Volume 58, Issue 3 , Pages 383-388, September 2011
Association Between Metabolic Syndrome and the Presence of Kidney Stones in a Screened Population
Article Outline
Background
Components of metabolic syndrome have been associated with kidney stone disease, but little evidence is available to support a relationship between metabolic syndrome and kidney stone development in healthy large screened populations.
Study Design
Cross-sectional analysis.
Setting & Participants
Data were obtained from 34,895 individuals who underwent general health screening tests between January 2006 and December 2006 at the Asan Medical Center.
Predictor
Metabolic syndrome was defined according to criteria established by the National Cholesterol Education Program Adult Treatment Panel III, American Heart Association, and National Heart, Lung, and Blood Institute.
Outcomes & Measurements
The presence of kidney stones was evaluated using computed tomography or ultrasonography.
Results
Of all those screened, 839 (2.4%) had radiologic evidence of kidney stones and metabolic syndrome was diagnosed in 4,779 (13.7%). The multivariable-adjusted OR for kidney stones increased with an increasing quintile of waist circumference and systolic/diastolic blood pressure (P < 0.001). Age, sex, hypertension, and metabolic syndrome status were independent risk factors for kidney stones. The presence of metabolic syndrome had an OR of 1.25 (95% CI, 1.03-1.50) for kidney stone prevalence. In participants with hypertension, the OR for the presence of kidney stones was 1.47 (95% CI, 1.25-1.71) compared with that for participants without hypertension after adjustment for other variables.
Limitations
Cross-sectional design, absence of stone composition.
Conclusion
Metabolic syndrome is associated with a significantly increased risk of kidney stone development. Our findings suggest the need for interventional studies to test the effects of preventing and treating metabolic syndrome on the risk of kidney stone development.
Index Words: Kidney calculi, metabolic syndrome X, mass screening
Metabolic syndrome, the simultaneous occurrence of hyperglycemia, hyperlipidemia, hypertension, and visceral obesity, is a chronic disease associated with high mortality. In addition, this condition substantially increases the risk of developing cardiovascular diseases and type 2 diabetes.1 In the United States, the prevalence of metabolic syndrome is 24% in men and 23.4% in women, increasing at ages 60-69 years to 43.5% in both sexes.2 In Korea, 19.9% of men and 23.7% of women meet the metabolic syndrome criteria established by the National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III).3
Kidney stone disease is common throughout the world, with a lifetime cumulative incidence of symptomatic nephrolithiasis ranging from 5%-10%.4 The prevalence of kidney stones has increased in recent years. In American adults, the lifetime occurrence of kidney stones increased significantly by 37% in 1976-1980 and again in 1988-1994.4 Concurrent with the westernization of Asian culture, kidney stone formation has increased recently in Asian countries.5 The origin of kidney stones is multifactorial, with epidemiologic studies showing that male sex, race/ethnicity, age, climate, occupation, and obesity are associated with kidney stone formation.6, 7
Obesity and components of metabolic syndrome have been associated with nephrolithiasis,7, 8, 9, 10, 11, 12 and several studies have suggested that metabolic syndrome is linked directly to the formation of kidney stones.13, 14, 15 Although the exact pathophysiologic mechanisms underlying the association between metabolic syndrome and nephrolithiasis are unclear, metabolic syndrome has been associated with changes in urinary constituents, including lower urinary pH, decreased citrate excretion, and increased uric acid and calcium excretion, leading to increased risks of uric acid and calcium stone formation.13, 16, 17
To date, little evidence has been available to support a relationship between metabolic syndrome and kidney stone development in healthy screened populations. Preventative health care intervention may be improved by studying the relationship between metabolic syndrome and kidney stone formation in a screened population. Determining common modifiable risk factors for the development of kidney stones might uncover new strategies for treatment and prevention. We therefore investigated the association of metabolic syndrome with kidney stone formation in a large screened population.
Methods
Study Participants
We retrospectively analyzed medical records of 34,895 individuals who visited the Health Promotion Center of the Asan Medical Center for routine health checkups between January 2006 and December 2006. Our health screening program includes anthropometric measurements (height, weight, and waist circumference), blood tests (complete blood cell count, basic chemistry, serologic tests, blood coagulation test, thyroid function tests, and assays for tumor markers), stool/urine analyses, abdominal ultrasonography and/or computed tomography (CT), gastrofiberscopy, chest radiography, pulmonary function tests, and electrocardiography. The study protocol was approved by the Institutional Review Board of the Asan Medical Center.
