Body Fat Content and Distribution and Urinary Risk Factors... : Clinical Journal of the American Society of Nephrology (original) (raw)
Introduction
Obesity and metabolic syndrome (MS) have emerged as risk factors for nephrolithiasis (1–3). Furthermore, studies have shown an association among obesity, MS, and various urinary biochemical abnormalities recognized to increase the propensity for kidney stone formation (4–6). Greater body weight has been associated with lower urinary pH in stone-forming (7) as well as non–stone-forming individuals (8). The presence of increasing MS features has also been linked with greater urine calcium and oxalate excretion in both stone-forming and non–stone-forming individuals (9). However, the contribution of dietary factors (including higher intake of salt and animal proteins) to the link among obesity, MS, and calcium nephrolithiasis has not yet been fully explored.
Although higher body weight is associated with the metabolic abnormalities of MS, higher fat mass and abnormal fat distribution appear to have a greater influence than total body weight on MS (10). In fact, abnormal body fat with greater visceral distribution appears to have a greater influence in MS than does total body weight on cardiovascular disease and diabetes risk (10–13). On the other hand, lower-body fat mass (leg fat in particular) seems to be related negatively to metabolic risk factors in both men and women and has been considered a fat reservoir to avoid visceral fat deposition (10,14,15).
The correlation between body weight and various urinary constituent abnormalities predisposing to urinary nephrolithiasis has been widely recognized (4,8,16), but to date such a relationship has not been defined between body fat and urinary kidney stone risk factors. This cross-sectional study was designed to assess the influence of fat mass and fat distribution on kidney stone risk and compare it to the contribution of lean body mass in this relationship.
Materials and Methods
Study Participants
A local advertisement within the University of Texas Southwestern Medical Center campus and the Dallas Metroplex area was used to recruit volunteers who were willing to take part in this study. Inclusion criteria were age>21 years and ability to provide informed consent. Individuals recruited to the study had a wide range of body weight and body mass index (BMI). Excluded from participation were volunteers with systemic conditions, including distal renal tubular acidosis, chronic diarrheal illness, kidney stone disease, primary hyperparathyroidism, urinary tract infections, and CKD (estimated GFR<70 ml/min per 1.73 m2). The participants were instructed to withhold any drugs that are known to affect urinary pH, including alkali therapy and diuretics, for 1 week before the study. Participants with type 2 diabetes mellitus (T2DM) participated in the study if they were not receiving insulin or thiazolidinediones. The study was approved by the institutional review board at the University of Texas Southwestern Medical Center (Dallas, Texas).
Study Design and Methods
The recruited participants underwent an extensive comprehensive metabolic evaluation. During the first 3 days (study days 1–3), the participants were maintained at home on a frozen metabolic diet (30% fat, 55% carbohydrates, 15% protein, and 300 mg cholesterol per day) with a constant daily intake of 400 mg calcium, 800 mg phosphorus, 100 mEq sodium, and 3000 ml distilled water. During the next 3 days (study days 4–6), the participants were admitted to the clinical research center and they received a freshly prepared diet with the same caloric content, mineral composition, and fluid intake. On study days 4 and 5, all participants collected a 24-hour urine sample under mineral oil and the urine was kept refrigerated. Fasting blood was drawn at the end of each 24-hour urine collection. At the end of the second urinary collection, total body composition was assessed with fan beam dual-energy absorptiometry (DXA) using Hologic Discovery software (Bedford, MA). DXA directly assesses total body fat, regional body fat, and fat-free mass, which includes lean soft issues and bone mineral content; it is accurate, reproducible, and easily applicable to people with or without diseases (17). DXA scan measurements were performed as recommended by the manufacturer by two experienced DXA technologists. Fat mass was measured in total body trunk, lower body, and lower extremities. As previously described (18), the trunk was defined superiorly from below the chin, laterally by lines passing through the glenoid fossa and lateral to the ribs, and inferiorly by a line passing through iliac crests. Lower extremities were defined as the region below the oblique lines passing through the femoral necks and converging below the pubic symphysis (18). For our center, coefficients of variation are 0.66% for lean mass measurement, 1.26% for fat mass, 1.17% for leg fat mass, and 2.49% for truncal fat mass.
