Open Access

Prevalence of Metabolic Syndrome and its influence on microvascular complications in the Indian population with Type 2 Diabetes Mellitus. Sankara Nethralaya Diabetic Retinopathy Epidemiology And Molecular Genetic Study (SN-DREAMS, report 14)

  • Rajiv Raman1,
  • Aditi Gupta1,
  • Swakshyar S Pal1,
  • Suganeswari Ganesan1,
  • Kadri Venkatesh1,
  • Vaitheeswaran Kulothungan2 and
  • Tarun Sharma1Email author
Diabetology & Metabolic Syndrome20102:67

https://doi.org/10.1186/1758-5996-2-67

Received: 26 February 2010

Accepted: 11 November 2010

Published: 11 November 2010

Abstract

Background

The Metabolic syndrome (MS) consists of central obesity, glucose intolerance, hyperinsulinemia, low high density lipoproteins, high triglycerides and hypertension. Different studies have observed that MS causes microvascular complications in patients with type 2 diabetes. The aim of the study was to find out the prevalence of MS in the Indian population with type 2 diabetes mellitus in relation to gender, duration of diabetes, and to evaluate the influence of MS and its individual components on microvascular complications such as diabetic retinopathy, diabetic nephropathy and diabetic neuropathy.

Methods

A population-based cross sectional survey was conducted with 1414 patients having type 2 diabetes mellitus. The International Diabetes Federation (IDF) criteria were used to identify the metabolic syndrome. Diabetic retinopathy was graded using the stereoscopic digital fundus photography. Neuropathy was assessed by measuring the vibration perception threshold through a sensitometer. Nephropathy was diagnosed by the presence of microalbuminuria in the first morning urine sample.

Results

The age and gender adjusted prevalence of MS, using the IDF criteria, in the South Indian population was 73.3%. The prevalence was higher in women (83.3%), compared to men (65.3%). In subjects with diabetes mellitus, without and with MS, the prevalence of retinopathy was 21.3% and 16.9% (p = 0.057); prevalence of nephropathy was 20.5% and 18.0% (p = 0.296), and prevalence of neuropathy was17.2% and 19.4% (p = 0.353) respectively. Overall and in women, the clustering of MS components led to an increase in the prevalence of diabetic nephropathy. The prevalence of retinopathy and neuropathy in MS subjects, who had diabetes for < 10 years, was more in both men and women; it was more in women but not in men when the duration of diabetes varied from 11-20 years.

Conclusions

The association of MS with microangiopathies decreased with an increase in the duration of diabetes. MS behaved differently in men and women. It may need to be managed differently in the two groups.

Background

The Metabolic Syndrome (MS) is a constellation of central obesity, glucose intolerance, hyperinsulinemia, low high density lipoproteins (HDL), high triglycerides and hypertension [1]. It is associated with a high risk of coronary heart disease (CHD) and premature mortality [2]. Besides resulting in macrovascular complications, there is growing evidence that MS, like diabetes mellitus, causes microvascular complications in patients with type 2 diabetes mellitus [35]. Nearly 70-80% of the population with diabetes mellitus is diagnosed with MS [68].

The correlation between MS and macro- and microvascular complications, in patients with diabetes mellitus, has been shown previously in American and European subjects [911]. The data in the Asian population is scanty and controversial. In Japan, the Funagata Study observed that MS, using the definition of the International Diabetes Federation (IDF), was associated with microvascular changes in the retina [12]. However, Terauchi et al[13] found that neither the presence of MS (as defined by the IDF guideline) nor an increased waist circumference increased the risk of micro- or macrovascular complications in Japanese patients with type 2 diabetes mellitus.

The Asian population is somewhat different from the Caucasian population. The incidence of CHD and the absolute risk of death from CHD, at the same level of blood pressure, is lower in Asians, more so in populations with diabetes [14, 15]. The prevalence of obesity and its impact on cardiovascular disease is also different in Asians, compared to Caucasians [16].

The present population-based study aims to find out the prevalence of MS in the Indian population with type 2 diabetes mellitus in relation to gender, duration of diabetes, and to evaluate the influence of MS and its individual components on microvascular complications such as diabetic retinopathy (DR), diabetic nephropathy and diabetic neuropathy.

Methods

The sample population was recruited from the SN-DREAMS 1 study which was a population-based cross-sectional study. The methodology has been described elsewhere [17]. The study population was selected by multistage systematic random sampling. The sampling was done in two stages: selection of divisions using computer generated random numbers, and selection of study subjects randomly from each selected division. A target sample size was calculated based on the following assumptions: the prevalence of diabetic retinopathy was assumed to be 1.3%, with a relative precision of 25%, a drop out rate of 20% and a design effect of 2. The sampling was stratified based on the socio-economic criteria. Ten divisions were selected and 600 individuals were enumerated from each division to meet the target. Thus, 5830 subjects from the general population aged ≥ 40 years were enumerated.

Of the 5830 subjects enumerated, 1414 subjects with diabetes (both known and newly diagnosed) were analyzed for the study (the response rate for the first fasting blood sugar estimation was 96.20%; the response rate for the base hospital examination was 85.60%; 8.7% were non-diabetic, after the second blood sugar estimation, and 0.78% retinal images were un-gradable). Subjects with diabetes were identified based on the American Diabetes Association criteria and they underwent a detailed examination at the base hospital [18].

