Ken Uechi1, Keiko Asakura, Yui Ri, Shizuko Masayasu, Satoshi Sasaki. 1. aDepartment of Social and Preventive Epidemiology, School of Public HealthbInterfaculty Initiative in Information Studies, the University of Tokyo, TokyocIkurien-naka, Ibaraki, Japan.
Abstract
OBJECTIVE: Several estimation methods for 24-h sodium excretion using spot urine sample have been reported, but accurate estimation at the individual level remains difficult. We aimed to clarify the most accurate method of estimating 24-h sodium excretion with different numbers of available spot urine samples. METHODS: A total of 370 participants from throughout Japan collected multiple 24-h urine and spot urine samples independently. Participants were allocated randomly into a development and a validation dataset. Two estimation methods were established in the development dataset using the two 24-h sodium excretion samples as reference: the 'simple mean method' estimated by multiplying the sodium-creatinine ratio by predicted 24-h creatinine excretion, whereas the 'regression method' employed linear regression analysis. The accuracy of the two methods was examined by comparing the estimated means and concordance correlation coefficients (CCC) in the validation dataset. RESULTS: Mean sodium excretion by the simple mean method with three spot urine samples was closest to that by 24-h collection (difference: -1.62 mmol/day). CCC with the simple mean method increased with an increased number of spot urine samples at 0.20, 0.31, and 0.42 using one, two, and three samples, respectively. This method with three spot urine samples yielded higher CCC than the regression method (0.40). When only one spot urine sample was available for each study participant, CCC was higher with the regression method (0.36). CONCLUSION: The simple mean method with three spot urine samples yielded the most accurate estimates of sodium excretion. When only one spot urine sample was available, the regression method was preferable.
OBJECTIVE: Several estimation methods for 24-h sodium excretion using spot urine sample have been reported, but accurate estimation at the individual level remains difficult. We aimed to clarify the most accurate method of estimating 24-h sodium excretion with different numbers of available spot urine samples. METHODS: A total of 370 participants from throughout Japan collected multiple 24-h urine and spot urine samples independently. Participants were allocated randomly into a development and a validation dataset. Two estimation methods were established in the development dataset using the two 24-h sodium excretion samples as reference: the 'simple mean method' estimated by multiplying the sodium-creatinine ratio by predicted 24-h creatinine excretion, whereas the 'regression method' employed linear regression analysis. The accuracy of the two methods was examined by comparing the estimated means and concordance correlation coefficients (CCC) in the validation dataset. RESULTS: Mean sodium excretion by the simple mean method with three spot urine samples was closest to that by 24-h collection (difference: -1.62 mmol/day). CCC with the simple mean method increased with an increased number of spot urine samples at 0.20, 0.31, and 0.42 using one, two, and three samples, respectively. This method with three spot urine samples yielded higher CCC than the regression method (0.40). When only one spot urine sample was available for each study participant, CCC was higher with the regression method (0.36). CONCLUSION: The simple mean method with three spot urine samples yielded the most accurate estimates of sodium excretion. When only one spot urine sample was available, the regression method was preferable.
Authors: Norm R C Campbell; Feng J He; Monique Tan; Francesco P Cappuccio; Bruce Neal; Mark Woodward; Mary E Cogswell; Rachael McLean; Joanne Arcand; Graham MacGregor; Paul Whelton; Antti Jula; Mary R L'Abbe; Laura K Cobb; Daniel T Lackland Journal: J Clin Hypertens (Greenwich) Date: 2019-05-14 Impact factor: 3.738
Authors: Karen Elizabeth Charlton; Aletta Elisabeth Schutte; Leanda Wepener; Barbara Corso; Paul Kowal; Lisa Jayne Ware Journal: Nutrients Date: 2020-07-08 Impact factor: 5.717