Evidence map›Paper›PMID 25646336›Full record

ArticleThe American journal of clinical nutrition2015

Difference between 24-h diet recall and urine excretion for assessing population sodium and potassium intake in adults aged 18-39 y.

Carla I Mercado, Mary E Cogswell, Amy L Valderrama, Chia-Yih Wang, Catherine M Loria, Alanna J Moshfegh, Donna G Rhodes, Alicia L Carriquiry

Registry-linked trialOpen access · bronzeAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in The American journal of clinical nutrition, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01631240 (National Health and Nutrition Examination Survey), which is not on this map. Cited by 40 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed, 2 pooled it
4.0field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT01631240 completednot on this map

National Health and Nutrition Examination Survey (NHANES), Urinary Sodium Calibration Study

TypeobservationalSponsorCenters for Disease Control and PreventionRan2011 to 2011Enrolled441ConditionsNutrition Assessment
3 · Its place in the literature

Who cites it

40 citing papers in PubMed, 2 syntheses or guidelines pooled it, 50 citations in OpenAlex.

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  8. Validation of the Brasil-Nutri software for 24-hour dietary recall using recovery biomarkers.Revista brasileira de epidemiologia = Brazilian journal of epidemiology · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 1 institution in 1 country.

Carla I MercadoFrom the Division for Heart Disease and Stroke Prevention, National Center for Chronic Disease Prevention and Health Promotion, Atlanta, GA (CIM, MEC, and ALV); the Division of Health and Nutrition Examination Surveys, National Center for Health Statistics, Hyattsville, MD (C-YW), the Centers for Disease Control and Prevention; National Heart, Lung, and Blood Institute, NIH, Bethesda, MD (CML); the Beltsville Human Nutrition Research Center, Agricultural Research Service, USDA, Beltsville, MD (AJM and DGR); and the Department of Statistics, Iowa State University, Ames, IA (ALC).
Mary E CogswellFrom the Division for Heart Disease and Stroke Prevention, National Center for Chronic Disease Prevention and Health Promotion, Atlanta, GA (CIM, MEC, and ALV); the Division of Health and Nutrition Examination Surveys, National Center for Health Statistics, Hyattsville, MD (C-YW), the Centers for Disease Control and Prevention; National Heart, Lung, and Blood Institute, NIH, Bethesda, MD (CML); the Beltsville Human Nutrition Research Center, Agricultural Research Service, USDA, Beltsville, MD (AJM and DGR); and the Department of Statistics, Iowa State University, Ames, IA (ALC).
Amy L ValderramaFrom the Division for Heart Disease and Stroke Prevention, National Center for Chronic Disease Prevention and Health Promotion, Atlanta, GA (CIM, MEC, and ALV); the Division of Health and Nutrition Examination Surveys, National Center for Health Statistics, Hyattsville, MD (C-YW), the Centers for Disease Control and Prevention; National Heart, Lung, and Blood Institute, NIH, Bethesda, MD (CML); the Beltsville Human Nutrition Research Center, Agricultural Research Service, USDA, Beltsville, MD (AJM and DGR); and the Department of Statistics, Iowa State University, Ames, IA (ALC).
Chia-Yih WangFrom the Division for Heart Disease and Stroke Prevention, National Center for Chronic Disease Prevention and Health Promotion, Atlanta, GA (CIM, MEC, and ALV); the Division of Health and Nutrition Examination Surveys, National Center for Health Statistics, Hyattsville, MD (C-YW), the Centers for Disease Control and Prevention; National Heart, Lung, and Blood Institute, NIH, Bethesda, MD (CML); the Beltsville Human Nutrition Research Center, Agricultural Research Service, USDA, Beltsville, MD (AJM and DGR); and the Department of Statistics, Iowa State University, Ames, IA (ALC).
Catherine M LoriaFrom the Division for Heart Disease and Stroke Prevention, National Center for Chronic Disease Prevention and Health Promotion, Atlanta, GA (CIM, MEC, and ALV); the Division of Health and Nutrition Examination Surveys, National Center for Health Statistics, Hyattsville, MD (C-YW), the Centers for Disease Control and Prevention; National Heart, Lung, and Blood Institute, NIH, Bethesda, MD (CML); the Beltsville Human Nutrition Research Center, Agricultural Research Service, USDA, Beltsville, MD (AJM and DGR); and the Department of Statistics, Iowa State University, Ames, IA (ALC).
Alanna J MoshfeghFrom the Division for Heart Disease and Stroke Prevention, National Center for Chronic Disease Prevention and Health Promotion, Atlanta, GA (CIM, MEC, and ALV); the Division of Health and Nutrition Examination Surveys, National Center for Health Statistics, Hyattsville, MD (C-YW), the Centers for Disease Control and Prevention; National Heart, Lung, and Blood Institute, NIH, Bethesda, MD (CML); the Beltsville Human Nutrition Research Center, Agricultural Research Service, USDA, Beltsville, MD (AJM and DGR); and the Department of Statistics, Iowa State University, Ames, IA (ALC).
Donna G RhodesFrom the Division for Heart Disease and Stroke Prevention, National Center for Chronic Disease Prevention and Health Promotion, Atlanta, GA (CIM, MEC, and ALV); the Division of Health and Nutrition Examination Surveys, National Center for Health Statistics, Hyattsville, MD (C-YW), the Centers for Disease Control and Prevention; National Heart, Lung, and Blood Institute, NIH, Bethesda, MD (CML); the Beltsville Human Nutrition Research Center, Agricultural Research Service, USDA, Beltsville, MD (AJM and DGR); and the Department of Statistics, Iowa State University, Ames, IA (ALC).
Alicia L CarriquiryFrom the Division for Heart Disease and Stroke Prevention, National Center for Chronic Disease Prevention and Health Promotion, Atlanta, GA (CIM, MEC, and ALV); the Division of Health and Nutrition Examination Surveys, National Center for Health Statistics, Hyattsville, MD (C-YW), the Centers for Disease Control and Prevention; National Heart, Lung, and Blood Institute, NIH, Bethesda, MD (CML); the Beltsville Human Nutrition Research Center, Agricultural Research Service, USDA, Beltsville, MD (AJM and DGR); and the Department of Statistics, Iowa State University, Ames, IA (ALC).
Centers for Disease Control and Prevention · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLimited data are available on the accuracy of 24-h dietary recalls used to monitor US sodium and potassium intakes.

