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International Journal of Nephrology and Renovascular Disease 2018:11 165–172
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REVIEW
open access to scientific and medical research
Open Access Full Text Article
http://dx.doi.org/10.2147/IJNRD.S162230
Prevalence of chronic kidney disease in Nigeria:
systematic review of population-based studies
Innocent Ijezie
Chukwuonye1
Okechukwu Samuel Ogah2
Ernest Ndukaife Anyabolu3
Kenneth Arinze Ohagwu1
Ogbonna Collins Nwabuko4
Uwa Onwuchekwa5
Miracle Erinma
Chukwuonye6
Emmanuel Chukwuebuka
Obi1
Efosa Oviasu7
1Division of Nephrology, Department
of Internal Medicine, Federal Medical
Centre, Umuahia, Abia State, 2Division
of Cardiology, Department of Internal
Medicine, University College Hospital
Ibadan, Oyo State 3Division of
Nephrology, Department of Internal
Medicine, Chukwuemeka Odumegwu
Ojukwu University Teaching Hospital
Awka, Anambra State, 4Department of
Haematology, Federal Medical Centre,
Umuahia, 5Division of Nephrology,
Department of Internal Medicine, Abia
State University Teaching Hospital,
Aba, 6Department of Family Medicine,
Federal Medical Centre, Umuahia,
7Division of Nephrology, Department
of Internal Medicine, University of
Benin Teaching Hospital, Benin City,
Nigeria
Background: The aim of this study was to identify and discuss published population-based
studies carried out in Nigeria that have information on the prevalence of chronic kidney disease
(CKD) and have also used the Kidney Disease Outcomes Quality Initiative (KDOQI) practice
guidelines in defining CKD, with emphasis on the performance of three estimating equations
for glomerular filtration rate (GFR) – Modification of Diet in Renal Disease (MDRD), Cock-
croft–Gault, and CKD epidemiology collaboration (CKD-EPI) creatinine equation.
Materials and methods: A systematic literature search was carried out in Google, MEDLINE,
PubMed, and AJOL database, with the aim of identifying relevant population-based studies with
information on the prevalence of CKD in a location in Nigeria.
Results: Seven cross-sectional population-based studies were identified. Two of the studies used
the Cockcroft–Gault and observed a prevalence of 24.4% and 26%. Four of the studies used the
MDRD and the prevalences observed were 12.3%, 14.2%, 2.5%, and 13.4%. One of the studies
used the CKD-EPI equation and the prevalence was 11.4%. The male to female ratios of CKD
prevalence in six studies were 1:1.9, 0.8:1, 1:1.6, 1:2, 1:1.8, 1:1.4, and the observed risk factors
in the studies were old age, obesity, diabetes mellitus, hypertension, family history of hyperten-
sion, family history of renal disease, low-income occupation, use of traditional medication, low
hemoglobin, and abdominal obesity.
Conclusion: The prevalence of CKD was high but variable in Nigeria, influenced by the equa-
tion used to estimate the GFR. MDRD and CKD-EPI results are agreeable. There is a need for
more population-based studies, with emphasis on repeating the GFR estimation after 3 months
in subjects with GFR <60 mL/min/1.7 m2.
Keywords: CKD, Cockcroft–Gault, Modification of Diet in Renal Disease, CKD epidemiology
collaboration creatinine equation
Introduction
Chronic kidney disease (CKD) is defined as kidney damage or glomerular filtration
rate (GFR) <60 mL/min/1.73 m² for ≥3 months.1 CKD is a worldwide public health
problem, with adverse outcomes of kidney failure, cardiovascular disease, and premature
death.1 Presently, there is an increase in the prevalence of CKD. It was ranked 27th in
the list of causes of total number of global deaths in 1990; however, by 2010, it had
dropped to 18th in the list of causes of global deaths. This degree of movement up the
list was noted to be second only to that of HIV and AIDS.2 About 10% of the world’s
population is affected by CKD.3
Hypertension and diabetes mellitus (chronic non-communicable diseases [NCDs])
are the two major causes of CKD worldwide. However, chronic glomerulonephritis
Correspondence: Innocent Ijezie
Chukwuonye
Division of Nephrology, Department
of Internal Medicine, Federal Medical
Centre, PO Box 1229 Umuahia Branch
Ofce, Umuahia, Nigeria
Tel +234 803 877 4307
Email chukwuonye4@yahoo.com
Journal name: International Journal of Nephrology and Renovascular Disease
Article Designation: REVIEW
Year: 2018
Volume: 11
Running head verso: Chukwuonye et al
Running head recto: CKD in Nigeria
DOI: http://dx.doi.org/10.2147/IJNRD.S162230
This article was published in the following Dove Press journal:
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Chukwuonye et al
and interstitial nephritis are the major causes of CKD in
developing countries of the world. This is a reflection of the
high prevalence of bacterial, parasitic, and viral infections
(communicable diseases) that affect the kidneys in these
countries.4 The prevalence of CKD is also increasing at a more
rapid rate in developing countries. These differences between
the developed and the developing countries are due to the fact
that the burden of CKD is moving away from communicable
diseases and toward chronic NCDs in the developed coun-
tries of the world. However, in developing countries, there
is a double burden of communicable diseases and NCDs.
