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Original scientific article:

Manopriya Thiruvagounder1*, Shaheen Khan2, Dhastagir Sultan Sheriff3. The prevalence of metabolic syndrome in a local population in India. Biochemia Medica 2010;20(2):249-52. http://dx.doi.org/10.11613/BM.2010.031
 
1Institute of Research in Science and Medicine, Salem, India
2Institute of Cardiology, Banglore, India
3Department of Biochemistry, Al Arab Medical University, Benghazi, Libya
*Corresponding author: dhastagir [at] yahoo [dot] ca
 
Abstract
 
Introduction: People with metabolic syndrome are about twice as likely to develop cerebrovascular disease (CVD) and over four times as likely to develop type 2 diabetes compared to subjects without metabolic syndrome. This cross-sectional population based study was undertaken to explore the prevalence of metabolic syndrome in a local population in India.
Materials and methods: The prevalence was assessed in a group of 1,568 patients referred to High Tech Hospital affiliated to Vinayaka Missions University, Salem, India. We have analyzed the overall prevalence of metabolic syndrome, as well as the number of components of the metabolic syndrome present in the individuals in this study. For all subjects following variables were collected: age, gender, waist circumference, blood pressure and fasting clinical chemistry parameters. Blood pressure was monitored and measured in a sitting position by a mercury sphygmomanometer. Blood samples for HDL-cholesterol, triglyceride and fasting glucose were collected after 12h overnight fast.
Results: In our group 33.17% of males and 27.04% of females were identified as having the metabolic syndrome. Waist circumference, dyslipidemia and impaired glucose tolerance were significantly more prevalent in our male subjects than in females. Multiple logistic regression analysis showed that increasing age (OR (95% CI) = 1.06 (1.040–1.070); P < 0.001) and male gender (OR (95% CI) = 1.50 (1.190–1.890); P < 0.05) were significant predictors of metabolic syndrome in India.
Conclusion: The metabolic syndrome is substantially prevalent in India. Its prevalence increases with age and is higher in men than in women. A further study is required to understand the role and inter-relationship between some more and less known factors possibly associated with the metabolic syndrome.
Key words: dyslipidaemia; metabolic syndrome; prevalence; glucose intolerance; waist circumference
 
Received: January 22, 2010
Accepted: May 4, 2010
 
Introduction
 
Metabolic syndrome (MS) also known as syndrome X is characterized by hypertriglyceridaemia and low concentration of high density lipoprotein (HDL) cholesterol (dyslipidemia), elevated blood pressure, impaired glucose tolerance and central obesity (1). People with MS are about twice as likely to develop cerebrovascular disease (CVD) and over four times as likely to develop type 2 diabetes compared to subjects without metabolic syndrome (2–4). It is well recognized that the syndrome has a genetic basis along with certain modifiable environmental factors (5,6). The present study was undertaken to report the prevalence of MS in the city of Salem, located in southern part of India.
 
Materials and methods
 
Subjects
Patients who attended the High Tech Hospital affiliated to Vinayaka Missions University, Salem, India for routine medical checkup formed the cases for the present cross-sectional study. The total of 1,568 cases that referred to the hospital during June 2007 to September 2009 was enrolled into the study. Informed consent was taken from all the subjects.
Metabolic syndrome was diagnosed according to the NCEP-ATP III criteria (Third Report of the National Cholesterol Education Program Expert Panel on Detection, Evaluation and Treatment of High Blood Cholesterol in Adults – Adult Treatment Panel III). Three or more of the following criteria formed the basis for defining metabolic syndrome:
1. hypertension, defined as a history of hypertension or a blood pressure greater than or equal to 130/85mm Hg;
2. hypertriglyceridaemia, defined as fasting triglycerides greater than or equal to 1.7 mmol/L;
3. hyperglycaemia, defined as a history of diabetes or a fasting blood glucose greater than or equal to 5.60 mmol/L;
4. low HDL-cholesterol, defined as a fasting HDL-cholesterol less than 1.00 mmol/L in men or less than 1.3 mmol/L in women; and
5. central obesity, defined as a waist circumference greater than 90 centimeters in Asian men or greater than 80 centimeters in Asian women (8,9).
Methods
The following parameters were collected: age, gender, waist circumference, blood pressure and fasting clinical chemistry parameters. Blood pressure was monitored and measured in a sitting position by a mercury sphygmomanometer (7). Blood samples collected after 12h overnight fast were analyzed to determine the concentrations of HDL-cholesterol, triglyceride and fasting glucose using Hitachi 901 Autoanalyzer (Roche Diagnostics GmbH, Germany) (8).
Statistical analysis
Data are presented as arithmetic mean ± standard deviation. Student’s t-test was used for comparison of numerical variables. Chi-square test was used to determine the level of significance for categorical variables. Multivariate logistic regression was used to define predictors of metabolic syndrome. Values of P < 0.05 were considered statistically significant.
Analysis was done using SPSS statistical software (Chicago, IL, USA).
 
