Prevalence of chronic kidney disease based on estimated glomerular filtration rate and proteinuria in Icelandic adults
Olof Viktorsdottir1,
Runolfur Palsson1,2,
Margret B. Andresdottir2,3,
Thor Aspelund3,
Vilmundur Gudnason1,3 and
Olafur S. Indridason2
1 University of Iceland Faculty of Medicine, 2 Division of Nephrology, Department of Medicine, Landspitali University Hospital, 3 Icelandic Heart AssociationResearch Clinic, Reykjavik, Iceland
Correspondence and offprint requests to: Olafur Skuli Indridason, Division of Nephrology, Department of Medicine, Landspitali University Hospital, 101 Reykjavik, Iceland. Email: osi{at}tv.is
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Abstract
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Background. The purpose of this study was to compare three different equations to calculate estimated glomerular filtration rate (eGFR) based on serum creatinine (SCr) and to estimate the prevalence of chronic kidney disease (CKD) in the Icelandic population.
Methods. This was a cross-sectional study using data from the Reykjavik Heart Study. GFR was estimated with three equations: Equation I was based on 1/SCr; Equation II based on the Cockcroft-Gault equation; and Equation III was the modified MDRD equation. The eGFR calculated with Equation III and proteinuria were used to estimate the prevalence of CKD. The prevalence was age-standardized to the truncated world population. We used
-square and ANCOVA to compare the group with low eGFR to age-matched controls.
Results. The subjects consisted of 9229 males and 10 027 females, aged 3385 years. The equations performed very differently. Equation I showed women with higher eGFR than men and little change with age. Equation II showed men with higher eGFR than women and marked decline in eGFR with age. Equation III was similar to Equation II but the decline in eGFR with age was not as great. Regardless of the equation used, most subjects (63.780.7%) had an eGFR in the range of 6089 ml/min/1.73 m2. Using Equation III, age-standardized prevalence of low eGFR for the population aged 3580+ years was estimated to be 4.7 and 11.6% for men and women, respectively. The proportion of subjects with eGFR <60 ml/min/1.73 m2 increased with advancing age. An additional 2.39% of men and 0.89% of women had proteinuria. The prevalence of renal and cardiovascular risk factors including proteinuria, hypertension, lipid abnormalities and markers of inflammation was higher among those with low eGFR than age-matched controls.
Conclusions. GFR estimates and the prevalence of CKD are dependent on the equation used to calculate eGFR. Unexpectedly, a low proportion of the Icelandic population had normal kidney function according to the eGFR regardless of the equation used. These equations may not be useful in epidemiological research.
Keywords: chronic kidney disease (CKD); cohort study; epidemiology; estimation of GFR; prediction equations; prevalence; proteinuria; serum creatinine
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Introduction
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The frequency of end-stage renal disease (ESRD) has been increasing rapidly worldwide. While the greatest incidence and prevalence have been observed in the United States, where in excess of 300 new patients have initiated dialysis therapy per million population annually in the past few years [1,2], the surge in ESRD has been felt in other Western countries as well [3,4].
The explosion in ESRD has fuelled a rising interest in the epidemiology of chronic renal failure. Earlier studies focusing on serum creatinine levels (SCr) as a marker of renal function yielded variable results with the prevalence ranging from 0.1 to 10% [58]. This discrepancy is probably due to variable methodology and different assays and cut-off points for serum creatinine. Recently, guidelines on diagnosis and staging of chronic renal disease (CKD) were published by the K/DOQI of the NKF [9]. These guidelines have defined CKD as a state where one is either suffering from kidney damage and/or have a glomerular filtration rate (GFR) less than 60 ml/min/1.73 m2 for
3 months. They also advocate the use of GFR as the best indicator of renal function, to stage CKD where the first of five stages define a normal level of GFR,
90 ml/min/1.73 m2, with each successive stage defining a more severe decrease in GFR with the last stage defining kidney failure with GFR <15 ml/min/1.73 m2 or need for renal replacement therapy. However, measuring GFR is expensive and cumbersome and various methods of calculating estimated GFR (eGFR) from serum creatinine concentration have been studied, including the CockcroftGault equation and several equations derived from the MDRD study population [10,11]. The use of these equations in population-based studies suggests a surprisingly high prevalence of CKD [1214], leading some authors to doubt their usefulness in epidemiological research [1517]. Nevertheless, the use of GFR estimates based on serum creatinine has gained popularity both in research and clinical practice.
