Abstract
There is growing interest in assessing a population's prevalence of inadequate nutrient intake using biomarkers. However, within-person variation is generally ignored because repeated data collections are considered costly and burdensome. The study aimed to show the importance of estimating, from repeated 24-h urine collections, a population's habitual salt intake and to explore the potential of using the ratio of within-person variance to total variance from an external source (W:T variance) with single 24-h urine collection. Salt intake was predicted from data for 24-h urinary sodium excretion in adult kidney transplant recipients in 1992-1997 (n=432) and 2006-2011 (n=1159). The salt intake distribution of single-day measurements was compared with estimates from multiple 24-h urine collections, which were statistically corrected for within-person variance. Habitual salt intake was also estimated using single-day measurements and external variance estimates. From each distribution, the proportion below specified cut-off values was estimated. In 2006-2011 the average habitual salt intake was 10.6 g/d (men) and 8.5 g/d (women); in 1992-1997 these values were 8.6 g/d and 7.5 g/d, respectively. The proportion with salt intake <6 g/d was 5% and 13% in 2006-2011 and 22% and 28% in 1992-1997, respectively, for men and women. Correction for within-person variance significantly narrowed the salt intake distribution-the proportion with salt intake <6 g/d was overestimated by 3-13 percentage points using single-day data. Sensitivity analyses showed the importance of a sufficient sample size for estimating variance components. Variation of the W:T variance showed up to 40 percentage points deviation in the proportion with intakes below a specified cut-off value. To estimate a population's salt intake distribution, it is important to correct 24-h urinary sodium excretion for within-person variance. Predicting habitual salt intake distribution using single-day measurements with external variances is promising; a sensitivity analysis is recommended to show the effect of different external variances.
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