Methods
Study Population
We retrospectively analyzed detailed clinical data from 30,448 patients with urolithiasis enrolled in the 6th Nationwide Survey on Urolithiasis in Japan conducted in 2005. This survey was designed to estimate the annual incidence of urolithiasis and included all 1,218 hospitals approved by the Japanese Board of Urology, thus covering nearly all urologists practicing in Japan. Materials and methods used in the surveys have been described previously. In brief, the enrolled hospitals were asked by way of a mailed questionnaire to investigate all patient visits in 2005 that resulted in a diagnosis of urolithiasis. Patients with only a history of stone passage (patients with no stones in 2005) were excluded from the study. The survey included questions about the age and sex of patients with stones, stone location (upper or lower urinary tract or both), and number of stone episodes (first time or recurrent). The survey also included a detailed questionnaire about individual patient characteristics, such as body size (height and weight), number of stones (single or multiple), possible causes of stone formation (urinary obstruction, urinary tract infection, prolonged immobility, primary hyperparathyroidism, renal tubular acidosis, cystinuria, hypercalcemia, hyperuricemia, and medication), abnormalities in urine chemistry (hypercalciuria, hyperuricosuria, hyperoxaluria, and hypocitraturia), stone composition (calcium oxalate, calcium phosphate, uric acid, magnesium ammonium phosphate, cystine, and others), and comorbid conditions (diabetes, hypertension, dyslipidemia, and osteoporosis). The response to individual questionnaires was obtained from 174 hospitals, including detailed clinical data for 30,448 patients with urolithiasis.
Because previous reports have suggested that metabolic syndrome might be associated with kidney stones composed of calcium oxalate or uric acid, we excluded patients with only lower urinary tract stones; with struvite stones, cystine stones, and other types of rare stone composition; who had a clinically apparent cause of stone formation (urinary obstruction, urinary tract infection, prolonged immobility, primary hyperparathyroidism, renal tubular acidosis, cystinuria, and medication); and younger than 15 years. The number of patients who were excluded based on these criteria was 4,004. We also excluded another 14,889 patients with missing data for age, sex, body size, diabetes, hypertension, and dyslipidemia. A total of 11,555 patients was included in the final analyses (Fig 1).
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Figure 1.
Flow diagram of the study cohort. Abbreviation: BMI, body mass index.
Exposures
The number of metabolic syndrome traits (obesity, hypertension, dyslipidemia, and diabetes) was counted for each patient. Obesity was defined as body mass index (BMI) ≥25 kg/m. Although diagnostic criteria for other traits were not defined in the survey, commonly used criteria in Japan were as follows: hypertension, blood pressure ≥140/90 mm Hg; dyslipidemia, low-density lipoprotein cholesterol level ≥140 mg/dL, high-density lipoprotein cholesterol level <40 mg/dL, or triglyceride level ≥150 mg/dL; diabetes, fasting plasma glucose level ≥126 mg/dL, 2-hour plasma glucose level by 75-g glucose tolerance test ≥200 mg/dL, or hemoglobin A1c level ≥6.5%.
Outcomes
Severe kidney stone disease was defined as recurrent and/or multiple stones. Numbers of stone episodes (first time/recurrent) and existing stones (single/multiple) were reported based on medical and radiology records. Abnormalities in urine constituents (hypercalciuria, hyperuricosuria, hyperoxaluria, and hypocitraturia) were reported based on the medical record. Commonly used criteria in Japan were as follows: (1) hypercalciuria, urinary calcium excretion ≥4.0 mg/kg/d; (2) hyperoxaluria, urinary oxalate excretion ≥45 mg/d; (3) hyperuricosuria, urinary uric acid excretion ≥800 mg/d in men and ≥750 mg/d in women; and (4) hypocitraturia, urinary citrate excretion <320 mg/d.
Analytical Procedures
The severity of kidney stone disease, assessed by the number of existing stones and number of stone episodes, and abnormalities in urine constituents were examined by the number of metabolic syndrome traits using χ test. Logistic regression was used to calculate the multivariable-adjusted odds of recurrent and/or multiple stones, as well as urine abnormalities, by the number of metabolic syndrome traits. Patients with missing data were excluded from each analysis. All tests were performed at the 5% significance level using JMP 7 software (SAS Institute Inc). The study was approved by the Institutional Review Board of Wakayama Medical University.