Exposure Measures
Weight, waist circumference, and blood pressure were measured after an overnight fast, and a blood sample was drawn. Plasma fasting glucose, serum total cholesterol, high-density lipoprotein (HDL) cholesterol, and triglycerides were measured using enzymatic methods with an autoanalyzer (Toshiba 200-FR; Toshiba Medical System Co, Ltd, www.toshiba-medical.co.jp).
Metabolic syndrome was defined according to the criteria established in 2005 by the National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III), American Heart Association, and National Heart, Lung, and Blood Institute.18 For the criteria for metabolic syndrome, abdominal obesity was defined as waist circumference >90 cm in men and >80 cm in women, according to the World Health Organization Asia-Pacific obesity criteria.19 Metabolic syndrome was diagnosed in those who satisfied at least 3 of the following 5 criteria: waist circumference >80 cm in women and >90 cm in men, triglyceride concentration ≥150 mg/dL or undergoing treatment for hypertriglyceridemia, HDL cholesterol concentration <40 mg/dL in men and <50 mg/dL in women or undergoing treatment for low HDL-C level, blood pressure ≥130/85 mm Hg or undergoing treatment for hypertension, and fasting plasma glucose level ≥100 mg/dL or undergoing treatment for hyperglycemia.
Outcome Measures
The presence of kidney stones was the outcome of our analysis. We retrospectively reviewed radiology records of all participants and recorded kidney stones as present if they were detected using abdominal ultrasonography (n = 27,884; IU-22 ultrasound unit; Philips Medical Systems, www.healthcare.philips.com) or CT (n = 7,091; SOMATOM Sensation 16; Siemens AG, www.siemens.com/entry/cc/en); stone size did not matter and we even counted cases for which patients did not require treatment. Ultrasonographic examinations were conducted by one of several clinically experienced radiologists at our Health Promotion Center, and an ultrasonographic diagnosis of kidney stones required demonstration of any hyperechoic structure causing acoustic shadowing. The CT diagnosis of kidney stones was established by visualization of a high-attenuation structure (>100 Hounsfield units) in the kidney.
Statistical Analyses
We performed inter-rater reliability analysis using the κ statistic to determine the agreement between CT and ultrasonography in 7,091 participants who underwent both CT and ultrasonography. The prevalence of metabolic syndrome and individual components thereof and the numbers of metabolic syndrome components present (0, 1, 2, or ≥3) were determined for the overall study sample. Mean values for continuous demographic and metabolic variables were calculated relative to the presence of kidney stones. The statistical significance of differences among these variables was assessed using Mann-Whitney U test and χ2 test. Crude and multivariable-adjusted odds ratios (ORs) of kidney stone presence were calculated using logistic regression models with age, sex, metabolic syndrome components, and metabolic syndrome status as input factors. The best-fitting model was judged according to the Akaike information criterion (AIC), and the model with the lowest AIC was considered to be the best-fitting model. The AIC was used to select the most parsimonious model.20 All P values were 2 tailed, and P < 0.05 was defined as statistically significant. All statistical analysis was performed using Stata, version 10.1 (StataCorp).
Results
Baseline demographic characteristics of the 34,895 participants are listed in Table 1. In the study population, 59.6% were men and 67.9% were aged 40-59 years. As the number of metabolic syndrome components increased, waist circumference, triglyceride concentration, blood pressure, and fasting blood glucose level increased, whereas HDL cholesterol level decreased.
Table 1. Baseline Demographic Characteristics
A total of 839 participants (2.4% of the population) had radiologic evidence of kidney stones. Of the 7,091 participants who underwent CT and ultrasonography, 368 (5.2%) had kidney stones detected using CT or ultrasonography. Of the 7,091 participants who underwent both CT and ultrasonography, κ was 0.78 (P < 0.001), for excellent agreement (Table 2). Of 839 participants with kidney stones, a single stone was found in 638 (76.0%); 2 stones, in 107 (12.8%); 3 stones, in 53 (6.3%); 4 stones, in 38 (4.5%); and 5 stones, in 3 participants (0.4%). Mean number of kidney stones per person was 1.4. Mean kidney stone size was 6.5 mm (median, 6; range, 1-27). Characteristics of kidney stones by the number of metabolic syndrome component fulfilled are listed in Table 3. As the number of metabolic syndrome components increased, the frequency of kidney stones increased regardless of the diagnostic test used.