After eight hours of overnight fasting, the fasting blood sample was taken to estimate the plasma glucose and serum lipids. For those with provisional diabetes, confirmation of diabetes was done by re-estimation of fasting blood glucose by enzymatic assay; glucose was oxidized by glucose oxidase to produce gluconate and hydrogen peroxide, which was then detected photometrically. A biochemical analysis was done on Merck Micro Lab 120, semi automated analyzer. The total serum cholesterol (CHOD-POD method), HDL (after protein precipitation CHOD-POD method) and serum triglycerides (CHOD-POD) were estimated.

Anthropometric measurements including weight, height, waist and hip measurements were obtained using standardized techniques. The blood pressure was recorded, in the sitting position, in the right arm to the nearest 2 mm Hg using the mercury sphygmomanometer (Diamond Deluxe BP apparatus, Pune, India). Two readings were taken, five minutes apart, and their mean was taken as the blood pressure.

The study was approved by the Institutional Review Board, and a written informed consent was obtained from the subjects as per the Helsinki declaration [19].

Definitions

Metabolic syndrome

MS was defined using the International Diabetes Federation (IDF) consensus group guidelines as abdominal obesity (waist circumference ≥ 90 cm for men and ≥ 80 cm for women) plus two or more of the following risk factors: blood pressure ≥ 130/85 mm Hg, fasting plasma glucose ≥ 5.6 mmol/l (100 mg/dl) or pre-existing diabetes, serum triglycerides ≥ 1.7 mmol/l (≥ 150 mg/l) and HDL levels < 1.03 mmol/l (< 40 mg/dl) for men and < 1.29 mmol/l (< 50 mg/dl) for women [20].

Diabetic Retinopathy

All patients had their fundi photographed using the 45° four-field stereoscopic digital photography. The diagnosis of DR was based on the modified Klein classification (Modified Early Treatment Diabetic Retinopathy Study scales) [21]. DR was divided into mild, moderate and severe non-proliferative diabetic retinopathy (NPDR) and proliferative diabetic retinopathy (PDR); clinically significant macular edema (CSME) was graded as absent or present [22]. This grading was done by two independent observers in a masked fashion; the grading agreement was high (k = 0.83) [17].

Diabetic Nephropathy

The microalbuminuria was estimated, using the first morning urine sample, by a semi-quantitative procedure (Clintek 50 Bayer Urine Analyzer). Subjects were considered to have microalbuminuria, if the Albumin Creatinine Ratio (ACR) was between 30 and 299 mg/g [23].

Diabetic Neuropathy

Diabetic neuropathy assessment was done by measuring the Vibration Perception Threshold (VPT) using a sensitometer. The VPT was measured, by a single observer, by placing a biothesiometer probe perpendicular to the distal plantar surface of the great toe of both the legs. The VPT was measured at a voltage level when the patient felt the first vibration sensation. The mean VPT measure of the three readings, of both the legs, was considered for the analysis. The presence of diabetic neuropathy was considered if the VPT value was > 20 V [24].

Statistical analysis

A computerized database was created for all the records. A statistical package for the Social Sciences-SPSS (version 9.0) was used for statistical analysis. All the data were expressed as mean ± S.D or as percentage. The statistical significance was assumed at p value ≤ 0.05. Univariate and multivariate logistic regression analyses were performed to elucidate the risk factors for microangiopathies. The Odds Ratio (OR), with 95% confidence intervals, was calculated for the studied variables.

Results

The prevalence of MS in our subjects, with type 2 diabetes mellitus, was 73.8% (95% CI 71.5-76.0); the age and gender adjusted prevalence being 73.3% (95% CI 73.2-73.3). The prevalence was higher in women 83.3% (95% CI 80.4-86.1) compared to men 65.3% (95% CI 61.9-68.7). Table 1 shows the prevalence of MS in relation to gender and the duration of diabetes in subjects with type 2 diabetes mellitus. The prevalence of MS in men decreased with an increase in the duration of diabetes (67.4%, 59.7% and 39.1% in duration < 10 years, 10-20 years and > 20 years respectively, trend p = 0.002) whereas it remained almost similar in women (83.8%, 79.1% and 81.8%, trend p = 0.401).
Table 1

Prevalence of Metabolic Syndrome in relation to gender and duration of Diabetes in the study population

Duration of Diabetes

Prevalence of Metabolic Syndrome

 

(Years)

n

%

(95% CI)

Trend p

Overall

    

0-10

(N = 1194)

901

75.5

[73.0-77.9]

0.0002

11-20

(N = 186)

124

66.7

[59.9-73.4]

 

> 20

(N = 34)

18

52.9

[36.2-69.7]

 

Total (N = 1414)

1043

73.8

[71.5-76.0]

 

Men

    

0-10 (N = 608)

410

67.4

[63.7-71.2]

0.002

11-20

(N = 119)

71

59.7

[50.8-68.5]

 

> 20

(N = 23)

9

39.1

[19.2-59.1]

 

Total

(N = 750)

490

65.3

[61.9-68.7]

 

Women

    

0-10 (N = 586)

491

83.8

[80.8-86.8]

0.401

11-20

(N = 67)

53

79.1

[69.4-88.8]

 

> 20

(N = 11)

9

81.8

[59.0-104.6]

 

Total

(N = 664)

553

83.3

[80.4-86.1]

 

N, Total population; n, Population with metabolic syndrome.

