Latin American consumption of major food groups: Results from the ELANS study


Autoři: Irina Kovalskys aff001;  Attilio Rigotti aff003;  Berthold Koletzko aff004;  Mauro Fisberg aff005;  Georgina Gómez aff007;  Marianella Herrera-Cuenca aff008;  Lilia Yadira Cortés Sanabria aff009;  Martha Cecilia Yépez García aff010;  Rossina G. Pareja aff011;  Ioná Zalcman Zimberg aff012;  Ana Del Arco aff006;  Luciana Zonis aff001;  Agatha Nogueira Previdelli aff013;  Viviana Guajardo aff001;  Luis A. Moreno aff014;  Regina Fisberg aff016
Působiště autorů: Nutrition, Health and Wellbeing Area, International Life Science Institute (ILSI-Argentina), Buenos Aires, Argentina aff001;  Pontifica Universidad Catolica Argentina Facultad de Medicina, Buenos Aires, Argentina aff002;  Departamento de Nutrición, Diabetes y Metabolismo, Centro de Nutrición Molecular y Enfermedades Crónicas, Escuela de Medicina, Pontificia Universidad Católica, Santiago, Chile aff003;  Ludwig-Maximilians-Universität Munich, Division of Metabolic and Nutritional Medicine, Dr. von Hauner Children's Hospital, University of Munich Medical Center, Munich, Germany aff004;  Instituto Pensi, Fundação Jose Luiz Egydio Setubal, Hospital Infantil Sabara, São Paulo, Brazil aff005;  Departamento de Pediatria, Universidade Federal de São Paulo, São Paulo, Brazil aff006;  Departamento de Bioquímica, Escuela de Medicina, Universidad de Costa Rica, San José, Costa Rica aff007;  Centro de Estudios del Desarrollo, Universidad Central de Venezuela (CENDES-UCV)/Fundación Bengoa, Caracas, Venezuela aff008;  Departamento de Nutrición y Bioquímica, Pontificia Universidad Javeriana, Bogotá, Colombia aff009;  Colegio de Ciencias de la Salud, Universidad San Francisco de Quito, Quito, Ecuador aff010;  Instituto de Investigación Nutricional, Lima, Peru aff011;  Departamento de Psicobiologia, Universidade Federal de São Paulo, São Paulo, Brazil aff012;  Faculdade de Ciências Biológicas e da Saúde, Universidade São Judas Tadeu, São Paulo, Brazil aff013;  Instituto de Investigación Sanitaria Aragón (IIS Aragón), Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y Nutrición (CIBERObn), University of Zaragoza, Zaragoza, Spain aff014;  GENUD (Growth, Exercise, Nutrition and Development) Research Group, Instituto Agroalimentario de Aragón (IA2), University of Zaragoza, Zaragoza, Spain aff015;  Departmento de Nutrição, Faculdade de Saúde Pública, Universidade de São Paulo, São Paulo, Brazil aff016
Vyšlo v časopise: PLoS ONE 14(12)
Kategorie: Research Article
doi: 10.1371/journal.pone.0225101

Souhrn

Background

The Latin American (LA) region is still facing an ongoing epidemiological transition and shows a complex public health scenario regarding non-communicable diseases (NCDs). A healthy diet and consumption of specific food groups may decrease the risk of NCDs, however there is a lack of dietary intake data in LA countries.

Objective

Provide updated data on the dietary intake of key science-based selected food groups related to NCDs risk in LA countries.

Design

ELANS (Latin American Study of Nutrition and Health) is a multicenter cross-sectional study assessing food consumption from an urban sample between15 to 65 years old from 8 LA countries (Argentina, Brazil, Chile, Colombia, Costa Rica, Ecuador, Peru, and Venezuela). Two 24-HR were obtained from 9,218 individuals. The daily intake of 10 food groups related to NCDs risk (fruits; vegetables; legumes/beans; nuts and seeds; whole grains products; fish and seafood; yogurt; red meat; processed meats; sugar-sweetened beverages (ready-to-drink and homemade)) were assessed and compared to global recommendations.