Table 2. Agreement Between Diagnostic Tests for the Detection of Kidney Stones in Participants Who Had Both CT and US
Table 3. Characteristics of Kidney Stone by Number of Metabolic Syndrome Components Fulfilled
Overall, 4,779 (13.7%) participants were given a diagnosis of metabolic syndrome. The criterion for increased blood pressure was fulfilled in 30.5% of participants and was the most common of the 5 metabolic syndrome components (increased triglycerides, 27.2%; increased waist circumference, 24.2%; low HDL cholesterol, 15.4%; and impaired glucose tolerance, 13.7%). A total of 61% of participants fulfilled at least one criterion of metabolic syndrome.
Table 4 lists crude and multivariable-adjusted ORs for kidney stones according to quintile of the 5 metabolic syndrome components. Crude and multivariable-adjusted ORs for kidney stones increased with increasing quintile of waist circumference (P < 0.001) and systolic and diastolic blood pressure (P < 0.001 and P < 0.001, respectively). When each of the 5 metabolic components was analyzed as a continuous variable, systolic and diastolic blood pressure (P < 0.001 and P < 0.001, respectively), waist circumference (P < 0.001), and triglyceride concentration (P = 0.02) were independent risk factors for kidney stones after adjustment for age and sex. HDL cholesterol and fasting blood glucose levels were not associated independently with risk of kidney stones (P = 0.3 and P = 0.7, respectively).
Table 4. Crude and Multivariable-Adjusted ORs for Kidney Stone by Quintile of the 5 Metabolic Syndrome Components
| Total No. | Cases of StonesNo. (%) | Crude OR (95% CI) | P | Adjusted OR (95% CI)a | P | |
|---|---|---|---|---|---|---|
| Waist circumference | <0.001 | <0.001 | ||||
 Quintile 1 (≤72 cm) | 7,024 | 100(1.4) | 1.00(reference) | 1.00(reference) | ||
| Quintile 2 (73-78 cm) | 7,946 | 142(1.8) | 1.26(0.97-1.63) | 0.98(0.75-1.28) | ||
| Quintile 3 (79-83 cm) | 7,536 | 185(2.5) | 1.74(1.36-2.23) | 1.13(0.86-1.49) | ||
| Quintile 4 (84-88 cm) | 5,510 | 178(3.2) | 2.31(1.80-2.96) | 1.42(1.07-1.89) | ||
| Quintile 5 (≥89 cm) | 6,879 | 234(3.4) | 2.44(1.93-3.09) | 1.48(1.12-1.95) | ||
| Triglycerides | <0.001 | 0.2 | ||||
| Quintile 1 (≤69 mg/dL) | 6,994 | 138(2.0) | 1.00(reference) | 1.00(reference) | ||
| Quintile 2 (70-92 mg/dL) | 6,955 | 129(1.9) | 0.94(0.74-1.20) | 0.79(0.62-1.01) | ||
| Quintile 3 (93-122 mg/dL) | 6,991 | 186(2.7) | 1.36(1.09-1.70) | 1.06(0.85-1.33) | ||
| Quintile 4 (123-170 mg/dL) | 6,967 | 180(2.6) | 1.31(1.05-1.65) | 0.97(0.77-1.22) | ||
| Quintile 5 (≥171 mg/dL) | 6,988 | 206(3.0) | 1.51(1.22-1.88) | 1.07(0.86-1.35) | ||
| HDL cholesterol | 0.001 | 0.2 | ||||
| Quintile 1 (≤44 mg/dL) | 7,080 | 212(3.0) | 1.00(reference) | 1.00(reference) | ||
| Quintile 2 (45-51 mg/dL) | 6,893 | 174(2.5) | 0.84(0.69-1.03) | 0.89(0.73-1.09) | ||
| Quintile 3 (52-58 mg/dL) | 6,984 | 169(2.4) | 0.80(0.66-0.99) | 0.90(0.73-1.10) | ||
