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ORIGINAL ARTICLE
Year : 2020  |  Volume : 13  |  Issue : 4  |  Page : 321-325  

Comparison between three different diagnostic criteria in evaluating metabolic syndrome: An experience from college students of Kolkata, India


1 Department of Food and Nutrition, Prasanta Chandra Mahalanobis Mahavidyalaya, West Bengal State University, Kolkata, Bengal, India
2 Department of Biochemistry and Nutrition, All India Institute of Hygiene and Public Health, Kolkata, Bengal, India
3 Department of Community Medicine, IQ City Medical College, Burdwan, West Bengal, India
4 Department of Home Science (Food and Nutrition), Viharilal College Campus, University of Calcutta, Kolkata, Bengal, India

Date of Submission21-Jul-2019
Date of Decision20-Dec-2019
Date of Acceptance21-Jan-2020
Date of Web Publication20-Jul-2020

Correspondence Address:
Tanima Paul Das
C/o Amiya Kanti Das, Sukanta Nagar 4th Sarani, P.O. Michaelnagar, P.S. Airport, Kolkata - 700 133, West Bengal
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/mjdrdypu.mjdrdypu_213_19

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  Abstract 


Background: Metabolic syndrome (MS) is gradually surging particularly among Asian Indians. Documented data on comparative studies based on different definitions with respect to MS prevalence among college students are few. Aim: The aim of this is to find the validity and degree of agreement between three different diagnostic criteria recommended by the International Diabetes Federation (IDF), the National Cholesterol Education Program-Adult Treatment Panel III (NCEP-ATP III), and the Consensus definition for Asian Indians (CDAI). Materials and Methods: A cross-sectional study was conducted among 477 college students aged 18–24 years of Kolkata selected by systematic random sampling from August 2011 to December 2014. Three different criteria, i.e., IDF, NCEP-ATP III, and CDAI, were used. Individuals signed a consent form before the study. Using IDF as a reference standard, validity of other criteria was measured by sensitivity and specificity. Cohen's kappa (κ) coefficient was used to identify the degree of agreement between three different definitions. Statistical analysis was performed using SPSS software, version 19.0. P ≤ 0.05 was considered statistically significant. Results: The prevalence of MS among college students was highest using the CDAI criteria (5.7%), followed by the IDF criteria (4.5%) and the NCEP-ATP III criteria (2.9%) being significantly higher in females (P ≤ 0.05). Using IDF as a reference standard, the sensitivity, specificity, positive predictive value, negative predictive value, and likelihood ratio of positive test for CDAI were 100%, 98.9%, 81.5%, 100%, and 90.9, respectively; whereas, for the NCEP-ATP III criteria, these were 45.5%, 99.1%, 71.4%, 97.4%, and 50.56, respectively. IDF presented “almost perfect” agreement in relation to the CDAI with κ of 0.892 (95% CI: 0.798–0.986, P = 0.000) and “moderate” agreement with respect to the NCEP-ATP III criteria with κ of 0.539 (95% CI: 0.339–0.739, P = 0.000). Conclusion: At least 2.9% of the Kolkata college students studied had MS. The CDAI criteria were superior to the NCEP-ATP III criteria for predicting MS in this population, when compared with the IDF criteria.

Keywords: Asian Indians, college students, criteria, Kolkata, metabolic syndrome


How to cite this article:
Das TP, Chaudhuri D, Saha I, Sen M. Comparison between three different diagnostic criteria in evaluating metabolic syndrome: An experience from college students of Kolkata, India. Med J DY Patil Vidyapeeth 2020;13:321-5

How to cite this URL:
Das TP, Chaudhuri D, Saha I, Sen M. Comparison between three different diagnostic criteria in evaluating metabolic syndrome: An experience from college students of Kolkata, India. Med J DY Patil Vidyapeeth [serial online] 2020 [cited 2020 Dec 1];13:321-5. Available from: https://www.mjdrdypv.org/text.asp?2020/13/4/321/290165




