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Updated: Sep 19, 2025

Human Circadian Phenotyping and Diurnal Performance Testing in the Real World
Published on: April 7, 2020
The potential of nighttime urine samples for epidemiologic research on sodium intake: Evidence from a
Pascal Geldsetzer1, Arthur Jaques2, Nancy R Cook3
1Division of Primary Care and Population Health, Department of Medicine, Stanford University School of Medicine, Stanford, CA, United States; Chan Zuckerberg Biohub - San Francisco, San Francisco, CA, United States.
Background:
The gold standard for measuring sodium intake is based on multiple 24-h urine sodium (UNa) collections, which are logistically complex and pose a high burden on study participants. Its major alternative, spot urine sampling, has been shown to lead to systematic bias in sodium intake estimation. Nighttime urine collections are a potential alternative, as they place a substantially lower burden on participants and are thus less likely to lead to underestimation of UNa compared with 24-h urinary collections.
Objectives:
We examined the possibility of estimating 24-h UNa excretion using nighttime collections only, both at the individual and population level.
Methods:
We used the data from the Swiss kidney project on genes in the hypertension cohort, containing 1757 24-h urine collections from 1090 individuals, divided into daytime and nighttime samples. The participants were adults of European ancestry living in Switzerland. We examined the ability to predict 24-h UNa excretion based on nighttime collections using the following 3 methods for sodium estimation: 1) normalization by collection duration, 2) normalization by mean urine volume, and 3) multivariable linear regression models.
Results:
The Pearson correlation coefficient for nighttime collections compared with the 24-h measurements were 0.661, 0.651, and 0.682-0.749 (depending on the regression model specifications) using the 3 nighttime collection methods of sodium estimation, respectively. All of the estimation methods led to different probability distributions from the target distribution. Method 1 showed systematic negative bias, method 1 and method 2 showed bias with respect to diabetes and hypertension status, and method 3 showed an overestimation of low excretion and an underestimation of high excretion.
Conclusions:
Estimating 24-h UNa excretion based on nighttime collections was found to be imprecise and/or biased at the individual level and failed to capture population-level characteristics beyond central tendency.
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