Predictors of metabolic syndrome in Asian north Indians with newly detected type 2 diabetes.
Subject: Type 2 diabetes (Risk factors)
Insulin resistance (Risk factors)
Cholesterol
Medical testing products
Medical research
Medicine, Experimental
Diabetics
Authors: Dhanaraj, Ethiraj
Bhansali, Anil
Jaggi, Shallu
Dutta, Pinaki
Jain, Shikha
Tiwari, Pramil
Ramarao, Poduri
Pub Date: 05/01/2009
Publication: Name: Indian Journal of Medical Research Publisher: Indian Council of Medical Research Audience: Academic Format: Magazine/Journal Subject: Biological sciences; Health Copyright: COPYRIGHT 2009 Indian Council of Medical Research ISSN: 0971-5916
Issue: Date: May, 2009 Source Volume: 129 Source Issue: 5
Product: Product Code: 8000200 Medical Research; 9105220 Health Research Programs; 8000240 Epilepsy & Muscle Disease R&D NAICS Code: 54171 Research and Development in the Physical, Engineering, and Life Sciences; 92312 Administration of Public Health Programs
Accession Number: 221850569
Full Text: Background & objectives: The identification of metabolic syndrome (MS) among patients with type 2 diabetes (T2DM) is of great importance, since those with MS carry a cluster of cardiovascular risk factors. This study evaluates suitable criteria with high efficiency in diagnosing MS and to identify the strongest predictors of MS in newly detected type 2 diabetes individuals.

Methods: Newly detected type 2 diabetes (<6 months) patients were assessed. The MS was assessed by WHO, National Cholesterol Education Program Adult Treatment Panel III (NCEP-ATP III), modified NCEP-ATP-III and International Diabetes Federation (IDF) criteria. Receiver operating characteristics (ROC) curves of serum triglycerides, HDL, and waist circumference were created for the prediction of MS and the area under the corresponding curves (AUC) were used to evaluate the predictive efficiency of each MS parameter. Different cut points in the selected variables and the corresponding sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were estimated.

Results: Among the 563 newly detected T2DM individuals, the presence of MS ranged from 57 to 68 per cent according to the different criteria. The higher percentage of MS was observed in modified NCEP-ATP III criteria. In comparison to men, presence of MS was higher in women in all the four criteria [198 (67%) vs. 165 (62%); 209 (70%) vs. 111 (42%); 231 (78%) vs. 151 (57%); 222 (75%) vs. 129 (49%)] by modified WHO, NCEP-ATP III, modified NCEP-ATP III, and IDF, respectively. The predictive ability to diagnose MS was highest with modified NCEP-ATP III and lowest with IDF criteria. The optimal cut-off of waist circumference in men and women were 90 and 88 cm respectively. Serum triglyceride in men effectively indicated the presence of MS in newly detected T2DM individuals, whereas, in women the HDL-C was the stronger predictor of MS.

Interpretation & conclusions: The study results show that modified NCEP-ATP III criteria predict highest occurrence of MS in newly detected T2DM patients. Elevated serum triglyceride for men and decreased serum HDL-C in women were the strongest single predictors, effectively indicating presence of MS in newly detected T2DM.

Key words Hypertension--lipids--metabolic syndrome--newly detected T2DM

**********

The metabolic syndrome (MS) is described as clusters of abnormalities including abdominal obesity, insulin resistance, hypertension, hyperglycaemia, increased triglycerides, and decreased high-density lipoprotein cholesterol (HDL-C) (1). It is estimated that 13 per cent of adolescents in the United States (2) and 15 per cent nondiabetic European adults have metabolic syndrome (3). The number of people with the metabolic syndrome also differs by sex, race, and ethnicity (2). Most patients with diabetes have metabolic syndrome with estimated prevalence of 69.9 per cent for Whites, 64.8 per cent for Blacks, and 62.4 per cent for Mexican Americans (4). Several studies indicate a rising prevalence of diabetes and insulin resistance in India (5-7) with varying prevalence of MS in Asian Indian immigrants (31.6 to 33.9%) (8,9), and in urban Asian Indian adults (41.1 to 49.2%) (l0,11).

Type 2 diabetes mellitus (T2DM) is a significant risk factor for coronary heart disease (CHD) and stroke (1). At least 65 per cent of people with T2DM die of some form of heart disease and stroke (12). Patients with T2DM have an increased prevalence of lipid abnormalities, which contribute to higher rates of CHD. High triglyceride and low HDL cholesterol levels were significantly related to all coronary heart disease events and to coronary mortality in patients with T2DM (13). Moreover, the prevalence of CHD in diabetes patients increases significantly with the addition of MS components (14). According to Third National Health and Nutrition Examination Survey (NHANES III) data, people who did not have MS, had the lowest risk for cardiovascular disease (CVD) events, those with MS had an intermediate level of risk, and those with diabetes had the highest level of risk (15).

