A Survey on the Relationship of Metabolic Syndrome Components and the Number of Blood Cells Using Count Data Regression Model

Document Type : Original Article (s)

Authors

1 Department of Statistics, School of Science, The University of Isfahan, Isfahan, Iran.

2 Assistant Professor, Department of Statistics, School of Science, The University of Isfahan, Isfahan, Iran.

3 Professor, Department of Pediatrics,Child Health Promotion Research Center, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran.

Abstract

Background: The metabolic syndrome is characterized by a group of metabolic risk factors at increased risk of coronary heart disease and type 2 diabetes. Obese children with metabolic syndrome have at least three of these risk factors. Since the lifestyle changed resulting in the obesity of Iranian children, this syndrome became one of the important concerns in these age groups. There have been many researches on the relationship between this syndrome and number of blood cells in children. However, it was not considered in Iran to some extent. Since the number of blood cells is a counting variable, using traditional statistical methods ends up with erroneous inferences. In this paper, the generalized Poisson model was used to identify the effect of metabolic syndrome on the number of (red and white) blood cells.Methods: 292 obese children in the age group of 6 to 12 years old participated in the children Hospital of Isfahan Medical University for this cross-sectional Study. Metabolic syndrome characteristics were analyzed considering coronary and growth parameters.Finding: Generalized Poisson model, as the best fitting model on the count data, showed that the following two factors, BMI and ratio between triglyceride and HDL-C, significantly affect the number of white blood cells; the ratio between cholesterol and HDL-C, the ratio between triglyceride and HDL-C and the ratio between LDL-C and HDL-C had a significant effect on the number of red blood cells.Conclusion: This study shows that some of the characteristics of metabolic syndrome affect the number of blood cells.

Keywords


  1. Weiss R, Dziura J, Burgert TS, Tamborlane WV, Taksali SE, Yeckel CW, et al. Obesity and the metabolic syndrome in children and adolescents. N Engl J Med 2004; 350(23): 2362-74.
  2. Maki KC. Dietary factors in the prevention of diabetes mellitus and coronary artery disease as-sociated with the metabolic syndrome. Am J Cardiol 2004; 93(11A): 12C-7C.
  3. Steinberger J, Daniels SR. Obesity, insulin re-sistance, diabetes, and cardiovascular risk in children: an American Heart Association scien-tific statement from the Atherosclerosis, Hyper-tension, and Obesity in the Young Committee (Council on Cardiovascular Disease in the Young) and the Diabetes Committee (Council on Nutrition, Physical Activity, and Metabolism). Circulation 2003; 107(10): 1448-53.
  4. Bacha F, Saad R, Gungor N, Janosky J, Arslanian SA. Obesity, regional fat distribution, and syndrome X in obese black versus white ad-olescents: race differential in diabetogenic and atherogenic risk factors. J Clin Endocrinol Metab 2003; 88(6): 2534-40.
  5. Jalali R, Vasheghani M, Dabbaghmanesh MH, Ranjbar Omrani Gh. Prevalence of metabolic syndrome among adults in a rural area. Iranian. Journal of Endocrinology and Metabolism 2009; 11(4): 405-14.
  6. Nishina M, Kikuchi T, Yamazaki H, Kameda K, Hiura M, Uchiyama M. Relationship among sys-tolic blood pressure, serum insulin and leptin, and visceral fat accumulation in obese children. Hypertens Res 2003; 26(4): 281-8.
  7. Ebrahimi-Mamaghani M, Arefhosseini SR, Gol-zarand M, Aliasgarzadeh A, Vahed-Jabbary M. Long-term effects of processed berberis vulgaris on some metabolic syndrome components. Ira-nian Journal of Endocrinology and Metabolism 2009; 11(1): 41-7.
  8. Steinberger J. Diagnosis of the metabolic syn-drome in children. Curr Opin Lipidol 2003; 14(6): 555-9.
  9. Cole TJ, Bellizzi MC, Flegal KM, Dietz WH. Es-tablishing a standard definition for child over-weight and obesity worldwide: international sur-vey. BMJ 2000; 320(7244): 1240-3.
  10. Ascaso JF, Romero P, Real JT, Lorente RI, Mar-tinez-Valls J, Carmena R. Abdominal obesity, in-sulin resistance, and metabolic syndrome in a southern European population. Eur J Intern Med 2003; 14(2): 101-6.
  11. Rodriguez-Moran M, Salazar-Vazquez B, Vio-lante R, Guerrero-Romero F. Metabolic syn-drome among children and adolescents aged 10-18 years. Diabetes Care 2004; 27(10): 2516-7.
  12. Wang YY, Lin SY, Liu PH, Cheung BM, Lai WA. Association between hematological parameters and metabolic syndrome components in a Chi-nese population. J Diabetes Complications 2004; 18(6): 322-7.
  13. Cameron AC, Trivedi PK. Regression Analysis of Count Data. Cambridge: Cambridge University Press; 1998.
  14. Hardin JW, Hilbe JM. Generalized Linear Models and Extensions. 2nd ed. Texas: Stata Press; 2007.
  15. Lee Y. Fixed-effect versus random-effect mod-els for evaluating therapeutic preferences. Stat Med 2002; 21(16): 2325-30.
  16. Kim JA, Choi YS, Hong JI, Kim SH, Jung HH, Kim SM. Association of metabolic syndrome with white blood cell subtype and red blood cells. Endocr J 2006; 53(1): 133-9.
  17. Hsieh CH, Pei D, Kuo SW, Chen CY, Tsai SL, Lai CL, et al. Correlation between white blood cell count and metabolic syndrome in adoles-cence. Pediatr Int 2007; 49(6): 827-32.
  18. Wu CZ, Hsiao FC, Lin JD, Su CC, Wang KS, Chu YM, et al. Relationship between white blood cell count and components of metabolic syndrome among young adolescents. Acta Diabetol 2010; 47(1): 65-71.
  19. Roberts CK, Won D, Pruthi S, Kurtovic S, Sindhu RK, Vaziri ND, et al. Effect of a short-term diet and exercise intervention on oxidative stress, in-flammation, MMP-9, and monocyte chemotac-tic activity in men with metabolic syndrome fac-tors. J Appl Physiol 2006; 100(5): 1657-65.
  20. Sanchez-Chaparro MA, Calvo-Bonacho E, Gonzalez-Quintela A, Cabrera M, Sainz JC, Fer-nandez-Labandera C, et al. Higher red blood cell distribution width is associated with the metabol-ic syndrome: results of the Ibermutuamur Car-diovascular RIsk assessment study. Diabetes Care 2010; 33(3): e40.
  21. Motlagh ME, Kelishadi R, Amirkhani MA, Ziaoddini H, Dashti M, Aminaee T, et al. Double burden of nutritional disorders in young Iranian children: findings of a nationwide screening sur-vey. Public Health Nutr 2011; 14(4): 605-10.