Cutoff Point Measurement of the waist circumference for the diagnosis of Metabolic Syndrome in Iraqi university students

 

Alaa Hasoon Zamil*, Seenaa Sadiq Amin

Department of Clinical Laboratory Sciences, College of Pharmacy, University of Baghdad, Baghdad, Iraq.

*Corresponding Author E-mail: alaa.hasoon.zamil@gmail.com

 

ABSTRACT:

Background: Metabolic syndrome (MetS) is a collection of connected cardiovascular risk factors that characterizes the complicated illness. The waist circumference cutoff point fluctuation has so far defined Mets. Objective: This study aimed to determine the cutoff point for WC in healthy Iraqi adults. Methods: This cross-sectional survey establishes the standard value for WC among 300 healthy university students in Wasit city, Iraq. They are aged between 18-25 years. The receiver operator characteristic (ROC) curve was used WC to predict the presence of two or more risk factors for MetS, as defined by IDF. Results: The cutoff level yielding maximum sensitivity and specificity for predicting the presence of multiple risk factors was 82.5cm in females (sensitivity 65%, specificity 70%) and 91cm in males(sensitivity 50%, specificity 75%). Conclusion: Results propose that 82.5cm for females and 91cm for males represent the ideal WC cutoff points for diagnosing MetS in young adult participants from Iraq.

 

KEYWORDS: Metabolic syndrome, Waist circumference.

 

 


INTRODUCTION: 

Metabolic syndrome (MetS) is a complex disorder categorized by a group of interrelated factors that rise the risk of cardiovascular disease (CVD) and type 2 diabetes (T2DM)1-5. The etiology of MetS contributes to numerous factors upon which genetic and environmental factors have a  critical role in the disposition of the disease6-8; several health organizations have defined the syndrome and published diagnostic criteria  using five parameters, including elevation of waist circumference (WC), blood pressure (BP), triglycerides (TG), fasting blood glucose (FBG), and reduced HDL-C level to define MetS9-11. A critical component in the pathogenesis of MetS is elevated WC, which is characterized by the accumulation of fat in the visceral region of the abdomen12-14.

 

WC is recommended by many organizations and professional groups as a criterion to define MetS.

 

Before suitable cutoff levels are established for use in clinical practice, the International Diabetes Federation (IDF) definition of MetS considers WC to be ethnically specific and strongly advises that more in-depth investigations be carried out15.

 

The determination of cutoff points for healthy waist circumference (WC) is of chief importance for the prevention and controlling of obesity, metabolic syndrome (MetS), type 2 diabetes mellitus, and coronary heart disease16. WC is widely regarded as the most accurate anthropometric measure of abdominal adiposity17. and is one of the five anthropometric indices for diagnosing obesity18. Additionally, it serves as a more accurate indicator of obesity than the body mass index (BMI). Because BMI alone is not a sufficient biomarker of abdominal adiposity, it falls short of accurately capturing cardiometabolic risk. Waist circumference is a straight forward, standard, and clinically applicable way to measure abdominal adiposity19. The IDF advised using European data for populations in the eastern Mediterranean and Middle East (Arab) until more specific data became available. For Europeans, the cutoff was ≥94cm for males and ≥80 cm for females15. The purpose of this study was to estimate the cutoff level for WC in  healthy university students in Iraq as one of the diagnostic criteria of MetS.

 

MATRERIALS AND METHODS:

Design and samples:

This cross-sectional study was conducted between October 2021 and February 2022 at Wasit University in Wasit, Iraq. by participant 300 adult university students aged between (18-25) years.

 

Data collection:

Anthropometric, blood pressure, and biochemical parameters were measured and self-administered standard questionnaires were used to collect the data. Measurements of blood pressure was taken after the participants had rested for at least five minutes. At the level of the heart, the left arm was used to take the measurements. The analysis in each case used the average of two results20. BMI was calculated as weight (kg) divided by height squared (m2). The non-elastic measuring tape was placed halfway between the lower rib margin and the iliac crest, where the WC was measured. To the nearest 0.5cm, it was measured21. 5 mL of blood samples were drawn with the subjects, following an overnight 8-10hr. fast.  The serum was separated within 30minutes (3000rpm, 5minutes) to measure FBG, TG, and HDL-C.

