Cut-Off Values of Anthropometric Indices for the Prediction of Hypertension in a Sample of Egyptian Adults
DOI:
https://doi.org/10.3889/oamjms.2014.016Keywords:
Cut-off values, anthropometric indices, hypertension, adult Egyptians.Abstract
Background: Obesity, particularly abdominal adiposity, is closely associated with premature atherosclerosis and many metabolic modifications including insulin resistance dyslipidemia hypertension and diabetes. Cut-off values for abdominal obesity predicting future cardiovascular disease are known to be population specific.
Objective: To identify cut-off points of some anthropometric measurements (BMI, WC, WHR and WHtR) that associated with hypertension in a sample of Egyptian adults.
Subjects and Methods: This is a cross-sectional analysis. The blood pressure of 5550 Egyptian adults was measured (2670 females – 2880 males).The subjects represented different geographic localities and different social classes. Anthropometric measurements including height, weight, waist circumferences, and hip circumferences were also measured by practitioners.
Results: The cut-off values to detect hypertension in females were 30.08 for BMI, 87.75 for WC , 0.81 for WHR and 0.65 for WHtR, and the corresponding sensitivity and specificity were 69.1; 60.7- 80.9; 48.6 -65.3; 53.4 and 61.4; 58.9, respectively. The cut-off values to detect hypertension in males were 27.98 for BMI, 95.75 for WC, 0.92 for WHR, and 0.57 for WHtR and the corresponding sensitivity and specificity were 62.8; 59.9 -71.9; 51.9 -64.6; 55.8 and 59.7; 55.8, respectively.
Conclusion: The BMI, Waist circumference, WHR and WHtR values can predict the presence of hypertension risk in adult Egyptians.Downloads
Metrics
Plum Analytics Artifact Widget Block
References
Prinsloo J, Malan L, de Ridder JH, Potgieter JC, Steyn HS. Determining the waist circumference cut off which best predicts the metabolic syndrome components in urban Africans: the SABPA study. Exp Clin Endocrinol Diabetes. 2011;119(10):599-603. DOI: https://doi.org/10.1055/s-0031-1280801
Arthur FK, Adu-Frimpong M, Osei-Yeboah J, Mensah FO, Owusu L. Prediction of metabolic syndrome among postmenopausal Ghanaian women using obesity and atherogenic markers. Lipids Health Dis. 2012;11:101. DOI: https://doi.org/10.1186/1476-511X-11-101
Chakraborty R, Bose K, Kozieł S. Waist circumference in determining obesity and hypertension among 18-60 years old Bengalee Hindu male slum dwellers in Eastern India. Ann Hum Biol. 2011;38(6):669-75. DOI: https://doi.org/10.3109/03014460.2011.605396
Siren R, Eriksson JG, Vanhanen H. Waist circumference a good indicator of future risk for type 2 diabetes and cardiovascular disease. BMC Public Health. 2012;12:631. DOI: https://doi.org/10.1186/1471-2458-12-631
World Health Organization. Reducing risks, promoting healthy life - The World Health Report. Geneva: World Health Organization, 2002.
Ko GT, Chan JC, Cockram CS, Woo J. Prediction of hypertension, diabetes, dyslipidaemia or albuminuria using simple anthropometric indexes in Hong Kong Chinese.Int J Obes Relat Metab Disord. 1999;23: 1136-1142. DOI: https://doi.org/10.1038/sj.ijo.0801043
Dalton M, Cameron AJ, Zimmet PZ, Shaw JE, Jolley D, Dunstan DW, Welborn TA. AusDiab Steering Committee: Waist circumference, waist-hip ratio and body mass index and their correlation with cardiovascular disease risk factors in Australian adults. J Intern Med. 2003; 254:555-563. DOI: https://doi.org/10.1111/j.1365-2796.2003.01229.x
Welborn TA, Dhaliwal SS, Bennett SA. Waist-hip ratio is the dominant risk factor predicting cardiovascular death in Australia. Med J Aust. 2003;179:580–585. DOI: https://doi.org/10.5694/j.1326-5377.2003.tb05704.x
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) final report. Circulation. 2002; 106: 3143 – 3421. DOI: https://doi.org/10.1161/circ.106.25.3143
World Health Organization: Obesity: Preventing and managing the global epidemic: Report of a WHO Consultation on Obesity. Geneva, World Health Organization, 1998.
Hiernaux J, Tanner JM. Growth and physique: anthropometry. In: Weiner JS, Lourie JA, editors. Human biology: a guide to field methods. Oxford: Blackwell Scientific, 1969:pp. 2–42.
Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo JL Jr, Jones DW, Materson BJ, Oparil S, Wright JT Jr, Roccella EJ; National Heart, Lung, and Blood Institute Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure; National High Blood Pressure Education Program Coordinating Committee. The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report. JAMA. 2003;289(19):2560-72. DOI: https://doi.org/10.1001/jama.289.19.2560
Lee M, Saver JL, Chang B, Chang KH, Hao Q, Ovbiagele B. Presence of baseline prehypertension and risk of incident stroke. Neurology. 2011;77(14):1330–1337. DOI: https://doi.org/10.1212/WNL.0b013e3182315234
Baker JL, Olsen LW, Sorensen TI. Childhood body-mass index and the risk of coronary heart disease in adulthood. New Eng J Med. 2007; 357(23):2329-37. DOI: https://doi.org/10.1056/NEJMoa072515
Anderson RJ, Freedland KE, Clouse RE, Lustman PJ. The prevalence of comorbid depression in adults with diabetes: a meta-analysis. Diabetes Care. 2001; 24:1069–1078. DOI: https://doi.org/10.2337/diacare.24.6.1069
Direk K, Cecelja M, Astle W, Chowienczyk P, Spector T D, Falchi M and Andrew T. The relationship between DXA-based and anthropometric measures of visceral fat and morbidity in women. BMC Cardiovascular Disorders. 2013; 13:25. DOI: https://doi.org/10.1186/1471-2261-13-25
Kahn BB, Flier JS. Obesity and insulin resistance. Journal of Clinical Investigation. 2000;106(4):473–481. DOI: https://doi.org/10.1172/JCI10842
Hall JE, Hildebrandt DA, Kuo J. Obesity hypertension: role of leptin and sympathetic nervous system. American Journal of Hypertension. 2001;14(6):103S–115S. DOI: https://doi.org/10.1016/S0895-7061(01)02077-5
Horita S, Seki G, and Fujita T. Insulin Resistance, Obesity, Hypertension, and Renal Sodium Transport. Int J Hypertens. 2011; 2011: 391762. DOI: https://doi.org/10.4061/2011/391762
Sanya, AO, Ogwumike OO, Ige AP, Ayanniyi OA. Relationship of Waist-Hip Ratio and Body Mass Index to Blood Pressure of Individuals in Ibadan North Local Government. AJPARS. 2009;1(1):7-11. DOI: https://doi.org/10.4314/ajprs.v1i1.51306
Grundy SM, Brewer HB Jr, Cleeman JI, Smith SC Jr, Lenfant C. Definition of metabolic syndrome: Report of the National Heart, Lung, and Blood Institute/American Heart Association conference on scientific issues related to definition. Circulation. 2004; 109:433–438. DOI: https://doi.org/10.1161/01.CIR.0000111245.75752.C6
Deshmukh PR, Gupta SS, Dongre AR, et al. Relationship of anthropometric indicators with blood pressure levels in rural Wardha. Indian J Med Res. 2006; 123: 657-64.
Liu Y, Tong G , Tong W , Lu L , Qin X .Can body mass index, waist circumference, waist-hip ratio and waist-height ratio predict the presence of multiple metabolic risk factors in Chinese subjects? BMC Public Health. 2011; 11: 35. DOI: https://doi.org/10.1186/1471-2458-11-35
Despre´s J P. Obesity.Body Fat Distribution and Risk of Cardiovascular Disease An Update. Circulation. 2012;126:1301-1313. DOI: https://doi.org/10.1161/CIRCULATIONAHA.111.067264
Doll S, Paccaud F, Bovet P, Burnier M, Wietlisbach V. Body mass index, abdominal adiposity and blood pressure: consistency of their association across developing and developed countries. Int J Obes. 2002;6:48–57. DOI: https://doi.org/10.1038/sj.ijo.0801854
Zhao LC, Wu YF, Zhou BF, Li Y, Yang J. Mean level of blood pressure and rate of hypertension among people with different levels of body mass index and waist circumference. Zhonghua Liu Xing Bing Xue Za Zhi. 2003; 24: 471-5.
Fang F, Nie J. Study of body mass index and waist circumference in association with blood pressure in adult Guangzhou residents. Di Yi Jun Yi Da Xue Xue Bao. 2003; 23: 837-40.
Moni MA, Rahman MA, Haque MA, Islam MS, Ahmed K. Blood pressure in relation to selected anthropometric measurements in senior citizens. Mymensingh Med J. 2010;19(2):254-8.
