Abstract

Background

Many publications report the prevalence of chronic kidney disease (CKD) in the general population. Comparisons across studies are hampered as CKD prevalence estimations are influenced by study population characteristics and laboratory methods.

Methods

For this systematic review, two researchers independently searched PubMed, MEDLINE and EMBASE to identify all original research articles that were published between 1 January 2003 and 1 November 2014 reporting the prevalence of CKD in the European adult general population. Data on study methodology and reporting of CKD prevalence results were independently extracted by two researchers.

Results

We identified 82 eligible publications and included 48 publications of individual studies for the data extraction. There was considerable variation in population sample selection. The majority of studies did not report the sampling frame used, and the response ranged from 10 to 87%. With regard to the assessment of kidney function, 67% used a Jaffe assay, whereas 13% used the enzymatic assay for creatinine determination. Isotope dilution mass spectrometry calibration was used in 29%. The CKD-EPI (52%) and MDRD (75%) equations were most often used to estimate glomerular filtration rate (GFR). CKD was defined as estimated GFR (eGFR) <60 mL/min/1.73 m2 in 92% of studies. Urinary markers of CKD were assessed in 60% of the studies. CKD prevalence was reported by sex and age strata in 54 and 50% of the studies, respectively. In publications with a primary objective of reporting CKD prevalence, 39% reported a 95% confidence interval.

Conclusions

The findings from this systematic review showed considerable variation in methods for sampling the general population and assessment of kidney function across studies reporting CKD prevalence. These results are utilized to provide recommendations to help optimize both the design and the reporting of future CKD prevalence studies, which will enhance comparability of study results.

INTRODUCTION

Chronic kidney disease (CKD) is considered to be a major public health problem [1]. CKD has an important impact both at the patient level, by decreasing the quality of life and life expectancy, and at the population level, by increasing health-care costs and the demand for health-care services.

Since CKD prevalence estimation is central to CKD management and prevention planning at the population level [2], it is not surprising that many publications report CKD prevalence in the general population. It is common research practice to put study results into context by comparing them with previous publications to identify the regional CKD burden, assessing the impact on regional health-care systems and for tailoring preventive strategies to communities. In the case of CKD prevalence, such comparisons are likely hampered as CKD prevalence estimations are influenced by study population characteristics and by the methods used to assess kidney function [3, 4]. To realistically compare CKD prevalence across different population-based studies, methodological factors should be taken into account.

The purpose of this systematic literature review was to (i) identify all studies reporting on CKD prevalence in the European adult general population and (ii) to describe the methodology used in these studies. The findings from this review are utilized to provide recommendations that may help investigators to optimize both the design and the reporting of future CKD prevalence studies, which will enhance comparability of results across studies.

METHODS

Search strategy

A systematic literature search was performed in PubMed, MEDLINE and EMBASE to identify all original research articles reporting the prevalence of CKD in the adult general population. As Kidney Disease Outcomes Quality Initiative (KDOQI) published a guideline on CKD definition [5] in 2002, we included articles published between 1 January 2003, which is one year after the publication of the KDOQI guideline, and 1 November 2014, when our search was last updated. The database-specific search queries are presented in the Supplementary data, Appendix S1. Additionally, the representatives of national kidney foundations, renal registries and expert nephrologists in 39 European countries were asked to provide information on any relevant studies.

Study selection

Publications that presented original research, were designed to select a representative sample of a European adult general population and reported a CKD prevalence estimate were included. We excluded studies that ended subject recruitment prior to 1996 and studies lacking glomerular filtration rate (GFR) estimation based on serum creatinine. Cystatin C-based estimated GFR (eGFR) will lead to higher CKD prevalence estimates than creatinine-based eGFR [6]. For the sake of comparability, we chose not to include publications that solely reported cystatin C-based prevalence estimates. No language restrictions were applied. The literature search was done by two investigators (KB, ED). Any study that was judged relevant on the basis of its title was retrieved in abstract form, and if relevant, in full-text form. Any doubt about eligibility was resolved by discussion with another investigator (VS).

Data extraction

All publications were initially seen by one investigator (KB) and then independently reassessed by two additional investigators (ED for the first half and AK for the second half). For studies with multiple eligible publications, we selected the publication with a primary objective of reporting CKD prevalence or the most recent publication. Publications were assessed on method of population selection, which included the sampling frame (i.e. source used to identify subjects) and the sample design (i.e. the method of sample selection). Additionally, we extracted information on the assessment of kidney function. The extracted data were categorized as follows:

  • Creatinine assay was categorized as enzymatic, Jaffe, modified Jaffe, compensated Jaffe or unclear. The Jaffe method is known to suffer from interference by other substances [7], and multiple adaptations have been implemented to improve method specificity [7]. The compensated and modified Jaffe assays were developed to improve method specificity and minimize susceptibility of interfering substances [7]. The compensated Jaffe method is the use of a manufacturer-specific mathematical compensation [8]. The modified Jaffe assays are modifications of the method such as deproteinization of the sample prior to analysis or the addition of potassium ferricyanide [9].

  • Calibration was categorized as calibrated to the standardized isotope dilution mass spectrometry (IDMS) or calibrated by another method or calibrator.

  • Urinary albumin assay was categorized as dipstick, immunoassay (including both nephelometric and turbidometric immunoassays) or other.

  • The CKD definition was categorized as use of the KDOQI 2002 definitions [5] or use of other definitions. Use of chronicity criterion, i.e. persistence of albuminuria or decreased eGFR for at least 3 months, was assessed.

  • Ethnicity reporting was categorized as ‘yes’ if publication reported collection of ethnicity data and as ‘no’ if ‘ethnicity’ data were not collected or if those were not reported.

Finally, we extracted the following data on presentation of CKD prevalence results: the use of 95% confidence intervals (95%CI), the use of standardization of the prevalence estimate to a reference population and the presentation of results by age group and sex. If CKD prevalence was not the main focus of the publication, the use of 95%CI was rated as not applicable (n/a). The data extraction form is shown in the Supplementary data, Appendix S2.

RESULTS

Study selection

Figure 1 shows the selection process of inclusion and exclusion of publications in a flow chart. We retrieved 2000 individual publications of which only one study was solely identified through contacting national representatives. A total of 1842 publications were excluded based on title or abstract. Twenty-five publications were excluded as the study was not designed to select a representative sample of the general population, 9 studies were excluded as they ended recruitment prior to 1996 and 42 publications were excluded for not presenting a CKD prevalence estimate. Eighty-two publications fulfilled the inclusion criteria. Eighteen studies had multiple publications, highlighting various aspects of CKD (overall 34 publications). Finally, we included 48 publications of individual studies for the data extraction.

Flow chart of publication selection.
FIGURE 1:

Flow chart of publication selection.

Data extraction

Table 1 describes the method of general population sample selection including the response per study. Details on the laboratory assessment of kidney function, the CKD definition used and on the reporting of CKD prevalence are presented in Table 2.

Table 1.