The prevalence of some diseases such as obesity, hyperten-
sion, and diabetes mellitus has increased in the developing
countries of the world such as Nigeria due to many factors.4–6
The attention being paid globally to CKD is attribut-
able to five factors: the rapid increase in its prevalence, the
enormous cost of treatment, recent data indicating that overt
disease is the tip of an iceberg of covert disease, an apprecia-
tion of its major role in increasing the risk of cardiovascular
disease, and the discovery of effective measures to prevent
its progression.4
CKD has a huge financial burden on families of subjects
with the medical condition in Nigeria7,8 and in order to dras-
tically reduce the frequency of CKD in the country, a good
knowledge of its prevalence is needed and such knowledge
can only be obtained from population-based epidemiologic
studies. There are several studies on CKD in Nigeria.9–11
However, most of these studies are hospital based. This study
reviews only published population-based studies that have
information on the prevalence of CKD in Nigeria, and that
also used the Kidney Disease Outcomes Quality Initiative
(KDOQI) practice guidelines in defining CKD with empha-
sis on the performance of three estimating equations for
GFR – the Modification of Diet in Renal Disease (MDRD),
Cockcroft–Gault (CG), and CKD epidemiology collaboration
(CKD-EPI) creatinine equation.
Materials and methods
Selection of eligible studies, types of
studies, and sources of information
A systematic literature search was conducted in Google and
MEDLINE database to identify all publications on CKD
in Nigeria with the aim to sieve out population-based stud-
ies with relevant information on the prevalence of CKD in
locations in Nigeria published before 1 November, 2017
(search limit). The systematic review was carried out in
the last quarter of 2017. The search terms used in Google
and MEDLINE database were “chronic kidney disease in
Nigeria” or “chronic renal failure in Nigeria”. In addition,
some full articles of identified community-based studies that
we had difficulty obtaining were also searched for in PubMed
and the African Journals Online using the title of the article
or the name of the first author.
Search strategy
The articles are published in English language, the official
language of Nigeria. In order to eliminate difficulties in
analyzing the data, attention was paid to population-based
studies that made use of the same definition of CKD.
Inclusion criteria
1. The study is population based with relevant information
on the prevalence of CKD in a location in Nigeria.
2. CKD is defined as estimated GFR <60 mL/min by the
CG formula, or an estimated GFR of <60 mL/min/1.73
m2 by the MDRD and CKD-EPI creatinine equation.
This definition is in keeping with the K/DOQI practice
guidelines published in 2002 by the National Kidney
Foundation.12
3. The study involves adult Nigerians of both male and
female gender.
4. There is a representative sample of the general population
in the study.
5. The MDRD, CG, or the CKD epidemiology equation was
used to estimate the GFR in the study.
6. The study has a full publication, and is not published only
in abstract.
Exclusion criteria
Studies that did not meet the inclusion criteria were excluded
from this review. Population-based studies limited to a
particular profession or patients with a particular disease
condition (e.g., civil servants, HIV, university community)
were excluded.
Denition of terms
Chronic kidney disease
This is defined as creatinine clearance or GFR <60 mL/
min/1.73 m2.12
Cockcroft–Gault
Creatinine clearance (mL/min)=(140–age)/(serum
creatinine)×(weight/72)×(0.85 if female)13
Serum creatinine is measured in mg/dL, age in years,
weight in kg, and GFR is expressed as mL/min.
