef]
- Ley, S.H.; Hamdy, O.; Mohan, V.; et al. Prevention and management of type 2 diabetes: dietary components and nutritional strategies. The Lancet. 2014 Jun;383(9933):1999–2007. [CrossRef]
- Lutomski, J.E.; Van den Broeck, J.; Harrington, J.; et al. Sociodemographic, lifestyle, mental health and dietary factors associated with direction of misreporting of energy intake. Public Health Nutr. 2011 Mar 16;14(03):532–41. [CrossRef]
- Rippin, H.L.; Hutchinson, J.; Greenwood, D.C.; et al. Inequalities in education and national income are associated with poorer diet: Pooled analysis of individual participant data across 12 European countries. PLoS One. 2020 May 7;15(5):e0232447. [CrossRef]
- Gómez, G.; Kovalskys, I.; Leme, A.C.B.; et al. Socioeconomic Status Impact on Diet Quality and Body Mass Index in Eight Latin American Countries: ELANS Study Results. Nutrients. 2021 Jul 14;13(7):2404. [CrossRef]
- Shlisky, J.; Bloom, D.E.; Beaudreault, A.R.; et al. Nutritional Considerations for Healthy Aging and Reduction in Age-Related Chronic Disease. Advances in Nutrition. 2017 Jan 20;8(1):17.2-26. [CrossRef]
- Santos, P.V.F.; Sales, C.H.; Vieira, D.A.S.; et al. Family income per capita, age, and smoking status are predictors of low fiber intake in residents of São Paulo, Brazil. Nutrition Research. 2016 May;36(5):478–87. [CrossRef]
- Lu, L.; Li, X.; Lv, L.; et al. Associations between omega-3 fatty acids and insulin resistance and body composition in women with polycystic ovary syndrome. Front Nutr. 2022 Oct 5;9. [CrossRef]
- Carballo-Casla, A.; García-Esquinas, E.; Banegas, J.R.; et al. Fish consumption, omega-3 fatty acid intake, and risk of pain: the Seniors-ENRICA-1 cohort. Clinical Nutrition. 2022 Nov;41(11):2587–95. [CrossRef]
- Bhatt, D.L.; Steg, P.G.; Miller, M.; et al. Cardiovascular Risk Reduction with Icosapent Ethyl for Hypertriglyceridemia. New England Journal of Medicine. 2019 Jan 3;380(1):11–22. [CrossRef]
- Castelló, A.; Rodríguez-Barranco, M.; Fernández de Larrea, N.; et al. Adherence to the Western, Prudent and Mediterranean Dietary Patterns and Colorectal Cancer Risk: Findings from the Spanish Cohort of the European Prospective Investigation into Cancer and Nutrition (EPIC-Spain). Nutrients. 2022 Jul 27;14(15):3085. [CrossRef]
- Sisa, I.; Abeyá-Gilardon, E.; Fisberg, R.M.; et al. Impact of diet on CVD and diabetes mortality in Latin America and the Caribbean: a comparative risk assessment analysis. Public Health Nutr. 2021 Jun 3;24(9):2577–91. [CrossRef]
- IBGE. Instituto Brasileiro de Geografia e Estatística. Pesquisa de orçamentos familiares 2017-2018: avaliação nutricional da disponibilidade domiciliar de alimentos no Brasil. Rio de Janeiro; 2020.
- Institute of Medicine (US) Committee to Review Dietary Reference Intakes for Vitamin D and Calcium; Ross AC TCYA et al. Dietary Reference Intakes for Calcium and Vitamin D. Washington; 2011.
- Martini, L.A.; Verly, E.; Marchioni, D.M.L.; et al. Prevalence and correlates of calcium and vitamin D status adequacy in adolescents, adults, and elderly from the Health Survey—São Paulo. Nutrition. 2013 Jun;29(6):845–50. [CrossRef]
- Fontanelli, M.M.; Sales, C.H.; Castro, M.A.; et al. Healthful grain foods consumption by São Paulo residents: a 12-year analysis and future trends. Public Health Nutr. 2021 Jul 1;24(10):2987–97. [CrossRef]
- Fontanelli, M.M.; Martinez-Arroyo, A.; Sales, C.H.; et al. Opportunities for diet quality improvement: the potential role of staple grain foods. Public Health Nutr. 2021 Dec 12;24(18):6145–56. [CrossRef]
- Steluti, J.; Selhub, J.; Paul, L.; et al. An overview of folate status in a population-based study from São Paulo, Brazil and the potential impact of 10 years of national folic acid fortification policy. Eur J Clin Nutr. 2017 Oct 10;71(10):1173–8. [CrossRef]
- Brazil. Ministry of Health of Brazil. Secretariat of Health Care. Primary Health Care Department. Dietary Guidelines for the Brazilian population. Brasília; 2015.
