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 Table of Contents  
Year : 2021  |  Volume : 21  |  Issue : 4  |  Page : 194-202

The burden of diabetic kidney disease in Nigeria − systematic review and meta-analysis

1 Endocrinology Unit, Department of Medicine, University College Hospital, Ibadan; Oluwafemi EFUNTOYE (MBBS, FWACP), Alliance Hospital, Abuja, Nigeria
2 Oluwafemi EFUNTOYE (MBBS, FWACP), Alliance Hospital, Abuja, Nigeria
3 Zenith Medical and Kidney Centre, Alliance Hospital, Abuja, Nigeria
4 Department of Medicine, University College Hospital, Ibadan, Nigeria
5 College of Medicine, University of Ibadan, Ibadan, Nigeria

Date of Submission25-Jun-2021
Date of Acceptance25-Jul-2021
Date of Web Publication27-Oct-2021

Correspondence Address:
Dr. Taoreed A Azeez
Endocrinology Unit, Department of Medicine, University College Hospital, Ibadan, Postal/Zip Code: 23402
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/jesnt.jesnt_16_21

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Background Diabetic kidney disease (DKD) is a microvascular complication of diabetes mellitus. Considering that the burden of diabetes mellitus is rising in Nigeria, there is a need to ascertain the burden of one of its most common complications. The objective of the meta-analysis was to determine the pooled prevalence of DKD in Nigeria and identify its risk factors.
Patients and methods The study is a meta-analysis and it followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Google scholar, PubMed, AJOL, SCOPUS, medRxiv, and the gray literature were systematically searched using appropriate key terms. Statistical analysis was done with MetaXL. The inverse-variance heterogeneity model was used for the meta-analysis and heterogeneity was determined using the I2 statistic and the Cochran’s Q test. Publication bias was checked with the Doi plot and LFK index.
Results Nineteen studies met the eligibility criteria. The total sample size was 56 571. The pooled prevalence of DKD in Nigeria was 28% (95% confidence interval 3–58). The Cochran’s Q was 747 (P<0.001), while the I2 statistic was 97.6%. The Doi plot was drawn and the LFK index was 6.22. The most common risk factors for DKD were suboptimal glycemic control, hypertension, obesity, duration of diabetes, male sex, and advancing age.
Conclusion The prevalence of DKD in Nigeria is high and greater attention should be focused on managing the risk factors so as to alleviate the burden of the disease.

Keywords: diabetic kidney disease, diabetic nephropathy, meta-analysis, Nigeria, prevalence, risk factors

How to cite this article:
Azeez TA, Efuntoye O, Abiola BI, Adeyemo SP, Adewale BA. The burden of diabetic kidney disease in Nigeria − systematic review and meta-analysis. J Egypt Soc Nephrol Transplant 2021;21:194-202

How to cite this URL:
Azeez TA, Efuntoye O, Abiola BI, Adeyemo SP, Adewale BA. The burden of diabetic kidney disease in Nigeria − systematic review and meta-analysis. J Egypt Soc Nephrol Transplant [serial online] 2021 [cited 2022 Aug 16];21:194-202. Available from: http://www.jesnt.eg.net/text.asp?2021/21/4/194/329320

  Introduction Top

Diabetes mellitus is a chronic metabolic disorder where reduced insulin secretion or action leads to persistent hyperglycemia with attendant deleterious effects. It is the most common disease encountered in endocrinology practice in Nigeria [1],[2]. In sub-Saharan Africa, Nigeria has the highest number of individuals living with diabetes mellitus [3]. In a meta-analysis, the pooled prevalence of diabetes mellitus among adults in Nigeria was 5.77% [4]. According to the International Diabetes Federation (IDF), the prevalence of diabetes mellitus in Nigeria, as at 2020, was 3% although studies have suggested that the burden of the disease in Nigeria was underestimated by IDF because IDF worked with extrapolated data [4],[5]. In terms of hospitalization, about 223 individuals per 100 000 general population get admitted for diabetes and/or its complications yearly in Nigeria, out of which about 22% die [6].

