Reporting chronic kidney disease in Greenland

ABSTRACT

Background: Chronic kidney disease (CKD) is a major health burden affecting more than 10% of the global population. It is a multifactorial disease with many risk factors attributed lifestyle diseases. The prevalence of CKD in Greenland is unknown; however, the prevalence of risk factors contributing to CKD is increasing.

Objectives: To estimate the prevalence of CKD in Greenland.

Methods: The study was a cross-sectional register-study including all Greenlandic residents aged ≥20 years with serum creatinine analysis within the last 2 years. We identified those with CKD based on eGFR and UACR and those registered with a CKD diagnosis code. Two limitations of the study are possible lack of data completeness and the reliance of a single time point to report CKD.

Results: A total of 2,157 patients were identified with CKD with an age-standardised prevalence of 3.01%. Only 75 patients were registered with a diagnosis code for CKD. Approximately 80% of patients were classified with CKD stages 1–2.

Conclusion: This is the first study reporting CKD in Greenland. We found a lower prevalence of CKD than reported by other studies, and a low number of patients correctly diagnosed with CKD. We call for increased awareness and diagnosis coding of CKD in Greenland.

KEYWORDS:

• CKD
• chronic kidney disease
• epidemiology
• creatinine
• Greenland
• original people

Introduction

Chronic kidney disease (CKD) is a major public health burden affecting more than 10% of the population worldwide [1]⁠. CKD is defined and staged using a combination of estimated glomerular filtration rate (eGFR) and indicators of kidney damage such as albuminuria. It is irreversible and progressive and is associated with increased risk of cardiovascular disease [2–4]. CKD is furthermore estimated as the 12th most frequent cause of death [5]⁠.

Multiple risk factors for CKD exist with many of them being attributed to lifestyle diseases such as hypertension, diabetes, overweight [2], and smoking [6]⁠. Patients, especially in the early stages of CKD, tend to be asymptomatic leading not only to their own [7]⁠ but also to the clinicians’, unawareness of the disease [8]⁠. This is concerning, as timely recognition and treatment can delay progression and reduce complications of CKD [9–12]⁠. Hence, it is important to assess trends in CKD to advise on prevention and healthcare planning.

The reported prevalence of CKD varies among different countries and with the applied methods. Recently, a large study including individual-level data reported the prevalence of measured CKD ranging from 9.8% in Portugal to 5.6% in Belgium with a pooled prevalence of 7.0% [13]. Differences in estimated prevalence may be caused by random variation, methodological and analytical differences across studies or reflect true changes. Importantly, the global prevalence of CKD is projected to increase in the coming years, especially for end-stage kidney disease (ESKD) which is projected to double by 2030 [14]⁠, which could be expected due to a continued increase in diabetes and hypertension as well as an ageing population [15,16]⁠. In Greenland, the prevalence of CKD is unknown. However, as risk factors such as smoking and overweight are major burdens among the Greenland population, the prevalence of CKD is expected to be high.

Therefore, the primary aim of this study was to estimate the age- and gender-specific prevalence of CKD among the adult Greenland population. Second, to characterise patients with CKD, to provide better terms for detection, prevention, and treatment of CKD in Greenland.

Materials and methods

Study design

The study was designed as a cross-sectional study using data extracted from the electronic medical record (EMR) in Greenland.

Setting

Greenland is the largest island in the world, covering an area of more than 2 million km², however, most of the area is uninhabited because of the icecap. The population thus lives along the coastline, distributed in 17 cities and approximately 60 minor settlements. Despite the large distances and remote locations, primary healthcare is provided in all cities and settlements. The healthcare system in Greenland is divided into five healthcare regions, each covering several cities and settlements. Each city has a primary health care centre, whereas the settlements have smaller health care units. Secondary specialised healthcare is provided by Queen Ingrid’s Hospital in Nuuk. Patients with CKD are treated in the local health care centres. In case of severe or complicated CKD, patients are referred to Queen Ingrid’s Hospital in Nuuk or consulted by visiting specialists. Patients with ESKD can be treated in Greenland with peritoneal dialysis or referred for kidney transplantation at Rigshospitalet, Denmark.

Since 2014, all consultations, including hospital, health care centre and settlement consultation, have been registered in the same EMR. Prescription medicine and all services provided by the health care system are free of charge.

