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Parent reported nutritional risk and laboratory indices of cardiometabolic risk and in preschool-aged children

  • Navindra Persaud , Hedyeh Ziai , Gerald Lebovic , Jonathon L. Maguire , Marina Khovratovich , Janis A. Randall Simpson , Khosrow Adeli , Jill Hamilton , Brian W. McCrindle , Patricia C. Parkin , Catherine S. Birken EMAIL logo and on behalf of the TARGet Kids! collaboration
Published/Copyright: July 19, 2017

Abstract

Background:

Eating habits formed during childhood may contribute to the increasing prevalence of cardiometabolic disorders. Assessing nutritional risk in young children may help to prevent later cardiometabolic disease. The objective of this study was to determine whether parent-reported nutritional risk in preschool-aged children was associated with laboratory indices of cardiometabolic risk, namely leptin and insulin.

Methods:

In this cross-sectional study, the relationship between nutritional risk as determined by the parent-completed NutriSTEP® questionnaire was assessed and compared to the serum leptin and insulin concentrations, hormones involved in regulation of food intake and biomarkers of adiposity and cardiometabolic risk. The community-based primary care research network for children in Toronto, Canada (TARGet Kids!) was used. The participants were children aged 3–5 years recruited from TARGet Kids! A total of 1856 children were recruited from seven primary care practices. Of these, 1086 children completed laboratory testing. Laboratory data for leptin and insulin were available for 714 and 1054 of those individuals, respectively.

Results:

The total NutriSTEP® score was significantly associated with serum leptin concentrations (p=0.003); for each unit increase in the total NutriSTEP® score, there was an increase of 0.01 ng/mL (95% confidence interval [CI] 0.004–0.018) in serum leptin concentrations after adjusting for potential confounders. The total NutriSTEP® score was not significantly associated with serum insulin concentration.

Conclusions:

Parent reported nutritional risk is associated with serum leptin, but not insulin, concentrations in preschool-aged children. The NutriSTEP® questionnaire may be an effective tool for predicting future cardiometabolic risk in preschool-aged children.


Corresponding author: Catherine S. Birken, Associate Professor, Division of Pediatric Medicine, The Hospital for Sick Children, University of Toronto, 686 Bay St, ON M5G 0X4, Canada, Phone: +416-813-4930, Fax: +416-813-5663
TARGet Kids! Collaboration Site Investigators: Jillian Baker, Tony Barozzino, Joey Bonifacio, Douglas Campbell, Sohail Cheema, Brian Chisamore, Karoon Danayan, Paul Das, Mary Beth Derocher, Anh Do, Michael Dorey, Sloane Freeman, Keewai Fung, Charlie Guiang, Curtis Handford, Hailey Hatch, Sheila Jacobson, Tara Kiran, Holly Knowles, Bruce Kwok, Sheila Lakhoo, Margarita Lam-Antoniades, Eddy Lau, Fok-Han Leung, Jennifer Loo, Sarah Mahmoud, Rosemary Moodie, Julia Morinis, Sharon Naymark, Patricia Neelands, James Owen, Michael Peer, Marty Perlmutar, Navindra Persaud, Andrew Pinto, Michelle Porepa, Nasreen Ramji, Noor Ramji, Alana Rosenthal, Janet Saunderson, Rahul Saxena, Michael Sgro, Susan Shepherd, Barbara Smiltnieks, Carolyn Taylor, Thea Weisdors, Sheila Wijayasinghe, Peter Wong, Ethel Ying, Elizabeth Young.

Acknowledgments

The authors thank all participating families for their time and involvement in TARGet Kids! and are grateful to all practitioners who are currently involved in the TARGet Kids! research network. Steering Committee: Tony Barozzino, Brian Chisamore, Mark Feldman, Moshe Ipp. Research Team: Charmaine Camacho, Diviya Elango, Julie DeGroot, Shanique Edwards, Nadia Kabir, Marina Khovratovich, Tarandeep Malhi, Juela Sejdo, Laurie Thompson, Mandy Tran. Applied Health Research Centre: Magda Melo, Patricia Nguyen. Mount Sinai Services Laboratory: Azar Azad.