Saeed F, Jawad A, Azmat A, Azam I, Kagazwala S. Anthropometric measurements as a risk for hypertensive disorders in pregnancy: a hospital based study in South Asian population. J Pak Med Assoc. 2011;61(1):58-63.
Zhang WH, Zhang L, An WF, Ma JL. Prehypertension and clustering of cardiovascular risk factors among adults in suburban Beijing, China. J Epidemiol. 2011;21(6):440-6. DOI: https://doi.org/10.2188/jea.JE20110022
Selcuk A, Bulucu F, Kalafat F, Cakar M, Demirbas S, Karaman M, Ay SA, Saglam K, Balta S, Demirkol S, Arslan E. Skinfold thickness as a predictor of arterial stiffness: obesity and fatness linked to higher stiffness measurements in hypertensive patients. Clin Exp Hypertens. 2013;35(6):459-64. DOI: https://doi.org/10.3109/10641963.2012.746357
Shahbazpour N. Prevalence of overweight and obesity and their relation to hypertension in adult male university students in Kerman, Iran. Int J Endocrinol Metab. 2003; 2 : 55-60.
Hsieh SD, Yoshinaga H, Muto T, Sakurai Y, Kosaka K. Health risks among Japanese men with moderate body mass index. Int J Obes Relat Metab Disord. 2000; 24: 358–362. DOI: https://doi.org/10.1038/sj.ijo.0801157
Seidell JC, Cigolini M, Deslypere JP, Charzewska J, Ellsinger BM, Cruz A. Body fat distribution in relation to serum lipids and blood pressure in 38-year-old European men: the European fat distribution study. Atherosclerosis. 1991; 86: 251-60. DOI: https://doi.org/10.1016/0021-9150(91)90221-N
Gus M, Fuchs SC, Moreira LB, Moraes RS, Wiehe M, Silva AF, et al. Association between different measurements of obesity and the incidence of hypertension. Am J Hypertens. 2004; 17 : 50-3. DOI: https://doi.org/10.1016/j.amjhyper.2003.08.010
Assmann G, editor. Lipid metabolism disorders and coronary heart disease: primary prevention, diagnosis, and therapy guidelines for general practice. 2nd ed. Munich: MMV Medizin Verlag, 1993:281.
Bonorra E, Zenere M, Branzi P, Bagnani M, Maggiulli L,Tosi F, et al. Influence of body fat and its regional localization on risk factors for atherosclerosis in young men. Am J Epidemiol. 1992; 135 : 1271-8. DOI: https://doi.org/10.1093/oxfordjournals.aje.a116233
Woo J, Ho SC, Yu AL, Sham A. Is waist circumference a useful measure in predicting health outcomes in the elderly? Int J Obes Relat Metab Disord. 2002; 26 : 1349-55. DOI: https://doi.org/10.1038/sj.ijo.0802080
Al-Lawati JA, and Jousilahti P. Body mass index, waist circumference and waist-to-hip ratio cut-off points for categorisation of obesity among Omani Arabs. Public Health Nutr. 2008;11(1):102-8. DOI: https://doi.org/10.1017/S1368980007000183
Wang Z, Hoy WE. Waist circumference, body mass index, hip circumference and waist-to-hip ratio as predictors of cardiovascular disease in Aboriginal people. Eur J Clin Nutr. 2004;58(6):888-93. DOI: https://doi.org/10.1038/sj.ejcn.1601891
Janssen I, Katzmarzyk PT, Ross R. Waist circumference and not body mass index explains obesity-related health risk. Am J Clin Nutr. 2004; 79:379-384. DOI: https://doi.org/10.1093/ajcn/79.3.379
Brenner DR, Tepylo K, Eny KM, Cahill LE, El-Sohemy A: Comparison of body mass index and waist circumference as predictors of cardiometabolic health in a population of young Canadian adults. Diabetol Metab Syndr. 2010; 2(1):28. DOI: https://doi.org/10.1186/1758-5996-2-28
Leitzmann MF, Moore SC, Koster A, Harris TB, Park Y, Hollenbeck A, et al: Waist circumference as compared with body-mass index in predicting mortality from specific causes. PLoS One. 2011; 6(4):e18582. DOI: https://doi.org/10.1371/journal.pone.0018582
Reidpath DD, Cheah JC, Lam FC, Yasin S, Soyiri I, Allotey P. Validity of self-measured waist and hip circumferences: results from a community study in Malaysia. Nutr J. 2013;12(1):135. DOI: https://doi.org/10.1186/1475-2891-12-135
