RENAL DATA FROM ASIA - AFRICA
|Year : 2016 | Volume
| Issue : 6 | Page : 1231-1238
|Chronic kidney disease stages among diabetes patients in the Cape Coast Metropolis
Richard K. D. Ephraim1, Eric Arthur1, W. K. B. A. Owiredu2, Prince Adoba1, Hope Agbodzakey1, Ben A Eghan3
1 Department of Medical Laboratory Technology, University of Cape Coast, Cape Coast, Ghana
2 Department of Molecular Medicine, School of Medical Sciences, College of Health Sciences, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
3 Department of Medicine, School of Medical Sciences, College of Health Sciences, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
Click here for correspondence address and email
|Date of Web Publication||28-Nov-2016|
| Abstract|| |
Diabetes patients worldwide are at a high risk of chronic kidney disease (CKD) which affects their quality of life and increases the risk of early death. This study used the new kidney disease improving global outcomes (KDIGO) guidelines to establish the prevalence and also identify the factors associated with CKD among diabetes patients in the Cape Coast Metropolis. Two hundred (200) diabetes patients were randomly recruited from the diabetic clinic of the Cape Coast Teaching Hospital from January to April 2014. Blood and urine samples were collected for the estimation of serum creatinine and urine protein, respectively. The estimated glomerular filtration rate (eGFR) was calculated using the chronic kidney disease epidemiology collaboration (CKD-EPI) equation; the 2012 KDIGO guidelines was used to assess CKD. Based on these guidelines, 37% of our participants had CKD. Sixteen percent (16%) of the participants had Stage 1 CKD and 17% had an eGFR <60 mL/min/1.73 m 2 . Albuminuria was higher among female diabetic patients compared to males (69.2% vs. 30.8%, P = 0.017). CKD was present in participants on oral hypoglycemic agents (OHAs) alone or both OHA and insulin. Duration of diabetes, systolic blood pressure, older age, and use of OHA were associated with CKD (P <0.05).
|How to cite this article:|
Ephraim RK, Arthur E, Owiredu W, Adoba P, Agbodzakey H, Eghan BA. Chronic kidney disease stages among diabetes patients in the Cape Coast Metropolis. Saudi J Kidney Dis Transpl 2016;27:1231-8
|How to cite this URL:|
Ephraim RK, Arthur E, Owiredu W, Adoba P, Agbodzakey H, Eghan BA. Chronic kidney disease stages among diabetes patients in the Cape Coast Metropolis. Saudi J Kidney Dis Transpl [serial online] 2016 [cited 2020 Aug 9];27:1231-8. Available from: http://www.sjkdt.org/text.asp?2016/27/6/1231/194658
| Introduction|| |
Chronic kidney disease (CKD), a worldwide health problem,  is caused by abnormality in kidney structure or function and is known to have implications for health.  In Sub-Saharan Africa, CKD affects mainly young adults in their productive years and is a major cause of mortality.  This may occur through end-stage renal disease (ESRD), and cardiovascular complications which are found to be higher in those with CKD.  Diabetes mellitus (DM) is one of the leading causes of CKD and is recognized as one of the main causes of ESRD in the USA.  In diabetes, there is excess glucose filtration by the kidney resulting in hyperfunction of the kidney. The filtering units of the kidney are filled with tiny blood vessels which become narrow and get clogged over time due to high sugar levels in the blood. Without enough blood passing through the kidneys gets further damaged, and albumin begins to pass through these filters and ends up in the urine. Progressive damage to the nephrons occurs as a result of the deposition of end products of glucose metabolism on the basement membrane causing CKD which is characterized by rising creatinine and urea levels and decreased estimated GFR. 
Diverse studies have provided varying prevalence rates of CKD among the Ghanaian populace. Bamgboye  reported a CKD prevalence in 1.6% per million people whereas Addo et al,  reported a 4% prevalence among Ghanaian hypertensives. In 2011, Osafo et al recorded a prevalence of 46.9% among hypertensives in Ghana.  All these studies established the prevalence of CKD in patients with conditions other than diabetes.
