Physical Activity and Body Weight Assessment
Physical activity was recorded in the study diary on a daily basis as time (minutes) engaged in different type of exercise. A four-level score (inactive, moderately inactive, moderately active, and active) was assigned by combining occupational physical activity together with time participating in higher-intensity physical activities such as cycling, aerobics, swimming, jogging, exercising at a gym on a regular basis, etc. (30). Subjects weighed themselves daily on an electric balance without shoes and in light clothing and recorded their body weight in the study diary.
PABA concentration in urine was measured by a colorimetric technique described elsewhere (29). Sucrose and fructose concentration in urine were measured with a kit specific for sucrose, glucose, and fructose (sucrose/D-glucose/D-fructose from Biochemica Mannheim, R-Biopharm, Roche) using Cecil CE 2041 2000 Series spectrophotometer to measure the absorbance (31). Urinary samples of each subject were analyzed in one run for the first study and as two batches for every subject in the second. On the day of the assay, urine samples were thawed and thoroughly mixed before the analysis. Standards in the range of expected values for sucrose (10, 20, and 30 mg/L) and fructose (5, 10, and 20 mg/L) were run in every assay. To ensure the consistency of the results and the assay conditions, an internal quality control was also included in each assay consisting of aliquots from a single source preserved with boric acid and stored at －20°C. Over 1.5 years of the study, values for this quality control remained consistent throughout (meanSUC = 12.36 ± 0.82 mg/L; meanFRU = 5.77 ± 0.24 mg/L).
SPSS version 11 for Windows was used for data analysis. Data are presented as means and SDs. Individuals' body weights at the beginning and at the end of the studies were compared by paired t test. Other statistical analyses employed are presented separately for the two studies.
Study 1: Dose-Response Study. Individuals' means of urinary sugars (sucrose, fructose, and the sum of both) were skewed; hence, they were transformed by square root transformation, whereas dietary sugars and sucrose data were normally distributed. The coefficient of variation (%CV; SD/mean × 100) was used to present the within- and between-subject variability in intake and excretion levels. Repeated measures two-way ANOVA was employed to assess the between-subjects effect and to compare the daily sugars excretion during different periods of sugars intake. Wilks' Lambda multivariate test and Eta squared were used to report the significance of the repeated-measures models and the effect size, respectively. Repeated-measures one-way ANOVA was used to compare the individuals' means of urinary sucrose and fructose excretion during different sugars intake periods. Spearman correlation coefficients were used to examine colinearity between dietary and urinary sugars. To further explore the association between urinary and dietary sugars, a linear regression model with the square root transformed individuals' mean sum of sucrose and fructose in urine as a dependent and mean total sugar intake as independent variable was fitted and adjusted R2 was reported. No effect of age, body weight, or physical activity was detected. The regression equation was therefore derived by plotting unadjusted nontransformed individuals' means of sugars excretion against their mean total sugars intake.
Study 2: Habitual Varying Diet Study. Both daily measurements and individuals' means of urinary sugars were skewed; hence, they were log10 transformed, whereas dietary sugars and sucrose data were normally distributed. To compare body weight between men and women, an independent t test was used. Randomization was done for each subject separately; first, randomly selecting 16 of 30 days diet and second, randomizing 8 of the 16 days. A paired t test was used to compare levels of sugars excretion and intake between the means of 30-day and randomized measurements. An ANOVA random effect model was employed to quantify variance components in sugar excretion and intake within and between subjects to calculate the ratio of within- to between-subject variance (σ2WS/σ2BS). Reproducibility of the dietary intake and urinary excretion measurements was assessed by the intraclass correlation coefficient, calculated as the ratio of between-subject variance, and the sum of within- and between-subject variance [σ2BS/(σ2BS + σ2WS)]. Spearman correlation coefficients were used to examine colinearity between dietary and urinary sugars. A hierarchical regression model with the log10 transformed individuals' mean sum of sucrose and fructose in urine as a dependent and mean total sugar intake as independent variable was fitted adjusted for sex, age, body weight, and physical activity. As there was little effect of these variables, the regression equation was derived by plotting nontransformed individuals' unadjusted means of sugar excretion against their mean total sugars intake.