Abstract
Although metabolic syndrome, including visceral fat accumulation, causes kidney and cardiovascular diseases, the impact of visceral fat accumulation on mild decreased renal function remains unclear. This study examines the association between visceral fat area (VFA) measured by bioimpedance methods and the estimated glomerular filtration rate based on serum cystatin C (eGFRcys) in the Japanese urban population. This community-based cross-sectional study enrolled 952 individuals (287 men, 665 women) who participated in the second follow-up survey of the Kobe Orthopedic and Biomedical Epidemiological (KOBE) study. We compared the multivariate-adjusted means of eGFRcys among VFA quartile groups by gender using the analysis of covariance. Models were adjusted for age, high blood pressure, hypercholesterolemia, glucose intolerance, smoking, and alcohol use, and further adjusted for body mass index (BMI). The highest VFA quartile group had lower eGFRcys than the lowest VFA quartile group after adjusted for cardiometabolic risk factors, except for BMI (93.1 [95% confidence interval (CI), 90.1–96.2] vs. 82.1 [95% CI, 79.1–85.0] in men and 95.8 [95% CI, 94.1–97.5] vs. 89.4 [95% CI, 87.8–90.9] in women). Moreover, further adjustment for BMI revealed a similar result in men (93.5 [95% CI, 89.8–97.2] vs. 81.6 [95% CI, 77.9–85.3]), while no significant association was found in women. This study suggests a significant association between increased VFA levels and lower eGFRcys levels independent of cardiometabolic risk factors, such as glucose intolerance and hypercholesterolemia in men and women, as well as independent of BMI in men.
METABOLIC SYNDROME based on visceral fat accumulation causes atherosclerosis and kidney diseases [1]. A visceral fat area (VFA) ≥100 cm2 is the Japanese criteria for diagnosing metabolic syndrome [2]. Computed tomography (CT) is the gold standard method for measuring VFA [3]; however, measuring VFA using CT is not practical in primary care or health checkups because of the cost-effectiveness and/or radiation exposure of the procedure. Thus, VFA-measuring devices that use impedance-based methods, which have received regulatory approval, are prevalent in clinical setting [4, 5].
Among major noncommunicable diseases, chronic kidney disease (CKD) is a global public health concern associated with several lifestyle-related diseases [6]. Early detection and appropriate treatment of CKD can improve and prevent worse outcomes. Two studies in the Japanese general population indicated an association between metabolic syndrome and mild decline in the estimated glomerular filtration rate based on serum creatinine (eGFRcreat) levels [7, 8]. In addition, Tamba et al. established a correlation between visceral fat accumulation and an increase of the urinary albumin–creatinine ratio [9]. Lee et al. claimed that higher CT-measured VFA correlated with lower eGFRcreat in healthy Korean women [10], and Yoon et al. demonstrated a correlation between higher bioimpedance-measured VFA levels and lower eGFRcreat in the Korean general population [11].
To date, little research has been conducted on the association using the estimated glomerular filtration rate based on serum cystatin C (eGFRcys). Of note, eGFRcys offers the following advantages over eGFRcreat: (i) it is less affected by muscular mass, diet, and exercise [12, 13]; (ii) it strongly correlates with inulin clearance [14]; and (iii) it is more sensitive to detect mild glomerular filtration rate reduction [15]. Hence, this study aims to examine the association between visceral fat accumulation measured by the bioimpedance method and eGFRcys in the Japanese urban population.
Material and Methods
Study participants
The Kobe Orthopedic and Biomedical Epidemiology (KOBE) study is a population-based cohort study of risk factors for cardiovascular diseases or worsening quality of life in Kobe, an urban area in Japan. The KOBE study is detailed elsewhere [16, 17]. Participants comprised healthy men and women aged 40–74 years, without a history of malignant neoplasms and cerebro-cardiovascular diseases, and not being treated for hypertension, diabetes mellitus, or dyslipidemia at the baseline. A total of 1,117 individuals were enrolled in the baseline survey from 2010 to 2011. A follow-up survey of participants was performed every 2 years.
In this cross-sectional study, from 1,004 participants of the second follow-up survey conducted during 2014–2015, 52 participants whose VFA was not measured were excluded. Finally, the evaluation data were available for 952 participants (287 men, 665 women).
