J Nephrol DOI 10.1007/s40620-014-0077-9
ORIGINAL ARTICLE
A longitudinal assessment of the natural rate of decline in renal function with age Eytan Cohen • Yuval Nardi • Irit Krause • Elad Goldberg • Gai Milo • Moshe Garty • Ilan Krause
Received: 22 October 2013 / Accepted: 28 February 2014 Ó Italian Society of Nephrology 2014
Abstract Background Cross-sectional studies have long suggested that renal function declines with age. Longitudinal studies regarding this issue are limited. Methods We retrospectively analyzed a database of subjects attending a screening center in Israel between the years 2000–2012. Only subjects with normal estimated glomerular filtration rate (eGFR) were included. eGFR was assessed consequently at 5 or more yearly visits. The rate
E. Cohen (&) E. Goldberg I. Krause Department of Medicine F—Recanati, Rabin Medical Center (Beilinson Campus), 49100 Petah Tikva, Israel e-mail: [email protected] E. Cohen Clinical Pharmacology Unit, Rabin Medical Center (Beilinson Campus), Petah Tikva, Israel E. Cohen I. Krause E. Goldberg G. Milo M. Garty I. Krause Sackler Faculty of Medicine, Tel Aviv University, Ramat Aviv, Israel Y. Nardi Faculty of Industrial Engineering and Management, Technion—Israel Institute of Technology, Haifa, Israel I. Krause Nephrology Institute and Dialysis Unit, Schneider’s Children Medical Center of Israel Petah Tikva, Petah Tikva, Israel G. Milo Nephrology Unit, Rabin Medical Center (Beilinson Campus), Petah Tikva, Israel M. Garty Recanati Center for Preventive Medicine, Rabin Medical Center (Beilinson Campus), Petah Tikva, Israel
of decline in GFR with age was assessed in healthy subjects and in subjects with comorbidities. Results The cohort included 2693 healthy subjects and 230 subjects with different comorbidities. Mean (±standard error) annual rate of decline in eGFR in healthy subjects was 0.97 ± 0.02 ml/min/year/1.73 m2. This decline increased significantly from 0.82 ± 0.22 in agegroup 20–30 years to 0.84 ± 0.08, 1.07 ± 0.08 and 1.15 ± 0.12 ml/min/year/1.73 m2 in age groups 31–40, 41–50 and 50 years and older respectively (p \ 0.001). No correlation was found between the annual decline in eGFR and body mass index. In subjects with hypertension, diabetes mellitus, impaired fasting glucose or combined comorbidity the decline in eGFR was 1.12 ± 0.12, 0.77 ± 0.16, 0.85 ± 0.17, and 1.18 ± 0.26 ml/min/year/ 1.73 m2 respectively. Conclusions This large longitudinal study provides new data on the decrease in eGFR with age. Accurate prediction of the natural rate of GFR decline might be used to distinguish between normally aging kidneys and those with chronic disease. This approach could avoid unnecessary diagnostic procedures in the former and facilitate appropriate treatment in the latter. Keywords Estimated GFR Longitudinal study Renal function decline
Introduction It is common knowledge that renal function declines with age. This has been known since the pioneering work of Shock and Davies beginning in 1945 [1]. In their original study on 70 healthy males they found the average decline in glomerular filtration rate (GFR) to be 0.96 ml/min/year
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or about 10 ml/min/decade. Since then, numerous published studies have pointed to a possible age-related decline in renal function after the age of 30 [2–6]. However, interpretation of the results from all these studies is problematic due to their cross-sectional study design, i.e. renal function was compared among subjects of different ages rather than looking at changes in GFR within individuals over time. Few longitudinal studies have addressed the issue of age-related decline in GFR. Some of these studies came about as a secondary analysis of randomized controlled studies in subjects with established renal disease [7, 8], while others were restricted to a subgroup of an older population [9–11]. Lindeman et al. were the first to summarize data on age-related decline in creatinine clearance in a longitudinal study on a small group of 446 participants aged 30 years and older who were followed between the years 1958–1981. They demonstrated that in subjects without renal disease the average yearly decline in GFR was 0.75 ml/min/year [12]. Estimation of the natural decline in GFR due to aging is important since the aged kidney is more vulnerable as a result of reduced adaptive capacity and higher susceptibility to acute kidney injury (AKI). AKI is associated with a higher risk of developing chronic kidney disease (CKD) and increased mortality [13]. The paucity of longitudinal studies on GFR changes with age means that more data are needed to assess this issue. Ideally, such studies should measure GFR using clearance techniques or exogenous filtration markers; however, these approaches are invasive and costly. Currently GFR is estimated by equations. The most recent, and seemingly the most accurate one, is the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation [14]. We therefore aimed to perform a longitudinal study on a large population based cohort to calculate the natural rate of GFR decline with age. In order to achieve this, at least five consecutive measurements of estimated GFR (eGFR), assessed by the CKD-EPI equation, were performed throughout the follow up period of 4 years or more. Only subjects with a baseline GFR above 90 ml/min/1.73 m2 were included. The rate of decline in GFR was assessed both in healthy subjects and in subjects with comorbidities.
