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The Best Central Adiposity Index in the Prediction of Cardiovascular Risk Factors in South-Western Nigeria

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DOI: 10.4236/ojemd.2015.512023    3,014 Downloads   3,450 Views   Citations

ABSTRACT

Objective: To determine the best index of central obesity that predicts cardiovascular risk factors (general obesity and hypertension). Methods: A cross-sectional study involving nine hundred and sixteen (443 males and 473 females) participants of a community health survey in Sagamu and Remo-North Local Government Areas of Ogun State, Nigeria. The body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR) and waist-to-height ratio (WHtR) of the participants were determined by standard protocols. Pearson correlation between BMI and the three central obesity indices was determined. The area under curve (AUC) on the ROC was used to determine the best measure of central obesity which identified individuals with general obesity and hypertension. Results: WHtR and WC were better than WHR at detecting the presence of both general obesity and hypertension in both males (WHtR vs WHR {difference in areas = 0.131} p < 0.0001; WC vs WHR {difference in areas = 0.132} p < 0.0001), and females (WHtR and WHR {difference in areas = 0.214} p < 0.0001; WC and WHR {difference in areas = 0.205} p < 0.0001). Conclusions: WHtR is as good as WC but better than WHR in identifying individuals with cardiovascular risk factors, and may also be a good criterion to diagnose metabolic syndrome.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

Raimi, T. , Fasanmade, O. , Odusan, O. and Ohwovoriole, A. (2015) The Best Central Adiposity Index in the Prediction of Cardiovascular Risk Factors in South-Western Nigeria. Open Journal of Endocrine and Metabolic Diseases, 5, 184-192. doi: 10.4236/ojemd.2015.512023.