  Introduction Top


The main cause of mortality in India is attributed to cardiovascular diseases (CVDs).[1] CVD results mainly due to metabolic risk factors.[2] The constellation of key metabolic risk factors, namely insulin resistance, glucose intolerance, low high-density lipoprotein (HDL) cholesterol concentration, hypertriglyceridemia, hypertension, and abdominal obesity based on different formal definitions by various authorities is termed metabolic syndrome (MS).[3],[4],[5] The prevalence of MS varies markedly between different studies because of the lack of an international consensus for its definition although essential components are the same but often cutoff values are different and have varied mandatory inclusion criteria.[6] Increased prevalence and lowered age for the onset of MS are on rise among South Asians.[7] It may be due to Asian Indian phenotype with body composition features of having excess body fat with respect to skeletal muscle mass, low body mass index, higher magnitude of abdominal fat mass, higher waist-to-hip ratio, and truncal subcutaneous fat[8] in comparison to Caucasians. Westernization of diet also has a contributory role.[9] This age group of young college students is usually underestimated as per the clinical condition of MS is concerned.

With increasing burden of MS worldwide, several organizations have framed clinical criteria for the diagnosis of MS. In 2001, National Cholesterol Education Program-Adult Treatment Panel III (NCEP-ATP III, 2001) proposed an updated definition of MS with a focus on primary prevention of CVD. Equal weightage was given to all “lipid and nonlipid” parameters with the notion that all components posed an equivalent risk and their clustering will further increase the future risk of development of type 2 diabetes mellitus (T2DM) and CVD.[10] The NCEP-ATP III definition is diagnostic friendly being able to be carried out in a simple laboratory, but its applicability in risk prediction of CVD and T2DM is questionable and has been shown to underdiagnose insulin resistance.[11] The International Diabetes Federation (IDF) in 2005 proposed a single worldwide definition of MS which facilitates international comparisons of data in clinical and research purposes.[5] In the conceptual framework, the IDF definition emphasized on ethnic-specific threshold of waist circumference (WC) which is the mandatory criterion, and cutoffs of WC were lowered in both genders.[12] Literature suggest that Asian Indians exhibit higher morbidity at much lower values of WC than Caucasians.[13],[14] In the IDF criteria, cutoff value of fasting blood glucose (FBG) was also lowered to 100 mg/dl at par with the American Diabetes Association's new lower cutoff value of impaired fasting glucose (IFG),[15] as insulin resistance is the underlying factor which culminates to CVD. The IDF criteria are now being widely used in epidemiological studies to gather evidence.[16],[17] Misra et al. suggested a modification of the IDF criteria and termed it “consensus definition for Asian Indians” (CDAI, 2009) to provide guidelines in detection of MS specifically for Asian Indians. Abnormality of any three components out of five components was diagnostically defined as MS according to the CDAI criteria.[18] Cutoffs were similar to IDF, but there was no obligatory criterion. The use of different criteria to investigate MS leads to differences in the prevalence of MS in the same population.[6]

The prevalence of MS among college students of Kolkata has been reported earlier.[19] However, epidemiological studies involving the comparison between three criteria to diagnose MS have not been done earlier in Kolkata. The purpose of the study was to examine and compare the prevalence of MS among college students (both boys and girls) aged 18–24 years of Kolkata using different diagnostic criteria.


