joint association of urinary sodium and potassium · confidential: for review only 4 abstract...

Confidential: For Review Only

Joint Association of Urinary Sodium and Potassium

Excretion with Cardiovascular Events and Mortality

A Prospective Cohort Study

Journal: BMJ

Manuscript ID BMJ.2018.046280

Article Type: Research

BMJ Journal: BMJ

Date Submitted by the Author: 30-Jul-2018

Complete List of Authors: O Donnell, Martin; National University of Ireland, Galway, HRB Clinical Research Facility Mente, Andrew; Population Health Research Institute Hamilton General Hospital Hamilton Canada Rangarajan, Sumathy; Population Health Research Institute, Hamilton Health Sciences/McMaster University, McQueeen, Matthew; Hamilton Health Sciences, Pathology and Molecular Medicine; McMaster University, Pathology and Molecular Medicine O'Leary , Neil; National University of Ireland Galway Yin, Lu; Chinese Academy of Medical Sciences and Peking Union Medical College, Fuwai Hospital, National Center for Cardiovascular Diseases Xiaoyun, Liu ; Chinese Academy of Cardiovascualr Diseases Swaminathan, Sumathi; St John's Research Institute, Division of Nutrition Khatib, Rasha; Northwestern University Rosengren, Annika; Institute of Medicine, Sahlgrenska Academy, Molecular and Clinical Medicine Ferguson, John; National University of Ireland Galway Smyth, Andrew; National University of Ireland Galway López-Jaramillo, Patricio; Universidad de Santander (UDES), Fundacion Oftalmologica de Santander (FOSCAL) and Medical School Diaz, Rafael; ECLA - Academic Research Organization, Avezum, Alvaro; Dante Pazzanese Institute of Cardiology, Lanas, Fernando; Universidad de La Frontera, Internal Medicine Noor Hassim, Ismail; Universiti Kebangsaan Malaysia, Department of Community Health Yussoff, Khalid; UCSI University Dans, Antonio; Lyceum of the Philippines University Iqbal, Romaina; Aga Khan University, Departments of Community Health Sciences and Medicine Szuba, Andrzej; Akademia Medyczna im Piastow Slaskich Wydzial Lekarski Mohammadifard, Noushin; Isfahan Cardiovascular Research Center Oguz, Aytekin; Istanbul Medeniyet Universitesi Tip Fakultesi Yusufali, Afzalhussein; Dubai Health Authority, Alhabib, Khalid; Dubai Medical University Kruger, Iolanthe; North-West University

https://mc.manuscriptcentral.com/bmj

BMJ

Confidential: For Review OnlyYusuf, Rita; Independent University Chifamba, Jephat; University of Zimbabwe, College Of Health Sciences, Physiology Yeates, Karen; Queen's University, Medicine Dagenais, Gilles; Laval University Heart and Lung Institute, Cardiology Wielgosz, Andreas; University of Ottawa Lear, Scott; Simon Fraser University, Faculty of Health Sciences Teo, Koon; Population Health Research Institute, Hamilton Health Sciences/McMaster University, Yusuf, Salim; McMaster University, Cardiology

Keywords: Cardiovascular, sodium, potassium, intake

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Joint Association of Urinary Sodium and Potassium Excretion with Cardiovascular Events

and Mortality

A Prospective Cohort Study

1,2Martin O’Donnell MB PhD, associate professor

1Andrew Mente PhD, associate professor

1Sumathy Rangarajan MSc, program manager

1Matthew J McQueen MB PhD, professor

2Neil

O’Leary, senior research fellow 3Yin Lu, senior researcher

3Xiaoyun Liu PhD,

senior

researcher 4Sumathy Swaminathan MD, associate professor

5Rasha Khatib PhD, senior

research fellow 6Annika Rosengren MD, professor

2 John Ferguson, senior research fellow

2Andrew Smyth, associate professor

7Patricio Lopez-Jaramillo MD, PhD, professor

8Rafael Diaz

MD, professor 9Alvaro Avezum MD, PhD, professor

10Fernando Lanas MD, professor

11Noorhassim Ismail MD PhD,

11Khalid Yussoff, professor

12Antonio Dans MD MSc, professor

13Romaina Iqbal PhD, associate professor

14Andrzej Szuba MD, PhD, professor,

15Noushin

Mohammadifard PhD, assistant professor 16

Atyekin Oguz MD, professor 17

Afzal Hussein

Yusufali MD, professor 18

Khalid F Alhabib MBBS, associate professor 19

Iolanthe Kruger PhD,

associate professor 20

Rita Yusuf PhD, professor and dean 21

Jephat Chifamba MPhil, senior

lecturer 22

Karen Yeates MD, associate professor 23

Gilles Dagenais MD, professor 24

Andreas

Wielgosz MD PhD, professor 25

Scott A. Lear PhD, professor 1Koon Teo MB PhD, professor

1Salim Yusuf DPhil, professor on behalf of the PURE Investigators.

