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HTN: Potassium (2015)


Hedayati SS, Minhajuddin AT, Ijaz A, Moe OW, Elsayed EF, Reilly RF, Huang CL. Association of urinary sodium/potassium ratio with blood pressure: sex and racial differences. Clin J Am Soc Nephrol. 2012; 7 (2): 315-322.

PubMed ID: 22114147
Study Design:
Cross-Sectional Study
D - Click here for explanation of classification scheme.
Quality Rating:
Neutral NEUTRAL: See Quality Criteria Checklist below.
Research Purpose:
  • To investigate the association of urinary sodium:potassium ratio [U(Na+)/K+] with increased systolic blood pressure and diastolic blood pressure independent of cardiovascular risk factors, albuminuria and estimated glomerular filtration rate (eGRF)
  • To further delineate whether an interaction by race or sex exists.
Inclusion Criteria:
Participants in the Dallas Heart Study which was a cross-sectional population based sample of Dallas county residents aged 30 years to 65 years.
Exclusion Criteria:
Participants where serum and urine creatinine, urine electrolytes and urine microalbumin and eGRF were not available.
Description of Study Protocol:


Participants were part of the Dallas Heart Study.


Cross-sectional study.

Blinding Used

Implied with measurements

Statistical Analysis

  • For bivariate comparisons, categorical variables were compared using the chi-squared test and continuous variables were compared using the T-test
  • Multivariate robust linear regression was used to evaluate the association of U[Na+]/[K+] with SBP and DBP
  • To minimize any potential effect of the right-skewed U[Na+]/[K+] distribution on the regression fit, robust linear regression estimation was used instead of classic linear regression
  • Robust regression is less sensitive to the extreme values of predictors; thus, the regression fit is less affected by the skewed U[Na+]/[K+] distribution
  • Regression diagnostics were used to explore the presence and effect of potential outliers (influence points) and less than 2.5% of the sample was classified as outliers, which is considered acceptable
  • The association between U[Na+]/[K+] as an independent variable and the presence of hypertension as the dependent variable was explored using logistic regression
  • Other candidate covariates were included in the multivariable models if clinically relevant or statistically significant in univariate analyses
  • The interaction of race X U[Na+]/[K+] and sex X U[Na+]/[K+] were also tested
  • To test the potential effect of diuretics, angiotensin-converting enzyme (ACE) inhibitors and angiotensin receptors blockers (ARBs) on urinary Na+ and K+ excretion did not significantly affect the results, sensitivity analyses with the exclusion of participants receiving treatment with these medications were performed
  • All statistical tests were two-sided, were conducted at the 0.05 significance level and were reported using P values
  • Interaction term P<0.01 were considered statistically significant.
Data Collection Summary:

Timing of Measurements

An in-home visit was performed for fasting venous blood and first-void morning urine samples. Five BP measurements were taken by trained personnel and the mean of the third, fourth and fifth measurements was used for analysis.

Dependent Variables

Presence of hypertension was defined as:

  • Self-reported diagnosis
  • Treatment for hypertension
  • SBP of 140mm Hg or higher
  • DBP of 90mm Hg or higher.

Independent Variables

Urine [NA+]/[K+].

Control Variables

  • Age
  • Sex
  • African-Americans
  • Diabetes mellitus
  • Smoker status
  • Body mass index (BMI)
  • Total cholesterol
  • eGRF
  • Urine albumin:creatinine ratio (UACR)
  • Diuretic use
  • ACE inhibitor use
  • ARB medication use.
Description of Actual Data Sample:
  • Initial N: N=3,557
  • Attrition (final N): N=3,303, 55.9% women
  • Age: Aged 30 years to 65 years, mean age was 43±10.1 years.


Ethnicity Percentage
African-American 52%
Caucasian 17.1%
Hispanic 17.1%
Other races 2.1%


Dallas County, Texas, United States.