Data collection and definitions
A self-reported questionnaire-based survey was conducted about the lifestyle-related factors, including medication history, medical history, smoking habit, and drinking habit among all study participants. In addition, blood pressure was measured using an automated sphygmomanometer (BP-103i II; Fukudacorin Co., Ltd., Tokyo, Japan) after a 5-min rest in the sitting position. Blood tests were conducted in the Clinical Laboratory Center (SRL, Inc., Tokyo, Japan). Each blood sample was measured as follows: hemoglobin A1c (HbA1c) level by the latex coagulation method; serum total cholesterol, high-density lipoprotein cholesterol (HDL-C), and triglyceride (TG) levels by enzymatic methods. Furthermore, serum cystatin C was measured using the colloidal gold immunoassay.
We used data from the second follow-up survey for each definition. Body mass index (BMI) was defined as body weight in kilograms divided by height in meters squared. Low-density lipoprotein cholesterol (LDL-C) was calculated the Friedewald formula. High blood pressure was defined as undertreatment for hypertension or blood pressure ≥135/85 mmHg, adopted as a criterion for hypertension based on out-of-office blood pressure to more strictly identify hypertensive patients [18]. Hypercholesterolemia was defined as under treatment for high LDL-C or LDL-C ≥140 mg/dL based on the Japan Atherosclerosis Society Guidelines [19]. Glucose intolerance was defined as under treatment for diabetes mellitus or fasting blood glucose level ≥110 mg/dL or HbA1c level ≥6.0% based on suspicion of present diabetes mellitus in the report of the Committee of the Japan Diabetes Society on the Diagnostic Criteria of Diabetes Mellitus [20].
To calculate eGFRcys, we used the Chronic Kidney Disease Epidemiology Collaboration Equation (CKD-EPI), which performs well in Japanese individuals [21], as follows: eGFRcys (mL/min/1.73 m2) = 133 × min (serum cystatin C/0.8, 1)–0.499 × max (serum cystatin C/0.8, 1)–1.328 × 0.996Age × 0.932 [if women] [22]. Furthermore, CKD was defined as eGFRcys <60 mL/min/1.73 m2, where min denotes the minimum of serum cystatin C/0.8 or 1, and max indicates the maximum of serum cystatin C/0.8 or 1. We used the CKD-EPI to calculate the eGFRcreat. The formula to calculate eGFRcreat is as follows: eGFRcreat (mL/min/1.73 m2) = 141 × min (serum creatinine/κ, 1)α × max (serum creatinine /κ, 1)–1.209 × 0.993Age × 1.018 [for women] where κ is 0.7 for females and 0.9 for males and α is –0.329 for females and –0.411 for men [23].
In addition, VFA were measured by Visceral Fat Meter EW-FA90 (approved by the Pharmaceutical Affairs Law; Panasonic K.K., Osaka, Japan), which was based on the principle of the abdominal bioelectrical impedance analysis (BIA) method. The BIA method was noninvasive with short-term measurability, and excellent correlation was observed while estimating visceral fat accumulation between the abdominal BIA method and CT [24]. It should be noted that only trained healthcare professionals performed VFA measurements. The umbilical electrode unit of the measuring belt was aligned with the participants’ umbilical waist, and the back-electrode unit was located on the spine, with the belt horizontal before wearing the flank unit. Then, the electrode units were placed directly on the skin. The measurement was performed at the end of normal expiration in a standing position, and each measurement was taken two times. Notably, the measurement was checked for the third time when the first two attempts were 5 cm2 apart. Belts for measurement instruments were selected according to the subject’s body size.
Statistical analysis
All analyses were conducted in a sex-specific manner. Participants’ characteristics were summarized as a percentage for categorical variables and mean and standard deviation (SD) for continuous variables divided by quartiles of VFA (Q1, the lowest; Q4, the highest). All categorical variables were compared using the Cochran–Armitage trend test, while the analysis of variance with linear contrast was applied to continuous variables. Using the analysis of covariance (ANCOVA) test, we compared the influence of quartiles of VFA on eGFRcys after adjustment for covariables. Each model was adjusted for the following variables: model 1, age; model 2, age, high blood pressure, hypercholesterolemia, glucose intolerance, smoking, and alcohol use; model 3, model 2 variables and BMI. In addition, we used Bonferroni adjusted tests for significance to assess the significance of each group compared with the lowest VFA quartile group. In addition, we performed the ANCOVA test to compare the influence of quartiles of waist circumference on eGFRcys. In the sensitivity analysis, the ANCOVA test was performed in the population, excluding 9 participants (2 men and 7 women) who had some metal implants in their body, such as knee bolt, and 20 participants with CKD (13 men and 7 women), respectively. We also compared the influence of VFA quartiles on eGFRcreat adjusting for covariables. Furthermore, SAS software version 9.4 (SAS Institute, Cary NC) was used for statistical analyses. In this study, a two-sided p < 0.05 was considered statistically significant.