Subjects and methods We analyzed a large health database from a screening center at the Rabin Medical Center in Israel. This referral institute provides regular health assessments for employees of different companies. Approximately 23,000 people were assessed from 2000 to 2012. The population attending the
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center for screening includes male and non-pregnant female subjects with an age range between 20 and 80 years. At each visit, each subject has a thorough medical history taken and undergoes a complete physical examination along with blood and urine tests, chest X-ray, an electrocardiogram, an exercise stress test and a lung function test. The same tests are repeated at each visit, including creatinine serum levels. Subjects may return once a year for repeated investigations despite no apparent change in their health. Estimated GFR was calculated using the latest CKD-EPI equation [14]. Creatinine serum levels were assessed on a Beckman Coulter AU 2700 analyzer (Brea, CA, USA). The method involved is based on the kinetic color test (Jaffe’s method), in which the creatinine forms a yellow-orange colored compound with picric acid in alkaline medium. The rate of change in absorbance is proportional to the creatinine concentration in the sample. The calibration of the method is traceable to the isotope dilution mass spectroscopy (IDMS). The study population consisted of subjects with baseline eGFR [ 90 ml/min/1.73 m2 who had 5 or more visits to the screening center throughout their follow up. The interval between visits was 1 year or more so the follow-up period was at least 4 years. Subjects older than 80 years were excluded. We estimated the rate of the annual decline in eGFR per subject using a linear regression model which regressed the eGFR against the year variable. The following issues were assessed: (a)
(b) (c)
(d)
The overall annual rate of decline in eGFR in healthy subjects. Healthy subjects were defined as those without hypertension, impaired fasting glucose or overt diabetes mellitus. Hypertension was defined as blood pressure C140/90 mmHg. Impaired fasting glucose was defined as fasting glucose 100–125 mg/ dl. Diabetes mellitus was defined as at least two fasting glucose levels C126 mg/dl. The annual rate of decline in eGFR in healthy subjects in relation to different age groups. In healthy subjects, comparison of the annual rate of decline in eGFR in relation to body surface area (BSA) and body mass index (BMI) subgroups: \25 kg/m2 (normal weight); 25–29.9 kg/m2 (overweight); 30–35 kg/m2 (obesity); [35 kg/m2 (morbid obesity). The annual rate of decline in eGFR in subjects with a comorbidity of hypertension, diabetes mellitus, impaired fasting glucose or combination of these comorbidities.
The study was approved by the Helsinki Ethics committee of the Rabin Medical Center.
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Statistical analysis We used linear regression methodology to estimate the eGFR change per subject. To increase the reliability of the linear regression estimates, we included only those subjects who had at least five consecutive assessments performed at least 1 year apart. We then compared the slopes [the yearly change in eGFR ± standard error (SE)] among several groups defined using demographic, clinical and laboratory data. Emphasis was put on the age (at entry to the study) variable. We used Welch’s two-sample t test and analysis of variance (ANOVA) to assess the statistical significance associated with numeric variables, and Pearson’s Chi squared test for binary variables. All statistical analysis was done using the R software environment for statistical computing and graphics (version 2.15.2).
Results Subjects’ characteristics Between the years 2000 and 2012, 2923 subjects with baseline eGFR above 90 ml/min/1.73 m2 attended the screening center five times or more, each visit at least 1 year apart. The average number of visits was 6.8 (range 5–12). The mean (SD) follow-up time was 7.8 ± 2.18 years (range 4–12). The subjects’ baseline characteristics are presented in Table 1. The average age was 42.4 ± 8.0 years and 23.9 % were females. There were no statistically significant differences between men and women as to their age, smoking habits, the percentage of hypertension or presence of overt diabetes mellitus. However, men had significantly higher rates of impaired fasting glucose, higher serum levels of low-density lipoprotein (LDL) cholesterol, triglycerides, creatinine and uric acid and a higher BMI. In contrast, their serum levels of high-density lipoprotein (HDL) cholesterol and their baseline eGFR were lower compared to women (p \ 0.001). The mean overall decline in eGFR over time The mean (SE) annual rate of decline in eGFR of all the 2923 subjects was 0.97 ± 0.02 ml/min/year/1.73 m2. The yearly decline in eGFR was similar in males and females; 0.99 ± 0.02 and 0.92 ± 0.05 ml/min/year/1.73 m2, respectively (p = 0.18). In 15.4 % of subjects there was no decline in eGFR with advancing age during the follow-up period. Out of the 2,923 subjects, 2,693 were apparently healthy, namely subjects without hypertension, impaired fasting glucose or diabetes mellitus, while 230 had different comorbidities. Healthy subjects had an overall mean
Table 1 Baseline characteristics of the study population (n = 2,923)
Age in years [mean (SD)] Hypertension (%) Impaired fasting glucose Diabetes mellitus (%) Smoker (%) HDL cholesterol, mg/dl [mean (SD)] LDL cholesterol, mg/dl [mean (SD)] Triglycerides, mg/dl [mean (SD)] Baseline creatinine, mg/dl [mean (SD)] Uric acid, mg/dl [mean (SD)] eGFR (CKD-EPI) ml/min/ 1.73 m2 [mean (SD)] BMI [mean (SD)]
Men n = 2224
Women n = 699
p
42.3 (7.9) 4.1 3.0 2.2 12.7 45.6 (9.8)
42.8 (8.1) 3.1 1.4 1.3 12.2 59.0 (13.8)
0.20 0.29 0.03 0.20 0.77 \0.001
125.7 (30.0)
120.0 (31.3)
\0.001
135.8 (86.1)
104.0 (57.3)
\0.001
1.0 (0.1)
0.8 (0.1)
\0.001
6.0 (1.1) 104.6 (8.8)
4.2 (0.9) 107.6 (10.0)
\0.001 \0.001
26.7 (4.1)
24.9 (4.6)
\0.001
SD standard deviation; HDL high density lipoprotein; LDL low density lipoprotein; eGFR estimated glomerular filtration rate; CKD-EPI chronic kidney disease epidemiologic collaboration equation; BMI body mass index
annual rate of decline in eGFR of 0.97 ± 0.02; males 0.99 ± 0.02 and females 0.93 ± 0.05 ml/min/year/ 1.73 m2. The gender differences were not significant. Decline in eGFR in relation to age The rate of decline in eGFR increased as the subjects became older (Fig. 1). The differences in the annual rate of decline in eGFR between age-groups were statistically significant (p \ 0.001). Gender differences were not significant (data not shown). Decline in eGFR in relation to BSA and BMI In healthy subjects there was no correlation between body surface area and decline in eGFR (data not shown). Subjects’ characteristics by the different groups of BMI are presented in Table 2. The calculation of decline of eGFR in relation to different levels of BMI is presented in Fig. 2. The differences between the groups as well as between genders (data not shown) were not found to be significant. Decline in eGFR in subjects with comorbidity The characteristics of subjects with different comorbidities are presented in Table 3. The decline of eGFR in subjects with comorbidities is presented in Fig. 3. Differences between the groups were not found to be significant, nor were any differences found for gender (data not shown).