Results
 
Out of 1,568 participants, there were 896 (56.8%) men and 672 (43.2%) women. Ten subjects did not participate in the study. The mean age was 49 ± 13 years (age range: 18–80 years), males: 50 ± 60 years; females: 53 ± 15 years.
The demographic characteristics of the population are shown in Table 1. Abdominal obesity, dyslipidemia and impaired glucose tolerance were more prevalent in male subjects than in the females. None of the studied variables differed significantly between various age groups, with the exception of waist circumference (Table 2). The prevalence of metabolic syndrome was 33.17% in men and 27.04% in women (Table 3), the difference was statistically different (P = 0.001).
Multiple logistic regression analysis showed that increasing age (OR (95% CI) = 1.06 (1.040–1.070); P < 0.001) and male gender (OR (95% CI) = 1.50 (1.190–1.890); P < 0.05) were significant predictors of metabolic syndrome.
 
Table 1. Demographic characteristics of studeid population.
 
Table 2. Difference of clinical and biochemical parameters among age subgroups.
 
Table 3. Prevalence of components of metabolic syndrome.
Discussion
 
The National Cholesterol Education Program (NCEP) Adult Treatment Panel (ATP) III defined the criteria for the diagnosis of metabolic syndrome and laid down guidelines for its management (8). Insulin resistance is reported to be the key component for the clustering of risk factors that lead to metabolic syndrome (9).
In this cross-sectional population based study, 33% of men and 27% of women were diagnosed with the metabolic syndrome. Our results show that the prevalence of MS rises with age. Also, MS was more prevalent in men than in women. Asian Indians are known to have lower body mass index (BMI) than Europeans (10). However, for any given BMI, Asian Indians have greater waist-to-hip ratios and abdominal fat than Europeans (11,12).
It will be useful to measure factors associated with MS in different population to identify the prevalence of the syndrome and also to establish whether its prevalence differs according to region, religion and life style (13). It would be possible to prevent the early precipitation of diabetes or cardiovascular events in a community by finding out the presence of metabolic syndrome. This may help to establish basic guidelines of prevention and cure (14). It will be the best approach to formulate a health policy at a community level to provide health care and also educate the medical graduates to understand the basic health needs of the community they serve.
 