Study population and variables

Medical data were extracted from the EMR by 16 November 2021. Extracted data included all Greenlandic residents aged ≥20 years with a serum creatinine analysis performed within the last 2 years. We identified those with CKD based on an estimated glomerular filtration rate (eGFR) <60 ml/min or a combination of eGFR >60 ml/min and urine albumin–creatinine ratio (UACR) >3 mg/mmol.

As background population, the entire population of Greenland as of NaN Invalid Date was used.

Biochemical procedure and eGFR calculation

Venous blood was analysed for lipids, glycosylated haemoglobin (HbA_1c) and creatinine, and urine was analysed for excretion of albumin at The Central Laboratory, Queen Ingrid’s Hospital in Nuuk, using an Architect 8000T from Abbott. The Central Laboratory is a participant in the Danish Quality Control System for Laboratories, DEKS.

eGFR was calculated using the CKD-EPI formula:

Women (P-creatinine ≤62 µmol/L): eGFR = 144 × (P-creatinine/0.7 × 88.4)^−0.329 × 0.993^age

Women (P-creatinine >62 µmol/L): eGFR = 144 × (P-creatinine/0.7 × 88.4)^−1.209 × 0.993^age

Men (P-creatinine ≤80 µmol/L): eGFR = 141 × (P-creatinine/0.9 × 88.4)^−0.411 × 0.993^age

Men (P-creatinine >80 µmol/L): eGFR = 141 × (P-creatinine/0.9 × 88.4)^−1.209 × 0.993^age

Covariates

Information on age, gender, weight, height, body mass index (BMI), blood pressure, smoking status, blood levels of creatinine, cholesterol, glycated haemoglobin (HbA_1c) and urine albumin–creatinine ratio (UACR) was extracted from the EMR. Only the most recent measurements performed within 24 months prior to the date of the data extraction were included in the analysis.

Proportion of patients diagnosed with CKD was identified by presence of at least one of the following International Classification of Diseases 10^th revision (ICD-10) diagnosis codes; DN00–08 (glomerular diseases), DN17–19 (acute kidney failure and chronic kidney disease), DQ61 (cystic kidney disease), DZ49.0 (preparatory care for renal dialysis), DZ94.0 (kidney transplant status), DZ99.2 (dependence on renal dialysis). Prevalence of the comorbidities diabetes and hypertension was evaluated based on the presence of one or more of the following diagnosis codes; T89 (diabetes insulin dependent), T90 (diabetes non-insulin dependent, K85 (elevated blood pressure), K86 (hypertension uncomplicated), and K87 (hypertension complicated) from the International Classification of Primary Care version 2 (ICPC-2) or DE10 (type 1 diabetes mellitus), DE11 (type 2 diabetes mellitus), DE13 (other specified diabetes mellitus), DE14 (unspecified diabetes mellitus), DI10 (essential hypertension) from the ICD-10.

Statistical analysis

Prevalence estimates were calculated using the background population as denominator. All estimates were calculated using 95% confidence intervals (CI) and compared using chi-square tests. Continuous measures are presented as mean ± standard deviation (SD) if normally distributed and median/interquartile range (IQR) if no normal distribution could be assumed. Categorical variables are shown as percentages. Chi-square tests were used to compare frequencies, and normally distributed variables were compared using two tailed t-tests. Wilcoxon test was used to compare means of variables not normally distributed. P-values below 0.05 were considered significant. Linear regression analyses were performed to investigate the association with eGFR and selected risk factors (diabetes diagnosis (1 = yes, 0 = no), hypertension diagnosis (1 = yes, 0 = no), sex (1 = men, 0 = women), daily smoking (1 = yes, 0 = no), age, BMI, systolic/diastolic blood pressure, low-density lipoprotein (LDL) cholesterol, HbA_1c,) to level of eGFR. Initially, univariate regression was conducted to evaluate the association with eGFR together with a single variable (model 1), whereafter multiple regression was conducted in which all variables were included (model 2). Statistical analyses were performed in IBM SPSS Statistics 27 and R studio, version 4.2.

Ethics

The study was approved by the Ethics Committee for Medical Research in Greenland (no. 2021–14).

Results

We initially extracted data on all inhabitants ≥20 years with a measurement of serum-creatinine from within the past 24 months. Here, we found that serum-creatinine was measured in 17,504 inhabitants, corresponding to 42.4% of the Greenland population ≥20 years (41,303). Of these, we identified a total of 2,157 patients (1,153 women and 1,004 men) with CKD based on levels of eGFR and UACR. The patients had a mean age of 61 years, BMI of 31 kg/m², and blood pressure of 135/81 mmHg. Only 75 patients (26 women and 49 men) were registered with a diagnosis code for CKD. Of these, 66 had eGFR <60 ml/min, while the remaining 11 had eGFR >60 ml/min but UACR >3 mg/mmol (data not shown).

