Daily intake of macronutrients and energy in childhood and its association with cardiometabolic risk factors in Colombians
-
Lyda Z. Rojas
Abstract
Objectives
Determine the intake and percentage of adequacy of macronutrients and their association with cardiovascular risk factors in a sample of Colombian schoolchildren.
Methods
Cross-sectional study nested in a prospective population-based cohort in schoolchildren between 6 and 10 years of age; cardiovascular risk markers and anthropometric measures were measured. Macronutrient intake was established through a food consumption frequency questionnaire (FFQ). The percentage of adequacy was evaluated by comparison with the dietary reference intakes (DRI) and the recommendations for energy and nutrient intake (RIEN) for the Colombian population. Linear regression analysis was performed to assess the association between daily macronutrient/energy intake and cardiometabolic risk factors.
Results
A total of 1,282 school children (51.09% boys and 48.91% girls; mean age 8.4 ± 1.4 years). The percentage of energy adequacy was 107% (Q1=87.5; Q3=127.2). The macronutrients in overadequacy were proteins and carbohydrates. The total fiber had a low adequacy around 26.0% (Q1=15.8; Q3=38.6). Fat intake was positively associated with BMI, insulin, and HOMA-IR index, while carbohydrate consumption was related to these same factors, although negatively in tight models.
Conclusions
Schoolchildren in this study had an inadequate protein, carbohydrate, and fiber intake. The results suggest a significant positive and negative relationship between the consumption of both fat and carbohydrates and cardiometabolic risk factors such as BMI, insulin levels, and HOMA-IR.
Acknowledgment
We thank the Fundación Cardiovascular de Colombia for their invaluable contributions to the database.
Research funding: None declared.
Author contribution: All authors significantly contributed to the intellectual content of this manuscript during the conception and design of the study, acquisition of data, analysis and interpretation of data, drafting or revising the content, and final approval of the paper. LZR, EMGD, and DCQL designed the study, LZR analyzed the data. EMDG and DCQL were involved in data interpretation and wrote the first draft of the manuscript, which was then reviewed and revised by all coauthors.
Conflict of interests: The authors declare no conflict of interest.
Data statement: The data sets generated during and/or analyzed during the current study are not publicly available due to them being data from a population cohort that is still being carried out but are available from the corresponding author on reasonable request.
References
1. American Heart Association Nutrition Committee, Lichtenstein, AH, Appel, LJ, Brands, M, Carnethon, M, Daniels, S, et al.. Diet and lifestyle recommendations revision 2006: a scientific c statement from the American Heart Association Nutrition Committee. Circulation 2006;114:82–96. https://doi.org/10.1161/CIRCULATIONAHA.106.176158.Search in Google Scholar
2. Morrison, JA, Friedman, LA, Wang, P, Glueck, CJ. Metabolic syndrome in childhood predicts adult metabolic syndrome and type 2 diabetes mellitus 25 to 30 years later. J Pediatr 1991;152:201–6. https://doi.org/10.1016/j.jpeds.2007.09.010.Search in Google Scholar
3. Porkka, KV, Viikari, JS, Taimela, S, Dahl, M, Akerblom, HK. Tracking and predictiveness of serum lipid and lipoprotein measurements in childhood: a 12-year follow-up. The Cardiovascular Risk in Young Finns study. Am J Epidemiol 1994;140:1096–110. https://doi.org/10.1093/oxfordjournals.aje.a117210.Search in Google Scholar
4. Berenson, GS. Childhood risk factors predict adult risk associated with sub clinical cardiovascular disease. The Bogalusa Heart Study. Am J Cardiol 2002;90:3L–7L. 9. https://doi.org/10.1016/s0002-9149(02)02953-3.Search in Google Scholar