Ethical consideration
We obtained written informed consent from all participants. The KOBE study was approved by the Clinical Research Review Committee for Drugs (Ethics Committee) of the Institute of Biomedical Research and Innovation (Hyogo, Japan; No. 10–20). In addition, this study was approved by the Ethics Committee of Keio University School of Medicine (Tokyo, Japan; No. 20170142).
Results
Of all, 665 participants (69.9%) were women, participants’ mean age (SD) was as follows: men, 65.2 (8.5) years; women, 62.0 (8.5) years. The mean VFA and eGFRcys were as follows: men, 87.6 (43.9) cm2 and 88.4 (16.0) mL/min/1.73 m2; women, 54.0 (27.1) cm2 and 93.4 (13.2) mL/min/1.73 m2, respectively. Tables 1 and 2 present the characteristics of 952 participants stratified by VFA quartiles. The VFA levels were classified as follows: men, Q1 (≤55 cm2), Q2 (55<, ≤85 cm2), Q3 (85<, ≤115 cm2), Q4 (115< cm2); women, Q1 (≤30 cm2), Q2 (30<, ≤50 cm2), Q3 (50<, ≤70 cm2), Q4 (70< cm2). In both men and women, waist circumference and BMI tended to be higher with higher VFA (p < 0.0001 for both sexes). Female participants with higher VFA tended to have a higher rate of high blood pressure (p = 0.0112), glucose intolerance (p < 0.0001), and hypercholesterolemia (p = 0.0005). In contrast, male participants with higher VFA tended to have a higher rate of high blood pressure (p < 0.0001) and hypercholesterolemia (p = 0.0225). In participants with higher VFA, mean eGFRcys was lower in both men (p = 0.0005) and women (p < 0.0001). Moreover, the prevalence of CKD was significantly different in women (p = 0.0011), whereas it did not differ in men. Of note, no participant had CKD in the Q1 and Q2 groups of women, while 6 (3.8%) participants had CKD in the Q4 group.
Table 1
Participant baseline characteristics (men)
1
|
Q1 (n = 70)
VFA ≤55 cm2 |
Q2 (n = 73)
55< VFA ≤85 cm2 |
Q3 (n = 70)
85< VFA ≤115 cm2 |
Q4 (n = 74)
115< VFA cm2 |
| Age, years (SD) |
65.3 (8.7) |
65.8 (7.6) |
64.8 (9.5) |
64.9 (8.5) |
| Waist circumference, cm (SD)§ |
73.4 (4.1) |
79.9 (3.5) |
84.6 (3.4) |
92.1 (6.8) |
| BMI, kg/m2 (SD)§ |
20.1 (1.7) |
21.6 (1.5) |
23.4 (1.7) |
25.5 (2.4) |
| Systolic blood pressure, mmHg (SD)§ |
112.7 (16.8) |
117.1 (17.9) |
122.6 (15.3) |
125.7 (15.3) |
| Diastolic blood pressure, mmHg (SD)§ |
71.2 (10.3) |
73.1 (9.6) |
78.5 (9.4) |
80.3 (8.9) |
| Fasting blood glucose, mg/dL (SD)‡ |
91.9 (7.9) |
91.6 (7.9) |
97.5 (13.7) |
96.9 (11.5) |
| HbA1c, % (SD) |
5.6 (0.4) |
5.6 (0.4) |
5.7 (0.6) |
5.7 (0.5) |
| Total cholesterol, mg/dL (SD) |
194.5 (27.6) |
203.6 (28.8) |
203.3 (32.1) |
200.9 (23.5) |
| HDL-cholesterol, mg/dL (SD)§ |
68.3 (12.8) |
61.5 (14.2) |
57.4 (12.7) |
53.4 (11.7) |
| LDL-cholesterol, mg/dL (SD)* |
113.8 (26.1) |
124.4 (27.6) |
125.5 (29.0) |
122.6 (24.7) |
| Triglycerides, mg/dL (SD)§ |
62.4 (17.8) |
88.5 (41.4) |
102.0 (51.5) |
124.9 (71.0) |
| High blood pressure, n (%)§ |
8 (11.4) |
10 (13.7) |
21 (30.0) |
26 (35.1) |
| Glucose intolerance, n (%) |
14 (20.0) |
8 (11.0) |
18 (25.7) |
19 (25.7) |
| Hypercholesterolemia, n (%)* |
10 (14.3) |
24 (32.9) |
27 (38.6) |
23 (31.1) |
| Current alcohol consumption, n (%) |
57 (81.4) |
50 (68.5) |
58 (82.9) |
58 (78.4) |
| Current smoking, n (%) |
4 (5.7) |
9 (12.3) |
7 (10.0) |
6 (8.1) |
| eGFRcys, mL/min/1.73 m2 (SD)‡ |
93.6 (14.3) |
89.2 (16.1) |
88.6 (15.8) |
82.6 (16.2) |
| eGFRcreat, mL/min/1.73 m2 * |
92.5 ± 9.6 |
89.9 ± 10.6 |
89.5 ± 11.5 |
86.8 ± 12.2 |
| CKD (eGFRcys), n (%) |
2 (2.9) |
5 (6.8) |
4 (5.7) |
2 (2.7) |
BMI, body mass index; CKD, chronic kidney disease; eGFRcys, estimated glomerular filtration rate based on cystatin C; HDL, high-density lipoprotein; LDL, low-density lipoprotein; eGFRcreat, estimated glomerular filtration rate based on serum creatinine; SD, standard deviation.