Results

Only 7.2% of the overall sample reached WHO’s recommendation for fruits and vegetables consumption (400 grams per day). Regarding the dietary patterns related to a reduced risk of NCDs, among the overall sample legumes and fruits were the food groups with closer intake to the recommendation, although much lower than expected (13.1% and 11.5%, respectively). Less than 3.5% of the sample met the optimal consumption level of vegetables, nuts, whole grains, fish and yogurt. Largest country-dependent differences in average daily consumption were found for legumes, nuts, fish, and yogurt. Mean consumption of SSB showed large differences between countries.

Conclusion

Diet intake quality is deficient for nutrient-dense food groups, suggesting a higher risk for NCDs in the urban LA region in upcoming decades. These data provide relevant and up-to-date information to take urgent public health actions to improve consumption of critically foods in order to prevent NCDs.

Klíčová slova:

Argentina – Beverages – Food – Food consumption – Fruits – Latin American people – Meat – Peru


Zdroje

1. Kelly T, Yang W, Chen CS, Reynolds K, He J. Global burden of obesity in 2005 and projections to 2030. Int J Obes (Lond). 2008;32(9):1431–7. doi: 10.1038/ijo.2008.102 18607383.

2. Alwan A. Global status report on noncommunicable diseases 2010: World Health Organization; 2011.

3. Encuesta de Seguimiento al Consumo de Alimentos (ESCA). Caracas: Venezuela. Instituto Nacional de Estadística; 2014 2014//.

4. Schwingshackl L, Schwedhelm C, Hoffmann G, Lampousi AM, Knuppel S, Iqbal K, et al. Food groups and risk of all-cause mortality: a systematic review and meta-analysis of prospective studies. Am J Clin Nutr. 2017;105(6):1462–73. doi: 10.3945/ajcn.117.153148 28446499.

5. Bechthold A, Boeing H, Schwedhelm C, Hoffmann G, Knuppel S, Iqbal K, et al. Food groups and risk of coronary heart disease, stroke and heart failure: A systematic review and dose-response meta-analysis of prospective studies. Crit Rev Food Sci Nutr. 2017:1–20. doi: 10.1080/10408398.2017.1392288 29039970.

6. Micha R, Wallace SK, Mozaffarian D. Red and processed meat consumption and risk of incident coronary heart disease, stroke, and diabetes mellitus: a systematic review and meta-analysis. Circulation. 2010;121(21):2271–83. doi: 10.1161/CIRCULATIONAHA.109.924977 20479151; PubMed Central PMCID: PMC2885952.

7. Micha R, Khatibzadeh S, Shi P, Andrews KG, Engell RE, Mozaffarian D, et al. Global, regional and national consumption of major food groups in 1990 and 2010: a systematic analysis including 266 country-specific nutrition surveys worldwide. BMJ Open. 2015;5(9):e008705. doi: 10.1136/bmjopen-2015-008705 26408285; PubMed Central PMCID: PMC4593162.

8. Micha R, Shulkin ML, Penalvo JL, Khatibzadeh S, Singh GM, Rao M, et al. Etiologic effects and optimal intakes of foods and nutrients for risk of cardiovascular diseases and diabetes: Systematic reviews and meta-analyses from the Nutrition and Chronic Diseases Expert Group (NutriCoDE). PLoS One. 2017;12(4):e0175149. doi: 10.1371/journal.pone.0175149 28448503; PubMed Central PMCID: PMC5407851.

9. McRae MP. Health Benefits of Dietary Whole Grains: An Umbrella Review of Meta-analyses. J Chiropr Med. 2017;16(1):10–8. doi: 10.1016/j.jcm.2016.08.008 28228693; PubMed Central PMCID: PMC5310957.

10. Wu L, Sun D. Consumption of Yogurt and the Incident Risk of Cardiovascular Disease: A Meta-Analysis of Nine Cohort Studies. Nutrients. 2017;9(3). doi: 10.3390/nu9030315 28327514; PubMed Central PMCID: PMC5372978.

11. Benisi-Kohansal S, Saneei P, Salehi-Marzijarani M, Larijani B, Esmaillzadeh A. Whole-Grain Intake and Mortality from All Causes, Cardiovascular Disease, and Cancer: A Systematic Review and Dose-Response Meta-Analysis of Prospective Cohort Studies. Adv Nutr. 2016;7(6):1052–65. doi: 10.3945/an.115.011635 28140323; PubMed Central PMCID: PMC5105035.

