Abstract
Accumulation of fat in renal sinus and hilum is associated with hypertension development. We evaluated the relationship between perirenal fat and hypertension in a population of morbidly obese patients and the potential variations after sleeve‐gastrectomy. Two hundred and eighty‐four morbidly obese patients were included in the study, and 126 underwent sleeve‐gastrectomy. At baseline and 10‐12 months after surgery, we evaluated anthropometric parameters, blood pressure, glycometabolic, and lipidic assessment, and performed an ultrasonographic evaluation of visceral fat area and perirenal fat thickness. The perirenal fat thickness in hypertensive obese was higher than in nonhypertensive (13.6 ± 4.8 vs 11.6 ± 4.1, P = 0.001). It showed a significant direct correlation with age, waist circumference, BMI, systolic blood pressure (SBP), insulinemia, HOMA‐IR, glycated hemoglobin, and creatinine. The independent predictors (R 2 = 0.129) of SBP were perirenal fat thickness (β = 0.160, P = 0.022) and age (β = 0.175, P = 0.011). After surgery, perirenal fat thickness significantly decreased (from 13 ± 4 to 9 ± 4 mm, P <0.001). In the 89 hypertensive obese patients who underwent sleeve‐gastrectomy, we observed a significant decrease in antihypertensive medications needed. Sixteen patients suspended therapy. The perirenal fat thickness in obese patients could be a valuable tool to define the risk of developing hypertension, providing the clinician with an additional parameter to define those who need a more aggressive treatment and could benefit most from bariatric surgery.
Keywords: adipose tissue, bariatric surgery, hypertension, obesity, perirenal fat
1. INTRODUCTION
Nowadays, it is well known that obesity is associated with numerous comorbidities such as cardiovascular disease (myocardial infarction and ischemic stroke), type 2 diabetes mellitus, dyslipidemia, hypertension, and some types of neoplasia. Obesity seems to be the cause of hypertension in 77% of hypertensive men and 64% of hypertensive women, and its prevalence increases from 18.1% in lean patients to 52.5% in patients with grade III obesity.1, 2 Population studies have shown that blood pressure is closely correlated with anthropometric indexes of obesity such as BMI, waist circumference (WC), and waist/hip ratio (W/H ratio).3, 4 It has also been shown that weight gain is associated with an increase in blood pressure, while weight loss results in a decrease in pressure values in obese and normotensive patients. Excessive weight gain is a valid predictor of hypertension development,4 and weight loss is effective in primary prevention of hypertension.5
The perirenal adipose tissue is contained in the space extending from the internal and external margins of the kidney and the renal fascia, including also the adipose tissue of renal sinus and hilum. The accumulation of fat in the renal sinus has been associated with more severe and resistant hypertension6 and has been documented that fat accumulation in renal hilum lead to a compression of lymphatic and venous vessels and ureters, resulting in increased hydrostatic pressure and activation of renin‐angiotensin‐aldosterone system (RAAS) system, responsible for a cascade of events leading to development of hypertension, insulin resistance, and atherosclerosis.7
According to this hypothesis, it has been documented that the accumulation of fat in these sites is associated with hypertension development, even after adjustment for cardiovascular risk factors including visceral fat tissue.6, 8 However, currently, there are no studies investigating, in overweight and obese patients, the possible presence of a close relationship between decrease in perirenal thickness and hypertension remission.
It is well known that bariatric surgery is responsible for a marked improvement in the control of type 2 diabetes, dyslipidemia, obese patient inflammation, and quality of life9; moreover, losing weight leads to a decrease and to a better control of blood pressure.1 Nowadays, bariatric surgery is the most effective tool for obtaining a lasting effect on weight loss and, consequently, achieving a remission of hypertension in obese patient.10
The aim of our study was to evaluate the relationship between perirenal adipose tissue and hypertension in patient with morbid obesity, and the potential variations after sleeve‐gastrectomy (SG).
2. METHODS
Two hundred and eighty‐four morbidly obese patients were included in the study, and 126 underwent sleeve‐gastrectomy. Inclusion criteria were the following: BMI ≥40 or ≥35 kg/m2 in the presence of comorbidities and age between 18 and 65 years old. Exclusion criteria were the following: hepatic or renal failure, heart failure (NYHA II‐IV), secondary causes of obesity and major psychiatric disorders. The study protocol was approved by the Ethics Committee of our Institution, and the study was carried out in accordance with The Code of Ethics of the World Medical Association (Declaration of Helsinki—1964) for human studies. Informed consent was obtained from all participants.
