Estimation of serum creatinine, serum urea, glomerular filtration rate and proteinuria among apparently healthy adults to assess the renal impairment and its association with body mass index: An observational hospital-based study
Abstract
Background: Serum urea, creatinine, and estimated glomerular filtration rate (eGFR) are the most widely accepted parameters for the assessment of renal impairment. Renal dysfunction in Indian obese adults has not been sufficiently investigated.
Aims: To evaluate the renal function by using serum urea, serum creatinine, eGFR, and proteinuria in normal, overweight, and obese adults to identify renal impairment.
Materials and Methods: This observational and cross-sectional study was done on a total of 100 normoglycemic, normotensive healthy adults, and these were divided into three groups as per the criteria of body mass index (BMI) as; normal, overweight and obese groups. Estimation of urea and creatinine was done by fully automated chemistry analyzer methods. eGFR was calculated by Modified Diet Renal Disease (MDRD) formula. The excretion of protein in urine was checked by the urine dipsticks method. p<0.05 was considered as significant level.
Results: The present study was conducted in 100 normal study subjects which included 48 males and 52 females. A maximum number of subjects were found in the obese subgroup (34%). Among subjects low eGFR prevalence was found 3% and prevalence of chronic kidney disease (CKD) was also found 3%. The obese subjects showed higher urea and creatinine levels compared to normal subjects. A significant negative relationship was noted in eGFR (MDRD) and BMI. The prevalence of proteinuria among subjects was 3%.
Conclusions: A total of 3% prevalence of renal dysfunction was noted among adults and out of this 2% was found in obese adults. Therefore, it can be concluded that increasing BMI has a significant contributing factor for renal impairment in obese adults.
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Ranjani H, Anjana RM, Garg R, Anand K. Epidemiology of childhood overweight and obesity in India: A systemic Review. Indian J Med Res. 2016;143(2):160-174. doi: https://doi.org/10.4103/0971-5916.180203.
Obesity and Overweight Fact Sheet 311. WHO. 2015. Available at https://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight.
Karla S, Unikrishnan A. Obesity in India: The weight of the Nation. J Med Nutraceut. 2012;1(1):37-41. doi: https://doi.org/10.4103/2278-019X.94634.
Sam S, Mazzone T. Adipose tissue changes in obesity and the impact on met
abolic function. Trans Res. 2014;164(4):284-292. doi: https://doi.org/10.1016/j.trsl.2014.05.008.
Kiortsis DN, Christou MA. Management of obesity-induced kidney disease: A critical review of the literature. Obes facts. 2012;5(6):821-832. doi: https://doi.org/10.1159/000345919.
Gelber RP, Kurth T, Kausz AT, Manson, JE, Buring JE, Levey AS, et al. Association between body mass index and CKD in apparently healthy men. Am J Kidney Dis. 2005;46(5):871-880. doi: https://doi.org/10.1053/j.ajkd.2005.08.015.
Kramer H, Luke A, Bidani A, Cao G, Cooper R, McGee D. Obesity and prevalent and incident CKD: the Hypertension Detection and Follow-Up Program. Am J Kidney Dis. 2005;46(4):587-594. doi: https://doi.org/10.1053/j.ajkd.2005.06.007.
Levey AS, Coresh J, Greene T, Stevens LA, Zhang YL. Using standardized serum creatinine values in the modification of diet in renal disease study equation for estimating glomerular filtration rate. Ann Intern Med. 2006;145(4):247-254. doi: https://doi.org/10.7326/0003-4819-145-4-200608150-00004.
Levey AS, Stevens LA, Schmid CH, Zhang YL, Castro AF, Feldman HI, et al. A new equation to estimate glomerular filtration rate. Ann Intern Med. 2009;150(9):604-612.
Wickman C, Kramer H. Obesity and kidney disease. Potential mechanisms. Semin Nephrol. 2013;33(1):14-22. doi: https://doi.org/10.1016/j.semnephrol.2012.12.006.
Khashayar P, Aghaei Meybodi H, Rezaei Hemami M, Larijani B. Role of obesity variables in detecting hypertension in an Iranian population. High Blood Press Cardiovasc Prev. 2017;24(3):305-312. doi: https://doi.org/10.1007/s40292-017-0219-y.
Cho YG, Song HJ, Kim JM, Park KH, Paek YJ, Cho JJ, et al. The estimation of cardiovascular risk factors by body mass index and body fat percentage in Korean male adults. Metabol. 2009;58(6):765-771. doi: https://doi.org/10.1016/j.metabol.2009.01.004.
