Characteristics of subjects
A total of 34,416 healthy people were enrolled in this study. The mean age of total population was 39.0 years and 45.23% of which were males (N = 15568). The mean Scr was 0.75 mg/dL, the level of it showed stable before 40 years, then increased with aging. Other observation indices were shown in Table 1.
Table 1
Baseline characteristics of the healthy subjects.
Variable
|
All subjects
|
18-29years
|
30-39years
|
40-49years
|
50-59years
|
60-69years
|
≥ 70years
|
(n = 34416)
|
(n = 7226)
|
(n = 13358)
|
(n = 7890)
|
(n = 4046)
|
(n = 1413)
|
(n = 483)
|
male [n(%)]
|
15568(45.23%)
|
39.84(38.75%)
|
5261(39.38%)
|
3808(48.26%)
|
2370(58.58%)
|
906(64.12%)
|
344(71.22%)
|
SBP(mmHg)
|
116.41(11.47)
|
116.21(11.23)
|
114.63(11.29)*
|
116.55(11.48)*
|
119.34(10.95)*
|
122.52(10.76)*
|
126.99(9.50)*
|
DBP(mmHg)
|
71.58(8.34)
|
70.72(7.97)
|
70.74(8.18)
|
72.30(8.61)*
|
73.88(8.45)*
|
73.98(8.08)
|
70.76(8.00)*
|
BMI(kg/m2)
|
22.55(2.24)
|
21.94(2.21)
|
22.39(2.22)*
|
22.94(2.19)*
|
23.15(2.12)*
|
23.28(2.18)
|
23.24(2.22)
|
HDL(mmol/L)
|
1.44(0.27)
|
1.45(0.26)
|
1.44(0.27)
|
1.45(0.28)
|
1.44(0.28)
|
1.43(0.27)
|
1.43(0.28)
|
LDL (mmol/L)
|
2.95(0.53)
|
2.81(0.53)
|
2.91(0.52)*
|
3.03(0.51)*
|
3.13(0.50)*
|
3.08(0.54)*
|
2.91(0.62)*
|
TG(mmol/L)
|
1.07(0.40)
|
0.95(0.36)
|
1.04(0.39)*
|
1.12(0.41)*
|
1.20(0.41)*
|
1.25(0.42)*
|
1.17(0.34)*
|
TC(mmol/L)
|
4.88(0.70)
|
4.68(0.70)
|
4.82(0.69)*
|
5.00(0.66)*
|
5.11(0.64)*
|
5.09(0.70)
|
4.88(0.80)*
|
FBG(mmol/L)
|
5.07(0.46)
|
4.94(0.41)
|
5.02(0.41)*
|
5.13(0.46)*
|
5.24(0.51)*
|
5.37(0.54)*
|
5.46(0.56)*
|
ALB(g/L)
|
45.40(2.52)
|
46.47(2.58)
|
45.72(2.43)*
|
44.88(2.34)*
|
44.60(2.33)*
|
44.12(2.13)*
|
42.93(2.35)*
|
UA(umol/L)
|
297.27(60.92)
|
298.10(60.61)
|
292.27(61.05)*
|
295.26(62.06)*
|
308.66(57.18)*
|
312.09(57.62)
|
317.34(59.16)
|
BUN(mmol/L)
|
4.76(1.12)
|
4.55(1.08)
|
4.65(1.07)*
|
4.82(1.11)*
|
5.16(1.14)*
|
5.25(1.15)
|
5.43(1.34)
|
Scr(mg/dL)
|
0.75(0.15)
|
0.73(0.15)
|
0.73(0.15)
|
0.75(0.15)*
|
0.79(0.15)*
|
0.80(0.14)*
|
0.84(0.16)*
|
Values were presented as mean (standard deviation) or percent |
Abbreviations: SBP systolic blood pressure; DBP diastolic blood pressure; BMI body mass index; HDL-C high density lipoprotein cholesterol; LDL-C low-density lipoprotein cholesterol; TG triglyceride; TC total cholesterol; FBG: fasting blood glucose; ALB albumin; UA uric acid; BUN blood urea nitrogen. |
*P < 0.05, compared with former age spectrum. |
Age-related trend of eGFR
eGFRs calculated by three equations yielded a significant decline with aging. The tendency of eGFR calculated by CKD-EPI equations with aging showed the constant decline from 119.6 mL/min/1.73 m2 in 18–29 years to 80.7 mL/min/1.73 m2 in above 70 years, and the decline rate of eGFR was 0.81 mL/min/1.73 m2/year. The eGFR level by FAS equation was approximately stable with 116.5 mL/min/1.73 m2 below age 40, and gradually declined with a rate of 1.27 mL/min/1.73 m2/year above age 40 with aging. Xiangya equations showed the constant decline from 98.1 to 73.7 mL/min/1.73 m2, the rate of decline was 0.56 mL/min/1.73 m2/year. Descending trends of eGFR in subgroups by gender were shown in Fig. 2. Both males and females had similar descending trend as total population. Compared with males, females have faster decline rate of eGFR.