Description of the method of general population sample selection per study

Author (Ref.)Study nameCountryTime periodNumber of subjects, NAge rangeSampling frameSample designResponse, %
Aumann et al. [10]SHIPGermany2001–6283025–88Not specifiedaMultistage sampling69
Bongard et al. [11]MONA LISAFrance2006–7472735–75Electoral rollsAge and sex stratifiedNot given
Browne et al. [12]SLANIreland2007109845+Other (Geo directory)Multistage random sampling: by area and region66
Capuano et al. [13]VIPItaly1998–99 and 2008–9240025–74Electoral rollsAge and sex stratifiedNot given
Christensson et al. [14]GASSweden2001–4281560–93CensusStratified, age, sex and urban/rural location60
Chudek et al. [15]PolSeniorPoland2007–11379365+Not specifiedaNot specifieda32
Cirillo et al. [16]Gubbio Population StudyItalyNot specified457418–95Not specifiedaNot specifiedaNot givena
Codreanu et al. [17]Early Detection and Intervention Program for Chronic Renal and Cardiovascular Disease in the Rep MoldovaMoldova2006–797318–77Not specifiedNot specifiedNot given
De Nicola et al. [18]CARHESItaly2008407735–79Electoral rollsAge and sex stratified45
Delanaye et al. [19]Belgium2008–9199245–75Not specifiedVoluntary natureNot given
Donfrancesco et al. [20]MATISSItaly1993–96292420–79Electoral rollsAge- and sex-stratified random sample60
Formiga et al. [21]OctabaixSpain200932885Not specifiedaNot specifiedaNot given
Fraser et al. [22]HSEEngland2009–10579916+Other (address list)Random two-stage sampleNot givena
Gambaro et al. [23]INCIPEItaly2006362940+General practitioner listRandom sample62
Gianelli et al. [24]InChiantiItaly1998–200067665+Not specifiedMultistage stratified random sampleNot given
Goek et al. [25]KORAGermany1999–1110454–75Not specifiedNot specifiedNot given
Gu et al. [26]FLEMENGHOBelgium2005–1079718–89Not specifiedNot specified78
Guessous et al. [27]Swiss Study on Salt intakeSwitzerland2010–11114515+Other (phone directory)Age- and sex-stratified random sample10
Hallan et al. [28]HUNT 2Norway1995–9765 18120+Not specifiedAll inhabitants70
Hernandez et al. [29]IMAPSpain2007227018–80Not specifiedaRandom sampleNot given
Juutilainen et al. [30]FINRISKFinland2002 and 200711 27725–74CensusAge- and sex-stratified random sample71 in men
74 in women
Lieb et al. [31]MONICA/KORAGermanyNot specified118725–74Not specifiedAge- and sex-stratified random sample71
Meuwese et al. [32]Leiden 85 + studyNetherlands1997–9955885Not specifiedAll in birth cohort87
Nitsch et al. [33]BWHHSUK1999–2001385160–79Not specifiedaRandom sample60
Nitsch et al. [34]SAPALDIA 2Switzerland1991 and 2002631718+Not specifiedaRandom sample73
Otero et al. [35]EPIRCESpain2004–8274620+CensusAge-, sex- and region-stratified random sample43
Pani et al. [36]SardiNIA studyItaly2001–447114–102Not specifiedaNot specifieda56
Pattaro et al. [37]MICROSItaly2002–3119918+Not specifiedaNot specifiedaNot given
Ponte et al. [38]CoLausSwitzerland2003–6592135–75Population registryRandom sample41
Redon et al. [39]PREV-ICTUSSpain2005641960+General practitioner listsRandom sample72
Robles et al. [40]HERMEXSpainNot specified281325–79Other (health-care system database)Age- and sex-stratified random sample83
Roderick et al. [41]MRC Older Age StudyUK1994–9913 17975+General practitioner listPractices stratified by mortality score and deprivation score73
Rothenbacher et al. [42]ActiFE UlmGermany2009–10147165+CensusRandom sample20
Rutkowski et al. [43]PolNefPoland2004–52476n/aOther (address list)Random sample26
Sahin et al. [44]Turkey2005107918–95Not specifiedAge, sex and region stratifiedNot given
Schaeffner et al. [45]BISGermany201157070+Not specifiedaNot specifiedaNot given
Scheven et al. [46]PREVENDThe Netherlands1997–98812128–75Not specifiedAll inhabitants48
Stasevic et al. [47]Kosovo + Metohia200642318+Not specifiedAll inhabitants43
Stengel et al. [48]3CFrance1991–2001870565+Electoral rollsRandom sample37
Suleymanlar et al. [49]CREDITTurkeyNot specified10 05618+Not specifiedAge, sex and region stratifiedNot given
Tavira et al. [50]RENASTURSpain2010–1259255–85Not specifiedRandom sampleNot given
Van Pottelbergh et al. [51]CrystalRussia200961165–91General practitioner listAll registered on list66
Viktorsdottir et al. [52]RHSIceland1967–9619 25633–85Not specifiedAll in birth cohortNot given
Vinhas et al. [53]PREVADIABPortugal2008–9516720–79Other (universal health card)Age, sex and region stratified84
Wasen et al. [54]Finland1998–99124664–100Not specifiedAll residents born ≤193383
Wetmore et al. [55]Iceland2001–3163018+Not specifiedRandom sample71
Zambon et al. [56]ProV.A.Italy1995–97306365+Other (health district registries)Age- and sex-stratified random sample77 in men
64 in women
Zhang et al. [57]ESTHERGermany2000–2980650–74General practitionersAll participants who underwent a general health check-upNot given
Author (Ref.)Study nameCountryTime periodNumber of subjects, NAge rangeSampling frameSample designResponse, %
Aumann et al. [10]SHIPGermany2001–6283025–88Not specifiedaMultistage sampling69
Bongard et al. [11]MONA LISAFrance2006–7472735–75Electoral rollsAge and sex stratifiedNot given
Browne et al. [12]SLANIreland2007109845+Other (Geo directory)Multistage random sampling: by area and region66
Capuano et al. [13]VIPItaly1998–99 and 2008–9240025–74Electoral rollsAge and sex stratifiedNot given
Christensson et al. [14]GASSweden2001–4281560–93CensusStratified, age, sex and urban/rural location60
Chudek et al. [15]PolSeniorPoland2007–11379365+Not specifiedaNot specifieda32
Cirillo et al. [16]Gubbio Population StudyItalyNot specified457418–95Not specifiedaNot specifiedaNot givena
Codreanu et al. [17]Early Detection and Intervention Program for Chronic Renal and Cardiovascular Disease in the Rep MoldovaMoldova2006–797318–77Not specifiedNot specifiedNot given
De Nicola et al. [18]CARHESItaly2008407735–79Electoral rollsAge and sex stratified45
Delanaye et al. [19]Belgium2008–9199245–75Not specifiedVoluntary natureNot given
Donfrancesco et al. [20]MATISSItaly1993–96292420–79Electoral rollsAge- and sex-stratified random sample60
Formiga et al. [21]OctabaixSpain200932885Not specifiedaNot specifiedaNot given
Fraser et al. [22]HSEEngland2009–10579916+Other (address list)Random two-stage sampleNot givena
Gambaro et al. [23]INCIPEItaly2006362940+General practitioner listRandom sample62
Gianelli et al. [24]InChiantiItaly1998–200067665+Not specifiedMultistage stratified random sampleNot given
Goek et al. [25]KORAGermany1999–1110454–75Not specifiedNot specifiedNot given
Gu et al. [26]FLEMENGHOBelgium2005–1079718–89Not specifiedNot specified78
Guessous et al. [27]Swiss Study on Salt intakeSwitzerland2010–11114515+Other (phone directory)Age- and sex-stratified random sample10
Hallan et al. [28]HUNT 2Norway1995–9765 18120+Not specifiedAll inhabitants70
Hernandez et al. [29]IMAPSpain2007227018–80Not specifiedaRandom sampleNot given
Juutilainen et al. [30]FINRISKFinland2002 and 200711 27725–74CensusAge- and sex-stratified random sample71 in men
74 in women
Lieb et al. [31]MONICA/KORAGermanyNot specified118725–74Not specifiedAge- and sex-stratified random sample71
Meuwese et al. [32]Leiden 85 + studyNetherlands1997–9955885Not specifiedAll in birth cohort87
Nitsch et al. [33]BWHHSUK1999–2001385160–79Not specifiedaRandom sample60
Nitsch et al. [34]SAPALDIA 2Switzerland1991 and 2002631718+Not specifiedaRandom sample73
Otero et al. [35]EPIRCESpain2004–8274620+CensusAge-, sex- and region-stratified random sample43
Pani et al. [36]SardiNIA studyItaly2001–447114–102Not specifiedaNot specifieda56
Pattaro et al. [37]MICROSItaly2002–3119918+Not specifiedaNot specifiedaNot given
Ponte et al. [38]CoLausSwitzerland2003–6592135–75Population registryRandom sample41
Redon et al. [39]PREV-ICTUSSpain2005641960+General practitioner listsRandom sample72
Robles et al. [40]HERMEXSpainNot specified281325–79Other (health-care system database)Age- and sex-stratified random sample83
Roderick et al. [41]MRC Older Age StudyUK1994–9913 17975+General practitioner listPractices stratified by mortality score and deprivation score73
Rothenbacher et al. [42]ActiFE UlmGermany2009–10147165+CensusRandom sample20
Rutkowski et al. [43]PolNefPoland2004–52476n/aOther (address list)Random sample26
Sahin et al. [44]Turkey2005107918–95Not specifiedAge, sex and region stratifiedNot given
Schaeffner et al. [45]BISGermany201157070+Not specifiedaNot specifiedaNot given
Scheven et al. [46]PREVENDThe Netherlands1997–98812128–75Not specifiedAll inhabitants48
Stasevic et al. [47]Kosovo + Metohia200642318+Not specifiedAll inhabitants43
Stengel et al. [48]3CFrance1991–2001870565+Electoral rollsRandom sample37
Suleymanlar et al. [49]CREDITTurkeyNot specified10 05618+Not specifiedAge, sex and region stratifiedNot given
Tavira et al. [50]RENASTURSpain2010–1259255–85Not specifiedRandom sampleNot given
Van Pottelbergh et al. [51]CrystalRussia200961165–91General practitioner listAll registered on list66
Viktorsdottir et al. [52]RHSIceland1967–9619 25633–85Not specifiedAll in birth cohortNot given
Vinhas et al. [53]PREVADIABPortugal2008–9516720–79Other (universal health card)Age, sex and region stratified84
Wasen et al. [54]Finland1998–99124664–100Not specifiedAll residents born ≤193383
Wetmore et al. [55]Iceland2001–3163018+Not specifiedRandom sample71
Zambon et al. [56]ProV.A.Italy1995–97306365+Other (health district registries)Age- and sex-stratified random sample77 in men
64 in women
Zhang et al. [57]ESTHERGermany2000–2980650–74General practitionersAll participants who underwent a general health check-upNot given

N, Number of subjects with creatinine measurement; n/a, not applicable.

aAuthors refer to previous publication.

Table 1.