  Materials and Methods Top


This was a cross-sectional epidemiological study; 477 students aged 18–24 years were recruited by systematic random sampling from ten-degree colleges in Kolkata city and suburban areas. Unwilling students were excluded from the study. Students participated voluntarily and signed the consent form. The study protocol was approved by the Bioethics Committee for Animal and Human Research Studies, University of Calcutta (Ref. No. BEHR/1098/2304 dated 22/06/11). Systolic blood pressure (SBP) and diastolic blood pressure (DBP) were measured by a standardized sphygmomanometer.[20] Waist circumference measurement was made by a nonstretchable fiber plastic tape.[21] Biochemical tests for FBG,[22] serum HDL cholesterol,[23] and triglycerides[24] were done by standardized methods. For determining MS diagnostically, three criteria were employed: NCEP-ATP III,[10] IDF (for Asians),[5] and CDAI criteria.[18] The key characteristics of these criteria are presented in [Table 1]. The IDF criteria for assessing MS were assigned “reference standard,” and comparisons were drawn separately with the NCEP-ATP III and CDAI criteria, respectively, in this study considering the vulnerability of Asian Indians to central obesity (CO).
Table 1: Characteristics of diagnostic criteria for assessing metabolic syndrome

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Statistical analysis

The analysis was performed using Windows-based SPSS software, version 19.0 (Statistical Package for the Social Sciences Inc., Chicago, IL, USA). Categorical data were expressed in proportions. Continuous data were checked for normality by the Kolmogorov–Smirnov test. Cohen's kappa (κ) statistics were used for finding the agreement between the three definitions of MS. P ≤ 0.05 was considered statistically significant.


  Results Top


The prevalence of MS among college students of Kolkata was found to be 2.9%, 4.5%, and 5.7% according to the NCEP-ATP III, IDF, and CDAI criteria, respectively.

The absence of diagnostic concordance between different definitions poses confusion. The concordance and disparity between diagnoses using the NCEP-ATP III, IDF, and CDAI criteria among college students are presented in [Table 2] and [Table 3], respectively.
Table 2: Agreement among three definitions of metabolic syndrome (n=477)

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Table 3: Diagnosis of metabolic syndrome by International Diabetes Federation criteria and other criteria (National Cholesterol Education Program-Adult Treatment Panel III and Consensus Definition for Asian Indians) (n=477)

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Using the IDF criteria as “reference standard,” kappa statistics show that the CDAI is a better predictor of MS than the NCEP-ATP III criteria as there was “almost perfect” agreement between the CDAI and IDF criteria (κ = 0.892, 95% CI (0.798–0.986), P = 0.000), whereas there was a moderate agreement between the NCEP-ATP III and IDF criteria (κ = 0.539, 95% CI (0.339–0.739), P = 0.000) [Table 2].

The study revealed that 10 students with MS according to the definition of IDF had MS by the NCEP-ATP III definition as well (true positive), 12 students had MS as per the IDF definition but not by the NCEP-ATP III definition (false negative). Four hundred and fifty-one students fulfilled neither the IDF nor the NCEP-ATP III criteria. In consideration of the CDAI criteria, 22 students with MS according to the definition of IDF had MS by the CDAI criteria as well (true positive). Four hundred and fifty students fulfilled neither the IDF nor the NCEP-ATP III criteria [Table 3].

Moreover, the sensitivity of the CDAI criteria in detecting MS is 100% while that of the NCEP-ATP III criteria is 45.5%. The specificity values of the NCEP-ATP III and CDAI criteria were 99.1% and 98.9%, respectively. Other agreement statistics including positive predictive value (PPV), negative predictive value (NPV), likelihood ratio of positive test, and likelihood ratio of negative test indicate CDAI to be a better alternative to the IDF criteria in screening for MS than the NCEP-ATP III criteria [Table 3].


  Discussion Top


MS continues to amplify the public health burden in Asian Indians. However, data pertaining to MS among college students of Kolkata are rare. This study was designed to understand the difference in agreement between three definitions of MS given by the NCEP-ATP III, IDF, and CDAI criteria in this population. In this study, the prevalence of MS was highest with the CDAI criteria (5.7%) followed by IDF (4.5%) and NCEP-ATP III (2.9%), thus exhibiting differential prevalence. Prevalence estimates are similar to reports of the pooled analysis involving multiple studies across varied ethnicities which suggested a 5%–7% prevalence of MS among college students worldwide.[25] Discrepancies between different definitions could be explained by the fact that the prevalence of MS varied widely depending on the definition applied with different cutoff points for markers of CO and FBG. Moreover, the cutoff points of WC in the NCEP-ATP III criteria were primarily developed for Caucasians and might be inappropriate for Asian Indians[26],[27] which practically may have led to the exclusion of some metabolically deranged students.

