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INTRODUCTION
Chronic kidney disease (CKD) is a public health problem affecting around 10% of the world's population1,2, with the highest overall incidence in low- and middle-income countries3. At the same time, obesity is growing exponentially, affecting more than 600 million people4.
Obesity is possibly a strong risk factor with a direct impact on the development of CKD2. Studies suggest that, in addition to obesity, localized fat in the abdominal region is an important factor for renal dysfunction5,6,7. Total abdominal adipose tissue includes visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT), which are predictors for different health outcomes. VAT is the component that exerts the greatest deleterious effects on metabolic and hemodynamic parameters8,9,10. Madero et al. demonstrated that VAT is significant association with renal function decline and risk of developing CKD11. Moreover, beyond the abdominal cavity, adipose tissue stored in ectopic locations outside of subcutaneous tissue such as in muscle, is also associated with kidney function decline11,12.
Although it is well known that global obesity and abdominal obesity increase the risk of hypertension (HT) and diabetes mellitus (DM), which are the main causes of CKD13, studies suggest the involvement of other metabolic pathways relating excess body fat and visceral fat to higher risk of CKD14. In this regard, the association between abdominal fat and CKD is not fully elucidated, especially in populations in developing countries, such as Brazil, where studies are scarce. Thus, this study aims to evaluate the relationship between abdominal fat components (visceral and subcutaneous fat) and renal function in outpatients in Northeast Brazil.
METHODS
Study population
This was an observational, case-series study conducted with 146 patients at a general nursing outpatient clinic of a public university hospital that is a reference hospital for cardiology in the Brazilian Northeast in 2013.
The sample was designed based on voluntary participation and included individuals of both sexes, aged ≥20 years, without previous diagnosis of CKD. Patients were invited at the first consultation with a nutritionist.
We excluded individuals with hepatomegaly and/or splenomegaly, ascites, recent abdominal surgery, pregnant women, and women who had children ≤6 months prior to the survey because these characteristics could influence the measurement of intra-abdominal fat and/or anthropometric measurements. In addition, we also considered ineligible individuals, those with physical limitations, which could prevent anthropometric measurements. Patients with acute kidney injury were also excluded from this study.
The sample size was calculated assuming a 5% α error, a β error of 20%, an estimated average correlation between the VAT/SAT ratio and GFR of 0.6 (p) and a variability of 0.12 (d2). Using the formula
Evaluation of visceral and subcutaneous adipose tissue
VAT was evaluated by computed tomography, without contrast, of the abdomen, performed at the medical care service by a single observer trained in the study protocol. The examination was performed after a four-hour fast with the patient in a supine position. The tomographic cut was obtained with the following radiographic parameters: 140 kV and 45 mA at the level L4 and thickness of 10 mm. Total abdominal fat area and VAT were manually determined by a radiologist using free cursor circumventing each region. VAT area was measured considering as limits the inner edges of the rectus abdominis, internal oblique and quadratus lumborum muscles, excluding the vertebral body and including retroperitoneal, mesenteric and omental fat. SAT was then calculated by subtracting the VFA from total abdominal fat area. All fat areas were expressed in cm2. To identify the adipose tissue, density values of −50 and −250 Hounsfield units were used15,16.
A visceral fat volume greater than 130 cm2 represented visceral obesity diagnosis16,17. However, due to a lack of individuals within the normal range, these values were divided into tertiles. The value equal to or greater than the third tertile was considered as the cutoff point: VAT ≥ 284 and 380 cm2 and SAT ≥ 545 and ≥ 485 cm2 for women and men, respectively. A VAT/SAT ratio ≥ 0.4 was considered the cutoff point to indicate individual predisposition to accumulate visceral fat18.
Evaluation of renal function
To assess renal function, the estimated glomerular filtration rate (GFR) was calculated using the formula of the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI)19. The cut-off point considered for renal function changes in most studies is GFR < 60 ml/min/1.73 m2(19,20,21).
Socio-demographic, anthropometric and clinical evaluations
Socio-demographic data (age, gender, years of study) and anthropometric data (weight, height, waist circumference, hip circumference) were collected. Body weight and height of patients were measured using techniques recommended by Lohman, Roche and Martorell22. A platform scale with a capacity of 150 kg (100 g precision) and a coupled stadiometer with a precision of 1 mm were used. Weight and height values were used for the calculation of body mass index (BMI), and a value of ≥30.0 kg/m2 was used for the diagnosis of obesity23.
Abdominal circumference (AC) and hip circumference (HC) were measured using a non-extendible measuring tape in accordance with the norms recommended by the World Health Organization23. Abdominal obesity was defined in this study as AC >102 cm for men and >88 cm for women, which represents very high risk23.