Iceland has one of the lowest ESRD prevalences among Western nations [3] and a previous study using serum creatinine cut-off of 150 mmol/l (1.7 mg/dl) to define chronic renal failure indicated its prevalence to be <0.5% [8].
The purpose of the current study was to assess three different equations used to estimate GFR based on serum creatinine in an unselected sample of community-dwelling adults. We also wanted to calculate the prevalence of CKD as manifested by proteinuria and/or low eGFR (eGFR <60 ml/min/1.73 m2) determined with one of these equation to assess whether a lower prevalence of CKD in Iceland might explain intercontinental differences in the ESRD prevalence. Finally, we examined the prevalence of cardiovascular and renal risk factors in this population.
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Subjects and methods
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We used the data from the Reykjavik Heart Study, a population-based cohort study conducted in the years 19671996. A detailed description of the Reykjavik Heart Study has been published previously [8]. In brief, all men born between 1907 and 1934 and women born between 1908 and 1935 and living in the Reykjavik area in 1967 were divided into six groups and invited to the Research Centre during six phases, the first phase taking place in 196769 and the last one 199196 (Figure 1). The participants answered a thorough questionnaire on demographic issues, social and medical history as well as undergoing standardized physical examination and laboratory testing. All participants were Caucasians as expected in the Icelandic population. The present study is cross-sectional, using the first visit of each participant to the Research Centre. The study was approved by the National Bioethics Committee in Iceland.

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Fig. 1. Outline of the Reykjavik Heart Study. The participants were divided into six groups (AF), which were examined in six different phases. The gray boxes indicate in which phase each group was invited to participate. Groups B and C had repeated visits but in the present study we used only the first visit of each participant to the Research Centre.
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Laboratory tests
Fasting morning blood samples were analysed for erythrocyte sedimentation rate (ESR), glucose, triglycerides, cholesterol and SCr. SCr concentration was measured by an endpoint Jaffé reaction between 1967 and 1988 (Autoanalyzer I from Technicon 19671986 and an SMA-6 19861988). After 1988 SCr was measured with a kinetic Jaffé reaction (Cobas-Mira analyzer). When instruments were changed, repeated measurements and standardization was performed to assure that SCr results were comparable. Nevertheless, we re-analyzed frozen samples from 246 subjects using the current analytical instruments at the Research Centre. However, the results were on average 2030% higher than the initial measurements regardless of which analyser was used initially. We therefore did not attempt to perform further standardization of the serum creatinine assay. Urine specimen was collected and proteinuria measured with Albustix.
Evaluation and staging of renal function
We used the following equations to calculate eGFR in ml/min/1.73 m2:
These equations have previously been examined in the estimation of GFR and found to have an R2 value in excess of 80% in predicting logGFR [10,11]. Equation I is based on 1/SCr. Equation II is based on the CockcroftGault equation and corrected for body surface area (Du Bois method), whereas Equation III is a modified MDRD study equation. All the equations predict GFR in ml/min/1.73 m2 and correction factors used in Equation I and Equation II decrease bias observed in GFR prediction [10,11]. For each equation we used the staging suggested by the K/DOQI guidelines, to define different stages of kidney function [9].
Stage 1. eGFR
90 ml/min/1.73 m2: normal or increased
GFR levels.
Stage 2. eGFR 6089 ml/min/1.73 m2: mild decrease in GFR
but may be normal for age.
Stage 3. eGFR 3059 ml/min/1.73 m2: moderate decrease in
GFR.
Stage 4. eGFR 1529 ml/min/1.73 m2: severe decrease in
GFR.
Stage 5. eGFR <15 ml/min/1.73 m2 or in dialysis: kidney
failure.
Definitions
Proteinuria was defined as 1+ or greater measured by Albustix. Individuals were considered to have hypertension if the blood pressure measured
140/90 mm Hg on the second of two blood pressure measurements or if they were taking blood pressure lowering medications. Patients were considered to have diabetes if they answered yes to the question Do you have diabetes (now or before)? and/or if fasting serum glucose was >7 mmol/l (126 mg/dl). History of other medical conditions was determined by self-report.
Data analysis
To analyse the results of the different eGFR equations we used descriptive statistics. We used the results from equation III to calculate the prevalence of low eGFR, defined as an eGFR <60 ml/min/1.73 m2 since several studies have implied that equation III is the most accurate of the three equations we used in this study (R2 = 0.89) [10,11]. The prevalence of low eGFR and proteinuria is presented as crude prevalence and, because we only have data on subjects aged 3080 years or older, we also present the prevalence of low eGFR standardized to the world population, truncated to age groups 3580 years or greater. We used analysis of variance, analysis of covariance and
-squared to compare the group with low eGFR to a control group that was matched for age and time of visit to the research centre. For variables with a skewed distribution we used logarithmic transformation. Men and women were analysed separately. Data are presented as mean±SD or as a percentage (%).