Description of the method of general population sample selection per study

Author (Ref.)Study nameCountryTime periodNumber of subjects, NAge rangeSampling frameSample designResponse, %
Aumann et al. [10]SHIPGermany2001–6283025–88Not specifiedaMultistage sampling69
Bongard et al. [11]MONA LISAFrance2006–7472735–75Electoral rollsAge and sex stratifiedNot given
Browne et al. [12]SLANIreland2007109845+Other (Geo directory)Multistage random sampling: by area and region66
Capuano et al. [13]VIPItaly1998–99 and 2008–9240025–74Electoral rollsAge and sex stratifiedNot given
Christensson et al. [14]GASSweden2001–4281560–93CensusStratified, age, sex and urban/rural location60
Chudek et al. [15]PolSeniorPoland2007–11379365+Not specifiedaNot specifieda32
Cirillo et al. [16]Gubbio Population StudyItalyNot specified457418–95Not specifiedaNot specifiedaNot givena
Codreanu et al. [17]Early Detection and Intervention Program for Chronic Renal and Cardiovascular Disease in the Rep MoldovaMoldova2006–797318–77Not specifiedNot specifiedNot given
De Nicola et al. [18]CARHESItaly2008407735–79Electoral rollsAge and sex stratified45
Delanaye et al. [19]Belgium2008–9199245–75Not specifiedVoluntary natureNot given
Donfrancesco et al. [20]MATISSItaly1993–96292420–79Electoral rollsAge- and sex-stratified random sample60
Formiga et al. [21]OctabaixSpain200932885Not specifiedaNot specifiedaNot given
Fraser et al. [22]HSEEngland2009–10579916+Other (address list)Random two-stage sampleNot givena
Gambaro et al. [23]INCIPEItaly2006362940+General practitioner listRandom sample62
Gianelli et al. [24]InChiantiItaly1998–200067665+Not specifiedMultistage stratified random sampleNot given
Goek et al. [25]KORAGermany1999–1110454–75Not specifiedNot specifiedNot given
Gu et al. [26]FLEMENGHOBelgium2005–1079718–89Not specifiedNot specified78
Guessous et al. [27]Swiss Study on Salt intakeSwitzerland2010–11114515+Other (phone directory)Age- and sex-stratified random sample10
Hallan et al. [28]HUNT 2Norway1995–9765 18120+Not specifiedAll inhabitants70
Hernandez et al. [29]IMAPSpain2007227018–80Not specifiedaRandom sampleNot given
Juutilainen et al. [30]FINRISKFinland2002 and 200711 27725–74CensusAge- and sex-stratified random sample71 in men
74 in women
Lieb et al. [31]MONICA/KORAGermanyNot specified118725–74Not specifiedAge- and sex-stratified random sample71
Meuwese et al. [32]Leiden 85 + studyNetherlands1997–9955885Not specifiedAll in birth cohort87
Nitsch et al. [33]BWHHSUK1999–2001385160–79Not specifiedaRandom sample60
Nitsch et al. [34]SAPALDIA 2Switzerland1991 and 2002631718+Not specifiedaRandom sample73
Otero et al. [35]EPIRCESpain2004–8274620+CensusAge-, sex- and region-stratified random sample43
Pani et al. [36]SardiNIA studyItaly2001–447114–102Not specifiedaNot specifieda56
Pattaro et al. [37]MICROSItaly2002–3119918+Not specifiedaNot specifiedaNot given
Ponte et al. [38]CoLausSwitzerland2003–6592135–75Population registryRandom sample41
Redon et al. [39]PREV-ICTUSSpain2005641960+General practitioner listsRandom sample72
Robles et al. [40]HERMEXSpainNot specified281325–79Other (health-care system database)Age- and sex-stratified random sample83
Roderick et al. [41]MRC Older Age StudyUK1994–9913 17975+General practitioner listPractices stratified by mortality score and deprivation score73
Rothenbacher et al. [42]ActiFE UlmGermany2009–10147165+CensusRandom sample20
Rutkowski et al. [43]PolNefPoland2004–52476n/aOther (address list)Random sample26
Sahin et al. [44]Turkey2005107918–95Not specifiedAge, sex and region stratifiedNot given
Schaeffner et al. [45]BISGermany201157070+Not specifiedaNot specifiedaNot given
Scheven et al. [46]PREVENDThe Netherlands1997–98812128–75Not specifiedAll inhabitants48
Stasevic et al. [47]Kosovo + Metohia200642318+Not specifiedAll inhabitants43
Stengel et al. [48]3CFrance1991–2001870565+Electoral rollsRandom sample37
Suleymanlar et al. [49]CREDITTurkeyNot specified10 05618+Not specifiedAge, sex and region stratifiedNot given
Tavira et al. [50]RENASTURSpain2010–1259255–85Not specifiedRandom sampleNot given
Van Pottelbergh et al. [51]CrystalRussia200961165–91General practitioner listAll registered on list66
Viktorsdottir et al. [52]RHSIceland1967–9619 25633–85Not specifiedAll in birth cohortNot given
Vinhas et al. [53]PREVADIABPortugal2008–9516720–79Other (universal health card)Age, sex and region stratified84
Wasen et al. [54]Finland1998–99124664–100Not specifiedAll residents born ≤193383
Wetmore et al. [55]Iceland2001–3163018+Not specifiedRandom sample71
Zambon et al. [56]ProV.A.Italy1995–97306365+Other (health district registries)Age- and sex-stratified random sample77 in men
64 in women
Zhang et al. [57]ESTHERGermany2000–2980650–74General practitionersAll participants who underwent a general health check-upNot given
Author (Ref.)Study nameCountryTime periodNumber of subjects, NAge rangeSampling frameSample designResponse, %
Aumann et al. [10]SHIPGermany2001–6283025–88Not specifiedaMultistage sampling69
Bongard et al. [11]MONA LISAFrance2006–7472735–75Electoral rollsAge and sex stratifiedNot given
Browne et al. [12]SLANIreland2007109845+Other (Geo directory)Multistage random sampling: by area and region66
Capuano et al. [13]VIPItaly1998–99 and 2008–9240025–74Electoral rollsAge and sex stratifiedNot given
Christensson et al. [14]GASSweden2001–4281560–93CensusStratified, age, sex and urban/rural location60
Chudek et al. [15]PolSeniorPoland2007–11379365+Not specifiedaNot specifieda32
Cirillo et al. [16]Gubbio Population StudyItalyNot specified457418–95Not specifiedaNot specifiedaNot givena
Codreanu et al. [17]Early Detection and Intervention Program for Chronic Renal and Cardiovascular Disease in the Rep MoldovaMoldova2006–797318–77Not specifiedNot specifiedNot given
De Nicola et al. [18]CARHESItaly2008407735–79Electoral rollsAge and sex stratified45
Delanaye et al. [19]Belgium2008–9199245–75Not specifiedVoluntary natureNot given
Donfrancesco et al. [20]MATISSItaly1993–96292420–79Electoral rollsAge- and sex-stratified random sample60
Formiga et al. [21]OctabaixSpain200932885Not specifiedaNot specifiedaNot given
Fraser et al. [22]HSEEngland2009–10579916+Other (address list)Random two-stage sampleNot givena
Gambaro et al. [23]INCIPEItaly2006362940+General practitioner listRandom sample62
Gianelli et al. [24]InChiantiItaly1998–200067665+Not specifiedMultistage stratified random sampleNot given
Goek et al. [25]KORAGermany1999–1110454–75Not specifiedNot specifiedNot given
Gu et al. [26]FLEMENGHOBelgium2005–1079718–89Not specifiedNot specified78
Guessous et al. [27]Swiss Study on Salt intakeSwitzerland2010–11114515+Other (phone directory)Age- and sex-stratified random sample10
Hallan et al. [28]HUNT 2Norway1995–9765 18120+Not specifiedAll inhabitants70
Hernandez et al. [29]IMAPSpain2007227018–80Not specifiedaRandom sampleNot given
Juutilainen et al. [30]FINRISKFinland2002 and 200711 27725–74CensusAge- and sex-stratified random sample71 in men
74 in women
Lieb et al. [31]MONICA/KORAGermanyNot specified118725–74Not specifiedAge- and sex-stratified random sample71
Meuwese et al. [32]Leiden 85 + studyNetherlands1997–9955885Not specifiedAll in birth cohort87
Nitsch et al. [33]BWHHSUK1999–2001385160–79Not specifiedaRandom sample60
Nitsch et al. [34]SAPALDIA 2Switzerland1991 and 2002631718+Not specifiedaRandom sample73
Otero et al. [35]EPIRCESpain2004–8274620+CensusAge-, sex- and region-stratified random sample43
Pani et al. [36]SardiNIA studyItaly2001–447114–102Not specifiedaNot specifieda56
Pattaro et al. [37]MICROSItaly2002–3119918+Not specifiedaNot specifiedaNot given
Ponte et al. [38]CoLausSwitzerland2003–6592135–75Population registryRandom sample41
Redon et al. [39]PREV-ICTUSSpain2005641960+General practitioner listsRandom sample72
Robles et al. [40]HERMEXSpainNot specified281325–79Other (health-care system database)Age- and sex-stratified random sample83
Roderick et al. [41]MRC Older Age StudyUK1994–9913 17975+General practitioner listPractices stratified by mortality score and deprivation score73
Rothenbacher et al. [42]ActiFE UlmGermany2009–10147165+CensusRandom sample20
Rutkowski et al. [43]PolNefPoland2004–52476n/aOther (address list)Random sample26
Sahin et al. [44]Turkey2005107918–95Not specifiedAge, sex and region stratifiedNot given
Schaeffner et al. [45]BISGermany201157070+Not specifiedaNot specifiedaNot given
Scheven et al. [46]PREVENDThe Netherlands1997–98812128–75Not specifiedAll inhabitants48
Stasevic et al. [47]Kosovo + Metohia200642318+Not specifiedAll inhabitants43
Stengel et al. [48]3CFrance1991–2001870565+Electoral rollsRandom sample37
Suleymanlar et al. [49]CREDITTurkeyNot specified10 05618+Not specifiedAge, sex and region stratifiedNot given
Tavira et al. [50]RENASTURSpain2010–1259255–85Not specifiedRandom sampleNot given
Van Pottelbergh et al. [51]CrystalRussia200961165–91General practitioner listAll registered on list66
Viktorsdottir et al. [52]RHSIceland1967–9619 25633–85Not specifiedAll in birth cohortNot given
Vinhas et al. [53]PREVADIABPortugal2008–9516720–79Other (universal health card)Age, sex and region stratified84
Wasen et al. [54]Finland1998–99124664–100Not specifiedAll residents born ≤193383
Wetmore et al. [55]Iceland2001–3163018+Not specifiedRandom sample71
Zambon et al. [56]ProV.A.Italy1995–97306365+Other (health district registries)Age- and sex-stratified random sample77 in men
64 in women
Zhang et al. [57]ESTHERGermany2000–2980650–74General practitionersAll participants who underwent a general health check-upNot given

N, Number of subjects with creatinine measurement; n/a, not applicable.

aAuthors refer to previous publication.

Table 2.

Laboratory assessment of kidney function, CKD definition used and details on the reporting of CKD prevalence per study