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110 100
-0.82
-0.84
90
-1.07 -1.15
80
eGFR (mL/min/ 1.73m2)
120
Discussion
20
30
40
50
60
70
Age (years)
Fig. 1 Annual rate of decline in eGFR (ml/min/year/1.73 m2) in healthy subjects at different age groups. eGFR estimated glomerular filtration rate
Table 2 Characteristics of healthy subjects (n = 2,683) by BMI subgroup BMI kg/m2
\25 n = 1116
25–29.9 n = 1171
30–35 n = 326
[35 n = 70
Age [mean (SD)]
40.1 (7.4)
43.2 (7.7)
43.3 (7.7)
43.9 (7.6)
Male percentage (%)
65
83
83
79
BSA m2 [mean (SD)]
1.8 (0.2)
2.0 (0.1)
2.1 (0.2)
2.3 (0.2)
BMI body mass index; BSA body surface area
1.6
ml/min/year/1.73m 2
1.4 1.2 1 0.8 0.6 0.4 0.2 0
BMI Kg/m2
Fig. 2 Annual rate of decline in eGFR (ml/min/year/1.73 m2) in relation to different BMI categories eGFR estimated glomerular filtration rate; BMI body mass index; trend lines standard error
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Our longitudinal study involving 2,923 subjects with baseline eGFR above 90 ml/min/1.73 m2 provides new data on an old subject, namely the rate of decline in GFR with age. Apart from the large number of subjects included, the study is unique for using the latest CKD-EPI equation for estimating GFR. Serum creatinine levels were assessed by a kinetic color test (Jaffe’s method). Ideally those levels should have been assessed by an enzymatic method which is considered more precise especially in the pediatric population in whom serum creatinine levels are low. Since our study did not include a pediatric population and all subjects were 18 years and older it seems that the kinetic color test used was appropriate. A recent study comparing the different formulas for estimating GFR to the gold standard GFR measurement by 125I-iothalamate has shown that in patients with GFR C90 ml/min/1.73 m2 the CKDEPI equation was the one that estimated GFR closest to the directly measured GFR [15]. Nevertheless, we performed the same analysis using the Modification of Diet in Renal Disease (MDRD) (4 variables) equation for estimating GFR and found similar results (data not shown). In our study, GFR estimation was performed at least 5 times throughout the follow-up period, each assessment being at least 1 year apart giving reliable and powerful strength to the results. We found in a subgroup of 2,693 healthy subjects that the overall yearly decline in eGFR with advancing age was 0.97 ± 0.02 ml/min/1.73 m2. This value is higher than the common value referred to in the literature by about 0.8 ml/min/year/1.73 m2 [16]. However, it should be emphasized that this is the first time that such a large group of normal subjects has been assessed in a longitudinal study. The fact that GFR assessment was performed 5 times or more throughout the study, and the small standard error of the average rate of decline of only 0.02 ml/min/year/1.73 m2, suggest that the yearly decline in GFR of 0.97 ml/min/1.73 m2 is probably the best estimation found in normal subjects. Moreover, we have demonstrated that the annual change in GFR is not constant but increases significantly with age. It was 0.82 ml/min/year/1.73 m2 in the 20–30 year age-group and increased constantly to 1.15 ml/min/year/1.73 m2 in those over the age of 50. Our results are in line with Lindeman et al. [12] who found an increase in the annual change in GFR with age. However the number of subjects in each of their study age-groups was small causing the standard error of the results to be high, all of which precludes an accurate assessment of the true slopes of GFR change. The physiological changes that occur in the aging kidney have been summarized in a recent review by Musso et al.
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Table 3 Baseline characteristics of subjects (n = 230) with comorbidity
Age in years [mean, (SD)] Mean follow-up Male percentage (%) Smoker (%) Cardiovascular disease (%) Use of statins (%) Use of ACE/ARB (%) HDL cholesterol, mg/dl [mean (SD)] LDL cholesterol, mg/dl [mean (SD)] Triglycerides, mg/dl [mean (SD)] Baseline creatinine, mg/dl [mean (SD)] Uric acid, mg/dl [mean (SD)] eGFR (CKD-EPI) ml/min/ 1.73 m2 [mean, SD)] BMI [mean (SD)]
Diabetes mellitus
n = 96
n = 46
Impaired fasting glucose n = 70
49.7 (7.7) 7.9 (2.3) 83 8 2 54 57 47.4 (12.2)
48.1 (8.9) 7.3 (2.1) 91 22 4 59 39 44.8 (10.3)
45.7 (8.3) 5.6 (1.7) 87 17 6 29 14 46.2 (11.2)
131.0 (33.7)
114.0 (36.1)
122.9 (31.0)
147.7 (73.0)
189.0 (137.3)
158.1 (84.0)
0.9 (0.1)
0.9 (0.1)
0.9 (0.1)
6.2 (1.3)
5.3 (1.5)
5.8 (1.2)
100.3 (7.4)
104.6 (9.2)
101.2 (8.2)
29.3 (4.8)
28.2 (3.9)
27.8 (4.7)
ACE anti converting enzyme; ARB angiotensin receptor blocker; SD standard deviation; HDL high density lipoprotein; LDL low density lipoprotein; eGFR estimated glomerular filtration rate; CKD-EPI chronic kidney disease epidemiologic collaboration equation; BMI body mass index Note that 11 subjects had both hypertension and diabetes mellitus and 7 subjects had both hypertension and impaired fasting glucose and are therefore excluded from Table 3
[16]. These changes include senile hypo-filtration due to glomerulosclerosis, mesangial expansion, vascular changes such as renal atherosclerosis, arteriole subendothelial hyalinosis and tubulointerstitial changes such as tubular atrophy and interstitial fibrosis. Several other mechanisms are involved in the aging process of the kidney. These include: increased responsiveness to vasoconstrictor mediators (renin-angiotensin system, catecholamines); decreased sensitivity to vasodilators such as nitric oxide and prostaglandins; augmented expression of fibrosing mediators; and accumulation of oxidative stress. The aging kidney has reduced capacity for cell repair, diminished proliferative reserve, increased apoptosis and decreased cell senescence [13, 17]. Although the normal aged kidney and the kidney in subjects with chronic kidney disease both show a decrease in GFR, the two conditions differ tremendously. In contrast to CKD, in the normal aged kidney erythropoietin levels are preserved and therefore there is no anemia [18]. In addition calcium-phosphorus balance is preserved in the normally aging kidney while it is disturbed in CKD [19]. Urinalysis is normal in healthy old people and they have neither hematuria nor proteinuria [20].