In every patient, at baseline and 10‐12 months after surgery, we evaluated anthropometric parameters (BMI, waist, and hip circumference) and blood pressure (BP); BP was measured by a physician with a mercury sphygmomanometer with the subject sitting for ≥10 minutes in a quiet room, and the average of three measurements taken on nondominant arm was considered for the analysis. The sphygmomanometer cuff size (adult size and large adult size) was adequate to patient arm diameter. High blood pressure was defined as systolic blood pressure (SBP) ≥140 mm Hg or diastolic blood pressure (DBP) ≥90 mm Hg, or chronic assumption of antihypertensive therapy. Hypertension remission was evaluated on the basis of blood pressure decrease under 140/90 mm Hg, decreased assumption of antihypertensive drugs or complete interruption of antihypertensive therapy. Blood was drawn in the morning after a 13‐hours fast and the parameters were determined as follows: glycemia (automated analyser), insulinemia (Elisa), glycated hemoglobin (HbA1C, high‐pressure liquid chromatography), total cholesterol (TC), triglycerides (TG, enzymatic colorimetric method), LDL cholesterol (LDL‐C, Friedewald formula), HDL cholesterol (HDL‐C, enzymatic colorimetric method following precipitation with polyethylene glycol), and creatinine (automated analyser). The Homeostasis Model Assessment‐Insulin resistance (HOMA‐IR) has been used to determine insulin resistance. Diabetes mellitus presence was defined when fasting glycemia ≥126 mg/dL, HbA1C ≥ 6.5% or in case of chronic assumption of antidiabetic therapy, according to WHO criteria.11
Perirenal fat thickness was measured at the right kidney by a single operator using the MyLab 50 ultrasound (Esaote, Italy), with patient in supine position. The probe was placed perpendicularly to the patient's skin at the right abdominal lateral surface, and an ultrasound longitudinal scan of the right kidney was obtained, with the kidney lateral edge parallel to skin surface. During image sampling, the pressure exerted on the probe by the operator was as low as possible in order to obtain a good image resolution without causing adipose tissue compression. Measurement of perirenal fat thickness was taken from the right kidney lower pole to the psoas muscle surface by two skilled investigators who were unaware of patients’ clinical data. This measurement technique was validated by our group. We reported an intraoperator intraclass correlation (ICC) of 0.25 (SE 0.10) and an interoperator ICC of 0.51 (SE 0.15). The visceral fat area (VFA) was measured by a single operator with the MyLab 50 ultrasound (Esaote), using Hirooka formula12: VFA = −9.008 + 1.191 × [distance between the inner face of the abdominal muscle and splenic vein (mm)] + 0.978 × [the distance between the inner abdominal face and the aortic wall of the aorta at the level of the navel (mm)] + 3644 × [fat thickness of the adipose tissue layer of the wall renal artery (mm)]. The intraoperator variability coefficient is 5% (135). The hepatic steatosis was evaluated by an ultrasound semiquantitative method as follows: grade 1 = enhanced echogenicity with preserved visualization of diaphragm and intrahepatic vessels; grade 2 = enhanced echogenicity, posterior attenuation of the ultrasonic beam with preserved visualization of diaphragm and intrahepatic vessels; grade 3 = markedly increased echogenicity, posterior attenuation of the ultrasonic beam and inability to visualize the intrahepatic vessels, the diaphragm and the right hepatic lobe.
2.1. Statistical analysis
Analyses were performed using SPSS software for Windows (version 17.0; SPSS, Inc, Chicago, IL, USA), with significance set at a two‐sided P < 0.05. Values are expressed as mean ± standard deviation. Differences between two groups were calculated by Student’s t test for normally distributed variables and Mann‐Whitney U Test for non‐normally distributed ones. Correlation coefficients were calculated with Pearson or Spearman’s correlation rank tests, as appropriate. Multivariate analysis was performed using stepwise regression, and the variables included in the models were age, perirenal fat thickness, BMI and HbA1C for SBP and age, perirenal fat thickness and SBP for serum creatinine.
3. RESULTS
In the period from October 2013 to January 2017, we enrolled 284 patients with high‐grade obesity awaiting SG intervention. Of these patients, 126 underwent bariatric surgery.
Table 1 shows patients characteristics at baseline. Table 2 shows prevalence of population comorbidities.
