Int Urol Nephrol DOI 10.1007/s11255-017-1572-4
NEPHROLOGY – ORIGINAL PAPER
Impact of chronic kidney disease among Korean adults with chronic obstructive pulmonary disease Min Young Kim1 · Sungmin Boo1 · Mijung Yoo1 · Jonghyun Lee1 · Na Ree Kang1
Received: 7 January 2017 / Accepted: 14 March 2017 © Springer Science+Business Media Dordrecht 2017
Abstract Purpose Chronic kidney disease (CKD) is an emerging issue in patients with chronic obstructive pulmonary disease (COPD). In COPD, loss of muscle mass is relatively common finding, and diagnosis of CKD should be based on measured or estimated GFR (Cavailles et al. Eur Respir Rev 22:454–475, 2013; Gosker et al. Am J Clin Nutr 71:1033–1047, 2000; Delanaye and Mariat Nat Rev Nephrol 9:513–522, 2013). We aimed to determine the prevalence and impact of CKD, defined by using chronic kidney disease epidemiology collaboration (CKD-EPI) equation, in COPD patients. Methods This study analyzed data of 3393 adults 40 years of age or older who completed pulmonary function tests in the fifth Korea National Health and Nutritional Examination Survey 2012. Participants with normal lung function (NLF) and COPD were included. CKD was defined as an eGFR <60 mL/min/1.73 m2. Multivariate logistic regression analysis was performed to evaluate the relationship between CKD and COPD. Results Among 3393 participants, 528 (15.6%) were classified as COPD. The prevalence values of participants with eGFR level ≥90, 60–90, and <60 mL/min/1.73 m2 were 54.1, 43.6, and 2.2% in those with NLF and 39.8, 51.5, and 8.7% in those with COPD (p = 0.000). We analyzed the relationship between COPD and all factors that had a statistically significant association with COPD. The significant factors were older age, lower education, BMI, pulmonary tuberculosis, current bronchial asthma, smoking, and CKD.
* Min Young Kim
[email protected] 1
Department of Internal Medicine, Seoul Medical Center, 156 Sinnae‑ro, Jungnang‑gu, Seoul 131‑865, Korea
Conclusions In a Korean population ≥40 years old, the prevalence of participants with COPD is 15.6%. CKD is an independent risk factor for COPD. In addition to CKD, older age, lower education, BMI, pulmonary tuberculosis, current bronchial asthma, and smoking are significantly associated with COPD. Keywords Chronic kidney disease · Chronic obstructive pulmonary disease · Adult · Prevalence · Risk factor
Introduction Chronic obstructive pulmonary disease (COPD) is characterized by fixed airflow limitation resulting from chronic inflammation [4]. The morbidity and mortality rates of patients with COPD are increasing, and COPD is expected to be the third leading cause of mortality worldwide by 2020 [4]. Meanwhile, the main causes of death in patients with COPD are cardiovascular disease and lung cancer [5]. Extrapulmonary comorbidities are common and negatively affect quality of life, exacerbation and mortality in patients with COPD [1]. Common comorbidities include cardiovascular disease, lung cancer, anxiety, depression, osteoporosis, malnutrition, diabetes mellitus, sleep disturbance, anemia, and pulmonary fibrosis [1]. Recently, several studies reported that chronic kidney disease (CKD) might be associated with COPD. Van Gestel et al. showed that the prevalence of COPD was high in patients with CKD who underwent vascular surgery with peripheral arterial disease [6]. Gjerde et al. reported that CKD was identified in 6.9% of patients with COPD [7]. Incalzi et al. founded that the prevalence of CKD was more than 20% in COPD patients ≥65 years [8].
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CKD is known to be an independent risk factor for hospitalization and all-cause mortality [9]. In addition, Incalzi et al. and Ford et al. reported that CKD is associated with high mortality in patients with COPD [10, 11]. Early identification of and intervention for COPD patients with CKD might provide better outcomes for this population. Meanwhile, COPD and CKD share multiple risk factors, such as smoking, aging, diabetes mellitus, and hypertension [4, 9]. There is need to adjust those factors to evaluate the relationship between COPD and CKD. In addition, CKD should be defined according to GFR, not serum creatinine because sarcopenia is relatively prevalent in COPD [1–3, 12]. International guidelines recommend using modification of diet in renal disease (MDRD) and chronic kidney disease epidemiology collaboration (CKD-EPI) equations for estimating GFR [3]. Recent studies have demonstrated that the CKD-EPI equation performed better than the MDRD equation [13]. However, to our knowledge, there have been no studies evaluating CKD using the CKD-EPI equation in patients with COPD. Thus, we aimed to determine the prevalence and impacts of CKD, based on GFR estimated by CKD-EPI equation, in COPD patients using the fifth Korea National Health and Nutritional Examination Survey (KNHANES V-3), carried out in 2012.