Characteristics of patients with CKD in Greenland

Table 1 shows the characteristics of patients with CKD in Greenland based on levels of eGFR and UACR (N = 2,157). Men were significantly older than women (p < 0.001); however, no significant differences were observed in eGFR, UACR, body mass index (BMI), levels of triglyceride and systolic blood pressure. Additionally, men had significantly higher levels of HbA_1c (48.5 mmol/mol vs. 45.6 mmol/mol, p < 0.001), increased prevalence of both diabetes (44.7% vs. 33.9%, p < 0.001) and hypertension (77.4% vs 70.9%, p < 0.001). Women, however, had higher levels of LDL-, high-density lipoprotein (HDL)- and total cholesterol (p < 0.001) and a bigger proportion of women were smoking on a daily basis (p < 0.01).

Table 1. Basic characteristics of patients with CDK according to eGFR and UACR levels (N = 2,157).

	Women		Men			Total
	Mean (SD)	N	Mean (SD)	N	P	Mean (SD)	N
Age (years)	60.3 (13.0)	1,153	62.2 (11.2)	1,004	<0.001	61.2 (12.2)	2,157
Weight (kg)	76.2 (18.5)	958	89.7 (19.6)	872	<0.001	82.6 (20.2)	1,830
Height (cm)	157.4 (7.3)	948	171.3 (8.5)	857	<0.001	164.0 (10.5)	1,805
BMI (kg/m^2)	30.7 (6.9)	948	30.5 (6.0)	857	0.529	30.6 (6.5)	1.805
Blood pressure (mm Hg)
− systolic	134.8 (16.3)	967	135.9 (15.7)	876	0.113	135.3 (16.0)	1,843
− diastolic	79.7 (10.1)	967	83.4 (10.5)	876	<0.001	81.4 (10.4)	1,843
LDL-cholesterol (mmol/l)	2.9 (1.2)	1,036	2.6 (1.2)	916	<0.001	2.7 (1.2)	1,952
HDL-cholesterol (mmol/l)	1.3 (0.5)	1,039	1.1 (0.4)	918	<0.001	1.2 (0.5)	1,957
Total cholesterol (mmol/l)	5.0 (1.2)	1,036	4.6 (1.2)	916	<.001	4.8 (1.2)	1,952
HbA1c (mmol/mol)	45.6 (13.7)	1,140	48.5 (14.9)	943	<0.001	46.9 (14.3)	2,131
eGFR (ml/min)	78.5 (19.8)	1,153	77.3 (21.5)	1,004	0.163	78.0 (20.6)	2,157
UACR (mg/mmol)	17.2 (36.1)	1,119	15.3 (22.5)	943	0.163	16.4 (30.6)	2,054
	Median (IQR)	N	Median (IQR)	N	p	Median (IQR)	N
Creatinine (µmol/l)	70.0 (14)	1,153	87.0 (30.3)	1,004	<0.001	77.0 (25)	2,157
	% (n)	N	% (n)	N		% (n)	N
Smoking on daily basis	46.0 (435)	945	39.0 (332)	851	0.003	42.7 (767)	1,796
Diagnosed with CKD	2.3 (26)	1,153	4.9 (49)	1,004	<0.001	3.5 (75)	2,157
Diagnosed with diabetes	33.9 (391)	1,153	44.7 (449)	1,004	<0.001	38.9 (840)	2,157
Diagnosed with hypertension	70.9 (818)	1,153	77.4 (777)	1,004	<0.001	73.9 (1,595)	2,157

n/N, number of patients/population.

P values below 0.05 are in bold.

Prevalence estimates

Based on the levels of eGFR and UACR, we estimated the age- and gender-specific prevalence of CKD (Table 2). The total estimated prevalence of CKD among adults ≥20 years of age was 5.22%. The prevalence was significantly higher among women compared to men at (5.96% vs. 4.57%, p < 0.001) and increased with advancing age reaching a maximum prevalence of 24.49% in patients aged 90 years or more. The overall age-standardised prevalence of CKD was estimated to be 3.01% (3.51% among women and 2.56% among men).

Table 2. Crude prevalence estimates of patients with CKD according to eGFR and UACR levels (N = 2,157).