5. McMahan, CA, Gidding, SS, Malcom, GT, Tracy, RE, Strong, JP, McGill, HCJr. Pathobiological Determinants of Atherosclerosis in Youth Research Group. Pathobiological determinants of atherosclerosis in youth risk scores are associated with early and advanced atherosclerosis. Pediatrics 2006;118:1447–55. https://doi.org/10.1542/peds.2006-0970.Search in Google Scholar PubMed
6. Dwyer, T, Sun, C, Magnussen, CG, Raitakari, OT, Schork, NJ, Venn, A, et al.. Cohort profile: the international childhood cardiovascular cohort (i3C) Consortium. Int J Epidemiol 2013;42:86–96. https://doi.org/10.1093/ije/dys004.Search in Google Scholar PubMed PubMed Central
7. Skinner, AC, Perrin, EM, Moss, LA, Skelton, JA. Cardiometabolic risks and severity of obesity in children and young adults. N Engl J Med 2015;373:1307–17. https://doi.org/10.1056/nejmoa1502821.Search in Google Scholar
8. Setayeshgar, S, Ekwaru, JP, Maximova, K, Majumdar, SR, Storey, KE, McGavock, J, et al.. Dietary intake and prospective changes in cardiometabolic risk factors in children and youth. Appl Physiol Nutr Metabol 2017;42:39–45. https://doi.org/10.1139/apnm-2016-0215.Search in Google Scholar PubMed
9. Villa-Roel, C, Buitrago, A, Rodriguez, DC, Cano, DJ, Martinez, MP, Camacho, PA, et al.. Prevalence of metabolic syndrome in scholars from Bucaramanga, Colombia: a population-based study. BMC Pediatr 2009;9:28. https://doi.org/10.1186/1471-2431-9-28.Search in Google Scholar PubMed PubMed Central
10. National high blood pressure education program working group on high blood pressure in children and adolescents. The fourth report on the diagnosis, evaluation and treatment of high blood pressure in children and adolescents. Pediatrics 2004;114:555–76.10.1542/peds.114.S2.555Search in Google Scholar
11. World Health Organization. WHO child growth standards: length/height-for-age, weight-for-age, weight-for-height and body mass index-for-age: Methods and development. Geneva, Switzerland: World Health Organization; 2006. Available from: http://www.who.int/childgrowth/publications/technical_report_pub/en/index.htmlExternal.Search in Google Scholar
12. American Diabetes Association. Standards of Medical Care in Diabetes 2016. The journal of clinical and applied research and education. Diabetes Care 2016;39:S86–93.10.2337/dc16-S014Search in Google Scholar
13. Matthews, DR, Hosker, JP, Rudenski, AS, Naylor, BA, Treacher, DF, Turner, RC. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 1985;28:412–9. https://doi.org/10.1007/bf00280883.Search in Google Scholar
14. Expert panel on integrated guidelines for cardiovascular health and risk reduction in children and adolescents. National heart, lung and blood institute, NHI. USA. Pediatrics 2011;128:S213–56.10.1542/peds.2009-2107CSearch in Google Scholar
15. Institute of Medicine of the National Academies. Dietary Reference Intakes: the Essential Guide to Nutrient Requirements. Washington: National Academy Press; 2005. Available from: http://www.nap.edu/catalog/11537.Search in Google Scholar
16. Ministerio de Salud y Protección Social. Resolución 003803 de 2016. Recomendaciones de ingesta de Energía y Nutrientes – RIEN para población colombiana [Ministry of Health and Social Protection. Resolution 003803 of 2016. Energy and Nutrient Intake Recommendations - RIEN for the Colombian population]. Available from: https://www.minsalud.gov.co/Normatividad_Nuevo/Resoluci%C3%B3n%203803%20de%202016.pdf.Search in Google Scholar
17. Kivimäki, M, Vahtera, J, Tabák, AG, Halonen, JI Vineis P, Pentti, J, et al.. Neighbourhood socioeconomic disadvantage, risk factors, and diabetes from childhood to middle age in the Young Finns Study: a cohort study. Lancet Public Health 2018;3:e365–73. https://doi.org/10.1016/s2468-2667(18)30111-7.Search in Google Scholar
18. Laitinen, T, Vahtera, J, Pahkala, K, Magnussen, CG, Nuotio, J, Hutri-Kähönen, et al.. Childhood socioeconomic disadvantage and risk of fatty liver in adulthood: the Cardiovascular Risk in Young Finns Study. Hepatology ;71:67–75. https://doi.org/10.1002/hep.30804.Search in Google Scholar PubMed
19. Juonalaa, M, Harcourtc, BE, Sanerc, C, Sethid, M, Safferyc, R, Magnussenf, CG. Neighbourhood socioeconomic circumstances, adiposity andcardiometabolic risk measures in children with severe obesity. Obes Res Clin Pract 2019. in Press.10.1016/j.orcp.2019.05.004Search in Google Scholar PubMed