Table 2 shows the age and gender adjusted prevalence of individual components of MS in subjects with type 2 diabetes mellitus. The prevalence of increased waist circumference was 75.5% (95% CI 75.4-75.6); of hypertension, 75.3%, (95% CI 75.2-75.3%); of elevated serum triglycerides, 37.5% (95% CI 37.5-37.6); and of reduced serum HDL, 71.3% (95% CI 71.2-71.3%).
Table 2

Prevalence of individual components of Metabolic Syndrome

 

Prevalence of Metabolic Syndrome

Components

N

n

% *

[95% of CI]*

Increased Waist circumference

1414

1077

75.5

[75.4-75.6]

Hypertension

1414

1026

75.3

[75.2-75.3]

Elevated serum triglyceride

1414

547

37.5

[37.5-37.6]

Reduced serum HDL-Cholesterol

1414

1026

71.3

[71.2-71.3]

>N, Total population; n, Population with metabolic syndrome;

Age and gender adjusted

Table 3 shows the baseline demographic and laboratory characteristics of the study population. Overall, subjects with MS had a higher serum non HDL cholesterol (p = 0.029). However, they had lesser duration of diabetes than those without MS (p < 0.0001). On evaluating men and women separately, men with MS showed similar findings except for a raised level of hemoglobin in subjects with MS (p = 0.013). But in women with MS, the duration of diabetes and serum non HDL cholesterol were not significantly different (p = 0.084 and 0.488 respectively), and the levels of total serum cholesterol and LDL cholesterol were lower when compared to subjects without MS (p = 0.048 and 0.002 respectively). As observed in men, the hemoglobin level was significantly higher in women with MS (p = 0.003).
Table 3

Baseline characteristics of the study population

 

Metabolic Syndrome

Variables

Overall

Men

Women

 

Absent

Present

p

Absent

Present

p

Absent

Present

p

 

n = 371

n = 1043

 

n = 260

n = 490

 

n = 111

n = 553

 

Age (years)

57.0 ± 10.3

56.1 ± 9.9

0.119

57.1 ± 10.5

56.8 ± 10.5

0.664

56.8 ± 9.8

55.4 ± 9.4

0.181

HbA1C (%)

8.3 ± 2.4

8.2 ± 2.1

0.366

8.3 ± 2.4

8.2 ± 2.1

0.475

8.2 ± 2.6

8.1 ± 2.1

0.687

Duration of diabetes (years)

6.6 ± 7.5

5.1 ± 5.7

< 0.0001

7.1 ± 8.0

5.7 ± 6.0

0.008

5.5 ± 5.6

4.6 ± 5.3

0.084

Total serum cholesterol (mg/dl)

184.5 ± 40.9

187.2 ± 40.7

0.266

178.1 ± 38.4

183.2 ± 38.4

0.081

199.5 ± 42.8

190.8 ± 42.3

0.048

Serum LDL cholesterol (mg/dl)

113.2 ± 35.9

111.8 ± 35.2

0.506

106.8 ± 33.6

106.3 ± 33.8

0.845

128.2 ± 37.2

116.7 ± 35.8

0.002

Serum Non HDL cholesterol (mg/dl)

3.7 ± 1.0

3.8 ± 1.0

0.029

3.6 ± 0.9

3.8 ± 0.9

0.009

3.9 ± 1.0

3.9 ± 1.1

0.488

Hemoglobin (gm/dl)

13.8 ± 1.8

13.8 ± 1.4

0.884

14.2 ± 1.9

14.5 ± 1.4

0.013

12.7 ± 1.3

13.1 ± 1.1

0.003

HbA1C (%), Glycosylated hemoglobin; LDL, Low density lipoprotein; HDL, High-density lipoprotein

Table 4 evaluates the effect of MS on the prevalence of microvascular complications of diabetes. In subjects with diabetes mellitus, without and with MS, the prevalence of retinopathy was 21.3% and 16.9% (p = 0.057); prevalence of nephropathy was 20.5% and 18.0% (p = 0.296) and prevalence of neuropathy was17.2% and 19.4% (p = 0.353) respectively. When evaluated separately, in men and women, the diagnosis of MS was not significantly associated with the presence of microvascular complications in our study population except for a lower prevalence of nephropathy in men with MS (p = 0.029).
Table 4

Comparison of prevalence of microangiopathies in the study population with and without Metabolic Syndrome

Metabolic Syndrome

Diabetic Retinopathy, n = 255

p

Diabetic Nephropathy, n = 264

p

Diabetic Neuropathy, n = 264

p

Overall

      

Absent (n = 371)

79 (21.3)

0.057

76 (20.5)

0.296

63 (17.2)

0.353

Present (n = 1043)

176 (16.9)

 

188 (18.0)

 

201 (19.4)

 

Men

      

Absent (n = 260)

61 (23.5)

0.241

60 (23.1)

0.029

46 (17.9)

0.304

Present (n = 490)

97 (19.8)

 

81 (16.5)

 

103 (21.1)

 

Women

      

Absent (n = 111)

18 (16.2)

0.599

16 (14.4)

0.222

17 (15.6)

0.556

Present (n = 553)

79 (14.3)

 

107 (19.3)

 

98 (17.9)