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Results
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Study population
A total of 19 381 persons participated in the study, of whom 9229 males and 10 027 females had serum creatinine measurements available, accounting for more than 70% of the group invited and alive at the time of the initial visit. Table 1 describes clinical characteristics of the subjects. It shows that females were older than males. As expected, the males were taller, heavier and had higher SCr values than females. More males smoked.
Estimation of GFR
The three equations gave results that differed markedly between males and females and depended on age to a varying degree (Figure 2). Equation I gave higher values of eGFR for females than for males. The mean difference between males and females was 12.9 ml/min/1.73 m2. However, the values were similar for all age groups. Equation II produced higher values of eGFR for males and the eGFR declined by approximately 10 ml/min/1.73 m2 for each decade in both genders. The difference in eGFR between males and females was in the range of 0.23.7 ml/min/1.73 m2 and had a tendency to decrease with advancing age. Equation III gave a higher value of eGFR for males than females across all age groups and this gender difference was similar in all age groups, with a mean difference of 7.2 ml/min/1.73 m2, except in the oldest age group (80 years and older), where it was 11.5 ml/min/1.73 m2. The eGFR values decreased by
5 ml/min/1.73 m2 per decade in both males and females.

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Fig. 2. Mean GFR (ml/min/1.73 m2) calculated with each of the three equations for males (A) and females (B). Equation I, diamonds; Equation II, squares; and Equation III, triangles.
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Stages of kidney function
Using the eGFR cut-off values as defined by K/DOQI, the number of subjects in each stage was variable, depending on equation used (Figure 3). The prevalence of normal eGFR (Stage 1, eGFR
90 ml/min/1.73 m2) was unexpectedly low, from 1.8 to 24.9%, depending on which equation was used. According to Equation III, 24.9% of males and 14.6% of females had normal eGFR. Most of the participants were in stage 2 (eGFR 6089 ml/min/1.73 m2), regardless of the equation used. The percent of females in that stage was 63.780.7% depending on the equation and the percent of males was 70.376.9%. Equation III placed
70% of males and females in the second stage. Stage 3 (eGFR 3059 ml/min/1.73 m2) had a lower prevalence where, for instance, Equation III gave 3.7% of males and 11.0% of females. In stage 4 (eGFR 1529 ml/min/1.73 m2) there were 0.00.3% of subjects and in stage 5, which defined ESRD, there were zero subjects when Equation I was used, three males and a female using Equation II and a single female when Equation III was used.

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Fig. 3. Stages of kidney function according to the three different GFR equations for males (A) and females (B). Equation I, white bar; Equation II, gray bar; and Equation III, black bar.
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Prevalence of low eGFR and proteinuria
The crude prevalence of eGFR <60 ml/min/1.73 m2 calculated by Equation III, was 3.7% for males and 10.9% for females. The age-standardized prevalence was 4.71 and 11.55% for males and females, respectively (Table 2). The prevalence increased with advancing age and there were more females than males with low eGFR in all age groups (Figure 4). At the age of 80 years,
25% of the males had eGFR <60 ml/min/1.73 m2, but roughly 50% of the females. Among all subjects with eGFR
60 ml/min/1.73 m2, proteinuria was present in 2.39% of males and 0.89% of females. The prevalence of CKD as defined by the K/DOQI guidelines was therefore about 7% for males and 12.5% for females.

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Fig. 4. Prevalence of CKD in different age groups. Equation III was used to estimate GFR. Males, squares; and females, triangles.
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Characteristics of subjects with low eGFR
Compared to age-matched controls from the study cohort, males with low eGFR had significantly higher serum triglyceride concentration and haemoglobin levels. Both systolic and diastolic blood pressure, as well as body mass index (BMI), were higher than in controls. In addition, a higher percentage of males with low eGFR were taking antihypertensive medications or had elevated blood pressure or known urinary tract disease or proteinuria. However, fewer of them were current smokers and although more of them had diabetes or known heart disease, this difference was not statistically significant (Table 3). Females with low eGFR had higher BMI, ESR, serum cholesterol or triglyceride concentration than age-matched controls, and a greater number of them were taking antihypertensive medications, had known heart disease or diabetes mellitus, had systolic blood pressure above 140 mmHg or proteinuria, compared to the controls. Fewer women in the low eGFR group were current smokers but there was no difference in the rate of known urinary tract disease between the low eGFR and the control groups (Table 4).