1.4
ml/min/year/1.73m 2
Hypertension
1.2 1 0.8 0.6 0.4 0.2 0 Healthy subjects
Hypertension
Impaired Combined Diabetes mellitus fasting glucose comorbidity
Fig. 3 Annual rate of decline in eGFR (ml/min/year/1.73 m2) in healthy subjects and in subjects with comorbidity eGFR estimated glomerular filtration rate; combined comorbidity = subjects with hypertension and either impaired fasting glucose or diabetes mellitus; trend lines standard error
Very few longitudinal studies have previously addressed the issue of declining kidney function with age in healthy subjects. Lindeman et al. [12] showed in a subgroup of 254 subjects with no apparent kidney disease a mean yearly decline in eGFR of 0.75 ± 0.12 ml/min/year. The strength of their study was the use of the creatinine clearance method for estimating GFR, but their study featured a relatively small sample of healthy subjects. Three other longitudinal studies in healthy aging populations yielded a wide range of results in regard to the rate of decline in GFR ranging from 0.4 to 2.37 ml/min/year/1.73 m2 [9–11]. These studies, however, assessed an elderly population over 65 years of age. Various methods of estimation of GFR including the Cockcroft formula and MDRD equation were used. Possible limitations of these studies were the small number of measurements during the follow-up period and selection by age, as only older subjects were included. In comparison with previous studies, the strengths of our study are the relatively large number of subjects (approximately 3,000 with complete datasets) and employment of the latest and most accurate equation for estimating GFR. Furthermore, our data come from a general population sample designed specifically to examine this issue rather than a secondary analysis of data from a different study. Subjects with a wide age range were included. Our study was not limited to subjects with impaired baseline GFR. Lastly, five or more repeated measurements of eGFR were performed throughout the follow-up period giving a powerful validation of the results. Nevertheless, our study has a few limitations. The main limitation is the estimation of GFR with an equation, in that ideally the best way would have been to use an exogenous filtration marker or a clearance technique. However, such methods are invasive and costly, and in order to be able to assess a large population we preferred to use an
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equation. Other limitations are: a possible difference between the Israeli population and the US population where the CKD-EPI equation was generated; a possible selection bias by choosing subjects with only five or more visits who may have a higher awareness of keeping in good health compared to those with fewer visits; lack of urinary data such as albuminuria or proteinuria which were not part of the routine tests assessed at the screening center. And lastly, the data of the study is from a selected population attending an examination center and hence may not necessarily be applied to the general population. Apart from assessing the normal decline in renal function in normal subjects we also studied the relationship of GFR decline with age in relation to several factors. The annual rate of decline in eGFR was not affected by the subjects’ basic BMI or body surface area. To the best of our knowledge this is the first time that this issue has been addressed. The only data in the literature in this respect concern the association between BMI and CKD. In a recent large cross-sectional study we found for both men and women a positive association between BMI and CKD [21]. Other longitudinal studies have shown inconclusive results. Some have shown that a higher baseline BMI can predict future renal dysfunction [22–26] whereas other recent studies showed no such association either in non-diabetic or diabetic patients [27–29]. According to the results of our study it seems that BMI has no significant effect on the actual decline in GFR with age. As expected, subjects with hypertension had a higher annual rate of decline in eGFR, i.e. 1.12 ml/min/year/ 1.73 m2, while subjects with either diabetes mellitus or impaired fasting glucose, in whom hyper-filtration is expected at early stages of the disease [30, 31], had a lower rate of the annual decline in eGFR compared to healthy subjects (0.77 and 0.85 ml/min/year/1.73 m2 respectively). Since our study population was designed to evaluate healthy subjects, the percentage of subjects with hypertension and/or diabetes mellitus was relatively small. More studies with a larger number of participants with comorbidity are needed to confirm the actual rate of decline in GFR in these subjects. In conclusion, in this large longitudinal study on subjects with baseline eGFR above 90 ml/min/1.73 m2, we provide new data on the annual decrease in eGFR both in healthy subjects as well as in those with comorbidity. An accurate prediction of the natural rate of GFR decline can help to distinguish between a normally aging kidney and one with CKD. This may avoid unnecessary diagnostic procedures in the former and provide for appropriate treatment in the latter. Conflict of interest None of the authors had any conflict of interest in relation to the study. The study had no financial support.