  1. Author contributions: All of the authors made substantial contributions to the conception and design of the study; the acquisition, analysis and interpretation of the data; and the drafting of the manuscript or its critical revision for important intellectual content. All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  2. Research funding: This work was supported by the Canadian Institute of Health Research, Physician Services Incorporated, Paediatric Outcomes Research Team through the SickKids Foundation, and St. Michael’s Hospital Foundation (grant number MOP-119375). The funding agencies had no role in the design, analysis or writing of this article.

  3. Employment or leadership: Navindra Persaud is an Associate Editor for CMAJ. Janis Randall Simpson has received grant funding from the Canadian Institutes of Health Research (CIHR); she is a board member for the Danone Institute of Canada; she is a consultant for Dietitians of Canada; she receives royalties for NutriSTEP© licences; and she has been reimbursed for travel expenses by the CIHR. Brian McCrindle is a board member for Medpace; he has been a consultant for Eli Lilly, Merck and Bristol-Myers-Squibb; and he has received grant funding from AstraZeneca. Patricia Parkin and Catherine Birken work for institutions that have received grants from the CIHR. No other competing interests were declared. The other authors have no financial relationships relevant to this article to declare.

  4. Honorarium: None declared.

  5. Competing interests: The funding organization(s) played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.

References

1. Randall Simpson JA, Keller HH, Rysdale LA, Beyers JE. Nutrition screening tool for every preschooler (NutriSTEP): validation and test-retest reliability of a parent-administered questionnaire assessing nutrition risk of preschoolers. Eur J Clin Nutr 2008;62:770–80.10.1038/sj.ejcn.1602780Search in Google Scholar

2. Whitaker RC, Wright JA, Pepe MS, Seidel KD, Dietz WH. Predicting obesity in young adulthood from childhood and parental obesity. N Engl J Med 1997;337:869–73.10.1056/NEJM199709253371301Search in Google Scholar

3. Chen AK, Roberts CK, Barnard RJ. Effect of a short-term diet and exercise intervention on metabolic syndrome in overweight children. Metabolism 2006;55:871–8.10.1016/j.metabol.2006.03.001Search in Google Scholar

4. American Diabetic Association. ADA’s definitions for nutrition screening and nutrition assessment. J Am Diet Assoc 1994;94:838–9.10.1016/0002-8223(94)92357-4Search in Google Scholar

5. NIH Technology Assessment Conference Panel. Methods for voluntary weight loss and control. Ann Intern Med 1993;119:764–70.10.7326/0003-4819-119-7_Part_2-199310011-00026Search in Google Scholar

6. Jääskeläinen P, Magnussen CG, Pahkala K, Mikkilä V, Kähönen M, et al. Childhood nutrition in predicting metabolic syndrome in adults: the cardiovascular risk in Young Finns Study. Diabetes Care 2012;35:1937–43.10.2337/dc12-0019Search in Google Scholar

7. Katzmarzyk PT, Pérusse L, Malina RM, Bergeron J, Després JP, et al. Stability of indicators of the metabolic syndrome from childhood and adolescence to young adulthood: the Québec Family Study. J Clin Epidemiol 2001;54:190–5.10.1016/S0895-4356(00)00315-2Search in Google Scholar

8. Watson-Jarvis K, McNeil D, Fenton TR, Campbell K. Implementing the nutrition screening tool for every preschooler (NutriSTEP) in community health centres. Can J Diet Pract Res 2011;72:96–8.10.3148/72.2.2011.96Search in Google Scholar PubMed

9. Persaud N, Maguire JL, Lebovic G, Carsley S, Khovratovich M, et al. Association between serum cholesterol and eating behaviours during early childhood: a cross-sectional study. Can Med Assoc J 2013;185:E531–6.10.1503/cmaj.121834Search in Google Scholar PubMed PubMed Central