	Women	Men	p	Total
	(95% CI) (n/N)	(95% CI) (n/N)		(95% CI) (n/N)
Prevalence (%) among adults ≥20 years of age	5.96 (5.63–6.29) (1,153/19,343)	4.57 (4.30–4.85) (1,004/21,960)	<0.001	5.22 (5.01–5.44) (2,157/41,303)
Prevalence (%) among adults aged 20–79 years	5.067 (5.67–6.0) (1,078/18,996)	4.41 (4.13–4.68) (956/21,688)	<0.001	5.00 (4.79–5.21) (2,034/40,684)
WHO age-standardised prevalence (%)	3.51	2.56		3.01
Prevalence (%) in age groups
20–29 years	0.48 (0.27–0.69) (20/4,148)	0.16 (0.04–0.28) (7/4,279)	.090	0.32 (0.20–0.44) (27/8,427)
30–39 years	1.58 (1.20–1.95) (67/4,253)	0.66 (0.42–0.89) (30/4,573)	.001	1.10 (0.88–1.32) (97/8,826)
40–49 years	3.83 (3.12–4.53) (109/2,848)	2.39 (1.88–2.91) (82/3,424)	<.001	3.05 (2.62–3.47) (191/6,272)
50–59 years	8.45 (7.59–9.32) (337/3,987)	5.74 (5.07–6.41) (269/4,686)	<.001	6.99 (6.45–7.52) (606/8,673)
60–69 years	12.92 (11.65–14.18) (350/2,710)	10.41 (9.39–11.43) (360/3,458)	.002	11.51 (10.71–12.31) (710/6,168)
70–79 years	18.57 (16.22–20.92) (195/1,050)	16.40 (14.37–18.44) (208/1,268)	.170	17.39 (15.84–18.93) (403/2,318)
80–89 years	22.04 (17.38–26.70) (67/304)	17.19 (12.57–22.81) (44/256)	.151	19.82 (16.52–23.12) (111/560)
90+	24.24 (9.62–38.86) (8/33)	25.00 (3.78–46.22) (4/16)	.954	24.49 (12.45–36.53) (12/49)

n/N, number of patients/population.

P values below 0.05 are in bold.

Stages of CKD in Greenland

CKD is categorised from stages 1 to 5 according to the levels of eGFR, and for stages 1 and 2, UACR must be >3 mg/mmol (Table 3). Stages 1–3 are considered the early stages of CKD, while stages 4–5 are the late stages, of which stage 5 is referred to as the end stage.

Table 3. Distribution of CKD stages in the adult population (N = 2,157).

CKD stages		Women, % (n) (N = 1,153)	Men, % (n) (N = 1,004)	p	Total (N = 2,157)
Stage 1	eGFR >90 ml/min + UACR >3 mg/mmol	28.27 (326)	34.06 (342)	0.004	31.00 (668)
Stage 2	eGFR 60–89 ml/min + UACR >3 mg/mmol	54.47 (628)	42.83 (430)	<0.001	49.05 (1,058)
Stage 3A	eGFR 45–59 ml/min	10.49 (121)	14.54 (146)	0.004	12.38 (267)
Stage 3B	eGFR 30–44 ml/min	4.77 (55)	5.58 (56)	0.397	5.15 (111)
Stage 4	eGFR 15–29 ml/min	1.73 (20)	2.59 (26)	0.170	2.13 (46)
Stage 5	eGFR <15 ml/min	0.26 (3)	0.40 (4)	0.573	0.32 (7)

Of the 2,157 patients with CKD based on eGFR and UACR, 80% belonged to stages 1 and 2. This corresponds to 4.2% of the Greenland population. The prevalence of CKD stages 3–5 was 1.04% among the Greenland population. The prevalence of patients treated with haemodialysis is not formally registered; however, on request, information from the consulting nephrologist at the Department of Internal Medicine suggests that between 15 and 18 patients are treated with haemodialysis.

The majority of patients (49.05%) were in stage 2, with women being more prevalent than men (54.47% vs. 42.83%, p < 0.001), whereas men were more prevalent than women in stages 1 and 3 (p <0.01).

Contribution of risk factors to eGFR

Univariate regression analyses were conducted to evaluate the relationship between each individual risk factor and the change in eGFR (Table 4). The results demonstrated significant negative associations between eGFR and diagnosed hypertension, diagnosed diabetes, male sex, advanced age, and increased levels of HbA_1c.

Table 4. Risk factor association with eGFR based on individuals with creatinine measurement within 2 years (N = 17,504).

