Authors: Huang Y, Van Horn L, Tinker LF, Neuhouser ML, Carbone L, Mossavar-Rahmani Y, Thomas F, Prentice RL
Citation: Hypertension 2014 Feb;63(2):238-44
PMID : 24277763, Journal: Hypertension, 63, 2
Date created: 2014-01-09
Epidemiological studies of the association of sodium and potassium intake with cardiovascular disease risk have almost exclusively relied on self-reported dietary data. Here, 24-hour urinary excretion assessments are used to correct the dietary self-report data for measurement error under the assumption that 24-hour urine recovery provides a biomarker that differs from usual intake according to a classical measurement model. Under this assumption, dietary self-reports underestimate sodium by 0% to 15%, overestimate potassium by 8% to 15%, and underestimate sodium/potassium ratio by ≈20% using food frequency questionnaires, 4-day food records, or three 24-hour dietary recalls in Women’s Health Initiative studies. Calibration equations are developed by linear regression of log-transformed 24-hour urine assessments on corresponding log-transformed self-report assessments and several study subject characteristics. For each self-report method, the calibration equations turned out to depend on race and age and strongly on body mass index. After adjustment for temporal variation, calibration equations using food records or recalls explained 45% to 50% of the variation in (log-transformed) 24-hour urine assessments for sodium, 60% to 70% of the variation for potassium, and 55% to 60% of the variation for sodium/potassium ratio. These equations may be suitable for use in epidemiological disease association studies among postmenopausal women. The corresponding signals from food frequency questionnaire data were weak, but calibration equations for the ratios of sodium and potassium/total energy explained ≈35%, 50%, and 45% of log-biomarker variation for sodium, potassium, and their ratio, respectively, after the adjustment for temporal biomarker variation and may be suitable for cautious use in epidemiological studies. Clinical Trial Registration- URL: www.clinicaltrials.gov. Unique identifier: NCT00000611.