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2010 | 5 | 6 | 724-732

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Differences in the body composition and biochemistry in women grouped as normal-weight, overweight and obese according to body mass index and their relation with cardiometabolic risk


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Morbidity of obesity-related diseases tends to increase due to a rise in the body mass index (BMI). We aimed to investigate how the body composition and biochemical parameters change while BMI increases in adult women were categorized as so: as normal weight, overweight and obese. Our objectives are to study the effects of those changes in the development of metabolic disturbances and to find out which parameters are the most sensitive to predict cardiometabolic risks. Three hundred and twenty two records of adult women (mean age: 38.62±12.71 year) who admitted to our unit concerning about losing or preserving their weights, were analyzed in the study. All patients had undergone anthropometric measurements and body composition analyses as well as some biochemical tests. Body composition analyses were performed by means of the Bioelectrical Impedance Analyzer (BIA). Increase in BMI significantly increased the body fat, blood sugar, insulin, triglyceride and uric acid levels. BMI and circumference of the waist were significantly and negatively correlated with the ratio of body water and lean mass/fat mass. However they were positively correlated with the ratio of fat mass and basal metabolism. Furthermore, it was also found that BMI and circumference of the waist were significantly and positively correlated with level of fasting blood sugar, insulin, triglyceride, homeostasis model assessment insulin resistance (HOMA-IR), uric acid and fibrinogen levels, and negatively correlated with high density lipoprotein (HDL) cholesterol level. In multiple regression analyses, circumference of waist measurements was significantly correlated with insulin, triglyseride and HDL, whereas the correlation between BMI and these parameters was not found significant. Total body fat mass (as %) showed significant correlation only with HDL-C level. It could be said that obesity which is a disorder that causes many health complications and affects the quality of life in the short and long term could be prevented or cured by keeping negative environmental conditions under control. According to our results, visceral adipose tissue (VAT) measurement was thought to be more related for metabolic and cardiovascular disorders rather than BMI. We also propose to test fasting blood glucose, insulin, triglyceride, HDL, fibrinogen, homocystein (HOM) levels along with VAT measurements to predict more truly about not only global cardiometabolic risk but also dementia in later life.










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1 - 12 - 2010
7 - 10 - 2010


  • Samsun Health School, Nutrition and Dietetics Department, Ondokuz Mayis University, 55139, Samsun, Turkey
  • Division of Rheumatology, Department of Medicine, Fatih Sultan Mehmet Education and Research Hospital, 34752, Istanbul, Turkey
  • Department of Public Health, Cerrahpasa Medical Faculty, University of Istanbul, 34099, Istanbul, Turkey
  • Division of gastroenterology, Department of Medicine, Cumhuriyet University Medical Faculty, 58140, Sivas, Turkey
  • Department of Family Medicine, Cumhuriyet University Medical Faculty, 58140, Sivas, Turkey


