Central Obesity and Comorbidity Risk in Hemodialysis Patients: A Cross Sectional Study in Lebanon

Abstract

Introduction: Abdominal deposition of fat has been described as the type of obesity that offers the greatest risk for the health of individuals, and is associated with increased mortality, and morbidity. Conicity index (Ci), Body mass index (BMI), and waist hip ratio (WHR) are used to predict the risk of obesity related diseases. However, it has not been ex amined whether these indicators can predict the comorbidities in hemodialysis subjects in Lebanon. Objective: to determine the effect of central obesity on comorbidities in hemodialysis patients in Lebanon. Material and Method: This is a cross-sectional study of obesity in 60 hemodialysis subjects in Lebanon. A linear regression analysis was used to determine the relationship between BMI, Ci, WHR, and comorbidities measured by Charlson (CCI) and Davies comorbidities indexes. Results: Ci values were significantly associated with age, and CCI; the abdominal fat deposition evaluated by the conicity index and WHR were a predictor of the comorbidities according to CCI (= 2.96; p = 0.01), and Davies comorbidity index (= 1.19; p = 0.05) scores. BMI was a weak predictor of comorbidity. Conclusion: Abdominal obesity by using simple anthropometric measurements e.g. Ci, and WHR values can similarly predict the presence of comorbidities in hemodialysis patients. Maintaining appropriate Ci and WHR values might be important to improve outcome in hemodialysis patients.

Share and Cite:

I. Sabbah, H. Sabbah, S. Sabbah, H. Akoum and N. Droubi, "Central Obesity and Comorbidity Risk in Hemodialysis Patients: A Cross Sectional Study in Lebanon," Open Journal of Nephrology, Vol. 2 No. 4, 2012, pp. 109-115. doi: 10.4236/ojneph.2012.24018.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] F. J. G. Pitanga and I. Lessa, “Anthropometric Indexes of Obesity as an Instrument of Screening for High Coronary Risk in Adults in the City of Salvador—Bahia,” Arquivos Brasileiros de Cardiologia, Vol. 85, No. 1, 2005, pp. 26-31. http://www.scielo.br/pdf/abc/v85n1/en_a06v85n1.pdf
[2] D. A. Webb, J. M. Robbins, J. R. Bloch and J. F. Culhane, “Estimating Prevalence of Overweight and Obesity at the Neighborhood Level: The Value of Maternal Height and Weight Data Available on Birth Certificate Records,” Population Health Metrics, Vol. 8, No. 1, 2010, p. 16. http://www.pophealthmetrics.com/content/8/1/16.
[3] E. Mannucci, M. L. Petroni, N. Villanova, et al., “Clinical and Psychological Correlates of Health-Related Quality of Life in Obese Patients,” Health and Quality of Life Outcomes, Vol. 8, 2010, p. 90 http://www.hqlo.com/content/8/1/90.
[4] S. Hermann, S. Rohrmann, J. Linseisen, et al., “The Association of Education with Body Mass Index and Waist Circumference in the EPIC-PANACEA Study,” BMC Public Health, Vol. 11, No. 1, 2011, pp. 1-12 http://www.biomedcentral.com/1471-2458/11/169.
[5] R. Cherqaoui, T. A. Kassim, J. Kwagyan, C. Freeman, G. Nunlee-Bland, M. Ketete, S. Xu and O. S. Randall, “The Metabolically Healthy But Obese Phenotype in African Americans”, The Journal of Clinical Hypertension, Vol. 14, No. 2, 2012, pp. 92-96. doi:10.1111/j.1751-7176.2011.00565.x
[6] K. Kaur and R. Mogra, “Association of Body Mass Index, Body Fat and Hypertension among Postmenopausal Women,” Journal of Human Ecology, Vol. 20, No. 3, 2006, pp. 171-175. http://www.krepublishers.com/02-Journals/JHE/JHE-20-0-000-000-2006-Web/JHE-20-3-000-000-2006-Abstract-PDF/JHE-20-3-171-175-2006-1442-Kaur-K/JHE-20-3-171-175-2006-1442-Kaur-K-Text.pdf.
[7] A. C. Cordeiro, A. R. Qureshi, P. Stenvinkel, et al., “Abdominal Fat Deposition Is Associated with Increased Inflammation, Protein-Energy Wasting and Worse Outcome in Patients Undergoing Haemodialysis,” Nephrology Dialysis Transplantation, Vol. 25, No. 2, 2010, pp. 562-568. doi:10.1093/ndt/gfp492
[8] M. S. Flora, C. G. N. Mascie-Taylor and M. Rahman, “Conicity Index of Adult Bangladeshi Population and Their Socio-Demographic Characteristics,” Ibrahim Medical College Journal, Vol. 3, No. 1, 2009, pp. 1-8. http://www.banglajol.info/index.php/IMCJ/article/viewArticle/2910
[9] A. M. Hodge, L. Maple-Brown, J. Cunningham, J. Boyle, T. Dunbar, T. Weeramanthri, J. Shaw and K. O’Dea, “Abdominal Obesity and Other Risk Factors Largely Explain the High CRP in Indigenous Australians Relative to the General Population, But Not Gender Differences: A cross-Sectional Study,” BMC Public Health, Vol. 10, No. 1, 2010, p. 700. http://www.biomedcentral.com/1471-2458/10/700.
[10] Y. Liu, G. Tong, W. Tong, L. Lu and X. Qin, “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, Vol. 11, No. 35, 2011, pp. 1-10. http://www.biomedcentral.com/1471-2458/11/35.
[11] C. Zoccali, S. M. Seck and F. Mallamaci, “Obesity and the Epidemiology and Prevention of Kidney Disease: Waist Circumference versus Body Mass Index,” American Journal of Kidney Diseases, Vol. 58, No. 2, 2011, pp. 177-185. doi:10.1053/j.ajkd.2011.05.009 http://download.journals.elsevierhealth.com/pdfs/journals/0272-6386/PIIS0272638611006998.pdf.
[12] R. de Moutsert, D. C. Grootendorst, J. Axelsson, E. W. Boeschoten, R. T. Krediet, F. W. Dekker and NECOSAD Study Group, “Excess Mortality Due to Interaction between Protein Energy Wasting, Inflammation and Cardiovascular Disease in Chronic Dialysis Patients,” Nephrology Dialysis Transplantation, Vol. 23, No. 9, 2008, pp. 2957-2964. doi:10.1093/ndt/gfn167
[13] R. Pellicano, B. J. Strauss, K. R. Polkinghorne and P. G. Kerr, “Body Composition in Home Haemodialysis versus Conventional Haemodialysis: A cross-Sectional, Matched, Comparative Study,” Nephrology Dialysis Transplantation, Vol. 25, No. 2, 2010, pp. 568-573. doi:10.1093/ndt/gfp490
[14] S. Yusuf, S. Reddy, S. Ounupuu and S. Anand, “Global Burden of Cardiovascular Diseases. Part I: General Considerations, the Epidemiologic Transition, Risk Factors and Impact of Urbanization,” Circulation, Vol. 104, No. 22, 2001, pp. 2746-2753. doi:10.1161/hc4601.099487
[15] C. Arambepola1, S. Allender, R. Ekanayake and D. Fernando, “Urban Living and Obesity: Is It Independent of Its Population and Lifestyle Characteristics?” Tropical Medicine and International Health, Vol. 13, No. 4, 2008, pp. 448-457. doi:10.1111/j.1365-3156.2008.02021.x
[16] I. Sabbah, N. Drouby, S. Sabbah, N. Retel-Rude and M. Mercier, “Quality of Life in rural and urban populations in Lebanon using SF-36 Health Survey,” Health and Quality of Life Outcomes, Vol. 1, 2003, p. 30. http://www.hqlo.com/content/1/1/30.
[17] R. A. Sherman and R. Hootkins, “Simplified Formula and normograms for monitoring hemodialysis Adequacy,” In: A. R. Nissensson and R. N. Fine, Eds., Handbook of Dialysis Therapy, 4th Edition, Saunders Elsevier, Philadel- phia, 2008, pp. 310-318. doi:10.1016/B978-1-4160-4197-9.50024-7
[18] B. T. Bikbov and N. A. Tomilina, “Letters and Replies: Some Notes about the Usage of the Charlson Comorbidity Index,” Nephrology Dialysis Transplantation, Vol. 19, No. 11, 2004, pp. 2926-2927. doi:10.1093/ndt/gfh463
[19] L. Fried, J. Bernardini and B. Piraino, “Comparison of the Charlson Comorbidity Index and the Davies Score as a Predictor of Outcomes in PD Patients,” Peritoneal Dialysis International, Vol. 23, No. 6, 2003, pp. 568-573. www.pdiconnect.com
[20] J. C. McGregor, P. W. Kim, E. N. Perencevich, D. D. Bradham, J. P. Furuno, K. S. Kaye, J. C. Fink, P. Langenberg, M.-C. Roghmann and A. D. Harris, “Utility of the Chronic Disease Score and Charlson Comorbidity Index as Comorbidity Measures for Use in Epidemiologic Studies of Antibiotic-resistant Organisms,” American Journal of Epidemiology, Vol. 161, No. 5, 2005, pp. 483-493. doi:10.1093/aje/kwi068 http://aje.oxfordjournals.org/content/161/5/483.full.pdf+html?sid=4b1ea8f0-b988-4c57-974a-75de648c5424
[21] L. F. Morrone, S. Mazzaferro, D. Russo, F. Aucella, M. Cozzolino, M. G. Facchini, A. Galfre, F. Malberti, M. C. Mareu, M. Nordio, G. Pertosa, D. Santoro and CPCP Study Investigators, “Interaction between Parathyroid Hormone and the Charlson Comorbidity Index on Survival of Inci- dent Haemodialysis Patients,” Nephrology Dialysis Transplantation, Vol. 24, No. 9, 2009, pp. 2859-2865. doi:10.1093/ndt/gfp170
[22] T. Ancelle, “Statistique Epidemiologie,” 2nd Edition, Maloine, Paris, 2008.
[23] P. Czenrnichow, J. Chaperon and X. Le Coutour, “Epidemiologie Abreges Connaissances et Pratique,” Masson, Paris, 2001.
[24] A. Zadeh-Vakili, F. R. Tehrani and F. Hosseinpanah, “Waist circumference and Insulin Resistance: A Community Based cross Sectional Study on Reproductive Aged Iranian Women,” Diabetology & Metabolic Syndrome, Vol. 3, No. 18, 2011, p. 6. http://www.dmsjournal.com/content/3/1/18.
[25] I. Sabbah, D.-A. Vuitton, N. Droubi, S. Sabbah and M. Mercier, “Morbidity and Associated Factors in Rural and Urban Populations of South Lebanon: A cross-Sectional Community-Based Study of Self-Reported Health in 2000,” Tropical Medicine and International Health, Vol. 12, No. 8, 2007, pp. 907-919. doi:10.1111/j.1365-3156.2007.01886.x
[26] K/DOQITM, “Nutrition Work Group Membership,” American Journal of Kidney Diseases, Vol. 35, Suppl. 2, 2000, pp. S1-S3.

Copyright © 2024 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.