All measurements were collected in duplicate by a single observer and repeated when the measuring error among them was greater than 0.1 cm (stature, AC and HC) or 0.1 kg (weight). The final measurement was the average between the two closest values. Waist-to-height ratio (WHtR) was calculated by the relation between AC (cm) and height (cm). Waist-hip ratio (WHR) was determined by the division of AC (cm) and HC (cm).
We also considered the presence of clinical co-morbidities such as HT and DM when the patient reported a previous diagnosis made by a physician, used antihypertensive and/or hypoglycemic drugs, respectively, and/or there was a record of it in the medical record.
Statistical analysis
Data were analyzed using the software Statistical Package for Social Sciences (SPSS), version 13.0 (SPSS Inc., Chicago, IL, USA). Continuous variables were tested for distribution normality by the Kolmogorov Smirnov test and, as if they presented a normal distribution, were expressed as mean and standard deviation and compared using the Student t test. For description of proportions, the binomial distribution was approximated to the normal distribution by a 95% confidence interval. Pearson's linear correlation was used to evaluate the correlation between GFR and visceral, subcutaneous and anthropometric fat parameters. Proportions were compared using Pearson's Chi Square test or by Fisher Exact test. A simple linear regression was used to evaluate the explanatory power of VAT, SAT and VAT/SAT ratio in relation to GFR. The statistical significance was defined as p<0.05.
The protocol of this study was guided by the ethical standards for research involving humans provided for in the Resolution no. 466/12 of the National Health Council and was submitted to the Research Ethics Committee for Research with Humans of the University of Pernambuco. It was approved under the protocol no. 271.400/2013.
RESULTS
We evaluated 146 patients with a mean age of 52.5 ± 13.2 years, 71.9% of whom were female. Mean BMI was within the obesity range for both sexes. The prevalence of HT and DM was 56.9% and 25.0%, respectively, being similar for both sexes.
Table 1 shows that, for similar average age and BMI, males had higher mean values of VAT and VAT/SAT ratio. In addition, mean GFR was similar for both genders and was within the normal range: 2.8% of patients presented an GFR < 60ml/min/1.73 m2 (data not shown in table 1).
Table 1 Characteristics of the sample (mean plus standard deviation) according to the gender of outpatients in a hospital in the Brazilian Northeast (2013).
| Parameters | Males (n= 41) Values | Females (n= 105) Values | p |
|---|---|---|---|
| Age (years) | 52.8 (13.9) | 52.4 (13.0) | 0.859 |
| Years of study | 10.4 (4.22) | 10.0 (4.24) | 0.682 |
| HAS, n (%) | 25.0 (30.5) | 57.0 (69.5) | 0.667 |
| DM, n (%) | 9.0 (25.0) | 27.0 (75.0) | 0.749 |
| BMI (kg/m2) | 30.4 (5.90) | 31.6 (6.12) | 0.304 |
| WHtR | 0.631 (0.111) | 0.625 (0.114) | 0.405 |
| WHR | 1.05 (0.143) | 0.924 (0.121) | < 0.001 |
| AC (cm) | 106 (15.2) | 100 (13.4) | 0.024 |
| TA FA (cm2) | 787 (224) | 754 (179) | 0.355 |
| VAT (cm 2) | 331 (115) | 251 (78.9) | < 0.001 |
| SAT (cm 2) | 457 (165) | 502 (155) | 0.124 |
| VAT/SAT ratio | 0.784 (0.305) | 0.544 (0.213) | < 0.001 |
| eGFR (ml/min/1.73 m2) | 104 (21.0) | 103 (18.1) | 0.913 |
BMI: Body mass index; WHtR: waist-to-height ratio; WHR: waist-hip ratio; AC: abdominal circumference; TAFA: total adipose tissue; VAT: visceral adipose tissue; SAT: subcutaneous adipose tissue; eGFR: Estimated glomerular filtration rate according to the CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration). p-value: Student t test (for means) and Chi-square (for proportions).
Correlations between GFR, abdominal fat tissue components and anthropometric variables are presented in table 2. In females, GFR was negatively correlated with VAT (r= −0.22, p= 0.025), VAT/SAT ratio (r= −0.23, p= 0.019) and WHR (r= −0.23; p= 0.023). Among men, GFR was negatively correlated with VAT/SAT ratio (r= −0.47, p= 0.002) (Table 2).