Across the globe and in Africa, several studies have reported high rates of CKD among diabetic patients. Janmohamed et al  reported the prevalence rate of CKD as 83.7% among diabetics in Tanzania while Sumaili et al  observed 39% prevalence among diabetics in a study conducted among the high-risk population in the Democratic Republic of Congo. Rodriguez-Poncelas et al  and Lou Arnal et al,  reported prevalence rates of 27.9% and 34.6% prevalence, respectively, among type 2 diabetics in Spain. However, there is a paucity of data on the prevalence of CKD among diabetics in Ghana as the few studies conducted have not particularly focused on diabetes as a cause of CKD. Thus, this study used the kidney disease improving global outcomes (KDIGO 2012) guidelines to establish the prevalence and also identify risk factors associated with CKD among diabetes patients in the Cape Coast Metropolis.
| Patients and Methods|| |
Study design/study site
A cross-sectional study was carried out from December 2013 to April 2014 at the Cape Coast Teaching Hospital (CCTH) in the Central Region of Ghana. Cape Coast is the capital town of the Central Region and is located in the Southern part of Ghana along the Gulf of Guinea. The metropolis has a land size of approximately 122 km 2 with a total population of the metropolis was 118,106 in 2000 (Population and Housing Census, 2000). It is principally a fishing community.
Study population/selection of participants
We used simple randomized sampling to recruit 200 diabetes patients aged 18 years and above from the diabetes clinic of the CCTH. Socio-demographic and clinical data of participants were obtained with the aid of a wellstructured pre-tested questionnaire.
The participants included people with confirmed diabetes who are not taking any drug that interferes with normal kidney function. Patients with acute kidney damage, rheumatoid arthritis, inflammatory bowel disease, and CKD patients who were on any form of dialysis were exempted from the study.
The study was approved by the authorities at the CCTH and the Institutional Review Board of the University of Cape Coast. Informed verbal consent was obtained from the participants before collecting their data and samples.
Measurement of blood pressure (using Korotkoff 1 and 5)
After the participants have rested for >5 min, trained personnel used a mercury sphygmomanometer (ACCOSON, England) with a standard or large cuff and a stethoscope to measure the blood pressure. Mean values of duplicate measurements were recorded as the blood pressure. Recommendations of the American Heart Association (2003) on blood pressure measurement were followed. 
Body mass index
Height (nearest centimeter) without shoes and weight (nearest 0.1 kg) in light clothing were measured. Participants were weighed with a weighing balance (Seca, Hamburg, Deutschland) and their height measured with height meter (LINDELS, Klippan, Sweden). Body mass index (BMI) was calculated by dividing weight (kg) by height squared (m 2 ) and categorized into normal weight (BMI 18.5-24.9), underweight (<18.5), overweight (25.0-29.9), and obese (30.0-39.9). 
Blood sample collection and processing
From each participant, we collected 4 mL of venous blood of which 1 and 3 mL were dispensed into fluoride oxalate tubes and serum gel separator tubes, respectively. After centrifugation at 1500 g for 3 min, the plasma and serum were stored in cryovials at −80°C until assay.
Plasma fasting blood sugar and serum creatinine were estimated spectrophotometrically [(Spectronic-20), 820 Linden Avenue, Rochester, NY 14625, USA] using glucose oxidase/peroxidase method  and the Jaffe reaction, respectively. The reagents for these measurements were obtained from Fortress Diagnostics (Fortress diagnostics, Antrim, United Kingdom).
Estimated glomerular filtration rate was calculated using the chronic kidney diseaseepidemiology collaboration equation (CKDEPI):GFR=141×min(Scr/κ,1)α×max(Scr/κ,1) − 1.209×0.993Age,×1.018(if female),×1.159(if black). 
