|Year : 2015 | Volume
| Issue : 2 | Page : 83-87
Factor analysis of metabolic syndrome components in North Indian adult population of Kashmir
Riyaz Ahmad Bhat
Department of Internal Medicine, Sher-i-Kashmir, Institute of Medical Sciences, Srinagar, Jammu and Kashmir, India
|Date of Web Publication||20-Aug-2015|
Riyaz Ahmad Bhat
Flat F-18, Married Hostel Sher-i-Kashmir Institute of Medical Sciences (SKIMS) Soura, Srinagar, Jammu and Kashmir
Source of Support: None, Conflict of Interest: None
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
| Introduction|| |
Metabolic syndrome (MS), a cluster of traits comprised of obesity, dyslipidemia, hypertension, and insulin resistance,  is widely prevalent in developing countries such as India where insulin resistance is widely prevalent.  The first formal definition of the MS was put forth in 1998 by the World Health Organization (WHO).  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.  Recently, the International Diabetes Federation (IDF) has proposed new population-specific criteria for the MS. 
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. 
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.  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. ,,,
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.  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|| |
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.  This formula is based on the assumption of normal approximation.
Persons fulfilling following criteria were included in the study:
- Age 20-60 years,
- No personal history of diabetes, hypertension, obesity, dyslipidemia, coronary artery disease, or smoking, and
- 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.
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|| |
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.
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 5: Sex-specific factor analysis showing contribution of individual parameters to MS|
Click here to view
| Discussion|| |
Insulin resistance is common in adult Asian Indians, accounting for high prevalence of MS. , The prevalence of MS is related to the prevalence of its component factors. Clustering of these component factors defines this syndrome complex.  Our population is less obese compared to the southern and northern Indian populations. ,,, This observation has a direct connection to the prevalence of MS and its components. Because of the higher prevalence of obesity in Kashmiri women,  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. ,,,, 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. , 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.  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.  Finally, whether prevalence estimates plateau or drop off steeply after the age of 60 years also varies according to the MS definition being used. ,
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.  Prasad et al. in their study on an urban population in eastern India found that the prevalence of MS was 33.5%.  Other Indian studies found prevalence estimates in the range of 15-40%. ,, 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.  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|| |
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
Conflicts of interest
There are no conflicts of interest.
| References|| |
Moller DE, Kaufman KD. Metabolic syndrome: A clinical and molecular perspective. Annu Rev Med 2005;56:45-62.
Deedwania PC, Gupta R. Management Issues in the metabolic syndrome. J Assoc Physicians India 2006;54:797-810.
Alberti KG, Zimmet PZ. Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: Diagnosis and classification of diabetes mellitus provisional report of a WHO consultation. Diabet Med 1998;15:539-53.
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.
Alberti KG, Zimmet P, Shaw J. Metabolic syndrome - a new world-wide definition. A Consensus Statement from the International Diabetes Federation. Diabet Med 2006;23:469-80.
Misra A, Vikram NK, Gupta R, Pandey RM, Wasir JS, Gupta VP. Waist circumference cutoff points and action levels for Asian Indians for identification of abdominal obesity. Int J Obes (Lond) 2006;30:106-11.
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 Pract 2003;60: 199-204.
Mohan V, Shanthirani S, Deepa R, Premalatha G, Sastry NG, Saroja R; Chennai Urban Population Study [CUPS No. 4]. Intra-urban differences in the prevalence of the metabolic syndrome in southern India - the Chennai Urban Population Study [CUPS No. 4]. Diabet Med 2001;18:280-7.
Gupta A, Gupta R, Sarna M, Rastogi S, Gupta VP, Kothari K. Prevalence of diabetes, impaired fasting glucose and insulin resistane syndrome in an urban Indian population. Diabetes Res Clin Pract 2003;61:69-76.
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.
Misra A, Misra R, Wijesuriya M, Banerjee D. The metabolic syndrome in South Asians: Continuing escalation & possible solutions. Indian J Med Res 2007;125:345-54.