12. Imamura F, O'Connor L, Ye Z, Mursu J, Hayashino Y, Bhupathiraju SN, et al. Consumption of sugar sweetened beverages, artificially sweetened beverages, and fruit juice and incidence of type 2 diabetes: systematic review, meta-analysis, and estimation of population attributable fraction. Br J Sports Med. 2016;50(8):496–504. doi: 10.1136/bjsports-2016-h3576rep 27044603; PubMed Central PMCID: PMC4853528.

13. Li B, Zhang G, Tan M, Zhao L, Jin L, Tang X, et al. Consumption of whole grains in relation to mortality from all causes, cardiovascular disease, and diabetes: Dose-response meta-analysis of prospective cohort studies. Medicine (Baltimore). 2016;95(33):e4229. doi: 10.1097/MD.0000000000004229 27537552; PubMed Central PMCID: PMC5370779.

14. O'Connor LE, Kim JE, Campbell WW. Total red meat intake of >/ = 0.5 servings/d does not negatively influence cardiovascular disease risk factors: a systemically searched meta-analysis of randomized controlled trials. Am J Clin Nutr. 2017;105(1):57–69. doi: 10.3945/ajcn.116.142521 27881394; PubMed Central PMCID: PMC5183733.

15. Zong G, Gao A, Hu FB, Sun Q. Whole Grain Intake and Mortality From All Causes, Cardiovascular Disease, and Cancer: A Meta-Analysis of Prospective Cohort Studies. Circulation. 2016;133(24):2370–80. doi: 10.1161/CIRCULATIONAHA.115.021101 27297341; PubMed Central PMCID: PMC4910651.

16. Wang X, Lin X, Ouyang YY, Liu J, Zhao G, Pan A, et al. Red and processed meat consumption and mortality: dose-response meta-analysis of prospective cohort studies. Public Health Nutr. 2016;19(5):893–905. doi: 10.1017/S1368980015002062 26143683.

17. Xi B, Huang Y, Reilly KH, Li S, Zheng R, Barrio-Lopez MT, et al. Sugar-sweetened beverages and risk of hypertension and CVD: a dose-response meta-analysis. Br J Nutr. 2015;113(5):709–17. doi: 10.1017/S0007114514004383 25735740.

18. Abete I, Romaguera D, Vieira AR, Lopez de Munain A, Norat T. Association between total, processed, red and white meat consumption and all-cause, CVD and IHD mortality: a meta-analysis of cohort studies. Br J Nutr. 2014;112(5):762–75. doi: 10.1017/S000711451400124X 24932617.

19. Greenwood DC, Threapleton DE, Evans CE, Cleghorn CL, Nykjaer C, Woodhead C, et al. Association between sugar-sweetened and artificially sweetened soft drinks and type 2 diabetes: systematic review and dose-response meta-analysis of prospective studies. Br J Nutr. 2014;112(5):725–34. doi: 10.1017/S0007114514001329 24932880.

20. Leung Yinko SS, Stark KD, Thanassoulis G, Pilote L. Fish consumption and acute coronary syndrome: a meta-analysis. Am J Med. 2014;127(9):848–57 e2. doi: 10.1016/j.amjmed.2014.04.016 24802020.

21. Mortality GBD, Causes of Death C. Global, regional, and national age-sex specific all-cause and cause-specific mortality for 240 causes of death, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet. 2015;385(9963):117–71. doi: 10.1016/S0140-6736(14)61682-2 25530442; PubMed Central PMCID: PMC4340604.

22. Li YH, Zhou CH, Pei HJ, Zhou XL, Li LH, Wu YJ, et al. Fish consumption and incidence of heart failure: a meta-analysis of prospective cohort studies. Chin Med J (Engl). 2013;126(5):942–8. 23489806.

23. Lim SS, Vos T, Flaxman AD, Danaei G, Shibuya K, Adair-Rohani H, et al. A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012;380(9859):2224–60. doi: 10.1016/S0140-6736(12)61766-8 23245609; PubMed Central PMCID: PMC4156511.