Urine sample collection and processing
Urine protein was quantitatively estimated using the method described by Osafo et al.  Urine creatinine concentration was measured with the ENVOY500/BT 3000 chemistry analyzer. Urine protein-creatinine ratio (uPCR) was calculated from the relation: uPCR (mg/ mmol) = urine protein (mg/dL)/urine creatinine (mmol/dL). The urine protein/creatinine ratio (PCR) was reported in mg/mg.
CKD according to KDIGO is defined as either decreased eGFR (<60 mL/min/1.73 m 2 corresponding to Stage 3-5) or evidence of kidney damage (albuminuria, or overt proteinuria). 
| Statistical Analysis|| |
Data were analyzed using Statistical Package for Social Sciences (SPSS) version 16.0 (SPSS Inc, Chicago, IL, USA) and GraphPad Prism version 5.0 (GraphPad Software, San Deigo California, USA, www.graphpad.com). Unpaired t-test was used to compare means, and Chi-square (χ2 test statistic to compare categorical variables. Results were expressed in means and percentages. P <0.05 was considered statistically significant.
| Results|| |
[Table 1] presents the demographic and clinical characteristics of the study participants. Majority of the participants were females in their fifth and sixth decades of life. The males had a significantly higher fasting blood glucose compared to the females (P = 0.019). The mean systolic blood pressure, diastolic blood pressure, and eGFR were higher in the females compared to the males (P >0.05). However, a significant difference was found between the males and females with respect to BMI (P = 0.037).
Prevalence of albuminuria, eGFR, and stages of CKD stratified by gender is shown in [Table 2]. Of the 52 diabetes patients with albuminuria, 16 (30.8%) were males and 36 (69.2%) were females. Majority (71.0%) of the diabetes patients had eGFR >90 mL/min/1.73 m 2. The prevalence of CKD (stage 1-stage 5) in our participants was 37.0%. Stage 2 CKD was more prevalent in males than in females (P = 0.026).
|Table 2: Prevalence of albuminuria, eGFR, and stages of CKD stratified by gender.|
Click here to view
[Table 3] presents the characteristics of DM participants with CKD. A significant association was found between duration of diabetes mellitus, blood pressure, type of treatment, eGFR, and CKD (P <0.05).
|Table 3: Proportion of DM participants with CKD and their characteristics.|
Click here to view
[Table 4] shows the characteristics of DM patients stratified by CKD stages. Majority of the participants had Stage 1 CKD. SBP and DBP decreased as CKD progressed, but SBP increased in Stages 3b and 4 while DBP increased in Stage 4. CKD was present in participants on either oral hypoglycemic agents (OHA) alone or both OHA and insulin. Stage 1 CKD was highest among type 2 diabetics on OHA (P = 0.000) while majority on both OHA and insulin had Stage 1 and 2 CKD (P = 0.000).
| Discussion|| |
CKD and its complications are more prevalent among African diabetic patients than those in the developed world due to late presentation, limited screening and diagnostic resources, poor glycemic control, and inadequate treatment of complications at an early stage. 
This study used the new KDIGO guidelines (2012) to establish the prevalence and also identified risk factors of CKD among diabetes patients in the Cape Coast Metropolis. The prevalence of CKD in this population was 37% with majority having Stage 1 CKD. Duration of diabetes, systolic blood pressure, older age, and the use of OHAs were all associated with the development of CKD.
The CKD prevalence recorded in this study is similar to the findings of Sumaili et al  and Lou Arnal et al  who reported a 39% and 34.6% prevalence of CKD among diabetics type 1 and 2) and only type 2 diabetics in Kinshasa and Spain, respectively.