High degree of concordance between the IDF and CDAI criteria was observed (Cohen's κ coefficient = 0.892) [Table 2] which might be due the fact that the two definitions use the same five diagnostic components, and apart from WC (mandatory component in IDF), the remaining components along with their threshold levels are nearly identically defined. Moreover, both criteria emphasize Asian Indian ethnicity considerations.

Concordance between the IDF and NCEP-ATP III definitions was found to be moderate (Cohen's κ coefficient = 0.539) [Table 2]. Possible explanation for this could be that NCEP-ATP III criteria was initially designed for risk prediction in Non-Asian Indian population and a wide gap exists between these two criteria in terms of WC cut off values. Moreover, recent data suggest that the NCEP-ATP III criteria cannot satisfactorily predict risk in Asian Indians.[26],[27] The NCEP-ATP III criteria give more priority to chronic metabolic conditions with equal weightage to all components, whereas IDF criteria emphasize more on abdominal obesity which gains importance in young college going population of Asian Indian origin. Hirani and Stamatakis conducted a study “Health Survey for England” among Chinese, Bangladeshi, Indian, and Pakistani (South Asian) men and general population of the UK; they reported that South Asians had the highest prevalence of CO.[28]

The sensitivity, specificity, PPV, NPV, likelihood ratio of positive test, and likelihood ratio of negative test of CDAI in diagnosing MS further explain its suitability over the NCEP-ATP III criteria [Table 3] for college students of Kolkata.

Published reports on the concordance between the diagnostic criteria for MS among college students are very rare. In a study carried out among university students in Fortaleza, Brazil, in 2017 by de Freitas et al., the prevalence of MS was 0.7% and 4.1% according to the NCEP-ATP III and IDF criteria, respectively. A reasonable agreement (Cohen's κ coefficient = 0.294) between the IDF and NCEP-ATP III criteria was reported.[29]

In a study among overweight and obese college students in Korea, carried out in 2010, by Cha et al., 12% and 20% of the students were found having MS according to the NCEP-ATP III and IDF criteria, respectively. Substantial agreement (Cohen's κ coefficient = 0.74) between the IDF and NCEP-ATP III definitions was found.[30]

Till date, no study compared the IDF, NCEP-ATP III, and CDAI criteria to assess MS among college students. However, a similar type of study was done among postmenopausal women of Singur, West Bengal, India, by Srimani and Chaudhuri[31] which reported the prevalence of MS being highest by the CDAI criteria (40.52%) followed by the IDF criteria (32.76%) and 27.59% by the NCEP-ATP III criteria. Agreement statistics revealed that CDAI was the better predictor of MS than the NCEP-ATP III criteria. Thus, the importance of CDAI was similarly established with regards to our study which may be due to same ethnicity and locale.

Limitations

The present study was cross-sectional in design with a sample size of 477; large-scale prospective studies with a much higher sample size would provide much more definitive findings. Only three most commonly used criteria were compared between themselves without considering other criteria such as the World Health Organization, 1998; the European Group of Insulin Resistance, 1999; and the modified ATP III, 2005, in this study.


  Conclusion Top


College students of Kolkata were found to be vulnerable to MS although the prevalence varied considerably according to the criteria used for diagnosis. Considering all the three criteria for determining MS, it can be said that at least 2.9% of the Kolkata college students studied were having MS. The CDAI criteria were established to be a superior predictor of MS over the NCEP-ATP III criteria in this population, when compared with the IDF criteria. Early detection, health promotion strategies, and positive motivation for good health need to be initiated in college and university settings.

