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RESEARCH PAPER
Prevalence of metabolic syndrome in normal
weight individuals
1
Faculty of Medicine and Health Sciences, Jan Kochanowski University, Kielce, Poland
Corresponding author
Ann Agric Environ Med. 2016;23(4):631-635
KEYWORDS
ABSTRACT
Introduction and objective:
The prevalence of metabolic syndrome and overweight in individuals with normal body weight is connected with higher exposure to type 2 diabetes and cardiovascular diseases. The aim of the study was to evaluate the risk and frequency of occurrence of metabolic syndrome and each of its components among individuals with normal weight.
Material and Methods:
Data were obtained by structured interview, and by measurements of anthropometric factors and blood analyses among 13,172 individuals aged 37–66. The risk of occurrence of metabolic syndrome was analysed in tertiles within the normal range of BMI (18.5–24.9 kg/m2).
Results:
Metabolic syndrome was diagnosed in 17.27% of individuals with normal weight. A significant increase in the risk of occurrence of metabolic syndrome in females was observed within the second (OR = 2.22; 95% CI: 1.63–3.05) and the third (OR = 3.97; 95% CI: 2.97–5.36) tertiles of normal BMI values. In males, a significantly higher risk of occurrence of metabolic syndrome was noted only in the highest BMI tertile (OR = 2.16; 95% CI: 1.26–3.83), compared to the reference level.
Conclusions:
A high frequency of occurrence of metabolic syndrome risk factors was observed among individuals with BMI close to the upper cut-off point of the normal range. In order to early diagnose metabolically obese individuals with normal weight it is necessary to check the waist circumference when BMI ≥ 22.5 kg/m2 in females, and BMI ≥ 23.8 kg/m2 in males, where abnormal values should be a signal that further examinations should be performed to determine other risk factors of metabolic syndrome.
The prevalence of metabolic syndrome and overweight in individuals with normal body weight is connected with higher exposure to type 2 diabetes and cardiovascular diseases. The aim of the study was to evaluate the risk and frequency of occurrence of metabolic syndrome and each of its components among individuals with normal weight.
Material and Methods:
Data were obtained by structured interview, and by measurements of anthropometric factors and blood analyses among 13,172 individuals aged 37–66. The risk of occurrence of metabolic syndrome was analysed in tertiles within the normal range of BMI (18.5–24.9 kg/m2).
Results:
Metabolic syndrome was diagnosed in 17.27% of individuals with normal weight. A significant increase in the risk of occurrence of metabolic syndrome in females was observed within the second (OR = 2.22; 95% CI: 1.63–3.05) and the third (OR = 3.97; 95% CI: 2.97–5.36) tertiles of normal BMI values. In males, a significantly higher risk of occurrence of metabolic syndrome was noted only in the highest BMI tertile (OR = 2.16; 95% CI: 1.26–3.83), compared to the reference level.
Conclusions:
A high frequency of occurrence of metabolic syndrome risk factors was observed among individuals with BMI close to the upper cut-off point of the normal range. In order to early diagnose metabolically obese individuals with normal weight it is necessary to check the waist circumference when BMI ≥ 22.5 kg/m2 in females, and BMI ≥ 23.8 kg/m2 in males, where abnormal values should be a signal that further examinations should be performed to determine other risk factors of metabolic syndrome.
REFERENCES (25)
1.
Ruderman N, Chisholm D, Pi-Sunyer X, Schneider S. The metabolically obese, normal-weight individual revisited. Diabetes. 1998; 47: 699–713.
2.
Dvorak RV, DeNino WF, Ades PA, Poehlman ET. Phenotypic characteristics associated with insulin resistance in metabolically obese but normal-weight young women. Diabetes. 1999; 48: 2210–2214.
3.
Meigs JB, Wilson PW, Fox CS, Vasan RS, Nathan DM, Sullivan LM, et al. Body mass index, metabolic syndrome, and risk of type 2 diabetes or cardiovascular disease. J Clin Endocrinol Metab. 2006; 91: 2906–2912.
4.
Hyun YJ, Koh SJ, Chae JS, Kim JY, Kim OY, Lim HH, et al. Atherogenecity of LDL and unfavorable adipokine profile in metabolically obese, normal-weight woman. Obesity 2008; 16: 784–789.
5.
Romero-Corral A, Somers VK, Sierra-Johnson J, Korenfeld Y, Boarin S, Korinek J, et al. Normal weight obesity: a risk factor for cardiometabolic disregulation and cardiovascular mortality. Eur Heart Jour. 2010; 31: 737–746.