 
Table 5 shows the effect of aggregation of more number of components of MS on the prevalence of microangiopathies. The IDF definition of MS requires central obesity to be the essential criterion. Since our whole study population was diabetic, the presence of diabetes or raised plasma glucose also became an unchangeable criterion in our study cohort. To study the desired outcome, we grouped the patients into three sets, in increasing order of presence of three, four or five criteria of MS. When patients were grouped in such a way, the prevalence of diabetic retinopathy, overall and in men, was not different. In women, however, the prevalence of retinopathy increased with a rise in the number of MS components (12.6%, 20.1% and 16.4%, trend p = 0.193 overall; 17.5%, 22.8% and 21.6%, trend p = 0.779 in men; 6.5%, 18.0% and 15.0%, trend p = 0.049 in women). Overall and in women, the clustering of MS components led to an increase in the prevalence of diabetic nephropathy. However, there was no such trend in men (13.9%, 18.5% and 21.7%, trend p = 0.013 overall; 11.6%, 19.2% and 26.3%, trend p = 0.001 for women; 15.8%, 17.6% and 15.9%, trend p = 0.945 in men). For diabetic neuropathy, the prevalence was not different overall and in men, but it increased with grouping of MS components in women (21.2%, 16.8% and 21.6%, trend p = 0.929 overall; 26.9%, 17.1% and 19.2%, trend p = 0.077 in men and 14.0%, 16.6% and 23.6%, trend p = 0.003 in women).
Table 5

Effect of clustering of components of Metabolic Syndrome on microangiopathies

  

Prevalence of Microangiopathies

Components of MS

 

Diabetic Retinopathy

Diabetic Nephropathy

Diabetic Neuropathy

 

N

n

%

Trend p

n

%

Trend p

n

%

Trend p

Overall (n = 1043)

          

   + Any one

309

39

12.6

0.193

43

13.9

0.013

65

21.2

0.929

   +Any two

448

90

20.1

 

83

18.5

 

75

16.8

 

   + Any three

286

47

16.4

 

62

21.7

 

61

21.6

 

Men (n = 490)

          

   + Any one

171

30

17.5

0.779

27

15.8

0.945

46

26.9

0.077

   +Any two

193

44

22.8

 

34

17.6

 

33

17.1

 

   + Any three

126

23

18.3

 

20

15.9

 

24

19.2

 

Women (n = 553)

          

   + Any one

138

9

6.5

0.049

16

11.6

0.001

19

14.0

0.030

   +Any two

255

46

18.0

 

49

19.2

 

42

16.6

 

   + Any three

160

24

15.0

 

42

26.3

 

37

23.6

 

MS, Metabolic Syndrome; MS absent, Diabetes only or Diabetes + Obesity; + Any one, Diabetes + Obesity + Any of hypertension, reduced HDL or elevated triglyceride; + Any two, Diabetes + Obesity + Any two of hypertension, reduced HDL or elevated triglyceride; + Any three, Diabetes + Obesity + All three of hypertension, reduced HDL or elevated triglyceride; N, Total population with metabolic syndrome; n, Population with metabolic syndrome having microangiopathies

Table 6 shows the influence the duration of diabetes has on the prevalence of microangiopathies in patients with and without MS. The prevalence of retinopathy and neuropathy in MS subjects, who had diabetes for < 10 years, was more in both men and women; it was more in women but not in men when the duration of diabetes varied from 11-20 years; and when the duration of diabetes was > 20 years, it was not different in men or women when compared to subjects without MS. Nephropathy was more prevalent in women with MS and whose duration of diabetes was < 10 years and 11-20 years but the prevalence was not different when the duration of diabetes was > 20 years.
Table 6

Effect of duration of Diabetes on the prevalence of microangiopathies in study population with or without Metabolic Syndrome

  

Prevalence of Microangiopathy

 

Variables

Groups

Duration (0-10 years)

p

Duration (11-20 years)

p

Duration (> 20 years)

p

Overall

       

Retinopathy

MS Absent

48 (28.2)

< 0.0001

25 (34.7)

0.013

6 (46.2)

1.000

 

MS Present

122 (71.8)

 

47 (65.3)

 

7 (53.8)

 

Nephropathy

MS Absent

61 (29.6)

< 0.0001

12 (22.6)

< 0.0001

3 (60.0)

1.000

 

MS Present

145 (70.4)

 

41 (77.4)

 

2 (40.0)

 

Neuropathy

MS Absent

38 (19.9)

< 0.0001

18 (31.0)

0.005

7 (46.7)

1.000

 

MS Present

153 (80.1)

 

40 (69.0)

 

8 (53.3)

 

Men

       

Retinopathy

MS Absent

36 (34.3)

0.002

19 (43.2)

0.451

6 (66.7)

0.508

 

MS Present

69 (65.7)

 

25 (56.8)

 

3 (33.3)

 

Nephropathy

MS Absent

46 (43.4)

0.206

11 (36.7)

0.200

3 (60.0)

1.000

 

MS Present

60 (56.6)

 

19 (63.3)

 

2 (40.0)

 

Neuropathy

MS Absent

24 (24.2)

< 0.0001

16 (40.0)

0.268

6 (60.0)

0.754

 

MS Present

75 (75.8)

 

24 (60.0)

 

4 (40.0)

 

Women

       

Retinopathy

MS Absent

12 (18.5)