Author (Ref.)Creatinine assayIDMSAlbuminuriaCKD definitioneGFR equationEthnicityCIAge and sex standardizedStratified prevalence
Aumann et al. [10]JaffeOthern/a2CKD-EPI + otherYesn/aNoYes: other
Bongard et al. [11]JaffeNon/a2MDRD (old)NoYesYes to national pop.No
Browne et al. [12]Modified JaffeYesOther1 + 2CKD-EPI + new MDRDNoYesYes to national pop.Yes: age, sex and other
Capuano et al. [13]Modified JaffeNon/a2CGNoNoYes to national pop.Yes: age, sex and other
Christensson et al. [14]UnclearOthern/aOtherCKD-EPI, MDRD (old) + CGYesNoNoYes: age and sex
Chudek et al. [15]JaffeUnclearIf dipstick − → immunoassay1 + 2 + 3CKD-EPINoNoNoYes: age, sex and other
Cirillo et al. [16]Modified JaffeNoImmunoassay2MDRD (old)YesYes for N
Not for %
Yes to national pop.Yes: age and sex
Codreanu et al. [17]UnclearNoOther2 + 3MDRD (old)NoNoNoYes: age, sex and other
De Nicola et al. [18]EnzymaticYesImmunoassay1 + 2 + 3CKD-EPINoYesNoNo
Delanaye et al. [19]Compensated JaffeYesn/a2CKD-EPI + new MDRDNoNoNoYes: sex
Donfrancesco et al. [20]EnzymaticYesn/a2CKD-EPINoNoNoYes: sex
Formiga et al. [21]Compensated JaffeNon/a2MDRD (old)NoNoNoNo
Fraser et al. [22]EnzymaticYesNot specified1 + 2 + 3 + otherCKD-EPI + new MDRDYesNoUnclearYes: other
Gambaro et al. [23]Modified JaffeOtherIf dipstick + → immunoassay1 + 2 + 3CKD-EPIYesYesYes to US pop.Yes: age, sex and other
Gianelli et al. [24]Modified JaffeNon/a2MDRD (old) and CGNoNoNoNo
Goek et al. [25]Compensated JaffeUnclearn/a2CKD-EPINon/aNoNo
Gu et al. [26]Modified JaffeUnclearNot specified2CKD-EPI + MDRD (old)NoNoNoNo
Guessous et al. [27]Compensated JaffeUnclearUnclear1CKD-EPIYesn/aNoNo
Hallan et al. [28]JaffeOtherImmunoassay1 + 2 + 3New MDRDYesYesYes to national + US pop.Yes: age, sex and other
Hernandez et al. [29]Not specifiedUnclearNot specified1 + otherCKD-EPIYesn/aNoYes: other
Juutilainen et al. [30]EnzymaticYesn/a2 + otherCKD-EPI + new MDRDNonoNoYes: age and sex
Lieb et al. [31]EnzymaticNoImmunoassay3 + otherMDRD (old)Non/aNoNo
Meuwese et al. [32]JaffeNon/a2CKD-EPI + MDRD (old)Non/aNoNo
Nitsch et al. [33]Modified JaffeOthern/a2MDRD (old)Yesn/aNoYes: other
Nitsch et al. [34]JaffeOthern/a2MDRD (old) and CGYesYesNoYes: age and sex
Otero et al. [35]UnclearUnclearUnclear1 + 2MDRD (old)YesYesYes to national pop.Yes: age, sex and other
Pani et al. [36]Not specifiedOtherNot specified1 + 2 + 3CKD-EPI + new MDRDNoYesNoYes: age and sex
Pattaro et al. [37]EnzymaticYesn/a2CKD-EPI, new MDRD + otherNoYesNoYes: age
Ponte et al. [38]Compensated JaffeYesImmunoassay1 + 2 + 3CKD-EPI + new MDRDYesYesNoYes: age and sex
Redon et al. [39]JaffeYesImmunoassay2CGNon/aNoNo
Robles et al. [40]Modified Jaffe + enzymaticNoDipstick2 + otherCKD-EPI + new MDRDYesYesYes to EU pop.Yes: age and sex
Roderick et al. [41]Modified JaffeYesImmunoassay2 + otherMDRD (old)NoYesNoYes: age and sex
Rothenbacher et al. [42]Modified JaffeNoIf dipstick + → immunoassay1 + 2 + 3CKD-EPI + new MDRDNoNoNoYes: age and sex
Rutkowski et al. [43]Modified JaffeUnclearn/a1 + 2 + 3MDRD (old)NoNoNoNo
Sahin et al. [44]EnzymaticYesNot specified2New MDRDNoNoNoYes: age, sex and other
Schaeffner et al. [45]UnclearUnclearImmunoassay2CKD-EPI + otherYesn/aNoNo
Scheven et al. [46]Modified JaffeUnclearIf dipstick + → immunoassay1 + 2 + 3CKD-EPINon/aNo*No
Stasevic et al. [47]JaffeYesUnclear2 + 3 + otherMDRD (old)NoNoNoNo
Stengel et al. [48]JaffeYesaImmunoassay1 + 2CKD-EPI + new MDRDNoNoNoYes: age and sex
Suleymanlar et al. [49]Not specifiedNoNot specified1 + 2 + 3MDRD (old)YesNoYes to national pop.Yes: age and sex
Tavira et al. [50]Modified JaffeNon/a2MDRD (old)Yesn/aNoNo
Van Pottelbergh et al. [51]Modified JaffeNoDipstick2MDRD (old) and CGNoNoNoYes: age and sex
Viktorsdottir et al. [52]Modified JaffeNon/a1 + 2 + 3MDRD (old) and CGYesNoYes to global pop.Yes: age and sex
Vinhas et al. [53]JaffeUnclearImmunoassay2MDRD (old)NoYesYes to national pop.Yes: age, sex and other
Wasen et al. [54]UnclearYesn/a2 + otherNew MDRD and CGNoNoNoYes per sex
Wetmore et al. [55]JaffeOtherDipstick2New MDRD and CGYesNoNoNo
Zambon et al. [56]Modified JaffeNoImmunoassay2 + otherCKD-EPI and MDRD (old)Yesn/aYes to national pop.No
Zhang et al. [57]Modified JaffeOthern/a2 + otherMDRD (old)NoNoNoYes: age, sex and other
Author (Ref.)Creatinine assayIDMSAlbuminuriaCKD definitioneGFR equationEthnicityCIAge and sex standardizedStratified prevalence
Aumann et al. [10]JaffeOthern/a2CKD-EPI + otherYesn/aNoYes: other
Bongard et al. [11]JaffeNon/a2MDRD (old)NoYesYes to national pop.No
Browne et al. [12]Modified JaffeYesOther1 + 2CKD-EPI + new MDRDNoYesYes to national pop.Yes: age, sex and other
Capuano et al. [13]Modified JaffeNon/a2CGNoNoYes to national pop.Yes: age, sex and other
Christensson et al. [14]UnclearOthern/aOtherCKD-EPI, MDRD (old) + CGYesNoNoYes: age and sex
Chudek et al. [15]JaffeUnclearIf dipstick − → immunoassay1 + 2 + 3CKD-EPINoNoNoYes: age, sex and other
Cirillo et al. [16]Modified JaffeNoImmunoassay2MDRD (old)YesYes for N
Not for %
Yes to national pop.Yes: age and sex
Codreanu et al. [17]UnclearNoOther2 + 3MDRD (old)NoNoNoYes: age, sex and other
De Nicola et al. [18]EnzymaticYesImmunoassay1 + 2 + 3CKD-EPINoYesNoNo
Delanaye et al. [19]Compensated JaffeYesn/a2CKD-EPI + new MDRDNoNoNoYes: sex
Donfrancesco et al. [20]EnzymaticYesn/a2CKD-EPINoNoNoYes: sex
Formiga et al. [21]Compensated JaffeNon/a2MDRD (old)NoNoNoNo
Fraser et al. [22]EnzymaticYesNot specified1 + 2 + 3 + otherCKD-EPI + new MDRDYesNoUnclearYes: other
Gambaro et al. [23]Modified JaffeOtherIf dipstick + → immunoassay1 + 2 + 3CKD-EPIYesYesYes to US pop.Yes: age, sex and other
Gianelli et al. [24]Modified JaffeNon/a2MDRD (old) and CGNoNoNoNo
Goek et al. [25]Compensated JaffeUnclearn/a2CKD-EPINon/aNoNo
Gu et al. [26]Modified JaffeUnclearNot specified2CKD-EPI + MDRD (old)NoNoNoNo
Guessous et al. [27]Compensated JaffeUnclearUnclear1CKD-EPIYesn/aNoNo
Hallan et al. [28]JaffeOtherImmunoassay1 + 2 + 3New MDRDYesYesYes to national + US pop.Yes: age, sex and other
Hernandez et al. [29]Not specifiedUnclearNot specified1 + otherCKD-EPIYesn/aNoYes: other
Juutilainen et al. [30]EnzymaticYesn/a2 + otherCKD-EPI + new MDRDNonoNoYes: age and sex
Lieb et al. [31]EnzymaticNoImmunoassay3 + otherMDRD (old)Non/aNoNo
Meuwese et al. [32]JaffeNon/a2CKD-EPI + MDRD (old)Non/aNoNo
Nitsch et al. [33]Modified JaffeOthern/a2MDRD (old)Yesn/aNoYes: other
Nitsch et al. [34]JaffeOthern/a2MDRD (old) and CGYesYesNoYes: age and sex
Otero et al. [35]UnclearUnclearUnclear1 + 2MDRD (old)YesYesYes to national pop.Yes: age, sex and other
Pani et al. [36]Not specifiedOtherNot specified1 + 2 + 3CKD-EPI + new MDRDNoYesNoYes: age and sex
Pattaro et al. [37]EnzymaticYesn/a2CKD-EPI, new MDRD + otherNoYesNoYes: age
Ponte et al. [38]Compensated JaffeYesImmunoassay1 + 2 + 3CKD-EPI + new MDRDYesYesNoYes: age and sex
Redon et al. [39]JaffeYesImmunoassay2CGNon/aNoNo
Robles et al. [40]Modified Jaffe + enzymaticNoDipstick2 + otherCKD-EPI + new MDRDYesYesYes to EU pop.Yes: age and sex
Roderick et al. [41]Modified JaffeYesImmunoassay2 + otherMDRD (old)NoYesNoYes: age and sex
Rothenbacher et al. [42]Modified JaffeNoIf dipstick + → immunoassay1 + 2 + 3CKD-EPI + new MDRDNoNoNoYes: age and sex
Rutkowski et al. [43]Modified JaffeUnclearn/a1 + 2 + 3MDRD (old)NoNoNoNo
Sahin et al. [44]EnzymaticYesNot specified2New MDRDNoNoNoYes: age, sex and other
Schaeffner et al. [45]UnclearUnclearImmunoassay2CKD-EPI + otherYesn/aNoNo
Scheven et al. [46]Modified JaffeUnclearIf dipstick + → immunoassay1 + 2 + 3CKD-EPINon/aNo*No
Stasevic et al. [47]JaffeYesUnclear2 + 3 + otherMDRD (old)NoNoNoNo
Stengel et al. [48]JaffeYesaImmunoassay1 + 2CKD-EPI + new MDRDNoNoNoYes: age and sex
Suleymanlar et al. [49]Not specifiedNoNot specified1 + 2 + 3MDRD (old)YesNoYes to national pop.Yes: age and sex
Tavira et al. [50]Modified JaffeNon/a2MDRD (old)Yesn/aNoNo
Van Pottelbergh et al. [51]Modified JaffeNoDipstick2MDRD (old) and CGNoNoNoYes: age and sex
Viktorsdottir et al. [52]Modified JaffeNon/a1 + 2 + 3MDRD (old) and CGYesNoYes to global pop.Yes: age and sex
Vinhas et al. [53]JaffeUnclearImmunoassay2MDRD (old)NoYesYes to national pop.Yes: age, sex and other
Wasen et al. [54]UnclearYesn/a2 + otherNew MDRD and CGNoNoNoYes per sex
Wetmore et al. [55]JaffeOtherDipstick2New MDRD and CGYesNoNoNo
Zambon et al. [56]Modified JaffeNoImmunoassay2 + otherCKD-EPI and MDRD (old)Yesn/aYes to national pop.No
Zhang et al. [57]Modified JaffeOthern/a2 + otherMDRD (old)NoNoNoYes: age, sex and other

Albuminuria = method of albuminuria measurement; CKD definition 1 = eGFR below 60 mL/min/1.73 m2 and or the presence of albuminuria >30 mg/g (i.e. CKD Stages 1–5); 2 = eGFR below 60 mL/min/1.73 m2 (i.e. CKD Stages 3–5); 3 = albuminuria >30 mg/g. Ethnicity = ‘yes’ if collection is reported; ‘no’ if not reported or not collected. CI, confidence interval given for prevalence estimate; CG, Cockcroft and Gault equation; n/a, not applicable.

aIn order to standardize creatinine values, 1720 frozen serum samples were remeasured in a single laboratory with an IDMS-traceable enzymatic assay. Hereafter, equations relating the Jaffe and IDMS-traceable creatinine were developed to standardize all baseline values as follows: ScrIDMS = 0.86 × ScrJaffe + 4.40. *Population corrected for sampling design (i.e. oversampling of albuminuria).

Table 2.

Laboratory assessment of kidney function, CKD definition used and details on the reporting of CKD prevalence per study