Values represent number (%) or mean (SD). When the trend test observed significant differences, p values were denoted as follows: * <0.05; † <0.01; ‡ <0.001; § <0.0001.
Table 2
Participant baseline characteristics (women)
2
|
Q1 (n = 137)
VFA ≤30 cm2 |
Q2 (n = 185)
30< VFA ≤50 cm2 |
Q3 (n = 184)
50< VFA ≤70 cm2 |
Q4 (n = 159)
70< VFA cm2 |
| Age, years (SD)† |
60.1 (8.6) |
61.9 (8.8) |
62.5 (8.0) |
63.3 (8.2) |
| Waist circumference, cm (SD)§ |
68.7 (3.5) |
75.6 (3.0) |
81.2 (3.9) |
89.3 (6.0) |
| BMI, kg/m2 (SD)§ |
18.2 (1.5) |
19.7 (1.4) |
21.5 (1.6) |
24.1 (2.7) |
| Systolic blood pressure, mmHg (SD)§ |
105.6 (14.9) |
107.9 (15.6) |
111.9 (16.8) |
117.4 (15.1) |
| Diastolic blood pressure, mmHg (SD)§ |
65.1 (10.5) |
65.7 (9.5) |
67.9 (10.3) |
72.2 (10.2) |
| Fasting blood glucose level, mg/dL (SD)§ |
85.6 (6.5) |
88.5 (8.2) |
89.1 (7.3) |
91.6 (8.6) |
| HbA1c, %† |
5.6 (0.3) |
5.6 (0.3) |
5.7 (0.3) |
5.8 (0.3) |
| Total cholesterol, mg/dL (SD) |
219.7 (35.4) |
219.5 (32.3) |
222.7 (30.3) |
223.9 (30.3) |
| HDL-cholesterol, mg/dL (SD)§ |
77.5 (16.2) |
71.5 (14.7) |
68.8 (14.6) |
62.0 (12.8) |
| LDL-cholesterol, mg/dL (SD)§ |
130.2 (29.7) |
133.4 (27.4) |
137.3 (26.5) |
141.3 (27.7) |
| Triglycerides, mg/dL (SD)§ |
60.1 (26.7) |
72.9 (26.9) |
83.4 (34.2) |
103.6 (62.5) |
| High blood pressure, n (%)* |
9 (6.6) |
15 (8.1) |
14 (7.6) |
25 (15.7) |
| Glucose intolerance, n (%)§ |
7 (5.1) |
23 (12.4) |
30 (16.3) |
44 (27.7) |
| Hypercholesterolemia, n (%)‡ |
52 (38.0) |
80 (43.2) |
92 (50.0) |
90 (56.6) |
| Current alcohol consumption, n (%) |
49 (35.8) |
74 (40.0) |
73 (39.7) |
65 (40.9) |
| Current smoking, n (%) |
1 (0.7) |
3 (1.6) |
2 (1.1) |
1 (0.6) |
| eGFRcys, mL/min/1.73 m2 (SD)§ |
97.6 (12.8) |
95.4 (12.3) |
92.9 (12.2) |
88.2 (14.1) |
| eGFRcreat, mL/min/1.73 m2 |
95.9 ± 8.9 |
95.3 ± 9.8 |
94.0 ± 9.6 |
93.6 ± 10.4 |
| CKD (eGFRcys), n (%)† |
0 (0.0) |
0 (0.0) |
1 (0.5) |
6 (3.8) |
BMI, body mass index; CKD, chronic kidney disease; eGFRcys, estimated glomerular filtration rate based on cystatin C; HDL, high-density lipoprotein; LDL, low-density lipoprotein; eGFRcreat, estimated glomerular filtration rate based on serum creatinine; SD, standard deviation.
