European Journal of Cardiovascular Medicine

Type 2 diabetes mellitus (T2DM) is a chronic metabolic disorder characterized by hyperglycemia resulting from insulin resistance, impaired insulin secretion, or a combination of both. Over recent decades, T2DM has emerged as one of the most significant global public health challenges, with rapidly increasing prevalence driven by urbanization, sedentary lifestyles, obesity, and dietary transitions. According to the International Diabetes Federation (IDF), approximately 463 million adults worldwide were living with diabetes in 2019, and this number is projected to rise to 578 million by 2030 and 700 million by 2045, with the majority of cases occurring in low- and middle-income countries [1].

Metabolic syndrome (MetS) represents a cluster of interrelated cardiovascular risk factors that include central obesity, hypertension, dyslipidaemia, and impaired glucose metabolism. The syndrome is strongly associated with insulin resistance and is recognized as a major precursor for both T2DM and cardiovascular disease (CVD) [2-3]. Various organizations, including the World Health Organization (WHO), National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III), and the International Diabetes Federation (IDF), have proposed diagnostic criteria for MetS, all emphasizing the central role of abdominal obesity and insulin resistance [4-5].

The interrelationship between T2DM and metabolic syndrome is well established. Insulin resistance acts as a common pathophysiological link, contributing to hyperglycemia, dyslipidaemia, hypertension, and pro-inflammatory states.⁸⁻¹⁰ Individuals with metabolic syndrome are reported to have a nearly five-fold increased risk of developing T2DM, while a substantial proportion of patients with established T2DM fulfill diagnostic criteria for MetS [6-7]. The coexistence of these conditions markedly increases the risk of macrovascular complications such as coronary artery disease, stroke, and peripheral vascular disease, thereby significantly contributing to morbidity and mortality [8].

India bears a disproportionate burden of both diabetes and metabolic syndrome. Rapid socioeconomic transitions, urbanization, and genetic susceptibility have resulted in high prevalence rates of central obesity and insulin resistance among the Indian population [9-10]. Several Indian studies have reported a high prevalence of metabolic syndrome among patients with T2DM, ranging from 50% to over 75%, depending on the diagnostic criteria used [11-12]. Despite this, data from tertiary care settings remain limited, particularly regarding the association of metabolic syndrome with demographic, anthropometric, and biochemical parameters.

Tertiary care hospitals cater to patients with advanced disease, multiple comorbidities, and prolonged duration of diabetes, providing an ideal setting to evaluate the complex interaction between T2DM and metabolic syndrome. Understanding this association in such settings can facilitate early identification of high-risk individuals and enable targeted interventions focusing on modifiable risk factors such as obesity, central adiposity, and lifestyle behaviors [13].

In this context, the present study was undertaken to evaluate the association between type 2 diabetes mellitus and metabolic syndrome in patients attending a tertiary care hospital, and to assess the relationship of metabolic syndrome with various clinical, anthropometric, and biochemical parameters.

AIMS AND OBJECTIVES

To study the prevalence of metabolic syndrome and association between type 2 diabetes mellitus and metabolic syndrome in a tertiary care hospital. Correlate demographic, lifestyle factors, anthropometric and biochemical parameters with metabolic syndrome in patients with T2DM.

Study Design and Setting: This was a hospital-based cross-sectional study conducted in the Department of General Medicine of a tertiary care teaching hospital, over a period of 12 months after obtaining approval from the Institutional Ethics Committee.

Sample Size: Based on a reported prevalence of metabolic syndrome of 78% among patients with T2DM, the minimum sample size calculated was 70 patients.

Inclusion Criteria

• Age >35 years
• Diagnosed cases of type 2 diabetes mellitus
• Patients who provided informed consent

Exclusion Criteria

• Type 1 diabetes mellitus
• Gestational diabetes mellitus
• Patients unwilling to participate

Data Collection: Data were collected using a pre-designed and pre-tested proforma. Detailed history regarding demographic variables, smoking and alcohol consumption, duration of diabetes, hypertension, and dyslipidaemia was obtained.