Table 1.
Population characteristics at baseline
| Population characteristics | Mean | SD |
|---|---|---|
| Age, y | 44 | 12 |
| Weight, kg | 124 | 24 |
| BMI, kg/m2 | 45 | 7 |
| Waist circumference, cm | 132 | 17 |
| Hip circumference, cm | 139 | 15 |
| Systolic blood pressure, mm Hg | 136 | 16 |
| Diastolic blood pressure, mm Hg | 84 | 10 |
| Visceral fat area, cm2 | 250 | 69 |
| Perirenal fat thickness, mm | 13 | 5 |
| Creatinine, mg/dL | 0.68 | 0.17 |
| Total cholesterol, mg/dL | 189 | 39 |
| HDL, mg/dL | 49 | 14 |
| LDL, mg/dL | 139 | 37 |
| Triglycerides, mg/dL | 152 | 223 |
| Glycemia, mg/dL | 105 | 39 |
| HOMA‐IR | 5.4 | 5.6 |
| Glycated hemoglobin, % | 6.2 | 2.2 |
Data are expressed by mean ± standard deviation (SD).
Table 2.
Prevalence of population comorbidities
| Comorbidities | Known pathology, % | New diagnosis, % | Total, % |
|---|---|---|---|
| Smoke | 28 | ||
| Hypertension | 57 | 43 | 63 |
| Type 2 diabetes mellitus | 69 | 31 | 23 |
| Dyslipidemia | 2 | ||
| Lung diseases | 9 | ||
| Steatosis | |||
| No steatosis | 6 | ||
| Grade 1 | 26 | ||
| Grade 2 | 36 | ||
| Grade 3 | 30 | ||
| Others | 46 | ||
Data are expressed by percentage.
Patients with known hypertension are 103 (57%), with new diagnosis of hypertension 76 (43%). Patients with known diabetes mellitus are 45 (69%), with new diagnosis 20 (31%). One hundred and twenty‐six patients underwent SG and were clinically re‐evaluated after 10‐12 months (Table 3).
Table 3.
Population characteristics before and after sleeve‐gastrectomy. Data are expressed by mean ± standard deviation (SD)
| Presurgery | Postsurgery | P | |||
|---|---|---|---|---|---|
| Mean | SD | Mean | SD | ||
| Weight, kg | 126 | 25 | 93 | 20 | <0.001 |
| BMI, kg/m2 | 45 | 7 | 33 | 6 | <0.001 |
| Waist circumference, cm | 132 | 18 | 107 | 15 | <0.001 |
| Hip circumference, cm | 141 | 14 | 116 | 14 | <0.001 |
| Systolic blood pressure, mm Hg | 138 | 16 | 125 | 14 | <0.001 |
| Diastolic blood pressure, mm Hg | 86 | 10 | 77 | 9 | <0.001 |
| Visceral fat area, cm2 | 253 | 70 | 152 | 54 | <0.001 |
| Perirenal fat thickness, mm | 13 | 4 | 9 | 4 | <0.001 |
| Creatinine, mg/dL | 0.69 | 0.17 | 0.68 | 0.16 | 0.740 |
| Total cholesterol, mg/dL | 195 | 36 | 193 | 37 | 0.564 |
| HDL, mg/dL | 51 | 15 | 56 | 15 | <0.001 |
| LDL, mg/dL | 144 | 33 | 137 | 34 | 0.014 |
| Triglycerides, mg/dL | 148 | 95 | 104 | 51 | <0.001 |
| Glycemia, mg/dL | 106 | 41 | 85 | 19 | <0.001 |
| HOMA‐IR | 5.3 | 5.3 | 1.6 | 1.2 | <0.001 |
| Glycated hemoglobin, % | 6.4 | 3.1 | 5.4 | 0.5 | 0.002 |
Significance set at P < 0.05.
Among the 179 hypertensive patients, 94 (52%) were receiving antihypertensive therapy, and 65 (36%) of these were on polypharmacy (24% assumed two drugs, 8% three drugs, 3% four drugs, and 1% five drugs). Eighty‐five (48%) hypertensive patients did not take any antihypertensive therapy at the time of enrollment (Figure 1).
Figure 1.
Antihypertensive therapy in the study population
In order to clarify the role of perirenal fat in the development of obesity‐related hypertension, we evaluated potential differences in perirenal fat thickness in the whole population before surgery. The thickness of the perirenal fat of hypertensive patients was higher compared to nonhypertensive patients, with mean values of 13.6 ± 4.8 and 11.6 ± 4.1 mm (P = 0.001) respectively.