Asian Indian men and women have a higher incidence and mortality rate from CVD than Caucasian men and women (16). Both MS and T2DM are heterogeneous and complex conditions due to interplay between environmental and genetic factors operating differentially in different populations. The International Diabetes Federation (IDF) (17), World Health Organization (WHO) and the National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP-III) have proposed working definitions for the MS based on the traits like overall obesity, central obesity, dyslipidaemia as characterized by elevated levels of triglycerides and low levels of HDL cholesterol, hyperglycaemia, and hypertension. In this study an attempt was made to determine the parameters used for diagnosing MS according to modified WHO, NCEP-ATP III, modified NCEP-ATP III (18) and IDF classifications which could effectively predict the presence of the MS in newly detected T2DM. South Asians develop metabolic abnormalities at a lower body mass index and waist circumference than other groups (19). Hence, to determine the prevalence of MS and formulating preventive strategies remains contentious. Therefore, the recognition of suitable criteria with high efficiency in diagnosing MS and to identify the strongest predictors of MS in newly detected T2DM individuals were the main objectives of this study.

Material & Methods

This study was carried out from January 2005 to December 2007 at the Nehru Hospital, Postgraduate Institute of Medical Education and Research (PGIMER), Chandigarh, north India. All consecutive patients with newly detected type 2 diabetes (<6 months) attending the Endocrinology Outpatient Clinic were included. Informed and written consent was obtained from all the participants after explaining the procedure. The study protocol was approved by the Institute's Ethics Committee. Initial evaluation included a detailed history and clinical examination to exclude any systemic disease.

Diagnosis of MS was based on modified WHO criteria (microalbuminuria was excluded) (17), NCEP ATP III criteria (20), modified NCEPATP III criteria (18) and IDF criteria (17) (Table I).

Anthropometric assessment: Standing body height (to the nearest 0.5 cm) was measured with a commercial stadiometer. A digital scale, with an accuracy of [+ or -]100 g, was used to measure body weight (BW). The waist circumference (WC) was measured in a horizontal plane, midway between the inferior margin of the ribs and the superior border of the iliac crest. Hip circumference (HC) was measured at the fullest point around the buttocks with a metallic tape. The measurements were taken thrice and the mean was taken in all eases. WC (cm) was divided by HC (cm) to calculate waist to hip ratio (WHR). Body mass index (BMI) (kg/[m.sup.2]) was calculated by dividing weight (in kilograms) by the square of height (in meters), as a measure of total adiposity.

Systolic and diastolic blood pressure (SBP & DBP) were measured twice at an interval of 3 min in the sitting position after a 15 min rest, and the mean was taken. Per cent body fat (%BF) was evaluated by impedance plethysmography (bioelectrical impedance meter (Omron BF 302, Tokyo). Blood samples (3 ml) were drawn after 8-12 h overnight fasting for the measurement of lipid profile [total cholesterol, high density lipoprotein (HDL) cholesterol, and triglycerides] and fasting plasma glucose levels. Plasma glucose was measured using the glucose oxidaseperoxidase method (21), serum total cholesterol (22) and triglycerides (23) by standard enzymatic procedures and HDL cholesterol (24) by direct assay method. Diagnosis of diabetes was based on fasting plasma glucose (FPG) [greater than or equal to] 126 mg/dl and/or a 2 h plasma glucose [greater than or equal to] 200 mg/dl (25).

Statistical analysis: Differences in characteristics between T2DM with and without MS were tested with independent sample t tests for normal distributed variables, with the Wilcoxon rank sum test for skewed variables and with the chi-square test for categorical variables. The significance level was set at 5 per cent.

All statistical analyses were carried out using sigma stat (Version 2.03) and Analyse-it software (Analyse--it Software Ltd., trial version 1.0.5.0). Receiver operating characteristics (ROC) curves of serum triglycerides, HDL, and waist circumference were created for the prediction of MS and area under the corresponding curves (AUC) were used to evaluate the predictive efficiency of each MS parameter. The AUCs derived from different samples were compared by the method described by Hanley and McNeil (26). The critical level for the z statistic was set at 1.96. Different cut points in the selected variables and the corresponding sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were also estimated. Serum HDL and waist circumference were analyzed according to the gender. The optimal cut-off (27) was calculated as the minimum value of the square root of [[(1 - sensitivity).sup.2] + [(1 - specificity).sup.2]], and greater accuracy is reflected by a smaller distance to (0,1).

Results

Among the 563 patients (266 males and 297 females) metabolic syndrome was diagnosed in 363 (64.47%), 320 (56.83%), 382 (67.85%), 351 (62.34%) patients according to the modified WHO, NCEP ATP III, modified NCEP ATP III and IDF criteria, respectively. After stratification by gender, 165 men (62.03%) and 198 women (66.7%), 111 men (41.7%) and 209 women (70.4%), 151 men (56.8%) and 231 women (77.8%), 129 men (48.5%) and 222 women (74.7%), had MS according to the modified WHO, NCEP ATP III, modified NCEP ATP III and IDF criteria, respectively. Presence of components of metabolic syndrome was seen more in women in comparison to men (Table II). Baseline and demographic characteristics of the patients with MS versus those without MS according to the modified NCEP-ATP III criteria are summarized in Table III.