Raatikainen K, Heiskanen N, Heinonen S. Transition from overweight to obesity worsens pregnancy outcome in a BMI-dependent manner. Obesity (Silver Spring). 2006;14(1):165-171. doi: https://doi.org/10.1038/oby.2006.20.
Mishra A, Chowbey P, Makkar BM, Vikram NK, Wasir JS, Chadha D, et al. Consensus statement for diagnosis of obesity, abdominal obesity and the metabolic syndrome for Asian Indians and recommendations for physical activity, medical and surgical management. J Assoc Physicians India. 2009;57:163-170.
Rosenthal, HL. Determination of urea in blood and urine with diacetyl monoxime. Anal. Chem. 1955;27(12):1980-1982. doi: https://doi.org/10.1021/ac60108a039.
Bowers LD, Wong ET. Kinetic serum creatinine assays. II. A critical evaluation and review. Clin Chem. 1980;26(5):555-561.
Agaba EI, Mamven MH, Agaba PA, Tzamaloukas AH. Self-reported screening of nephrologists for chronic kidney disease: a nationwide survey. Int Urol Nephrol. 2009;41(4):973-976. doi: https://doi.org/10.1007/s11255-009-9538-9.
Alebiosu CO, Ayodele OE. The global burden of chronic kidney disease and the way forward. Ethn Dis. 2005;15(3):418-423.
Singh NP, Ingle GK, Saini VK, Jami A, Beniwal P, Lal M, et al. Prevalence of low glomerular filtration rate, proteinuria and associated risk factors in North India using Cockcroft-Gault and Modification of Diet in Renal Disease Equation: an observational, cross-sectional study. BMC Nephrol. 2009;10(4):1-13. doi: https://doi.org/10.1186/1471-2369-10-4.
Agarwal SK, Dash SC, Irshad M, Raju S, Singh R, Pandey RM. Prevalence of chronic renal failure in adults in Delhi, India. Nephrol Dial Transplant. 2005;20(8):1638-1642. doi: https://doi.org/10.1093/ndt/gfh855.
Mani MK. Experience with a program for prevention of chronic renal failure in India. Kidney Int Suppl. 2005;95:S75-S78.
Sabiullah M. Estimation of serum creatinine, blood urea nitrogen and urine analysis in patients with diabetes to assess the renal impairments. Int. J. Adv. Biochem. Res. 2017;3(2):1-4. doi: https://doi.org/10.33545/26174693.2019.v3.i2a.32.
Hall JE, Henegar JR, Dwyer TM, Liu J, Da Silva AA, Kuo JJ, et al. Is obesity a major cause of chronic kidney disease? Adv Ren Replce Ther. 2004;11(1):41-54. doi: https://doi.org/10.1053/j.arrt.2003.10.007.
Mittal A, Sathian B, Kumar A, Chandrashekharan N, Sunka A. Diabetes mellitus as a potential risk factor for renal disease among Nepalese; A hospital based control study. Nepal J Epidemiol. 2010;1(1):22-25. doi: https://doi.org/10.3126/nje.v1i1.4108.
Kapoor S, Cohen D, Townsend R. Effects of Chronic Kidney Disease on Pulse Counter Analysis. Indian J Nephrol. 2007;17(3):91-94.
Dada SA, Raimi TH, Aremu AO. Association between Body Mass Index as a measure of excess weight and glomerular filtration rate among Healthy Nigerian Population. J Nephrol Res. 2018;4(1):153-158. doi: 10.17554/j.issn.2410-0579.2018.04.32.
Hobbs H, Farmer C, Irving J, Klebe B, Stevens P. Is high body mass index independently associated with diminished glomerular filtration rate? An epidemiological study. J Ren Care. 2011;37(3):148-154. doi: https://doi.org/10.1111/j.1755-6686.2011.00231.x.
Fox CS, Larson MG, Leip EP, Gulleton B, Wilson PW, Levy D. Predictors of new-onset kidney disease in a community-based population. JAMA. 2004;291(7):844-850. doi: https://doi.org/10.1001/jama.291.7.844.
Ahmed I, John GT, Kirubakaran MG, Jacob CK, Muliyil J. Prevalence of proteinuria in rural adults population in Tamil Nadu. Indian J Med Res. 2006;124(2):185-188.
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