Acknowledgment

The authors sincerely acknowledge participants who voluntarily agreed to participate in this study as also supportive staff and laboratory technicians of the Department of Biochemistry and Nutrition, All India Institute of Hygiene and Public Health, Kolkata, for their technical support.

Financial support and sponsorship

We thank UGC Eastern Regional Office, Kolkata, for funds vide UGC ERO Minor Research Project Grant Reference No. PSW-112/12-13(ERO) dated February 05, 2013.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Prabhakaran D, Jeemon P, Roy A. Cardiovascular diseases in India: Current epidemiology and future directions. Circulation 2016;133:1605-20.  Back to cited text no. 1
    
2.
Prabhakaran D, Singh K, Roth GA, Banerjee A, Pagidipati NJ, Huffman MD. Cardiovascular diseases in India compared with the United States. J Am Coll Cardiol 2018;72:79-95.  Back to cited text no. 2
    
3.
Alberti KG, Zimmet P, Shaw J; IDF Epidemiology Task Force Consensus Group. The metabolic syndrome-a new worldwide definition. Lancet 2005;366:1059-62.  Back to cited text no. 3
    
4.
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.  Back to cited text no. 4
    
5.
The IDF Consensus Worldwide Definition of the Metabolic Syndrome. Available from: http://www.idf.org/webdata/docs/IDF_Metasyndrome_definition.pdf. [Last accessed on 2019 Jun 01].  Back to cited text no. 5
    
6.
Day C. Metabolic Syndrome or what you will: Definitions and Epidemiology. Diabetes and Vascular Disease Research; 2007. Available from: http://dvr.sagepub.com/content/4/1/32.full.pdf+html. [Last accessed on 2019 May 31].  Back to cited text no. 6
    
7.
Gupta R, Misra A, Vikram NK, Kondal D, Gupta SS, Agrawal A, et al. Younger age of escalation of cardiovascular risk factors in Asian Indian subjects. BMC Cardiovasc Disord 2009;9:28.  Back to cited text no. 7
    
8.
Banerji MA, Faridi N, Atluri R, Chaiken RL, Lebovitz HE. Body composition, visceral fat, leptin, and insulin resistance in Asian Indian men. J Clin Endocrinol Metab 1999;84:137-44.  Back to cited text no. 8
    
9.
Misra A, Khurana L, Isharwal S, Bhardwaj S. South Asian diets and insulin resistance. Br J Nutr 2009;101:465-73.  Back to cited text no. 9
    
10.
National Cholesterol Education Program High Blood Cholesterol ATP III Guidelines At-A-Glance Quick Desk Reference. Available from: https://www.nhlbi.nih.gov/files/docs/guidelines/atglance.pdf. [Last accessed on 2019 Jun 01].  Back to cited text no. 10
    
11.
Liao Y, Kwon S, Shaughnessy S, Wallace P, Hutto A, Jenkins AJ, et al. Critical evaluation of adult treatment panel III criteria in identifying insulin resistance with dyslipidemia. Diabetes Care 2004;27:978-83.  Back to cited text no. 11
    
12.
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.  Back to cited text no. 12
    
13.
Misra A, Wasir JS, Vikram NK. Waist circumference criteria for the diagnosis of abdominal obesity are not applicable uniformly to all populations and ethnic groups. Nutrition 2005;21:969-76.  Back to cited text no. 13
    
14.
Snehalatha C, Viswanathan V, Ramachandran A. Cutoff values for normal anthropometric variables in Asian Indian adults. Diabetes Care 2003;26:1380-4.  Back to cited text no. 14
    
15.
Dekker JM, Balkau B. Counterpoint: Impaired fasting glucose: The case against the new American Diabetes Association Guidelines. Diabetes Care 2006;29:1173-5.  Back to cited text no. 15
    