On Behalf of the PURE Investigators

Affiliations:

1. Population Health Research Institute, Hamilton Health Sciences, McMaster University, Hamilton, Canada

2. HRB-Clinical Research Facility, Galway University Hospital, NUI Galway, Galway, Ireland

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3. Medical Research & Biometrics Center National Center for Cardiovascular Diseases Cardiovascular

Institute & Fuwai Hospital Chinese Academy of Medical Sciences Xishan Institute of Fuwai Hospital,

Fengcunxili, Mentougou Dist.Beijing 102300, China

4. Division of Epidemiology and Population Health, St. John’s Research Institute, Bangalore, Karnataka,

India

5. Departments of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.

6. Sahlgrenska Academy, University of Gothenburg, Sweden

7. Fundacion Oftalmologica de Santander (FOSCAL), Medical School, Universidad de Santander,

Floridablanca-Santander, Colombia

8. Estudios Clinicos Latinoamerica ECLA, Rosario, Santa Fe, Argentina

9. Dante Pazzanese Institute of Cardiology, Sao Paulo, SP Brazil

10. Universidad de La Frontera, Temuco, Chile

11. Department of Community Health. University Kebangsaan Malaysia Medical Centre, Malaysia

12. University of the Philippines – Manila, Pedro Gil St., Ermita, Manila, Philippines, 1000

13. Department of Community Health Sciences and Medicine, Aga Khan University, Karachi Pakistan

14. Wroclaw Medical University, Department of Food Science and Dietetics, Wroclaw; Poland

15. Isfahan Cardiovascular Research Center, Isfahan Cardiovascular Research Institute, Isfahan University of

Medical Sciences, Isfahan, Iran

16. Ankara University Faculty of Medicine, Department of Cardiology, Ankara, Turkey

17. Hatta Hospital, Dubai Health Authority. Dubai, United Arab Emirates

18. Department of Cardiac Sciences, King Fahad Cardiac Center, College of Medicine, King Saud University.

PO Box: 7805, Riyadh 11472, Saudi Arabia

19. Faculty of Health Science, North-West University, Potchefstroom campus, Potchefstroom, South Africa

20. School of Life Sciences and The Centre for Health, Population and Development. Independent University,

Bangladesh, Dhaka, Bangladesh

21. University of Zimbabwe, College of Health Sciences, Physiology Department, Harare, Zimbabwe

22. Dept of Medicine, School of Medicine, Queen’s University, Kingston, Canada

23. Laval University Heart and Lungs Institute, Quebec City, Canada

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24. Faculty of Medicine, University of Ottawa, Ottawa, Canada

25. Faculty of Health Sciences, Simon Fraser University, and Division of Cardiology, Providence Health Care,

BC, Canada

Correspondence: Dr. Martin O’Donnell, Population Health Research Institute, DBCVS

Research Institute, McMaster University, 2nd Floor, Room C2-104, 237 Barton St East,

Hamilton, Ontario, L8L 2X2, Canada. Telephone: 905-527-4322; Fax: 905-297-3782; E-mail:

[email protected]

Running head: Sodium and potassium excretion with mortality and cardiovascular disease

Word count: 3,503

Abstract word count: 372

Number of Tables/Figures: 7

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ABSTRACT

Objective: To evaluate the joint association of sodium and potassium urinary excretion

(surrogates of intake) with cardiovascular events and mortality, in the context of current World

Health Organisation recommendation (<2.0g/day of sodium and >3.5g/day of potassium).

Design: International prospective cohort study.

Setting: PURE study in 18 high, middle and low-income countries, sampled from urban and

rural communities.

Participants: We obtained morning fasting urine samples on 103,570 individuals and estimated

24-hour sodium and potassium excretion, surrogates for sodium and potassium intake.

Main Outcome Measures: We examined the association of estimated urinary sodium and

potassium excretion with all-cause mortality and major cardiovascular events, employing

multivariable Cox regression. A six-category variable for joint sodium and potassium was

generated, sodium excretion [low (<3g/day), moderate (3-5g/day) and high sodium (>5g/day)

intake], by potassium excretion [above and below median (2.1g/day)].