- The World Bank. https://data.worldbank.org/indicator/SP.RUR.TOTL.ZS?locations=BR. 2018. Rural population (% of total population) - Brazil.

| Total population (n=1812) | Male (n=828) | Female (n=984) | |||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Age strata (years) | Age strata (years) | Age strata (years) | |||||||||||||||||||
| 19 - 30 | 31 - 50 | 51 - 65 | 19 - 30 | 31 - 50 | 51 - 65 | 19 - 30 | 31 - 50 | 51 - 65 | |||||||||||||
| N | % | N | % | N | % | p-value | N | % | N | % | N | % | p-value | N | % | N | % | N | % | p-value | |
| 573 | 32.0 | 851 | 47.0 | 388 | 21.0 | 295 | 16.0 | 394 | 22.0 | 139 | 8.0 | 278 | 15.0 | 457 | 25.0 | 249 | 14.0 | ||||
| Education level | |||||||||||||||||||||
| None to middle school | 196 | 23.8 | 380 | 46.2 | 247 | 30.0 | <0.001 | 95 | 32.2 | 178 | 45.2 | 86 | 61.9 | <0.001 | 101 | 36.3 | 202 | 44.2 | 161 | 64.7 | <0.001 |
| High school | 345 | 60.2 | 372 | 43.7 | 104 | 26.8 | 185 | 62.7 | 172 | 43.7 | 38 | 27.3 | 160 | 57.6 | 200 | 43.8 | 66 | 26.5 | |||
| College/university degree | 32 | 5.6 | 99 | 11.6 | 37 | 9.5 | 15 | 5.1 | 44 | 11.2 | 15 | 10.8 | 17 | 6.1 | 55 | 12.0 | 22 | 8.8 | |||
| Socioeconomic status | |||||||||||||||||||||
| High | 44 | 7.7 | 78 | 9.2 | 31 | 8.0 | 0.003 | 26 | 8.8 | 33 | 8.4 | 13 | 9.4 | 0.099 | 18 | 6.5 | 45 | 9.9 | 18 | 7.2 | 0.033 |
| Middle | 269 | 47.0 | 402 | 47.2 | 143 | 36.9 | 157 | 53.2 | 200 | 50.8 | 55 | 39.6 | 112 | 40.3 | 202 | 44.2 | 88 | 35.3 | |||
| Low | 260 | 45.4 | 371 | 43.6 | 214 | 55.2 | 112 | 38.0 | 161 | 40.9 | 71 | 51.1 | 148 | 53.2 | 210 | 46.0 | 143 | 57.4 | |||
| Excess weight | |||||||||||||||||||||
| BMI <25 kg/m2 | 298 | 52.0 | 303 | 35.6 | 99 | 25.5 | <0.001 | 156 | 52.9 | 148 | 37.6 | 34 | 24.5 | <0.001 | 142 | 51.1 | 155 | 33.9 | 65 | 26.1 | <0.001 |
| BMI>=25 kg/m2 | 275 | 48.0 | 548 | 64.4 | 289 | 74.5 | 139 | 47.1 | 246 | 62.4 | 105 | 75.5 | 136 | 48.9 | 302 | 66.1 | 184 | 73.9 | |||
| PAL (IPAQ) | |||||||||||||||||||||
| Insufficiently active | 300 | 54.4 | 462 | 56.6 | 233 | 62.1 | 0.058 | 131 | 46.1 | 210 | 54.8 | 75 | 55.2 | 0.058 | 169 | 63.1 | 252 | 58.1 | 158 | 66.1 | 0.010 |
| Active | 252 | 45.7 | 355 | 43.5 | 142 | 37.9 | 153 | 53.9 | 173 | 45.2 | 61 | 44.9 | 99 | 36.9 | 182 | 41.9 | 81 | 33.9 | |||
| Supplement use | |||||||||||||||||||||
| No | 488 | 85.2 | 722 | 84.8 | 318 | 82.0 | 0.624 | 257 | 87.1 | 345 | 87.6 | 115 | 82.7 | 0.558 | 231 | 83.1 | 377 | 82.5 | 203 | 81.5 | 0.986 |