6.
Park YW, Zhu S, Palaniappan L, Heshka S, Carnethon MR, Heymsfield SB. The metabolic syndrome: prevalence and associated risk factor findings in the US population from the Third National Health and Nutrition Examination Survey, 1988–199Arch Intern Med. 2003; 163: 427–436.
7.
Geetha L, Deepa M, Anjana RM, Mohan V. Prevalence and clinical profile of metabolic obesity and phenotypic obesity in Asian Indians. Diabetes Sci Technol. 2011; 5: 439–446.
8.
Lopez-Miranda J, Perez-Martinez P. It is time to define metabolically obese but normal-weight (MONW) individuals. Clin Endocrinol. (Oxf) 2013; 27: doi:10.1111/cen.12181.
9.
Pajunen P, Kotronen A, Korpi-Hyövälti E, Keinänen-Kiukaanniemi S, Oksa H, Leo Niskanenet L, et al. Metabolically healthy and unhealthy obesity phenotypes in the general population: the FIN-D2D Survey. BMC Public Health. 2011; 11: 754.
10.
Conus F, Allison DB, Rabasa-Lhoret R, St-Onge M, St-Pierre DH, Tremblay-Lebeau A, et al. Metabolic and behavioral characteristics of metabolically obese but normal-weight woman. J Clin Endocrinol Metab. 2004; 89: 5013–5020.
11.
Hadaegh F, Bozorgmanesh M, Safarkhani M, Khalil D, Azizi F. Predictability of body mass index for diabetes: affected by the presence of metabolic syndrome?. BMC Pub Health. 2011; 11: 383.
12.
Succurro E, Marini MA, Frontoni S, Hribal ML, Andreozzi F, Lauro R, et al. Insulin secretion in metabolically obese, but normal weight, and in metabolically healthy but obese individuals. Obesity 2008; 16: 1881–1886.
13.
Zatoński WA, Mańczuk M, and Kielce PONS team. POlish-Norwegian Study (PONS): research on chronic non-communicable diseases in European high risk countries – study design. Ann Agr Environ Med. 2011; 18: 203–206.
14.
Alberti KGMM, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, et al. Harmonizing the Metabolic Syndrome. A Joint Interim Statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation 2009; 120: 1640–1645.
15.
Sygnowska E, Piwońska A, Waśkiewicz A, Broda G. Socioeconomic factors and the risk of metabolic syndrome in the adult Polish population: the WOBASZ study. Kardiol Pol. 2012; 70: 718–727.
16.
Ilow R, Regulska-Ilow B, Różańska D, Kowalisko A, Biernat J. Prevalence of metabolic syndrome among 40- and 50-year-old inhabitants of Wroclaw, Poland. Ann Agr Environ Med. 2011; 19: 551–556.
17.
Ford ES, Giles WH, Dietz WH. Prevalence of the metabolic syndrome among US adults: findings from the Third National Health and Nutrition Examination Survey. JAMA 2002; 287: 356–359.
18.
Milewicz A, Jedrzejuk D, Dunajska K, Lwow F. Waist circumference and serum adiponectin levels in obese and non-obese postmenopausal women. Maturitas 2010; 65: 272–275.
19.
Mackenbach JP, Stirbu I, Roskam AJ, Schaap MM, Menvielle G, Leinsalu M, et al. European Union Working Group on Socioeconomic Inequalities in Health. Socioeconomic inequalities in health in 22 European countries. N Engl J Med. 2008; 358: 2468–2481.
20.
Huijts T, Eikemo TA, Skalická V. Income-related health inequalities in the Nordic countries: examining the role of education, occupational class, and age. Soc Sci Med. 2010; 71: 1964–1972.
21.
Alves L, Azevedo A, Silva S, Barros H. Socioeconomic inequalities in the prevalence of nine established cardiovascular risk factors in a Southern European population. PLoS ONE 2012; 7: e37158.
22.
Stringhini S, Tabak AG, Akbaraly TN, Sabia S, Shipley MJ, Marmot MG, et al. Contribution of modifiable risk factors to social inequalities in type 2 diabetes: prospective Whitehall II cohort study. BMJ 2012; 345: e5452.
24.
Beigh SH, Jain S. Prevalence of metabolic syndrome and gender differences. Bioinformation. 2012; 8: 613–616.
25.
Ärnlöv J, Sundström J, Ingelsson E, Lind L. Impact of BMI and the metabolic syndrome on the risk of diabetes in middle-aged men. Diabetes Care 2011; 34: 61–66.
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