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Discussion
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Our study examined the performance of three different equations estimating GFR in a large population of Icelandic adults. The results show that the staging and prevalence of CKD depends heavily on the method used to estimate GFR and considering the low ESRD prevalence in Iceland, the CKD prevalence estimates were surprisingly high, regardless of the equation used. In fact, the CKD prevalence was not lower than what has been shown in the USA where ESRD is two to three times more prevalent. Subjects with CKD had higher incidence and risk factors for cardiovascular disease.
In our study Equation I, which is based on 1/SCr and fails to account for age, sex and size, differed from the other equations in that females had higher eGFR than males. This may not come as a surprise since males tend to have higher SCr values than females. In addition, there was little or no difference in eGFR between age groups. These results are similar to the findings of Clase et al. [12] and this equation seems to be inadequate both for use in clinical practice and epidemiological research.
Recent epidemiological studies have also applied the CockcroftGault equation and variations of the MDRD equation to examine CKD prevalence [1214,18]. Clase et al. [12] used four clinically applicable equations to assess renal function in a large community-based non-diabetic population who participated in the NHANES III. By using the MDRD GFR prediction equation 7, 58% of the adult non-diabetic US population had GFR below 80 ml/min/1.73 m2, 13% below 60 ml/min/1.73 m2 and 0.26% below 30 ml/min/1.73 m2. By using the CockcroftGault equation, the comparable numbers were 39, 14 and 0.81%, respectively. Their findings of an unexpectedly high prevalence of low eGFR and creatinine clearance and the increased prevalence of low eGFR with age are consistent with our results. Similar to our study, they also found a higher prevalence of eGFR below 60 ml/min/1.73 m2 in white women compared with white men using both the MDRD equation and the CockcroftGault creatinine clearance estimate. This gender difference was not detected in African Americans who also were less likely to have low eGFR. Coresh et al. [13] also examined the NHANES III data but came to a somewhat different conclusion. They used the same simplified MDRD study equation as we did but calibrated the NHANES SCr to the MDRD study SCr measurements, resulting in a subtraction of 0.23 mg/dl (20.3 mmol/l) from the NHANES SCr. An overall prevalence of GFR less than 60 ml/min/1.73 m2 was 4.5%, with women having a 50% greater prevalence than men and Caucasians 50% greater prevalence than African Americans. Similar results were found when the CockcroftGault equation was used although older subjects were more affected. When adding information on proteinuria, the total prevalence of CKD was estimated to be 11% in the adult US population. The gender and race difference observed in these studies is interesting and flies in the face of ESRD statistics where men and African Americans are disproportionally affected [2]. Coresh et al. [13], found the prevalence of proteinuria to be about 3% for subjects with eGFR
60 ml/min/1.73 m2, which is similar to the 2.39% we observed in males but markedly higher than we found for females in our study. In a large study in Australians older than 25 years of age, Chadban et al. [14] found a prevalence of 11.2% for eGFR below 60 ml/min/1.73 m2 using the CockcroftGault equation and adjustment for body surface area with a 16% prevalence of CKD when proteinuria (2.4%) and hematuria (4.6%) were included. In this study, gender difference was unremarkable.
While inter-laboratory differences and need for calibration of SCr measurements pose a major problem when comparing epidemiological studies, the issue of whether the equations used are valid and which one to choose also remains a major question. Our study and those of others show that the different equations perform differently based on age, race and gender. Furthermore, several studies indicate that these equations, including the ones we used, do not accurately predict GFR in subjects with normal renal function or mild renal insufficiency [15,17]. A study by Bostom et al. [15] specifically evaluated the predictive performance of several GFR prediction equations in subjects with CKD and normal SCr. They found that the most accurate results were obtained with the CockcroftGault equation, whereas the most precise equation, albeit biased, was the MDRD Study equation. In addition, Lin et al. [17] found that none of the equations performed well in healthy potential kidney donors. Finally, Beddhu et al. [16] studied the validity of the assumption of the MDRD formula and concluded that the fundamental assumption of the formula was invalid in patients with advanced kidney failure and that its use in these patients might introduce bias.