Table 2 Pearson's correlations between estimated glomerular filtration rate (GFR), abdominal fat components and anthropometric variables, according to sex and age, among outpatients from a hospital in Northeast Brazil, 2013.
| FEMALE (n = 105) | ||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| VAT | SAT | VAT/SAT ratio | BMI | AC | WHtR | WHR | ||||||||
| GFR | -0.22 | 0.025 | 0.12 | 0.214 | -0.23 | 0.019 | 0.05 | 0.590 | -0.06 | 0.524 | -0.20 | 0.050 | -0.23 | 0.023 |
| MALE (n= 41) | ||||||||||||||
| VAT | SAT | VAT/SAT ratio | BMI | AC | WHtR | WHR | ||||||||
| GFR | -0.28 | 0.078 | 0.30 | 0.055 | -0.47 | 0.002 | 0.23 | 0.156 | 0.07 | 0.686 | 0.01 | 0.940 | -0.21 | 0.204 |
* GFR: Estimated glomerular filtration rate according to the CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration); BMI: Body mass index; AC: abdominal circumference; WHtR: waist-to-height ratio; WHR: waist-hip ratio; VAT: visceral adipose tissue; SAT: subcutaneous adipose tissue.
We observed that patients with a VAT ≥ third tertile had a lower mean GFR, a great frequency of DM and HT, were older and had higher mean values of anthropometric parameters (BMI, AC, WHR, and WHtR). In relation to SAT, patients in the highest tertile were younger, had more education, higher mean BMI, AC and WHrT, and a higher average GFR (Table 3).
Table 3 Comparative analyses of demographic, anthropometric and clinical variables according to visceral (VAT) and subcutaneous adipose tissue (SAT) tertile in adults recruited from an outpatient clinic in Northeast Brazil (2013).
| Variable | VAT | SAT | ||||
|---|---|---|---|---|---|---|
| 1st and 2nd | 3rd | p-value | 1st and 2nd | 3rd | p-value | |
| tertile | tertile** | tertile | tertile*** | |||
| (n= 98) | (n= 48) | (n= 97) | (n= 49) | |||
| Female (n, %) | 70.0 (71.4) | 35.2 (72.9) | 0.851 | 70.2 (72.2) | 35.4 (71.4) | 0.926 |
| Age, years (mean/SD) | 51.1±14.1 | 55.4±10.6 | 0.046 | 55.1±13.0 | 47.4±12.0 | 0.001 |
| Hypertension (n, %) | 50.3 (51.4) | 32.4 (68.1) | 0.060 | 54.1 (56.3) | 28.3 (58.3) | 0.812 |
| Diabetes (n, %) | 18.5 (18.6) | 18.3 (38.3) | 0.010 | 25.1 (26.0) | 11.3 (22.9) | 0.683 |
| Years of study (mean, SD) | 10.3±4.22 | 9.8±4.13 | 0.536 | 9.41±4.53 | 11.6±2.94 | 0.001 |
| BMI, kg/m2 (mean, SD) | 29.7±13.3 | 34.4±5.72 | <0.001 | 28.3±4.33 | 37.0±4.6 | <0.001 |
| AC, cm (mean, SD) | 97.9±13.3 | 111±11.6 | <0.001 | 96.0±11.8 | 114±10.0 | <0.001 |
| WHR (mean, SD) | 0.951±0.101 | 1.043±0.09 | <0.001 | 0.933±0.121 | 0.922±0.143 | 0.801 |
| WHtR (mean, SD) | 0.599±0.135 | 0.697±0.143 | <0.001 | 0.604±0.100 | 0.700±0.111 | <0.001 |
| eGFR, ml/min/1.73 m2 (mean, DP) | 108±19.9 | 99.0±15.6 | 0.048 | 101 ±19.9 | 109±17.6 | 0.016 |
* BMI: Body mass index; AC: abdominal circumference; WHR: waist-hip ratio; WHtR: waist-to-height ratio; eGFR: estimated glomerular filtration rate according to the CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration);
**3rd VAT Tertile for men: > 380.7 cm2; 3rd VAT tertile for women: > 284.2 cm2.
***3rd SAT tertile for men: > 485.2 cm2; 3rd SAT tertile for women: > 545.6 cm2; p-value: *Student's t test to compare means and Chi square test to compare proportions.
Comparative analysis of demographic, anthropometric and clinical variables with the VAT/SAT ratio evidenced that individuals with a higher predisposition for visceral fat accumulation (VAT/SAT ratio ≥ 0.4) were older, had a higher proportion of HT, lower BMI, lower WHtR, lower AC and lower GFR (Table 4).
