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Research Article Open access CC BY 4.0

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

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

Journal of Complementary and Alternative Medical Research · pp. 21–29 · Published 26 Dec 2020

10.9734/jocamr/2020/v12i230204

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.

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

References (17)

  1. 1 A New Equation to Estimate Glomerular Filtration Rate [DOI]
  2. 2 The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure The JNC 7 Report [DOI]
  3. 3 US Renal Data System 2016 Annual Data Report: Epidemiology of Kidney Disease in the United States [DOI]
  4. 4 A systematic analysis of worldwide population-based data on the global burden of chronic kidney disease in 2010 [DOI]
  5. 5 Maintenance Dialysis Population Dynamics [DOI]
  6. 6 A Nutrition Paradox — Underweight and Obesity in Developing Countries [DOI]
  7. 7 Efficient classification of chronic kidney disease by using multi‐kernel support vector machine and fruit fly optimization algorithm [DOI]
  8. 8 Prevalence of chronic kidney disease in Bangladesh: a systematic review and meta-analysis [DOI]
  9. 9 High prevalence of chronic kidney disease in a community survey of urban Bangladeshis: a cross-sectional study [DOI]
  10. 10 Prevalence of Chronic Kidney Disease and Its Association with Risk Factors in Disadvantageous Population [DOI]
  11. 11 Relationships of dietary patterns with body composition in older adults differ by gender and PPAR-γ Pro12Ala genotype [DOI]
  12. 12 Management of End Stage Renal Disease-Bangladesh Perspective [DOI]
  13. 13 Prevalence of Chronic Kidney Disease (CKD) and Identification of Associated Risk Factors among Rural Population by Mass Screening [DOI]
  14. 14 Renal insufficiency among urban populations in Bangladesh: A decade of laboratory-based observations [DOI]
  15. 15 Hybrid Kernel Support Vector Machine Classifier and Grey Wolf Optimization Algorithm Based Intelligent Classification Algorithm for Chronic Kidney Disease [DOI]
  16. 16 Prevalence of primary renal diseases among patients on maintenance haemodialysis: a hospital based study [DOI]
  17. 17 K/DOQI clinical practice guidelines for chronic kidney disease: Evaluation, classification, and stratification

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