20. Serrano, N, Robles Silva, A, Suárez, DP, Gamboa-Delgado, E, Quintero-Lesmes, DC. Relación entre la lactancia materna exclusiva los primeros seis meses de vida y el desarrollo de resistencia a la insulina en niños y adolescentes de Bucaramanga, Colombia. Nutr Hosp 2018;35:1042–8. https://doi.org/10.20960/nh.1754.Search in Google Scholar PubMed
21. Raatz, SK, Conrad, Z, Johnson, LK, Picklo, MJ, Jahns, L. Relationship of the reported intakes of fat and fatty acids to body weight in US adults. Nutrients 2017;9:438. https://doi.org/10.3390/nu9050438.Search in Google Scholar PubMed PubMed Central
22. Naude, CE, Visser, ME, Nguyen, KA, Durao, S, Schoonees, A. Effects of total fat intake on bodyweight in children. Cochrane Database Syst Rev 2018;2:CD012960. https://doi.org/10.1002/14651858.CD012960.pub2.Search in Google Scholar PubMed PubMed Central
23. Huang, T, Beaty, T, Li, J, Liu, H, Zhao, W, Wang, Y. Association between dietary fat intake and insulin resistance in Chinese child twins. Br J Nutr 2017;117:230–6. https://doi.org/10.1017/s0007114516004542.Search in Google Scholar
24. Nicklas, TA, Dwyer, J, Feldman, HA, Luepker, RV, Kelder, SH, Nader, PR. Serum cholesterol levels in children are associated with dietary fat and fatty acid intake. J Am Diet Assoc 2002;102:511–7. https://doi.org/10.1016/s0002-8223(02)90117-3.Search in Google Scholar
25. Sharma, S, Roberts, LS, Lustig, RH, Fleming, SE. Carbohydrate intake and cardiometabolic risk factors in high BMI/Age African American children. Nutr Metab 2010;7:10. https://doi.org/10.1186/1743-7075-7-10.Search in Google Scholar PubMed PubMed Central
26. Meissner, T, Wolf, J, Kersting, M, Fröhlich-Reiterer, E, Flechtner-Mors, M, Salgin, B, et al.. Carbohydrate intake in relation to BMI, HbA1c and lipid profile in children and adolescents with type 1 diabetes. Clin Nutr 2014;33:75–8. https://doi.org/10.1016/j.clnu.2013.03.017.Search in Google Scholar PubMed
27. Ma, Y, Olendzki, B, Chiriboga, D, Hebert, JR, Li, Y, Li, W, et al.. Association between dietary carbohydrates and body weight. Am J Epidemiol 2005;161:359–67. https://doi.org/10.1093/aje/kwi051.Search in Google Scholar PubMed PubMed Central
28. López-Sobaler, AM, Aparicio, A, Rubio, J, Marcos, V, Sanchidrián, R, Santos, S, et al.. Adequacy of usual macronutrient intake and macronutrient distribution in children and adolescents in Spain: a National Dietary Survey on the Child and Adolescent Population, ENALIA 2013-2014. Eur J Nutr 2019;58:705–19. https://doi.org/10.1007/s00394-018-1676-3.Search in Google Scholar PubMed PubMed Central
29. Hornell, A, Lagstrom, H, Lande, B, Thorsdottir, I. Protein intake from 0 to 18 years of age and its relation to health: a systematic literature review for the 5th Nordic Nutrition Recommendations. Food Nutr Res 2013;57:21083. https://doi.org/10.3402/fnr.v57i0.21083.Search in Google Scholar PubMed PubMed Central
30. Patro-Golab, B, Zalewski, BM, Kolodziej, M, Kouwenhoven, S, Poston, L, Godfrey, KM, et al.. Nutritional interventions or exposures in infants and children aged up to 3 years and their effects on subsequent risk of overweight, obesity and body fat: a systematic review of systematic reviews. Obes Rev 2016;17:1245–57. https://doi.org/10.1111/obr.12476.Search in Google Scholar PubMed PubMed Central
31. Öztürk, YE, Bozbulut, R, Döğer, E, Bideci, A, Köksal, E. The relationship between diet quality and insulin resistance in obese children: adaptation of the Healthy Lifestyle-Diet Index in Turkey. J Pediatr Endocrinol Metab 2018;28:391–8. https://doi.org/10.1515/jpem-2017-0271.Search in Google Scholar PubMed
32. Due, A, Toubro, S, Skov, AR, Astrup, A. Effect of normal-fat diets, either medium or high in protein, on body weight in overweight subjects: a randomised 1-year trial. Int J Obes Relat Metab Disord 2004;28:1283–90. https://doi.org/10.1038/sj.ijo.0802767.Search in Google Scholar PubMed