Materials and methods Subjects and data collection We used data from KNHANES V-3, a cross-sectional and nationally representative survey conducted by the Division of Chronic Disease Surveillance of the Korean Center for Disease Control and Prevention. KNHANES used a complex, stratified, probability-based study design with multistage and cluster sampling on the basis of the age, gender, and geographic area of registered households. Health interviews and examinations were performed at mobile examination centers. Of the 10,069 candidates, the interview and examination response rate was 75.9%. Spirometry was performed on participants ≥40 years of age using a dry rolling-seal spirometer (Vmax-2130, Sensor-Medics, Yorba Linda, CA, USA) operated by welltrained technicians. Of the 4502 participants ≥40 years of age, 3393 participants completed the pulmonary function test. The test was conducted until the curves of three measurements of pulmonary function were appropriate, up to a maximum of eight maneuvers. The criteria for acceptability and reproducibility followed the guidelines of the American Thoracic Society [14]. Post-bronchodilator testing was not performed. Participants with normal lung function (NLF) and COPD were included in the spirometric examinations. In this study, we excluded participants with
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restrictive lung function of forced expiratory volume in 1 s (FEV1)/forced vital capacity (FVC) ≥0.70 and FVC <80% predicted. Normal lung function was defined as F EV1/ FVC ≥0.70 and FVC ≥80% predicted. COPD was defined as FEV1/FVC <0.70, following the Global Initiative for Chronic Obstructive Lung Disease [15]. The severity of COPD was categorized according to the FEV1 (percentage of predicted) as follows: mild (FEV1 ≥80%), moderate (50% ≤FEV1 <80%), severe (30% ≤FEV1 <50%), and very severe (FEV1 <30%) [15]. Medical histories of comorbidities, level of education, and monthly private income were obtained by KNHANES staff using face-to face interviews, and participants completed self-questionnaires about health behaviors such as smoking and physical activity. Education level was divided into elementary school graduation or lower, middle school graduation, high school graduation, and college graduation or higher. Income level was classified into quartile ranges by dividing monthly household income by the square root of the number of family members. Based on smoking status, participants were categorized into three groups: never smokers, former smokers, and current smokers. Physical activity was divided into three groups: walking (walking for a minimum of 30 min per day on 5 days per week), moderate (moderate physical activity for a minimum of 30 min per day on 5 days per week), and vigorous (vigorous physical activity for a minimum of 20 min per day on 3 days per week). Body mass index (BMI) was calculated by dividing the body weight (kg) by the height squared (m2). Blood pressure was measured three times after the participant had rested for 5 min in a sitting position. We used an average of the second and third systolic blood pressure and diastolic blood pressure for our analysis. Blood samples were taken after fasting for 8 h or more. The concentrations of hemoglobin, glucose, total cholesterol, creatinine, and vitamin D were measured in a qualified central laboratory. A random urine sample was collected, and the albumin-to-creatinine ratio (ACR) was calculated by dividing the urinary albumin concentration (mg/dL) by the urinary creatinine concentration (g/dL). Glomerular filtration rates (eGFRs) were evaluated using the equation with creatinine described by the CKDEPI [16]. Three groups were classified according to eGFR: ≥90, 60–90, and <60 mL/min/1.73 m2. CKD was defined as an eGFR <60 mL/min/1.73 m2. Statistical analyses To represent an unbiased cross-sectional estimate for the Korean population, we analyzed data using a complex sampling design. All estimates were calculated based on sampling weights considering such factors as the sampling rate, response rate, age, and gender. Baseline characteristics are
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described as percentages. Comparisons between variables were made using the Chi-square test. Multivariate logistic regression analysis was performed to evaluate the relationship between CKD and COPD. A p value of <0.05 was considered significant. Statistical analyses were performed using SPSS version 18.0 (SPSS Inc., Chicago, IL, USA). This study protocol was approved by the Institutional Review Board of Korea Centers for Disease Control and Prevention.