Following clinical and anthropometric assessment were done

• Height, weight, body mass index (BMI)
• Waist circumference, hip circumference, waist–hip ratio
• Blood pressure measurement

Laboratory Investigations

• Fasting blood sugar (FBS)
• Postprandial blood sugar (PPBS)
• HbA1c
• Lipid profile
• Liver function tests (AST, ALT, ALP)

Statistical Analysis: Data were analysed using SPSS version 21. Continuous variables were expressed as mean ± standard deviation and categorical variables as frequencies and percentages. Student’s t-test and chi-square test were used as appropriate. A p-value <0.05 was considered statistically significant

A total of 70 patients with type 2 diabetes mellitus were included, of whom 46 were males and 24 females. The mean age was 52.2±5.6 years. Metabolic syndrome was present in 39 patients (55.7%).

Table 1: Comparison of mean Age and genders among type 2 DM patients

Graph 1: Association between Metabolic Syndrome and Area of Residence

No significant association was found between MetS and age, gender, area of residence, or alcohol consumption. Smoking status showed a statistically significant association with MetS (p=0.048).

Table 2: Association between life style factors and metabolic syndrome

Patients with MetS had significantly higher BMI, waist circumference, hip circumference, and waist–hip ratio compared to those without MetS

Table 3: Comparison of anthropometric parameters between metabolic syndrome

Fasting blood sugar levels were also significantly higher in the MetS group. However, PPBS, HbA1c, duration of diabetes, hypertension, dyslipidaemia, and liver enzymes (AST, ALT, ALP) did not show significant differences between the two groups.

Table 4: Comparison of Duration of Comorbidities between MetS Groups

Table 5: Comparison of Glycaemic Parameters between MetS Groups

Table 6: Comparison of Liver Enzymes between MetS Groups

The present hospital-based cross-sectional study demonstrates a high prevalence of metabolic syndrome (MetS) among patients with type 2 diabetes mellitus (T2DM), with more than half (55.7%) of the study population fulfilling the diagnostic criteria. This finding reinforces the close pathophysiological relationship between T2DM and MetS and is consistent with earlier Indian and international studies reporting prevalence rates ranging from 50% to 75% among individuals with established diabetes.

The observed prevalence of MetS in this study is comparable to that reported by Rani et al. and Gupta et al., who documented a high burden of MetS among Indian patients with T2DM and urban populations, respectively [14,15]. Variations in prevalence across studies may be attributed to differences in diagnostic criteria used, ethnic susceptibility, lifestyle patterns, and healthcare-seeking behavior of the study populations. Asian Indians are known to have a higher tendency toward insulin resistance and central obesity even at lower body mass indices, which may partly explain the high coexistence of MetS with T2DM [16].

In the present study, no significant association was observed between MetS and age or gender. Similar findings have been reported in several Indian studies, suggesting that once diabetes is established, the clustering of metabolic risk factors may occur relatively independent of age and sex [11]. The lack of association with area of residence may reflect the increasing penetration of urban lifestyle factors, such as physical inactivity and dietary changes, into rural settings.

Lifestyle factors showed a mixed pattern of association with MetS. Smoking status was significantly associated with MetS, highlighting the contributory role of tobacco use in worsening insulin resistance and promoting a pro-inflammatory state. Smoking has been shown to aggravate central adiposity and dyslipidaemia, thereby accelerating the development of MetS and cardiovascular disease in patients with diabetes [17, 18]. Alcohol intake, however, did not show a significant association, which may be due to variability in quantity, duration, and reporting of alcohol consumption among participants.

Anthropometric parameters emerged as the strongest correlates of MetS in this study. Patients with MetS had significantly higher BMI, waist circumference, hip circumference, and waist–hip ratio compared to those without MetS. Central obesity is a core component of MetS and a key driver of insulin resistance, particularly in South Asian populations [9,10]. The strong association observed in the present study underscores the importance of simple anthropometric measures as effective screening tools for identifying high-risk individuals in routine clinical practice.

Among biochemical parameters, fasting blood sugar (FBS) was significantly higher in patients with MetS, whereas postprandial blood sugar (PPBS) and HbA1c did not differ significantly between the two groups. This suggests that fasting hyperglycemia may be more closely linked to the metabolic disturbances associated with MetS, possibly reflecting hepatic insulin resistance. Similar observations have been reported by Gupta A, et al [19] and Srivastava AK et al [20, who emphasized the role of insulin resistance and impaired fasting glucose in the pathogenesis of MetS and its cardiovascular sequelae.

The absence of a significant association between MetS and duration of diabetes, hypertension, or dyslipidaemia in this study may indicate that the clustering of metabolic risk factors occurs early in the course of diabetes. Additionally, liver enzymes did not show a statistically significant difference between the two groups, although ALP levels tended to be higher in patients with MetS. This may warrant further investigation with larger sample sizes, as non-alcoholic fatty liver disease is increasingly recognized as a hepatic manifestation of MetS.