Poorly treated diabetes mellitus is associated with a myriad of microvascular and macrovascular complications. The most commonly documented microvascular complications of diabetes mellitus are neuropathy, nephropathy, and retinopathy [7]. The rising prevalence of diabetes mellitus, especially type 2, in Nigeria, would translate to increasing burden of microvascular complications and this is quite worrisome as Nigeria is a low-resource setting where most patients pay out of pocket [8]. Interestingly, the presence of microvascular complications independently increases the risk of cardiovascular death in people living with diabetes [9]. This further emphasizes the importance of addressing the microvascular complications of diabetes mellitus.

In Nigeria, the third most common cause of chronic kidney disease is diabetes mellitus, after hypertension and chronic glomerulonephritis, although diabetes remains the most common cause of end-stage renal disease globally [10],[11]. Diabetic kidney disease (DKD), formerly called diabetic nephropathy, is a complication of diabetes mellitus characterized by persistent albuminuria, confirmed on a second occasion at least 3 months apart and/or progressive deterioration of the estimated glomerular-filtration rate (eGFR) [12]. It is of remarkable importance to note that individuals diagnosed with DKD tend to die from cardiovascular diseases and infections even before renal replacement therapy is instituted [12]. The natural history of DKD is shown in [Figure 1] [13].
Figure 1 Natural stages of diabetic kidney disease.

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The risk factors for the development of DKD, in addition to suboptimal glycemic control, include hypertension, obesity, increasing age, male sex, duration of diabetes, ethnicity, and family history [14]. The earliest structural change in DKD on light microscopy is increased mesangial deposition and cellularity, summarily termed as mesangial expansion [15]. Other morphological changes are glomerular basement membrane thickening, microaneurysms, development of the Kimmelstiel–Wilson nodules, and hyaline arteriolosclerosis of the afferent and efferent arterioles [12]. However, recent studies have shown that the progression of DKD may not follow any specific pattern, suggesting that DKD is a heterogeneous group of disorders rather than a single entity [16]. A study documented that despite declining eGFR, about 40% of the patients never developed albuminuria [12]. The study concluded that albuminuria is a dynamic and fluctuating phenomenon that does not necessarily follow a clearly defined progressive pattern.

The pathophysiology of DKD involves four pathways: metabolic, hemodynamic, inflammatory, and fibrotic pathways [12]. The metabolic pathway is mediated by increased oxidative stress, formation of advanced glycation end products, and increased flux of glucose through the hexosamine pathway generating a higher level of transforming growth factor-β [15]. The hemodynamic pathway is mediated by the activation of the renin–angiotensin–aldosterone system, elaboration of nitric oxide, and the secretion and activation of endothelins. The inflammatory pathway is due to the increased production of transforming growth factor-α and enhanced synthesis of serum amyloid A. The fibrotic pathway is facilitated by transforming growth factor-β, vascular endothelial growth factor, and connective tissue growth factor. The various pathways converge and lead to the various functional, biochemical, and structural changes seen in DKD.

Microalbuminuria is defined using 24-h urinary protein of 30–300 mg or albumin–creatinine ratio of 30–300 mg/g in at least two out of three samples taken over 3–6 months [17]. Values above these ranges are termed ‘macroalbuminuria.’ Screening for microalbuminuria is commenced after the diagnosis of type 2 diabetes mellitus or 5–10 years postdiagnosis of type 1 diabetes mellitus and annually thereafter [18]. Diagnosis of DKD is made in the presence of persistent albuminuria (micro or macro), presence of diabetic retinopathy, and the absence of signs of other forms of renal disease [19]. So, DKD is a diagnosis of exclusion. Management of DKD involves intensive glycemic control, intensive blood-pressure control, renin–angiotensin–aldosterone-system blockade, dietary modification, treatment of dyslipidemia, and treatment of anemia. Recently, the use of sodium–glucose transporter 2 inhibitors and glucagon-like peptide 1 agonists has been reported to be beneficial in the management of DKD [20].