Of the four criteria assessed, serum triglycerides for men had shown highest predictive ability for MS in modified WHO criteria (AUC 0.859 with 95% CI 0.803 to 0.915). After stratification by gender, the AUC for triglycerides differed significantly (0.859 in men vs. 0.750 in women, P<0.05). However, in women HDL had shown highest predictive ability for MS in modified NCEP ATP Ill criteria. The displayed AUCs in all the four criteria were 0.669 with 95 per cent CI 0.588 to 0.749, 0.795 with 95 per cent CI 0.723 to 0.867, 0.846 with 95 per cent CI 0.778 to 0.914, and 0.668 with 95 per cent CI 0.577 to 0.760 in modified WHO, NCEP ATP III, modified NCEP ATP III, and IDF criteria respectively (Table IV). The AUC for HDL- C in women in comparison with men, differed significantly (0.846 by modified NCEP ATP Ill vs. 0.656 by IDF criteria, P<0.05).

The optimal cut point (calculated as the minimum value of the square root of [[(1 - sensitivity).sup.2] + [(1 - sensitivity).sup.2] for triglycerides in men was 153, 154, 170 mg/dl and it showed satisfactory sensitivity (%) and specificity (%) 78.9 and 92.9, 83.8 and 72.3, 78.2 and 82.1 in modified WHO, NCEP-ATP III, and modified ATP-III criteria respectively (Table V). For the IDF classification, a cut-off of 150 mg/dl for serum triglycerides in men showed 69.4 per cent sensitivity and 56 per cent specificity, while an optimal cut-off of 170 mg/dl showed 59.3 and 69.7 per cent values.

For women serum HDL-C cut-off of 50 mg/dl showed sensitivity (74%) and specificity (45%) of 80 and 77 per cent, 77 per cent and 86, 74 and 52 per cent by modified WHO, NCEP ATP III, modified NCEP ATP III and IDF criteria respectively. The optimal cut-off of 50 mg/all was observed in NCEP ATP III and modified NCEP ATP III criteria. Whereas, in modified WHO the optimal cut-off of 47.6 mg/dl (sensitivity 65%, specificity 58%), and 47 mg/dl (sensitivity 66%, specificity 62%) in IDF criteria was observed. However, HDL cut-offs above the suggested 50 mg/dl exhibited specificity lower than 60 per cent (Table III).

The optimal cut-off for HDL in men showed 44 mg/dl (sensitivity 58%, specificity 53%), 40 (sensitivity 55%, specificity 85%), 40 (sensitivity 46%, specificity 85%) and 47 mg/dl (sensitivity 72%, specificity 36%) in modified WHO, NCEP-ATP III, modified ATP-III and IDF criteria, respectively.

The optimal cut-off for waist circumference in men displayed 90.5 cm (sensitivity 67.1%, specificity 67%), 96.8 cm (sensitivity 55%, specificity 86%), and 90 cm (sensitivity 78%, specificity 76%) in modified WHO, NCEP-ATP III and modified ATP-III criteria respectively. The optimal cut point for waist circumference in women showed 88.7 cm (sensitivity 66%, specificity 55%), 88 cm (sensitivity 74%, specificity 71%) and 84 cm (sensitivity 83%, specificity 54%) in modified WHO, NCEP-ATP III and modified ATP-III criteria, respectively (Table V).

The metabolic components triglyceride and waist circumference for men and HDL-C for women had shown better predictive ability and observed AUC >0.800 in modified NCEP ATP III classification (Figs 1-3). However, the serum triglyceride and HDL did not show AUC >0.700 in IDF classification. Serum triglycerides for men AUC (0.824 vs. 0.666, P<0.05) and HDL-C for women (0.846 vs. 0.668, P<0.05) in modified NCEP ATP Ill classification differed significantly with the IDF criteria. The cut-off of 150 mg/dl for serum triglycerides in men showed the specificity and PPV of 90 and 94 per cent in modified WHO criteria, 70 and 72 per cent in NCEP ATP III criteria, 79 and 85 per cent in modified NCEP ATP III criteria whereas, in IDF criteria the observed values were 56 and 61 per cent, respectively. The cut-off of 50 mg/dl for serum HDL-C in women showed the specificity and PPV of 86 and 97 per cent in modified NCEP ATP III criteria whereas in IDF criteria the observed values were 52 and 87 per cent, respectively. However, cut-off of 40 mg/dl for HDL-C in men showed the specilicity and PPV of 85 and 83 per cent in modified NCEP ATP-III criteria (Fig. 3) and showed 69 and 54 per cent, respectively in IDF criteria.