Table 4 Comparative analyses of demographic, anthropometric and clinical variables according to ratio between visceral and subcutaneous adipose tissue (VAT/SAT) in adults recruited from an outpatient clinic in Northeast Brazil (2013).
| Variable | VAT/SAT ratio | ||
|---|---|---|---|
| < 0.4 | ≥ 0.4 | p-value | |
| n = 32 | n = 114 | ||
| Female (n, %) | 26.2 (81.3) | 79.2 (69.3) | 0.184 |
| Age, years (mean/SD) | 46.0 ± 13.8 | 54.4 ± 12.5 | 0.001 |
| Hypertension (n, %) | 13.0 (40.6) | 69.5 (61.6) | 0.035 |
| Diabetes (n, %) | 7.25 (21.9) | 29.5 (25.9) | 0.643 |
| Years of study (mean, SD) | 11.3 ± 3.63 | 9.81 ± 4.25 | 0.086 |
| BMI, kg/m2 (mean, SD) | 34.2 ± 5.73 | 30.4 ± 5.89 | 0.002 |
| AC, cm (mean, SD) | 106 ± 11.9 | 101 ± 14.5 | 0.056 |
| WHR (mean, SD) | 0.921 ± 0.143 | 0.879 ± 0.121 | 0.057 |
| WHtR (mean, SD) | 0.701 ± 0.123 | 0.630 ± 0.100 | 0.022 |
| eGFR (mean, SD) | 112 ± 19.5 | 101 ± 18.0 | 0.003 |
* BMI: Body mass index; AC: abdominal circumference; WHR: waist-hip ratio; WHtR: waist-to-height ratio; GFR: estimated glomerular filtration rate according to the CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration); p-value: *Student's t test to compare means and Chi square test to compare proportions.
To explain the relationship between GFR and abdominal fat compartments, we performed a simple linear regression and found that, in males, the decrease in GFR could be explained in 21.8% of cases by the VAT/SAT ratio; for females, both VAT and VAT/SAT ratio were associated with a decrease in GFR (r2= 4.8% and r2= 5.3%, respectively) (Table 5).
Table 5 Simple linear regression between visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT) and VAT/SAT ratio and glomerular filtration rate estimates in adults attended in an outpatient clinic in a hospital in Northeast Brazil (2013).
| Male (n= 41) eGFR |
|||||
|---|---|---|---|---|---|
| Variable | B | Standard error | β | p-value* | r2** |
| VAT | -1.545 | 0.853 | -0.282 | 0.078 | 7.9 |
| SAT | 2.112 | 1.068 | 0.305 | 0.055 | 9.3 |
| VAT/SAT ratio | -0.077 | 0.002 | -0.467 | 0.002 | 21.8 |
| Female (n= 105) eGFR |
|||||
|---|---|---|---|---|---|
| Variable | B | Standard error | β | p-value* | r2** |
| VAT | -0.945 | 0.416 | -0.220 | 0.025 | 4.8 |
| SAT | 1.036 | 0.829 | 0.123 | 0.214 | 1.5 |
| VAT/SAT ratio | -0.003 | 0.001 | -0.230 | 0.019 | 5.3 |
*Wald test.
**Coefficient of determination in %. eGFR: Estimated glomerular filtration rate according to the CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration).
DISCUSSION
The data presented here evidence a certain specificity because they were obtained from a sample of individuals who sought nutritional care in a public reference hospital in cardiology, which explains the high proportion of DM and HT in addition to BMI averages within the range of obesity for both sexes. In addition, very high values of anthropometric parameters, VAT and VAT/SAT ratio were evidenced, representing a population with a high level of global, abdominal and visceral adiposity. These last two parameters were related to lower GFR.
Abdominal obesity has been related to lower GFR and to a greater decrease in this rate over the years6,7. In this study, the mean value of GFR was within the normal range, and the percentage of individuals with an GFR < 60 ml/min/1.73 m2 was 2.8%. This low percentage of individuals with a possible diagnosis of CKD may relate to the exclusion criteria that included patients with a previous diagnosis of this disease. That is, the purpose of this study was to assess whether patients with high levels of adiposity already had some indications of early-stage renal damage. It is important to consider that these patients with a reduction in GFR do not necessarily correspond to patients with CKD, since the criteria for diagnosis and other markers of renal damage were not evaluated.
In our study, we also observed that patients with VAT ≥ 3rd tertile were older and had a lower mean GFR. The literature shows that as individuals age, changes in body composition occur, so that fat-free mass decreases and fat mass generally increases. Fat is stored in visceral and intramuscular compartments, rather than subcutaneously, as in young adults24. Therefore, age is an important variable predicting the accumulation of VAT25.