References
 
1. Reaven GM. Role of insulin resistance in human disease (syndrome X). An expanded definition. Ann Rev Med 1993; 44:121-31.
2. BlatonVH, KoritaI, BuloA. How is metabolic syndrome related to dyslipidemia? Biochem Med 2008;18:14-24.
3. Meigs JB. Epidemiology of the metabolic syndrome Amer J Manag Care 2002;8:S283-92.
4. Bloomagarden ZT. American Association of clinical Endocrinologists (AACE) consensus conference on the insulin resistance syndrome. Diabetes Care 2003;26:1297-303.
5. Unger RH, Scherer PE. Gluttony, sloth and the metabolic syndrome: a roadmap to lipotoxicity. Trends Endocrinol Metab. 2010 Feb 23. [Epub ahead of print]. Doi:10.1016/j.tem.2010.01.009.
6. Bogardus C, Lillioja S, Mott DM, Hollenbeck C, Reaven GM. Relationship between degree of obesity and in vivo insulin action in man. Amer J Physiol 1985;11:E286-91.
7. Expert Panel on Detection, Evaluation of and Treatment of High Blood Cholesterol in Adults. 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;285:2486-97.
8. Inoue S, Zimmet P. The Asia-Pacific Perspective: Redefining obesity, and its treatment. Health Communications Australia 2000:17-20.
9. 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) final report. Circulation 2002;106:3143-421.
10. WHO Expert Consultation. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet 2004;363:157-63.
11. Raji A, Seely EW, Arky RA, Siminson DC. Body fat distribution and insulin resistance in healthy Asian Indians and Caucasians. J Clin Endocrinol Metab 2001;86:5366-71.
12. Park YW, Zhu S, Palaniappan L,Heshik S, Carnethon MR, Heymsfield SB. The metabolic syndrome prevalence and associated risk factor findings in the US population from third National Health and Nutrition Examination survey, 1988– 1994. Arch Intern Med 2003;163:427-36.
13. Bray GA, Jablonski,KA, Fujimoto WY, Barrett-Connor E, Haffner S, Hanson RL, et al. Relation of central adiposity and body mass index to the development of diabetes in the Diabetes Prevention Program. Amer Jour Clin Nutr 2008;87: 1212-8.
14.  Knowler WC, Barrett-Connor E, Fowler SE, Hamman RF, Lachin JM, Walker EA, et al. Reduction in the incidence of
      type 2 diabetes with lifestyle intervention or metformin. New Eng J Med 2002;346:393-403.
 
 
Sažetak
 
Prevalencija metaboličkog sindroma kod lokalne populacije u Indiji
 
Uvod: Osobe s metaboličkim sindromom imaju dvostruko veći rizik od razvoja cerebrovaskularnih bolesti te više od četiri puta veći rizik od razvoja šećerne bolesti tipa 2 u usporedbi s osobama bez metaboličkog sindroma. Ovo presječno populacijsko istraživanje je provedeno kako bi se istražila prevalencija metaboličkog sindroma kod lokalne populacije u Indiji.
Materijali i metode: Prevalencija metaboličkog sindroma utvrđena je u skupini od 1.568 bolesnika koji su upućeni u bolnicu u sklopu Sveučilišta Vinayaka Missions, Salem, Indija. Ispitana je ukupna prevalencija, kao i broj sastavnica metaboličkog sindroma prisutnih kod ispitanika. Prikupljeni su podaci o sljedećim varijablama: dob, spol, opseg struka, krvni tlak i biokemijski parametri natašte. Krvni tlak je izmjeren u sjedećem položaju živinim tlakomjerom. Uzorci krvi za određivanje koncentracije HDL kolesterola, triglicerida i glukoze natašte uzeti su ujutro nakon 12-osatnog posta.
Rezultati: U našoj smo skupini otkrili da 33,17% muškaraca i 27,04% žena ima metabolički sindrom. Prevalencija opsega struka, dislipidemije i oštećenog podnošenja glukoze bile su statistički značajno veća kod muških ispitanika nego kod žena. Analiza višestruke logističke regresije pokazala je da su starija dob (OR (95% CI) = 1,06 (1,040–1,070); P < 0.001) i muški spol (OR (95% CI) = 1,50 (1,190–1,890); P < 0.05) značajni predskazatelji metaboličkog sindroma u Indiji.
Zaključak: Metabolički sindrom je u Indiji prisutan u znatnoj mjeri. Njegova prevalencija raste sa dobi te je veća kod muškaraca nego kod žena. Potrebna su daljnja istraživanja kako bi se razumjela uloga međusobne povezanosti između nekih dobro poznatih i nekih manje poznatih čimbenika koji bi mogli biti povezani s metaboličkim sindromom.
Ključne riječi: dislipidemija; metabolički sindrom; prevalencija; netolerancija glukoze; opseg struka