10. Wilasco MI, Goldani HA, Dornelles CT, Maurer RL, Kieling CO, et al. Ghrelin, leptin and insulin in healthy children: relationship with anthropometry, gender, and age distribution. Regul Pept 2012;173:21–6.10.1016/j.regpep.2011.08.013Search in Google Scholar PubMed

11. Ceddia RB, Koistinen HA, Zierath JR, Sweeney G. Analysis of paradoxical observations on the association between leptin and insulin resistance. FASEB J 2002;16:1163–76.10.1096/fj.02-0158revSearch in Google Scholar

12. Moran O, Phillip M. Leptin: obesity, diabetes and other peripheral effects–a review. Pediatr Diabetes 2003;4:101–9.10.1034/j.1399-5448.2003.00017.xSearch in Google Scholar

13. Zhang YY, Proenca R, Maffei M, Barone M, Leopold L, et al. Positional cloning of the mouse obese gene and its human homologue. Nature 1994;372:425–32.10.1038/372425a0Search in Google Scholar

14. Morrison CD. Leptin signaling in brain: a link between nutrition and cognition? Biochim Biophys Acta 2009;1792:401–8.10.1016/j.bbadis.2008.12.004Search in Google Scholar

15. Oral EA, Simha V, Ruiz E, Andewelt A, Premkumar A, et al. Leptin-replacement therapy for lipodystrophy. N Engl J Med 2002;346:570–8.10.1056/NEJMoa012437Search in Google Scholar

16. Schwartz MW, Woods SC, Porte D Jr, Seeley RJ, Baskin DG. Central nervous system control of food intake. Nature 2000;404:661–71.10.1038/35007534Search in Google Scholar

17. Hamnvik OP, Liu X, Petrou M, Gong H, Chamberland JP, et al. Soluble leptin receptor and leptin are associated with baseline adiposity and metabolic risk factors, and predict adiposity, metabolic syndrome, and glucose levels at 2-year follow-up: the Cyprus Metabolism Prospective Cohort Study. Metabolism 2011;60:987–93.10.1016/j.metabol.2010.09.009Search in Google Scholar

18. Savoye M, Dziura J, Castle J, DiPietro L, Tamborlane WV, et al. Importance of plasma leptin in predicting future weight gain in obese children: a two-and-a-half-year longitudinal study. Int J Obes Relat Metab Disord 2002;26:942–6.10.1038/sj.ijo.0802018Search in Google Scholar

19. Mansoub S, Chan MK, Adeli K. Gap analysis of pediatric reference intervals for risk biomarkers of cardiovascular disease and the metabolic syndrome. Clin Biochem 2006; 39:569–87.10.1016/j.clinbiochem.2006.02.013Search in Google Scholar

20. Burke GL, Webber LS, Srinivasan SR, Radhakrishnamurthy B, Freedman DS, et al. Fasting plasma glucose and insulin levels and their relationship to cardiovascular risk factors in children: Bogalusa Heart Study. Metabolism 1986;35:441–6.10.1016/0026-0495(86)90135-6Search in Google Scholar

21. Jiang X, Srinivasan SR, Bao W, Berenson GS. Association of fasting insulin with blood pressure in young individuals. The Bogalusa Heart Study. Arch Intern Med 1993;153:323–8.10.1001/archinte.153.3.323Search in Google Scholar

22. Chu NF, Wang DJ, Shieh SM, Rimm EG. Plasma leptin concentrations and obesity in relation to insulin resistance syndrome components among school children in Taiwan–The Taipei Children Heart Study. Int J Obes Relat Metab Disord 2000;24:1265–71.10.1038/sj.ijo.0801404Search in Google Scholar

23. Marquina D, Peña R, Fernández E, Baptista T. Abnormal correlation between serum leptin levels and body mass index may predict metabolic dysfunction irrespective of the psychopharmacological treatment. Int Clin Psychopharmacol 2011;26:169–72.10.1097/YIC.0b013e328342ce47Search in Google Scholar