Values represent number (%) or mean (SD). When the trend test observed significant differences, p values were denoted as follows: * <0.05; † <0.01; ‡ <0.001; § <0.0001.
Fig. 1 shows the association between quartiles of VFA and eGFRcys in ANCOVA. For men, the highest VFA quartile group (Q4) exhibited significantly lower eGFRcys compared with the lowest VFA quartile group (Q1) in each model (model 1: 93.7 [95% confidence interval (CI), 90.7–96.8] vs. 82.3 [95% CI, 79.3–85.3], p < 0.0001; model 2: 93.1 [95% CI, 90.1–96.2] vs. 82.1 [95% CI, 79.1–85.0], p < 0.0001; model 3: 93.5 [95% CI, 89.8–97.2] vs. 81.6 [95% CI, 77.9–85.3], p = 0.0009). Increases in VFA contributed monotonically to a decrease in eGFRcys independent of BMI (Table S1). We observed no significant eGFRcys decrease in the Q2 and Q3 groups compared with the Q1 group.
Among women, the Q4 group displayed significantly lower eGFRcys than the Q1 group in models 1 and 2 (95.6 [95% CI, 94.0–97.3] vs. 89.5 [95% CI, 87.9–91.0] in model 1, p < 0.0001; 95.8 [95% CI, 94.1–97.5] vs. 89.4 [95% CI, 87.8–90.9] in model 2, p < 0.0001), whereas no significant association was found in model 3. Increased VFA was not apparently associated with eGFRcys, but increased BMI contributed to lower eGFRcys (Table S2). Compared with the Q2 and Q3 groups, the Q1 group exhibited no significant eGFRcys decrease. BMI and VFA showed a linear association in men but a varied and curvilinear association in women (Fig. S1).
Scatter plots showed that there was a linear relationship between VFA and waist circumference (Fig. S2). However, the association between quartiles of waist circumference and eGFRcys in ANCOVA (Fig. 2) showed no significant association in model 3 in either men or women. In the sensitivity analysis, the results remained unchanged after excluding individuals with some metal implants in their bodies (data not shown) or also after excluding CKD participants (Fig. 3). The Q4 group had significantly lower eGFRcreat than the Q1 group did in model 1 (p = 0.0005) and model 2 (p = 0.0013) in men, although no significant association was found in model 3. In women, no significant differences of adjusted means of eGFRcreat between groups were shown in all models (Fig. S3).
Discussion
This study establishes a significant association between high levels of VFA and lower eGFRcys levels independent of risk factors for cardiovascular diseases, such as glucose intolerance and hypercholesterolemia, in men and women, as well as independent of BMI in men. Moreover, high VFA levels associated with mild decreased renal function even in individuals without CKD.
Metabolic syndrome, which is highly related to VFA, reportedly leads to various health-related problems, including renal function decline [1]. Because the abdominal circumference reflects VFA, the Examination Committee of the Criteria for Metabolic Syndrome, Japan, adopted waist circumference as an essential component applicable to general physicians [25]. In this study, adjusted means of eGFRcys did not exhibit significant differences among the quartile groups based on waist circumference independent of BMI in both men and women but did reveal significant differences among the groups based on VFA values in men. In another study, the VFA measured by the BIA method, which can be easily obtained, strongly correlated with VFA values measured by X-ray CT [26]. Accordingly, our findings are valuable to demonstrate the utility of measuring VFA using the BIA method.
In the association between VFA and decreased renal function, there is a likely mechanism that cytokine imbalances are secreted by the visceral fat. Plasma concentrations of some proinflammatory adipokines, such as interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), C-reactive protein, and resistin, are elevated in individuals with metabolic syndrome, whereas the levels of other anti-inflammatory adipokines, such as adiponectin, are decreased. Perhaps, cytokine imbalances secreted by visceral fat could contribute to insulin resistance—typical of type 2 diabetes—which leads to the progression of renal disease by worsening renal hemodynamics due to various mechanisms like an activated sympathetic nervous system and increased sodium reabsorption [27, 28].