< 0.0001

6 (21.4)

0.004

0 (0.0)

0.125

 

MS Present

53 (81.5)

 

22 (78.6)

 

4 (100.0)

 

Nephropathy

MS Absent

15 (15.0)

< 0.0001

1 (4.3)

< 0.0001

0 (0.0)

NA

 

MS Present

85 (85.0)

 

22 (95.7)

 

0 (0.0)

 

Neuropathy

MS Absent

14 (15.2)

< 0.0001

2 (11.1)

0.001

1 (20.0)

0.375

 

MS Present

78 (84.8)

 

16 (88.9)

 

4 (80.0)

 

MS, Metabolic Syndrome

To evaluate the relation between the presence of diabetic microvascular complications and individual MS components, we performed a multiple logistic regression analysis by adjusting variables such as age, gender, smoking and alcohol (Table 7). The results showed that the independent risk factors for retinopathy were glycosylated hemoglobin - OR 1.16 (95% CI 1.07-1.26) and duration of diabetes - OR 1.13 (95% CI 1.09-1.16). For nephropathy, the risk factors were glycosylated hemoglobin - OR 1.24 (95% CI 1.15-1.34), duration of diabetes - OR 1.04 (95% CI 1.01-1.07) and hypertension - OR 1.80 (95% CI 1.20-2.70). For neuropathy, the independent risk factors came out to be reduced serum HDL cholesterol - OR 1.03 (95% CI 1.01-1.05) and increased waist circumference - OR 1.02 (1.00-1.04).
Table 7

Multiple logistic model for risk factors for microangiopathies

 

Overall

Men

Women

Independent variables

OR (95% CI)

p

OR (95% CI) *

p

OR (95% CI)

p

Retinopathy

      

Glycosylated Hemoglobin

1.16 (1.07-1.26)

< 0.0001

1.14 (1.02-1.28)

0.020

1.19 (1.07-1.34)

0.002

Duration of Diabetes

1.13 (1.09-1.16)

< 0.0001

1.13 (1.08-1.17)

< 0.0001

1.13 (1.08-1.18)

< 0.0001

Hypertension

1.18 (0.80-1.77)

0.392

1.09 (0.65-1.82)

0.746

1.41 (0.74-2.69)

0.297

Elevated serum Triglyceride

1.01 (0.99-1.00)

0.560

1.00 (0.99-1.00)

0.256

1.00 (0.99-1.00)

0.857

Reduced serum HDL-Cholesterol

1.01 (0.99-1.03)

0.254

1.03 (1.00-1.06)

0.038

0.99 (0.97-1.02)

0.618

Increased Waist circumference

0.98 (0.96-1.01)

0.188

0.96 (0.93-0.99)

0.037

1.01 (0.98-1.04)

0.663

Nephropathy

      

Glycosylated Hemoglobin

1.24 (1.15-1.34)

< 0.0001

1.19 (1.07-1.34)

0.002

1.27 (1.15-1.39)

< 0.0001

Duration of Diabetes

1.04 (1.01-1.07)

0.008

1.04 (1.00-1.08)

0.052

1.04 (0.99-1.08)

0.076

Hypertension

1.80 (1.20-2.70)

0.004

1.50 (0.86-2.63)

0.155

2.17 (1.19-3.93)

0.011

Elevated serum Triglyceride

1.00 (0.99-1.00)

0.976

0.99 (0.99-1.00)

0.661

1.00 (0.99-1.00)

0.473

Reduced serum HDL-Cholesterol

0.99 (0.98-1.02)

0.857

1.01 (0.98-1.04)

0.612

0.99 (0.97-1.01)

0.450

Increased Waist circumference

1.02 (1.00-1.04)

0.055

1.03 (0.99-1.07)

0.064

1.01 (0.99-1.04)

0.289

Neuropathy

      

Glycosylated Hemoglobin

1.05 (0.97-1.14)

0.192

1.08 (0.96-1.21)

0.198

1.03 (0.92-1.15)

0.596

Duration of Diabetes

1.02 (0.99-1.05)

0.181

1.01 (0.97-1.05)

0.653

1.03 (0.98-1.07)

0.215

Hypertension

1.19 (0.80-1.76)

0.384

0.87 (0.51-1.48)

0.607

1.83 (0.98-3.44)

0.059

Elevated serum Triglyceride

1.00 (0.99-1.00)

0.381

1.00 (0.99-1.00)

0.313

1.00 (0.99-1.00)

0.496

Reduced serum HDL-Cholesterol

1.03 (1.01-1.05)

0.001

1.06 (1.03-1.09)

< 0.0001

1.00 (0.98-1.03)

0.806

Increased Waist circumference

1.02 (1.00-1.04)

0.043

1.01 (0.97-1.04)

0.640

1.03 (1.00-1.06)

0.027

* All factors adjusted with age, gender, glycosylated hemoglobin, hemoglobin, socioeconomic status, smoking status and alcohol status

All factors adjusted with age, glycosylated hemoglobin, hemoglobin, socioeconomic status, smoking status and alcohol status

Discussion

The present study reports an alarmingly high prevalence of MS, using IDF criteria, in subjects with type 2 diabetes mellitus in a population-based study. One of the IDF criteria for MS, the increased fasting plasma glucose ≥ 100 mg/dl or pre-existing diabetes, was present in all of the participants of the study; therefore, the "metabolic syndrome" in this study is not exactly the same as MS in general sense. In our cohort, almost every three out of four subjects with type 2 diabetes had MS. A similar high prevalence was reported by Surana et al[25] in urban Indian population with type 2 diabetes (77.2%) and by Foucan et al[26] in Indian immigrants in the USA with diabetes (77%). This prevalence of MS in the South Indian population with diabetes is more than two-fold higher than the reported prevalence in the general urban Indian population [27]. Using a similar definition as ours (IDF), Terauchi et al[13] and Bonadonna et al[11] reported the prevalence of MS to be 58.5% and 77.6% respectively, which was comparable to that observed in our study.