  Objective Top

The objective of the systematic review and meta-analysis was to estimate the pooled prevalence of DKD in Nigeria and identify the risk factors so as to intensify the efforts at preventing and managing the disease.

  Patients and methods Top

Relevant articles and papers were searched on the common medical databases. These databases included Google Scholar, PubMed, African journal online (AJOL), and SCOPUS. The preprint database, medRxiv, was also searched. The gray literature was also searched through the help of the librarian of a university and experts in the relevant fields in Nigeria. This was done to increase the depth of the retrieved articles and minimize publication bias. The search terms were ‘diabetes mellitus,’ ‘type 2 diabetes,’ ‘type 1 diabetes,’ ‘complications of diabetes,’ and ‘microvascular complications.’ Other terms used in the search process were ‘diabetic kidney disease,’ ‘diabetic nephropathy,’ ‘renal failure,’ ‘chronic kidney disease,’ ‘end-stage renal disease,’ ‘microalbuminuria,’ ‘macroalbuminuria,’ and ‘Nigeria.’ The Boolean operators ‘AND,’ ‘OR,’ as well as ‘NOT’ were used as deemed appropriate to enrich the specificity of the search results.

Abstracts and texts were critically examined by the authors independently. At least three authors agreed on each article that was selected. This was done to minimize the study-selection bias. Studies done from 2000 to 2021 were selected. The outcome variables of interest were the prevalence and risk factors for DKD in Nigeria. The data were initially collected on a spreadsheet before it was transferred to the meta-analysis software. Meta XL version 5.3 (EpiGear International Ltd, Sunrise Beach, Queensland, Australia), a meta-analysis add-in software for Microsoft Excel, was used for the meta-analysis. The inverse-variance heterogeneity model was used for the meta-analysis. Heterogeneity was determined using the I2 statistic and the Cochran’s Q test.

The literature-search process and study-selection algorithm were done according to the recommended Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses flow diagram is shown in [Figure 2].
Figure 2 The PRISMA flow diagram of the meta-analysis. PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses.

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  Results Top

A total of 19 studies met the eligibility criteria and were selected for the meta-analysis. [Table 1] shows the selected studies and the prevalence in each study. The total sample size in this meta-analysis was 56 571 individuals with diabetes mellitus. The prevalence of DKD ranges from 3.2 to 72.6% in the selected studies. [Figure 3] shows the regional distribution of the studies on the basis of the six geopolitical zones of Nigeria. [Figure 4] shows the pattern of diagnostic tool for DKD in the various studies. Slightly more studies (56.3%) of the studies adopted the albumin–creatinine ratio in diagnosing DKD as compared with eGFR.
Table 1 Prevalence of diabetic kidney disease in selected studies

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Figure 3 Frequency of studies on DKD done in the various geopolitical zones. DKD, diabetic kidney disease.

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Figure 4 Diagnostic approach to DKD. DKD, diabetic kidney disease.

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The forest plot is shown in [Figure 5]. The pooled prevalence of DKD in Nigeria is 28% (95% confidence interval 3–58). The Cochran’s Q was 747 (P<0.001), while the I2 statistic was 97.6% and these two parameters suggest a high level of heterogeneity in the studies. The Doi plot to check publication bias is shown in [Figure 6]. LFK index is 6.22, which suggests that there might have been some degree of publication bias.
Figure 5 Forest plot of the meta-analysis.

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Figure 6 The DOI plot for the meta-analysis.

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[Table 2] shows the risk factors for DKD reported from the selected studies. The frequency of the risk factor in the selected studies is depicted in [Figure 7].
Table 2 Risk factors for diabetic kidney disease in Nigeria

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Figure 7 Risk factors of diabetic kidney disease and their frequencies among selected studies.