24. Corvalan C, Garmendia ML, Jones-Smith J, Lutter CK, Miranda JJ, Pedraza LS, et al. Nutrition status of children in Latin America. Obes Rev. 2017;18 Suppl 2:7–18. doi: 10.1111/obr.12571 28741907; PubMed Central PMCID: PMC5601284.

25. Galicia L, Grajeda R, de Romana DL. Nutrition situation in Latin America and the Caribbean: current scenario, past trends, and data gaps. Rev Panam Salud Publica. 2016;40(2):104–13. 27982368.

26. Galicia L, de Romana DL, Harding KB, De-Regil LM, Grajeda R. Tackling malnutrition in Latin America and the Caribbean: challenges and opportunities. Rev Panam Salud Publica. 2016;40(2):138–46. 27982371.

27. Lopez-Jaramillo P, Gomez-Arbelaez D, Sotomayor-Rubio A, Mantilla-Garcia D, Lopez-Lopez J. Maternal undernutrition and cardiometabolic disease: a Latin American perspective. BMC Med. 2015;13:41. doi: 10.1186/s12916-015-0293-8 25858591; PubMed Central PMCID: PMC4346113.

28. Rivera JA, de Cossio TG, Pedraza LS, Aburto TC, Sanchez TG, Martorell R. Childhood and adolescent overweight and obesity in Latin America: a systematic review. Lancet Diabetes Endocrinol. 2014;2(4):321–32. doi: 10.1016/S2213-8587(13)70173-6 24703050.

29. Rivera JA, Pedraza LS, Martorell R, Gil A. Introduction to the double burden of undernutrition and excess weight in Latin America. Am J Clin Nutr. 2014;100(6):1613S–6S. doi: 10.3945/ajcn.114.084806 25411302.

30. Popkin BM, Adair LS, Ng SW. Global nutrition transition and the pandemic of obesity in developing countries. Nutr Rev. 2012;70(1):3–21. doi: 10.1111/j.1753-4887.2011.00456.x 22221213; PubMed Central PMCID: PMC3257829.

31. Fisberg M, Kovalskys I, Gomez G, Rigotti A, Cortes LY, Herrera-Cuenca M, et al. Latin American Study of Nutrition and Health (ELANS): rationale and study design. BMC Public Health. 2016;16:93. doi: 10.1186/s12889-016-2765-y 26829928; PubMed Central PMCID: PMC4736497.

32. Kovalskys I, Fisberg M, Gomez G, Rigotti A, Cortes LY, Yepez MC, et al. Standardization of the Food Composition Database Used in the Latin American Nutrition and Health Study (ELANS). Nutrients. 2015;7(9):7914–24. doi: 10.3390/nu7095373 26389952; PubMed Central PMCID: PMC4586568.

33. 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. doi: 10.1093/ajcn/88.2.324 18689367.

34. Harttig U, Haubrock J, Knuppel S, Boeing H, Consortium E. The MSM program: web-based statistics package for estimating usual dietary intake using the Multiple Source Method. Eur J Clin Nutr. 2011;65 Suppl 1:S87–91. Epub 2011/07/16. doi: 10.1038/ejcn.2011.92 21731011.

35. USDA. Center for Nutrition Policy and Promotion. Food Guide Pyramid. A guide to daily food choices. Home and Garden Bulletin, Number 52. 1992.

36. Schwingshackl L, Hoffmann G, Lampousi AM, Knuppel S, Iqbal K, Schwedhelm C, et al. Food groups and risk of type 2 diabetes mellitus: a systematic review and meta-analysis of prospective studies. Eur J Epidemiol. 2017;32(5):363–75. doi: 10.1007/s10654-017-0246-y 28397016; PubMed Central PMCID: PMC5506108.

37. Gholami F, Khoramdad M, Esmailnasab N, Moradi G, Nouri B, Safiri S, et al. The effect of dairy consumption on the prevention of cardiovascular diseases: A meta-analysis of prospective studies. J Cardiovasc Thorac Res. 2017;9(1):1–11. doi: 10.15171/jcvtr.2017.01 28451082; PubMed Central PMCID: PMC5402021.