Summary of Results:

Key Findings

Characteristics of the Cohort

  • Thirty-six percent had hypertension and 21% were being treated with anti-hypertensive medications
  • Mean SBP and DBP were 125.2±19mm Hg and 78.5±10.3mm Hg, respectively
  • The African-American group had a higher mean age than the non-African-American group, but the proportions of men and women did not significantly differ
  • A higher proportion of of African-Americans was diabetic, hypertensive and treated with anti-hypertensive medications
  • Mean SBP and DBP were higher among African Americans vs. non-African Americans at 130.5/81.2±20/10.7mm Hg vs. 119.5/75.5±16.1/9.1mm Hg, respectively (P<0.001)
  • The mean UACR was 32.4mm per g in African Americans and 10.4mg per g in non-Africans (P<0.001)
  •  U[NA+]/[K+] was 4.4±3 and 4.1±2.5 in the two racial groups, respectively (P=0.002)
  • Corresponding median values were 3.7 (3.2) for African Americans and 3.6 (2.8) for non-African Americans.

Univariate Associations Between Risk Factors and U[NA+]/[K+]

SBP and DBP, BMI and serum glucose were significantly and directly associated with U[NA+]/[K+] and UACR was indirectly correlated. Categorical variables significantly associated with higher U[NA+]/[K+] in univariate models included African-American racial group and presence of hypertension and non-smoker status.