| Yes | 26 | 4.5 | 42 | 4.9 | 25 | 6.4 | 11 | 3.7 | 14 | 3.6 | 9 | 6.5 | 15 | 5.4 | 28 | 6.1 | 16 | 6.4 | |||
| Not informed | 59 | 10.3 | 87 | 10.2 | 45 | 11.6 | 27 | 9.2 | 35 | 8.9 | 15 | 10.8 | 32 | 11.5 | 52 | 11.4 | 30 | 12.1 | |||
| Nutrient intake | Total population (n=1812) | K-Wallis | Male (n=828) | Female (n=984) | K-Wallis | ||||||||||||
| Mean | SD | P25 | P50 | P75 | p-value* | Mean | SD | P25 | P50 | P75 | Mean | SD | P25 | P50 | P75 | p value** | |
| Energy (kcal) | |||||||||||||||||
| 19 - 30 years | 1978 | 623 | 1564 | 1888 | 2275 | <0.001 a,b,c | 2252 | 651 | 1824 | 2162 | 2523 | 1687 | 430 | 1366 | 1691 | 1921 | <0.001 e,f,h,i,j,k,l |
| 31 - 50 years | 1830 | 576 | 1417 | 1753 | 2151 | 2088 | 594 | 1690 | 2034 | 2416 | 1609 | 458 | 1278 | 1564 | 1866 | ||
| 51 - 65 years | 1566 | 464 | 1230 | 1511 | 1844 | 1827 | 474 | 1493 | 1810 | 2077 | 1420 | 389 | 1147 | 1341 | 1648 | ||
| Carbohydrates (% EI) | |||||||||||||||||
| 19 - 30 years | 50.78 | 6.65 | 46.76 | 51.16 | 55.05 | 0.103 | 49.89 | 6.71 | 45.19 | 49.94 | 54.54 | 51.72 | 6.46 | 47.98 | 52.01 | 55.91 | <0.001j,k,l |
| 31 - 50 years | 50.13 | 6.61 | 45.76 | 50.29 | 54.71 | 49.30 | 6.76 | 44.81 | 49.62 | 53.67 | 50.84 | 6.4 | 46.59 | 50.67 | 55.33 | ||
| 51 - 65 years | 50.35 | 7.25 | 46.06 | 50.81 | 54.79 | 48.64 | 6.82 | 44.27 | 48.96 | 53.21 | 51.30 | 7.31 | 46.98 | 51.64 | 56.14 | ||
| Proteins (% EI) | |||||||||||||||||
| 19 - 30 years | 17.26 | 3.31 | 15.09 | 16.97 | 19.15 | 0.001 b,c | 17.58 | 3.42 | 15.38 | 17.11 | 19.6 | 16.92 | 3.15 | 14.9 | 16.77 | 18.7 | <0.001 e,f |
| 31 - 50 years | 17.53 | 3.37 | 15.18 | 17.21 | 19.46 | 17.51 | 3.33 | 15.35 | 17.21 | 19.58 | 17.54 | 3.41 | 15.11 | 17.21 | 19.32 | ||
| 51 - 65 years | 18.11 | 3.54 | 15.72 | 17.81 | 19.92 | 18.64 | 3.57 | 16.37 | 18.61 | 20.28 | 17.82 | 3.5 | 15.45 | 17.31 | 19.69 | ||
| Total fats (% EI) | |||||||||||||||||
| 19 - 30 years | 30.18 | 4.91 | 27.32 | 30.08 | 33.37 | 0.383 | 29.89 | 4.78 | 27.22 | 30.02 | 33.22 | 30.48 | 5.03 | 27.37 | 30.38 | 33.6 | 0.006 k |
| 31 - 50 years | 29.8 | 5.25 | 26.74 | 30.05 | 33.12 | 28.99 | 5.46 | 25.92 | 29.47 | 32.68 | 30.5 | 4.96 | 27.46 | 30.45 | 33.81 | ||
| 51 - 65 years | 29.7 | 5.38 | 26.43 | 29.83 | 33.31 | 29.3 | 5.25 | 25.94 | 29.71 | 32.88 | 29.93 | 5.46 | 26.7 | 30.25 | 33.54 | ||
| Saturated fats (% EI) | |||||||||||||||||
| 19 - 30 years | 9.95 | 1.99 | 8.69 | 9.9 | 11.33 | 0.274 | 9.85 | 1.9 | 8.62 | 9.93 | 11.25 | 10.06 | 2.07 | 8.75 | 9.87 | 11.55 | 0.003 k |
