Abstract

Background: Excess dietary sodium (Na) intake is linked to adverse cardiovascular health; the population distribution of urinary sodium (UNa) values in the US is unknown. We examined the population distribution of UNa and the validity of existing equations predicting 24-h Na excretion from a single spot urine sample among older adults with and without hypertension. Methods: Demographic, anthropometric, lab, and diet data along with 24-h urine collections were obtained from 555 MESA and CARDIA participants aged 45-79y. One third provided a second 24-h urine collection. Four timed voids (morning, afternoon, evening, and overnight) and the 24-h collection were analyzed for Na, creatinine, potassium and chloride concentrations. We examined the distribution of 24-h excretion of each analyte overall and by gender-race subgroups and hypertensive (HTN) status. We then examined the mean differences (bias) and confidence intervals between measured 24-h UNa excretion and the predicted from spot urine using 4 published equations by specimen timing, race-gender subgroups, and HTN status. Results: Using preliminary data from 265 participants with completed laboratory analysis, 55% female, 61% Black, and 60% had HTN. Mean 24-h Na excretion was 4234 ± 1920 mg for white men, 2706 ± 1136 mg for white women, 3463 ± 1691 mg for Black men and 3415 ± 1635 mg for Black women and did not significantly differ by hypertensive status. Mean bias in predicting 24-h Na excretion overall ranged from -268 (95% CI: -443.5, -91.8) to 1045 (849.3, 1240.4) mg/d. (Table) Conclusion: Among this group of older adults and those with hypertension, the mean 24-h UNa excretion levels for all race-gender groups exceeded current recommendations of 2,300 mg/d, with significant variation by race and gender. All of the four published equations under or overestimated mean 24-h Na excretion when using a single, timed spot urine sample but using evening samples appeared to produce the least bias. These preliminary findings are tentative until confirmed with the full dataset.

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