24. Chessler SD, Fujimoto WY, Shofer JB, Boyko EJ, Weigle DS. Increased plasma leptin levels are associated with fat accumulation in Japanese-Americans. Diabetes 1998;47:239–43.10.2337/diab.47.2.239Search in Google Scholar

25. Spiegelman BM, Flier JS. Adipogenesis and obesity: rounding out the big picture. Cell 1996;87:377–89.10.1016/S0092-8674(00)81359-8Search in Google Scholar

26. Havel PJ. Peripheral signals conveying metabolic information to the brain: short-term and long-term regulation of food intake and energy homeostasis. Exp Biol Med 2001;126:963–77.10.1177/153537020122601102Search in Google Scholar

27. Statistics Canada. Canadian Community Health Survey-Annual Component (CCHS). Available at http://www23.statcan.gc.ca/imdb/p2SV.pl?Function=getSurvey&SDDS=3226. Accessed on 6/2/2014.Search in Google Scholar

28. Anand SS, Yusuf S, Vuksan V, Devanesen S, Teo KK, et al. Differences in risk factors, atherosclerosis, and cardiovascular disease between ethnic groups in Canada: the Study of Health Assessment and Risk in Ethnic groups (SHARE). Lancet 2000;356:279–84.10.1016/S0140-6736(00)02502-2Search in Google Scholar

29. Balarajan R. Ethnic differences in mortality from ischaemic heart disease and cerebrovascular disease in England and Wales. Br Med J 1991;302:560–4.10.1136/bmj.302.6776.560Search in Google Scholar PubMed PubMed Central

30. World Health Organization. Training course on child growth assessment. Available at: www.who.int/childgrowth/training/module_c_interpreting_indicators.pdf. Accessed on 25/11/2013.Search in Google Scholar

31. de Onis M, Onyango A, Borghi E, Siyam A, Blössner M, et al. Worldwide implementation of the WHO Child Growth Standards. Public Health Nutr 2012;15:1603–10.10.1017/S136898001200105XSearch in Google Scholar PubMed

32. Harrell FE. Regression modeling strategies: with applications to linear models, logistic regression, and survival analysis. New York (NY): Springer Science, 2001:48–9;56–60.10.1007/978-1-4757-3462-1Search in Google Scholar

33. Little RJ, Rubin DB. Statistical analysis with missing data. 2nd ed. Hoboken, NJ: Wiley, 2002:41–53;66–70;85–9.Search in Google Scholar

34. Al-Daghri N, Al-Rubean K, Bartlett WA, Al-Attas O, Jones AF, et al. Serum leptin is elevated in Saudi Arabian patients with metabolic syndrome and coronary artery disease. Diabet Med 2003;20:832–7.10.1046/j.1464-5491.2003.01044.xSearch in Google Scholar

35. Moreno LA, Pineda I, Rodríguez G, Fleta J, Giner A, et al. Leptin and metabolic syndrome in obese and non-obese children. Horm Metab Res 2002;34:394–9.10.1055/s-2002-33472Search in Google Scholar

36. Schoppen S, Riestra P, García-Anguita A, López-Simón L, Cano B, et al. Leptin and adiponectin levels in pubertal children: relationship with anthropometric variables and body composition. Clin Chem Lab Med 2010;48:707–11.10.1515/CCLM.2010.142Search in Google Scholar

37. Stephens TW, Basinski M, Bristow PK, Bue-Valleskey JM, Burgett SG, et al. The role of neuropeptide Y in the antiobesity action of the obese gene product. Nature 1995;377:530–2.10.1038/377530a0Search in Google Scholar

38. Farooqi IS, Matarese G, Lord GM, Keogh JM, Lawrence E, et al. Beneficial effects of leptin on obesity, T cell hyporesponsiveness, and neuroendocrine/metabolic dysfunction of human congenital leptin deficiency. J Clin Invest 2002;110:1093–103.10.1172/JCI0215693Search in Google Scholar