References

[1] World Health Organization (2000) Obesity: Preventing and Managing the Global Epidemic. Report of a WHO Consultation. World Health Organ Technical Report Series 894, i-xii, 1-253.
http://whqlibdoc.who.int/trs/WHO_TRS_894_%28part1%29.pdf
[2] Flegal, K.M., Kit, B.K., Orpana, H. and Graubard, B.I. (2013) Association of All-Cause Mortality with Overweight and Obesity Using Standard Body Mass Index Categories: A Systematic Review and Meta-Analysis. JAMA, 309, 71-82. http://dx.doi.org/10.1001/jama.2012.113905
[3] Chen, Y., Copeland, W.K., Vedanthan, R., Grant, E., Lee, J.E., Gu, D., et al. (2013) Association between Body Mass Index and Cardiovascular Disease Mortality in East Asians and South Asians: Pooled Analysis of Prospective Data from the Asia Cohort Consortium. BMJ, 347, f5446.
http://dx.doi.org/10.1136/bmj.f5446
[4] Huang, K.C., Lin, W.Y., Lee, L.T., et al. (2002) Four Anthropometric Indices and Cardiovascular Risk Factors in Taiwan. International Journal of Obesity and Related Metabolic Disorders, 26, 1060-1068. http://dx.doi.org/10.1038/sj.ijo.0802047
[5] Farin, H.M., Abbasi, F. and Reaven, G.M. (2006) Comparison of Body Mass Index versus Waist Circumference with the Metabolic Changes That Increase the Risk of Cardiovascular Disease in Insulin-Resistant Individuals. American Journal of Cardiology, 98, 1053-1056.
http://dx.doi.org/10.1016/j.amjcard.2006.05.025
[6] Sung, K.C., Ryu, S. and Reaven, G.M. (2007) Relationship between Obesity and Several Cardiovascular Disease Risk Factors in Apparently Healthy Korean Individuals: Comparison of Body Mass Index and Waist Circumference. Metabolism: Clinical and Experimental, 56, 297-303.
http://dx.doi.org/10.1016/j.metabol.2006.09.016
[7] Page, J.H., Rexrode, K.M., Hu, F., Albert, C.M., Chae, C.U. and Manson, J.E. (2009) Waist-Height Ratio as a Predictor of Coronary Heart Disease among Women. Epidemiology, 20, 361-366.
http://dx.doi.org/10.1097/EDE.0b013e31819f38f1
[8] Goh, L.G., Dhaliwal, S.S., Welborn, T.A., Lee, A.H. and Della, P.R. (2014) Anthropometric Measurements of General and Central Obesity and the Prediction of Cardiovascular Disease Risk in Women: A Cross-Sectional Study. BMJ Open, 4, e004138. http://dx.doi.org/10.1136/bmjopen-2013-004138
[9] Alberti, K.G., Zimmet, P. and Shaw, J. (2005) The Metabolic Syndrome—A New Worldwide Definition. Lancet, 366, 1059-1062. http://dx.doi.org/10.1016/S0140-6736(05)67402-8
[10] Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (2001) 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, 285, 2486-2497. http://dx.doi.org/10.1001/jama.285.19.2486
[11] World Health Organization (1999) Definition and Diagnosis of Diabetes Mellitus and Intermediate Hyperglycemia: Report of a WHO Consultation. World Health Organization, Geneva.
http://www.who.int/diabetes/publications/Definition%20and%20diagnosis%20of%20diabetes_new.pdf
[12] Ashwell, M., Gunn, P. and Gibson, S. (2012) 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, 13, 275-286. http://dx.doi.org/10.1111/j.1467-789X.2011.00952.x
[13] Browning, L.M., Hsieh, S.D. and Ashwell, M. (2010) A Systematic Review of Waist-to-Height Ratio as a Screening Tool for the Prediction of Cardiovascular Disease and Diabetes: 0.5 Could Be a Suitable Global Boundary Value. Nutrition Research Reviews, 23, 247-269.
http://dx.doi.org/10.1017/S0954422410000144
[14] Molarius, A. and Seidell, J.C. (1998) Selection of Anthropometric Indicators for Classification of Abdominal Fatness—A Critical Review. International Journal of Obesity, 22, 719-727.
http://dx.doi.org/10.1038/sj.ijo.0800660
[15] Hadaegh, F., Zabetian, A., Harati, H. and Azizi, F. (2006) Waist/Height Ratio as a Better Predictor of Type 2 Diabetes Compared to Body Mass Index in Tehranian Adult Men—A 3.6-Year Prospective Study. Experimental and Clinical Endocrinology & Diabetes, 114, 310-315. http://dx.doi.org/10.1055/s-2006-924123
[16] Esmaillzadeh, A., Mirmiran, P. and Azizi, F. (2004) Waist-to-Hip Ratio Is a Better Screening Measure for Cardiovascular Risk Factors than Other Anthropometric Indicators in Tehranian Adult Men. International Journal of Obesity, 28, 1325-1332. http://dx.doi.org/10.1038/sj.ijo.0802757
[17] Bener, A., Yousafzai, M.T., Darwish, S., Al-Hamaq, A.O., Nasralla, E.A. and Abdul-Ghani, M. (2013) Obesity Index That Better Predict Metabolic Syndrome: Body Mass Index, Waist Circumference, Waist Hip Ratio, or Waist Height Ratio. Journal of Obesity, 2013, Article ID: 269038.
http://dx.doi.org/10.1155/2013/269038
[18] Xu, Z., Qi, X., Dahl, A.K. and Xu, W. (2013) Waist-to-Height Ratio Is the Best Indicator for Undiagnosed Type 2 Diabetes. Diabetic Medicine, 30, e201-e207. http://dx.doi.org/10.1111/dme.12168
[19] Okafor, C.I., Fasanmade, O., Ofoegbu, E. and Ohwovoriole, A.E. (2011) Comparison of the Performance of Two Measures of Central Adiposity among Apparently Healthy Nigerians Using the Receiver Operating Characteristic Analysis. Indian Journal of Endocrinology and Metabolism, 15, 320-326.
http://dx.doi.org/10.4103/2230-8210.85588
[20] World Health Organization (1995) Technical Report Series No. 854. Physical Status: The Use and Interpretation of Anthropometry. WHO, Geneva.
http://www.who.int/childgrowth/publications/physical_status/en/