Analytical Procedures
Urine pH and PCO2 were measured by pH electrodes. Urine creatinine was determined using the picric acid method. Urinary calcium was determined by atomic absorption spectroscopy; urinary oxalate was measured by a chromatography system using a carbonate-bicarbonate eluent and an anion column. Phosphorus was determined by ammonium molybdate-based reaction. Urinary uric acid was analyzed by the urate oxidase method using an alkalinized aliquot to prevent precipitation. Urinary sodium and potassium were analyzed by flame emission photometry; chloride, by Labconco Buchler chloridometer; and sulfate, by ion chromatography. Urinary bicarbonate was calculated from urine pH and PCO2. Urinary ammonium (NH4+) was determined by the glutamate dihydrogenase method. Titratable acidity was measured directly using an automated burette endpoint titration system (Radiometer, Copenhagen, Denmark). Citrate was calculated by citrate lyase assay, and milliequivalents of citrate were calculated from urine pH and a pKa of citrate2−/citrate3– of 5.6. Net acid excretion (NAE) was calculated as urine (NH4+ + titratable acidity) − (citrate2 −/3 − + HCO3−), all expressed in milliequivalents. Urinary supersaturation index (SI), a measure of urinary saturation with respect to calcium oxalate and uric acid, was calculated by dividing ionic activity product in urine samples by the respective thermodynamic solubility product, using the Joint Expert Speciation System (19).
Fasting serum triglycerides, HDL cholesterol, and glucose were measured using a multichannel analyzer. Serum insulin concentration was determined by a modified Yallow and Berson method (20). Homeostatic model assessment–insulin resistance (HOMA-IR) was estimated from serum glucose and insulin concentrations using the homeostasis model (HOMA2 computer model, HOMA calculator, version 2.2) (21).
Statistical Analyses
The association between body fat distribution and urinary biochemical variables was assessed using Spearman correlation coefficients. Results are presented as mean and SD. A two-sided P value <0.05 was considered to represent statistically significant differences. Statistical analysis was performed with SAS software, version 9.3 (SAS Institute, Inc., Cary, NC).
Results
Demographic and Baseline Biochemical Characteristics
Twenty-one male volunteers participated in the study: 15 white men, 4 African American men, 1 Hispanic man, and 1 Asian man. The demographic and baseline biochemical characteristics of the entire cohort are shown in Table 1. The average age ± SD was 52±14 years, the mean body weight was 91±23 kg, and the mean BMI was 28±7 kg/m2. The mean total body fat mass was 24±14 kg and total lean body mass was 67±12 kg. Lean mass and fat mass and distribution in individual study participants are shown in Supplemental Figures 1 and 2. Higher fat mass, truncal fat, and trunk/leg fat mass were associated with worse metabolic risk measures (low HDL cholesterol and high serum triglycerides, glucose, insulin, and HOMA-IR) (Supplemental Table 1). Twenty-four-hour hour urinary acid-base profile showed a mean urinary pH of 5.92±0.47, urine NH4+ of 35±9 mEq/d, titratable acidity of 15±6 mEq/d, and urinary citrate of 680±308 mg/d (9.5±4.3 mEq/d). Urinary sulfate was 37±12 mEq/d and urinary NAE was 39±14 mEq/d. Median urine NH4+/NAE was 0.72. The mean 24-hour urinary calcium was 153±56 mg/d, urinary uric acid was 517±198 mg/d, and urinary oxalate was 27±4 mg/d.
Baseline characteristics
Relationship Between Adiposity Measures and Risk Factors for Uric Acid Stones
Twenty-four-hour urine pH was negatively correlated with body weight (Table 2). It was also significantly and negatively correlated with fat mass (Spearman _R_=−0.49; _P_=0.024) (Figure 1A) and percentage body fat, but not with lean mass (_R_=−0.22; _P_=0.35) (Figure 1B). Twenty-four-hour urine uric acid was not significantly associated with any adiposity marker (_P_>0.2 for all associations) (Table 2). As a result of their association with urine pH, body weight, fat mass (Figure 1C), and percentage body fat were all positively and significantly correlated with SI uric acid.