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27. Mohsen A, Brown R, Hoefield R et al (2012) Body mass index has no effect on rate of progression of chronic kidney disease in subjects with type 2 diabetes mellitus. J Nephrol 25:384–393 28. Brown RN, Mohsen A, Green D et al (2012) Body mass index has no effect on rate of progression of chronic kidney disease in nondiabetic subjects. Nephrol Dial Transpl 27:2776–2780 29. Khedr A, Khedr E, House AA (2011) Body mass index and the risk of progression of chronic kidney disease. J Ren Nutr 21:455–461 30. Palatini P (2011) Glomerular hyperfiltration: a marker of early renal damage in pre-diabetes and pre-hypertension. Nephrol Dial Transpl 27:1708–1714 31. Jerums G, Premaratne E, Panagiotopoulos S, MacIsaac RJ (2010) The clinical significance of hyperfiltration in diabetes. Diabetologia 53:2093–2104
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ORIGINAL ARTICLE
A longitudinal assessment of the natural rate of decline in renal function with age Eytan Cohen • Yuval Nardi • Irit Krause • Elad Goldberg • Gai Milo • Moshe Garty • Ilan Krause
Received: 22 October 2013 / Accepted: 28 February 2014 Ó Italian Society of Nephrology 2014
Abstract Background Cross-sectional studies have long suggested that renal function declines with age. Longitudinal studies regarding this issue are limited. Methods We retrospectively analyzed a database of subjects attending a screening center in Israel between the years 2000–2012. Only subjects with normal estimated glomerular filtration rate (eGFR) were included. eGFR was assessed consequently at 5 or more yearly visits. The rate
E. Cohen (&) E. Goldberg I. Krause Department of Medicine F—Recanati, Rabin Medical Center (Beilinson Campus), 49100 Petah Tikva, Israel e-mail: [email protected] E. Cohen Clinical Pharmacology Unit, Rabin Medical Center (Beilinson Campus), Petah Tikva, Israel E. Cohen I. Krause E. Goldberg G. Milo M. Garty I. Krause Sackler Faculty of Medicine, Tel Aviv University, Ramat Aviv, Israel Y. Nardi Faculty of Industrial Engineering and Management, Technion—Israel Institute of Technology, Haifa, Israel I. Krause Nephrology Institute and Dialysis Unit, Schneider’s Children Medical Center of Israel Petah Tikva, Petah Tikva, Israel G. Milo Nephrology Unit, Rabin Medical Center (Beilinson Campus), Petah Tikva, Israel M. Garty Recanati Center for Preventive Medicine, Rabin Medical Center (Beilinson Campus), Petah Tikva, Israel
of decline in GFR with age was assessed in healthy subjects and in subjects with comorbidities. Results The cohort included 2693 healthy subjects and 230 subjects with different comorbidities. Mean (±standard error) annual rate of decline in eGFR in healthy subjects was 0.97 ± 0.02 ml/min/year/1.73 m2. This decline increased significantly from 0.82 ± 0.22 in agegroup 20–30 years to 0.84 ± 0.08, 1.07 ± 0.08 and 1.15 ± 0.12 ml/min/year/1.73 m2 in age groups 31–40, 41–50 and 50 years and older respectively (p \ 0.001). No correlation was found between the annual decline in eGFR and body mass index. In subjects with hypertension, diabetes mellitus, impaired fasting glucose or combined comorbidity the decline in eGFR was 1.12 ± 0.12, 0.77 ± 0.16, 0.85 ± 0.17, and 1.18 ± 0.26 ml/min/year/ 1.73 m2 respectively. Conclusions This large longitudinal study provides new data on the decrease in eGFR with age. Accurate prediction of the natural rate of GFR decline might be used to distinguish between normally aging kidneys and those with chronic disease. This approach could avoid unnecessary diagnostic procedures in the former and facilitate appropriate treatment in the latter. Keywords Estimated GFR Longitudinal study Renal function decline
Introduction It is common knowledge that renal function declines with age. This has been known since the pioneering work of Shock and Davies beginning in 1945 [1]. In their original study on 70 healthy males they found the average decline in glomerular filtration rate (GFR) to be 0.96 ml/min/year
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or about 10 ml/min/decade. Since then, numerous published studies have pointed to a possible age-related decline in renal function after the age of 30 [2–6]. However, interpretation of the results from all these studies is problematic due to their cross-sectional study design, i.e. renal function was compared among subjects of different ages rather than looking at changes in GFR within individuals over time. Few longitudinal studies have addressed the issue of age-related decline in GFR. Some of these studies came about as a secondary analysis of randomized controlled studies in subjects with established renal disease [7, 8], while others were restricted to a subgroup of an older population [9–11]. Lindeman et al. were the first to summarize data on age-related decline in creatinine clearance in a longitudinal study on a small group of 446 participants aged 30 years and older who were followed between the years 1958–1981. They demonstrated that in subjects without renal disease the average yearly decline in GFR was 0.75 ml/min/year [12]. Estimation of the natural decline in GFR due to aging is important since the aged kidney is more vulnerable as a result of reduced adaptive capacity and higher susceptibility to acute kidney injury (AKI). AKI is associated with a higher risk of developing chronic kidney disease (CKD) and increased mortality [13]. The paucity of longitudinal studies on GFR changes with age means that more data are needed to assess this issue. Ideally, such studies should measure GFR using clearance techniques or exogenous filtration markers; however, these approaches are invasive and costly. Currently GFR is estimated by equations. The most recent, and seemingly the most accurate one, is the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation [14]. We therefore aimed to perform a longitudinal study on a large population based cohort to calculate the natural rate of GFR decline with age. In order to achieve this, at least five consecutive measurements of estimated GFR (eGFR), assessed by the CKD-EPI equation, were performed throughout the follow up period of 4 years or more. Only subjects with a baseline GFR above 90 ml/min/1.73 m2 were included. The rate of decline in GFR was assessed both in healthy subjects and in subjects with comorbidities.
