Nutritional Epidemiological Study to Estimate Usual Intake and to Define Optimum Nutrient Profiling Choice in the Diet of Egyptian Youths — Oak Academic Publishing
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Nutritional Epidemiological Study to Estimate Usual Intake and to Define Optimum Nutrient Profiling Choice in the Diet of Egyptian Youths
Department of Biological Anthropology, National Research Centre, Giza, Egypt
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Department of Human Nutrition, National Research Centre, Giza, Egypt
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Department of Human Nutrition, National Research Centre, Giza, Egypt
,
Department of Human Nutrition, National Research Centre, Giza, Egypt
,
Department Information and Systems, National Research Centre, Giza, Egypt
1 Department of Biological Anthropology, National Research Centre, Giza, Egypt
2 Department of Human Nutrition, National Research Centre, Giza, Egypt
3 Department of Human Nutrition, National Research Centre, Giza, Egypt
4 Department of Human Nutrition, National Research Centre, Giza, Egypt
5 Department Information and Systems, National Research Centre, Giza, Egypt
Objectives: To define optimum food and nutrient profiling in gender-specific and age group-specific variant regression models. Setting: 481 subjects of both sexes (18.4 years old) from Giza urban were set. Design: Dietary assessment used the 24-h dietary recall data to calculate the estimated energy and (24) nutrients eaten by each individual. Four indices—food variety diversity score, healthy eating index (HEI), mean probability of nutrients adequacy (MPA) and nutrient rich food (NRF 9.3 ) index score were used for assessing the profiling of the diet. Results: A total of 163 individual food items were consumed by the participants within the 24-h dietary recall with an average daily intake of (6.6) different food varieties. Grains were the top contributors of energy and 10 macro and micro nutrients followed by the meat group. Based on the MPA data, the mean acceptable intake (AI) of dietary calcium (32.9%) and vitamin C (30%) were limiting in the diet. The diet profiling consumed by the teenagers aged 14.8 years was inferior compared to that consumed by subjects aging 23.9 years. Linear regression analyses were conducted between the 4 indices as the dependent variable and all possible combinations of 16 nutrients of interest as independent variables. NRF 9.3 was the optimum nutrient index and correlated negatively with markers of abdominal obesity. Conclusion: Implementation of nutrition intervention program was directed to youths to include age appropriate good healthy foods to decrease the risk of nutrient deficiencies.
KeywordsEgyptian YouthsHealthy Eating IndexMean Probability Nutrient AdequacyNutrient Rich Food IndexAnthropometric Measures of Health RiskCorrelations
Inman, D.D., van Bakergem, K.M., LaRosa, A.C. and Garr, D.R. (2011) Evidence-Based Health Promotion Programs for Schools and Communities. American Journal of Preventive Medicine, 40, 207-219. http://dx.doi.org/10.1016/j.amepre.2010.10.031
Verger, E.O., Mariotti, F., Holmes, B.A., Paineau, D. and Huneau, J.-F. (2012) Evaluation of a Diet Quality Index Based on the Probability of Adequate Nutrient Intake (PANDiet) Using National French and US Dietary Surveys. PLoS ONE, 7, e42155. http://dx.doi.org/10.1371/journal.pone.0042155
Drescher, L.S., Thiele, S. and Mensink, G.B.M. (2007) A New Index to Measure Healthy Food Diversity Better Reflects a Healthy Diet Than Traditional Measures. Journal of Nutrition, 137, 647-651.