39. Farooqi IS, O’Rahilly S. Leptin: a pivotal regulator of human energy homeostasis. Am J Clin Nutr 2009;89:980S–4S.10.3945/ajcn.2008.26788CSearch in Google Scholar

40. Dunbar JC, Hu Y, Lu H. Intracerebroventricular leptin increases lumbar and renal sympathetic nerve activity and blood pressure in normal rats. Diabetes 1997;46:2040–3.10.2337/diab.46.12.2040Search in Google Scholar

41. Eckel RH, Grundy SM, Zimmet PZ. The metabolic syndrome. Lancet 2005;365:1415–28.10.1016/S0140-6736(05)66378-7Search in Google Scholar

42. Wedick NM, Snijder MB, Dekker JM, Heine RJ, Stehouwer CD, et al. Prospective investigation of metabolic characteristics in relation to weight gain in older adults: the Hoorn Study. Obesity 2009;17:1609–14.10.1038/oby.2008.666Search in Google Scholar

43. Baskin DG, Figlewicz Lattemann D, Seeley RJ, Woods SC, Porte D Jr, et al. Insulin and leptin: dual adiposity signals to the brain for the regulation of food intake and body weight. Brain Res 1999;848:114–23.10.1016/S0006-8993(99)01974-5Search in Google Scholar

44. Ilett S, Freeman A. Improving the diet of toddlers of Pakistani origin: a study of intensive dietary health education. J Fam Health Care 2004;14:16–9.Search in Google Scholar

45. Wyse R, Wolfenden L, Campbell E, Campbell W, Brennan L, et al. A pilot study of a telephone-based parental intervention to increase fruit and vegetable consumption in 3–5-year-old children. Public Health Nutr 2011;14:2245–53.10.1017/S1368980011001170Search in Google Scholar PubMed

46. Yukuwa M, Phelan EA, Callahan HS, Spiekerman CF, Abrass IB, et al. Leptin levels recover normally in healthy older adults after acute diet-induced weight loss. J Nutr Health Aging 2008;12:652–6.Search in Google Scholar

47. Anderson PJ, Critchley JA, Chan JC, Cockram CS, Lee ZS, et al. Factor analysis of the metabolic syndrome: obesity vs insulin resistance as the central abnormality. Int J Obes Relat Metab Disord 2001;25:1782–8.10.1038/sj.ijo.0801837Search in Google Scholar PubMed

48. DeFronzo RA, Ferrannini E. Insulin resistance. A multifaceted syndrome responsible for NIDDM, obesity, hypertension, dyslipidemia, and atherosclerotic cardiovascular disease. Diabetes Care 1991;14:173–94.10.2337/diacare.14.3.173Search in Google Scholar PubMed

49. Gil-Campos M, Aguilera CM, Ramirez-Tortosa MC, Cañete R, Gil A. Fasting and post-prandial relationships among plasma leptin, ghrelin, and insulin in prepubertal obese children. Clin Nutr 2010;29:54–9.10.1016/j.clnu.2009.06.007Search in Google Scholar PubMed

50. Considine RV, Sinha MK, Heiman ML, Kriauciunas A, Stephens TW, et al. Serum immunoreactive leptin concentrations in normal-weight and obese humans. N Engl J Med 1996;334:292–5.10.1056/NEJM199602013340503Search in Google Scholar PubMed

51. Ruige JB, Dekker JM, Blum WF, Stehouwer CD, Nijpels G, et al. Leptin and variables of body adiposity, energy balance, and insulin resistance in a population-based study. The Hoorn Study. Diabetes Care 1999;22:1097–104.10.2337/diacare.22.7.1097Search in Google Scholar PubMed

Received: 2016-8-17
Accepted: 2017-5-12
Published Online: 2017-7-19
Published in Print: 2017-8-28

©2017 Walter de Gruyter GmbH, Berlin/Boston

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