Subjects and methods We analyzed a large health database from a screening center at the Rabin Medical Center in Israel. This referral institute provides regular health assessments for employees of different companies. Approximately 23,000 people were assessed from 2000 to 2012. The population attending the
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center for screening includes male and non-pregnant female subjects with an age range between 20 and 80 years. At each visit, each subject has a thorough medical history taken and undergoes a complete physical examination along with blood and urine tests, chest X-ray, an electrocardiogram, an exercise stress test and a lung function test. The same tests are repeated at each visit, including creatinine serum levels. Subjects may return once a year for repeated investigations despite no apparent change in their health. Estimated GFR was calculated using the latest CKD-EPI equation [14]. Creatinine serum levels were assessed on a Beckman Coulter AU 2700 analyzer (Brea, CA, USA). The method involved is based on the kinetic color test (Jaffe’s method), in which the creatinine forms a yellow-orange colored compound with picric acid in alkaline medium. The rate of change in absorbance is proportional to the creatinine concentration in the sample. The calibration of the method is traceable to the isotope dilution mass spectroscopy (IDMS). The study population consisted of subjects with baseline eGFR [ 90 ml/min/1.73 m2 who had 5 or more visits to the screening center throughout their follow up. The interval between visits was 1 year or more so the follow-up period was at least 4 years. Subjects older than 80 years were excluded. We estimated the rate of the annual decline in eGFR per subject using a linear regression model which regressed the eGFR against the year variable. The following issues were assessed: (a)
(b) (c)
(d)
The overall annual rate of decline in eGFR in healthy subjects. Healthy subjects were defined as those without hypertension, impaired fasting glucose or overt diabetes mellitus. Hypertension was defined as blood pressure C140/90 mmHg. Impaired fasting glucose was defined as fasting glucose 100–125 mg/ dl. Diabetes mellitus was defined as at least two fasting glucose levels C126 mg/dl. The annual rate of decline in eGFR in healthy subjects in relation to different age groups. In healthy subjects, comparison of the annual rate of decline in eGFR in relation to body surface area (BSA) and body mass index (BMI) subgroups: \25 kg/m2 (normal weight); 25–29.9 kg/m2 (overweight); 30–35 kg/m2 (obesity); [35 kg/m2 (morbid obesity). The annual rate of decline in eGFR in subjects with a comorbidity of hypertension, diabetes mellitus, impaired fasting glucose or combination of these comorbidities.
The study was approved by the Helsinki Ethics committee of the Rabin Medical Center.
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Statistical analysis We used linear regression methodology to estimate the eGFR change per subject. To increase the reliability of the linear regression estimates, we included only those subjects who had at least five consecutive assessments performed at least 1 year apart. We then compared the slopes [the yearly change in eGFR ± standard error (SE)] among several groups defined using demographic, clinical and laboratory data. Emphasis was put on the age (at entry to the study) variable. We used Welch’s two-sample t test and analysis of variance (ANOVA) to assess the statistical significance associated with numeric variables, and Pearson’s Chi squared test for binary variables. All statistical analysis was done using the R software environment for statistical computing and graphics (version 2.15.2).
Results Subjects’ characteristics Between the years 2000 and 2012, 2923 subjects with baseline eGFR above 90 ml/min/1.73 m2 attended the screening center five times or more, each visit at least 1 year apart. The average number of visits was 6.8 (range 5–12). The mean (SD) follow-up time was 7.8 ± 2.18 years (range 4–12). The subjects’ baseline characteristics are presented in Table 1. The average age was 42.4 ± 8.0 years and 23.9 % were females. There were no statistically significant differences between men and women as to their age, smoking habits, the percentage of hypertension or presence of overt diabetes mellitus. However, men had significantly higher rates of impaired fasting glucose, higher serum levels of low-density lipoprotein (LDL) cholesterol, triglycerides, creatinine and uric acid and a higher BMI. In contrast, their serum levels of high-density lipoprotein (HDL) cholesterol and their baseline eGFR were lower compared to women (p \ 0.001). The mean overall decline in eGFR over time The mean (SE) annual rate of decline in eGFR of all the 2923 subjects was 0.97 ± 0.02 ml/min/year/1.73 m2. The yearly decline in eGFR was similar in males and females; 0.99 ± 0.02 and 0.92 ± 0.05 ml/min/year/1.73 m2, respectively (p = 0.18). In 15.4 % of subjects there was no decline in eGFR with advancing age during the follow-up period. Out of the 2,923 subjects, 2,693 were apparently healthy, namely subjects without hypertension, impaired fasting glucose or diabetes mellitus, while 230 had different comorbidities. Healthy subjects had an overall mean
Table 1 Baseline characteristics of the study population (n = 2,923)
Age in years [mean (SD)] Hypertension (%) Impaired fasting glucose Diabetes mellitus (%) Smoker (%) HDL cholesterol, mg/dl [mean (SD)] LDL cholesterol, mg/dl [mean (SD)] Triglycerides, mg/dl [mean (SD)] Baseline creatinine, mg/dl [mean (SD)] Uric acid, mg/dl [mean (SD)] eGFR (CKD-EPI) ml/min/ 1.73 m2 [mean (SD)] BMI [mean (SD)]
Men n = 2224
Women n = 699
p
42.3 (7.9) 4.1 3.0 2.2 12.7 45.6 (9.8)
42.8 (8.1) 3.1 1.4 1.3 12.2 59.0 (13.8)
0.20 0.29 0.03 0.20 0.77 \0.001
125.7 (30.0)
120.0 (31.3)
\0.001
135.8 (86.1)
104.0 (57.3)
\0.001
1.0 (0.1)
0.8 (0.1)
\0.001
6.0 (1.1) 104.6 (8.8)
4.2 (0.9) 107.6 (10.0)
\0.001 \0.001
26.7 (4.1)
24.9 (4.6)
\0.001
SD standard deviation; HDL high density lipoprotein; LDL low density lipoprotein; eGFR estimated glomerular filtration rate; CKD-EPI chronic kidney disease epidemiologic collaboration equation; BMI body mass index
annual rate of decline in eGFR of 0.97 ± 0.02; males 0.99 ± 0.02 and females 0.93 ± 0.05 ml/min/year/ 1.73 m2. The gender differences were not significant. Decline in eGFR in relation to age The rate of decline in eGFR increased as the subjects became older (Fig. 1). The differences in the annual rate of decline in eGFR between age-groups were statistically significant (p \ 0.001). Gender differences were not significant (data not shown). Decline in eGFR in relation to BSA and BMI In healthy subjects there was no correlation between body surface area and decline in eGFR (data not shown). Subjects’ characteristics by the different groups of BMI are presented in Table 2. The calculation of decline of eGFR in relation to different levels of BMI is presented in Fig. 2. The differences between the groups as well as between genders (data not shown) were not found to be significant. Decline in eGFR in subjects with comorbidity The characteristics of subjects with different comorbidities are presented in Table 3. The decline of eGFR in subjects with comorbidities is presented in Fig. 3. Differences between the groups were not found to be significant, nor were any differences found for gender (data not shown).
