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 Table of Contents  
ORIGINAL ARTICLE
Year : 2015  |  Volume : 29  |  Issue : 2  |  Page : 83-87

Factor analysis of metabolic syndrome components in North Indian adult population of Kashmir


Department of Internal Medicine, Sher-i-Kashmir, Institute of Medical Sciences, Srinagar, Jammu and Kashmir, India

Date of Web Publication20-Aug-2015

Correspondence Address:
Riyaz Ahmad Bhat
Flat F-18, Married Hostel Sher-i-Kashmir Institute of Medical Sciences (SKIMS) Soura, Srinagar, Jammu and Kashmir
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/0972-4958.163196

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  Abstract 

Aim: The Kashmiri population is ethnically distinct, culturally unique, and has distinct lifestyle and dietary habits. There is high prevalence of obesity in the Kashmiri population. With this background, we designed this study to evaluate important metabolic parameters contributing to the prevalence of metabolic syndrome (MS). Materials and Methods: In this prospective study, a total of 500 subjects were recruited over a period of 1 year. Informed consent was taken from all the subjects before selection. Proper permission was sought from the hospital's Ethical Committee. The subjects were selected from among the attendants who accompanied patients at the inpatient and outpatient departments of Sher-i-Kashmir Institute of Medical Sciences, Srinagar, Kashmir. A stratified random sampling procedure was adopted for the study. All subjects underwent anthropometric assessments, blood pressure measurements, and biochemical analysis. Subjects were screened for the components of MS according to criteria given by the Adult Treatment Panel (ATP) III. Statistical Analysis: Analysis was made and inferences were drawn using the student's test, chi-square test, and Mann-Whitney U test. Data were analyzed by SPSS version 11.5. Results: The mean age of both the men and women was 37 years. The overall prevalence of MS was 8.6% (n = 43), with males constituting 7.4% and females constituting 9.9%. The prevalence of hypertension was 24.9% for males and 12.3% for females. The prevalence of hyperglycemia was 9.3% for males and 7.8% for females; 9.7% males and 25.9% females had low high-density lipoprotein (HDL) cholesterol; and 17.1% males and 13.2% females had elevated triglyceride levels. The prevalence of obesity in males was 1.9% and in females it was 8.6%. Hypertension was the commonest factor affecting the estimates of MS in men, whereas central obesity and low HDL cholesterol were the common contributing factors in women. Conclusion: Prevalence of component factors such as diabetes, hypertension, and dyslipidemia is high, which needs attention.

Keywords: Body mass index (BMI), high-density lipoprotein (HDL) cholesterol, metabolic syndrome (MS), waist circumference (WC)


How to cite this article:
Bhat RA. Factor analysis of metabolic syndrome components in North Indian adult population of Kashmir. J Med Soc 2015;29:83-7

How to cite this URL:
Bhat RA. Factor analysis of metabolic syndrome components in North Indian adult population of Kashmir. J Med Soc [serial online] 2015 [cited 2020 Oct 20];29:83-7. Available from: https://www.jmedsoc.org/text.asp?2015/29/2/83/163196


  Introduction Top


Metabolic syndrome (MS), a cluster of traits comprised of obesity, dyslipidemia, hypertension, and insulin resistance, [1] is widely prevalent in developing countries such as India where insulin resistance is widely prevalent. [2] The first formal definition of the MS was put forth in 1998 by the World Health Organization (WHO). [3] The National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III) published a new set of criteria based on common clinical measurements: Waist circumference (WC), blood lipids, blood pressure, and fasting glucose. [4] Recently, the International Diabetes Federation (IDF) has proposed new population-specific criteria for the MS. [5]

There is an increasing belief that the ATP III definition of MS is not optimal for the identification of risks of type 2 diabetes mellitus (DM) or cardiovascular disease (CVD) and does not identify MS correctly in the South Asian population in whom overweight definition criteria are different from their western counterpart. Data from recent studies in India show that WC levels of 90 cm for men and 80 cm for women were associated with higher odds ratios (ORs) for the presence of cardiovascular risk factors. [6]

Therefore, modified ATP III criteria that incorporate Asian-specific WC criteria (90 cm in men and 80 cm in women) have been used in recent Asian and Indian studies. [7] Most Indian studies have used ATP III criteria in their prevalence and factor analysis studies. However, studies show different trends of prevalence when different criteria are used. Different aspects of MS have been studies in many more Indian studies, including North Indian studies. [8],[9],[10],[11]

The Kashmiri population is ethnically very distinct due to their special dietary intakes. Owing to the temperate climatic conditions of Kashmir valley, the population is habituated to preserving foods in smoked, pickled, and sundried form. Obesity in the Kashmiri population is fairly common in females. [12] However, the burden of metabolic abnormalities contributing to MS is not known. This study was therefore designed to analyze factors contributing to MS and estimate its prevalence in the adult Kashmiri population.


