Effect of Being Overweight on Urinary Metabolic Risk Factors for Kidney Stone Formation

Linda Shavit; Pietro Manuel Ferraro; Nikhil Johri; William Robertson; Steven B. Walsh; Shabbir Moochhala; Robert Unwin

Disclosures

Nephrol Dial Transplant. 2015;30(4):607-613. 

In This Article

Materials and Methods

Study Population

The kidney stone database for the KSF attending the University College London Stone Clinic (University College and Royal Free Hospitals) from November 1995 to July 2012 was reviewed. Adult patients with a recorded BMI, confirmed diagnosis of kidney stone disease and full metabolic evaluation were divided into three categories: BMI ≤25.0 kg/m2 (NW group), BMI 25–30 kg/m2 (OW group) and BMI >30.0 kg/m2 (obese group). Patients with stone types other than calcium or uric acid (for example, cystine stones, infection-related stones, drug-related stones or from patients with primary hyperoxaluria or distal RTA) were excluded from the analyses.

Study Variables

Demographic and clinical characteristics were recorded for each individual at their first visit, including age, sex, body mass index (BMI), duration of stone disease, family history of kidney stones and history of urinary tract infections. Patients underwent a fasting blood sample for the determination of urea, creatinine, electrolytes, uric acid, bicarbonate and albumin, and a 24-h urine collection for measurement of 24 h urinary volume (U.Vol), pH (U.pH), calcium (U.Ca), oxalate (U.Ox), citrate (U.Cit), uric acid (U.UA), magnesium (U.Mg), sodium (U.Na) and potassium (U.K) excretions. Patients were also asked to fill out a food frequency questionnaire to investigate intakes of fluids, calcium, magnesium, phosphate, oxalate, animal protein, purine, fibre, sugar, sodium and potassium on their usual diet. For patients that spontaneously passed stones or who underwent surgery for kidney stones, biochemical stone analysis was performed. In addition, probability of stone formation (Psf), which is an index of the overall biochemical risk of forming stones consisting of uric acid, calcium oxalate, calcium phosphate or various combinations of these constituents, has been calculated for all patients. Generally, Psf discriminates well between stone-formers and normal subjects and predicts the likely severity of the disorder in a given individual as defined by the number of stone episodes per year experienced by the patient.[9,10]

Definitions of Urinary Metabolic Abnormalities

Low urine volume was defined as urine volume <1 L/day. Hypercalciuria was defined as urine calcium excretion >7.5 mmol/day for men and 6.5 mmol/day for women. Hyperoxaluria was defined as urine oxalate excretion >0.5 mmol/day. Hyperuricosuria was defined as urine uric acid excretion >4.8 mmol/day for men and 4.5 mmol/day for women. Hypocitraturia was defined as urine citrate excretion < 1.52 mmol/day.

A stone was considered to be made of a single type (e.g. a 'pure' stone) if >95% of the stone weight was represented by a single constituent. In general, for a constituent to be considered in the stone composition it had to represent ≥5% of the stone weight.

Statistical Analysis

Continuous variables were reported as both means with standard deviations, and medians with interquartile ranges. Between-sex differences were evaluated with the Wilcoxon rank sum test. Blood, 24-h urine and dietary data were trimmed at the 1st and 99th percentile to avoid an undue effect of extreme values.

Categorical variables were reported as counts and percent proportions and analysed for between-sex differences with the Fisher exact test and with the trend test for ordered variables.

Time trends for patient characteristics were evaluated with simple linear or logistic models with the patient characteristic of interest as the dependent variable and categorized year of visit as the predictor; the statistical significance of linear trends was checked using categorized year of visit as a continuous predictor. Stratifying the sample in quartiles of year of visit created categories of year of visit.

All the statistical analyses were performed with Stata version 12.1 (StataCorp, TX, USA).

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