Results The prevalence of COPD was 15.6% of the Korean population ≥40 years old. Of 3393 participants with eligible spirometry results, we included 3027 in this study. In total, 16.2% of subjects were 70 years of age and older, 48.9% of subjects were male, and 3.3% had CKD (Table 1). Subjects with COPD were older than those with NLF (p <0.001) and showed a higher proportion of males (p <0.001; Table 1). Mean eGFR was 89.2 ± 13.8 mL/min/1.73 m2 in subjects with NLF and 81.4 ± 14.6 mL/min/1.73 m2 in those with COPD (Fig. 1). Most participants had normal or mildly reduced renal function (Fig. 1). The prevalence of CKD was 8.7% in subjects with COPD, and 2.2% in those with NLF (p <0.001; Table 1). Subjects with eGFR <30 mL/ min/1.73 m2 accounted for 0.2% of subjects with COPD, and 0.2% of those with NLF (data not shown). Of subjects with COPD, 94.6% showed mild or moderate airflow limitation (Fig. 2). Figure 3 shows the prevalence of subjects with CKD according to the severity of COPD. The incidence of CKD was 11.5, 6.5, and 0% in subjects with mild, moderate, and severe or very severe COPD. We analyzed the relationship between COPD and all factors that had a statistically significant association with COPD (Table 2). The significant factors were older age (≥70 vs ≥40, OR 3.266, 95% CI 2.232–4.780), being male (OR 5.014, 95% CI 3.158–7.961), lower education (high school vs ≥university, OR 1.599, 95% CI 1.044–2.448; middle school vs ≥university, OR 2.155, 95% CI 1.373– 3.381; ≤elementary school vs ≥university, OR 3.889, 95% CI 2.475–6.109), lower BMI (18.5–25 vs ≥25 kg/ m2, OR 1.646, 95% CI 1.169–2.318; <18.5 vs ≥25 kg/ m2, OR 2.696, 95% CI 0.959–7.577), pulmonary tuberculosis (OR 3.515, 95% CI 1.735–7.122), current bronchial asthma (OR 8.374, 95% CI 3.588–19.544), smoking (former vs never, OR 1.643, 95% CI 1.087–2.484; current vs never, OR 1.605, 95% CI 1.058–2.436), and CKD (<60 mL/min/1.73 m2 vs ≥90 mL/min/1.73 m2, OR 2.199, 95% CI 1.196–4.043; 60–90 mL/min/1.73 m2 vs ≥90 mL/ min/1.73 m2, OR 0.899, 95% CI 0.637–1.240).
Discussion In this study, we evaluated the prevalence of CKD in subjects with COPD and the relationship between CKD and COPD. In the Korean population ≥40 years old, the prevalence of participants with COPD was 15.6%. In participants with COPD, 8.7% also had CKD. CKD was significantly associated with COPD after adjustment for factors related to COPD. The mechanisms linking COPD and CKD are still not fully understood. Inflammation could play an important role in the pathogenesis of both COPD and CKD. COPD is associated with chronic inflammation of the airways and lung parenchyma [17]. Structural and inflammatory cells in the lung release many inflammatory mediators, including lipids, free radicals, cytokines, chemokines, and growth factors [17]. These mediators result in systemic inflammation, which increases the risk of cardiovascular disease, diabetes, and pneumonia in patients with COPD [17]. Meanwhile, inflammatory markers such as IL-6, TNF receptor-2, and soluble TNF-like weak inducer of apoptosis correlate with a decline in renal function [18]. Amdur et al. examined the association of inflammatory biomarkers and the progression of CKD [19]. Elevated plasma levels of fibrinogen and TNF-α and decreased serum albumin correlated with a loss of renal function in patients with CKD [19]. Thus, systemic inflammation might be caused by a spillover of inflammation from the lung into the circulation, which could affect the development and progression of CKD [20]. Alternatively, COPD and CKD might be consequences of systemic inflammation caused by some other factor. Aging and tobacco exposure are important risk factors for the development and progression of both COPD and CKD [9, 20]. Aging is associated with chronic, low-grade inflammation, resulting in responses that lead to tissue degeneration [21]. IL-6, IL-1β, and TNF-α are the prominent inflammatory mediators shared across age-related pathologies [21]. It is also well known that smoking results in systemic inflammation and negatively affects both the lung and kidney [22]. Hypercapnia in patients with COPD has been associated with renal dysfunction. Anand et al. explained that patients with acute exacerbations of COPD retained salt and water and had neurohormonal activation, and reduction in renal blood flow and GFR [23]. The vasodilator properties of hypercapnia might be related with those findings [23]. Sharkey et al. found that hypoxemia and hypercapnia increased renovascular resistance in 14 patients with acute exacerbations of COPD, suggesting that hypercapnia might have a more dominant role in CKD than hypoxemia [24]. Patients with severe or very