[21] Chobanian, A.V., Bakris, G.L., Black, H.R., Cushman, W.C., Green, L.A., Izzo Jr., J.L., et al. (2003) The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: The JNC 7 Report. JAMA, 289, 2560-2572.
http://dx.doi.org/10.1001/jama.289.19.2560
[22] Adedoyin, R.A., Mbada, C.E., Balogun, M.O., Adebayo, R.A., Martins, T. and Ismail, S. (2009) Obesity Prevalence in Adult Residents of Ile-Ife, Nigeria. Nigerian Quarterly Journal of Hospital Medicine, 19, 100-105.
[23] Pettersson, J., Johansson, K., Rossner, S. and Neovius, M. (2008) Prevalence of Obesity and Abdominal Obesity in Swedish Primary Care and Occupational Health Clinics. Obesity Facts, 1, 251-257.
http://dx.doi.org/10.1159/000156530
[24] Knopp, R.H., Paramsothy, P., Retzlaff, B.M., Fish, B., Walden, C., Dowdy, A., et al. (2005) Gender Differences in Lipoprotein Metabolism and Dietary Response: Basis in Hormonal Differences and Implications for Cardiovascular Disease. Current Atherosclerosis Reports, 7, 472-479.
http://dx.doi.org/10.1007/s11883-005-0065-6
[25] Liu, A., Abbasi, F. and Reaven, G. (2011) Adiposity Indices in the Prediction of Metabolic Abnormalities Associated with Cardiovascular Disease in Non-Diabetic Adults. Nutrition, Metabolism and Cardiovascular Diseases, 21, 553-560. http://dx.doi.org/10.1016/j.numecd.2009.12.009
[26] Kurpad, S.S., Tandon, H. and Srinivasan, K. (2003) Waist Circumference Correlates Better with Body Mass Index than Waist-to-Hip Ratio in Asian Indians. The National Medical Journal of India, 16, 189-192.
[27] Dalton, M., Cameron, A.J., Zimmet, P.Z., Shaw, J.E., Jolley, D., Dunstan, D.W., et al. (2003) Waist Circumference, Waist-Hip Ratio and Body Mass Index and Their Correlation with Cardiovascular Disease Risk Factors in Australian Adults. Journal of Internal Medicine, 254, 555-563.
http://dx.doi.org/10.1111/j.1365-2796.2003.01229.x
[28] Akpinar, E., Bashan, I., Bozdemir, N. and Saatci, E. (2007) Which Is the Best Anthropometric Technique to Identify Obesity: Body Mass Index, Waist Circumference or Waist-Hip Ratio? Collegium Antropologicum, 31, 387-393.
[29] Schneider, H.J., Friedrich, N., Klotsche, J., Pieper, L., Nauck, M., John, U., et al. (2010) The Predictive Value of Different Measures of Obesity for Incident Cardiovascular Events and Mortality. The Journal of Clinical Endocrinology & Metabolism, 95, 1777-1785. http://dx.doi.org/10.1210/jc.2009-1584
[30] Khader, Y.S., Batieha, A., Jaddou, H., Batieha, Z., El-Khateeb, M. and Ajlouni, K. (2010) Anthropometric Cut-Off Values for Detecting Metabolic Abnormalities in Jordanian Adults. Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy, 3, 395-402. http://dx.doi.org/10.2147/DMSOTT.S15154
[31] Lin, W.Y., Lee, L.T., Chen, C.Y., Lo, H., Hsia, H.H., Liu, I.L., Lin, R.S., Shau, W.Y. and Huang, K.C. (2002) Optimal Cut-Off Values for Obesity: Using Simple Anthropometric Indices to Predict Cardiovascular Risk Factors in Taiwan. International Journal of Obesity, 26, 1232-1238.
http://dx.doi.org/10.1038/sj.ijo.0802040
[32] Song, X., Jousilahti, P., Stehouwer, C.D., S?derberg, S., Onat, A., Laatikainen, T., et al. (2013) Comparison of Various Surrogate Obesity Indicators as Predictors of Cardiovascular Mortality in Four European Populations. European Journal of Clinical Nutrition, 67, 1298-1302.
http://dx.doi.org/10.1038/ejcn.2013.203
[33] Taylor, R.W., Brooking, L., Williams, S.M., Manning, P.J., Sutherland, W.H., Coppell, K.J., Tipene-Leach, D., Dale, K.S., McAuley, K.A. and Mann, J.I. (2010) Body Mass Index and Waist Circumference Cutoffs to Define Obesity in Indigenous New Zealanders. The American Journal of Clinical Nutrition, 92, 390-397. http://dx.doi.org/10.3945/ajcn.2010.29317
[34] Ko, K.P., Oh, D.K., Min, H., Kim, C.S., Park, J.K., Kim, Y. and Kim, S.S. (2012) Prospective Study of Optimal Obesity Index Cutoffs for Predicting Development of Multiple Metabolic Risk Factors: The Korean Genome and Epidemiology Study. Journal of Epidemiology, 22, 433-439.
[35] Ko, G.T., Tang, J., Chan, J.C., Sung, R., Wu, M.M.F., Wai, H.P.S. and Chen, R. (2001) Lower BMI Cut-Off Value to Define Obesity in Hong Kong Chinese: An Analysis Based on Body Fat Assessment by Bioelectrical Impedance. British Journal of Nutrition, 85, 239-242. http://dx.doi.org/10.1079/BJN2000251
[36] Banerji, M.A., Faridi, N., Atluri, R., Chaiken, R.L. and Lebovitz, H.E. (1999) Body Composition, Visceral Fat, Leptin, and Insulin Resistance in Asian Indian Men. The Journal of Clinical Endocrinology & Metabolism, 84, 137-144. http://dx.doi.org/10.1210/jc.84.1.137
[37] Hsu, W.C., Araneta, M.R., Kanaya, A.M., Chiang, J.L. and Fujimoto, W. (2015) BMI Cut Points to Identify At-Risk Asian Americans for Type 2 Diabetes Screening. Diabetes Care, 38, 150-158.
http://dx.doi.org/10.2337/dc14-2391
[38] Lear, S.A., Toma, M., Birmingham, C.L. and Frohlich, J.J. (2003) Modification of the Relationship between Simple Anthropometric Indices and Risk Factors by Ethnic Background. Metabolism—Clinical and Experimental, 52, 1295-1301. http://dx.doi.org/10.1016/S0026-0495(03)00196-3
[39] Wang, Y. and Beydoun, M.A. (2007) The Obesity Epidemic in the United States—Gender, Age, Socioeconomic, Racial/Ethnic, and Geographic Characteristics: A Systematic Review and Meta-Regression Analysis. Epidemiologic Reviews, 29, 6-28. http://dx.doi.org/10.1093/epirev/mxm007

  
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