The present study has observed gender-wise differences with respect to prevalence of MS and its influence on microangiopathies. The MS, in the defined population of type II diabetes mellitus, was more prevalent in women than men (Table 1); there was a positive correlation between the number of components of MS and all types of microangiopathies (Table 5) in women. Like our study, Ghani et al[28] and Bonadonna et al[11] also reported a higher prevalence of MS in women; however Shimajiri et al[4] reported a higher prevalence in men. Among the Indian diabetic population, a higher prevalence of MS in women was reported by Surana et al[25]. They proposed the cause to be a higher prevalence of low HDL and central obesity in women, which could partially be attributed to the lower cut-off for waist circumference and higher cut-off for HDL in women as compared to men. In our study, we also noted a higher BMI and lower HDL cholesterol in women as compared to men. But the waist circumference was lower in women despite the lower cut-off, which suggests that there are other factors which increase the prevalence of MS in women. Bonadonna et al[11] also commented in their study that this trend could be both due to a true biological phenomenon or a suboptimal choice of gender-specific diagnostic thresholds. Because of these gender-wise differences, female gender should become a focus of high risk target-screening, and attempts should be made to normalize each component of MS so as to minimize the risk of microangiopathies.

Shimajiri et al[4] reported that the prevalence of MS decreases along with an increase in the duration of diabetes. They suggested the possible reason to be a decreased BMI as a result of medical intervention in the lifestyle of long term diabetic patients. In our study, we noted this trend only in men. We feel that the better accessibility to medical care and more health awareness among men in our country can be a factor responsible for this. Whether there are other biological or hormonal factors playing a role is not known. We also observed different trends in obesity indices in men and women in the same study cohort, which is possibly related to postmenopausal hormonal changes in women [29]. This might also explain the gender differences in the current study.

Similar to our finding, Ghani et al[28] also found an association of MS with less duration of diabetes. The occurrence of microangiopathies in diabetes mellitus is influenced by several of the components of the MS; this implies a possible relationship between microangiopathies and MS. The association of MS with microvascular complications of type 2 diabetes i.e. diabetic retinopathy, nephropathy and neuropathy has been studied in many reports [4, 9, 11, 28], They found the increased prevalence of all three complications in patients with diabetes using different definitions of MS. Kawasaki et al[12] used the IDF criteria and reported that the associations between MS and retinal microvascular signs appeared mainly driven by the associations with larger waist circumference. Isomaa et al[5] reported that MS was strongly associated with microalbuminuria but had little effect on the development of retinopathy and neuropathy. However, a study in Japanese patients, on the other hand, did not show any statistically significant association of MS with the prevalence of microvascular complications in type 2 diabetes mellitus [13]. They attributed it to possible ethnicity related differences because in Asian population, MS has also been reported to be non predictive of coronary artery disease in contrast to the results in Caucasian population. In our study, we found a similar lack of association between MS and the increased prevalence of microvascular disease.

Some previous studies have reported an increase in the prevalence of microangiopathies when patients were grouped according to the number of MS components [9, 28, 30]. In men, we found that there was no trend of increase in diabetic microvascular complications with an increase in the MS features. However, in women, there was a statistically significant increase in the prevalence of diabetic microangiopathies with an increase in the MS components.

On evaluating the influence of the duration of diabetes on the prevalence of microangiopathies in patients with MS, we found that there was a significant association between MS and the prevalence of microangiopathies in subjects with type 2 diabetes mellitus in the early course of the disease which disappeared with the increasing duration of diabetes in both men and women. This suggests that MS might have a more significant influence on increasing the prevalence of microvascular disease in recent diabetics, but gradually with increasing duration of diabetes, this influence decreases. One possible explanation for this could be better metabolic control in diabetic patients due to increasing awareness with longer duration of diabetes. We did find this trend in the present study; subjects with longer duration of diabetes (> 20 years) had better metabolic control (FBS< 110 mg %) than those with shorter duration of diabetes (0-10 and 11-20 years). The FBS < 110 mg% was noted in 61.8%, 73.7% and 79.2% of subjects with duration of diabetes mellitus being 0-10 years, 11-20 years and > 20 years, respectively (p = 0.005).

We found the risk factors for retinopathy to be glycosylated hemoglobin and duration of diabetes, for nephropathy to be glycosylated hemoglobin, duration of diabetes, hypertension, increased body mass index and increased waist circumference and for neuropathy to be reduced serum HDL cholesterol on multivariate analysis. Different associations have also been reported in previous studies [5, 12, 13]. We also found an association of waist circumference with nephropathy as was reported by Hanai et al[30].