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110 100
-0.82
-0.84
90
-1.07 -1.15
80
eGFR (mL/min/ 1.73m2)
120
Discussion
20
30
40
50
60
70
Age (years)
Fig. 1 Annual rate of decline in eGFR (ml/min/year/1.73 m2) in healthy subjects at different age groups. eGFR estimated glomerular filtration rate
Table 2 Characteristics of healthy subjects (n = 2,683) by BMI subgroup BMI kg/m2
\25 n = 1116
25–29.9 n = 1171
30–35 n = 326
[35 n = 70
Age [mean (SD)]
40.1 (7.4)
43.2 (7.7)
43.3 (7.7)
43.9 (7.6)
Male percentage (%)
65
83
83
79
BSA m2 [mean (SD)]
1.8 (0.2)
2.0 (0.1)
2.1 (0.2)
2.3 (0.2)
BMI body mass index; BSA body surface area
1.6
ml/min/year/1.73m 2
1.4 1.2 1 0.8 0.6 0.4 0.2 0
BMI Kg/m2
Fig. 2 Annual rate of decline in eGFR (ml/min/year/1.73 m2) in relation to different BMI categories eGFR estimated glomerular filtration rate; BMI body mass index; trend lines standard error
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Our longitudinal study involving 2,923 subjects with baseline eGFR above 90 ml/min/1.73 m2 provides new data on an old subject, namely the rate of decline in GFR with age. Apart from the large number of subjects included, the study is unique for using the latest CKD-EPI equation for estimating GFR. Serum creatinine levels were assessed by a kinetic color test (Jaffe’s method). Ideally those levels should have been assessed by an enzymatic method which is considered more precise especially in the pediatric population in whom serum creatinine levels are low. Since our study did not include a pediatric population and all subjects were 18 years and older it seems that the kinetic color test used was appropriate. A recent study comparing the different formulas for estimating GFR to the gold standard GFR measurement by 125I-iothalamate has shown that in patients with GFR C90 ml/min/1.73 m2 the CKDEPI equation was the one that estimated GFR closest to the directly measured GFR [15]. Nevertheless, we performed the same analysis using the Modification of Diet in Renal Disease (MDRD) (4 variables) equation for estimating GFR and found similar results (data not shown). In our study, GFR estimation was performed at least 5 times throughout the follow-up period, each assessment being at least 1 year apart giving reliable and powerful strength to the results. We found in a subgroup of 2,693 healthy subjects that the overall yearly decline in eGFR with advancing age was 0.97 ± 0.02 ml/min/1.73 m2. This value is higher than the common value referred to in the literature by about 0.8 ml/min/year/1.73 m2 [16]. However, it should be emphasized that this is the first time that such a large group of normal subjects has been assessed in a longitudinal study. The fact that GFR assessment was performed 5 times or more throughout the study, and the small standard error of the average rate of decline of only 0.02 ml/min/year/1.73 m2, suggest that the yearly decline in GFR of 0.97 ml/min/1.73 m2 is probably the best estimation found in normal subjects. Moreover, we have demonstrated that the annual change in GFR is not constant but increases significantly with age. It was 0.82 ml/min/year/1.73 m2 in the 20–30 year age-group and increased constantly to 1.15 ml/min/year/1.73 m2 in those over the age of 50. Our results are in line with Lindeman et al. [12] who found an increase in the annual change in GFR with age. However the number of subjects in each of their study age-groups was small causing the standard error of the results to be high, all of which precludes an accurate assessment of the true slopes of GFR change. The physiological changes that occur in the aging kidney have been summarized in a recent review by Musso et al.