| 31 - 50 years | 9.84 | 2.13 | 8.47 | 9.7 | 11.23 | 9.57 | 2.22 | 8.16 | 9.47 | 10.91 | 10.08 | 2.03 | 8.73 | 9.9 | 11.39 | ||
| 51 - 65 years | 9.81 | 2.17 | 8.35 | 9.8 | 11.1 | 9.58 | 2.05 | 8.25 | 9.58 | 10.93 | 9.93 | 2.23 | 8.53 | 9.94 | 11.27 | ||
| Unsaturated fats (% EI) | |||||||||||||||||
| 19 - 30 years | 7.61 | 1.87 | 6.27 | 7.52 | 8.76 | 0.319 | 7.46 | 1.82 | 6.19 | 7.5 | 8.51 | 7.77 | 1.92 | 6.47 | 7.57 | 8.94 | 0.093 |
| 31 - 50 years | 7.45 | 1.86 | 6.31 | 7.39 | 8.47 | 7.26 | 1.82 | 6.13 | 7.33 | 8.36 | 7.61 | 1.87 | 6.47 | 7.4 | 8.68 | ||
| 51 - 65 years | 7.41 | 1.79 | 6.26 | 7.31 | 8.43 | 7.31 | 1.65 | 6.19 | 7.39 | 8.26 | 7.47 | 1.86 | 6.27 | 7.31 | 8.62 | ||
| EPA (mg) | |||||||||||||||||
| 19 - 30 years | 11.81 | 8.42 | 7.51 | 10.5 | 13.32 | <0.001 a,b | 10.98 | 7.19 | 7.18 | 9.56 | 13.02 | 12.68 | 9.49 | 8.58 | 11.27 | 13.64 | <0.001 e,j,k |
| 31 - 50 years | 12.8 | 8.22 | 8.34 | 11.08 | 14.57 | 12.19 | 8.51 | 7.9 | 10.31 | 13.75 | 13.32 | 7.94 | 9.21 | 11.74 | 15.27 | ||
| 51 - 65 years | 13.49 | 10.73 | 8.55 | 11.58 | 14.67 | 12.93 | 8.31 | 8.47 | 11.06 | 14.7 | 13.8 | 11.87 | 8.96 | 11.92 | 14.67 | ||
| DHA (mg) | |||||||||||||||||
| 19 - 30 years | 48.16 | 33.58 | 29.41 | 40.23 | 54.51 | 0.187 | 49.46 | 37.06 | 29.41 | 40.69 | 55.86 | 46.79 | 29.43 | 29.28 | 39.19 | 54.1 | 0.550 |
| 31 - 50 years | 51.05 | 36.38 | 29.81 | 40.93 | 58.58 | 51.72 | 36.33 | 30.02 | 41.1 | 58.63 | 50.48 | 36.46 | 29.71 | 40.62 | 57.73 | ||
| 51 - 65 years | 50.4 | 39.84 | 28.28 | 39.26 | 57.41 | 52.03 | 35.75 | 26.2 | 38.68 | 64.18 | 49.49 | 42 | 29.25 | 39.31 | 53.35 | ||
| Nutrient | Total population (n=1812) | Male (n=828) | Female (n=984) | ||||||
|---|---|---|---|---|---|---|---|---|---|
| n | % | p-value | n | % | p-value | n | % | p-value | |
| Total fiber (g) | < 25g/day | < 25g/day | < 25g/day | ||||||
| Total - 19 - 65 years | 1,508 | 83.22 | 580 | 70.05 | 928 | 94.31 | |||
| 19 - 30 years | 463 | 80.8 | 0.062 | 197 | 66.78 | 0.170 | 266 | 95.68 | 0.354 |
| 31 - 50 years | 709 | 83.31 | 278 | 70.56 | 431 | 94.31 | |||
| 51 - 65 years | 336 | 86.6 | 105 | 75.54 | 231 | 92.77 | |||
| Added sugar (% EI) | > 10% of EI | > 10% of EI | > 10% of EI | ||||||
| Total - 19 - 65 years | 1,121 | 61.87 | 453 | 54.71 | 668 | 67.89 | |||
| 19 - 30 years | 404 | 70.51 | p<0.001 | 184 | 62.37 | p<0.001 | 220 | 79.14 | p<0.001 |
| 31 - 50 years | 523 | 61.46 | 212 | 53.81 | 311 | 68.05 | |||