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Table 1 Baseline characteristics in participants with NLF and COPD
Age, years ≥40 ≥70 Gender, male Income ≥75th percentile 50–75th percentile 25–50th percentile <25th percentile Education level ≥University High school Middle school ≤Elementary school Body mass index (kg/m2) ≥25 18.5–25 <18.5 Hypertension Diabetes mellitus Dyslipidemia Cerebrovascular accident Coronary heart disease Pulmonary tuberculosis Current bronchial asthma Depression Cancer Lung Other Smoking Never Former Current Physical activity Vigorous Moderate Walking Systolic blood pressure (mmHg) <140 140–180 ≥180 Diastolic blood pressure (mmHg) <90 90–110 ≥110 Hemoglobin <12 mg/dL Total cholesterol ≥200 mg/dL Fasting glucose ≥126 mg/dL
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Total (N = 3027) (%)
NLF (N = 2499) (%)
COPD (N = 528) (%)
83.8 16.2 48.9
87.6 12.4 43.5
64.2 35.8 76.7
21.7 25.3 25.9 27.1
22.0 25.2 25.1 27.7
19.9 26.1 30.2 23.9
22.3 34.3 14.7 28.8
24.1 35.8 14.3 25.8
13.0 26.6 16.6 43.8
37.3 61.2 1.5 26.3 8.6 13.7 1.7 3.3 4.8 1.9 2.4
38.8 60.0 1.2 23.9 7.4 13.8 1.6 3.1 3.4 1.0 2.6
29.5 67.2 3.2 38.2 14.7 13.3 2.4 4.4 12.1 6.6 1.3
p value 0.000
0.000 0.258
0.000
0.005
0.1 3.8
0.06 3.5
0.000 0.000 0.549 0.339 0.262 0.000 0.000 0.163 0.058
0.4 5.2 0.000
53.8 24.3 22.0
58.7 21.1 20.2
28.8 40.1 31.1
12.8 6.0 36.2
13.3 6.3 35.9
10.2 4.1 37.6
85.7 13.9 0.4
87.0 12.7 0.3
78.9 20.1 1.0
86.1 13.4 0.5 6.7 42.4 7.2
86.2 13.4 0.4 7.2 43.5 6.5
85.7 13.6 0.7 4.1 37.0 10.7
0.101 0.123 0.551 0.000
0.837
0.012 0.033 0.012
Int Urol Nephrol Table 1 continued
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Glomerular filtration rates, mL/min/1.73 m ≥90 60–90 <60 25-Hydroxyvitamin D <20 ng/mL Urine albumin-to-creatinine ratio (mg/g) 30–300 >300
Total (N = 3027) (%)
NLF (N = 2499) (%)
COPD (N = 528) (%)
51.8 44.9 3.3 69.1
54.1 43.6 2.2 71.0
39.8 51.5 8.7 59.4
7.1
6.6
9.7
0.9
0.9
1.0
p value 0.000
0.000 0.086
Non-responder for hypertension, diabetes mellitus, dyslipidemia, cerebrovascular accident, pulmonary tuberculosis, bronchial asthma, depression, and cancer: 1.2% on total; 1.3% on NLF; 0.6% on COPD N number
Fig. 3 Proportion of subjects with CKD according to the pulmonary function Fig. 1 Histogram of eGFR among individuals 40 years of age and older. a Participants with normal lung function and b participants with COPD
Fig. 2 Proportion of participants according to COPD severity
severe COPD are more likely to experience severe exacerbations of COPD [25] which could have poor renal function. In this study, we found CKD in subjects with mild and moderate COPD. This finding might result from the
small number of participants with severe or very severe COPD. Otherwise, because multiple mechanics link with development of CKD, CKD might not be found in participants with severe or very severe COPD. Van Gestel et al. did not find an association between severity of airflow obstruction and CKD, perhaps because patients with severe COPD die before they develop CKD [6]. However, further studies are needed to evaluate the relationship between the severity of COPD and CKD. Prolonged exposure to nephrotoxic medications increases the risk of CKD. Mapel et al. found that patients with COPD used a significantly higher number of prescription pills for cardiovascular agents, antibiotics, and analgesics than agematched and gender-matched controls [26]. In another study, patients with COPD had three times the prevalence of CKD and used approximately 30% more nephrotoxic agents than age-matched and gender-matched controls [27]. Because patients with COPD have a higher prevalence of cardiovascular disease and other comorbidities, medication might explain the higher prevalence of CKD among COPD patients in this study. Unfortunately, we did not explore the medications of participants.