38. Guo J, Astrup A, Lovegrove JA, Gijsbers L, Givens DI, Soedamah-Muthu SS. Milk and dairy consumption and risk of cardiovascular diseases and all-cause mortality: dose-response meta-analysis of prospective cohort studies. Eur J Epidemiol. 2017;32(4):269–87. doi: 10.1007/s10654-017-0243-1 28374228; PubMed Central PMCID: PMC5437143.

39. Aune D, Keum N, Giovannucci E, Fadnes LT, Boffetta P, Greenwood DC, et al. Nut consumption and risk of cardiovascular disease, total cancer, all-cause and cause-specific mortality: a systematic review and dose-response meta-analysis of prospective studies. BMC Med. 2016;14(1):207. doi: 10.1186/s12916-016-0730-3 27916000; PubMed Central PMCID: PMC5137221.

40. Aune D, Keum N, Giovannucci E, Fadnes LT, Boffetta P, Greenwood DC, et al. Whole grain consumption and risk of cardiovascular disease, cancer, and all cause and cause specific mortality: systematic review and dose-response meta-analysis of prospective studies. BMJ. 2016;353:i2716. doi: 10.1136/bmj.i2716 27301975; PubMed Central PMCID: PMC4908315.

41. Aune D, Giovannucci E, Boffetta P, Fadnes LT, Keum N, Norat T, et al. Fruit and vegetable intake and the risk of cardiovascular disease, total cancer and all-cause mortality-a systematic review and dose-response meta-analysis of prospective studies. Int J Epidemiol. 2017;46(3):1029–56. doi: 10.1093/ije/dyw319 28338764.

42. Alexander DD, Bylsma LC, Vargas AJ, Cohen SS, Doucette A, Mohamed M, et al. Dairy consumption and CVD: a systematic review and meta-analysis. Br J Nutr. 2016;115(4):737–50. doi: 10.1017/S0007114515005000 26786887.

43. Qin LQ, Xu JY, Han SF, Zhang ZL, Zhao YY, Szeto IM. Dairy consumption and risk of cardiovascular disease: an updated meta-analysis of prospective cohort studies. Asia Pac J Clin Nutr. 2015;24(1):90–100. doi: 10.6133/apjcn.2015.24.1.09 25740747.

44. Zhan J, Liu YJ, Cai LB, Xu FR, Xie T, He QQ. Fruit and vegetable consumption and risk of cardiovascular disease: A meta-analysis of prospective cohort studies. Crit Rev Food Sci Nutr. 2017;57(8):1650–63. doi: 10.1080/10408398.2015.1008980 26114864.

45. Afshin A, Micha R, Khatibzadeh S, Mozaffarian D. Consumption of nuts and legumes and risk of incident ischemic heart disease, stroke, and diabetes: a systematic review and meta-analysis. Am J Clin Nutr. 2014;100(1):278–88. doi: 10.3945/ajcn.113.076901 24898241; PubMed Central PMCID: PMC4144102.

46. Joint WHO/FAO Expert Consultation on Diet NatPoCD. Diet, nutrition and the prevention of chronic diseases: report of a joint WHO/FAO expert consultation. Geneva2003.

47. Moore LV, Thompson FE. Adults Meeting Fruit and Vegetable Intake Recommendations—United States, 2013. MMWR Morb Mortal Wkly Rep. 2015;64(26):709–13. 26158351; PubMed Central PMCID: PMC4584842.

48. Guenther PM, Reedy J, Krebs-Smith SM. Development of the Healthy Eating Index-2005. J Am Diet Assoc. 2008;108(11):1896–901. Epub 2008/10/29. doi: 10.1016/j.jada.2008.08.016 18954580.

49. Mensink GB, Truthmann J, Rabenberg M, Heidemann C, Haftenberger M, Schienkiewitz A, et al. [Fruit and vegetable intake in Germany: results of the German Health Interview and Examination Survey for Adults (DEGS1)]. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz. 2013;56(5–6):779–85. doi: 10.1007/s00103-012-1651-8 23703498.