Zhu S, Wang Z, Heshka S, et al. Waist circumference and obesity-associated risk factors among whites in the third National Health and Nutrition Examination Survey: clinical action thresholds. Am J Clin Nutr. 2002; 76: 743-749. DOI: https://doi.org/10.1093/ajcn/76.4.743
Janssen I, Katzmarzyk PT, Ross R. Body mass index, waist circumference, and health risk: evidence in support of current National Institutes of Health guidelines. Arch Intern Med. 2002;162:2074-9 DOI: https://doi.org/10.1001/archinte.162.18.2074
Huxley R, James WPT, Barzi F, Patel JV, Lear SA, Suriyawongpaisal P, Janus E, Caterson I, Zimmet P, Prabhakaran D, Reddy S, Woodward M, Obesity in Asia Collaboration: Ethnic comparisons of the cross-sectional relationships between measures of body size with diabetes and hypertension. Obes Rev. 2008, 9:53-61. DOI: https://doi.org/10.1111/j.1467-789X.2007.00439.x
Ashwell, M., Gunn, P. and Gibson, S. Waist-to-height ratio is a better screening tool than waist circumference and BMI for adult cardiometabolic risk factors: systematic review and meta-analysis. Obesity Reviews. 2013;13: 275–286. DOI: https://doi.org/10.1111/j.1467-789X.2011.00952.x
Lee K, Song YM, Sung J. Which obesity indicators are better predictors of metabolic risk? Healthy Twin Study. Obesity (Silver Spring). 2008;16:834-840. DOI: https://doi.org/10.1038/oby.2007.109
Sayeed MA, Mahtab H, Latif ZA, et al. Waist-to-height ratio is a better obesity index than body mass index and waist-to-hip ratio for predicting diabetes, hypertension and lipidemia. Bangladesh Med Res Counc Bull. 2003; 29: 1-10.
Cai L, Liu A, Zhang Y, Wang P. Waist-to-height ratio and cardiovascular risk factors among Chinese adults in Beijing. PLoS One. 2013;8(7):e69298. DOI: https://doi.org/10.1371/journal.pone.0069298
Tarleton HP, Smith LV, Zhang ZF, Kuo T. Utility of Anthropometric Measures in a Multiethnic Population: Their Association with Prevalent Diabetes, Hypertension and Other Chronic Disease Comorbidities. J Community Health. 2013 Oct 17. [Epub ahead of print] PubMed PMID: 24132872. DOI: https://doi.org/10.1007/s10900-013-9780-z
Lin WY, Lee LT, Chen CY, et al. Optimal cut-off values for obesity: using simple anthropometric indices to predict cardiovascular risk factors in Taiwan. Int J Obes Relat Metab Disord. 2002; 26: 1232-8. DOI: https://doi.org/10.1038/sj.ijo.0802040
Zhang X, Shu XO, Gao YT, Yang G, Matthews CE, Li Q, Li H, Jin F, Zheng W. Anthropometric predictors of coronary heart disease in Chinese women. Int J Obes Relat Metab Disord. 2004;28(6):734–40. DOI: https://doi.org/10.1038/sj.ijo.0802634
Ibrahim MM, Elamragy AA, Girgis H, Nour MA. Cut off values of waist circumference and associated cardiovascular risk in Egyptians. BMC Cardiovasc Disord. 2011;11:53. DOI: https://doi.org/10.1186/1471-2261-11-53
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: 253-8. DOI: https://doi.org/10.1016/j.arcmed.2006.09.014
Mansour AA, Al-Hassan AA, Al-Jazairi MI. Toward establishing normal waist circumference in Eastern Mediterranean and Middle East (Arab) populations. Cutoff values for waist circumference in Iraqi adults. Int J Diabetes & Metabolism. 2007;15: 14-16. DOI: https://doi.org/10.22605/RRH765
Park SH, Choi SJ, Lee KS, Park HY. Waist circumference and waist-to-height ratio as predictors of cardiovascular disease risk in Korean adults. Circ J. 2009;73(9):1643-50. DOI: https://doi.org/10.1253/circj.CJ-09-0161
Gupta S, Kapoor S. Optimal cut-off values of anthropometric markers to predict hypertension in North Indian population. J Community Health. 2012;37(2):441-7. DOI: https://doi.org/10.1007/s10900-011-9461-8
Downloads
Published
How to Cite
Issue
Section
License
http://creativecommons.org/licenses/by-nc/4.0