Correlation of adiposity measures with determinants of uric acid stone risk
Association of uric acid stone risk and measures of adiposity. (A) Twenty-four-hour urine pH versus fat mass. (B) Twenty-four-hour urine pH versus lean mass. (C) Supersaturation index (SI) uric acid versus fat mass.
We further examined the impact of fat distribution on uric acid stone risk (Figure 2, Table 2). Truncal fat mass was significantly inversely associated with 24-hour urine pH (_R_=−0.52; _P_=0.02) (Figure 2A) and was positively associated with SI uric acid (_R_=0.69; _P_=0.007) (Figure 2B). There was no statistically significant correlation between leg fat mass and urinary pH or SI uric acid (Table 2). Trunk fat/leg fat ratio was the adiposity measure that statistically exhibited the strongest correlation with urine pH (_R_=−0.58; _P_=0.006) (Figure 2C) and with SI uric acid (_R_=0.72; _P_=0.004) (Figure 2D). Furthermore, there was a significant negative correlation between trunk fat/leg fat mass and the proportion of NAE as NH4+ (described by the ratio of NH4+ to NAE [NH4+/NAE]) (_R_=−0.62; _P_=0.009) (Figure 3).
Association of uric acid stone risk and fat distribution. (A) Twenty-four-hour urine pH versus trunk fat mass. (B) Supersaturation index (SI) uric acid versus trunk fat mass. (C) Twenty-four-hour urine pH versus trunk fat/ lower-extremity fat. (D) SI uric acid versus trunk fat/lower-extremity fat.
Association of fat distribution with urinary ammonium/net acid excretion (NH4+/NAE) ratio.
Relationship Between Adiposity Measures and Risk Factors for Calcium Oxalate Stones
Urinary oxalate was significantly associated with body weight, total fat mass, total lean mass, percentage body fat, trunk fat mass, and trunk fat/leg fat ratio (Table 3). However, there was no significant association between the various measures of adiposity and 24-hour urinary calcium, 24-hour urinary citrate, and SI calcium oxalate (Table 3).
Correlation of adiposity measures with determinants of calcium oxalate stone risk
Association of Metabolic Risk Characteristics with Determinants of Stone Disease
We further examined the association between determinants of kidney stone risk and metabolic syndrome determinants (serum triglycerides, HDL cholesterol, glucose, HOMA-IR) (Table 4). Serum HDL cholesterol was significantly correlated with urine pH (_R_=0.53; _P_=0.02) and negatively with SI uric acid (_R_=−0.63; _P_=0.004) (Table 4). No significant association was seen between serum triglycerides or serum glucose with any determinant of uric acid stone risk. Serum insulin and HOMA-IR were significantly associated with urine uric acid (P<0.05) and had borderline association with SI uric acid (_P_=0.076 and 0.064, respectively). There was no association between metabolic risk characteristics and determinants of calcium oxalate risk (Table 4).
Correlation of metabolic risk characteristics with determinants of stone disease
Discussion
To our knowledge, this study is the first to assess the correlation between body fat mass and distribution and stone risk. The results showed a strong association between various measures of tissue adiposity and 24-hour urinary pH and SI uric acid, major determinants of uric acid stone formation. We found fat mass and truncal fat to be stronger determinants of risk factors for uric acid stones than were total body weight and lean body mass. Furthermore, under a controlled metabolic diet, adiposity was not associated with risk factors for calcium oxalate stones.
Previous studies have reported strong links among specific patterns of fat distribution, cardiovascular morbidity, diabetes mellitus, and insulin resistance (11,12,22,23). Uric acid stones occur more frequently in patients with T2DM than in nondiabetic stone formers (24–26) and in obese than in nonobese stone formers (27,28). Furthermore, greater BMI and T2DM are shown to be independent risk factors for uric acid nephrolithiasis (29). Cross-sectional studies in healthy non–stone-forming participants and kidney stone formers have shown an inverse relationship among urinary pH, body weight, and increasing features of MS (7,8). Moreover, defective NH4+ excretion has been shown not only in uric acid stone formers but also as a general feature of MS and T2DM (7,8,30,31). Furthermore, a hyperinsulinemic euglycemic study showed a mechanistic relationship between low urinary pH and urinary NH4+ excretion wherein urinary NH4+ excretion increased in lean, healthy participants but did not change in patients with uric acid nephrolithiasis (32). Supporting experimental evidence using Zucker diabetic fatty rats, an established animal model of obesity and MS (33), has shown the causative role of renal steatosis in the pathogenesis of urinary acidification defect. Other research demonstrated that treatment with thiazolidinediones, which ameliorate insulin resistance by redistributing fat to adipocytes, restores urinary profile to levels similar to those in control animals and reduces renal triglyceride accumulation (34).
