We addressed the study aim in two separate analyses: first, in a large cross-sectional population study examining the effects of chronic sugar-sweetened beverage intake on serum urate and gout, and second, in a short-term intervention study examining the effects of an acute fructose load on serum urate and fractional excretion of uric acid. In all analyses, the responses were analysed in those with body mass index <25 mg/kg2 (low body mass index group) and those with body mass index ≥ 25 mg/kg2 (high body mass index group).
Chronic sugar-sweetened beverage intake serum urate analysis
The effect of chronic sugar-sweetened beverage intake on serum urate in separate body mass index strata was assessed by analysing 12,870 people without gout from the Atherosclerosis Risk in Communities (ARIC), Framingham Heart Study (FHS) and New Zealand (NZ) datasets. The ARIC (n = 8,436) and FHS (n = 3,066) cohorts are US longitudinal studies described by us elsewhere [11] whereas the NZ dataset is a cross-sectional sample set recruited from 2007 to 2014 [4]. The FHS Generation 3 cohort was analysed with all measures taken at examination 1 (2002–2005) and all ARIC measures were taken at examination 1 (1987–1989). Sugar-sweetened beverage consumption was assigned to one of three categories – those drinking no sugar-sweetened beverages (no sugar-sweetened beverage intake group), >0 to <2 sugar-sweetened beverages per day (low sugar-sweetened beverage intake group) and ≥2 sugar-sweetened beverages per day (high sugar-sweetened beverage intake group). Serum urate was regressed against the three categories in body mass index <25 mg/kg2, body mass index ≥25 mg/kg2 and unstratified. All analyses were adjusted by ethnicity, age, sex, fruit intake, triglycerides, kidney disease (self-reported) and hypertension, and relatedness in FHS. Significant difference in the change in serum urate per sugar-sweetened beverage category between body mass index groups was assessed by calculating a Cochran’s Q test statistic and the corresponding P value (P
Q). Data were analysed using STATA version 13.1 (StataCorp, College Station, TX, USA) and R 3.0.2 in the RStudio GUI version 0.98.1087 (R Foundation for Statistical Computing, Vienna, Austria).
Chronic sugar-sweetened beverage intake gout analysis
The effect of chronic sugar-sweetened beverage intake on gout status in separate body mass index strata was assessed by analysing 2,578 people (n = 1,368 without gout and 1,210 with gout) from the NZ dataset [4]. Gout was clinically ascertained using the 1977 American Rheumatism Association preliminary gout classification criteria [12]. A logistic regression of sugar-sweetened beverage intake (based on the three categories: 0, >0 to <2, >2) with gout status was performed to determine the odds ratio for gout. All analyses were adjusted by ethnicity, age, sex, fruit intake, triglycerides, kidney disease and hypertension. Significant difference in the odds ratios for gout per sugar-sweetened beverage category between body mass index groups was assessed by calculating a Cochran’s Q test statistic and the corresponding P value (P
Q). Data were analysed using STATA version 13.1 and R 3.0.2 in the RStudio GUI version 0.98.1087.
Acute fructose intake analysis
The methods of the acute fructose intake study have been previously reported [13]. Exclusion criteria were: gout, diabetes mellitus or fructose intolerance, diuretic use, fasting glucose >6 mmol/L. Following an overnight fast, 76 healthy volunteers consumed a sugar solution between 8 a.m. and 9 a.m., and blood was obtained prior to ingestion and then 30 minutes, 60 minutes, 120 minutes, and 180 minutes after ingestion. Urine was obtained at each time point for testing of urate and creatinine to allow calculation of fractional excretion of uric acid (uric acid clearance/creatinine clearance expressed as a percentage). Weight and height were measured at the start of the study visit, and body mass index was calculated. The sugar solution of 300 kcal/300 ml was consumed within 10 minutes, according to the protocol of Akhavan and Anderson for fructose-induced hyperuricaemia [14]. This solution contained 80 % fructose and 20 % glucose (64 g fructose and 16 g glucose). The study was approved by the New Zealand Multiregional Ethics Committee, and each participant gave written informed consent.
Data were analysed using a mixed models approach to repeated measures. Significant main and interaction effects were explored using the method of Tukey. Sex, ethnicity and triglycerides were adjusted for within the models. For change in serum urate and other biochemical variables, a mixed models analysis of covariance (ANCOVA) approach to repeated measures was used. For ANCOVA, the dependent variable was change from baseline, and baseline level was included as a covariate. Analyses were performed using SAS v 9.2 (SAS Institute Inc., Cary, NC, USA). P <0.05 was considered significant and all tests were two-tailed.