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Table 2 Risk factors for chronic obstructive pulmonary disease among a Korean population (obtained by multivariate logistic regression analysis)
Int Urol Nephrol Odds ratio Age, years ≥40 ≥70 Gender, male Education level ≥University High school Middle school ≤Elementary school Body mass index, kg/m2 ≥25 18.5–25 <18.5 Hypertension Diabetes mellitus Pulmonary tuberculosis Current bronchial asthma Smoking Never Former Current Systolic blood pressure (mmHg) <140 140–180 ≥180 Hemoglobin <12 mg/dL Total cholesterol ≥200 mg/dL Fasting glucose ≥126 mg/dL Glomerular filtration rates, mL/min/1.73 m2 ≥90 60–90 <60 25-Hydroxyvitamin D <20 ng/mL
In this study, COPD was approximately four times more prevalent in participants with lower education than higher education. This finding matches the findings of a population study in Norway [28]. Bakke et al. demonstrated that educational level was an independent predictor of risk for obstructive lung disease independent of smoking and occupational exposure to airborne contaminants [28]. Educational intervention is an important element for the prevention and management of COPD and should focus especially on populations with lower education. Physical activity, anemia, dyslipidemia, and vitamin D levels did not differ significantly between the two groups in this study, although previous studies demonstrated that they each had a the relationship with COPD [1, 4, 29]. Our results might differ because most of our
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95% confidence interval
p value 0.000
1 3.266 5.014
2.232–4.780 3.158–7.961
1 1.599 2.155 3.889
1.044–2.448 1.373–3.381 2.475–6.109
0.000 0.000
0.004 1 1.646 2.696 1.132 1.390 3.515 8.374
1.169–2.318 0.959–7.577 0.869–1.474 0.860–2.244 1.735–7.122 3.588–19.544
1 1.643 1.605
1.087–2.484 1.058–2.436
0.356 0.177 0.001 0.000 0.045
0.446 1 1.294 1.503 0.624 0.911 1.205
0.856–1.958 0.177–12.757 0.378–1.032 0.680–1.220 0.722–2.009
1 0.889 2.199
0.637–1.240 1.196–4.043
0.827
0.608–1.126
0.066 0.530 0.473 0.016
0.226
participants had mild or moderate COPD. Meanwhile, lower BMI showed a significant positive correlation with COPD. Low BMI is the result of loss of fat mass and fatfree mass. In COPD, hypoxia, oxidative stress, disuse of skeletal muscle from a low level of physical activity, use of corticosteroids, nutritional depletion, and systemic inflammation all contribute to a loss of fat mass and fatfree mass [2]. Systemic inflammation has been suggested to elevate the level of the appetite-regulating hormone leptin, resting energy expenditure, and muscle protein catabolism [2]. Albuminuria is a risk marker for progression of renal and cardiovascular disease and is associated with all-cause mortality [9, 30]. Ford et al. reported that increased ACR levels were associated with all-cause mortality in COPD [11]. We did not find a relationship
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between albuminuria and COPD. However, microalbuminuria was more likely to occur in COPD. The significance of albuminuria needs to be better evaluated in COPD. It has been reported previously that CKD is prevalent in patients with COPD. Chen et al. examined the incidence rate of CKD among COPD patients from hospitalization records in Taiwan [31]. COPD and CKD were defined as diagnosis coded by the International Classification of Disease version 9 codes [31]. They found that the incidence rate of CKD in the COPD group was 1.61 times that of the non-COPD group [31]. A study by Gjerde et al. evaluated the prevalence of CKD according to eGFR by the Cockcroft Gault equation among COPD patients who were recruited from health institutions in Norway [7]. The prevalence of CKD was 6.9% in COPD patients [7]. Ford et al. compared mean levels of eGFR by the CKD-EPI equation between adults with COPD and normal lung function using data from the Third National Health and Nutrition Survey [11]. Ford et al. showed that mean levels of eGFR were 87.6 mL/ min/1.73 m2 and 89.6 