Conclusions

The strength of current study is that it was a population based study that used standardized methods for evaluation of microvascular complications of diabetes mellitus. However, the causal relationship could not be assessed because of the cross sectional nature of study. The prevalence and risk factors of microangiopathies among subjects with MS may also be influenced by presence of diabetes mellitus.

This study reports the prevalence and risk factors for MS in subjects with type 2 diabetes. The gender differences in the prevalence and the risk factors for MS in the population with diabetes need further confirmation in a larger prospective study.

Declarations

Acknowledgements

We acknowledge the support of the RD Tata Trust, Mumbai, for this project.

Authors’ Affiliations

(1)
Shri Bhagwan Mahavir Vitreoretinal Services
(2)
Department of Preventive Ophthalmology (Epidemiology and Biostatistics)

References

  1. Reaven GM: Banting lecture 1988. Role of insulin resistance in human disease. Diabetes. 1988, 37: 1595-607. 10.2337/diabetes.37.12.1595.View ArticlePubMedGoogle Scholar
  2. Isomaa B, Almgren P, Tuomi T, Forsen B, Lahti K, Nissen M, Taskinen MR, Groop L: Cardiovascular morbidity and mortality associated with the metabolic syndrome. Diabetes Care. 2001, 24: 683-9. 10.2337/diacare.24.4.683.View ArticlePubMedGoogle Scholar
  3. Szalat A, Raz I: Metabolic syndrome and microangiopathy. Isr Med Assoc J. 2006, 8: 424-5.PubMedGoogle Scholar
  4. Shimajiri Y, Tsunoda K, Furuta M, Kadoya Y, Yamada S, Nanjo K, Sanke T: Prevalence of metabolic syndrome in Japanese type 2 diabetic patients and its significance for chronic vascular complications. Diabetes Res Clin Pract. 2008, 79: 310-7. 10.1016/j.diabres.2007.08.026.View ArticlePubMedGoogle Scholar
  5. Isomaaa B, Henricsson M, Almgren P, Tuomi T, Taskinen MR, Groop L: The metabolic syndrome influences the risk of chronic complications in patients with type II diabetes. Diabetologica. 2001, 44: 1148-54. 10.1007/s001250100615.View ArticleGoogle Scholar
  6. Marchesini G, Forlani G, Cerrelli F, Manini R, Natale S, Baraldi L, Ermini G, Savorani G, Zocchi D, Melchionda N: WHO and ATPIII proposals for the definition of the metabolic syndrome in patients with Type 2 diabetes. Diabet Med. 2004, 21: 383-7. 10.1111/j.1464-5491.2004.01115.x.View ArticlePubMedGoogle Scholar
  7. Bonora E, Kiechl S, Willeit J, Oberhollenzer F, Egger G, Targher G, Alberiche M, Bonadonna RC, Muggeo M: Prevalence of insulin resistance in metabolic disorders: the Bruneck Study. Diabetes. 1998, 47: 1643-9. 10.2337/diabetes.47.10.1643.View ArticlePubMedGoogle Scholar
  8. Alexander C, 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: 1210-14. 10.2337/diabetes.52.5.1210.View ArticlePubMedGoogle Scholar
  9. Costa LA, Canani LH, Lisboa HRK, Tres GS, Gross JL: Aggregation of features of the metabolic syndrome is associated with increased prevalence of chronic complications in Type 2 diabetes. Diabetic Medicine. 2004, 21: 252-5. 10.1111/j.1464-5491.2004.01124.x.View ArticlePubMedGoogle Scholar
  10. Kilpatrick ES, Rigby AS, Atkin SL: Insulin resistance, the metabolic syndrome, and complication risk in type 2 diabetes: double diabetes in the Diabetes Control and Complications Trial. Diabetes care. 2007, 30: 707-12. 10.2337/dc06-1982.View ArticlePubMedGoogle Scholar
  11. Metascreen Writing Committee, Bonadonna RC, Cucinotta D, Fedele D, Riccardi G, Tiengo A: The metabolic syndrome is a risk indicator of microvascular and macrovascular complications in diabetes: results from Metascreen, a multicenter diabetes clinic-based survey. Diabetes care. 2006, 29: 2701-07. 10.2337/dc06-0942.View ArticleGoogle Scholar
  12. Kawasaki R, Tielsch JM, Wang JJ, Wong TY, Mitchell P, Tano Y, Tominaga M, Oizumi T, Daimon M, Kato T, Kawata S, Kayama T, Yamashita H: The metabolic syndrome and retinal microvascular signs in a Japanese population: the Funagata study. Br J Ophthalmol. 2008, 92: 161-6. 10.1136/bjo.2007.127449.View ArticlePubMedGoogle Scholar
  13. Iwasaki T, Togashi Y, Ohshige K, Yoneda M, Fujita K, Nakajima A, Terauchi Y: Neither the presence of metabolic syndrome as defined by the IDF guideline nor an increased waist circumference increased the risk of microvascular or macrovascular complications in Japanese patients with type 2 diabetes. Diabetes Res Clin Pract. 2008, 79: 427-32. 10.1016/j.diabres.2007.10.035.View ArticlePubMedGoogle Scholar
