Identification of People at Risk of Developing Chronic Kidney Disease among Rural Disadvantageous Population in Bangladesh

Main Article Content

Tanjina Rahman
Akibul Islam Chowdhury
Mohammad Asadul Habib
Harun Ur- Rashid
Shakib Arefin
Zannatul Ferdous Shashi
Aidah Tasnim

Abstract

Background: Chronic kidney disease (CKD) is a global disease and the prevalence of CKD is increasing in both developed and developing countries. The current study aimed to assess subjects in the rural areas of Sylhet district in Bangladesh to identify individuals who may be predisposed to at risk for developing CKD.

Methods: A cross-sectional study was carried out among 996 subjects from Sylhet district of Bangladesh. Data were collected by using a standard questionnaire from 82 villages. Data about socio-demographic, medical history and anthropometric and biochemical parameters were collected. Urine dipstick test was done for both albumin and glucose. Descriptive statistics and ANOVA-test were performed for statistical analysis.

Results: The study revealed that people living in rural areas of Sylhet in Bangladesh are at risk of developing CKD and the hidden cause behind it includes not only diabetes and hypertension, but also other lifestyle related factors. Younger participants were found to be at less risk compared to older participants for developing CKD. From urinary dipstick test, 2% and 3.3% subjects had severe traces of albumin and glucose in their urine. Approximately 16% of subjects had hypertension. From the data of 99 out of 996 subjects for urine albumin dipstick test, 98 respondents were identified as stage I CKD patients and only one was identified as stage II CKD patients.

Conclusion: As dialysis and transplants are unsustainable in the long term, it is important to seek preventive strategies when patients are in pre-dialysis state and identify and manage those at high risk. Nutrition and life-style choices can play key roles to achieve this. So, urgent low-cost programs are needed to identify people who are at risk of CKD as well as address their current medical condition to initiate early management of CKD patients.

Keywords:
Chronic kidney disease (CKD), BMI, BP (systolic and diastolic), serum creatinine, Bangladesh.

Article Details

How to Cite
Rahman, T., Chowdhury, A. I., Habib, M. A., Rashid, H. U.-, Arefin, S., Shashi, Z. F., & Tasnim, A. (2020). Identification of People at Risk of Developing Chronic Kidney Disease among Rural Disadvantageous Population in Bangladesh. Journal of Complementary and Alternative Medical Research, 12(2), 21-29. https://doi.org/10.9734/jocamr/2020/v12i230204
Section
Original Research Article

References

Health NIo: US Renal Data System, USRDS 1998 Annual Data Report; 1998. Available:http://www.usrds.org/adr_1998. htm

Levey AS, De Jong PE, Coresh J, Nahas ME, Astor BC, Matsushita K et al. The definition, classification, and prognosis of chronic kidney disease: A KDIGO controversies conference report. Kidney international. 2011;80:17-28.

Levey AS, Coresh J, Bolton K, Culleton B, Harvey KS, Ikizler TA et al. K/DOQI clinical practice guidelines for chronic kidney disease: Evaluation, classification, and stratification. American Journal of Kidney Diseases. 2002;39:137-149.

Levey AS, Stevens LA, Schmid CH, Zhang YL, Castro AF, Feldman HI et al. A new equation to estimate glomerular filtration rate. Annals of Internal Medicine. 2009; 150:604-612.

NIoH No D. USRDS annual data report: Epidemiology of kidney disease in the United States; 2018.

Anand S, Khanam MA, Saquib J, Saquib N, Ahmed T, Alam DS et al. High prevalence of chronic kidney disease in a community survey of urban Bangladeshis: A cross-sectional study. Global Health 2014:10:9.

Das SK, Afsana SM, Elahi SB, Chisti MJ, Das J, Al Mamun A, et al. Renal insufficiency among urban populations in Bangladesh: A decade of laboratory-based observations. PloS one 2019; 14:e0214568.

Mills KT, Xu Y, Zhang W, Bundy JD, Chen C-S, Kelly TN et al. A systematic analysis of worldwide population-based data on the global burden of chronic kidney disease in 2010. Kidney international. 2015;88:950-957.