| Quintile 4 (59-67 mg/dL) | 6,962 | 146(2.1) | 0.69(0.56-0.86) | 0.84(0.68-1.04) | ||
| Quintile 5 (≥68 mg/dL) | 6,976 | 138(2.0) | 0.65(0.53-0.81) | 0.88(0.70-1.10) | ||
| Systolic BP | <0.001 | <0.001 | ||||
| Quintile 1 (≤105 mm Hg) | 7,466 | 113(1.5) | 1.00(reference) | 1.00(reference) | ||
| Quintile 2 (106-113 mm Hg) | 7,138 | 161(2.3) | 1.50(1.18-1.91) | 1.27(0.99-1.62) | ||
| Quintile 3 (114-120 mm Hg) | 6,476 | 148(2.3) | 1.52(1.19-1.95) | 1.19(0.93-1.53) | ||
| Quintile 4 (121-130 mm Hg) | 7,171 | 202(2.8) | 1.89(1.50-2.38) | 1.40(1.10-1.78) | ||
| Quintile 5 (≥131 mm Hg) | 6,644 | 215(3.2) | 2.18(1.73-2.74) | 1.58(1.25-2.01) | ||
| Diastolic BP | <0.001 | <0.001 | ||||
| Quintile 1 (≤66 mm Hg) | 7,326 | 117(1.6) | 1.00(reference) | 1.00(reference) | ||
| Quintile 2 (67-71 mm Hg) | 6,888 | 148(2.2) | 1.35(1.06-1.73) | 1.15(0.90-1.48) | ||
| Quintile 3 (72-76 mm Hg) | 7,170 | 152(2.1) | 1.33(1.05-1.70) | 1.07(0.84-1.37) | ||
| Quintile 4 (77-82 mm Hg) | 6,939 | 189(2.7) | 1.72(1.37-2.18) | 1.31(1.03-1.66) | ||
| Quintile 5 (≥83 mm Hg) | 6,572 | 233(3.6) | 2.27(1.81-2.84) | 1.64(1.30-2.07) | ||
| Fasting glucose | <0.001 | 0.1 | ||||
| Quintile 1 (≤85 mg/dL) | 6,992 | 137(2.0) | 1.00(reference) | 1.00(reference) | ||
| Quintile 2 (86-91 mg/dL) | 7,098 | 139(2.0) | 1.00(0.91-1.44) | 0.89(0.70-1.13) | ||
| Quintile 3 (92-96 mg/dL) | 6,973 | 156(2.2) | 1.15(0.91-1.44) | 0.94(0.74-1.19) | ||
| Quintile 4 (97-103 mg/dL) | 6,903 | 196(2.8) | 1.46(1.17-1.82) | 1.12(0.89-1.40) | ||
| Quintile 5 (≥104 mg/dL) | 6,929 | 211(3.1) | 1.57(1.26-1.95) | 1.09(0.87-1.37) |
aAdjusted for age and sex. |
Table 5 lists crude and multivariable-adjusted ORs of kidney stone presence associated with age, sex, hypertension, and metabolic syndrome status. We selected this as the best-fitting model because it had the lowest AIC value. Age was significantly positively associated with the OR for kidney stone development. The presence of metabolic syndrome (≥3 criteria) was associated with a 71% increased OR of kidney stone prevalence compared with the absence of metabolic syndrome. After adjustment for age, sex, and the presence of hypertension, this OR decreased to 1.25 (95% confidence interval [CI], 1.03-1.50). Compared with men, women had a multivariable OR for the presence of kidney stones of 0.56 (95% CI, 0.48-0.65). In participants with hypertension, the OR for the presence of kidney stones was 1.47 (95% CI, 1.25-1.71) compared with those without hypertension after adjustment for other variables. The diagnostic test for detecting kidney stones was not associated significantly with the detection of kidney stones (crude OR, 0.94 for CT vs ultrasonography; 95% CI, 0.79-1.12; P = 0.5). After adjustment for age, sex, hypertension, and the presence of metabolic syndrome, diagnostic testing was not associated with the OR of the presence of kidney stones (multivariable-adjusted OR, 0.95; 95% CI, 0.80-1.12; P = 0.5).