Relationships Between U[NA+]/[K+] and BP
  • SBP increased by 1.58mm Hg (95% CI: 0.9, 2.2) per each three-unit increase in U[NA+]/[K+] and DBP increased by 1.02mmHg (95% CI: 0.6, 1.4) (P<0.001 for both correlations)
  • In adjusted models, SBP was 1.16mm Hg (95% CI: 0.6, 1.7) and DBP was 0.84mm Hg (95% CI: 0.5, 1.2) higher for each three-unit increase in U[NA+]/[K+] (P<0.01 for both associations)
  • Other factors associated with both SBP and DBP in multivariate models included age, male sex, African-American race and presence of diabetes mellitus, as will as higher BMI, total cholesterol and UACR
  • Smoker status was also associated with DBP and there was also a small but statistically significant correlation between eGRF and SBP
  • Of the 3,303 participants, 519 (15.7%) were receiving treatment with one or more diuretic, ACE inhibitor or ARB medication classes that could potentially affect urinary Na+ or K+
  • Sensitivity analyses by the exclusion of participants receiving treatment with these medications did not significantly affect the results
  • Finally, U[NA+]/[K+] was significantly associated with the presence of hypertension using logistic regression with an odds ratio of 1.13 (95%CI: 1.05, 1.22) in the univariate model and 1.12 (95% CI: 1.02, 1.22) in the multivariate model for each three-unit increase in U[NA+]/[K+].
Race and Sex Interactions
  • After stratification by race, in multi-variable models SBP increased by 1.22mm Hg (95% CI: 0.42, 2.01) for each three-unit increase in U[NA+]/[K+] (P=0.003) and DBP increased by 0.75mm Hg (95% CI: 0.27, 1.24 (P=0.002) in the African-American racial group
  • Corresponding values in non-African Americans were 1.09mm Hg (95% CI: 0.35, 1.82) for SBP and 0.91mm Hg (95% CI: 0.43, 1.40) for DBP
  • For any value of U[NA+]/[K+], on average, African Americans had an 11mm Hg higher SBP and 5.4mm Hg higher DBP than their non-African-American counterparts
  • The presence of African-American race vs. non-African-American increased the odds of having hypertension by 2.5 (multivariate OR, 2.51; 95% CI: 2.11, 3)
  • However, there was no statistically significant interaction detected between African-American race and U[NA+]/[K+] in models of systolic or DBP (interaction P values 0.7 and 0.4, respectively) or in models in which hypertension was the outcome measure
  • To investigate whether the absence of an effect of race on the correlation between U[NA+]/[K+] and BP was not diluted by the mixed racial composition of the non-African-American group, an exploratory analysis was performed in which three racial groups were considered separately: African Americans, Caucasians and others.
  • In that analysis, a significant U[NA+]/[K+] X race interaction was not found (P=0.38)
  • Sensitivity analysis by the exclusion of participants receiving diuretics, ACE inhibitors or ARBs attenuated the magnitude of the association between U[NA+]/[K+] and both SBP and DBP in African Americans but not in non-African Americans
  • SBP increased to a greater degree in men compared with women for every three-unit increase in U[NA+]/[K+], 1.57mm Hg (95% CI: 0.78, 2.36) vs. 0.89mm Hg (95% CI: 0.18, 1.61) in the adjusted models
  • The magnitude of the increase in DBP in men was more then two-fold that in women [1.27mm Hg (95% CI: 0.75, 1.78) vs. 0.51mm Hg (95% CI: 0.06, 0.96)] with an interaction P value that was statistically significant (P=0.03 for the multivariate model)
  • However, the U[NA+]/[K+]  X sex interaction P value for SBP was 0.1 and did not reach statistical significance
  • The U[NA+]/[K+] X sex interaction terms were also statistically significant after participants receiving treatment with diuretics, ACE inhibitors or ARB's were excluded (P=0.09 for SBP and P=0.06 for DBP)
  • In linear regression of U[NA+]/[K+] on SBP and DBP, for each value of U[NA+]/[K+], African Americans had a higher BP than non-African Americans. Similar results were observed for men compared with women.
Author Conclusion:
The findings indicate a robust positive correlation between U[NA+]/[K+] and prevalent BP independently of most relevant clinical covariates. The unique advantage of this study is the concurrent availability of data on kidney function and albuminuria. The analysis supports the hypothesis that dietary Na+ and K+ deficiency may play an important role in hypertension pathogenesis and extends the findings across both sexes and racial groups in a multi-ethnic sample. It further demonstrates that this association may be independent of other traditional cardiovascular risk factors and measures of kidney function.
Funding Source:
Government: National Center for Research Resources of the National Institutes of Health
University/Hospital: University of Texas Southwestern Medical Center O'Brien Kidney Research Core Center
Charles and Jane Pak Center for Mineral Metabolism, Simmons Family Foundations, Donald W. Reynolds Foundation
Foundation associated with industry:
Reviewer Comments:
The authors note the following limitations:
  • Given the cross-sectional nature of the analysis, future studies need to determine whether these relationships would hold longitudinally both by virtue of changes in diet (repeatability of the measurements) and the variability of BP over time
  • Further studies need to elucidate whether differences in urinary NA+/K+ ratio can be primarily explained by dietary Na+ and K+ intake or whether sex and racial differences in renal Na+ and K+ handling are also implicated
  • Larger trials are necessary to evaluate whether long-term dietary modifications in pre-hypertensive participants would decrease progression to hypertension and diminish long-term cardiovascular events.
Quality Criteria Checklist: Primary Research
Relevance Questions
  1. Would implementing the studied intervention or procedure (if found successful) result in improved outcomes for the patients/clients/population group? (Not Applicable for some epidemiological studies) Yes
  2. Did the authors study an outcome (dependent variable) or topic that the patients/clients/population group would care about? Yes
  3. Is the focus of the intervention or procedure (independent variable) or topic of study a common issue of concern to dieteticspractice? Yes