It is in this context that the results of our study need to be considered. It is possible that we have overestimated the prevalence of CKD, particularly for women, who had a greater prevalence of low eGFR compared to males. This contradicts the fact that more males than females receive treatment for ESRD in Iceland [3]. However, results from several of the other epidemiological studies are comparable in this regard [12,13,18], suggesting that gender and possibly age are too dominant in the equations, particularly Equation II. In addition, using Equation II to estimate GFR, a constant of 0.84 is used with the CockcroftGault equation [10,11] resulting in estimates of GFR that are lower than the creatinine clearance values. This may partly explain the high prevalence of low GFR obtained with this equation in our study but does not alter the gender and race differences observed in our and prior studies.
Our study showed that cardiovascular disease and certain cardiovascular and renal risk factors were more common among those with eGFR below 60 ml/min/1.73 m2 than age-matched controls. This includes hypertension, increased BMI, hypertriglyceridemia and proteinuria. ESR was significantly higher among women, and in men with CKD, the higher ESR was of borderline significance. The same was true for serum cholesterol. This suggests that these factors may contribute to the risk of developing renal or cardiovascular disease. Indeed, renal and cardiovascular diseases have many risk factors in common and renal disease may be an independent risk factor for cardiovascular disease as suggested by recent studies [1921]. Inflammation has been associated with renal failure and ESR, being an inflammatory marker, also appears to be an independent risk factor for cardiovascular disease [22]. The role of inflammation in CKD needs to be studied more thoroughly in prospective studies.
The main strength of our study is its foundation in an unselected population, consisting of approximately 20 thousand individuals, which accounts for a large proportion of the Icelandic population (numbering 267 809 on December 31st 1995). The participation rate also was very good. However, a possible selection bias is difficult to estimate as patients with significant kidney disease, diabetes or other chronic diseases may have been either less or more likely to attend. Our study is limited by the use of serum creatinine to estimate kidney function with the additional concern that the method for measuring serum creatinine was changed twice during the course of the Reykjavik Study. In spite of standardization when instruments were changed, the serum creatinine measurements were significantly lower following the last change of assay instrument, with a difference of 79% (data not shown). Reanalysis of 246 samples from the study showed that this difference remained. However, the results were on the average 2030% higher than the original value, possibly due to evaporation. These variations, therefore, are unexplained although they remain within the known intra-individual, inter-assay and inter-laboratory differences in serum creatinine measurements, which easily can add up to 1520% [23,24]. Furthermore, the bias is towards a lower disease prevalence suggesting that we are not overestimating chronic kidney disease in Iceland. However one should note that only 9.3% of the 10 027 women and 1.8% of the 9229 men in the study came for their first visit after the change in analysis method in 1988. We therefore believe that our results are robust and consistent with similar studies from other continents.
Another limitation of our study is its long duration compared with, for example, the NHANES III, which was completed in 6 years. In our 30 year study period it is possible that the prevalence of kidney failure has changed or perhaps the criteria for some of the underlying diseases, e.g. hypertension. Finally, a direct measurement of GFR in the study population is unavailable, and therefore we cannot compare the estimated GFR to a measured GFR. Thus, we cannot make firm conclusions about the reliability of the eGFR equations. One additional concern with our study is that proteinuria was defined by a single determination of a positive dipstick, which is subject to bias in dipstick reading. Consequently, we chose to present the data on proteinuria separately from the eGFR results. It is also not clear whether these markers of kidney disease, reduced GFR and proteinuria reflect similar disease process or prognosis.
We conclude that the prevalence of CKD in Iceland is high, which is in concordance with the results from other large epidemiological studies. All these studies, including ours, are limited by the inaccuracy of the equations used to estimate GFR, which have been derived from populations with known kidney disease and may not be applicable for use in the general population. These equations also perform differently among sub-populations and therefore are of questionable value in epidemiological studies. However, taken at face value, our results do not suggest that the lower prevalence of ESRD in Iceland compared to the USA is related to a lower CKD prevalence and further studies on disease progression and the fate of CKD patients are needed. Nevertheless, GFR prediction equations might be useful in clinical practice or for studying the progression of kidney disease. A large proportion of subjects with CKD have hypertension or other risk factors for kidney and cardiovascular disease. By diagnosing and treating CKD and associated risk factors early, the progression of kidney failure could possibly be delayed.
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Acknowledgments
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This work was presented in abstract form at the Scandinavian Society of Nephrology Meeting, September 1013, 2003, in Reykjavik, Iceland, and at the American Society of Nephrology Renal Week, November 1217, 2003, in San Diego, CA, USA.
Conflict of interest statement. None declared.
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Received for publication: 5. 7.04
Accepted in revised form: 22. 4.05