mL/min/1.73 m2 in adults with COPD and normal lung function. We analyzed the prevalence of CKD among Korean adults using data from KNHANES and used the CKD-EPI equation for estimating GFR. Serum creatinine is an easily measured marker to evaluate renal function in clinical practice. However, CKD must be defined according to GFR, not serum creatinine, in COPD patients with reduced muscle mass [2, 3]. International guidelines recommend using MDRD and CKD-EPI equations for estimating GFR [3]. The CKDEPI creatinine equation outperformed the MDRD study equation, especially at a GFR ≥60 mL/min/1.73 m2, with less bias, improved precision, and greater accuracy [3, 16]. Thus, the CKD-EPI creatinine equation could reduce the possibility of false-positive diagnoses of CKD, which avoids inappropriate reduction in drug dosage and withholding of important diagnostic tests in patients without CKD [16]. Our results confirmed that CKD, defined by using CKD-EPI equation, was significantly associated with COPD. Recently, the CKD-EPI consortium has proposed the CKD-EPI cystatin C equation and the CKDEPI creatinine–cystatin equation [3]. The CKD-EPI creatinine–cystatin equation is more precise than equations using only creatinine or cystatin C [3]. The KDIGO 2012 clinical practice guideline recommended using eGFR based on serum creatinine for initial evaluations and the CKD-EPI creatinine–cystatin equation in circumstances in which eGFR based on serum creatinine is less accurate [3]. However, cystatin is influenced by non-GFR determinants related to COPD, such as tobacco, steroid therapy, and inflammation [3]. Thus, more studies are needed to determine whether the CKD-EPI creatinine–cystatin
equation performs better than other eGFR equations in patients with COPD. Early identification and intervention of patients with CKD are needed to reduce progression to the end-stage renal disease (ESRD) and morbidity and mortality that are associated with CKD [32]. COPD is associated with high prevalence of CKD and high mortality in patients with CKD and ESRD [7, 31, 33, 34]. More frequent monitoring of renal function should be considered in patients with COPD. Meanwhile, there is little information regarding the impact of COPD on progression to the ESRD as well as management for CKD or kidney transplant recipients in patients with COPD. More studies are required to improve the management of patients with COPD and CKD. Notwithstanding, modifiable risk factors, such as smoking, diabetes, hypertension, and albuminuria, should be controlled to prevent disease progression or death [11, 32, 34]. Caution is needed when nephrotoxic medications or radiologic examinations using contrast media are prescribed for patients with COPD. This study had several limitations. First, our crosssectional design could not elucidate casual relationships. However, we included many covariates related to COPD and CKD using data from a nationally representative survey, which could mitigate the drawbacks of the cross-sectional design. Second, we did not exclude airway obstructive diseases such as asthma. The prevalence of asthma-COPD overlap syndrome ranges from 12.1 to 55.2% among patients with COPD and from 13.3 to 61.0% among patients with asthma [35]. The prevalence of COPD might be difficult to evaluate accurately except asthma, but we did analyze data from pre-bronchodilator spirometry. A better understanding of comorbidity could improve the quality of care in patients with COPD. CKD should be recognized as a common comorbidity of COPD, with earlier screening for appropriate management. Acknowledgments We thank the Korea Centers for Disease Control and Prevention for making this survey possible. Compliance with ethical standards Conflict of interest The authors declare that they have no conflict of interest. Ethical approval All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. Informed consent Informed consent was obtained from all individual participants included in the study.
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