  4. Is the intervention or procedure feasible? (NA for some epidemiological studies) Yes
Validity Questions
1. Was the research question clearly stated? Yes
  1.1. Was (were) the specific intervention(s) or procedure(s) [independent variable(s)] identified? Yes
  1.2. Was (were) the outcome(s) [dependent variable(s)] clearly indicated? Yes
  1.3. Were the target population and setting specified? Yes
2. Was the selection of study subjects/patients free from bias? ???
  2.1. Were inclusion/exclusion criteria specified (e.g., risk, point in disease progression, diagnostic or prognosis criteria), and with sufficient detail and without omitting criteria critical to the study? Yes
  2.2. Were criteria applied equally to all study groups? Yes
  2.3. Were health, demographics, and other characteristics of subjects described? Yes
  2.4. Were the subjects/patients a representative sample of the relevant population? No
3. Were study groups comparable? Yes
  3.1. Was the method of assigning subjects/patients to groups described and unbiased? (Method of randomization identified if RCT) Yes
  3.2. Were distribution of disease status, prognostic factors, and other factors (e.g., demographics) similar across study groups at baseline? Yes
  3.3. Were concurrent controls or comparisons used? (Concurrent preferred over historical control or comparison groups.) Yes
  3.4. If cohort study or cross-sectional study, were groups comparable on important confounding factors and/or were preexisting differences accounted for by using appropriate adjustments in statistical analysis? Yes
  3.5. If case control study, were potential confounding factors comparable for cases and controls? (If case series or trial with subjects serving as own control, this criterion is not applicable.) N/A
  3.6. If diagnostic test, was there an independent blind comparison with an appropriate reference standard (e.g., "gold standard")? N/A
4. Was method of handling withdrawals described? Yes
  4.1. Were follow-up methods described and the same for all groups? Yes
  4.2. Was the number, characteristics of withdrawals (i.e., dropouts, lost to follow up, attrition rate) and/or response rate (cross-sectional studies) described for each group? (Follow up goal for a strong study is 80%.) Yes
  4.3. Were all enrolled subjects/patients (in the original sample) accounted for? Yes
  4.4. Were reasons for withdrawals similar across groups? N/A
  4.5. If diagnostic test, was decision to perform reference test not dependent on results of test under study? N/A
5. Was blinding used to prevent introduction of bias? Yes
  5.1. In intervention study, were subjects, clinicians/practitioners, and investigators blinded to treatment group, as appropriate? N/A
  5.2. Were data collectors blinded for outcomes assessment? (If outcome is measured using an objective test, such as a lab value, this criterion is assumed to be met.) N/A
  5.3. In cohort study or cross-sectional study, were measurements of outcomes and risk factors blinded? Yes
  5.4. In case control study, was case definition explicit and case ascertainment not influenced by exposure status? N/A
  5.5. In diagnostic study, were test results blinded to patient history and other test results? N/A
6. Were intervention/therapeutic regimens/exposure factor or procedure and any comparison(s) described in detail? Were interveningfactors described? Yes
  6.1. In RCT or other intervention trial, were protocols described for all regimens studied? N/A
  6.2. In observational study, were interventions, study settings, and clinicians/provider described? Yes
  6.3. Was the intensity and duration of the intervention or exposure factor sufficient to produce a meaningful effect? Yes
  6.4. Was the amount of exposure and, if relevant, subject/patient compliance measured? Yes
  6.5. Were co-interventions (e.g., ancillary treatments, other therapies) described? Yes
  6.6. Were extra or unplanned treatments described? Yes
  6.7. Was the information for 6.4, 6.5, and 6.6 assessed the same way for all groups? Yes
  6.8. In diagnostic study, were details of test administration and replication sufficient? N/A
7. Were outcomes clearly defined and the measurements valid and reliable? Yes
  7.1. Were primary and secondary endpoints described and relevant to the question? Yes
  7.2. Were nutrition measures appropriate to question and outcomes of concern? Yes
  7.3. Was the period of follow-up long enough for important outcome(s) to occur? N/A
  7.4. Were the observations and measurements based on standard, valid, and reliable data collection instruments/tests/procedures? Yes
  7.5. Was the measurement of effect at an appropriate level of precision? Yes
  7.6. Were other factors accounted for (measured) that could affect outcomes? Yes
  7.7. Were the measurements conducted consistently across groups? Yes
8. Was the statistical analysis appropriate for the study design and type of outcome indicators? Yes
  8.1. Were statistical analyses adequately described and the results reported appropriately? Yes
  8.2. Were correct statistical tests used and assumptions of test not violated? Yes
  8.3. Were statistics reported with levels of significance and/or confidence intervals? Yes
  8.4. Was "intent to treat" analysis of outcomes done (and as appropriate, was there an analysis of outcomes for those maximally exposed or a dose-response analysis)? N/A
  8.5. Were adequate adjustments made for effects of confounding factors that might have affected the outcomes (e.g., multivariate analyses)? Yes
  8.6. Was clinical significance as well as statistical significance reported? Yes
  8.7. If negative findings, was a power calculation reported to address type 2 error? N/A
9. Are conclusions supported by results with biases and limitations taken into consideration? Yes
  9.1. Is there a discussion of findings? Yes
  9.2. Are biases and study limitations identified and discussed? Yes
10. Is bias due to study's funding or sponsorship unlikely? Yes
  10.1. Were sources of funding and investigators' affiliations described? Yes
  10.2. Was the study free from apparent conflict of interest? Yes