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Table 3 Baseline characteristics of subjects (n = 230) with comorbidity
Age in years [mean, (SD)] Mean follow-up Male percentage (%) Smoker (%) Cardiovascular disease (%) Use of statins (%) Use of ACE/ARB (%) HDL cholesterol, mg/dl [mean (SD)] LDL cholesterol, mg/dl [mean (SD)] Triglycerides, mg/dl [mean (SD)] Baseline creatinine, mg/dl [mean (SD)] Uric acid, mg/dl [mean (SD)] eGFR (CKD-EPI) ml/min/ 1.73 m2 [mean, SD)] BMI [mean (SD)]
Diabetes mellitus
n = 96
n = 46
Impaired fasting glucose n = 70
49.7 (7.7) 7.9 (2.3) 83 8 2 54 57 47.4 (12.2)
48.1 (8.9) 7.3 (2.1) 91 22 4 59 39 44.8 (10.3)
45.7 (8.3) 5.6 (1.7) 87 17 6 29 14 46.2 (11.2)
131.0 (33.7)
114.0 (36.1)
122.9 (31.0)
147.7 (73.0)
189.0 (137.3)
158.1 (84.0)
0.9 (0.1)
0.9 (0.1)
0.9 (0.1)
6.2 (1.3)
5.3 (1.5)
5.8 (1.2)
100.3 (7.4)
104.6 (9.2)
101.2 (8.2)
29.3 (4.8)
28.2 (3.9)
27.8 (4.7)
ACE anti converting enzyme; ARB angiotensin receptor blocker; SD standard deviation; HDL high density lipoprotein; LDL low density lipoprotein; eGFR estimated glomerular filtration rate; CKD-EPI chronic kidney disease epidemiologic collaboration equation; BMI body mass index Note that 11 subjects had both hypertension and diabetes mellitus and 7 subjects had both hypertension and impaired fasting glucose and are therefore excluded from Table 3
[16]. These changes include senile hypo-filtration due to glomerulosclerosis, mesangial expansion, vascular changes such as renal atherosclerosis, arteriole subendothelial hyalinosis and tubulointerstitial changes such as tubular atrophy and interstitial fibrosis. Several other mechanisms are involved in the aging process of the kidney. These include: increased responsiveness to vasoconstrictor mediators (renin-angiotensin system, catecholamines); decreased sensitivity to vasodilators such as nitric oxide and prostaglandins; augmented expression of fibrosing mediators; and accumulation of oxidative stress. The aging kidney has reduced capacity for cell repair, diminished proliferative reserve, increased apoptosis and decreased cell senescence [13, 17]. Although the normal aged kidney and the kidney in subjects with chronic kidney disease both show a decrease in GFR, the two conditions differ tremendously. In contrast to CKD, in the normal aged kidney erythropoietin levels are preserved and therefore there is no anemia [18]. In addition calcium-phosphorus balance is preserved in the normally aging kidney while it is disturbed in CKD [19]. Urinalysis is normal in healthy old people and they have neither hematuria nor proteinuria [20].
1.4
ml/min/year/1.73m 2
Hypertension
1.2 1 0.8 0.6 0.4 0.2 0 Healthy subjects
Hypertension
Impaired Combined Diabetes mellitus fasting glucose comorbidity
Fig. 3 Annual rate of decline in eGFR (ml/min/year/1.73 m2) in healthy subjects and in subjects with comorbidity eGFR estimated glomerular filtration rate; combined comorbidity = subjects with hypertension and either impaired fasting glucose or diabetes mellitus; trend lines standard error
Very few longitudinal studies have previously addressed the issue of declining kidney function with age in healthy subjects. Lindeman et al. [12] showed in a subgroup of 254 subjects with no apparent kidney disease a mean yearly decline in eGFR of 0.75 ± 0.12 ml/min/year. The strength of their study was the use of the creatinine clearance method for estimating GFR, but their study featured a relatively small sample of healthy subjects. Three other longitudinal studies in healthy aging populations yielded a wide range of results in regard to the rate of decline in GFR ranging from 0.4 to 2.37 ml/min/year/1.73 m2 [9–11]. These studies, however, assessed an elderly population over 65 years of age. Various methods of estimation of GFR including the Cockcroft formula and MDRD equation were used. Possible limitations of these studies were the small number of measurements during the follow-up period and selection by age, as only older subjects were included. In comparison with previous studies, the strengths of our study are the relatively large number of subjects (approximately 3,000 with complete datasets) and employment of the latest and most accurate equation for estimating GFR. Furthermore, our data come from a general population sample designed specifically to examine this issue rather than a secondary analysis of data from a different study. Subjects with a wide age range were included. Our study was not limited to subjects with impaired baseline GFR. Lastly, five or more repeated measurements of eGFR were performed throughout the follow-up period giving a powerful validation of the results. Nevertheless, our study has a few limitations. The main limitation is the estimation of GFR with an equation, in that ideally the best way would have been to use an exogenous filtration marker or a clearance technique. However, such methods are invasive and costly, and in order to be able to assess a large population we preferred to use an
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equation. Other limitations are: a possible difference between the Israeli population and the US population where the CKD-EPI equation was generated; a possible selection bias by choosing subjects with only five or more visits who may have a higher awareness of keeping in good health compared to those with fewer visits; lack of urinary data such as albuminuria or proteinuria which were not part of the routine tests assessed at the screening center. And lastly, the data of the study is from a selected population attending an examination center and hence may not necessarily be applied to the general population. Apart from assessing the normal decline in renal function in normal subjects we also studied the relationship of GFR decline with age in relation to several factors. The annual rate of decline in eGFR was not affected by the subjects’ basic BMI or body surface area. To the best of our knowledge this is the first time that this issue has been addressed. The only data in the literature in this respect concern the association between BMI and CKD. In a recent large cross-sectional study we found for both men and women a positive association between BMI and CKD [21]. Other longitudinal studies have shown inconclusive results. Some have shown that a higher baseline BMI can predict future renal dysfunction [22–26] whereas other recent studies showed no such association either in non-diabetic or diabetic patients [27–29]. According to the results of our study it seems that BMI has no significant effect on the actual decline in GFR with age. As expected, subjects with hypertension had a higher annual rate of decline in eGFR, i.e. 1.12 ml/min/year/ 1.73 m2, while subjects with either diabetes mellitus or impaired fasting glucose, in whom hyper-filtration is expected at early stages of the disease [30, 31], had a lower rate of the annual decline in eGFR compared to healthy subjects (0.77 and 0.85 ml/min/year/1.73 m2 respectively). Since our study population was designed to evaluate healthy subjects, the percentage of subjects with hypertension and/or diabetes mellitus was relatively small. More studies with a larger number of participants with comorbidity are needed to confirm the actual rate of decline in GFR in these subjects. In conclusion, in this large longitudinal study on subjects with baseline eGFR above 90 ml/min/1.73 m2, we provide new data on the annual decrease in eGFR both in healthy subjects as well as in those with comorbidity. An accurate prediction of the natural rate of GFR decline can help to distinguish between a normally aging kidney and one with CKD. This may avoid unnecessary diagnostic procedures in the former and provide for appropriate treatment in the latter. Conflict of interest None of the authors had any conflict of interest in relation to the study. The study had no financial support.
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