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  Discussion Top

In this meta-analysis, the pooled prevalence of DKD in Nigeria was 28%. Previous studies done in other sub-Saharan Africa countries have found a prevalence rate of 22–36% [37],[38],[39],[40],[41]. The wide range in the prevalence rate across the continent was also observed in this meta-analysis. This is probably due to the differences in the sociodemographics of the participants, study designs, as well as the diagnostic criteria used in the diagnosis of DKD. The tests of heterogeneity (Cochran’s Q test and I2 statistic) earlier mentioned are also in keeping with these observed marked variations in the selected studies. All these are in keeping with the hypothesis that DKD is not a single-disease entity but a heterogeneous group of related disorders with a common theme of functional or structural abnormalities of the kidneys in people living with diabetes. This therefore calls for more studies to unravel the various dimensions of the disease.

Most of the selected studies were done in Southern Nigeria. This might raise some questions about the generalizability of the findings of the meta-analysis to the whole nation because regional differences in the prevalence of hypertension, diabetes, obesity, and other risk factors for DKD had been earlier documented by various authors [4],[42],[43]. There is a need to conduct appropriately designed studies on the prevalence and risk factors of DKD in the northern geopolitical zones of Nigeria so as to be able to ascertain the burden of the disease in such areas.

This meta-analysis shows that there is lack of consensus in the definition of DKD across the various studies. This may be due to lack of Nigerian guidelines on the diagnosis of DKD and the various authors had to adapt the foreign guidelines. While some studies (43.7%) defined DKD using eGFR, others (56.3%) defined it with albuminuria. There have been controversies on the merits and demerits of each diagnostic criterion and this calls for a national consensus on how to define DKD because the drawbacks of missing patients in the early stage of the disease are quite enormous [44]. A systematic review on diabetic nephropathy in Africa has also identified the same challenge of adopting different criteria in diagnosing DKD [45]. Interestingly, most of the newer guidelines are beginning to incorporate both manifestations (albuminuria and declining eGFR) in the diagnosis and prognosis of DKD [46].

The most commonly reported modifiable risk factors for DKD, in this systematic review, were hypertension, poor glycemic control, and obesity. Various landmark trials, such as the United Kingdom Diabetes Prevention Study (UKPDS) and Diabetes Control and Complications Trial (DCCT), have clearly demonstrated an incontrovertible association between poor glyaemic control and the development of DKD [47]. Additionally, other clinical trials have demonstrated a delay or outright prevention of DKD by ensuring tight glycemic control. Previous studies done in other continents have also alluded to the relationship between poor glycemic control and the onset of DKD [48],[49],[50].

This review also found out that hypertension was quoted as a major risk factor by various studies on DKD in Nigeria. Previous studies had also reported a similar finding [51],[52]. Concerning the association between obesity and the development of DKD, a study in China documented a significant association between body mass index and proteinuria, just as was found in the present meta-analysis [53]. The mechanisms by which obesity exacerbates DKD include insulin resistance, dyslipidemia, activation of the renin–angiotensin–aldosterone system, and the activation of the sympathetic nervous system [54].

Other risk factors for DKD identified in this meta-analysis were the male sex, age of the patient, duration of diabetes, dyslipidemia, and diabetic neuropathy. These risk factors have also been reported by various authors in their studies [51],[55]. This meta-analysis has highlighted the enormous burden of DKD in Nigeria and it is high time intense efforts were put in place to address these risk factors so as to alleviate the burden of the disease.


The studies selected did not cut across all the regions equally due to the dearth of such studies in Northern Nigeria. Similarly, the lack of consensus in the diagnostic criteria limits the generalizability of the findings.


The number of studies selected were fairly large and the total sample size was also large enough. The meta-analysis spanned about two decades, which suggests a wide coverage. This meta-analysis did not only establish the pooled prevalence of DKD in Nigeria, but also highlighted the risk factors that need to be focused on so as to mitigate the burden of the disease.

  Conclusion Top

The prevalence of DKD in Nigeria is high. Efforts should be intensified to achieve a tight glycemic control, optimal blood-pressure control, and healthy weight as these can go a long way in alleviating the burden of DKD in Nigeria.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

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  [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6], [Figure 7]

  [Table 1], [Table 2]

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