  • [1] Wadden TA, Stunkard AJ (eds). Translators: Saçıkara A, Yılmaz A.M: Obesity treatment handbook. And Publishing Ltd. Sti. Vol. I. 2003. (Book in Turkish)
  • [2] Werrij MQ, Mulkens S, Hospers HJ, Jansen A. Overweight and obesity: The significance of a depressed mood. Patient Education and Counselling 2006 Jul; 62(1):126–131 http://dx.doi.org/10.1016/j.pec.2005.06.016[Crossref]
  • [3] Nicolls MR. The clinical and biological relationship between Type II diabetes mellitus and Alzheimer’s disease. Curr Alzheimer Res. 2004; 1(1):47–54 http://dx.doi.org/10.2174/1567205043480555[Crossref]
  • [4] Monte SM, wands JR. Review of insulid and insulin like growth factor expression, signaling and malfunction in the central nervous system:relevance to alzheimer’s disease. J Alzheimers Dis. 2005; 7(1):45–61 [PubMed]
  • [5] Yaffe K, Kanaya A, Lindquist K, Simonsick EM, et al. The metabolic syndrom, inflammation and the risk of cognitive decline. JAMA 2004; 292(18):2237–42 http://dx.doi.org/10.1001/jama.292.18.2237[Crossref]
  • [6] Luchsinger JA, Mayeux R. Cardiovascular risk factors and Alzheirmer’s disease. Curr Atheroscler Rep. 2004;6(4):261–266 http://dx.doi.org/10.1007/s11883-004-0056-z[Crossref]
  • [7] Kornhuber HH. Prevention of dementia. Gesundheitswesen 2004;66(5):346–351 http://dx.doi.org/10.1055/s-2004-812832[Crossref]
  • [8] Watson GS, Craft S. Modulation of memory by insulin and glucose neuropsychological observation in Alzheimer’s disease. Eur J Pharmacol. 2004, 19;490 (1–3):97–113 http://dx.doi.org/10.1016/j.ejphar.2004.02.048[Crossref]
  • [9] Rasgon N, Jarvik L. Insulin resistance, affective disorders, and Alzheimer’s disease: review and hypothesis. J Gerontol A Biol Sci Med Sci 2004;59(2):178–83 [Crossref]
  • [10] Grossman H. Does diabetes protect or provoke Alzheimer’s disease? Insight into the pathobiology and future treatment of Alzheimer’s disease. CNS Spectr. 2003; 8(11):815–823
  • [11] Mlinar B, Marc J, Janez A, Pfeifer M. Molecular mechanisms of insulin resistance and associated diseases. Clin Chim Acta 2007; 375: 20–35 http://dx.doi.org/10.1016/j.cca.2006.07.005[Crossref][WoS]
  • [12] Fonseca VA. The metabolic syndrome, hyperlipidemia, and insulin resistance. Clinical Cornerstone 2005; 7(2/3): 61–72 http://dx.doi.org/10.1016/S1098-3597(05)80069-9[Crossref]
  • [13] Despres JP, Lemieux I, Bergeron J, Pibarot P, Mathieu P, Larose E, et al. Abdominal obesity and the metabolic syndrome: contribution to global cardiometabolic risk. Arterioscler Thromb Vasc Biol 2008 Jun; 28(6): 1039–1049 http://dx.doi.org/10.1161/ATVBAHA.107.159228[WoS][Crossref]
  • [14] Ness-Abramof R, Apovian CM. Waist circumference measurements in clinical practice. Nutr Clin Pract 2008 Aug–Sept; 23(4): 397–404 http://dx.doi.org/10.1177/0884533608321700[Crossref]
  • [15] Executive summary of the third report of the National Cholesterol Education Program (NCEP) Expert Panel on detection, evaluation and treatment of high blood cholesterol in adults (Adult Treatment Panel III). JAMA 2001; 285: 2486–2497 http://dx.doi.org/10.1001/jama.285.19.2486[Crossref]
  • [16] Despres JP, Cartier A, Cote M, Arsenault BJ. The cocept of cardiometabolic risk: Bridging the fields of diabetology and cardiology. Ann Med 2008 Apr; 10: 1–10 [WoS]
  • [17] Depres JP. Cardiovascular disease under the influence of excess visceral fat. Crit Pathw Cardiol 2007 Jun; 6(2): 51–59
  • [18] Wildman RP, Muntner P, Reynolds K, McGinn AP, Rajpathak S. Et al: The obese without cardiometabolic risk factor clustering and the normal weight with cardiometabolic risk factor clustering. Arch Intern Med 2008; 168(15): 1617–1624 http://dx.doi.org/10.1001/archinte.168.15.1617[WoS][Crossref]
  • [19] Eckel RH, Grundy SM, Zimmet PZ. The metabolic syndrome. Lancet 2005; 365: 1415–1428 http://dx.doi.org/10.1016/S0140-6736(05)66378-7[WoS][Crossref]