When comparing the male and female population, a statistically significant difference in the thickness of perirenal fat was also found, with mean values of 15.6 ± 4.9 and 11.6 ± 4 mm (P < 0.001), respectively.
The thickness of perirenal fat in the study population showed a statistically significant direct correlation with SBP and serum creatinine (P < 0.001); it also correlated with age, WC, BMI, insulinemia, HOMA‐IR, and HbA1C (Table 4a).
Table 4.
Univariate (a) and partial (b) correlations of perirenal fat thickness in the study population (presurgery)
| (a) | Perirenal fat | |
| ρ | P | |
| Age | 0.136 | 0.026 |
| Waist circumference | 0.468 | 0.000 |
| BMI | 0.396 | 0.000 |
| Systolic blood pressure | 0.230 | 0.000 |
| Insulinemia | 0.270 | 0.000 |
| HOMA‐IR | 0.313 | 0.000 |
| Glycated hemoglobin | 0.378 | 0.000 |
| Creatinine | 0.261 | 0.000 |
| (b) | ||||
| Perirenal fat thickness confounders | SBP | Creatinine | ||
| ρ | P | ρ | P | |
| Age | 0.216 | 0.001 | 0.195 | 0.003 |
| Gender | 0.153 | 0.019 | 0.039 | 0.552 |
| BMI | 0.186 | 0.004 | 0.265 | <0.001 |
| HOMA‐IR | 0.188 | 0.005 | 0.240 | <0.001 |
SBP, systolic blood pressure.
Significance set at P < 0.05.
Correlations between perirenal fat thickness and SBP were also confirmed in the subgroup of hypertensive patients (ρ = 0.177, P = 0.026, Figure 2A); similarly, the correlation was found with serum creatinine (ρ = 0.246, P = 0.002, Figure 2B). In the study population, these significant correlations were confirmed after adjusting for age, BMI, and HOMA (Table 4b). After adjusting for gender, the significant correlation was confirmed only for SBP. In the subgroup of hypertensive patients, significant correlations were confirmed after adjusting for ongoing antihypertensive treatment (ρ = 0.179, P = 0.027 and ρ = 0.192, P = 0.017 for serum creatinine and SBP, respectively). In the subgroup of untreated patients (non hypertensive patients plus untreated hypertensive patients, n = 190), similarly, perirenal fat thickness showed a significant correlation with SBP (ρ = 0.241, P = 0.002), BMI (ρ = 0.489, P < 0.001), WC (ρ = 0.542, P < 0.001), insulinemia (ρ = 0.334, P < 0.001), HOMA‐IR (ρ = 0.371, P < 0.001), and HbA1C (ρ = 0.387, P < 0.001), while the correlation with age was direct but not significant.
Figure 2.
Univariate correlation between perirenal fat thickness and systolic blood pressure (A) and between perirenal fat thickness and serum creatinine (B) in hypertensive and nonhypertensive patients
At multivariate analysis performed on the study population, the independent predictors (R 2 = 0.129) of SBP were age (β = 0.175, P = 0.011) and perirenal fat thickness (β = 0.160, P = 0.022); the other parameters included in the model were BMI and HbA1C. Likewise, the independent predictors (R 2 = 0.054) of serum creatinine were age (β = 0.133, P = 0.039) and perirenal fat thickness (β = 0.194, P = 0.003); the other parameter included in the model was SBP.
After SG, perirenal fat thickness significantly decreased (Table 3). Of the 179 hypertensive patients, 89 underwent SG. Of these, 41 (46%) were receiving antihypertensive therapy. After surgical procedure, there was a significant change in drug intake with a statistically significant decrease in medications taken. In addition, 16 patients suspended therapy (Figure 3A,B). Forty‐eight patients who were not receiving any antihypertensive therapy before surgery did not need to start treatment.
Figure 3.
Antihypertensive therapy variations before (A) and after surgery (B, P=.003) and the relationship between presurgery perirenal fat thickness and postsurgery antihypertensive therapy variation (C)
In the 89 hypertensive patients undergoing surgery, we observed that patients who reduced the burden of antihypertensive therapy had higher presurgery perirenal fat thickness, compared with patients who did not change or even increased the number of antihypertensive therapy (P = 0.044; Figure 3C).
