Author(s): Alaa Hasoon Zamil, Seenaa Sadiq Amin


DOI: 10.52711/0974-360X.2024.00020   

Address: Alaa Hasoon Zamil*, Seenaa Sadiq Amin
Department of Clinical Laboratory Sciences, College of Pharmacy, University of Baghdad, Baghdad, Iraq.
*Corresponding Author

Published In:   Volume - 17,      Issue - 1,     Year - 2024

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.

Cite this article:
Alaa Hasoon Zamil, Seenaa Sadiq Amin. Cutoff Point Measurement of the waist circumference for the diagnosis of Metabolic Syndrome in Iraqi university students. Research Journal of Pharmacy and Technology. 2024; 17(1):127-0. doi: 10.52711/0974-360X.2024.00020

Alaa Hasoon Zamil, Seenaa Sadiq Amin. Cutoff Point Measurement of the waist circumference for the diagnosis of Metabolic Syndrome in Iraqi university students. Research Journal of Pharmacy and Technology. 2024; 17(1):127-0. doi: 10.52711/0974-360X.2024.00020   Available on:

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:
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.

Recomonded Articles:

Research Journal of Pharmacy and Technology (RJPT) is an international, peer-reviewed, multidisciplinary journal.... Read more >>>

RNI: CHHENG00387/33/1/2008-TC                     
DOI: 10.5958/0974-360X 

56th percentile
Powered by  Scopus

SCImago Journal & Country Rank

Recent Articles


Not Available