Fat content and distribution assessed by DXA have previously been shown to be superior to BMI in predicting cardiovascular events (35). Despite the strong association among obesity, MS, and the development of uric acid nephrolithiasis, no published study has evaluated whether fat in various adipose-tissue compartments links more strongly to the risk of uric acid and calcium oxalate stones. In this cross-sectional study, which took advantage of DXA technology, we assessed total body fat and pattern of fat distribution in 21 non–stone-forming men. Urinary pH was lower and SI uric acid was higher in participants with greater total fat mass and truncal fat mass, whereas leg fat mass was not associated with urinary pH. Moreover, greater truncal fat was associated with impaired NH4+ excretion (Figure 3).
Although MS is associated with a significantly increased risk of uric acid nephrolithiasis (36), calcium oxalate stones remain the most commonly encountered kidney stones. Adiposity markers were not associated with urine calcium or urine citrate in our cohort. However, we found a significant positive association between 24-hour urine oxalate and various markers of adiposity, including body weight, total fat mass, total lean mass, percentage body fat, trunk fat mass, and trunk fat/leg fat ratio (Table 3). Urinary oxalate excretion has previously been described to rise with increasing body size in healthy adults and stone-forming individuals (4,37). Greater BMI was associated with higher urinary oxalate excretion among women but not among men in two studies (38,39), whereas one report noted a correlation between body weight and urinary oxalate in men but not in women (40). Potential mechanisms for the greater oxalate excretion in the obese include increased dietary intake of oxalate precursors (41), reduced oxalate degradation in the gut lumen by intestinal bacterial flora (e.g., Oxalobacter formigenes) (42), enhanced intestinal absorption (43), greater endogenous oxalate production (44), and/or differences in renal oxalate handling (45). While the association among body weight, adiposity, and urine oxalate deserves further exploration, we did not observe a significant association between various adiposity markers and SI calcium oxalate in our cohort. The link between obesity and calcium oxalate nephrolithiasis has been in part explained by dietary factors, such as higher salt and animal protein intake (4,9). When these variables were controlled through the consumption of a fixed metabolic diet in our cohort, body weight, fat mass, and lean mass were not associated with determinants of calcium oxalate stone risk or SI calcium oxalate.
Some limitations within our study included the small sample size and the use of a urinary surrogate of stone formation. Participants were considered to be non–stone formers on the basis of history alone, and no imaging study was performed to rule out stone disease. Our study population was limited to male volunteers. Because fat mass and distribution are sex and sex hormone dependent (46), the findings may not necessarily be generalized to women. Therefore, further studies with a larger cohort of patients with both men and women, as well as stone formers and non–stone formers, are needed.
In conclusion, we found body fat and trunk fat to be stronger determinants of uric acid stone risk than are body weight and lean body mass in non–stone-forming male volunteers. Under a controlled metabolic diet, adiposity was not associated with calcium oxalate stone risk.
Disclosures
None.
Acknowledgments
The authors would like to acknowledge Ashlei L. Johnson for her editorial assistance in the preparation of the manuscript.
The authors were supported by National Institutes of Health grants R01-DK081423, UL1TR000451, and R21-DK097476; Beauticontrol Cosmetics LLC, a professorship in Mineral metabolism and osteoporosis; and the Laura Kim Pak professorship in mineral metabolism research.
Published online ahead of print. Publication date available at www.cjasn.org.
This article contains supplemental material online at http://cjasn.asnjournals.org/lookup/suppl/doi:10.2215/CJN.06180613/-/DCSupplemental.
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