4. DISCUSSION
From our study, interesting data emerged concerning the influence of perirenal fat in determining both hypertension prevalence and renal damage.
It is known that adipose tissue distribution in the abdominal region is closely associated with a greater risk of developing arterial hypertension.4, 13
The evaluation of VFA by ultrasound, a noninvasive and safe method, allows to quantify with adequate approximation (with respect to computed tomography or magnetic resonance imaging, gold standards) the visceral fat amount: This one plays an important role in the genesis of hypertension related to obesity, through both mechanical and endocrine action.13, 14 Starting from this observations, we meant to evaluate the role of perirenal fat in determining the development of hypertension in our population of obese patients.
By dividing our sample into two subpopulations, hypertensive and nonhypertensive, we found a statistically significant difference in perirenal fat thickness (it was higher in hypertensive patients), and a significant correlation between SBP and perirenal fat thickness, which is also an independent predictor of SBP at multivariate analysis. In the subpopulation of hypertensive patients, there was no correlation between perirenal fat thickness and number of antihypertensive drugs taken. However, in the subpopulation of hypertensive patients who underwent SG, we found a positive correlation between preintervention perirenal fat thickness and postintervention decrease in antihypertensive therapy, to signify a probable greater benefit from surgery in patients with a greater perirenal fat thickness, and therefore with a more compromised metabolic profile.
Differently from De Pergola et al7 observation that perirenal fat thickness was associated with an increase in DBP but not in SBP, in our population, we documented a significant correlation between perirenal fat and high SBP; also in the study population, perirenal fat thickness turned out to be an independent predictor of high SBP. Furthermore, the finding of a positive correlation between perirenal fat thickness and WC, a predictor of arterial hypertension,15, 16 strengthens the hypothesis of its central role in hypertension development in obese subject.
Another interesting finding is the close association between perirenal fat thickness and creatinine values. In fact, from the analysis of our data, perirenal fat shows a positive correlation with creatinine values and is an independent predictor of elevated creatinine values.
Longitudinal cohort studies documented that BMI is an independent risk factor for the development of end‐stage renal disease17 and that obesity, regardless of the presence of comorbidity, leads to chronic kidney disease development.18 The underlying pathogenic mechanism is still debated, but it is assumed the central role of insulin resistance,19 able to accelerate the age‐related decline of renal function20 and closely associated with ectopic fat depots. In association with the injurious insulin action, recent studies on animal models documented how proinflammatory molecules of adipocyte derivation such as angiotensin II, TNF‐alpha and leptin are able to stimulate kidney receptors inducing fibrosis.21 The accumulation of ectopic fat in the kidney is therefore associated with structural and functional changes of mesangial cells, podocytes and cells of the proximal tubule able to determine the so‐called obesity‐related glomerulopathy.20 These data therefore suggested a potential role of renal sinus fat in determining renal damage.
The close association between perirenal fat and creatinine resulting from our data, both in the whole study population and in the subpopulation of hypertensive patients, suggests a relevant connection between perirenal fat and chronic renal damage. The anatomical proximity, the common vascularization of perirenal adipose tissue and renal cortex mediated by Turner's plexus, and the presence of adipose tissue dysfunction typical of the obese subject could represent the main mechanisms through which, by mechanical and paracrine effect, perirenal fat contributes to the kidney damage.
The analysis of our data also shows a close association between perirenal fat thickness and VFA, insulinemia, insulin resistance, and HbA1C. Insulin plays a role in the pathogenesis of arterial hypertension of morbidly obese through a direct effect on renal tubules resulting in sodium‐retention, through a stimulating effect on the sympathetic nervous system and finally through direct action on vascular structures that contributes to obese subject vascular dysfunction.22 Therefore, the presence of a close association between perirenal fat thickness and systemic arterial pressure, VFA and insulin resistance suggests that fat accumulation in this site can contribute via multiple mechanisms to determine hypertension in morbidly obese patient.