Obesity leads to glomerulomegaly, segmental glomerulosclerosis and obesity-related glomerulopathy26,27,28. In a study with 6,475 participants without DM, increased BMI and AC were associated with lower GFR and higher frequency of CKD29. Abdominal obesity, defined as AC >102 cm for men and >88 cm for women, was associated with an increased risk of kidney disease (OR 1.4), even after adjustment for other components of the metabolic syndrome, such as dyslipidemia, hyperglycemia and HT29. In South Korea, Evangelista et al., in a cohort from 2008 to 2014, found that the prevalence of general obesity and abdominal obesity was highest in stage 2 CKD and stage 3a was significantly associated with abdominal obesity. Furthermore, the association between general obesity/abdominal obesity and CKD disappeared in the more advanced stages of kidney disease30.
Although it is well known that global obesity and abdominal obesity increase the risk of HT and DM, which are the main causes of CKD11, studies suggest the involvement of other metabolic pathways, which independently relate to excess body and visceral fat and higher risk of CKD14.
Few studies have evaluated the influence of abdominal fat components on the risk of declining renal function. It has been shown that the accumulation of VAT may cause renal compression with a consequent increase in intrarenal pressure31, thus increasing sodium chloride (NaCl) reabsorption by the Henle loop, reducing the amount of NaCl reaching the macula dense32. This process can cause, via tubuloglomerular feedback, to a reduction in the afferent arteriolar resistance and increases in renal blood flow, GFR and renin secretion in order to restore the sodium balance. Such compensatory mechanisms may also lead to increased glomerular wall tension and hypertrophy, changes that may cause renal damage, glomerulosclerosis and, ultimately, nephron loss33.
A recent study evaluating men and women from the U.S. with a mean age of 74 ± 3.0 years showed that SAT, VAT, BMI and WC were all significantly associated with a decline in kidney function and that only VAT remained a significant risk factor for incident CKD after adjustment for possible confounding factors11.
In our investigation, low GFR was observed for patients with higher VAT/SAT ratio values. Lee et al.34, evaluated 425 Korean women without a CKD diagnosis, HT, DM or CVD, and compared clinical and metabolic characteristics with VAT/SAT ratio ≥ 0.4 and < 0.4. Authors found that women who had a VAT/SAT ratio ≥ 0.4 were older, had a higher AC, higher blood pressure, higher fasting blood glucose and lower GFR. When evaluating the correlation between VAT and eGFR the same authors found a negative correlation, similar to the findings of our study. Kim et al.35, evaluating 929 diabetics with a mean age of 55 years, recruited from a hospital in South Korea, also found a negative correlation (r= −0.158; p= 0.001) between VAT and GFR, whereas SAT was not correlated with lower GFR.
VAT/SAT ratio seems to provide information independent from measurements of generalized or abdominal adiposity. The absolute amount of VAT seems to say little about the relative distribution of abdominal tissue36 and does not reflect a predisposition to visceral or subcutaneous fat storage. Therefore, to estimate the predisposition to visceral accumulated fat, Kaess et al.36, suggests the VAT/SAT ratio as a more relevant metric for abdominal fat composition and thus a better predictor of cardiometabolic changes36,37,38. However, there are few studies evaluating this ratio in relation with renal dysfunction. Lee et al.34, studying apparently healthy Korean women, found that for a VAT/SAT ratio ≥ 0.4, lower GFR was observed.
In our study, the results of simple linear regressions showed that, for males, the VAT/SAT ratio explained 21.8% of the decrease in GFR. For females, VAT explained 4.8% and the VAT/SAT ratio explained 5.3%. Lee et al.34, conducting a multiple linear regression analysis, found that VAT accounted for 29% of the decrease in GFR in Korean women. Such high results, when compared to ours, may possibly be explained by ethnic differences. Of course, our results should be carefully evaluated, given the limitations of the study described in the paragraphs below.
Race is an important aspect to be considered in the analysis of body composition, and different results in distinct populations may be partially explained by this aspect. The Brazilian population has specific racial characteristics marked by a complex miscegenation. Therefore, results of studies conducted with other ethnic groups should not be generalized to all populations. This reinforces the need for more studies on the components of the abdominal adipose tissue with the Brazilian population, where they are still very scarce.
The cross-sectional nature of our study also limits the determination of causality between VAT and renal function deterioration. In addition, this study was conducted in a single center; therefore, the generalization of our results to other population groups should be interpreted with caution. In addition, it is important to consider that the changes in glycemia and blood pressure were not evaluated, considering only self-reported diagnosis. The absence of these data may have influenced the findings.
It is difficult to determine VAT in the population and more studies are needed to define simple and population-based methods for the quantification of VAT, as well as predictive equations to estimate the VAT/SAT ratio which can be used for the screening of CKD at early stages.