Author (Ref.)Creatinine assayIDMSAlbuminuriaCKD definitioneGFR equationEthnicityCIAge and sex standardizedStratified prevalence
Aumann et al. [10]JaffeOthern/a2CKD-EPI + otherYesn/aNoYes: other
Bongard et al. [11]JaffeNon/a2MDRD (old)NoYesYes to national pop.No
Browne et al. [12]Modified JaffeYesOther1 + 2CKD-EPI + new MDRDNoYesYes to national pop.Yes: age, sex and other
Capuano et al. [13]Modified JaffeNon/a2CGNoNoYes to national pop.Yes: age, sex and other
Christensson et al. [14]UnclearOthern/aOtherCKD-EPI, MDRD (old) + CGYesNoNoYes: age and sex
Chudek et al. [15]JaffeUnclearIf dipstick − → immunoassay1 + 2 + 3CKD-EPINoNoNoYes: age, sex and other
Cirillo et al. [16]Modified JaffeNoImmunoassay2MDRD (old)YesYes for N
Not for %
Yes to national pop.Yes: age and sex
Codreanu et al. [17]UnclearNoOther2 + 3MDRD (old)NoNoNoYes: age, sex and other
De Nicola et al. [18]EnzymaticYesImmunoassay1 + 2 + 3CKD-EPINoYesNoNo
Delanaye et al. [19]Compensated JaffeYesn/a2CKD-EPI + new MDRDNoNoNoYes: sex
Donfrancesco et al. [20]EnzymaticYesn/a2CKD-EPINoNoNoYes: sex
Formiga et al. [21]Compensated JaffeNon/a2MDRD (old)NoNoNoNo
Fraser et al. [22]EnzymaticYesNot specified1 + 2 + 3 + otherCKD-EPI + new MDRDYesNoUnclearYes: other
Gambaro et al. [23]Modified JaffeOtherIf dipstick + → immunoassay1 + 2 + 3CKD-EPIYesYesYes to US pop.Yes: age, sex and other
Gianelli et al. [24]Modified JaffeNon/a2MDRD (old) and CGNoNoNoNo
Goek et al. [25]Compensated JaffeUnclearn/a2CKD-EPINon/aNoNo
Gu et al. [26]Modified JaffeUnclearNot specified2CKD-EPI + MDRD (old)NoNoNoNo
Guessous et al. [27]Compensated JaffeUnclearUnclear1CKD-EPIYesn/aNoNo
Hallan et al. [28]JaffeOtherImmunoassay1 + 2 + 3New MDRDYesYesYes to national + US pop.Yes: age, sex and other
Hernandez et al. [29]Not specifiedUnclearNot specified1 + otherCKD-EPIYesn/aNoYes: other
Juutilainen et al. [30]EnzymaticYesn/a2 + otherCKD-EPI + new MDRDNonoNoYes: age and sex
Lieb et al. [31]EnzymaticNoImmunoassay3 + otherMDRD (old)Non/aNoNo
Meuwese et al. [32]JaffeNon/a2CKD-EPI + MDRD (old)Non/aNoNo
Nitsch et al. [33]Modified JaffeOthern/a2MDRD (old)Yesn/aNoYes: other
Nitsch et al. [34]JaffeOthern/a2MDRD (old) and CGYesYesNoYes: age and sex
Otero et al. [35]UnclearUnclearUnclear1 + 2MDRD (old)YesYesYes to national pop.Yes: age, sex and other
Pani et al. [36]Not specifiedOtherNot specified1 + 2 + 3CKD-EPI + new MDRDNoYesNoYes: age and sex
Pattaro et al. [37]EnzymaticYesn/a2CKD-EPI, new MDRD + otherNoYesNoYes: age
Ponte et al. [38]Compensated JaffeYesImmunoassay1 + 2 + 3CKD-EPI + new MDRDYesYesNoYes: age and sex
Redon et al. [39]JaffeYesImmunoassay2CGNon/aNoNo
Robles et al. [40]Modified Jaffe + enzymaticNoDipstick2 + otherCKD-EPI + new MDRDYesYesYes to EU pop.Yes: age and sex
Roderick et al. [41]Modified JaffeYesImmunoassay2 + otherMDRD (old)NoYesNoYes: age and sex
Rothenbacher et al. [42]Modified JaffeNoIf dipstick + → immunoassay1 + 2 + 3CKD-EPI + new MDRDNoNoNoYes: age and sex
Rutkowski et al. [43]Modified JaffeUnclearn/a1 + 2 + 3MDRD (old)NoNoNoNo
Sahin et al. [44]EnzymaticYesNot specified2New MDRDNoNoNoYes: age, sex and other
Schaeffner et al. [45]UnclearUnclearImmunoassay2CKD-EPI + otherYesn/aNoNo
Scheven et al. [46]Modified JaffeUnclearIf dipstick + → immunoassay1 + 2 + 3CKD-EPINon/aNo*No
Stasevic et al. [47]JaffeYesUnclear2 + 3 + otherMDRD (old)NoNoNoNo
Stengel et al. [48]JaffeYesaImmunoassay1 + 2CKD-EPI + new MDRDNoNoNoYes: age and sex
Suleymanlar et al. [49]Not specifiedNoNot specified1 + 2 + 3MDRD (old)YesNoYes to national pop.Yes: age and sex
Tavira et al. [50]Modified JaffeNon/a2MDRD (old)Yesn/aNoNo
Van Pottelbergh et al. [51]Modified JaffeNoDipstick2MDRD (old) and CGNoNoNoYes: age and sex
Viktorsdottir et al. [52]Modified JaffeNon/a1 + 2 + 3MDRD (old) and CGYesNoYes to global pop.Yes: age and sex
Vinhas et al. [53]JaffeUnclearImmunoassay2MDRD (old)NoYesYes to national pop.Yes: age, sex and other
Wasen et al. [54]UnclearYesn/a2 + otherNew MDRD and CGNoNoNoYes per sex
Wetmore et al. [55]JaffeOtherDipstick2New MDRD and CGYesNoNoNo
Zambon et al. [56]Modified JaffeNoImmunoassay2 + otherCKD-EPI and MDRD (old)Yesn/aYes to national pop.No
Zhang et al. [57]Modified JaffeOthern/a2 + otherMDRD (old)NoNoNoYes: age, sex and other
Author (Ref.)Creatinine assayIDMSAlbuminuriaCKD definitioneGFR equationEthnicityCIAge and sex standardizedStratified prevalence
Aumann et al. [10]JaffeOthern/a2CKD-EPI + otherYesn/aNoYes: other
Bongard et al. [11]JaffeNon/a2MDRD (old)NoYesYes to national pop.No
Browne et al. [12]Modified JaffeYesOther1 + 2CKD-EPI + new MDRDNoYesYes to national pop.Yes: age, sex and other
Capuano et al. [13]Modified JaffeNon/a2CGNoNoYes to national pop.Yes: age, sex and other
Christensson et al. [14]UnclearOthern/aOtherCKD-EPI, MDRD (old) + CGYesNoNoYes: age and sex
Chudek et al. [15]JaffeUnclearIf dipstick − → immunoassay1 + 2 + 3CKD-EPINoNoNoYes: age, sex and other
Cirillo et al. [16]Modified JaffeNoImmunoassay2MDRD (old)YesYes for N
Not for %
Yes to national pop.Yes: age and sex
Codreanu et al. [17]UnclearNoOther2 + 3MDRD (old)NoNoNoYes: age, sex and other
De Nicola et al. [18]EnzymaticYesImmunoassay1 + 2 + 3CKD-EPINoYesNoNo
Delanaye et al. [19]Compensated JaffeYesn/a2CKD-EPI + new MDRDNoNoNoYes: sex
Donfrancesco et al. [20]EnzymaticYesn/a2CKD-EPINoNoNoYes: sex
Formiga et al. [21]Compensated JaffeNon/a2MDRD (old)NoNoNoNo
Fraser et al. [22]EnzymaticYesNot specified1 + 2 + 3 + otherCKD-EPI + new MDRDYesNoUnclearYes: other
Gambaro et al. [23]Modified JaffeOtherIf dipstick + → immunoassay1 + 2 + 3CKD-EPIYesYesYes to US pop.Yes: age, sex and other
Gianelli et al. [24]Modified JaffeNon/a2MDRD (old) and CGNoNoNoNo
Goek et al. [25]Compensated JaffeUnclearn/a2CKD-EPINon/aNoNo
Gu et al. [26]Modified JaffeUnclearNot specified2CKD-EPI + MDRD (old)NoNoNoNo
Guessous et al. [27]Compensated JaffeUnclearUnclear1CKD-EPIYesn/aNoNo
Hallan et al. [28]JaffeOtherImmunoassay1 + 2 + 3New MDRDYesYesYes to national + US pop.Yes: age, sex and other
Hernandez et al. [29]Not specifiedUnclearNot specified1 + otherCKD-EPIYesn/aNoYes: other
Juutilainen et al. [30]EnzymaticYesn/a2 + otherCKD-EPI + new MDRDNonoNoYes: age and sex
Lieb et al. [31]EnzymaticNoImmunoassay3 + otherMDRD (old)Non/aNoNo
Meuwese et al. [32]JaffeNon/a2CKD-EPI + MDRD (old)Non/aNoNo
Nitsch et al. [33]Modified JaffeOthern/a2MDRD (old)Yesn/aNoYes: other
Nitsch et al. [34]JaffeOthern/a2MDRD (old) and CGYesYesNoYes: age and sex
Otero et al. [35]UnclearUnclearUnclear1 + 2MDRD (old)YesYesYes to national pop.Yes: age, sex and other
Pani et al. [36]Not specifiedOtherNot specified1 + 2 + 3CKD-EPI + new MDRDNoYesNoYes: age and sex
Pattaro et al. [37]EnzymaticYesn/a2CKD-EPI, new MDRD + otherNoYesNoYes: age
Ponte et al. [38]Compensated JaffeYesImmunoassay1 + 2 + 3CKD-EPI + new MDRDYesYesNoYes: age and sex
Redon et al. [39]JaffeYesImmunoassay2CGNon/aNoNo
Robles et al. [40]Modified Jaffe + enzymaticNoDipstick2 + otherCKD-EPI + new MDRDYesYesYes to EU pop.Yes: age and sex
Roderick et al. [41]Modified JaffeYesImmunoassay2 + otherMDRD (old)NoYesNoYes: age and sex
Rothenbacher et al. [42]Modified JaffeNoIf dipstick + → immunoassay1 + 2 + 3CKD-EPI + new MDRDNoNoNoYes: age and sex
Rutkowski et al. [43]Modified JaffeUnclearn/a1 + 2 + 3MDRD (old)NoNoNoNo
Sahin et al. [44]EnzymaticYesNot specified2New MDRDNoNoNoYes: age, sex and other
Schaeffner et al. [45]UnclearUnclearImmunoassay2CKD-EPI + otherYesn/aNoNo
Scheven et al. [46]Modified JaffeUnclearIf dipstick + → immunoassay1 + 2 + 3CKD-EPINon/aNo*No
Stasevic et al. [47]JaffeYesUnclear2 + 3 + otherMDRD (old)NoNoNoNo
Stengel et al. [48]JaffeYesaImmunoassay1 + 2CKD-EPI + new MDRDNoNoNoYes: age and sex
Suleymanlar et al. [49]Not specifiedNoNot specified1 + 2 + 3MDRD (old)YesNoYes to national pop.Yes: age and sex
Tavira et al. [50]Modified JaffeNon/a2MDRD (old)Yesn/aNoNo
Van Pottelbergh et al. [51]Modified JaffeNoDipstick2MDRD (old) and CGNoNoNoYes: age and sex
Viktorsdottir et al. [52]Modified JaffeNon/a1 + 2 + 3MDRD (old) and CGYesNoYes to global pop.Yes: age and sex
Vinhas et al. [53]JaffeUnclearImmunoassay2MDRD (old)NoYesYes to national pop.Yes: age, sex and other
Wasen et al. [54]UnclearYesn/a2 + otherNew MDRD and CGNoNoNoYes per sex
Wetmore et al. [55]JaffeOtherDipstick2New MDRD and CGYesNoNoNo
Zambon et al. [56]Modified JaffeNoImmunoassay2 + otherCKD-EPI and MDRD (old)Yesn/aYes to national pop.No
Zhang et al. [57]Modified JaffeOthern/a2 + otherMDRD (old)NoNoNoYes: age, sex and other

Albuminuria = method of albuminuria measurement; CKD definition 1 = eGFR below 60 mL/min/1.73 m2 and or the presence of albuminuria >30 mg/g (i.e. CKD Stages 1–5); 2 = eGFR below 60 mL/min/1.73 m2 (i.e. CKD Stages 3–5); 3 = albuminuria >30 mg/g. Ethnicity = ‘yes’ if collection is reported; ‘no’ if not reported or not collected. CI, confidence interval given for prevalence estimate; CG, Cockcroft and Gault equation; n/a, not applicable.

aIn order to standardize creatinine values, 1720 frozen serum samples were remeasured in a single laboratory with an IDMS-traceable enzymatic assay. Hereafter, equations relating the Jaffe and IDMS-traceable creatinine were developed to standardize all baseline values as follows: ScrIDMS = 0.86 × ScrJaffe + 4.40. *Population corrected for sampling design (i.e. oversampling of albuminuria).