[FIGURE 1 OMITTED]

[FIGURE 2 OMITTED]

Discussion

The present study shows the prevalence of MS varying from 57 per cent (NCEP-ATP III) to 68 per cent (Modified NCEP-ATP III) by different criteria in newly detected T2DM individuals. In comparison to men, prevalence of MS was higher in women in all the criteria. The predictive ability to diagnose MS was highest with modified NCEP-ATP III and least with IDF criteria. Among the various components of MS hypertriglyceridemia showed highest predictive ability to diagnose MS in men and low HDL-C in women.

The prevalence of MS was highest with modified NCEP ATP III and least with NCEP ATP III. This difference in prevalence may be attributed to waist circumference cut-offs of 102 and 88 cm for men and women respectively in NCEP ATP III, while 90 and 80 cm for men and women respectively in modified NCEP ATP III. The prevalence of MS was higher in our study as compared to a similar study from South India (10) (68% vs 41%). This may be attributed to the different criteria used to define MS particularly the waist circumference of [greater than or equal to]85 cm in women as standard of 80 cm. The higher prevalence of MS in women with diabetes as compared to men is not a surprising observation. Eighty four per cent of women were centrally obese (waist circumference [greater than or equal to] 80 cm) with a significantly higher mean BMI than men and had higher prevalence of low HDL-C and hypertension. Excess weight has been shown to be the main underlying contributors to the development of MS in women (11). This further substantiates that women in general otherwise have higher prevalence of MS.

[FIGURE 3 OMITTED]

In a study by Hsieh et al (28) the most common combination of component of MS in patients with MS were obesity, hypertension and low HDL-C by modified NCEP ATP-III. We also had a similar observation however, hypertriglyceridemia dominated over low HDL-C. It was interesting to observe that patients with diabetes who fulfilled the criteria of MS had higher BMI, waist circumference, %BF, BP and dyslipidemia, than those who did not have MS, even though their blood glucose profile and [HbA.sub.1c] were comparable. This further explicit that diabetes with MS have clustering of more CV risk factors as compared to those without MS. This is further supported by NHANES survey (15). It will be interesting to observe in long term follow up the CV outcome in patients of diabetes with or without MS, as diabetes per se is considered as equivalent to one episode of myocardial infarction (29). This will also help in understanding the contribution of associated comorbidities for the CV outcome in patients with diabetes.

The modified NCEP-ATP III showed highest predictive ability to diagnose MS and it was least with IDF criteria. The difference could be attributed to the waist circumference as the primary inclusion criteria for diagnosis of MS by IDF classification. Therefore those subjects with DM who did not have central obesity were excluded for the diagnosis of MS. Among the various components of MS hypertriglyceridemia had the highest predictive ability for MS in men and low HDL-C in women. Literature is scarce in defining the predictive ability of different metabolic parameters to diagnose MS. A study by Kompoti et al (30) in patients with established diabetes showed increased serum triglyceride level was the strongest single predictor for MS in both men and women according to NCEP ATP-III classification. This is not surprising as hypertriglyceridemia is the most common and earliest lipid abnormalities in patients with DM. Ethnic differences have also been observed with hypertriglyceridemia in predicting insulin resistance in whites but not in blacks (31). Observation of a low HDL-C in women as a single most predictor to diagnose MS may be attributed to higher BMI, %BF and sedentary life style. These factors overshadowed the beneficial effects of estrogen as most of the women were perimenopausal.

The cut-off of 153 mg/dl for serum triglyceride in men had an optimal sensitivity and specificity which is marginally higher than the standard cut-off of 150 mg/dl. This may possibly be related to more preponderance of central obesity in Asian Indians as compared to Caucasians (19). The cut-off of 150 mg/dl for serum triglyceride in women had an optimal sensitivity and specificity, and it is in accordance with the standard levels. The cut-off for HDL-C in women of 50 mg/dl had an optimal sensitivity and specificity which is in accordance with the standard cut-off required to define MS. However, serum HDL-C level of 40 mg/dl in men had poor sensitivity to diagnose MS. Therefore, HDL-C in men as a single most predictor for diagnosing metabolic syndrome was weaker. The cut-off of 90 cm for the waist circumference in men displayed optimal sensitivity and specificity which is in accordance with the modified cut-off for Asian Indians. However, in women, the cut-off of 88 cm showed the optimal sensitivity and specificity of more than 70 per cent which is appreciably higher than the standard cut off of 80 cm. The mean waist circumference for women in this study group was 92 cm, which differ from the Caucasians and African American counterparts. A study from [ran has shown the waist cut-off of 91.5 cm in men and 85.5 cm in women had the highest sensitivity and specificity in predicting MS (32), Even a study from South India (10), a cutoff for waist circumference of 85 cm was considered rather than standard cut-off of 80 cm. We suggest that the commonly used definition to predict MS at least in present form requires modifications. As Asian Indians have higher truncal and abdominal fat mass compared with Caucasians and African American and abdominal obesity has been postulated as the leading modifiable cause of cardiovascular disease in Asia (33).