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CKD in Nigeria
Simplied (four-variable) MDRD equation
GFR (mL/min/1.73 m2)=186.3×(serum creatinine)−1.154×
(age)−0.203×(0.742 if female)×(1.21 if black)14
Serum creatinine is measured in mg/dL, age in years, and
GFR is expressed as mL/min/1.73 m2.
CKD-EPI formula
GFR=141×min (Scr/κ, 1) α×max (Scr/κ, 1)−1.209×0.993
age×1.018 (if female)×1.159 (if black)15
where Scr is serum creatinine in mg/dL, κ is 0.7 for females
and 0.9 for males, α is −0.329 for females and −0.411 for
males, min indicates the minimum of Scr/κ or 1, and max
indicates the maximum of Scr/κ or 1.
GFR is expressed as mL/min/1.73 m2.
Data collection
All identified articles from the search were downloaded, and
hospital-based studies were jettisoned from the study. The
full-text versions of all community-based studies on CKD
were obtained, and the articles that did not meet the inclusion
criteria were excluded.
Data extraction
The community-based studies that met the inclusion criteria
were closely scrutinized by at least two authors and the relevant
data extracted. Any controversy surrounding any article was
collectively resolved by all authors giving their opinion and
the final decision taken by consensus. The data extracted from
studies that met the inclusion criteria included the location of
the study in Nigeria, the year of the study, sample size, mean
age of subjects, sampling method, GFR equation/formula used,
prevalence of CKD, and the male:female ratio of prevalence of
CKD. Other data extracted from each of the studies included
prevalence of CKD by age and risk factors of CKD (in studies
that carried out multiple logistic regression). These data were
computed into tables to allow for easy comparison.
Results
The search on population-based studies that had relevant
information on the prevalence of CKD in Nigeria returned a
total of 65 articles. Sixteen of these articles were population-
based studies. Seven of the population-based studies met the
inclusion criteria.16–22 Each of the seven articles was closely
scrutinized by at least two authors. Any controversy surround-
ing any particular article was discussed by all the authors, and
a collective decision taken on the article (Figure 1).
7 articles included
16 articles retrieved
Inclusion/exclusion
criteria applied
Inclusion/exclusion
criteria applied
65 non-duplicate
citations screened
MEDLINE and Google
articles published before 1 November, 2017
82 citation(s)
9 articles excluded
after full-text screen
49 articles excluded
after title/abstract screen
Articles excluded
during data extraction
Figure 1 PRISMA ow diagram of studies.
Abbreviation: PRISMA, preferred reporting items for systematic reviews and meta-analysis.
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Chukwuonye et al
One of the seven articles was from South-south zone,16
two from South-west,17,20 two South-east,18,22 one from North-
west,19 one from the North-central,21 and none was from
the North-east geopolitical zone of Nigeria (Figure 2). The
subjects who took part in the studies were males and females
of age ≥18 years. The mean age in the studies ranged from
39.0±11.021 to 54.8±12.8 years.22 There was no particular
study that focused on a particular age group (e.g., elderly
subjects). The least sample size was 32822 and the largest
sample size was 194118 (Table 1).
All the seven relevant studies were cross-sectional. One of
the studies used cluster sampling method,16 three studies used
multistage sampling technique,17,19,22 two other studies used
convenience sampling technique,18,21 and one of the studies20
did not state what sampling method was used.
Two of the studies used the CG formula in estimating
GFR,16,19 four studies used the MDRD,17,20–22 whereas one
of the studies used the CKD-EPI creatinine equation.18 The
prevalence of CKD from two of the studies that used the CG
formula was very high when compared to those obtained
with the MDRD and the CKD-EPI creatinine equations.
Three of the studies that used the MDRD equation17,20,22 and
the only study that used the CKD-EPI creatinine equation18
had similar results. However, one of the studies that used the
MDRD21 has a very low prevalence of CKD when compared
to the other three results.
Six out of the seven studies provided a gender-specific
prevalence of CKD, and the prevalence of CKD was greater
in females in all the six studies (this is expressed in a ratio
format in Table 1).16,17,19–22
Cross
River
Abia
Imo
Delta
Edo
Kogi
Ogun
Lagos
Osun
Ekiti
Kaduna
Katsina
Gombe
Kebbi
FCT
Enugu
Anambra
Rivers Akwa
Iborn
Ebonyi
Benue
Plateau
Nasarawa
Taraba
Adamawa
Cameroon
Niger
Benin
Legend
South-east region
0112.5 225 450 km
South-south region
South-west region
North-central region
North-east region
North-west region
S
N
WS
Borno
Yobe
Jigawa
Kano
Bauchi
Niger
Zamfara
Sokoto
Kwara
Ondo
Oyo
Bayelsa
Figure 2 Map of Nigeria showing the six geopolitical zones.