16.
Kanitkar SA, Kalyan M, Diggikar P, More U, Kakrani AL, Gaikwad A, et al. Metabolic syndrome in medical students. J Int Med Sci Acad 2015;28:14-5.  Back to cited text no. 16
    
17.
Topè AM, Rogers PF. Metabolic syndrome among students attending a historically black college: Prevalence and gender differences. Diabetol Metab Syndr 2013;5:2.  Back to cited text no. 17
    
18.
Misra A, Chowbey P, Makkar BM, Vikram NK, Wasir JS, Chadha D, et al. Consensus statement for diagnosis of obesity, abdominal obesity and the metabolic syndrome for Asian Indians and recommendations for physical activity, medical and surgical management. J Assoc Physicians India 2009;57:163-70.  Back to cited text no. 18
    
19.
Das TP, Sen M, Saha I, Chaudhuri D. Prevalence and gender differentials of metabolic syndrome among college students of Kolkata, West Bengal, India. Int J Curr Res Rev 2017;9:14-8.  Back to cited text no. 19
    
20.
Pickering TG, Hall JE, Appel LJ, Falkner BE, Graves J, Hill MN, et al. Recommendations for blood pressure measurement in humans and experimental animals: Part 1: Blood pressure measurement in humans: A statement for professionals from the subcommittee of professional and public education of the American heart association council on high blood pressure research. Circulation 2005;111:697-716.  Back to cited text no. 20
    
21.
Anthropometry Procedures Manual. Available from: https://www.cdc.gov/nchs/data/nhanes/nhanes_07_08/manual_an.pdf. [Last accessed on 2018 Aug 30].  Back to cited text no. 21
    
22.
Jakobsen LK. Quantitative determination of blood glucose using glucose oxidase and peroxidase. Scalpel (Brux) 1960;12:76-9.  Back to cited text no. 22
    
23.
Herbert K. Lipids. In: Kaplan LA, Pesce AJ, editors. Clinical Chemistry; Theory, Analysis and Co-relation. Toronto: C.V. Mosby; 1984. p. 1182-230.  Back to cited text no. 23
    
24.
McGowan MW, Artiss JD, Strandbergh DR, Zak B. A peroxidase-coupled method for the colorimetric determination of serum triglycerides. Clin Chem 1983;29:538-42.  Back to cited text no. 24
    
25.
Nolan PB, Carrick-Ranson G, Stinear JW, Reading SA, Dalleck LC. Prevalence of metabolic syndrome and metabolic syndrome components in young adults: A pooled analysis. Prev Med Rep 2017;7:211-5.  Back to cited text no. 25
    
26.
Banerjee D, Misra A. Does using ethnic specific criteria improve the usefulness of the term metabolic syndrome? Controversies and suggestions. Int J Obes (Lond) 2007;31:1340-9.  Back to cited text no. 26
    
27.
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.  Back to cited text no. 27
    
28.
Hirani V, Stamatakis E. Anthropometric measures, overweight, and obesity. Scott Health Surv 2004;6:163-203.  Back to cited text no. 28
    
29.
de Freitas RW, de Araújo MF, Gaspar MW, Neto JC, Alencar AM, Zanetti ML, et al. Comparison of three criteria for metabolic syndrome among Brazilian university students. Nutr Food Sci 2017;47:543-52.  Back to cited text no. 29
    
30.
Cha E, Burke LE, Kim KH, Shin YA, Kim HY. Prevalence of the metabolic syndrome among overweight and obese college students in Korea. J Cardiovasc Nurs 2010;25:61-8.  Back to cited text no. 30
    
31.
Srimani S, Chaudhuri D. A Comparative study on metabolic syndrome using different criteria among rural post-menopausal women in Singur, West Bengal, India. Int J Sci Res 2016;5:43-5.  Back to cited text no. 31
    



 
 
    Tables

  [Table 1], [Table 2], [Table 3]



 

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