Table 5. Crude and Multivariable-Adjusted ORs of the Association Between Kidney Stone Presence and Metabolic Syndrome Status
| Total No. | Cases of StonesNo. (%) | Crude OR(95% CI) | P | AdjustedOR (95% CI)a | P | |
|---|---|---|---|---|---|---|
| Age category | ||||||
| 20-39 y | 5,163 | 65(1.2) | 1.00(reference) | 1.00(reference) | ||
| 40-49 y | 11,209 | 229(2.0) | 1.62(1.23-2.14) | 0.001 | 1.50(1.14-1.98) | 0.004 |
| 50-59 y | 11,896 | 367(3.0) | 2.45(1.88-3.20) | <0.001 | 2.13(1.63-2.79) | <0.001 |
| ≥60 y | 5,788 | 178(2.4) | 2.44(1.83-3.25) | <0.001 | 1.96(1.46-2.63) | <0.001 |
| Sex | ||||||
| Male | 20,171 | 619(3.0) | 1.00(reference) | 1.00(reference) | ||
| Female | 13,885 | 220(1.6) | 0.52(0.44-0.60) | <0.001 | 0.56(0.48-0.65) | <0.001 |
| Hypertension | ||||||
| No | 23,779 | 465(1.9) | 1.00(reference) | 1.00(reference) | ||
| Yes | 10,277 | 374(3.5) | 1.86(1.62-2.14) | <0.001 | 1.47(1.25-1.71) | <0.001 |
| Metabolic syndrome | ||||||
| No | 29,454 | 662(2.2) | 1.00(reference) | 1.00(reference) | ||
| Yes | 4,602 | 177(3.7) | 1.71(1.45-2.03) | <0.001 | 1.25(1.03-1.50) | 0.02 |
aMultivariable adjusted. |
Discussion
In our large screened population, metabolic syndrome was associated with a significantly increased risk of kidney stone presence after adjustment for other confounding variables. We also showed that metabolic syndrome is associated with risk of kidney stones in addition to already known independent metabolic risk factors, such as hypertension. Our results are consistent with those of an earlier study, which found a significant association between metabolic syndrome and echographic evidence of nephrolithiasis in an inpatient white population referred to the hospital for any reason.14 However, our present study is the first to show such an association in a large screened population of healthy Asian men.
Although the detailed mechanisms responsible for the association of metabolic syndrome with kidney stone development are unclear, the syndrome has been associated with a self-reported history of kidney stones. In a study of 14,870 participants in the Third National Health and Nutrition Examination Survey (NHANES III), the presence of 4-5 traits of metabolic syndrome was associated with an approximately 2-fold increase in self-reported kidney stone disease.15
We also found that hypertension was associated positively with risk of kidney stones after adjustment for patient age, sex, and the presence of metabolic syndrome. Compared with normotensive patients, the multivariable OR for kidney stones in hypertensive patients was 1.47. To date, several epidemiologic studies have analyzed the association between hypertension and nephrolithiasis. In cross-sectional studies, it has been reported that nephrolithiasis is more frequent in hypertensive patients than in those who are normotensive, but the pathologic link between hypertension and stone disease remains to be clarified.21, 22, 23, 24 In addition, some prospective studies reported the risk of stones in hypertensive patients.10, 22, 25
Although previous studies have suggested that the prevalence of kidney stones is amplified by diabetes mellitus, especially in those with uric acid nephrolithiasis, our data do not support a possible association between diabetes and kidney stones.8, 26, 27 In our study, fasting blood glucose level, which was analyzed as either a categorical or continuous variable, was not an independent risk factor for kidney stones after adjustment for patient age and sex. It is difficult to directly compare our results with those of studies conducted in Western countries. Differences in racial/ethnic variables, age distribution, frequency of nephrolithiasis, methods of detection of nephrolithiasis (ie, electronic data based or self-reported questionnaires vs a radiologic diagnosis), and study populations may have affected results of analyses. Therefore, additional studies are needed to determine whether diabetes is an independent risk factor for the formation of calcium stones.
Our findings have important implications for clinical care and public health because metabolic syndrome is so common. If metabolic syndrome and the presence of kidney stones are associated, stone development may be prevented by lifestyle modification and subsequent resolution of metabolic syndrome.
Our study was strengthened by the large size of the screened cohort population and the use of standardized clinical and laboratory covariates. However, the study was limited by our inability to measure and analyze stone composition. In addition, it was difficult to define the duration of any metabolic risk factor because a substantial number of individuals with such risk factors may be undiagnosed and the duration of risk factors may reflect the extent of medical surveillance. Last, because our study was not longitudinal, we could not determine whether a causal relationship existed between metabolic syndrome or obesity and kidney stone development.
In conclusion, we found that metabolic syndrome was a strong and independent risk factor for kidney stone formation. This association suggests that kidney stones may be a systemic disorder representing the interaction of multiple metabolic risk factors. These results argue for interventional studies to examine the effects of prevention and treatment of metabolic syndrome on the risk of kidney stone development.
Acknowledgements
Support: None.
Financial Disclosure: The authors declare that they have no relevant financial interests.
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Originally published online May 27, 2011.
PII: S0272-6386(11)00740-2
doi:10.1053/j.ajkd.2011.03.021
© 2011 National Kidney Foundation, Inc. Published by Elsevier Inc All rights reserved.
Volume 58, Issue 3 , Pages 383-388, September 2011