Population selection

All studies combined described a total of 247 342 subjects. The size of the study population ranged from 328 to 65 181 subjects. Twenty-three studies (48%) included virtually the entire age range of the adult population. The remaining (n = 25; 52%) studies restricted the recruitment of subjects to a higher age range.

Four studies (8%) used census data as the sampling frame to identify eligible study subjects. More than half of the studies (n = 26; 54%) did not report the sampling frame used. Fourteen studies (29%) were designed to select their population by age and sex stratification, and 12 studies (25%) selected a random sample. Ten studies (21%) did not provide details on the sample design, six of which referred to previous publications for more details.

The response was given in 31 studies (65%) and ranged from 10 to 87%. Of the 17 studies that did not report a response, 2 studies referred to a previous publication for details regarding responders and non-responders.

Assessment of kidney function

Serum creatinine was determined by Jaffe assay in the majority of studies (n = 32; 67%) and by enzymatic assay in six (13%) studies. Only few creatinine assays were calibrated to IDMS (n = 14; 29%). Urinary markers for kidney disease were assessed in 29 studies (60%), 15 of which (31%) used immunoassay to detect albuminuria. Seven studies (15%) used dipsticks to identify proteinuria, with confirmation of albuminuria by immunoassay in four studies (8%).

CKD definition

Almost all studies (n = 44; 92%) defined CKD as eGFR below 60 mL/min/1.73 m2. Eighteen studies (38%) reported CKD prevalence defined as eGFR below 60 mL/min/1.73 m2 and/or the presence of albuminuria >30 mg/g, and 15 studies (32%) reported CKD prevalence defined as albuminuria >30 mg/g. Although 10 studies (21%) additionally reported CKD according to another definition, only one study exclusively reported a CKD prevalence not defined by KDOQI.

The Modification of Diet in Renal Disease (MDRD) equation for unstandardized creatinine was used to estimate GFR in 22 studies (46%), and the MDRD equation for standardized creatinine was used in 14 studies (29%). Twenty-five studies (52%) used the CKD Epidemiology Collaboration (CKD-EPI) equation, and nine studies (19%) used the Cockcroft and Gault equation. Even though both the CKD-EPI and MDRD equations include an ethnicity variable, only 18 studies (38%) reported collecting ethnicity data. Eleven studies (23%) did not indicate whether ethnicity data were collected.

Reporting results

CKD prevalence reporting was the main objective in 36 publications, of which 39% reported a 95%CI. An age- and sex-standardized prevalence was reported in 12 studies (25%), of which 9 standardized to their national population. Although two studies standardized their population to the US population, only one study standardized to the European population. The presentation of CKD prevalence by strata was done by 31 studies, and these studies presented the CKD prevalence stratified per risk factor, mostly by age (n = 24; 50%) and by sex (n = 26; 54%).

DISCUSSION

We assessed 48 publications, published between 1 January 2003 and 1 November 2014, reporting CKD prevalence for the adult general population in 20 European countries. The results of this systematic literature review revealed considerable variation in general population sample selection methods and assessment of kidney function across studies. Moreover, often a clear description of the methods used was lacking, and the reporting of CKD prevalence was heterogeneous. These factors may have considerable influence on the prevalence estimates of CKD and need to be taken into account to allow comparison of CKD prevalence across studies.

Population sample selection

Although we restricted our search to studies that were designed to be representative of the general population, we observed great heterogeneity in population sample selection methods. Part of this variation was found in the sampling frame used to identify contact details of eligible subjects. The sampling frame should ideally include the entire target population [58], which in this case is the entire general population. National census or population registry data are ideal for sampling the general population; in principle, these should include all inhabitants of a country or region. However, general population surveys are typically limited to community-dwelling subjects who are physically and mentally capable to participate in such studies. At old age, a substantial proportion of those with age-related chronic diseases such as CKD may no longer fulfill these inclusion criteria, which may lead to substantial underestimation of the true prevalence of such diseases. In such circumstances, depending on the health system or country, general practitioner list- or registry-based approaches might be required to provide more valid estimates of true prevalence.

Additionally, there existed great variation in sample design. For example, some studies first performed stratification of population by age and sex, whereas others invited all inhabitants in the selected region. Both the sampling frame and sample design influence the response and non-response bias [58], which in turn may influence the representativeness of the resulting sample for the general population and consequently of the CKD prevalence estimate. Collecting information on non-responders may help to assess the possibility and likely direction of non-response bias [58].

Assessment of kidney function

Serum creatinine and albuminuria measurements

There was great variation in the laboratory methods used in studies that reported details of those methods, especially in the calibration of serum creatinine. Differences in creatinine assays are important to take into account in CKD prevalence comparisons, as Jaffe methods overestimate serum creatinine and therefore overestimate CKD prevalence [59]. In 2006, IDMS standardization has been implemented to reduce the systematic bias in creatinine determination and to increase inter laboratory comparability [7]. The publications that clearly reported the use of IDMS standardization were only published in 2010 or later.

Ethnicity

In equations used to estimate GFR, like MDRD and CKD-EPI, the variable ‘ethnicity’ is included to adjust for ethnicity-specific differences. Ethnicity may, therefore, influence CKD prevalence estimates; even so, less than half of the publications reported collection of ethnicity data. Since in most European countries the vast majority of the European population is Caucasian, the lack of ethnicity data is unlikely to influence the CKD prevalence of most countries. In the future, however, the proportion of Caucasian subjects in the European population may change, making the collection of ethnicity data more important.

CKD definition

Despite the KDOQI guideline on CKD that was published in 2002 [5] and updated by Kidney Disease Improving Global Outcomes (KDIGO) in 2012 [60], we observed great variation in the definition of CKD, both in eGFR equations used and in cut-off values for both eGFR and albuminuria. For future studies, it is advisable to report CKD as recommended in the updated KDIGO guideline, including six eGFR categories and three albuminuria categories, as this classification allows presentation by mortality and progression risk [61]. The chronicity criterion was never used, mainly because follow-up data on serum creatinine were not collected. In more recent studies, CKD was most commonly defined using the CKD-EPI equation, as recommended by KDOQI [5].

Reporting methods

A clear description of the population sample selection methods and assessment of kidney function may facilitate a more fair comparison of CKD prevalence across studies. Studies should, therefore, preferably report this in detail in the method section of their publication. Unfortunately, many studies did not report the sampling frame used. In addition, information about biological sample collection (e.g. nature of collecting procedure, participants conditions, time between sampling and further processing) and sample storage conditions (duration of storage, thawing cycles, etc.) should also be reported [62].

Reporting results

Another observed difference was the presentation of the results on CKD prevalence estimates. Part of this variation is likely explained by the fact that CKD prevalence was not the main focus of 12 publications. However, even in publications with the main focus on CKD prevalence, there was great variation in reporting. All studies did report unadjusted prevalence estimates, yet they were mostly reported without a 95%CI. The reporting of the 95%CI is necessary as it provides an indication of how much uncertainty there is in the prevalence estimate.

Future studies should preferably report CKD prevalence standardized to the European population to enable international comparison, at least across Europe. In the case of regional prevalence estimates, additional standardization to the national population is required for within-country comparison. This standardization is essential when comparing CKD prevalence estimates from different countries or regions to avoid the influence of differences in national or regional age and sex distributions.

European CKD Burden Consortium

In 2012, the European CKD Burden Consortium was established, including both nephrologists and epidemiologists, to enhance comparability of CKD prevalence across European regions and countries.

Box 1 provides an overview of the methodology used by the European CKD Burden Consortium to compare CKD prevalence results across different general population-based studies in Europe. This methodology facilitates comparability by providing a detailed description of the population selection method and the response of each study to help assess representativeness of the study population sample. Additionally, the figures and tables clearly show the serum creatinine method used (i.e. Jaffe versus enzymatic) and whether IDMS calibration standardization was used.

Box 1:
Recommended methodology for comparison of CKD prevalence results across general population-based studies as used by European CKD Burden Consortium

Recommended toolsDetails
1. General population sampling
 Sampling methodsDescribe:
  • – sampling frame, i.e. source used to identify subjects

  • – sample design, i.e. method of subject selection (e.g. age stratified, random)

 ResponseReport the response in percentages
2. Assessment of kidney function
 Serum creatinine assayDescribe assay used, i.e. Jaffe or enzymatic
 Albuminuria assayDescribe assay used, e.g. immunoassay and dipstick
 IDMS calibration standardizationDescribe if IDMS calibration standardization was used (yes/no)
 CKD definitionUse of the same definition of CKD:
  • CKD Stages 1–5:

  • eGFR < 60mL/min/1.73 m² calculated by the CKD-EPI equation, and/or ACR > 30 mg/g.

CKD Stages 3–5:
  • eGFR < 60mL/min/1.73 m² calculated by CKD-EPI equation.

3. Presentation of results
 CKD prevalence estimate
  • Report:

  • – unadjusted and adjusted CKD prevalence (e.g. standardized to the EU27 population)

  • – 95%CI

 CKD prevalence estimate by strata
  • Report:

  • – stratified by age groups: 20–44, 45–64, 65–74 and 75–84 years

  • – stratified by diabetic, hypertension and obesity status

 Serum creatinine determination
  • Indicate in tables and figures which studies use:

  • – Jaffe or enzymatic assay

  • – IDMS calibration standardization

Recommended toolsDetails
1. General population sampling
 Sampling methodsDescribe:
  • – sampling frame, i.e. source used to identify subjects

  • – sample design, i.e. method of subject selection (e.g. age stratified, random)

 ResponseReport the response in percentages
2. Assessment of kidney function
 Serum creatinine assayDescribe assay used, i.e. Jaffe or enzymatic
 Albuminuria assayDescribe assay used, e.g. immunoassay and dipstick
 IDMS calibration standardizationDescribe if IDMS calibration standardization was used (yes/no)
 CKD definitionUse of the same definition of CKD:
  • CKD Stages 1–5:

  • eGFR < 60mL/min/1.73 m² calculated by the CKD-EPI equation, and/or ACR > 30 mg/g.

CKD Stages 3–5:
  • eGFR < 60mL/min/1.73 m² calculated by CKD-EPI equation.