	Model 1: Univariate regression (eGFR + single variable)		Model 2: Multiple regression (all variables)
Independent variables	Estimate	p-value	Estimate	p-value
- Categorical variables
Diabetes diagnosis (1 = yes, 0 = no)	−12.88	<0.001	0.24	0.676
Hypertension diagnosis (1 = yes, 0 = no)	−16.60	<0.001	−3.47	<0.001
Sex (1 = male, 0 = female)	−2.42	<0.001	3.12	<0.001
Smoking daily (1 = yes, 0 = no)	4.02	<0.001	1.37	0.002
- Numerical variables
Age (years)	−0.81	<0.001	−0.77	<0.001
HbA1c (mmol/mol)	−0.43	<0.001	−0.05	0.014
LDL cholesterol (mmol/l)	0.18	0.289	−1.27	<0.001
BMI	0.05	0.095	0.08	0.011
Blood pressure systolic (mmHg)	−0.12	<0.001	0.02	0.277
Blood pressure diastolic (mmHg)	0.21	<0.001	0.07	0.011

Multiple regression analysis including all risk factors illustrated that diagnosed hypertension, advanced age, HbA1c, and LDL cholesterol were found to be significant predictors of a decline in eGFR. Notably, when accounting for other factors in the multiple regression, diagnosed diabetes was not shown to be significantly associated with a decline in eGFR, while male sex seemed to be associated with an increase in eGFR.

We assessed for collinearity using variable inflation factor (VIF) and found that all predictors had a VIF below 2, indicating that collinearity between predictors is not an issue.

Lastly, we compared how being normoglycemic, prediabetic or diabetic as well as having a diagnosis of hypertension or not influenced eGFR (Table 5). This demonstrates a decline in eGFR in hypertensive, diabetic and prediabetic patients (p < 0.001).

Table 5. The significance of HbA1c and diagnosis of diabetes/hypertension on eGFR and UACR levels (N = 17,504).

	Diabetes and subgroups						Hypertension
	Normoglycemic HbA1c <42 mmol/mol, no diabetes diagnosis (n = 7,611)	Prediabetic HbA1c: 42–47 mmol/mol, no diabetes diagnosis (n = 2,669)	Diabetes diagnosis (n = 1,751)	p (normorglycemia vs. prediabetes)	p (normoglycemia vs. diabetes)	p (prediabetes vs. diabetes)	No hypertension (n = 11,388)	Hypertension diagnosis (n = 6,116)	p
eGFR (ml/min), mean (SD)	93.0 (19.0)	84.0 (16.9)	79.2 (19.2)	<0.001	<0.001	<0.001	96.6 (17.6)	80.0 (18.7)	<0.001

n = number of patients, N = population. P values below 0.05 are in bold.

Discussion

The age-standardised prevalence of CKD was found to be 3.01%, and higher among women compared to men. The estimated prevalence in Greenland is thus approximately one-third of the global age-standardised prevalence estimated at 10% [1,17]⁠.

To our knowledge, this is the first study investigating the prevalence of CKD in Greenland. The practice of registering patients with a diagnosis code has been limited in Greenland, thus only a fraction of the patients with CKD were registered with a diagnosis. The same is seen for other diseases in Greenland such as hypertension [18], but also suggests a lack of clinical awareness of CKD, as seen in other countries [13]. ⁠

Our findings suggest a lower prevalence of CKD in Greenland than on global level. This might represent an actual lower prevalence in Greenland, but it might also, however, be a question of different methodologies. While some studies have included a representative sample of patients, our estimation is based on all patients with a measurement of serum creatinine regardless of the cause leading to the measurement, socioeconomic status and other factors. As mentioned earlier, many residents live in smaller settlements with irregular services regarding both healthcare and transportation to larger settlements. It is likely that these citizens are utilising the health care system to a lesser degree than city dwellers [19,20]⁠, resulting in a lower prevalence.

When looking at the prevalence among other indigenous people, the results vary. While the prevalence of both albuminuria and CKD stages 3–5 among Alaska Eskimos was found to be lower than reported for the US general population [21], others report of a two-fold higher prevalence of CKD⁠ among indigenous Canadians compared to the general population [22].