Van Lee, L., Anouk, G., Eveline, J., Huysduynen, J., Pieter, V. and Edith, J. (2012) The Dutch Healthy Diet Index (DHD-Index): An Instrument to Measure Adherence to the Dutch Guidelines for a Healthy Diet. Journal of Nutritional Science, 2, e40. http://dx.doi.org/10.1017/jns.2013.28
Drake, I., Gullberg, B., Ericson, U., Sonestedt, E., Nilsson, J., Wallstrom, P., Hedblad, B. and Wirfalt, E. (2011) Development of a Diet Quality Index Assessing Adherence to the Swedish Nutrition Recommendations and Dietary Guidelines in the Malmo Diet and Cancer Cohort. Public Health Nutrition, 14, 835-845. http://dx.doi.org/10.1017/S1368980010003848
Wong, J.E., Parnell, W.R., Howe, A.S., Black, K.E. and Skidmore, P.M.L. (2013) Development and Validation of a Food-Based Diet Quality Index for New Zealand Adolescents. BMC Pubic Health, 13, 562. http://dx.doi.org/10.1186/1471-2458-13-562
Drewnowski, A. (2009) Defining Nutrient Density: Development and Validation of the Nutrient Rich Foods Index. Journal of the American College of Nutrition, 28, 421S-426S. http://dx.doi.org/10.1080/07315724.2009.10718106
Fulgoni, V.L., Keast, D.R. and Drewnowski, A. (2009) Development and Validation of the Nutrient-Rich Foods Index: A Tool to Measure Nutritional Quality of Foods. Journal of Nutrition, 139, 1549-1554. http://dx.doi.org/10.3945/jn.108.101360
Kennedy, G., Fanou-Fogny, N., Seghieri, C., Arimond, M., Koreissi, Y., Dossa, R., Kok, F.J. and Brouwer, I.D. (2010) Food Groups Associated with a Composite Measure of Probability of Adequate Intake of 11 Micronutrients in the Diets of Women in Urban Mali. Journal of Nutrition, 140, 2070S-2078S. http://dx.doi.org/10.3945/jn.110.123612
Arsenault, J.E., Fulgoni, V.L., Hersey, J.C. and Muth, M.K. (2012) A Novel Approach to Selecting and Weighting Nutrients for Nutrient Profiling of Foods and Diets. Journal of the Academy of Nutrition and Dietetics, 112, 1968-1975. http://dx.doi.org/10.1016/j.jand.2012.08.032
FAO/WHO (2003) Joint Expert Consultation. Diet, Nutrition and the Prevention of Chronic Diseases. A Joint FAO/WHO Consultation Meeting, WHO, Geneva.
Foote, J.A., Murphy, S.P., Wilkens, L.R., Basiotis, P.P. and Carlson, A. (2004) Dietary Variety Increases the Probability of Nutrient Adequacy among Adults. Journal of Nutrition, 134, 1779-1785.
Zienczuk, N., Young, T.K., Cao, Z.R. and Egeland, G.M. (2012) Dietary Correlates of an At-Risk BMI among Inuit Adults in the Canadian High Arctic: Cross-Sectional International Polar Year Inuit Health Survey, 2007-2008. Nutrition Journal, 11, 73. http://dx.doi.org/10.1186/1475-2891-11-73
Vartanian, L., Schwartz, M. and Brownell, K. (2007) Effects of Soft Drink Consumption on Nutrition and Health: A Systematic Review and Meta Analysis. American Journal of Public Health, 97, 667-75. http://dx.doi.org/10.2105/AJPH.2005.083782
Rangan, A.M., Schindeler, S., Hector, D.J., Gill, T.P. and Webb, K.L. (2009) Consumption of “Extra” Foods by Australian Adults: Types, Quantities and Contribution to Energy and Nutrient Intakes. European Journal of Clinical Nutrition, 63, 865-871. http://dx.doi.org/10.1038/ejcn.2008.51
Ferreira, I., Twisk, J.W.R., van Mechelen, W., Kemper, H.C.G. and Stehouwer, C.D.A. (2005) Development of Fatness, Fitness, and Lifestyle from Adolescence to the Age of 36 Years Determinants of the Metabolic Syndrome in Young Adults: The Amsterdam Growth and Health Longitudinal Study. Archives of Internal Medicine, 165, 42-48. http://dx.doi.org/10.1001/archinte.165.1.42
Casanueva, F.F., Moreno, B., Rodríguez-Azeredo, R., Massien, C., Conthe, P., Formiguera, X., Barrios, V. and Balkau, B. (2010) Relationship of Abdominal Obesity with Cardiovascular Disease, Diabetes and Hyperlipidaemia in Spain. Clinical Endocrinology, 73, 35-40.
Janssen, V., Peter, T. and Robert, R. (2004) Waist Circumference and Not Body Mass Index Explains Obesity-Related Health Risk. The American Journal of Clinical Nutrition, 79, 379-384.
(2014) Egypt Demographic and Health Survey. 1-52.
Zaki, M.E., Ezzat, W., Elhosary, Y.A. and Saleh, O.M. (2013) Factors Associated with Nonalcoholic Fatty Liver Disease in Obese Adolescents. Macedonian Journal of Medical Sciences, 6, 273-277.
(2000) The Precise Egyptian Food Composition Table (unpublished data).
McCance and Widdowson’s Composition of Foods Integrated Dataset (CoFID) (2015) Food Data Ranks. 1-13.