50. Fruit and vegetable consumption, 2016. Health Reports. Statistics Canada Catalogue no. 82-625-X. September 2017.

51. Landais E, Bour A, Gartner A, McCullough F, Delpeuch F, Holdsworth M. Socio-economic and behavioural determinants of fruit and vegetable intake in Moroccan women. Public Health Nutr. 2015;18(5):809–16. doi: 10.1017/S1368980014001761 25166305.

52. Pessoa MC, Mendes LL, Gomes CS, Martins PA, Velasquez-Melendez G. Food environment and fruit and vegetable intake in a urban population: a multilevel analysis. BMC Public Health. 2015;15:1012. doi: 10.1186/s12889-015-2277-1 26437719; PubMed Central PMCID: PMC4595198.

53. Mackenbach JD, Brage S, Forouhi NG, Griffin SJ, Wareham NJ, Monsivais P. Does the importance of dietary costs for fruit and vegetable intake vary by socioeconomic position? Br J Nutr. 2015;114(9):1464–70. doi: 10.1017/S0007114515003025 26353803; PubMed Central PMCID: PMC4657115.

54. Brown RC, Tey SL, Gray AR, Chisholm A, Smith C, Fleming E, et al. Patterns and predictors of nut consumption: results from the 2008/09 New Zealand Adult Nutrition Survey. Br J Nutr. 2014;112(12):2028–40. doi: 10.1017/S0007114514003158 25354462.

55. Nielsen SJ, Kit BK, Ogden CL. Nut consumption among U.S. adults, 2009–2010. NCHS Data Brief. 2014;(176):1–8. 25519884.

56. Relja A, Miljkovic A, Gelemanovic A, Boskovic M, Hayward C, Polasek O, et al. Nut Consumption and Cardiovascular Risk Factors: A Cross-Sectional Study in a Mediterranean Population. Nutrients. 2017;9(12). doi: 10.3390/nu9121296 29182576; PubMed Central PMCID: PMC5748747.

57. Panahi S, Fernandez MA, Marette A, Tremblay A. Yogurt, diet quality and lifestyle factors. Eur J Clin Nutr. 2017;71(5):573–9. doi: 10.1038/ejcn.2016.214 27804959.

58. Astrup A. Yogurt and dairy product consumption to prevent cardiometabolic diseases: epidemiologic and experimental studies. Am J Clin Nutr. 2014;99(5 Suppl):1235S–42S. doi: 10.3945/ajcn.113.073015 24695891.

59. Fisberg M, Machado R. History of yogurt and current patterns of consumption. Nutr Rev. 2015;73 Suppl 1:4–7. doi: 10.1093/nutrit/nuv020 26175483.

60. Kovalskys I, Fisberg M, Gomez G, Pareja RG, Yepez Garcia MC, Cortes Sanabria LY, et al. Energy intake and food sources of eight Latin American countries: results from the Latin American Study of Nutrition and Health (ELANS). Public Health Nutr. 2018:1–13. Epub 2018/06/01. doi: 10.1017/S1368980018001222 29848396.

61. Aune D, Norat T, Romundstad P, Vatten LJ. Whole grain and refined grain consumption and the risk of type 2 diabetes: a systematic review and dose-response meta-analysis of cohort studies. Eur J Epidemiol. 2013;28(11):845–58. doi: 10.1007/s10654-013-9852-5 24158434.

62. Chanson-Rolle A, Meynier A, Aubin F, Lappi J, Poutanen K, Vinoy S, et al. Systematic Review and Meta-Analysis of Human Studies to Support a Quantitative Recommendation for Whole Grain Intake in Relation to Type 2 Diabetes. PLoS One. 2015;10(6):e0131377. doi: 10.1371/journal.pone.0131377 26098118; PubMed Central PMCID: PMC4476805.

63. Bellisle F, Hebel P, Colin J, Reye B, Hopkins S. Consumption of whole grains in French children, adolescents and adults. Br J Nutr. 2014;112(10):1674–84. doi: 10.1017/S0007114514002670 25300424; PubMed Central PMCID: PMC4234471.

64. Mann KD, Pearce MS, McKevith B, Thielecke F, Seal CJ. Whole grain intake and its association with intakes of other foods, nutrients and markers of health in the National Diet and Nutrition Survey rolling programme 2008–11. Br J Nutr. 2015;113(10):1595–602. doi: 10.1017/S0007114515000525 25893512; PubMed Central PMCID: PMC4462159.