  14. Van den Hoogen PC, Feskens EJ, Nagelkerke NJ, Menotti A, Nissinen A: The relation between blood pressure and mortality due to coronary heart disease among men in different parts of world. Seven Countries Study Research Group. N Engl J Med. 2000, 342: 1-8. 10.1056/NEJM200001063420101.View ArticlePubMedGoogle Scholar
  15. Lee ET, Keen H, Bennett PH, Fuller JH, Lu M: Follow-up of the WHO multinational study of vascular disease in diabetes: general description and morbidity. Diabetologia. 2001, 44 (Suppl 2): S3-13. 10.1007/PL00002936.View ArticlePubMedGoogle Scholar
  16. Sone H, Ito H, Ohashi Y, Akanuma Y, Yamada N: Japan diabetes complication study group. Obesity and type 2 diabetes in Japanese patients. Lancet. 2003, 361: 85-10.1016/S0140-6736(03)12151-4.View ArticlePubMedGoogle Scholar
  17. Agarwal S, Raman R, Paul PG, Rani PK, Uthra S, Gayathree R, McCarty C, Kumaramanickavel G, Sharma T: Sankara Nethralaya-Diabetic Retinopathy Epidemiology and Molecular Genetic Study (SN-DREAMS 1): study design and research methodology. Ophthalmic Epidemiol. 2005, 12: 143-53. 10.1080/09286580590932734.View ArticlePubMedGoogle Scholar
  18. Goldstein DE, Little RR, Lorenz RA, Malone JI, Nathan DM, Peterson CM, American Diabetes Association: Tests of glycemia in diabetes. Diabetes Care. 2003, 26 (Suppl 1): S106-108.PubMedGoogle Scholar
  19. Touitou Y, Portaluppi F, Smolensky MH, Rensing L: Ethical principles and standards for the conduct of human and animal biological rhythm research. Chronobiol Int. 2004, 21: 161-170. 10.1081/CBI-120030045.View ArticlePubMedGoogle Scholar
  20. International Diabetes Federation: New IDF worldwide definition of the metabolic syndrome. Press Conference 1st International Congress on 'Pre-diabetes' and the Metabolic Syndrome, Berlin, Germany. 2005, [http://www.idf.org/]Google Scholar
  21. Klein R, Klein BE, Magli YL, Brothers RJ, Meuer SM, Moss SE, Davis MD: An alternative method of grading diabetic retinopathy. Ophthalmology. 1986, 93: 1183-7.View ArticlePubMedGoogle Scholar
  22. Wilkinson CP, Ferris FL, Klein RE, Lee PP, Agardh CD, Davis M, Dills D, Kampik A, Pararajasegaram R, Verdaguer JT, Global Diabetic Retinopathy Project Group: Proposed international clinical diabetic retinopathy and diabetic macular edema disease severity scales. Ophthalmology. 2003, 110: 1677-82. 10.1016/S0161-6420(03)00475-5.View ArticlePubMedGoogle Scholar
  23. Molitch ME, DeFronzo RA, Franz MJ, Keane WF, Mogensen CE, Parving HH, Steffes MW, American Diabetes Association: Nephropathy in Diabetes. Diabetes Care. 2004, 27 (Suppl 1): S79-S83.PubMedGoogle Scholar
  24. Pradeepa R, Rema M, Vignesh J, Deepa M, Deepa R, Mohan V: Prevalence and risk factors for diabetic neuropathy in an urban south Indian population: the Chennai Urban Rural Epidemiology Study (CURES-55). Diabet Med. 2008, 25: 407-12. 10.1111/j.1464-5491.2008.02397.x.View ArticlePubMedGoogle Scholar
  25. Surana SP, Shah DB, Gala K, Susheja S, Hoskote SS, Gill N, Joshi SR, Panikar V: Prevalence of Metabolic Syndrome in An Urban Indian Diabetic Population Using The NCEP ATP III Guidelines. J Assoc Physicians India. 2008, 56: 865-8.PubMedGoogle Scholar
  26. Foucan L, Deloumeaux J, Donnet JP, Bangou J, Larifla L, Messerchmitt C, Salmi LR, Kangambega P: Metabolic syndrome components in Indian migrants with type 2 diabetes. A matched comparative study. Diabetes Metab. 2006, 32: 337-42. 10.1016/S1262-3636(07)70288-4.View ArticlePubMedGoogle Scholar
  27. 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. 10.1016/j.ijcard.2003.11.003.View ArticlePubMedGoogle Scholar
  28. Abdul-Ghani M, Nawaf G, Nawaf F, Itzhak B, Minuchin O, Vardi P: Increased prevalence of microvascular complications in type 2 diabetes patients with the metabolic syndrome. Isr Med Assoc J. 2006, 8: 378-82.PubMedGoogle Scholar
  29. Raman R, Rani PK, Gnanamoorthy P, Sudhir RR, Kumaramanikavel G, Sharma T: Association of obesity with diabetic retinopathy: Sankara Nethralaya Diabetic Retinopathy Epidemiology and Molecular Genetics Study (SN-DREAMS Report no. 8). Acta Diabetologica. 2010, 47: 209-15. 10.1007/s00592-009-0113-8.View ArticlePubMedGoogle Scholar
  30. Hanai K, Babazono T, Iwamoto Y: Renal manifestations of metabolic syndrome in type 2 diabetes. Diabetes Res Clin Pract. 2008, 79: 318-24. 10.1016/j.diabres.2007.08.032.View ArticlePubMedGoogle Scholar

Copyright

© Raman et al; licensee BioMed Central Ltd. 2010

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Advertisement