33. Herrán, O, Del Castillo, S, Patiño, G. Excess protein in poverty settings: the paradox of overweight in Colombian Children. R CH NUT 2017;44:45–56. https://doi.org/10.4067/s0717-75182017000100007.Search in Google Scholar
© 2020 Walter de Gruyter GmbH, Berlin/Boston
Articles in the same Issue
- Frontmatter
- Review Article
- Papillary thyroid carcinoma in children with Hashimoto’s thyroiditis – a review of the literature between 2000 and 2020
- Original Articles
- Tyrosine metabolism in health and disease: slow-release amino acids therapy improves tyrosine homeostasis in phenylketonuria
- Evolution of Hashimoto thyroiditis in children with type 1 diabetes mellitus (TIDM)
- Glycated hemoglobin variability and microvascular complications in patients with type 1 diabetes mellitus
- Delineation of the genetic and clinical spectrum, including candidate genes, of monogenic diabetes: a multicenter study in South Korea
- Can we use copeptin as a biomarker for masked hypertension or metabolic syndrome in obese children and adolescents?
- Relationship of acanthosis nigricans with metabolic syndrome in obese children
- Daily intake of macronutrients and energy in childhood and its association with cardiometabolic risk factors in Colombians
- The effect of treatment with recombinant human growth hormone (rhGH) on linear growth and adult height in children with idiopathic short stature (ISS): a systematic review and meta-analysis
- Growth in achondroplasia, from birth to adulthood, analysed by the JPA-2 model
- Short Communication
- Assessing disparities in barriers to attending pediatric diabetes camp
- Letter to the Editor
- Severity in pediatric type 1 diabetes mellitus debut during the COVID-19 pandemic
- Case Reports
- The use of glimepiride for the treatment of neonatal diabetes mellitus caused by a novel mutation of the ABCC8 gene
- Effect of recombinant human insulin-like growth factor 1 therapy in a child with 3-M syndrome-1 with CUL7 gene mutation
- A nonsense variant in FGFR1: a rare cause of combined pituitary hormone deficiency
- Treatment response to long term antiresorptive therapy in osteogenesis imperfecta type VI: does genotype matter?
Articles in the same Issue
- Frontmatter
- Review Article
- Papillary thyroid carcinoma in children with Hashimoto’s thyroiditis – a review of the literature between 2000 and 2020
- Original Articles
- Tyrosine metabolism in health and disease: slow-release amino acids therapy improves tyrosine homeostasis in phenylketonuria
- Evolution of Hashimoto thyroiditis in children with type 1 diabetes mellitus (TIDM)
- Glycated hemoglobin variability and microvascular complications in patients with type 1 diabetes mellitus
- Delineation of the genetic and clinical spectrum, including candidate genes, of monogenic diabetes: a multicenter study in South Korea
- Can we use copeptin as a biomarker for masked hypertension or metabolic syndrome in obese children and adolescents?
- Relationship of acanthosis nigricans with metabolic syndrome in obese children
- Daily intake of macronutrients and energy in childhood and its association with cardiometabolic risk factors in Colombians
- The effect of treatment with recombinant human growth hormone (rhGH) on linear growth and adult height in children with idiopathic short stature (ISS): a systematic review and meta-analysis
- Growth in achondroplasia, from birth to adulthood, analysed by the JPA-2 model
- Short Communication
- Assessing disparities in barriers to attending pediatric diabetes camp
- Letter to the Editor
- Severity in pediatric type 1 diabetes mellitus debut during the COVID-19 pandemic
- Case Reports
- The use of glimepiride for the treatment of neonatal diabetes mellitus caused by a novel mutation of the ABCC8 gene
- Effect of recombinant human insulin-like growth factor 1 therapy in a child with 3-M syndrome-1 with CUL7 gene mutation
- A nonsense variant in FGFR1: a rare cause of combined pituitary hormone deficiency
- Treatment response to long term antiresorptive therapy in osteogenesis imperfecta type VI: does genotype matter?