 

Multiple risk factors were defined in this study as subjects who had two or more of the following four IDF criteria risk factors:

·      Elevated TG level: >150mg/dL (1.7mmol/L);

·      Elevated blood pressure: systolic BP ≥130mmHg or diastolic BP ≥85mmHg;

·      Elevated fasting plasma glucose (FPG) ≥100mg/dL  (5.6mmol/L);

·      Reduced HDL cholesterol: <40mg/dL (0.9mmol/L) in males and <50mg/dL (1.1mmol/L) in females.

 

Statistical procedure:

The data analysis was done separately for males and females by using SPSS version 25 for windows. The receiver operator characteristic (ROC) curve for WC to predict the presence of two or more risk factors for MetS as defined by IDF was plotted. The WC value was calculated by plotting the true positive rate (sensitivity) against the false-positive rate (1-specificity).

 

RESULTS:

Plotting the ROC curves allowed for the determination of the WC cutoff values in relation to the study of different risk factors in the Iraqi population. Based on ROC curve analysis, the WC value for predicting metabolic risk factors—the best combination of sensitivity and specificity for identifying subjects with multiple risk factors—was determined. The cutoff level yielding maximum sensitivity and specificity for predicting the presence of multiple risk factors was 82.5 cm in female (sensitivity 65%, specificity 70%) (Fig. 1) and 91cm in males (sensitivity 50%, specificity 75%) (Fig. 2) (table 1).

 

Table 1: ROC curve results for waist circumference of the participant for both genders.

 

cutoff values cm)

AUC

Sensitivity (%)

Specificity (100%)

Waist circumference in male

91

0.64

50

75

Waist circumference in female

82.5

0.78

65

70

 

Fig 1. ROC curve for cut-off value of waist circumference for females.

 

Fig 2. ROC curve for cut-off value of waist circumference for males.

 

DISCUSSION:

The IDF determined that the presence of central obesity plus any two of the following four factors is required for the diagnosis of MetS: increased TG level, decreased HDL cholesterol, increased blood pressure, increased FBG (or prior type 2 diabetes)15.

 

The IDF proposed that the diagnosis of MetS must include central obesity as measured by WC cutoff values specific to ethnicity and gender22. A key aspect of the IDF definition is that central obesity is an important element of MetS and should have an ethnically specific value.

 

In Iraq, the study associating a cutoff point for WC with increased risk of cardiovascular disease suggested values was 97cm for males and 99cm for females23. Another study in Iraq's Erbil city determined the cutoff point to be 94.7cm for males and 97 cm for females24. While in this study, the cutoff point in Wasit, Iraq for healthy university students was near to IDF cutoff point at 82.5cm for females and 91cm for males. This data will allow us to study the prevalence of MetS in Iraq with far greater accuracy.

 

Several studies that have been carried out in Middle East countries showed that the cutoff values of waist circumference of the participant for both genders25-30 (Table 2). Regarding to the finding of these studies, Middle East countries are likely to obtain special criteria for diagnosing metabolic syndrome and optimal cut-off value for WC in more in accordance with the population in this region.

 

Table 2: Cutoff values of waist circumference of the participant for both genders.

Country-reference

Cutoff point for male

Cutoff point for female

Turkey25

83 cm

93 cm

Tunisian26

85 cm

85 cm

Iran 27

91 cm

89 cm

Egypt28

100.5 cm

96.25 cm

Omani Arabs29

80 cm

84.5 cm

Qatar30

102 cm

94 cm

Iraq23

Erbil24

Wasit

97 cm

94.7 cm

91 cm

99 cm

97 cm

82.5 cm

 

CONCLUSION:

As a result, we recommended 82.5 cm for females and 91 cm for males as the ideal WC cutoff point for the diagnosis of MetS in the adult population attending an Iraqi university.

 

REFERENCES:

1.     Razi SM, Manish G, Keshav GK, Sukriti K, Gupta A. Site or size of waist circumference, which one is more important in metabolic syndrome? Int J Med Public Heal. 2016; 6(2).