3. Presentation of results
 CKD prevalence estimate
  • Report:

  • – unadjusted and adjusted CKD prevalence (e.g. standardized to the EU27 population)

  • – 95%CI

 CKD prevalence estimate by strata
  • Report:

  • – stratified by age groups: 20–44, 45–64, 65–74 and 75–84 years

  • – stratified by diabetic, hypertension and obesity status

 Serum creatinine determination
  • Indicate in tables and figures which studies use:

  • – Jaffe or enzymatic assay

  • – IDMS calibration standardization

Recommended toolsDetails
1. General population sampling
 Sampling methodsDescribe:
  • – sampling frame, i.e. source used to identify subjects

  • – sample design, i.e. method of subject selection (e.g. age stratified, random)

 ResponseReport the response in percentages
2. Assessment of kidney function
 Serum creatinine assayDescribe assay used, i.e. Jaffe or enzymatic
 Albuminuria assayDescribe assay used, e.g. immunoassay and dipstick
 IDMS calibration standardizationDescribe if IDMS calibration standardization was used (yes/no)
 CKD definitionUse of the same definition of CKD:
  • CKD Stages 1–5:

  • eGFR < 60mL/min/1.73 m² calculated by the CKD-EPI equation, and/or ACR > 30 mg/g.

CKD Stages 3–5:
  • eGFR < 60mL/min/1.73 m² calculated by CKD-EPI equation.

3. Presentation of results
 CKD prevalence estimate
  • Report:

  • – unadjusted and adjusted CKD prevalence (e.g. standardized to the EU27 population)

  • – 95%CI

 CKD prevalence estimate by strata
  • Report:

  • – stratified by age groups: 20–44, 45–64, 65–74 and 75–84 years

  • – stratified by diabetic, hypertension and obesity status

 Serum creatinine determination
  • Indicate in tables and figures which studies use:

  • – Jaffe or enzymatic assay

  • – IDMS calibration standardization

Recommended toolsDetails
1. General population sampling
 Sampling methodsDescribe:
  • – sampling frame, i.e. source used to identify subjects

  • – sample design, i.e. method of subject selection (e.g. age stratified, random)

 ResponseReport the response in percentages
2. Assessment of kidney function
 Serum creatinine assayDescribe assay used, i.e. Jaffe or enzymatic
 Albuminuria assayDescribe assay used, e.g. immunoassay and dipstick
 IDMS calibration standardizationDescribe if IDMS calibration standardization was used (yes/no)
 CKD definitionUse of the same definition of CKD:
  • CKD Stages 1–5:

  • eGFR < 60mL/min/1.73 m² calculated by the CKD-EPI equation, and/or ACR > 30 mg/g.

CKD Stages 3–5:
  • eGFR < 60mL/min/1.73 m² calculated by CKD-EPI equation.

3. Presentation of results
 CKD prevalence estimate
  • Report:

  • – unadjusted and adjusted CKD prevalence (e.g. standardized to the EU27 population)

  • – 95%CI

 CKD prevalence estimate by strata
  • Report:

  • – stratified by age groups: 20–44, 45–64, 65–74 and 75–84 years

  • – stratified by diabetic, hypertension and obesity status

 Serum creatinine determination
  • Indicate in tables and figures which studies use:

  • – Jaffe or enzymatic assay

  • – IDMS calibration standardization

ACR, urinary albumin to urinary creatinine ratio; IDMS, isotope dilution mass spectrometry.

Furthermore, a uniform definition of CKD based on the KDIGO guideline was established [60]. CKD was defined as the presence of albuminuria >30 mg/g and/or an eGFR of <60 mL/min/1.73 m2 as calculated by the CKD-EPI equation. The chronicity criterion was not applied, for none of the assessed general population-based studies had this available.

The Consortium will additionally harmonize reporting of results in their publications. All CKD prevalence estimates will be presented as unadjusted rates and standardized to the EU27 population of 2005 [63] and include a 95%CI. As the occurrence of CKD is associated with age and not all study populations cover the entire range of the adult population, the CKD prevalence will also be presented for different age ranges, i.e. 20–44, 45–64, 65–74 and 75–84 years. Additionally, the prevalence estimates will be presented with stratification for the presence of the following risk factors: diabetes, hypertension and obesity. This stratification is useful to determine if differences in CKD prevalence are caused by differences in risk factor presence or differences in overall health status of the general population. Whether disparities in CKD prevalence are explained by important risk factors for CKD will guide policy makers to focus on secondary or primary prevention.

Implications

This systematic literature review revealed considerable variation in general population sample selection methods and assessment of kidney function across studies. In addition, a clear description of the methods used was often lacking, and the reporting of CKD prevalence was heterogeneous. The approach of The European CKD Burden Consortium will not eliminate the differences in population selection methods and laboratory assessment of kidney function. However, the recommendations regarding the reporting of both methods and results of CKD prevalence studies may enhance comparability of CKD prevalence results across Europe and even worldwide [64]. Our recommendations may be used by investigators to optimize both the design and the reporting of future CKD prevalence studies.

SUPPLEMENTARY DATA

Supplementary data are available online at http://ndt.oxfordjournals.org.

CONFLICT OF INTEREST STATEMENT

The authors hereby declare that the results presented in this article have not been published previously in whole or part, except in abstract format.

This article was written by K. B., K. J. J. and V. S. S. on behalf of the ERA-EDTA Registry which is an official body of the ERA-EDTA (European Renal Association – European Dialysis and Transplant Association). Dorothea Nitsch has received funding from BMJ informatica to carry out analyses for the Health Quality Improvement Partnership funded National CKD Audit in primary care.

NON-AUTHOR CONTRIBUTORS

FINRISK: Pekka Jousilahti; The Three City (3C) Study: Catherine Helmer, Marie Metzger; MONALISA: Jean Bernard Ruidavets, Vanina Bongard; ActiFE: Wolfgang Koenig, Michael D. Denkinger; ESTHER: Hermann Brenner, Kai-Uwe Saum; SHIP: Matthias Nauck, Sylvia Stracke; SLAN: Ivan Perry, Joseph Eustace; INCIPE: Antonio Lupo; MATISS: Chiara Donfrancesco, Simonetta Palleschi; VIP: Norman Lamaida, Ernesto Capuano; LifeLines: Steef Sinkeler, B.H.R. Wolffenbuttel; PREVEND: Stephan J.L. Bakker; HUNT: Knut Aasarød, Jostein Holmen; PolSenior: Jerzy Chudek, Mossakowska Malgorzata; PREVADIAB: Luis Gardete-Correia, João F. Raposo; EPIRCE: A.L. Martin de Francisco, P. Gayoso Diz; PIVUS: Elisabet Nerpin, Lars Lind; Bus Santé: Murielle Bochud, Jean-Michel Gaspoz; MRC: Astrid Fletcher, Paul Roderick; BELFRAIL + Intego Project: Gijs Van Pottelbergh; URIS: Arjan Van Der Tol; SURDIAGENE: Samy Hadjadj; SKROBB: Olivera Stojceva-Taneva.

REFERENCES

1

Levey
AS
Atkins
R
Coresh
J
et al. .
Chronic kidney disease as a global public health problem: approaches and initiatives—a position statement from Kidney Disease Improving Global Outcomes
.
Kidney Int
2007
;
72
:
247
259

2

Coresh
J
Selvin
E
Stevens
LA
et al. .
Prevalence of chronic kidney disease in the United States
.
JAMA
2007
;
298
:
2038
2047

3

Boutten
A
Bargnoux
AS
Carlier
MC
et al. .
Enzymatic but not compensated Jaffe methods reach the desirable specifications of NKDEP at normal levels of creatinine. Results of the French multicentric evaluation
.
ClinChimActa
2013
;
419
:
132
135

4

Van Biesen
W
Vanholder
R
Veys
N
et al. .
The importance of standardization of creatinine in the implementation of guidelines and recommendations for CKD: implications for CKD management programmes
.
Nephrol Dial Transplant
2006
;
21
:
77
83

5

K/DOQI Clinical Practice Guidelines for Chronic Kidney Disease: Evaluation, Classification, and Stratification. American Journal of Kidney Diseases: The Official Journal of the National Kidney Foundation
.
2002
;
39(February Supplement 1)

6

Shlipak
MG
Matsushita
K
Arnlov
J
et al. .
Cystatin C versus creatinine in determining risk based on kidney function
.
N Engl J Med
2013
;
369
:
932
943

7

Myers
GL
Miller
WG
Coresh
J
et al. .
Recommendations for improving serum creatinine measurement: a report from the Laboratory Working Group of the National Kidney Disease Education Program
.
ClinChem
2006
;
52
:
5
18

8

Delanaye
P
Cavalier
E
Cristol
JP
et al. .
Calibration and precision of serum creatinine and plasma cystatin C measurement: impact on the estimation of glomerular filtration rate
.
JNephrol
2014
;
27
:
467
475

9

Cholongitas
E
Marelli
L
Kerry
A
et al. .
Different methods of creatinine measurement significantly affect MELD scores
.
Liver Transpl Sur
2007
;
13
:
523
529

10

Aumann
N
Baumeister
SE
Werner
A
et al. .
Inverse association of estimated cystatin C- and creatinine-based glomerular filtration rate with left ventricular mass: Results from the Study of Health in Pomerania
.
Int J Cardiol
2013
;
167
:
2786
2791

11

Bongard
V
Dallongeville
J
Arveiler
D
et al. .
Assessment and characteristics of chronic kidney disease in France
.
[French]
.
Ann Cardiol Angeiol (Paris)
2012
;
61
:
239
244

12

Browne
GM
Eustace
JA
Fitzgerald
AP
et al. .
Prevalence of diminished kidney function in a representative sample of middle and older age adults in the Irish population
.
BMC Nephrol
2012
;
13
:
144

13

Capuano
V
Lamaida
N
Borrelli
MI
et al. .
[Chronic kidney disease prevalence and trends (1998–2008) in an area of southern Italy. The data of the VIP project]
.
G Ital Nefrol
2012
;
29
:
445
451

14

Christensson
A
Elmstahl
S
.
Estimation of the age-dependent decline of glomerular filtration rate from formulas based on creatinine and cystatin C in the general elderly population
.
Nephron Clin Prac
2011
;
117
:
c40
c50

15

Chudek
J
Wieczorowska-Tobis
K
Zejda
J
et al. .
The prevalence of chronic kidney disease and its relation to socioeconomic conditions in an elderly Polish population: results from the national population-based study PolSenior
.
Nephrol Dial Transplant
2014
;
29
:
1073
1082

16

Cirillo
M
Laurenzi
M
Mancini
M
et al. .
Low glomerular filtration in the population: Prevalence, associated disorders, and awareness
.
Kidney Int
2006
;
70
:
800
806

17

Codreanu
I
Sali
V
Gaibu
S
et al. .
Prevalence of hypertension and diabetes and coexistence of chronic kidney disease and cardiovascular risk in the population of the Republic of Moldova
.
Int J Hypertens
2012
;
2012: Article ID 951734

18

De Nicola
L
Donfrancesco
C
Minutolo
R
et al. .
Epidemiology of chronic kidney disease in Italy: current state and contribution of the CARHES study
.
Giornale Italiano di Nefrologia: Organo Ufficiale Della Societa Italiana di Nefrologia
2011
;
28
:
401
407