Majority of our participants had Stage 1 CKD in consonance with observations made by Janmohamed et al,  who reported predominantly Stage 1 CKD in a cross-sectional study among diabetic outpatients of the Bugando Medical Centre in Tanzania. This observation, however, contradicts the findings of earlier studies which reported Stage 3 as the most prevalent stage among diabetics in Spain and the Netherlands. , The difference could be due to the use of only type 2 diabetics in those studies, the use of the Kidney Disease Outcome Quality Initiative guidelines and differences in geographical locations and the older age of the participants enrolled in those studies.
In agreement with observations made in a study among diabetes patients in Tanzania,  17% of this population had an eGFR <60 mL/min/1.73 m 2 . An eGFR <60 mL/ min/1.73 m 2 represents a loss of half or more of adult kidney function which if undetected could lead to complications such as lactic acidosis from metformin or hypoglycemia from sulfonylureas or insulin.
Albuminuria was higher among female diabetics compared to males contrary to the findings of van der Meer et al  who demonstrated a similar prevalence of albuminuria among men and women in a cross-sectional survey conducted in the Netherlands. This could be attributed to the majority of our participants being females.
In a cross-sectional study carried out among the high-risk population in the Democratic Republic of Congo, Sumaili et al  stated that duration of diabetes influences the occurrence of CKD. Observations made in this study confirm this assertion that type 2 diabetes progresses to microalbuminuria at a fairly predictable rate (about 25% after 10 years of disease) and eventually leads to macroalbuminuria/ overt proteinuria, then finally a decrease in eGFR. 
In consonance with the findings of Sumaili et al  our study also established an association between hypertension and CKD. Similarly, we established through bivariate analysis that participants on OHAs reported an association with CKD confirming the observation of Janmohamed et al  among the diabetic population in Tanzania.
Severe CKD (Stages 3-4) was reported mostly in participants aged 70 years and above in consonance with the findings of Lou Arnal et al  and van der Meer et al  who established an association between decreased eGFR and older age. This could be due to the decline in kidney function as a person ages. 
The fluctuation in blood pressure through the various stages of CKD might be as a result of the use of blood pressure control medications which caused a decline in the SBP and DBP in the early stages. However, the increase in SBP and DBP in the late stages might be due to the loss of blood pressure control in these stages.
Diabetics with CKD have an elevated risk of cardiovascular and renal complications, thus requires improved intervention and control.  Glycemic control should be part of a multifactorial intervention strategy addressing blood pressure control and cardiovascular risk. Furthermore, annual screening for CKD in diabetic patients including the urine-albumin creatinine ratio and eGFR in the management of diabetics is recommended. Early identification of CKD would allow immediate intervention, thus diminishing the progression of renal disease and cardiovascular risk.
This study though having strengths such as the use of the new KDIGO guidelines also has certain limitations. The study is limited by the use of CKD-EPI equation, which is not validated in Ghana for the calculation of eGFR, the smaller sample size used, the use of single serum creatinine estimation, our inability to standardize serum creatinine to isotope mass dilution spectrophotometry (IMDS) and use of urine proteinuria (macroalbumin) instead of quantitative microalbumin estimation.
| Conclusion|| |
CKD was prevalent in 37% of diabetes patients and 17% had eGFR <60 mL/min/1.73 m 2 . Majority of the participants had Stage 1 CKD, and duration of diabetes, systolic blood pressure, older age, and use of OHAs were associated with CKD.
Conflict of interest: None declared.
| References|| |
El Nahas M. The global challenge of chronic kidney disease. Kidney Int 2005;68:2918-29.
KDOQI. NFK, KDOQI clinical practice guidelines and clinical practice recommendations for diabetes and chronic kidney disease. Am J Kidney Dis 2007;49 2 Suppl 2:S12-154.
Arogundade FA, Barsoum RS. CKD prevention in Sub-Saharan Africa: A call for governmental, nongovernmental, and community support. Am J Kidney Dis 2008;51:515-23.
Krzesinski JM, Sumaili KE, Cohen E. How to tackle the avalanche of chronic kidney disease in Sub-Saharan Africa: The situation in the Democratic Republic of Congo as an example. Nephrol Dial Transplant 2007;22:332-5.