Abbreviation: FCT, Federal Capital Territory.
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CKD in Nigeria
Table 1 Prevalence of chronic kidney disease from population-based studies in Nigeria
Reference Location in Nigeria/state Year of
study
Sample
size
Mean age
(years)
Sampling
method
GFR
equation
Prevalence
of CKD (%)
Prevalence
of CKD M:F
16 Etsako/Edo 2009 520 Cluster CG 24.3 1:1.9
17 Ilie, Olorunda/Osun 2008 454 45.8±19.0 Multistage MDRD 12.3 0.8:1
18 Enugu (Ujodo Nike, Emene-Nike
and Mbulu-Ujodo)/Enugu
2013 1941 43.7±13.2 Convenience CKD-EPI 11.4
19 Kumbotso/Kano 450 39.6±16.4 Multistage CG 26 1:1.6
20 Ten communities from Ekiti
North and Central senatorial
districts/Ekiti
2013 1084 56.3±19.9 MDRD 14.2 1:2
21 Jos/Plateau 2013 510 39.0±11.0 Convenience MDRD 2.5 1:1.8
22 Umuahia (Olokoro)/Abia 2014 328 54.8±12.8 Multistage MDRD 13.4 1:1.4
Notes: Each of the seven studies included men and women, and CKD was dened as GFR <60 mL/min/1.73 m2.
Abbreviations: CG, Cockcroft–Gault; CKD, chronic kidney disease; CKD-EPI, chronic kidney disease epidemiology collaboration; F, female; GFR, glomerular ltration rate;
M, male; MDRD, Modication of Diet in Renal Disease.
Table 2 Distribution of prevalence of CKD among the various
stratied age groups and the risk factors of CKD
References Prevalence of
CKD by age (%)
Risk factors for CKD
(multiple logistic regression)
16 Age ≥50 years
Obesity (↑BMI ≥30)
17 Female gender
Systolic blood pressure
Diabetes
18 Older age
Low-income occupation
Use of traditional medication
Low hemoglobin
19 18–29 years – 20.2
30–44 years – 20.9
45–60 years – 30.6
61–90 years – 42.9
Obesity (↑BMI ≥30)
Family history of hypertension
History of diabetes mellitus
Family history of renal disease
20
21 Age
22 Old age
Hypertension
Family history of kidney disease
Obesity (↑BMI ≥30)
Central obesity
Abbreviations: BMI, body mass index; CKD, chronic kidney disease.
One of the studies stratified the prevalence of CKD based
on age.19 The prevalence of CKD increased steadily with age
in this study population (Table 2).
Univariate binary logistic analysis was used in six stud-
ies16–19,21,22 to determine the relationship between CKD and
various variables. This was followed by multiple logistic
regression using the variables from the univariate binary
logistic analysis that were significantly associated with CKD,
in order to determine the predictors (risk factors) of CKD
(Table 2). The most common risk factor among the studies
was old age,16,18,21,22 followed by obesity (↑body mass index
≥30 kg/m2);16,19,22 others were diabetes mellitus,17,18 hyperten-
sion,17,22 family history of hypertension,19,22 and family his-
tory of renal disease.19,22 Less common risk factors included
low-income occupation, use of traditional medications, low
hemoglobin, and central obesity.18,22
Discussion
The prevalences of CKD observed from the seven population-
based cross-sectional studies that met the inclusion criteria
were 24.3%,16 12.3%,17 11.4%,18 26%,19 14.2%,20 2.5%,21 and
13.4%.22 The prevalences of CKD in the two studies that used
the CG to estimate the GFR were 24.3%16 and 26%.19 These
values were much higher than those obtained with the four
studies that used the MDRD (12.3%,17 14.2%,20 2.5%,21 and
13.4%22) and the only study that used the CKD-EPI18 creati-
nine equation (11.4%). The prevalences observed in three of
the MDRD equations (12.3%,17 14.2%,20 13.4%22) and that
observed in the CKD-EPI creatinine equation (11.4%18) were
within reasonable agreement. These results suggest that the
prevalence of CKD depends on the equation used to estimate
GFR and further showed that the CG gives a lower estimate
of GFR than the MDRD and the CKD-EPI creatinine equa-
tions. Similar observation was made by Viktorsdottir et al23
in a study in which 19, 381 subjects participated. The study
revealed that GFR estimates and the prevalence of CKD
are dependent on the equation used to calculate estimated
GFR. The study compared three different equations used to
calculate estimated GFR based on serum creatinine and to
estimate the prevalence of CKD in the Icelandic population.