In this study, the association between VFA and eGFRcys decline weakened after adjusting for BMI and different trends in BMI were observed for different groups of VFA in women. At least statistically, these findings suggest that BMI has a relatively stronger effect on eGFRcys decline than VFA in women. However, the pathophysiological mechanism is unknown; further research should be warranted. VFA was calculated by the electrical resistance determined by visceral fat and the waist circumference at the umbilical level. Croft et al. reported that waist circumference at the umbilicus underestimates the true waist circumference [29]. It is suggested that true VFA in women may have been underestimated owing to skeletal fracture and fat distribution. Hence, we assumed no significant association between VFA and eGFRcys adjusted for BMI in women.
Additional analysis revealed a similar association between high VFA and low eGFRcys levels in individuals without CKD, suggesting an association between high VFA levels and mild decreased renal function even in a healthy population whose renal function was considered to be normal. Accordingly, the follow-up of VFA is, perhaps, useful in renal function screening during health checkups for the general population, although we need to confirm the causal relationship between VFA and renal function in longitudinal studies. Kang et al. performed a VFA measurement using the BIA method on participants undergoing a medical examination and conducted a trend test for eGFRcreat in three groups of VFA-level tertiles [30], demonstrating that high VFA resulted in lower eGFRcreat; however, they evaluated eGFRcreat and performed univariate analyses on participants with CKD. In addition, Yoon et al. illustrated that high VFA using the BIA method correlated with low eGFRcreat using multivariate linear regression analysis adjusted for sex, age, and risk of cardiovascular diseases [11]; however, they did not measure eGFRcys and excluded individuals with eGFRcreat <60 mL/min/1.73 m2 at enrollment. The findings of this study show that eGFRcys can detect the association between VFA and mild decline in renal function compared to eGFRcreat. As previously mentioned, eGFRcys has advantages over eGFRcreat in terms of estimating glomerular filtration at some points [12-15]. Considering these findings, eGFRcys appears to be helpful for assessing more sensitive renal function in the general population. Accordingly, our results with eGFRcys, which detects a mild decline in renal function, seems to help assess early decline in renal function in the general population.
This study has several limitations. First, being a cross-sectional study, we could not establish a causal relationship between high VFA and low eGFRcys levels. We have conducted surveys every 2 years; however, we have not been able to measure VFA and eGFRcys with each survey. In addition, it is assumed that a significant decline in renal function does not occur over time in the healthy population. Therefore, we believe that the longitudinal relationship between VFA and eGFRcys should be reassessed using longer follow-up periods. Second, VFA was measured at the umbilical region in the standing position by the BIA method, and other VFA measurement methods, such as CT, were not assessed. Moreover, as we did not measure VFA by CT, the correlation of each VFA measurement method could not be studied. However, a strong correlation can be obtained between the VFA measurement result of EW-FA90 and the VFA measurement result by X-ray CT [26]. Third, in the present study we did not collect information on urinary analysis; thus, we defined CKD using eGFRcys alone. Finally, our study participants constituted apparently healthy population without a history of malignant neoplasms, cerebro-cardiovascular disease, and not being treated for diabetes, hypertension, or dyslipidemia at baseline survey, and were not representative of the general population in Japan; hence, this study’s findings have limited generalizability. Nevertheless, we examined this population because we could examine the association between VFA and mild decline in eGFRcys without CKD.
In conclusion, this study indicates an association between increased VFA and decreased eGFRcys in the Japanese urban population, even in participants without CKD. Hence, this study suggests that simple VFA measurement would be beneficial to predict decreased renal function. Nevertheless, further longitudinal studies are warranted to determine the causal relationship between VFA and renal function decline.
Acknowledgments
We are grateful to the volunteers involved in the administration of the KOBE study. We thank all the research staff for their valuable contribution.
Funding
This study was supported by grants from the Regional Innovation Cluster Program, Global Type, Ministry of Education, Culture, Sports, Science and Technology; a Grant-in-Aid for Scientific Research from the Japan Society for the Promotion of Science (B 16H05249, C 16K09157, C 16K09071, C 16 K09083, C 17K09224); a Grant-in-Aid for Young Scientist from the Japan Society for the Promotion of Science (B 17K15834, B 15K19232, B 16 K16618); Comprehensive Research on Cardiovascular and Life-Style Related Disease: H29-Junkankitou-Ippan-003, H30-Junkankitou-Ippan-003, H30-Junkankitou-Ippan-005, and 19FA1008, and 22FA1006.
Conflict of Interest
A. Tanabe is an employee of Daiichi Sankyo Co., Ltd. Other authors have no conflict of interest to declare.
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