Overall, the findings of this study highlight the substantial burden of metabolic syndrome among patients with T2DM in a tertiary care setting. Obesity and central adiposity remain the most important modifiable risk factors, emphasizing the need for early identification and comprehensive management strategies. Lifestyle modification focusing on weight reduction, smoking cessation, and regular physical activity, along with optimal glycaemic control, should be integral components of diabetes care to reduce future cardiovascular morbidity and mortality.

Metabolic syndrome is highly prevalent among patients with type 2 diabetes mellitus in a tertiary care setting. Obesity and central adiposity are the strongest correlates of MetS. Early identification and aggressive management of metabolic syndrome components, particularly weight reduction and lifestyle modification, should be an integral part of diabetes care to reduce cardiovascular risk

1. International Diabetes Federation. IDF Diabetes Atlas. 9th ed. Brussels: International Diabetes Federation; 2019.
2. Eckel RH, Grundy SM, Zimmet PZ. The metabolic syndrome. Lancet. 2005; 365(9468):1415-28.
3. Alberti KGMM, Zimmet P, Shaw J. Metabolic syndrome—a new worldwide definition. Diabet Med. 2006; 23(5):469-80.
4. National Cholesterol Education Program (NCEP). Third report of the NCEP Expert Panel. Circulation. 2002; 106:3143-421.
5. Alberti KGMM, Eckel RH, Grundy SM, et al. Harmonizing the metabolic syndrome. Circulation. 2009; 120(16):1640-45.
6. Kahn R, Buse J, Ferrannini E, Stern M. The metabolic syndrome: time for a critical appraisal. Diabetes Care. 2005; 28(9):2289-304.
7. Ford ES. Risks for all-cause mortality, cardiovascular disease, and diabetes associated with the metabolic syndrome. Diabetes Care. 2005; 28(7):1769-78.
8. Wilson PW, D’Agostino RB, Parise H, Sullivan L, Meigs JB. Metabolic syndrome as a precursor of cardiovascular disease and type 2 diabetes mellitus. Circulation. 2005; 112:3066-72.
9. Mohan V, Deepa R. Obesity and abdominal obesity in Asian Indians. Indian J Med Res. 2006; 123:593-96.
10. Misra A, Khurana L. Obesity and the metabolic syndrome in developing countries. J Clin Endocrinol Metab. 2008; 93(Suppl 1):S9-30.
11. Tripathy JP, Thakur JS, Jeet G, et al. Prevalence and determinants of metabolic syndrome in India. Diabetes Metab Syndr. 2018; 12(6):955-61.
12. Cameron AJ, Shaw JE, Zimmet PZ. The metabolic syndrome: prevalence in worldwide populations. Endocrinol Metab Clin North Am. 2004; 33(2):351–75.
13. Grundy SM. Metabolic syndrome pandemic. Arterioscler Thromb Vasc Biol. 2008;28 (4): 629–36.
14. Rani HS, Madhavi G, Rao VR, et al. Prevalence of metabolic syndrome in type 2 diabetes mellitus. J Assoc Physicians India. 2010; 58:152-56.
15. Gupta R, Deedwania PC, Gupta A, et al. Prevalence of metabolic syndrome in an Indian urban population. Int J Cardiol. 2004; 97:257-61.
16. Reaven GM. Insulin resistance: the link between obesity and cardiovascular disease. Med Clin North Am. 2011; 95(5):875–92.
17. Yadav D, Mahajan S, Subramanian SK, Bisen PS, Chung CH, Prasad GBKS. Prevalence of metabolic syndrome in type 2 diabetes mellitus using NCEP-ATP III and IDF criteria and its association with cardiovascular risk factors. J Diabetes Complications. 2013; 27(2):172–77.
18. 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. Indian J Med Res. 2002; 115:118–27.
19. Gupta A, Gupta R, Sarna M, Rastogi S, Gupta VP, Kothari K. Prevalence of diabetes, impaired fasting glucose and insulin resistance syndrome in an urban Indian population. Diabetes Res Clin Pract. 2003; 61(1):69–76.
20. Srivastava AK, Gupta A, Mathur P. Lifestyle risk factors and metabolic syndrome in type 2 diabetes mellitus. Indian J Endocrinol Metab. 2014; 18(6):838–42.