| 51 - 65 years | 194 | 50 | 57 | 41.01 | 137 | 55.02 | |||
| Saturated fat (%EI) | > 10% of EI | > 10% of EI | > 10% of EI | ||||||
| Total - 19 - 65 years | 814 | 44.92 | 346 | 41.79 | 468 | 47.56 | |||
| 19 - 30 years | 273 | 47.64 | 0.225 | 143 | 48.47 | 0.014 | 130 | 46.76 | 0.940 |
| 31 - 50 years | 366 | 43.01 | 148 | 37.56 | 218 | 47.7 | |||
| 51 - 65 years | 175 | 45.1 | 55 | 39.57 | 120 | 48.19 | |||
| Micronutrient | Brazil (n=1812) | Male (n=828) | Female (n=984) | |||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Mean | SD | Mean | SD | EAR | Inadequacy (%) | Mean | SD | EAR | Inadequacy (%) | |
| Vitamin A (mcg) | ||||||||||
| 19 - 30 years | 554.51 | 590.02 | 567.77 | 706.99 | 625 | 53.19% | 540.43 | 433.56 | 500 | 46.41% |
| 31 - 50 years | 547.55 | 459.15 | 557.57 | 497.32 | 625 | 55.57% | 538.91 | 423.85 | 500 | 46.41% |
| 51 - 65 years | 527.48 | 461.74 | 560.79 | 503.24 | 625 | 55.17% | 508.88 | 436.81 | 500 | 49.20% |
| Vitamin C (mg) | ||||||||||
| 19 - 30 years | 90.52 | 84.76 | 90.04 | 90.16 | 75 | 43.25% | 91.03 | 78.80 | 60 | 34.83% |
| 31 - 50 years | 91.56 | 79.72 | 90.19 | 84.13 | 75 | 42.86% | 92.74 | 75.78 | 60 | 33.36% |
| 51 - 65 years | 98.00 | 83.26 | 94.88 | 82.79 | 75 | 40.52% | 99.74 | 83.63 | 60 | 31.56% |
| Vitamin D (mcg) | ||||||||||
| 19 - 30 years | 3.54 | 2.16 | 3.79 | 2.27 | 10 | 99.69% | 3.28 | 2.00 | 10 | 99.88% |
| 31 - 50 years | 3.32 | 1.85 | 3.52 | 1.96 | 10 | 99.95% | 3.16 | 1.73 | 10 | 99.87% |
| 51 - 65 years | 3.12 | 1.73 | 3.24 | 1.72 | 10 | 99.99% | 3.05 | 1.73 | 10 | 99.46% |
| Vitamin E (mg) | ||||||||||
| 19 - 30 years | 7.40 | 2.73 | 8.03 | 2.86 | 12 | 91.77% | 6.72 | 2.43 | 12 | 98.50% |
| 31 - 50 years | 7.06 | 2.91 | 7.74 | 3.22 | 12 | 90.66% | 6.47 | 2.48 | 12 | 98.71% |
| 51 - 65 years | 6.55 | 2.61 | 7.41 | 3.09 | 12 | 93.06% | 6.07 | 2.15 | 12 | 99.70% |
| Thiamin (mg) | ||||||||||
| 19 - 30 years | 1.62 | 0.51 | 1.82 | 0.52 | 1.0 | 5.82% | 1.42 | 0.42 | 0.9 | 10.93% |
| 31 - 50 years | 1.60 | 0.57 | 1.78 | 0.58 | 1.0 | 9.01% | 1.45 | 0.52 | 0.9 | 14.23% |
| 51 - 65 years | 1.50 | 0.66 | 1.76 | 0.90 | 1.0 | 19.77% | 1.36 | 0.41 | 0.9 | 13.14% |
| Riboflavin (mg) | ||||||||||
| 19 - 30 years | 1.38 | 0.47 | 1.52 | 0.50 | 1.1 | 19.77% | 1.23 | 0.39 | 0.9 | 20.05% |
| 31 - 50 years | 1.30 | 0.45 | 1.43 | 0.47 | 1.1 | 24.20% | 1.18 | 0.39 | 0.9 | 23.27% |
| 51 - 65 years | 1.17 | 0.37 | 1.33 | 0.41 | 1.1 | 28.77% | 1.08 | 0.32 | 0.9 | 28.43% |
| Pyridoxine (mg) | ||||||||||