In addition to the increased life expectancy compared to half a century ago [23], the prevalence of chronic diseases among indigenous people has been augmented by a rising prevalence of obesity and hypertension [24]. This is also the case in Greenland, where the proportion of obese inhabitants (BMI ≥ 30 kg/m²) has increased from 12% in 1993 to nearly a third of the population in 2018 [25], and the proportion of hypertension has increased from 11.4% in 2012 to 17.5% in 2021 [18,26]. Also, the prevalence of diabetes has increased in Greenland over the past half a decade [27]. In this study, we found that the hypertension and elevated levels of HbA_1c, both of which are more prevalent among men than women, along with advanced age, were all associated with a decline in kidney function. Further analysis showed that hypertension, prediabetes, and diabetes, independently of other risk factors, were all associated with a significantly decreased eGFR, suggesting that these groups are more susceptible to CKD and could possibly benefit from increased monitoring.

Inversely, we found a positive association between daily smoking and eGFR. Currently, there is no consensus on whether smoking serves as an independent risk factor for CKD or if it merely works as a catalysator in the presence of comorbidities such as hypertension and diabetes [6,28]. These results should be interpreted in consideration of the methodology applied in this study. The broad inclusion criteria might have introduced a heterogeneous mix of patients into our study sample, possibly leading to observed associations that differ from studies with more stringent selection criteria. Furthermore, the proportion of daily smokers in our CKD cohort is lower than what is observed in the general population [25]⁠. This discrepancy might suggest that daily smokers with CKD could be underrepresented in our sample, potentially skewing the observed association between smoking and eGFR.

Although the higher prevalence of CKD among women is in line with other studies [29–32], we believe it is due to an overrepresentation of women with CKD stage 2, while the prevalence of all other CKD stages is slightly higher among men. Men are believed to have a higher prevalence of late-stage CKD, and therefore progressing faster to ESKD than women [33,34]⁠. We did not observe similar results but did, however, notice that men were older and had a higher prevalence of diabetes and hypertension compared to women, all of which are known risk factors for CKD and for its progression [35,36].

Strengths and limitations

The data in this study were extracted from the national EMR covering the entire adult population in Greenland. However, since we have only retrieved data on those with a serum creatinine measurement within the last 24 months, we might have excluded patients with CKD, who have not had a serum creatinine measurement within that time frame, causing us to underestimate the true prevalence of CKD. Additionally, the methodology adopted where we included all patients based on serum creatinine measurements, irrespective of the underlying cause, might not provide us with a true representation of the Greenlandic population thus skewing our data, although we have included 42.4% of the Greenlandic population aged 20 years or more.

Since January 2021, it has been mandatory for medical doctors in primary care in Nuuk to register all contacts in primary healthcare with an ICPC-2 code. However, this does not apply for medical doctors outside of Nuuk, which might explain the low number of patients registered with CKD in the EMR in multiple ways: First, we do not expect all patients with CKD to have visited the primary healthcare in Nuuk within the timeframe of 24 months. Second, patients with CKD, who did visit the primary healthcare in Nuuk due to other issues, would not necessarily have been registered with CKD. Third, patients outside Nuuk only rarely get registered with ICPC-2 codes in the EMR.

The lack of registration of diagnosis codes could also apply to registration of comorbidities, such as diabetes and hypertension, as well as current smoking status. The relationship between CKD and these risk factors might therefore also have been underestimated.

In this study, we calculated the eGFR using the CKD-EPI creatinine equation. This equation has not been validated among the Inuit population. However, it has been validated in several Asian populations including the Chinese [37–39], who the Inuit population is closely related to [40]⁠.

Lastly, this data used in this study relies on a single time point to define elevated UACR or decreased eGFR, thereby excluding the ability to examine the definition of chronicity according to Kidney Disease: Improving Global Outcomes (KDIGO), which includes persistence for at least 3 months [12]⁠. In this regard, we thereby potentially overestimate the prevalence of CKD.

Conclusion

In consideration to the limitations of this study, we report an age-standardised prevalence of CKD of 3.01% in Greenland with a higher prevalence among women than men. The estimated prevalence was lower than reported by other international studies. Comorbidities including diabetes and hypertension were highly prevalent in patients with CKD. This was, however, expected, as both hypertension and diabetes are established risk factors of CKD. The prevalence of comorbidities was higher among men compared to women. Unfortunately, registration with ICPC-2 codes in PHC has only been mandatory since January 2021, thus potentially decreasing the quality of our data. Ultimately, we call for increased awareness of CKD in Greenland and for the ICPC-2 registration of patients upon visiting the PHC.

Research data

The data used to support the findings of this study are included within the article.

Disclosure statement

This study was partly financed by the Novo Nordisk Foundation under grant NNF20SA0064190.

Additional information

Funding

The work was supported by the Novo Nordisk Fonden [NNF20SA0064190].