Despite various limitations including small sample size, inclusion of only native Punjabis and surrounding population of Chandigarh, this study shows that modified NCEP ATP-III criteria had a highest predictive ability to diagnose MS and increased triglyceride for men and low HDL-C in women was the strongest single predictor to recognize MS in newly detected T2DM. Larger studies are required to redefine the waist cut point for women to establish the risk of CV outcome.

In conclusion, the study results provide evidence that modified NCEP ATP III criteria was better than the other three criteria in identifying MS. The elevated serum triglyceride for men and serum HDL in women was the strongest single predictor, which effectively indicated the presence of MS in newly detected type 2 diabetes. The currently recommended cut points for waist circumference for the MS required some modifications for the better prediction.

Acknowledgment

The authors thank the Department of Science and Technology, SERC Division, Government of India, New Delhi, for the financial support.

Received March 19, 2008

References

(1.) Grundy SM. Hypertriglyceridemia, insulin resistance, and the metabolic syndrome. Am J Cardiol 1999; 83 : 25F-29F.

(2.) 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 : 356-9.

(3.) Hu G, Qiao Q, Tuomilehto J, Balkau B, Borch-Johnsen K, Pyorala K. DECODE Study Group. Prevalence of the metabolic syndrome and its relation to all-cause and cardiovascular mortality in nondiabetic European men and women. Arch Intern Med 2004; 164 : 1066-76.

(4.) Lin SX, Pi-Sunyer EX. Prevalence of the metabolic syndrome among US middle-aged and older adults with and without diabetes--a preliminary analysis of the NHANES 1999-2002 data. Ethn Dis 2007; 17 : 35-9.

(5.) Mohan V, Shanthirani CS, Deepa R. Glucose intolerance (diabetes and IGT) in a selected south Indian population with special reference to family history, obesity and lifestyle factors: the Chennai Urban Population Study (CUPS 14). J Assoc Physicians India 2003; 51 : 771-7.

(6.) Deepa R, Shanthirani CS, Premalatha G, Sastry NG, Mohan V. Prevalence of insulin resistance syndrome in a selected south Indian population- The Chennai urban population study-7 [CUPS-7]. Indian J Med Res 2002; 115 : 118-27.

(7.) Ramachandran A, Snehalatha C, Kapur A, Vijay V, Mohan V, Das AK, et al. Diabetes Epidemiology Study Group in India (DESI). High prevalence of diabetes and impaired glucose tolerance in India: National Urban Diabetes Survey. Diabetologia 2001; 44 : 1094-101.

(8.) Misra KB, Endemann SW, Ayer M. Leisure time physical activity and metabolic syndrome in Asian Indian immigrants residing in northern California. Ethn Dis 2005; 15 : 627-34.

(9.) Gupta R, Deedwania PC, Gupta A, Rastogi S, Panwar RB, Kothari K. Prevalence of metabolic syndrome in an Indian urban population. Int J Cardiol 2004; 97 : 257-61.

(10.) Ramachandran A, Snehalatha C, Satyavani K, Sivasankari S, Vijay V. Metabolic syndrome in urban Asian Indian adults--a population study using modified ATP III criteria. Diabetes Res Clin Practice 2003; 60 : 199-204.

(11.) Wasir JS, Misra A, Vikram NK, Pandey RM, Gupta R. Comparison of definitions of the metabolic syndrome in adult Asian Indians. J Assoc Physicians India 2008; 56: 158-64.

(12.) Centers for Disease Control and Prevention. Diabetes Surveillance Report, 1999. Atlanta, Ga: United States Department of Health and Human Services; 1999. Available at: http://www.ndep.nih.gov/campaigns/BeSmart/BeSmart_ overview.htm#. Accessed March 23, 2007.

(13.) Lehto S, Ronnemaa T, Haffner SM, Pyorala K, Kallio V, Laakso M. Dyslipidemia and hyperglycemia predict coronary heart disease events in middle-aged patients with NIDDM. Diabetes 1997; 46 : 1354-9.

(14.) Alexander CM, Landsman PB, Teutsch SM, Haffner SM. Third National Health and Nutrition Examination Survey (NHANES III); National Cholesterol Education Program (NCEP). NCEP-defined metabolic syndrome, diabetes, and prevalence of coronary heart disease among NHANES III participants age 50 years and older. Diabetes 2003; 52 : 1210-4.

(15.) Park YW, Zhu S, Palaniappan L, Heshka S, Camethon 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, 1988-1994. Arch Intern Med 2003; 163 : 427-36.

(16.) Enas EA, Yusuf S, Mehta JL. Prevalence of coronary artery disease in Asian Indians. Am J Cardiol 1992; 70 : 945-9.