Lysaght MJ. Maintenance dialysis population dynamics: Current trends and long-term implications. Journal of the American Society of Nephrology. 2002; 13:S37-S40.

Levey AS, Coresh J, Bolton K, Culleton B, Harvey KS, Ikizler TA et al. K/DOQI clinical practice guidelines for chronic kidney disease: evaluation, classification, and stratification. American Journal of Kidney Diseases. 2002;39.

Rashid HU. Management of end stage renal disease-Bangladesh perspective. The Open Urology & Nephrology Journal. 2014;7.

Saran R, Robinson B, Abbott KC, Agodoa LY, Bragg-Gresham J, Balkrishnan R et al. US Renal Data System 2017 Annual Data Report: epidemiology of kidney disease in the United States. Elsevier; 2018.

Ahmed S, Rahim M, Ali Z, Iqbal M. Prevalence of primary renal diseases among patients on maintenance haemodialysis: A hospital based study. KYAMC Journal. 2012;2:182-186.

Rashid H. Bangladesh renal registry report 1986–1996. Bang Renal J. 2002;21:25-28.

Hasan MJ, Muqueet A, Sharmeen A, Rahman M, Ahmed TU, Haque A et al. Prevalence of diabetes mellitus, hypertension and proteinuria in a rural area of bangladesh. Community Based Medical Journal. 2012;1:8-13.

Caballero B: A nutrition paradox—under weight and obesity in developing countries. N Engl J Med. 2005;352:1514-1516.

Banik S, Ghosh A: Prevalence of chronic kidney disease in Bangladesh: A systematic review and meta-analysis. International Urology and Nephrology. 2020:1-6.

Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo Jr JL, et al. The seventh report of the joint national committee on prevention, detection, evaluation, and treatment of high blood pressure: the JNC 7 report. Jama. 2003; 289:2560-2571.

Anderson AL, Harris TB, Houston DK, Tylavsky FA, Lee JS, Sellmeyer DE et al. Relationships of dietary patterns with body composition in older adults differ by gender and PPAR-γ Pro12Ala genotype. European Journal of Nutrition. 2010; 49:385-394.

Primack BA, Kim KH, Shensa A, Sidani JE, Barnett TE, Switzer GE. Tobacco, marijuana and alcohol use in university students: a cluster analysis. Journal of American College Health. 2012;60:374-386.

Huda MN, Alam KS. Prevalence of chronic kidney disease and its association with risk factors in disadvantageous population. International Journal of Nephrology; 2012.

Hasan MJ, Kashem MA, Rahman MH, Qudduhush R, Rahman M, Sharmeen A, et al. Prevalence of chronic kidney disease (CKD) and identification of associated risk factors among rural population by mass screening. Community Based Medical Journal. 2012;1:20-26.

Hasan MJ, Muqueet MA: Prevalence of Diabetes mellitus, hypertension and proteinuria in a rural area of Bangladesh. Nephrology Dialysis Transplantation. 2013; 28:404-405.

Anand S, Khanam MA, Saquib J, Saquib N, Ahmed T, Alam DS et al. High prevalence of chronic kidney disease in a community survey of urban Bangladeshis: A cross-sectional study. Globalization and Health. 2014;10:9.

Saha M, Faroque M, Alam K, Alam M, Ahmed S. Chronic kidney disease specific cardiovascular risk factors among non dialytic patients with chronic kidney disease stage-v an experience of a specialized hospital. Bangladesh Medical Research Council Bulletin. 2012;38:18-22.

Jerlin Rubini L, Perumal E. Efficient classification of chronic kidney disease by using multi‐kernel support vector machine and fruit fly optimization algorithm. International Journal of Imaging Systems and Technology. 2020;30:660-673.

Rubini LJ, Perumal E. Hybrid kernel support vector machine classifier and grey wolf optimization algorithm based intelligent classification algorithm for chronic kidney disease. Journal of Medical Imaging and Health Informatics. 2020; 10:2297-2307.

Rubini LJ, Eswaran P: Optimal fuzzy min-max neural network for medical data classification using group search optimiser algorithm. International Journal of Mobile Network Design and Innovation. 2017; 7:140-149.