2.     S. Mounika , G. Savitha. Association of Periodontal Diseases and Metabolic Syndrome. Research J. Pharm. and Tech. 2015; 8(8): 994-996. doi: 10.5958/0974-360X.2015.00166.3

3.     Do-Jin Kim, Jong-HyuckKim. Relationship between Cardiopulmonary function Metabolic Syndrome Indices. Research J. Pharm. and Tech. 2017; 10(11): 3868-3872. doi: 10.5958/0974-360X.2017.00702.8

4.     Manikumar. M, R. Monisha. Comparative Study of Aerobic Exercise and Weight training on Metabolic Syndrome among Breast Cancer Survivors. Research J. Pharm. and Tech. 2019; 12(6): 2772-2775. doi: 10.5958/0974-360X.2019.00465.7

5.     Parvathi K J, Ramalingam Kameswaran R, Sambathkumar R. Pshycotropic Drugs: A Persuader for Metabolic Syndromes. Research J. Pharm. and Tech. 2020; 13(6): 2695-2698. doi: 10.5958/0974-360X.2020.00479.5

6.     Aziz TA. The Role of Ginkgo biloba Extract as Monotherapy in Improving the Outcomes of Patients with Metabolic Syndrome: A Pilot Comparative Study with Metformin. Iraqi J Pharm Sci. 2021; 30(1): 258–69.

7.     Mahadeva Rao US, S. Siddharthan, Sowmya. R, A. Sathivel, Thant Zin, Naresh Bhaskar Raj. Assessment of Malaysian University Undergraduate’s Knowledge and Awareness on Metabolic Syndrome and Conditions related to it. Research Journal of Pharmacy and Technology. 2021; 14(4): 1893-8. doi: 10.52711/0974-360X.2021.00334

8.     Nageeb Hassan, Moyad Shahwan, Sahab Alkhoujah, Ammar Jairoun. Association between Serum liver Enzymes and Metabolic Syndrome among Type 2 Diabetes mellitus patients. Research J. Pharm. and Tech. 2021; 14(2): 1050-1054. doi: 10.5958/0974-360X.2021.00188.8

9.     Pedrinelli R, Dell’Omo G, Di Bello V, Pontremoli R, Mariani M. Microalbuminuria, an integrated marker of cardiovascular risk in essential hypertension. J Hum Hypertens. 2002;16(2):79–89.

10.   S. Sarumathy, P. Samuel Gideon George, B.Yeswanth Prasanna Kumar, V.Atheena Mukundan, T.S. Shanmugarajan, P. Maheshwari. Clinical Comparison of Serum Lipids between Cyclosporine and Tacrolimus Treated Renal Transplant Recipients. Research J. Pharm. and Tech. 2016; 9(6): 694-698 . doi: 10.5958/0974-360X.2016.00130.X

11.   Akram Ashames, Nageeb Hassan, Kristen Alamir, Kamar Modalaleh, Alin Naser, Aya Khawatmi. Correlation between Neck Circumference, Waist Circumference, Body Mass Index, and Overweight/Obesity among Ajman University Students. Research J. Pharm. and Tech. 2019; 12(5): 2443-2452. doi: 10.5958/0974-360X.2019.00410.4

12.   Fezeu L, Balkau B, Kengne A-P, Sobngwi E, Mbanya J-C. Metabolic syndrome in a sub-Saharan African setting: central obesity may be the key determinant. Atherosclerosis. 2007; 193(1): 70–6.

13.   Nihal Abdalla Ibrahim, Nada M Saleh, Fatma Koprulu, Altaf H Abdulrahim. Metabolic Syndrome associated Risk factors: Findings among female undergraduate university students. Research J. Pharm. and Tech. 2020; 13(12): 6093-6097. doi: 10.5958/0974-360X.2020.01062.8

14.   Koushik Bhattacharya, Pallav Sengupta, Sulagna Dutta, Soumita Bhattacharya. Pathophysiology of Obesity: Endocrine, Inflammatory and Neural regulators. Research J. Pharm. and Tech. 2020; 13(9): 4469-4478. doi: 10.5958/0974-360X.2020.00789.1

15.   Alberti KGMM, Zimmet P, Shaw J. The metabolic syndrome—a new worldwide definition. Lancet [Internet]. 2005 Sep 24 [cited 2022 Mar 1];366(9491):1059–62. Available from: http://www.thelancet.com/article/S0140673605674028/fulltext

16.   Alkhalidy H, Orabi A, Alnaser K, Al-Shami I, Alzboun T, Obeidat MD, et al. Obesity measures as predictors of type 2 diabetes and cardiovascular diseases among the jordanian population: A cross-sectional study. Int J Environ Res Public Health. 2021; 18(22).