| 19 - 30 years | 1.74 | 0.72 | 2.01 | 0.80 | 1.1 | 12.17% | 1.46 | 0.47 | 1.1 | 22.06% |
| 31 - 50 years | 1.67 | 0.70 | 1.95 | 0.78 | 1.1 | 13.79% | 1.43 | 0.50 | 1.1 | 25.14% |
| 51 - 65 years | 1.49 | 0.65 | 1.80 | 0.82 | 1.4 | 31.21% | 1.32 | 0.45 | 1.3 | 48.40% |
| Vitamin B12 (mcg) | ||||||||||
| 19 - 30 years | 4.41 | 2.38 | 4.97 | 2.57 | 2.0 | 12.30% | 3.82 | 2.01 | 2.0 | 18.14% |
| 31 - 50 years | 4.26 | 2.34 | 4.76 | 2.58 | 2.0 | 14.23% | 3.83 | 2.01 | 2.0 | 18.14% |
| 51 - 65 years | 3.87 | 1.63 | 4.71 | 1.95 | 2.0 | 8.23% | 3.41 | 1.19 | 2.0 | 11.70% |
| Choline* | Prob. Adeq. (%) | Prob. Adeq. (%) | ||||||||
| 19 - 30 years | 337.85 | 123.23 | 387.9 | 132.47 | 550* | 10.51% | 284.74 | 85.042 | 425* | 6.12% |
| 31 - 50 years | 325.45 | 113.15 | 370.34 | 118.32 | 550* | 6.60% | 286.75 | 92.497 | 425* | 6.78% |
| 51 - 65 years | 295.85 | 98.167 | 351.12 | 107.99 | 550* | 2.28% | 265 | 76.691 | 425* | 4.02% |
| Micronutrient | Brazil (n=1812) | Male (n=828) | Female (n=984) | |||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Mean | SD | Mean | SD | EAR | Inadequacy (%) | Mean | SD | EAR | Inadequacy (%) | |
| Calcium (mg) | ||||||||||
| 19 - 30 years | 470.80 | 244.02 | 509.13 | 265.31 | 800 | 86.42% | 430.12 | 212.21 | 800 | 95.91% |
| 31 - 50 years | 451.66 | 239.22 | 463.56 | 219.30 | 800 | 93.70% | 441.40 | 254.94 | 800 | 92.07% |
| 51 - 65 years | 424.57 | 204.40 | 454.31 | 213.32 | 800 | 95.73% | 407.98 | 197.75 | 1000 | 99.86% |
| Iron (mg) | ||||||||||
| 19 - 30 years | 12.36 | 4.18 | 14.20 | 4.18 | 6.0 | 2.50% | 10.40 | 3.17 | 8.10 | 23.27% |
| 31 - 50 years | 11.36 | 4.11 | 13.22 | 4.38 | 6.0 | 4.95% | 9.75 | 3.05 | 8.10 | 29.46% |
| 51 - 65 years | 9.98 | 3.27 | 11.77 | 3.02 | 6.0 | 2.81% | 8.98 | 2.97 | 5.00 | 9.01% |
| Magnesium (mg) | ||||||||||
| 19 - 30 years | 216.45 | 71.79 | 246.95 | 77.02 | 330 | 85.99% | 184.09 | 48.01 | 255 | 93.06% |
| 31 - 50 years | 211.69 | 69.51 | 240.75 | 73.45 | 350 | 93.19% | 186.64 | 54.77 | 265 | 92.36% |
| 51 - 65 years | 199.76 | 62.56 | 228.55 | 65.74 | 350 | 96.78% | 183.69 | 54.58 | 265 | 93.19% |
| Zinc (mg) | ||||||||||
| 19 - 30 years | 12.40 | 5.33 | 14.53 | 6.04 | 9.4 | 19.77% | 10.13 | 3.15 | 6.8 | 14.46% |
| 31 - 50 years | 11.51 | 4.48 | 13.29 | 4.87 | 9.4 | 21.19% | 9.97 | 3.43 | 6.8 | 17.88% |
| 51 - 65 years | 10.41 | 4.05 | 12.29 | 3.95 | 9.4 | 23.27% | 9.36 | 3.71 | 6.8 | 24.51% |
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