19

Delanaye
P
Cavalier
E
Mariat
C
et al. .
MDRD or CKD-EPI study equations for estimating prevalence of stage 3 CKD in epidemiological studies: which difference? Is this difference relevant?
BMC Nephrol
2010
;
11
:
8

20

Donfrancesco
C
Palleschi
S
Palmieri
L
et al. .
Estimated glomerular filtration rate, all-cause mortality and cardiovascular diseases incidence in a low risk population: the MATISS study
.
[Erratum appears in PLoS One. 2014; 9(1). doi:10.1371/annotation/1f5e18af-4a68–4419-9f3f-7e8bff410b48]
.
PLoS ONE
2013
;
8
:
e78475

21

Formiga
F
Ferrer
A
Cruzado
JM
et al. .
Geriatric assessment and chronic kidney disease in the oldest old: The Octabaix study
.
Eur J Intern Med
2012
;
23
:
534
538

22

Fraser
SD
Roderick
PJ
Aitken
G
et al. .
Chronic kidney disease, albuminuria and socioeconomic status in the Health Surveys for England 2009 and 2010
.
J Public Health (Oxf)
2014
;
36
:
577
586

23

Gambaro
G
Yabarek
T
Graziani
MS
et al. .
Prevalence of CKD in northeastern Italy: results of the INCIPE study and comparison with NHANES
.
Clin J Am Soc Nephrol
2010
;
5
:
1946
1953

24

Giannelli
SV
Graf
CE
Herrmann
FR
et al. .
Natural history of older adults with impaired kidney function: The InCHIANTI study
.
Rejuvenation Res
2011
;
14
:
513
523

25

Goek
ON
Prehn
C
Sekula
P
et al. .
Metabolites associate with kidney function decline and incident chronic kidney disease in the general population
.
Nephrol Dial Transplant
2013
;
28
:
2131
2138

26

Gu
YM
Thijs
L
Liu
YP
et al. .
The urinary proteome as correlate and predictor of renal function in a population study
.
Nephrol Dial Transplant
2014
;
29
:
2260
2268

27

Guessous
I
McClellan
W
Kleinbaum
D
et al. .
Comparisons of serum vitamin D levels, status, and determinants in populations with and without chronic kidney disease not requiring renal dialysis: a 24-hour urine collection population-based study
.
J Ren Nutr
2014
;
24
:
303
312

28

Hallan
SI
Coresh
J
Astor
BC
et al. .
International comparison of the relationship of chronic kidney disease prevalence and ESRD risk
.
J Am Soc Nephrol
2006
;
17
:
2275
2284

29

Hernandez
D
Espejo-Gil
A
Bernal-Lopez
MR
et al. .
Association of HbA1c and cardiovascular and renal disease in an adult Mediterranean population
.
BMC Nephrol
2013
;
14
:
151

30

Juutilainen
A
Kastarinen
H
Antikainen
R
et al. .
Comparison of the MDRD Study and the CKD-EPI Study equations in evaluating trends of estimated kidney function at population level: findings from the National FINRISK study
.
Nephrol Dial Transplant
2012
;
27
:
3210
3217

31

Lieb
W
Mayer
B
Stritzke
J
et al. .
Association of low-grade urinary albumin excretion with left ventricular hypertrophy in the general population: the MONICA/KORA Augsburg echocardiographic substudy
.
Nephrol Dial Transplant
2006
;
21
:
2780
2787

32

Meuwese
CL
Gussekloo
J
de Craen
AJ
et al. .
Thyroid status and renal function in older persons in the general population
.
J Clin Endocrinol Metab
2014
;
99
:
2689
2696

33

Nitsch
D
Lawlor
DA
Patel
R
et al. .
The association of renal impairment with all-cause and cardiovascular disease mortality
.
Nephrol Dial Transplant
2010
;
25
:
1191
1199

34

Nitsch
D
Felber Dietrich
D
von Eckardstein
A
et al. .
Prevalence of renal impairment and its association with cardiovascular risk factors in a general population: results of the Swiss SAPALDIA study
.
Nephrol Dial Transplant
2006
;
21
:
935
944

35

Otero
A
de Francisco
A
Gayoso
P
et al. .
Prevalence of chronic renal disease in Spain: results of the EPIRCE study
.
Nefrologia
2010
;
30
:
78
86

36

Pani
A
Bragg-Gresham
J
Masala
M
et al. .
Prevalence of CKD and its relationship to eGFR-related genetic loci and clinical risk factors in the SardiNIA study cohort
.
J Am Soc Nephrol
2014
;
25
:
1533
1544

37

Pattaro
C
Riegler
P
Stifter
G
et al. .
Estimating the glomerular filtration rate in the general population using different equations: effects on classification and association
.
Nephron
2013
;
123
:
102
111

38

Ponte
B
Pruijm
M
Marques-Vidal
P
et al. .
Determinants and burden of chronic kidney disease in the population-based CoLaus study: A cross-sectional analysis
.
Nephrol Dial Transplant
2013
;
28
:
2329
2339

39

Redon
J
Gil
V
Cea-Calvo
L
et al. .
The impact of occult renal failure on the cardiovascular risk stratification in an elderly population: the PREV-ICTUS study
.
Blood Press
2008
;
17
:
212
219

40

Robles
NR
Felix
FJ
Fernandez-Berges
D
et al. .
Cross-sectional survey of the prevalence of reduced estimated glomerular filtration rate, albuminuria and cardiovascular risk in a native Spanish population
.
J Nephrol
2013
;
26
:
675
682

41

Roderick
PJ
Atkins
RJ
Smeeth
L
et al. .
Detecting chronic kidney disease in older people; what are the implications?
[Erratum appears in Age Ageing. 2009; 38: 638 Note: Flectcher, Astrid E (corrected to Fletcher, Astrid E )]
.
Age Ageing
2008
;
37
:
179
186

42

Rothenbacher
D
Klenk
J
Denkinger
M
et al. .
Prevalence and determinants of chronic kidney disease in community-dwelling elderly by various estimating equations
.
BMC Public Health
2012
;
12
:
343

43

Rutkowski
B
Krol
E
.
Epidemiology of chronic kidney disease in Central and Eastern Europe
.
Blood Purif
2008
;
26
:
381
385

44

Sahin
I
Yildirim
B
Cetin
I
et al. .
Prevalence of chronic kidney disease in the black sea region, Turkey, and investigation of the related factors with chronic kidney disease
.
Ren Fail
2009
;
31
:
920
927

45

Schaeffner
ES
Ebert
N
Delanaye
P
et al. .
Two novel equations to estimate kidney function in persons aged 70 years or older
.
Ann Intern Med
2012
;
157
:
471
481

46

Scheven
L
de Jong
PE
Hillege
HL
et al. .
High-sensitive troponin T and N-terminal pro-B type natriuretic peptide are associated with cardiovascular events despite the cross-sectional association with albuminuria and glomerular filtration rate
.
Eur Heart J
2012
;
33
:
2272
2281

47

Stasevic
Z
Gorgieva
GS
Vasic
S
et al. .
High prevalence of kidney disease in two rural communities in Kosovo and Metohia
.
Ren Fail
2010
;
32
:
541
546

48

Stengel
B
Metzger
M
Froissart
M
et al. .
Epidemiology and prognostic significance of chronic kidney disease in the elderly—the Three-City prospective cohort study
.
Nephrol Dial Transplant
2011
;
26
:
3286
3295

49

Suleymanlar
G
Uta
C
Arinsoy
T
et al. .
A population-based survey of Chronic REnal Disease in Turkey—the CREDIT study
.
Nephrol Dial Transplant
2011
;
26
:
1862
1871

50

Tavira
B
Coto
E
Gomez
J
et al. .
Association between a MYH9 polymorphism (rs3752462) and renal function in the Spanish RENASTUR cohort
.
Gene
2013
;
520
:
73
76

51

Van Pottelbergh
C
Gurina
N
Degryse
J
et al. .
Prevalence of impaired renal function in the elderly in the St. Petersburg District: results of the Crystal study
.
Adv Gerontol
2011
;
24
:
108
113

52

Viktorsdottir
O
Palsson
R
Andresdottir
MB
et al. .
Prevalence of chronic kidney disease based on estimated glomerular filtration rate and proteinuria in Icelandic adults
.
Nephrol Dial Transplant
2005
;
20
:
1799
1807

53

Vinhas
J
Gardete-Correia
L
Boavida
JM
et al. .
Prevalence of chronic kidney disease and associated risk factors, and risk of end-stage renal disease: data from the PREVADIAB study
.
Nephron Clin Prac
2011
;
119
:
c35
c40

54

Wasen
E
Isoaho
R
Mattila
K
et al. .
Estimation of glomerular filtration rate in the elderly: a comparison of creatinine-based formulae with serum cystatin C
.
J Intern Med
2004
;
256
:
70
78

55

Wetmore
JB
Palsson
R
Belmont
JM
et al. .
Discrepancies between creatinine- and cystatin C-based equations: implications for identification of chronic kidney disease in the general population
.
Scand J Urol Nephrol
2010
;
44
:
242
250

56

Zambon
S
Maggi
S
Zanoni
S
et al. .
Association of single measurement of estimated glomerular filtration rate and non-quantitative dipstick proteinuria with all-cause and cardiovascular mortality in the elderly
.
Results From the Progetto Veneto Anziani (Pro.V.A.) Study. Atherosclerosis
2012
;
220
:
201
207

57

Zhang
QL
Koenig
W
Raum
E
et al. .
Epidemiology of chronic kidney disease: results from a population of older adults in Germany
.
Prev Med
2009
;
48
:
122
127

58

Groves
R
Fowler
F
Couper
M
et al. .
Survey Methodology
. 2nd edn.
Hoboken, New Jersey: John Wiley & Sons, Inc.
,
2009

59

Drion
I
Cobbaert
C
Groenier
KH
et al. .
Clinical evaluation of analytical variations in serum creatinine measurements: why laboratories should abandon Jaffe techniques
.
BMC Nephrol
2012
;
13
:
133

60

Kidney Disease: Improving Global Outcomes (KDIGO) CKD Work Group
.
KDIGO 2012 Clinical Practice Guideline for the Evaluation and Management of Chronic Kidney Disease
.
Kidney IntSuppl
2012
;
3
:
1
163

61

Levey
AS
de Jong
PE
Coresh
J
et al. .
The definition, classification, and prognosis of chronic kidney disease: a KDIGO Controversies Conference report
.
Kidney Int
2011
;
80
:
17
28

62

Gallo
V
Egger
M
McCormack
V
et al. .
STrengthening the Reporting of OBservational studies in Epidemiology—Molecular Epidemiology (STROBE-ME): an extension of the STROBE statement
.
PLoS Medicine
2011
;
8
:
e1001117

63

Eurostat: http://epp.eurostat.ec.europa.eu/portal/page/portal/population/data/database Table: Average population by sex and five-year age groups. [Internet].
(15 August 2013, date last accessed
)

64

Bikbov
B
Perico
N
Remuzzi
G
.
Mortality landscape in the global burden of diseases, injuries and risk factors study
.
Eur J Intern Med
2014
;
25
:
1
5

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