objectiveWe examined the difference in usual sodium and potassium intakes estimated from 24-h dietary recalls and urine collections.

designWe used data from a cross-sectional study in 402 participants aged 18-39 y (∼50% African American) in the Washington, DC, metropolitan area in 2011. We estimated means and percentiles of usual intakes of daily dietary sodium (dNa) and potassium (dK) and 24-h urine excretion of sodium (uNa) and potassium (uK). We examined Spearman's correlations and differences between estimates from dietary and urine measures. Multiple linear regressions were used to evaluate the factors associated with the difference between dietary and urine measures.

resultsMean differences between diet and urine estimates were higher in men [dNa - uNa (95% CI) = 936.8 (787.1, 1086.5) mg/d and dK - uK = 571.3 (448.3, 694.3) mg/d] than in women [dNa - uNa (95% CI) = 108.3 (11.1, 205.4) mg/d and dK - uK = 163.4 (85.3, 241.5 mg/d)]. Percentile distributions of diet and urine estimates for sodium and potassium differed for men. Spearman's correlations between measures were 0.16 for men and 0.25 for women for sodium and 0.39 for men and 0.29 for women for potassium. Urinary creatinine, total caloric intake, and percentages of nutrient intake from mixed dishes were independently and consistently associated with the differences between diet and urine estimates of sodium and potassium intake. For men, body mass index was also associated. Race was associated with differences in estimates of potassium intake.

conclusionsLow correlations and differences between dietary and urinary sodium or potassium may be due to measurement error in one or both estimates. Future analyses using these methods to assess sodium and potassium intake in relation to health outcomes may consider stratifying by factors associated with the differences in estimates from these methods. This trial was registered at clinicaltrials.gov as NCT01631240.

Indexed as

Mental RecallAdolescentAdultBiomarkersBody Mass IndexCross-Sectional StudiesDietEthnicityFemaleHumansLinear ModelsMalePotassium, DietaryReproducibility of ResultsSodium, DietaryYoung AdultBiomarkersPotassium, DietarySodium, Dietarybiomarkerdietsodiumurinevalidation study

Identifiers

PMID25646336
PMCPMC4307208
OpenAlexW2037105492

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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.