Finally, about a half of the population under investigation underwent SG. We analyzed the changes in the anthropometric and metabolic parameters after this procedure. The beneficial effect of SG in inducing a significant weight loss23 was confirmed, along with a clear improvement of coexisting comorbidities.24, 25, 26
We observed a weight loss of at least 33 kg and at least 25% of the initial body weight in 50% of the population, a result much greater than the desired goal of 10%.25 BMI decreased up to an average of 33 kg/m2, with about 34% of the population reaching values below 30 kg/m2, thus regressing to an overweight or normal weight condition.25
About blood pressure control, in the population object of the study, we observed a reduction in mean SBP and DBP of 13 and 9 mm Hg, respectively. Analyzing the population of hypertensive patients, we observed a similar response with a mean pressure values reduction of 17 mm Hg for SBP and 11 mm Hg for DPB resulting in 72% of patients in therapy suspension or no need to start therapy. These data appear to be of considerable importance because in a meta‐analysis of 2013, there was no significant decrease in blood pressure values after bariatric surgery24 and in a recent review, the remission of arterial hypertension after SG was estimated to be 58%.27
Therefore, data found in the population treated with SG suggest that this procedure represents, in the great obese, an effective tool not only able to reduce body weight, but also able to control and significantly modify the main cardiovascular risk contributors.
This study has some limitations: The interventional design of the study prevents us from drawing any conclusion on an eventual causative effect of perirenal fat thickness on hypertension development in obese patients. The absence of a control group prevents us from comparing sleeve‐gastrectomy intervention with other weight loss strategies. Also, the follow‐up time after sleeve‐gastrectomy is relatively short, and for this reason, we are planning to repeat the analysis after a longer follow‐up. Moreover, the relatively small number of enrolled patients prevented us from making further analysis in particular subgroups (ie, treated vs untreated hypertensive patients). Regarding this latter limitation, we should notice that perirenal fat thickness is significantly different between the two genders and this topic deserves further targeted studies.
To our knowledge, this study first identifies that the hypertension remission observed after bariatric surgery is related to perirenal fat thickness. For the very first time, we can state that the thickness of perirenal fat, evaluated by ultrasound method, could represent, in the obese subject, an integrated parameter able to define both the risk of developing arterial hypertension and chronic renal pathology. This, in addition to the already known predictors of cardiovascular disease, could provide the clinician with an additional parameter for a correct classification of the obese subject, and therefore define those patients who need a more aggressive treatment, and those who could benefit most from bariatric surgery.
CONFLICT OF INTEREST
The authors report no conflict of interest to disclose.
Ricci MA, Scavizzi M, Ministrini S, De Vuono S, Pucci G, Lupattelli G. Morbid obesity and hypertension: The role of perirenal fat. J Clin Hypertens. 2018;20:1430–1437. 10.1111/jch.13370
REFERENCES
- 1. Nguyen NT, Magno CP, Lane KT, Hinojosa MW, Lane JS. Association of hypertension, diabetes, dyslipidemia and metabolic syndrome with obesity: findings from the National Health and Nutrition Examination Survey, 1999 to 2004. J Am Coll Surg. 2008;207:928‐934. [DOI] [PubMed] [Google Scholar]
- 2. Garrison RJ, Kannel WB, Stokes J 3rd, Castelli WP. Incidence and precursor of hypertension in young adults: the Framingham Offspring study. Prev Med. 1987;16:235‐251. [DOI] [PubMed] [Google Scholar]
- 3. Jones DW, Kim JS, Andrew ME, Kim SJ, Hong YP. Body mass index and blood pressure in Korean men and women: the Korean national blood pressure survey. J Hypertens. 1994;12:1433‐1437. [DOI] [PubMed] [Google Scholar]
- 4. Hall ME, do Camo JM, da Silva AA, Juncos LA, Wang Z, Hall JE. Obesity, hypertension and chronic kidney disease. Int J Nephrol Renovasc Dis. 2014;18:75‐88. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Stevens VJ, Obarzanek E, Cook NR, et al. Long‐term Weight loss and changes in blood pressure: results of the trials of hypertension prevention, phases II. Ann Intern Med. 2001;134:1‐11. [DOI] [PubMed] [Google Scholar]