(17.) Zimmet P, Magliano D, Matsuzawa Y, Alberti G, Shaw J. The metabolic syndrome: a global public health problem and a new definition. J Atheroscler Thromb 2005; 12 : 295-300.

(18.) Heng D, Ma S, Lee JJM, Tai BC, Mak KH, Hughes K, et al. Modification of the NCEPATP III definitions of the metabolic syndrome for use in Asians identifies individuals at risk of ischemic heart disease. Atherosclerosis 2006; 186 : 367-73.

(19.) Enas EA, Mohan V, Deepa M, Farooq S, Pazhoor S, Chennikkara H. The metabolic syndrome and dyslipidemia among Asian Indians: a population with high rates of diabetes and premature coronary artery disease. J Cardiometab Syndr 2007; 2 : 267-75.

(20.) Expert Panel on Detection, Evaluation, 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.

(21.) Trinder P. Determination of blood glucose using an oxidase-peroxidase system with a non-carcinogenic chromogen. J Clin Path 1969; 22 : 158-61.

(22.) Allain CC, Poon LS, Chan CS, Richmond W, Fu PC. Enzymatic determination of total serum cholesterol. Clin Chem 1974; 20 : 470-5.

(23.) Fossati P, Prencipe L. Serum triglycerides determined colorimetrically with an enzyme that produces hydrogen peroxide. Clin Chem 1982; 28 : 2077-80.

(24.) Lang PD, Schettler G. In: Schettler G, Gross R.Arteriosklerose, Grundlageon-Diagnostik-Therapie. Deutscher Arzte Verlag GmbH. Cologne/W.Germany; 1985.

(25.) Resnick HE, Harris MI, Brock DB, Harris TB. American Diabetes Association diabetes diagnostic criteria, advancing age, and cardiovascular disease risk profiles: results from the Third National Health and Nutrition Examination Survey. Diabetes Care 2000; 23 : 176-80.

(26.) Hanley JA, McNeil BJ. The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology 1982; 143 : 29-36.

(27.) Perkins NJ, Schisterman EF. The inconsistency of "optimal" cutpoints obtained using two criteria based on the receiver operating characteristic curve. Am J Epidemiol 2006; 163 : 670-5.

(28.) Hsieh CH, Pei D, Hung Y J, Kuo SW, He CT, Lee CH, et al. Identifying subjects with insulin resistance by using the modified criteria of metabolic syndrome. J Korean Med Sci 2008; 23 : 465-9.

(29.) Rosenzweig JL, Ferrannini E, Grundy SM, Haffner SM, Heine R J, Horton ES, et al. Primary prevention of cardiovascular disease and type 2 diabetes in patients at metabolic risk: an endocrine society clinical practice guideline. J Clin Endocrinol Metab 2008; 29: 3671-89.

(30.) Kompoti M, Mariolis A, Alevizos A, Kyrazis I, Protopsaltis I, Dimou E, et al. Elevated serum triglycerides is the strongest single indicator for the presence of metabolic syndrome in patients with type 2 diabetes. Cardiovasc Diabetol 2006; 5 : 2105.

(31.) Sumner AE. The relationship of body fat to metabolic disease: influence of sex and ethnicity. Gend Med 2008; 5 : 361-71.

(32.) Esteghamati A, Ashraf H, Rashidi A, Meysamie A. Waist circumference cut-off points for the diagnosis of metabolic syndrome in Iranian adults. Diabetes Res Clin Pract 2008; 82 : 104-7.

(33.) Mohan V, Deepa R. Obesity and abdominal obesity in Asian Indians. Indian J Med Res 2006; 123 : 593-6.

Reprint requests: Prof. Anil Bhansali, Head, Department of Endocrinology., Postgraduate Institute of Medical Education & Research Chandigarh 160 012, India e-mail: anilbhansali_endocrine@rediffmail.com

Ethiraj Dhanaraj *,**, Anil Bhansali (-), Shallu Jaggi (+), Pinaki Dutta (+), Shikha Jain (+), Pramil Tiwari ** & Poduri Ramarao *

Departments of * Pharmacology & Toxicology, & ** Pharmacy Practice, National Institute of Pharmaceutical Education & Research, Mohali, Punjab & (+) Department of Endocrinology, Postgraduate Institute of Medical Education & Research, Chandigarh, India
Table 1. Diagnosis of metabolic syndrome as per different criteria

NCEP-ATP III                                  Modified
                                            NCEP-ATP III

Presence of > 3 of                  Presence of [greater than or
the following:                      equal to] 3 of the following:

(i) Waist circumference (>102 cm    (i) Waist circumference
in men, >88 cm in women)            (>90 cm in men, >80 cm in
(ii) SBP >130 mmHg and/or           women)
DBP >85 mmHg or medical             (ii) SBP [greater than or
treatment of previously diagnosed   equal to] 130 mmHg and/or
hypertension                        DBP [greater than or
(iii) TG >150 mg/dl (1.7 mmol/1)    equal to] 85 mmHg or medical
(iv) HDL-C <40 mg/dl (1.03          treatment of previously
mmol/1) in men, <50 mg/dl (1.29     diagnosed hypertension
mmol/1) in women                    (iii) TG [greater than or
(v) Fasting glucose >110 mg/dl      equal to] 150 mg/dl
                                    (iv) HDL-C <40 mg/dl in
                                    men, <50 mg/dl in women
                                    (v) Fasting glucose >110
                                    mg/dl

      Modified WHO                              IDF
(Microalbuminuria was
      excluded)

Presence of diabetes and      Presence of central obesity with waist
[greater than or equal        circumference >90 cm (men) and >80 cm
to] 2 of the following:       (women) plus any 2 of the following:
(i) BMI >30 kg/[m.sup.2] or   (i) TG >150 mg/dl or specific treatment
WHR >0.9 for men >0.85        for this lipid abnormality
for women                     (ii) HDL-C <40 mg/dl (men), <50 mg/dl
(ii) TG [greater than or      (women) or specific treatment for this
equal to] 150 mg/dl           lipid abnormality
(1.7 mmol/1) or HDL-C         (iii) SBP >130 mmHg and/or DBP >85
<35 mg/dl (0.9 mmol/1)        mmHg or medical treatment for previously
for men <39 mg/dl (1.0        diagnosed hypertension
mmol/1) for women             (iv) Fasting plasma glucose (>100 mg/dl)
(iii) BP [greater than or     or previously diagnosed type 2 diabetes
equal to] 140/90 mmHg
or medication

NCEP-ATP III, National Cholesterol Education Program Adult Treatment
Panel III; WHO, World Health Organization; IDF, International
Diabetes Federation; TG, triglyceride; HDL-C, high-density lipoprotein
cholesterol; SBP, systolic blood pressure; DBP, diastolic blood
pressure; WHR, Waist Hip ratio

Table II. Presence of components of metabolic syndrome in newly
detected T2DM

Variable                          Men          Women
                                (n=266)       (n=297)
Waist circumference
(Men >102 cm; Women >88 cm)   49 (18.42)    179 (60.26)
(Men >90 cm; Women >80 cm)    145 (54.51)   250 (84.17)
Hypertension                  154 (57.89)   191 (64.30)
Elevated triglyceride (>150   127 (47.74)   129 (43.43)
mg/dl)
Low HDL cholesterol
(Men <40 mg/dl; Women         72 (27.06)    159 (53.53)
<50 mg/dl)

Values in parentheses are percentages

Table III. Baseline characteristics in newly detected type 2
diabetes individuals with MS and without MS by modified NCEP-ATP
criteria

Variable                   DM with MS                   DM
                            (n=382)                 without MS
                                                      (n=181)

Age (Yr)               49.94 [+ or -] 10.85     49.14 [+ or -] 10.73
Weight (kg)          71.57 [+ or -] 13.80 *     61.99 [+ or -] 12.52
Height (cm)            159.25 [+ or -] 8.97     160.65 [+ or -] 9.24
BMI (kg/[m.sup.2])    28.26 [+ or -] 5.05 *      24.01 [+ or -] 4.43
Waist (cm)           95.27 [+ or -] 11.39 *     85.02 [+ or -] 10.94
Hip (cm)            100.02 [+ or -] 10.07 *      92.16 [+ or -] 8.59
WHR                    0.95 [+ or -] 0.08 *       0.92 [+ or -] 0.07
SBP (mm Hg)         132.69 [+ or -] 17.66 *    119.29 [+ or -] 13.51
DBP (mm Hg)          85.89 [+ or -] 11.33 *      78.63 [+ or -] 7.66
%BF                   35.07 [+ or -] 7.94 *      27.78 [+ or -] 7.23
FPG                   199.29 [+ or -] 72.63    211.67 [+ or -] 82.26
PPG                   277.42 [+ or -] 87.08   281.15 [+ or -] 103.15
[HbA.sub.1c]             8.62 [+ or -] 1.95       8.34 [+ or -] 1.87
TCh (mg/dl)         198.16 [+ or -] 45.21 *    181.80 [+ or -] 35.25
HDL-C (mg/dl)         43.03 [+ or -] 9.28 *      48.36 [+ or -] 9.11
LDL-C (mg/dl)         113.10 [+ or -] 37.98    103.57 [+ or -] 30.58
TG (mg/dl)          200.18 [+ or -] 97.95 *    129.44 [+ or -] 49.47

* P<0.001 compared to T2DM patients without MS.