65. Messina V. Nutritional and health benefits of dried beans. Am J Clin Nutr. 2014;100 Suppl 1:437S–42S. doi: 10.3945/ajcn.113.071472 24871476.

66. Engeset D, Braaten T, Teucher B, Kuhn T, Bueno-de-Mesquita HB, Leenders M, et al. Fish consumption and mortality in the European Prospective Investigation into Cancer and Nutrition cohort. Eur J Epidemiol. 2015;30(1):57–70. doi: 10.1007/s10654-014-9966-4 25377533; PubMed Central PMCID: PMC4356893.

67. Skuland SE. Healthy Eating and Barriers Related to Social Class. The case of vegetable and fish consumption in Norway. Appetite. 2015;92:217–26. doi: 10.1016/j.appet.2015.05.008 25982927.

68. Singh GM, Micha R, Khatibzadeh S, Lim S, Ezzati M, Mozaffarian D, et al. Estimated Global, Regional, and National Disease Burdens Related to Sugar-Sweetened Beverage Consumption in 2010. Circulation. 2015;132(8):639–66. doi: 10.1161/CIRCULATIONAHA.114.010636 26124185; PubMed Central PMCID: PMC4550496.

69. Park S, McGuire LC, Galuska DA. Regional Differences in Sugar-Sweetened Beverage Intake among US Adults. J Acad Nutr Diet. 2015;115(12):1996–2002. doi: 10.1016/j.jand.2015.06.010 26231057; PubMed Central PMCID: PMC4663103.

70. Fisberg M, Kovalskys I, Gomez G, Rigotti A, Sanabria LYC, Garcia MCY, et al. Total and Added Sugar Intake: Assessment in Eight Latin American Countries. Nutrients. 2018;10(4). Epub 2018/03/23. doi: 10.3390/nu10040389 29565308.

71. Popkin BM, Hawkes C. Sweetening of the global diet, particularly beverages: patterns, trends, and policy responses. Lancet Diabetes Endocrinol. 2016;4(2):174–86. doi: 10.1016/S2213-8587(15)00419-2 26654575; PubMed Central PMCID: PMC4733620.

72. Sanchez-Romero LM, Penko J, Coxson PG, Fernandez A, Mason A, Moran AE, et al. Projected Impact of Mexico's Sugar-Sweetened Beverage Tax Policy on Diabetes and Cardiovascular Disease: A Modeling Study. PLoS Med. 2016;13(11):e1002158. doi: 10.1371/journal.pmed.1002158 27802278; PubMed Central PMCID: PMC5089730.

73. Lanas F, Bazzano L, Rubinstein A, Calandrelli M, Chen CS, Elorriaga N, et al. Prevalence, Distributions and Determinants of Obesity and Central Obesity in the Southern Cone of America. PLoS One. 2016;11(10):e0163727. doi: 10.1371/journal.pone.0163727 27741247; PubMed Central PMCID: PMC5065193.

74. Duffey KJ, Poti J. Modeling the Effect of Replacing Sugar-Sweetened Beverage Consumption with Water on Energy Intake, HBI Score, and Obesity Prevalence. Nutrients. 2016;8(7). doi: 10.3390/nu8070395 27367719; PubMed Central PMCID: PMC4963871.

75. Kim E, Coelho D, Blachier F. Review of the association between meat consumption and risk of colorectal cancer. Nutr Res. 2013;33(12):983–94. doi: 10.1016/j.nutres.2013.07.018 24267037.

76. Rohrmann S, Linseisen J, Overvad K, Lund Wurtz AM, Roswall N, Tjonneland A, et al. Meat and fish consumption and the risk of renal cell carcinoma in the European prospective investigation into cancer and nutrition. Int J Cancer. 2015;136(5):E423–31. doi: 10.1002/ijc.29236 25258006.

77. Pan A, Sun Q, Bernstein AM, Manson JE, Willett WC, Hu FB. Changes in red meat consumption and subsequent risk of type 2 diabetes mellitus: three cohorts of US men and women. JAMA Intern Med. 2013;173(14):1328–35. doi: 10.1001/jamainternmed.2013.6633 23779232; PubMed Central PMCID: PMC3847817.