It was observed that the GFRs estimated by the three equa-
tions used in the study were different. CG gave lower values
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Chukwuonye et al
of estimated GFR when compared to MDRD. Chen et al24
in a study that evaluated the prevalence of decreased kidney
function in Chinese adults aged 35–74 years observed that
the prevalence of moderately and severely decreased kidney
function estimated using the CG equation was much higher
than that estimated using the four variable MDRD study
equations in a Chinese population. Using CG, the prevalences
of GFR 30–59 mL/min/1.73 m2 and GFR <30 mL/min/1.73
m2 were 19.6% and 0.8%, respectively, while for MDRD,
the prevalences of estimated GFR of 30–59 mL/min/1.73
m2 and GFR <30 mL/min/1.73 m2 were 2.4% and 0.14%,
respectively. However, for mildly decreased GFR (60–90
mL/min/1.73 m2), the same prevalence value (39.4%) was
observed with both equations.
Matsha et al25 assessed the prevalence and determinants
of CKD and evaluated the concordance of commonly
advocated estimators of GFR in a mixed ancestry popu-
lation from South Africa in their study comprising 1202
subjects. The estimated GFR was based on the CG, MDRD,
and CKD-EPI equations (with and without adjustment for
ethnicity). The crude prevalence of CKD stage 3–5 was
14.8% for CG, 7.6% and 23.9% for MDRD with and with-
out ethnicity correction, respectively, and 7.4% and 17.3%
for the CKD-EPI creatinine equations with and without
ethnicity correction, respectively. The highest agreement
between GFR estimators was between MDRD and CKD-EPI
equations, both with ethnicity correction.25 There are contro-
versies over which one of these popular equations is more
reliable in patients with GFR <60 mL/min/1.73 m2. Evans
et al26 compared the performance of five different estimated
GFR equations, CG, MDRD, CKD-EPI, Mayo Clinic, and
Lund-Malmö, with measured GFR (plasma iohexol clear-
ance) in 2098 referred CKD patients with advanced renal
failure. The GFR-estimating equations showed reasonably
good performance at the population level. The best overall
performance was achieved by Lund-Malmö and CKD-EPI
equations, followed by the MDRD. The performance of
MDRD was much better than that of CG. The performance
of MDRD was almost the same as the CKD-EPI equation.26
However, this study was carried out in a Caucasian popu-
lation. The high agreement between the GFR estimation
by the four-variable MDRD and the CKD-EPI creatinine
equation is due to the fact that the CKD-EPI creatinine
equation is based on the same four variables as the MDRD
study equation, the only difference being that it uses a two-
slope spline to model the relationship between estimated
GFR and serum creatinine and a different relationship for
race, age and gender.15
Four of the studies in this review used the MDRD equa-
tion for GFR estimation.17,20–22 However, one of the studies21
observed a very low prevalence when compared to the other
three. The study was carried out in Jos in the North-central
region of Nigeria. The very low prevalence observed in the
study tends to suggest that the prevalence of CKD is low in
that region. However, this is not an assumption. It is most
likely that the low prevalence observed in the study is due to
the study method used – convenience sampling method. The
convenience sampling method does not require the generation
of a simple random sample; the only requirement is usually
the availability of participants who have agreed to participate.
It is more likely that a sample will resemble the population
when the method used to select the sample utilizes a random
process. The convenience sampling method is characterized
by insufficient power to identify the differences in popula-
tion subgroups. The results of convenience sampling method
cannot be generalized to the target population because of
the potential bias of the sampling technique. Inferences on
a study based on convenience sampling method are made
about the sample itself.27,28
One other study that used the MDRD creatinine equa-
tion did not state the sampling method used in the study.20
However, the fact that 10 communities were chosen by a
random process from two senatorial districts in Ekiti state,
and that the study period was 6 months, clearly shows that
convenience sampling method was not the sampling method
used. It is most likely that the method that was used was either
cluster or stratified random or multistage, like in their earlier
study in Osun state.17 The study seems to have also used the
CKD-EPI creatinine equation in estimating the GFR. This is
implied in the article. However, only the result of the MDRD
equation was reported in the article.