The average eGFR decreased across age groups, but different equations have different performances. Values were presented as mean and SD.
eGFR estimated glomerular filtration rate by CKD-EPI, FAS and Xiangya respectively.
Differences between equations stratified by Scr level
Partial correlation analysis of the difference between three equations and important related factors showed Δ (CKD-EPI, FAS), Δ (CKD-EPI, Xiangya) and Δ (FAS, Xiangya) were all significantly correlated with Scr and age. We plotted scatter diagrams to show the difference between these equations under different Scr level (Fig. 3). Δ (CKD-EPI, FAS) reduced with increasing Scr level when Scr was less than 0.9 mg/dL in males or 0.7 mg/dL in females, while was relatively stable when Scr levels more than above cut-off point. Δ (CKD-EPI, Xiangya) and Δ (FAS, Xiangya) were considerable with elevating Scr level. We performed agreement analysis by adopting 0.9 mg/dL in males and 0.7 mg/dL in females as the cut-off point, a substantial agreement between CKD-EPI and FAS equations was seen with Scr ≥ 0.9mg/dL in males (κ 0.798) and Scr ≥ 0.7mg/dL in females (κ 0.745). Whereas agreement between Xiangya and other two equations were all slight (κ<0.2). Agreement between equations was poor for subjects with Scr < 0.9mg/dL in males and Scr < 0.7mg/dL in females (Table S2 and Table S3).
The black, orange and blue circle represents the total, females and males, respectively. The solid line in the scatter plot represents the trend line. CKD-EPI: chronic kidney disease epidemiology collaboration; FAS full age spectrum; Δ: difference.
Differences between equations stratified by age
As shown in Fig. 4, Δ (CKD-EPI, FAS), Δ (CKD-EPI, Xiangya) and Δ (FAS, Xiangya) existed differences across age groups. Δ (CKD-EPI, FAS) was relatively stable with aging. Δ (CKD-EPI, Xiangya) and Δ (FAS, Xiangya) have marked difference in females and males. In addition, we divided into six age groups, and used weighted κ statistic to quantify agreement between equations. We observed moderate to near-perfect in age 18–59 years (κ 0.617–0.901 for males and 0.536–0.861 for females) between CKD-EPI and FAS equations, whereas fair to moderate in age ≥ 60 years (κ 0.494–0.513 for males and 0.373–0.526 for females). However, the agreement in every age group was no more than moderate between Xiangya and CKD-EPI equations or FAS equations. In addition, CKD-EPI equation had higher estimates than FAS and Xiangya equations in GFR categories (Table S4 and Table S5).
The black, orange and blue circle represents the total, females and males, respectively. The solid line in the scatter plot represents the trend line. CKD-EPI: chronic kidney disease epidemiology collaboration; FAS full age spectrum; Δ: difference.