WHO (2003) Fruit and Vegetable Promotion Initiative. Report of the Meeting, 25-27 August 2003, World Health Organization, Geneva.
FAO-WHO (2004) Vitamin and Mineral Requirements in Human Nutrition. 2nd Edition, WHO, Geneva.
Schroeder, S., Alexandra, F., Christina, V., Mike, B., Constance, S., Myriam, D. and Olaf, H. (2008) Nutrition Concepts for Elite Distance Runners Based on Macronutrient and Energy Expenditure. Journal of Athletic Training, 43, 489-504.
Olumakaiye, M.F. (2013) Adolescent Girls with Low Dietary Diversity Score Are Predisposed to Iron Deficiency in Southwestern Nigeria. Infant, Child, & Adolescent Nutrition, 5, 85-91. http://dx.doi.org/10.1177/1941406413475661
Hu, F. and Malik, V. (2010) Sugar-Sweetened Beverages and Risk of Obesity and Type 2 Diabetes: Epidemiologic Evidence. Physiology & Behavior, 100, 47-54. http://dx.doi.org/10.1177/1941406413475661
Hussein, L., Hermann-Kunz, E., Dortschy, E., Kojlmeier, L. and Kuhn, G. (1995) Food Consumption Patterns and Nutrient Intakes among Selected Egyptian Employees Differing in Their Socioeducational Status. Egyptian Journal of Nutrition, 10, 75-112.
Padilla, M., Ahmed, Z.S. and Wassef, H.H. (2005) In the Mediterranean Region: Overall Food Security in Quantitative Terms but Qualitative Insecurity. CIHEAM Analytic Note, No. 4, June 2005, 1-100.
Youssef, M.M., Mohsen, M.A., Abou El-Soud, N.H. and Kazem, Y.A. (2010) Energy Intake, Diet Composition among Low Social Class Overweight and Obese Egyptian Adolescents. The Journal of American Science, 6, 160-168.
Streppel, M.T., de Groot, L.C. and Feskens, E.J. (2012) Nutrient-Rich Foods in Relation to Various Measures of Anthropometry Family Practice, 29, i36-i43. http://dx.doi.org/10.1093/fampra/cmr093
Jones, J.M. (2014) CODEX-Aligned Dietary Fiber Definitions Help to Bridge the “Fiber Gap”. Nutrition Journal, 13, 34. http://dx.doi.org/10.1186/1475-2891-13-34
Burton-Freeman, B. (2000) Dietary Fiber and Energy Regulation. The American Journal of Clinical Nutrition, 130, 2725-2755.
Malik, V.S., Pan, A., Willett, W.C. and Hu, F.B. (2013) Sugar-Sweetened Beverages and Weight Gain in Children and Adults: A Systematic Review and Meta-Analysis. The American Journal of Clinical Nutrition, 98, 1084-1102. http://dx.doi.org/10.3945/ajcn.113.058362
Stefan, N., H?ring, H.-U., Hu, F.B. and Schulze, M.B. (2014) Metabolically Healthy Obesity: Epidemiology, Mechanisms, and Clinical Implications. The Lancet, 1, 152-162. www.thelancet.com/diabetes-endocrinology
Willett, W.C., Sacks, F., Trichopoulou, A., Drescher, G., Ferro-Luzzi, A., Helsing, E. and Trichopoulos, D. (1995) Mediterranean Diet Pyramid: A Cultural Model for Healthy Eating. The American Journal of Clinical Nutrition, 61, 1402S-1406S.
Nicklas, T.A., O’Neil, C. and Myers, L. (2004) The Importance of Breakfast Consumption to Nutrition of Children, Adolescents, and Young Adults. Nutrition Today, 39, 30-39.
Saleh, Z., Abdel Razek, F. and Hussein, L. (2002) Composition of Energy Intake and Eating Behaviors among College Women Differing in Their Body Mass Indices. Egyptian Journal of Nutrition, 17, 85-107.
Andrieu, E., Darmon, N. and Drewnowski, A. (2006) Low-Cost Diets: More Energy, Fewer Nutrients. European Journal of Clinical Nutrition, 60, 434-436. http://dx.doi.org/10.1038/sj.ejcn.1602331
Buttriss, J.L., Briend, A., Darmon, N., Ferguson, E.L., Maillot, M. and Lluch, A. (2014) Diet Modeling: How It Can Inform the Development of Dietary Recommendations and Public Health Policy. Nutrition Bulletin, 39, 115-125. http://dx.doi.org/10.1111/nbu.12076