17.   Zhang F-L, Ren J-X, Zhang P, Jin H, Qu Y, Yu Y, et al. Strong Association of Waist Circumference (WC), Body Mass Index (BMI), Waist-to-Height Ratio (WHtR), and Waist-to-Hip Ratio (WHR) with Diabetes: A Population-Based Cross-Sectional Study in Jilin Province, China. J Diabetes Res. 2021.

18.   Consultation WHO. Obesity: preventing and managing the global epidemic. World Health Organ Tech Rep Ser. 2000; 894: 1–253.

19.   Ross R, Neeland IJ, Yamashita S, Shai I, Seidell J, Magni P, et al. Waist circumference as a vital sign in clinical practice: a Consensus Statement from the IAS and ICCR Working Group on Visceral Obesity. Nat Rev Endocrinol. 2020; 16(3): 177–89.

20.   Ranasinghe P, Cooray DN, Jayawardena R, Katulanda P. The influence of family history of hypertension on disease prevalence and associated metabolic risk factors among Sri Lankan adults. BMC Public Health. 2015; 15(1): 1–9.

21.   Tolonen H, Kuulasmaa K, Laatikainen T, Wolf H. European Health Risk Monitoring Project. Recomm Indic Int Collab Protoc Man Oper chronic Dis risk factor Surv. 2002;

22.   Al-Azzawi OF. Metabolic syndrome; comparing the results of three definition criteria in an Iraqi sample. AL-Kindy Coll Med J. 2018; 14(2): 7–12.

23.   Mansour AA, Al-Jazairi MI. Cut-off values for anthropometric variables that confer increased risk of type 2 diabetes mellitus and hypertension in Iraq. Arch Med Res. 2007; 38(2): 253–8.

24.   Ahmed SM, Ismail SA. Cut-off measurement of waist circumference for the diagnosis of abdominal obesity in a population of Erbil City, Iraq. Invest Clin. 2019; 60(3): 213–20.

25.   Uzunlulu M, Oğuz A, Aslan G, Karadağ F. Cut-off values for waist circumference in Turkish population: is there a threshold to predict insulin resistance. Turk Kardiyol Dern Ars. 2009; 37(Suppl 6):17–23.

26.   Bouguerra R, Alberti H, Smida H, Salem LB, Rayana CB, El Atti J, et al. Waist circumference cut‐off points for identification of abdominal obesity among the Tunisian adult population. Diabetes, Obes Metab. 2007; 9(6): 859–68.

27.   Delavari A, Forouzanfar MH, Alikhani S, Sharifian A, Kelishadi R. First nationwide study of the prevalence of the metabolic syndrome and optimal cutoff points of waist circumference in the Middle East: the national survey of risk factors for noncommunicable diseases of Iran. Diabetes Care. 2009; 32(6): 1092–7.

28.   Assaad-Khalil SH, Mikhail MM, Aati TA, Zaki A, Helmy MA, Megallaa MH, et al. Optimal waist circumference cutoff points for the determination of abdominal obesity and detection of cardiovascular risk factors among adult Egyptian population. Indian J Endocrinol Metab. 2015; 19(6): 804.

29.   Al-Lawati JA, Barakat NM, Al-Lawati AM, Mohammed AJ. Optimal cut-points for body mass index, waist circumference and waist-to-hip ratio using the Framingham coronary heart disease risk score in an Arab population of the Middle East. Diabetes Vasc Dis Res. 2008; 5(4): 304–9.

30.   Al-Thani MH, Cheema S, Sheikh J, Mamtani R, Lowenfels AB, Al-Chetachi WF, et al. Prevalence and determinants of metabolic syndrome in Qatar: results from a National Health Survey. BMJ Open. 2016; 6(9): e009514.

 

 

 

 

Received on 17.08.2022           Modified on 12.06.2023

Accepted on 05.12.2023          © RJPT All right reserved

Research J. Pharm. and Tech 2024; 17(1):127-130.

DOI: 10.52711/0974-360X.2024.00020