Zargar AH, Masoodi SR, Laway BA, Khan AK, Wani AI, Bashir MI, et al
. Prevalence of obesity in adults - an epidemiological study from Kashmir Valley of Indian Subcontinent. J Assoc Physicians India 2000;48:1170-4.
Daniel WW. Biostatistics: A Foundation for Analysis in the Health Sciences. 7 th
ed. New York: John Wiley & Sons; 1999.
Chopra HK, Kaur S, Sambi RS. Potbelly - the most powerful predictor of metabolic syndrome and premature morbidity and mortality. Indian Heart J 2007;59:56-63.
Gupta R, Sarna M, Thanvi J, Rastogi P, Kaul V, Gupta VP. High prevalence of multiple coronary risk factors in Punjabi Bhatia community: Jaipur Heart Watch-3. Indian Heart J 2004;56:646-52.
Garg C, Khan SA, Ansari SH, Garg M. Prevalence of obesity in Indian women. Obes Rev 2010;11:105-8.
Third National Family Health Survey, Minster of Health and Family Welfare, Govt of India. International Institute for Population Sciences; 2006.
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.
Mujica V, Leiva E, Icaza G, Diaz N, Arredondo M, Moore-Carrasco R, et al
. Evaluation of metabolic syndrome in adults of Talca city, Chile. Nutr J 2008;7:14.
Zaman MM, Ahmed J, Choudhury SR, Numan SM, Islam MS, Parvin K. Prevalence of metabolic syndrome in rural Bangladeshi women. Diabetes Care 2006;29:1456-7.
Flegal KM, Carroll MD, Ogden CL, Curtin LR. Prevalence and trends in obesity among US adults,1999-2008. JAMA 2010;303:235-41.
Mokdad AH, Bowman BA, Ford ES, Vinicor F, Marks JS, Koplan JP. The continuing epidemics of obesity and diabetes in the United States. JAMA 2001;286:1195-200.
Duncan GE, Li SM, Zhou XH. Prevalence and trends of a metabolic syndrome phenotype among U.S. Adolescents, 1999-2000. Diabetes Care 2004;27:2438-43.
Ford ES, Giles WH, Mokdad AH. Increasing prevalence of the metabolic syndrome among U.S. Adults. Diabetes Care 2004;27:2444-9.
Cameron AJ, Magliano DJ, Zimmet PZ, Welborn T, Shaw JE. The metabolic syndrome in Augustralia: Prevalence using four definitions. Diabetes Res Clin Pract 2007;77:471-8.
Elia M. Obesity in the elderly. Obes Res 2001;9(Suppl 4):244-8s.
Kozan O, Oguz A, Abaci A, Erol C, Ongen Z, Temizhan A, et al.
Prevalence of the metabolic syndrome among Turkish adults. Eur J Clin Nutr 2007;61:548-53.
Sawant A, Mankeshwar R, Shah S, Raghavan R, Dhongde G, Raje H, et al
. Prevalence of metabolic syndrome in urban India. Cholesterol 2011;2011:920983.
Prasad DS, Kabir Z, Dash AK, Das BC. Prevalence and risk factors for metabolic syndrome in Asian Indians: A community study from urban Eastern India. J Cardiovasc Dis Res 2012;3:204-11.
Aggarwal A, Aggarwal S, Sharma V. Metabolic syndrome and coronary artery disease in Indians younger than 40 years. J Endocrinol Metab 2012;2:39-45.
Kotokey RK, Kalita D, Agarwala R, Purkayastha S. Prevalence of metabolic syndrome in urban population of Dibrugarh town of upper Assam. Journal of Indian College of Cardiology 2013;3:52-6.
Kanjilal S, Shanker J, Rao VS, Khadrinarasimhaih NB, Mukherjee M, Iyengar SS, et al
. Prevalence and component analysis of metabolic syndrome: An Indian atherosclerosis research study perspective. Vasc Health Risk Manag 2008;4:189-97.
Oh JY, Hong YS, Sung YA, Barrett-Connor E. Prevalence and factor analysis of metabolic syndrome in an urban Korean population. Diabetes Care 2004;27:2027-32.
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5]