  • [20] Grundy SM, BrewerJr HB, Cleeman JI, Smith Jr SC, Lenfant C. Definition of metabolic syndrome: Report of the National Heart, Lung, and Blood Institute/American Heart Association conference on scientific issues related definition. Circulation 2004; 109; 433–438 http://dx.doi.org/10.1161/01.CIR.0000111245.75752.C6[Crossref]
  • [21] Alberti KGMM, Zimmet P, Shaw J. Metabolic syndrome-a new worldwide definition: A Consensus Statement from the International Diabetes Federation. Diabet Med 2006; 23: 469–480 http://dx.doi.org/10.1111/j.1464-5491.2006.01858.x[Crossref]
  • [22] Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacker DF, Tumer RC. Homeostasis model assesment: insulin resistance and B-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologica 1985; 28:412–419 http://dx.doi.org/10.1007/BF00280883[Crossref]
  • [23] Watson GS, Craft S. The role of insulin resistance in the pathogenesis of Alzheimer’s disease: implications for treatment. CNS Drugs. 2003; 17(1):27–45 http://dx.doi.org/10.2165/00023210-200317010-00003[Crossref][WoS]
  • [24] Gomez-Ambrosi J, Salvador J, Paramo JA, et al. Involvement of leptin in the association between percentage of body fat and cardiovascular risk factors. Clin Biochem 2002; 35(4):315–320 http://dx.doi.org/10.1016/S0009-9120(02)00320-X[Crossref]
  • [25] Groop L, Orho-Melander M. The dysmetabolic syndrom. Journal of Internal Medicine 2001; 250:105–120. http://dx.doi.org/10.1046/j.1365-2796.2001.00864.x[Crossref]
  • [26] Ozenoglu A, Can G, Hatemi H. Body composition referance values of adult women grouped as normalweight, overweight, obese and morbid obese according to body mass index. Endocrinologic Invest 2001; 10(2): 58–63 (Journal in Turkish)
  • [27] Després JP. Is visceral obesity the cause of the metabolic syndrome? Ann Med 2006;38:52–63 http://dx.doi.org/10.1080/07853890500383895[Crossref]
  • [28] Björntorp P. Metabolic implications of body fat distribution. Diabetes Care. 1991;14:1132–1143 http://dx.doi.org/10.2337/diacare.14.12.1132[Crossref]
  • [29] Després JP, Moorjani S, Lupien PJ, et al. Regional distribution of body fat, plasma lipoproteins, and cardiovascular disease. Arteriosclerosis. 1990;10:497–511 [PubMed][Crossref]
  • [30] Kissebah AH, Krakower GR. Regional adiposity and morbidity. Physiol Rev. 1994;74:761–811 [PubMed]
  • [31] Lebovitz HE, Banerji MA. Point: visceral adiposity is causally related to insulin resistance. Diabetes Care. 2005;28:2322–2325 http://dx.doi.org/10.2337/diacare.28.9.2322[Crossref]
  • [32] Grospe EC, Dave JK. The risk of dementia with increased body mass index: a systematic review. Age Aging 2007; 36: 23–29 http://dx.doi.org/10.1093/ageing/afl123[Crossref]
  • [33] Gustafson D. Adiposity indices and dementia. Lancet Neurol 2006; 5: 713–720 http://dx.doi.org/10.1016/S1474-4422(06)70526-9[Crossref]
  • [34] Razay G, Vreugdenhil A, Wilcock G. Obesity, abdominal obesity and Alzheimer disease. Dement Geriatr Cogn Disord 2006; 22: 173–6 http://dx.doi.org/10.1159/000094586[Crossref]
  • [35] Luchsinger JA, Patel B, Tang MX, Schupf N, Mayeux R. Measures of adiposity and dementia risk in elderly persons. Arch Neurol 2007; 64:392–398 http://dx.doi.org/10.1001/archneur.64.3.392[WoS][Crossref]
  • [36] Despres JP, Lemieux I. Abdominal obesity and metabolic syndrome. Nature 2006; 444: 881–887 http://dx.doi.org/10.1038/nature05488[Crossref]
  • [37] Scheneider HJ, Glaesmer H, Klotsche J, et al. Accuracy of anthropometric indicators of obesity to predict cardiovascular risk. J Clin Endocrinol Metab 2007; 92: 589–594 http://dx.doi.org/10.1210/jc.2006-0254[WoS][Crossref]
  • [38] Cereda E, Sansone V, Meola G, Malavazos AE. Increased visceral adipose tissue rather than BMI as a risk factor for dementia. Age and Aging 2007; 36: 488–491 http://dx.doi.org/10.1093/ageing/afm096[Crossref]

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