- 6. Chughtai HL, Morgan TM, Rocco M, et al. Renal sinus fat and poor blood pressure control in middle‐age and elderly individuals at risk for cardiovascular events. Hypertension. 2010;56:901‐906. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. De Pergola G, Campobasso N, Nardecchia A, et al. Para‐ and perirenal ultrasonographic fat thickness is associated with 24‐hours mean diastolic blood pressure levels in overweight and obese subject. BMC Cardiovasc Disord. 2015;15:108. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8. Foster MC, Hwang SJ, Porter SA, Massaro JM, Hoffmann U, Fox CS. Fatty kidney, hypertension, and chronic kidney disease: the Framingham Heart Study. Hypertension. 2011;58:784‐790. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9. Beamish AJ, Olbers T, Kelly AS, Inge TH. Cardiovascular effect of bariatric surgery. Nat Rev Cardiol. 2016;13:730‐743. [DOI] [PubMed] [Google Scholar]
- 10. Noria SF, Grantcharov T. Biological effects of bariatric surgery on obesity‐related comorbidities. Can J Surg. 2013;56:47‐57. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. International Expert Committee . International Expert Committee Report on the role of the HbA1c assay in the diagnosis of diabetes. Diabetes Care. 2009;32:1327‐1334. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12. Hirooka M, Kumagi T, Kurose K, et al. A technique for the measurement of visceral fat by ultrasonography: comparison of measurements by ultrasonography and computed tomography. Intern Med. 2005;44:794‐799. [DOI] [PubMed] [Google Scholar]
- 13. Krakoff LR. Adiposity and risk for hypertension. Does location matter? J Am Coll Cardiol. 2014;64:1003‐1004. [DOI] [PubMed] [Google Scholar]
- 14. Chiba Y, Saitoh S, Takagai S, et al. Relationship between visceral fat and cardiovascular disease risk factors: the Tanno and Sobetsu study. Hypertens Res. 2007;30:229‐236. [DOI] [PubMed] [Google Scholar]
- 15. Landsberg L, Aronne LJ, Beilin LJ, et al. Obesity‐related hypertension: pathogenesis, cardiovascular risk, and treatment: a position paper of the Obesity Society and the American Society of Hypertension. J Clin Hypertens (Greenwich). 2013;15:14‐33. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16. Ganatiuc L, Alegre‐Diaz J, Halsey J, et al. Adiposity and blood pressure in 110000 Mexican adults. Hypertension. 2017;69:608‐614. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17. Hsu CY, McCulloch CE, Iribarren C, et al. Body mass index and risk for end‐stage renal disease. Ann Intern Med. 2006;144:21‐28. [DOI] [PubMed] [Google Scholar]
- 18. deVries A, Ruggenenti P, Ruan XZ, et al. Fatty Kidney: emerging role of ectopic lipid in obesity‐related renal disease. Lancet Diabetes Endocrinol. 2014;2:417‐426. [DOI] [PubMed] [Google Scholar]
- 19. Reaven GM. Banting lecture 1988. Role of insulin resistance in human disease. Diabetes. 1988;1988(37):1595‐1607. [DOI] [PubMed] [Google Scholar]
- 20. Oterdoom LH, de Vries A, Ganservoort RT, de Jong PE, Gans RO, Bakker SJ. Fasting insulin modifies the relation between age and renal function. Nephrol Dial Transplant. 2007;22:1587‐1592. [DOI] [PubMed] [Google Scholar]
- 21. Favre G, Grangen‐Chapon C, Raffaelli C, François‐Chalmin F, Iannelli A, Esnault V. Perirenal fat thickness measured with computed tomography is a reliable estimate of perirenal fat mass. PLoS One. 2017;12:e0175561. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22. Kotsis V, Stabouli S, Papakatsika S, Rizos Z, Parati G. Mechanisms of obesity‐induced hypertension. Hypertens Res. 2010;33:386‐393. [DOI] [PubMed] [Google Scholar]
- 23. Chang SH, Stoll CR, Song J, Varela JE, Eagon CJ, Colditz GA. The effectiveness and risks of bariatric surgery: an update systematic review and meta‐analysis, 2003–2012. JAMA Surg. 2014;149:275‐287. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24. Gloy VL, Briel M, Bhatt DL, et al. Bariatric surgery versus non‐surgical treatment for obesity: a systematic review and meta‐analysis of randomised controlled trials. BMJ. 2013;347:f5934. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25. Buchwald H, Estok R, Fahrbach K, et al. Weight and type 2 diabetes after bariatric surgery: systematic review and meta‐analysis. Am J Med. 2009;122(248–256):e5. [DOI] [PubMed] [Google Scholar]
- 26. Schauer PR, Kashyap SR, Wolski K, et al. Bariatric surgery versus intensive medical therapy in obese patients with diabetes. N Engl J Med. 2012;366:1567‐1576. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27. Noah J, Smith A, Birch D, et al. The Metabolic effects of laparoscopic sleeve gastrectomy: a review. J Minim Invasive Surg Sci. 2013;2:3‐7. [Google Scholar]