Collins AJ, Foley RN, Herzog C, et al. US Renal Data System 2010 Annual Data Report. Am J Kidney Dis 2011;57 1 Suppl 1:A8, e1526.
Bamgboye EL. End-stage renal disease in SubSaharan Africa. Ethn Dis 2006;16 2 Suppl 2:S2-5-9.
Addo J, Smeeth L, Leon DA. Hypertensive target organ damage in Ghanaian civil servants with hypertension. PLoS One 2009;4:e6672.
Osafo C, Mate-Kole M, Affram K, Adu D. Prevalence of chronic kidney disease in hypertensive patients in Ghana. Ren Fail 2011;33: 388-92.
Janmohamed MN, Kalluvya SE, Mueller A, et al. Prevalence of chronic kidney disease in diabetic adult out-patients in Tanzania. BMC Nephrol 2013;14:183.
Sumaili EK, Cohen EP, Zinga CV, Krzesinski JM, Pakasa NM, Nseka NM. High prevalence of undiagnosed chronic kidney disease among at-risk population in Kinshasa, the Democratic Republic of Congo. BMC Nephrol 2009;10:18.
Rodriguez-Poncelas A, Garre-Olmo J, FranchNadal J, et al. Prevalence of chronic kidney disease in patients with type 2 diabetes in Spain: PERCEDIME2 study. BMC Nephrol 2013;14:46.
Lou Arnal LM, Campos Gutiérrez B, Cuberes Izquierdo M, et al. Prevalence of chronic kidney disease in patients with type 2 diabetes mellitus treated in primary care. Nefrologia 2010;30:552-6.
Kirkendall WM, Burton AC, Epstein FH, Freis ED. Recommendations for human blood pressure determination by sphygmomanometers. Circulation 1967;36:980-8.
WHO, editor. Physical status: The use and interpretation of anthropometry. Report of a WHO Expert Committee. Technical Report Series. Geneva: WHO; 1995.
Trinder P. Determination of blood glucose using an oxidase-peroxidase system with a non-carcinogenic chromogen. J Clin Pathol 1969;22:158-61.
Kidney Disease: Improving Global Outcomes (KDIGO) CKD Work Group. KDIGO 2012 Clinical Practice Guideline for the Evaluation and Management of Chronic Kidney Disease. Kidney interSuppl. 2013;3(1):1-150.
Stevens PE, Levin A; Kidney Disease: Improving Global Outcomes Chronic Kidney Disease Guideline Development Work Group Members. Evaluation and management of chronic kidney disease: Synopsis of the kidney disease: Improving global outcomes 2012 clinical practice guideline. Ann Intern Med 2013;158:825-30.
Gill GV, Mbanya JC, Ramaiya KL, Tesfaye S. A Sub-Saharan African perspective of diabetes. Diabetologia 2009;52:8-16.
van der Meer V, Wielders HP, Grootendorst DC, et al. Chronic kidney disease in patients with diabetes mellitus type 2 or hypertension in general practice. Br J Gen Pract 2010;60: 884-90.
Adler AI, Stevens RJ, Manley SE, Bilous RW, Cull CA, Holman RR; UKPDS Group. Development and progression of nephropathy in type 2 diabetes: The United Kingdom prospective diabetes study (UKPDS 64). Kidney Int 2003;63:225-32.
Action to Control Cardiovascular Risk in Diabetes Study Group, Gerstein HC, Miller ME, et al. Effects of intensive glucose lowering in type 2 diabetes. N Engl J Med 2008; 358:2545-59.
Richard K. D. Ephraim
Department of Medical Laboratory Technology, University of Cape Coast, Cape Coast
[Table 1], [Table 2], [Table 3], [Table 4]
| Article Access Statistics|
| Viewed||1636 |
| Printed||12 |
| Emailed||0 |
| PDF Downloaded||292 |
| Comments ||[Add] |