78. Michelozzi P, Lapucci E, Farchi S. [Meat consumption reduction policies: benefits for climate change mitigation and health]. Recenti Prog Med. 2015;106(8):354–7. doi: 10.1701/1960.21296 26228857.

79. Sharma S, Sheehy T, Kolonel LN. Contribution of meat to vitamin B(1)(2), iron and zinc intakes in five ethnic groups in the USA: implications for developing food-based dietary guidelines. J Hum Nutr Diet. 2013;26(2):156–68. doi: 10.1111/jhn.12035 23398393; PubMed Central PMCID: PMC5023012.

80. de Carvalho AM, Cesar CL, Fisberg RM, Marchioni DM. Meat consumption in Sao Paulo-Brazil: trend in the last decade. PLoS One. 2014;9(5):e96667. doi: 10.1371/journal.pone.0096667 24792240; PubMed Central PMCID: PMC4008596.

81. Daniel CR, Cross AJ, Koebnick C, Sinha R. Trends in meat consumption in the USA. Public Health Nutr. 2011;14(4):575–83. doi: 10.1017/S1368980010002077 21070685; PubMed Central PMCID: PMC3045642.

82. Domene SMÁ. Técnica Dietética: teoria e aplicações. Técnica dietética: teoria e aplicações2011.

83. Haubrock J, Nothlings U, Volatier JL, Dekkers A, Ocke M, Harttig U, et al. Estimating usual food intake distributions by using the multiple source method in the EPIC-Potsdam Calibration Study. J Nutr. 2011;141(5):914–20. doi: 10.3945/jn.109.120394 21430241.

84. Willett W. Nutritional epidemiology: Oxford University Press; 2012. doi: 10.1097/EDE.0b013e31825afb0b

85. Fisberg RM, Slater B, Marchioni DML, Martini LA. Inquéritos alimentares: métodos e bases científicos. 2005.

86. Rodrigues PRM, Souza RAGd, Cnop MLD, Monteiro LS, Coura CP, Brito AP, et al. Dietary quality varies according to data collection instrument: a comparison between a food frequency questionnaire and 24-hour recall. Cadernos de saude publica. 2016;32:e00047215. doi: 10.1590/0102-311X00047215 26910251

87. Avelino GF, Previdelli ÁN, de Castro MA, Marchioni DML, Fisberg RM. Sub-relato da ingestão energética e fatores associados em estudo de base populacional. Cad Saúde Pública. 2014;30(3):663–8. doi: 10.1590/0102-311x00073713 24714955

88. Conway JM, Ingwersen LA, Vinyard BT, Moshfegh AJ. Effectiveness of the US Department of Agriculture 5-step multiple-pass method in assessing food intake in obese and nonobese women. Am J Clin Nutr. 2003;77(5):1171–8. doi: 10.1093/ajcn/77.5.1171 12716668.

89. Pomerleau J, Lock K, Knai C, McKee M. Effectiveness of interventions and programmes promoting fruit and vegetable intake: WHO; 2005.

90. Guenther PM, Reedy J, Krebs-Smith SM, Reeve BB. Evaluation of the Healthy Eating Index-2005. J Am Diet Assoc. 2008;108(11):1854–64. Epub 2008/10/29. doi: 10.1016/j.jada.2008.08.011 18954575.

91. Tooze JA, Midthune D, Dodd KW, Freedman LS, Krebs-Smith SM, Subar AF, et al. A new statistical method for estimating the usual intake of episodically consumed foods with application to their distribution. J Am Diet Assoc. 2006;106(10):1575–87. Epub 2006/09/27. doi: 10.1016/j.jada.2006.07.003 17000190; PubMed Central PMCID: PMC2517157.

92. Harttig U, Haubrock J, Knüppel S, Boeing H. The MSM program: web-based statistics package for estimating usual dietary intake using the multiple source method. Eur J Clin Nutr. 2011;65. doi: 10.1038/ejcn.2011.92 21731011


Článek vyšel v časopise

PLOS One


2019 Číslo 12