The only study that used the CKD-EPI creatinine equa-
tion18 used a hybrid of a random sampling method and
convenience sampling method. The initial sampling method
was a random process (two semi-urban and two rural com-
munities selected by a random process). However, due to
the age distribution of the populations, that is, younger
population in semi-urban areas and older population in
rural communities, the study ultimately used a convenience
sampling strategy.18
The male to female ratios (M:F) of the prevalence of
CKD in six of the studies were 1:1.9,16 0.8:1,17 1:1.6,19 1:2,21
1:1.8,21 and 1:1.4,22 respectively. The studies presented a
gender-specific prevalence of CKD, with the prevalence being
higher in the female gender. Zhang and Rothenbacher12 in
a review of population-based studies on the prevalence of
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CKD in Nigeria
CKD observed that several studies had higher prevalence of
CKD in females. Kalyesubula et al29 in a community-based
study on kidney disease in Uganda also recorded a higher
prevalence of CKD in the female gender. The fact that men
have more muscle mass than women, and the differences in
hormone metabolism and glomerular structure are assumed to
play a role in the differences in prevalence of CKD observed
between male and female gender.30
Only one study stratified the prevalence of CKD based on
age.19 The prevalence of CKD increased steadily with age in
the study population. van Blijderveen et al31 in a retrospective
cohort study conducted in a dynamic population using data of
784,563 adult participants also observed that the incidence/
prevalence of CKD increases steadily with age. Several other
previous population-based studies also observed a steady
increase in the prevalence of CKD with age.12
Six of the studies16–19,21,22 used binary/multiple regressions
to determine the risk factors of CKD in their location/region
in Nigeria. Old age,16,18,21,22 obesity (body mass index ≥30 kg/
m2),16,19,22 diabetes mellitus,17,18 hypertension,17,22 family his-
tory of hypertension,19,22 family history of renal disease,19,22
low-income occupation,18 use of traditional medication,18
low hemoglobin,18 and central obesity22 were found to be
the risk factors of CKD. The observed risk factors did not
include any communicable diseases because communicable
diseases were not included in the binary/multiple regressions.
However, studies from other African nations show that com-
municable diseases are risk factors of CKD in sub-Saharan
African countries.32
Limitations of the studies
A major drawback in these studies is that the estimated
GFR of the subjects who were observed to have CKD was
only assessed once. Ideally, the assessments should have
been repeated 3 months later to find out if the values of the
estimated GFR were still below 60 mL/min/1.73 m2 in the
subjects with CKD.1 This would have given an accurate
prevalence of CKD with creatinine equations. It is worth
noting that one of the studies did repeat the GFR estima-
tion 3 months later; estimated GFR <60 mL/min/1.73 m2
was found in 44 (13.4%) participants at the first assessment
and only 15 participants (4.6%) had persistently low GFR
at reassessment 3 months later.22 The sharp drop in the
prevalence clearly shows that a good majority of the earlier
captured subjects did not have CKD. A major limitation of
the study that repeated the estimation of GFR 3 months
later is that the sample size was small (328), and the value
obtained is not likely to be the true prevalence of CKD in
Nigeria. However, the prevalence of CKD is most likely to
be below 10% and may be close to 4.6% using the MDRD
and CKD-EPI creatinine equation.
Conclusion
There was variable prevalence of CKD in the studies, influ-
enced by the creatinine equation used to estimate the GFR.
The MDRD and CKD-EPI results are agreeable, and they are
better than the CG creatinine formula in estimating the GFR
in subjects with GFR <60 mL/min/1.7 m2. Discordantly high
CKD prevalence at the first test and low value at 3 months
interval in one of the studies demonstrated that high preva-
lence values were obtained in estimating the GFR once and
not repeating the test 3 months later.
Recommendation
We recommend more cross-sectional, large sample size,
population-based studies on the prevalence of CKD, using
multistage sampling method, with emphasis on repeating the
GFR estimation 3 months later. These will provide the true
prevalence of CKD using the popular creatinine equations
(preferably MDRD or CKD-EPI creatinine equation).
Disclosure
The authors report no conflicts of interest in this work.
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