  Materials and methods Top


This study was conducted among the attendants who accompanied the patients at the inpatient and outpatient departments of a tertiary care hospital in North India. It was a cross-sectional study done over a period of 1 year (from December 2010 to December 2011). A stratified random sampling procedure was adopted for the study. The sample size for the study was calculated from the formula given by Daniel. [13] This formula is based on the assumption of normal approximation.

Persons fulfilling following criteria were included in the study:

  1. Age 20-60 years,
  2. No personal history of diabetes, hypertension, obesity, dyslipidemia, coronary artery disease, or smoking, and
  3. No such family history.


Written, personally given consent was taken for the study.

The study was approved by the hospital Ethical Committee.

Measurements and definition

All subjects underwent anthropometric assessment such as measurement of height, weight, BMI, WC, and blood pressure. WC was measured in minimal light clothing mid-respiration between the 10th ribs and the iliac crest to the nearest 0.1 cm. Height and weight were measured with a beam balance with minimal clothing and no footwear. The BMI was obtained by dividing weight in kilogram by the square of the height in meters. Blood pressure was estimated in the nondominant arm in the sitting position. It was measured 3-5 min after the subject was comfortable using correctly-sized cuff. Blood pressure was recorded twice within an interval of 5 min and the average of systolic and diastolic blood pressures was taken.

After an overnight fast of at least 8 h, a nonheparinized venous blood sample was taken, serum was separated within 2 h of venipuncture, and analysis was done within 24 h. Biochemical parameters were analyzed with commercially available enzymatic reagents (Audit Diagnostics, Ireland) adapted to the Hitachi 912 autoanalyzer (Japan). MS was diagnosed according to the criteria given by ATP III, when any three of the following were present: Abdominal obesity, raised triglycerides ≥150 mg/dL, low high-density lipoprotein (HDL) cholesterol ≤40 mg/dL in men and ≤50 mg/dL in women, blood pressure ≥130/85, and diabetes or fasting blood glucose ≥110 mg/dL.

Statistical analysis

Data were analyzed by IBM SPSS statistical package, version 11.5. The prevalence was reported in percentages. Factor analysis was performed to describe the sex-specific clustering of MS factors. Analysis was made and inferences were drawn using the student's test for continuous variables, chi-square test for proportions, and Mann-Whitney U test. A two-tailed P value was used for calculating statistical significance. A P value of <0.05 was taken as statistically significant.


  Results Top


This study's population of 500 people consisted of 257 men and 243 women. The mean age ± standard deviation (SD) was 38 ± 7.9 years in men and 36.7 ± 6.8 years in women. [Table 1] summarizes the anthropometric and metabolic parameters in the study population. Men had significantly higher levels of blood pressure. Serum triglyceride levels were on the higher side in males but the elevation was not statistically significant. WC was significantly elevated in females and serum HDL cholesterol levels were significantly reduced in females.
Table 1: Clinical characteristics of study population

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Factor analysis

Factors that were analyzed for significance of relationship with MS include age, blood pressure, WC, serum HDL cholesterol, serum triglyceride levels, and serum blood glucose levels. The overall prevalence of MS was 8.6% (males 7.4%, females 9.9%) and it increased with age, peaking at 40-50 years of age [Table 2]. The same trend was shown by WC [Table 3]. Among various factors WC showed a significant positive correlation with the prevalence of MS (P = 0.005). The prevalence of hypertension was 24.9% for males and 12.3% for females. The prevalence of hyperglycemia was 9.3% for males and 7.4% for females, while 9.7% males and 25.9% females had low HDL cholesterol, and 17% males and 13.2% females had elevated triglyceride levels [Table 4].