DM, Diabetes mellitus; MS, metabolic syndrome; NCEP-ATP III,
National Cholesterol Education Program Adult Treatment Panel
III; BMI, body mass Index; WHR: Waist Hip ratio; SBP, systolic
blood pressure; DBP, diastolic blood pressure; %BF, per cent
body fat; FPG, fasting plasma glucose; PPG, postprandial plasma
glucose; [HbA.sub.1c], glycated haemoglobin C; Tch, total cholesterol;
HDL-C, high density lipoprotein cholesterol; LDL-C: low density
lipoprotein cholesterol; TG, triglyceride

Table IV. Area under the ROC curve of TG, HDL-C, and waist
circumference

Variable       NCEP ATP-III       Modified NCEP ATP-III
              ROC curve area         ROC curve area
                 (95% CI)               (95% CI)
TG:
  Overall   0.737 (0.688-0.785)   0.776 (0.728-0.824)
  Men       0.805 (0.746-0.864)   0.824 (0.768-0.881)
  Women     0.715 (0.634-0.795)   0.760 (0.676-0.843)
HDL-C:
  Men       0.700 (0.628-0.773)   0.656 (0.584-0.728)
  Women     0.795 (0.723-0.867)   0.846 (0.778-0.914)
Waist:
  Men       0.724 (0.659-0.790)   0.807 (0.754-0.860)
  Women     0.757 (0.697-0.817)   0.722 (0.647-0.797)

Variable       Modified WHO               IDF
              ROC curve area        ROC curve area
                 (95% CI)              (95% CI)
TG:
  Overall   0.806 (0.761-0.852)   0.638 (0.583-0.692)
  Men       0.859 (0.803-0.915)   0.666 (0.594-0.738)
  Women     0.750 (0.677-0.823)   0.639(0.545-0.734)
HDL-C:
  Men       0.591 (0.514-0.668)   0.530 (0.452-0.608)
  Women     0.669 (0.588-0.749)   0.668 (0.577-0.760)
Waist:
  Men       0.735 (0.673-0.797)           --
  Women     0.650 (0.580-0.719)           --

ROC, Receiver operating characteristic; TG, triglyceride; HDL-C,
high density lipoprotein cholesterol; NCEP-ATP Ill, National
Cholesterol  Education Program Adult Treatment Panel 111; WHO, World
Health Organization; IDF, International Diabetes Federation; TG,
triglyceride; HDL-C, high density lipoprotein cholesterol

Table V. TG cut-of with sensitivity, specificity, PPV, NPV of MS
diagnosis according to different criteria

Optimal cut point           NCEP-ATP III

                      SEN    SPE    PPV    NPV
TG-all (mg/dl)
147                   72.1   69.8   81.5   57.5
155
TG-men (mg/dl)
153
154                   83.8   72.3   73.9   82.6
170
TG-women (mg/dl)
136
140                   70.9   70.2   90.5   37.5
149
HDL-C men (mg/dl)
40                    54.9   85.5   77.7   67.1
44
47
HDL-C women (mg/dl)
47.6
47
50                    80.1   76.7   93.7   47.1
Waist-men (Cm)
90
96.8                  55.5   85.8   73.4   73.0
Waist-women (Cm)
84
88                    73.6   71.3   85.9   52.9

Optimal cut point       Modified NCEP-ATP III

                      SEN    SPE    PPV    NPV
TG-all (mg/dl)
147                   69.7   69.7   90.3   47.1
155
TG-men (mg/dl)
153
154                   78.2   82.1   87.3   70.4
170
TG-women (mg/dl)
136                   65.9   75.0   94.8   30.0
140
149
HDL-C men (mg/dl)
40                    46.5   85.5   83.3   50.7
44
47
HDL-C women (mg/dl)
47.6
47
50                    77.1   85.7   97.4   34.2
Waist-men (Cm)
90                    78.0   76.5   81.2   72.7
96.8
Waist-women (Cm)
84                    83.5   53.8   86.4   47.9
88

Optimal cut point           Modified WHO

                      SEN    SPE    PPV    NPV
TG-all (mg/dl)
147                   73.0   82.7   91.5   54.4
155
TG-men (mg/dl)
153                   78.9   92.9   95.8   67.7
154
170
TG-women (mg/dl)
136
140
149                   65.9   78.9   90.7   42.4
HDL-C men (mg/dl)
40
44                    57.6   52.9   72.1   37.1
47
HDL-C women (mg/dl)
47.6                  65.3   58.5   83.9   33.7
47
50
Waist-men (Cm)
90
96.8
Waist-women (Cm)
84
88

Optimal cut point                IDF

                      SEN    SPE    PPV    NPV
TG-all (mg/dl)
147
155                   59.7   61.8   74.7   44.7
TG-men (mg/dl)
153
154
170                   59.3   69.7   65.9   63.3
TG-women (mg/dl)
136                   71.6   56.5   87.1   32.5
140
149
HDL-C men (mg/dl)
40
44
47                    72.4   36.4   52.7   57.3
HDL-C women (mg/dl)
47.6
47                    65.8   61.9   88.4   28.8
50
Waist-men (Cm)
90
96.8
Waist-women (Cm)
84
88

SEN, Sensitivity; SPE, specificity; PPV, positive predictive
value; NPV, negative predictive value
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