Estimating 24-hour Urinary Excretion of Sodium and Potassium is More Reliable from 24-hour Urine than Spot Urine Sample in a Feeding Study of US Older Postmenopausal Women

Author:

Tinker Lesley F1ORCID,Huang Ying1,Johnson Karen C2,Carbone Laura D3,Snetselaar Linda4,Van Horn Linda5ORCID,Manson JoAnn E6,Liu Simin7ORCID,Mossavar-Rahmani Yasmin8ORCID,Prentice Ross L1,Lampe Johanna W1ORCID,Neuhouser Marian L1ORCID

Affiliation:

1. Division of Public Health Sciences, Cancer Prevention Program, Fred Hutchinson Cancer Research Center, Seattle, WA

2. Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis, TN

3. Department of Medicine, Medical College of Georgia at Augusta University, and J. Harold Harrison, MD, Distinguished University Chair in Rheumatology, Augusta, GA

4. Department of Epidemiology, College of Public Health, University of Iowa, Iowa City, IA

5. Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL

6. Division of Preventive Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA

7. Departments of Epidemiology Medicine and Surgery, and Center for Global Cardiometabolic Health, Brown University

8. Department of Epidemiology & Population Health Albert Einstein College of Medicine, Bronx, NY

Abstract

Abstract Background Assessing estimated sodium (Na) and potassium (K) intakes derived from 24-h urinary excretions versus a spot urine sample if comparable could reduce participant burden in epidemiologic and clinical studies. Objectives In a two-week controlled feeding study, Na and K excretion from a 24-h urine collection were compared with a first void spot urine sample, applying established algorithms and enhanced models to estimate 24-h excretion. Actual and estimated 24-h excretions were evaluated relative to mean daily Na and K intakes in the feeding study. Methods 153 older postmenopausal women ages 75.4 ± 3.5 years participated in a 2-week controlled feeding study with a 4-day repeating menu cycle based on their usual intake (ClinicalTrials.gov Identifier: NCT00000611). Of the 150 participants who provided both a first void spot urine sample and a 24-h urine collection on the penultimate study day, statistical methods included Pearson correlations for Na and K between intake, 24-h collections and the 24-h estimated excretions using four established algorithms; enhanced biomarker models by regressing ln-transformed intakes on ln-transformed 24-h excretions or ln-transformed 24-h estimated excretions plus participant characteristics; and sensitivity analyses for factors potentially influencing Na or K excretion, e.g., possible kidney disease estimated eGFR < 60 mL/min/1.73m). Results Pearson correlation coefficients between Na and K intakes and actual 24-h excretions were 0.57 and 0.38–0.44 for estimated 24-h excretions, depending on electrolyte and algorithm used. Enhanced biomarker model cross-validated R2 (CVR2s) for 24-h excretions were 38.5% (Na), 40.2% (K) and 42.0% (Na/K). After excluding participants with possible kidney disease, the CVR2s were 43.2% (Na), 40.2% (K) and 38.1% (Na/K). Conclusions 24-h urine excretion measurement performs better than estimated 24-h excretion from a spot urine as a biomarker for Na and K intake among a sample of primarily white postmenopausal women. Summary 24-h urine excretion measurement performs better than estimated 24-h excretion from a spot urine as a biomarker for Na and K intake among a sample of primarily white postmenopausal women.

Publisher

Oxford University Press (OUP)

Subject

Nutrition and Dietetics,Food Science,Medicine (miscellaneous)

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3