High blood pressure showed a significant contribution toward MS in case of males (OR 21.1; P- 0.000), whereas increased WC and low HDL cholesterol had significant contribution in females (OR 216, P 0.000, and OR 102.9, P 0.000 respectively). Hypertriglyceridemia and hyperglycemia were more common in males, although statistically insignificant. Of the MS patients, 55% had DM. Among all these factors, WC was the single most contributory factor toward MS [Table 5].
Table 2: Trend of MS with increasing age

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Table 3: Trend of WC with increasing age

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Table 4: Sex-specific prevalence of individual components of MS

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Table 5: Sex-specific factor analysis showing contribution of individual parameters to MS

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  Discussion Top


Insulin resistance is common in adult Asian Indians, accounting for high prevalence of MS. [14],[15] The prevalence of MS is related to the prevalence of its component factors. Clustering of these component factors defines this syndrome complex. [1] Our population is less obese compared to the southern and northern Indian populations. [10],[15],[16],[17] This observation has a direct connection to the prevalence of MS and its components. Because of the higher prevalence of obesity in Kashmiri women, [12] a higher tendency toward MS and its components, particularly central obesity and dyslipidemia in the form of low HDL cholesterol, was observed in the female population.

The observation that MS becomes more prevalent with each decade of life increasing in parallel with obesity has been made in many studies. [18],[19],[20],[21],[22] We observed that prevalence increases steadily with age up to 50 years. Highest prevalence was seen in the fifth decade. Women displayed increased prevalence after the age of 40 years (P = 0.000). A similar trend was shown in WC when compared with age. In the National Health and Nutrition Examination Survey (NHANES) cohorts, MS prevalence continued to increase with age into the sixth decade, with prevalence in women catching up to and then exceeding that in men after the age of 60 years. [23],[24] The definition used to estimate prevalence, however, may influence this interaction. Studies that have compared age-related increases in prevalence among different definitions have observed variable prevalence estimates after the sixth or seventh decades. [25] Much of this variability in these later decades of life may be due to a survival effect, because those most susceptible to obesity-related mortality have likely died by this point. [26] Finally, whether prevalence estimates plateau or drop off steeply after the age of 60 years also varies according to the MS definition being used. [12],[27]

Sawant et al. in their study on an urban Indian population found the prevalence of MS to be 19.2%. The prevalence was higher in females as compared to males. [28] Prasad et al. in their study on an urban population in eastern India found that the prevalence of MS was 33.5%. [29] Other Indian studies found prevalence estimates in the range of 15-40%. [30],[31],[32] Although limited data are available from North India, most of the Indian studies showed high prevalence rates as compared to our observation. Immediate measures are needed to prevent progression of an MS epidemic.

The clustering of various metabolic abnormalities differs in men and women. Abdominal obesity and abnormal HDL cholesterol levels are more common in women (OR = 216.0, P = 0.000; OR = 102.9, P = 0.000, respectively), whereas high blood pressure is more prevalent in men than in women (OR = 21.1, P = 0.000 vs OR = 14.0, P = 0.000). Abnormal triglyceride levels and high plasma blood glucose, although common in men, did not point to statistically significant difference. Overall, WC emerged to be the most accurate parameter in predicting MS (95%), with a sensitivity of 84.9% and specificity of 95.5%.

Component analysis revealed that WC is the most important factor in defining MS. Globally, an increased prevalence has been seen with the International Diabetes Federation (IDF) definition because it uses lower cutoffs for WC. [33] Using modified WC criteria for the existing ATP III definition, we estimate that 52.2% men and 94.4% women qualified for MS, as against 21.1% men and 75% women estimated with the ATP III criteria. It is clear that Asian-specific criteria for WC identify more persons having MS as compared to the ATP III criteria alone.


  Conclusion and limitations Top


Abnormalities in the form of dyslipidemia, hypertension, and hyperglycemia are very common, a scenario that needs immediate attention. Preventing development of central obesity, besides controlling other factors, will prevent the development of MS in a large proportion of the population. The results in our study should be considered with some limitations. The sample size in our study was relatively small. In addition, as our study was a hospital-based study, errors made while selecting patients with a low threshold for exclusion cannot be wholly ruled out.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.

 
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    Tables

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5]



 

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