Results: Mean estimated sodium and potassium urinary excretion were 4.93 g/day and 2.12

g/day, respectively. After a mean follow-up of 8.1 years, 7,884 (6.1%) participants had died or

experienced a major cardiovascular event. Increasing urinary sodium excretion was positively

associated with increasing potassium excretion (unadjusted r=0.34), and only 0.001% had a

concomitant urinary excretion of <2.0g/day of sodium and >3.5g/day of potassium. We observed

a J-shaped association of sodium excretion, and inverse association of potassium excretion, with

death and cardiovascular events. For joint sodium and potassium excretion categories, the lowest

risk of death and cardiovascular events occurred in the group with moderate sodium excretion (3-

5g/day) and higher potassium excretion (21.9% of cohort). Compared to this reference group, the

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combinations of low potassium with low sodium excretion (HR 1.23; 1.11-1.37; 7.4% of cohort)

and low potassium with high sodium excretion (HR 1.21; 1.11-1.32; 13.8% of cohort) were

associated with the highest risk, followed by high sodium excretion (HR 1.10; 1.02-1.18 [29.6%

of cohort]) and low sodium excretion (HR 1.19; 1.02-1.38 [3.3% of cohort]) among those with

potassium excretion above median. Higher potassium excretion attenuated the increased

cardiovascular risk associated with high sodium excretion (P-interaction=0.007).

Conclusions: Our findings suggest that the simultaneous target of low sodium (<2g/day) with

high potassium intake (>3.5g/day) is impractical, and not associated with lowest cardiovascular

risk. Combined moderate sodium intake (3-5g/day) with high potassium intake is associated with

lowest risk of mortality and cardiovascular events.

Key Words: Sodium, Salt, Potassium, Cardiovascular, Mortality

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INTRODUCTION

Consumption of sodium and potassium is essential to health, as neither are produced

endogenously and both are necessary for critical physiologic processes.1-3

Maintaining

homeostasis requires a mutual interdependence of sodium and potassium, meaning that their

relationship with health is necessarily linked.1-3

Despite these fundamental physiologic

considerations, current public health policy adopts markedly opposing guidance for sodium and

potassium intake, with the World Health Organisation (WHO) recommending extremely low

sodium intake (<2g/day, while the current average intake is about 4g/day), but high potassium

intake (>3.5g/day, while the average intake is about 2g/day) in the entire population.4,5,6

There

are limited international data reporting the percentage of people with both very low intakes of

sodium and simultaneously high potassium intakes7, and on their joint effects on health outcomes

from large international epidemiologic studies.4,5

Current public health policy is based primarily on small, and mostly short-term, clinical

trials evaluating the relationship of changes in sodium and potassium intake with blood

pressure.4,5

While clinical trials have reported a reduction in blood pressure with reducing

sodium intake,8, 9

many prospective cohort studies have reported a J-shaped association of

sodium intake and cardiovascular disease10-16

, with an increased risk emerging at sodium intake

under 3g/day, and above 5g/day.10

The increased cardiovascular risk associated with high sodium

intake appears to be largely confined to individuals with hypertension17

, while the increased risk

associated with low sodium intake may be mediated through activation of physiologic systems to

conserve sodium (e.g. renin-angiotensin-aldosterone system)18

In contrast, the association of

potassium intake with blood pressure and cardiovascular disease is consistent, with both a linear

reduction in blood pressure and cardiovascular risk reported with increasing potassium intake,

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reported in most studies.9 There are some epidemiologic reports of an interactive association of

sodium and potassium intake with blood pressure, and studies reporting use of sodium to

potassium ratios for predicting risk of cardiovascular events and mortality.19-25

Whether a

potential modifying effect of increased potassium intake is directly causal, or simply a marker of

improved diet quality26

, as diets rich in fruit and vegetables (which are associated with lower

cardiovascular risk) are high in potassium, is uncertain.3

The PURE prospective cohort study is the largest international study to evaluate the

association of sodium and potassium intake with health outcomes. We have previously reported

on the intermediate-term (3.7 years follow-up)16,17

association of sodium and potassium intake

with mortality and cardiovascular events. In the current analyses, we report on the association of

sodium and potassium intake with death and cardiovascular disease in extended follow-up (8

years). The larger event rate facilitates the exploration of the inter-relation of sodium and

potassium intake with mortality and cardiovascular events.

METHODS

Study Population

The Prospective Urban Rural Epidemiological Study (PURE Study) is a large-scale

epidemiological cohort study that has enrolled individuals (aged 35 to 70 years) residing in 628

urban and rural communities in low, middle and high-income countries (Bangladesh, India,

Pakistan, Zimbabwe, Argentina, Brazil, Chile, Malaysia, Poland, South Africa, Turkey, China,

Colombia, Iran, Canada, Sweden, and United Arab Emirates).27-29

A description of participant

selection is provided in the Supplementary Appendix. Recruitment began in January 2003. All

participants provided written informed consent. For the current analysis, we included 103,570

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participants who collected early morning fasting urine samples suitable for analysis from 18

countries, of which 103,200 (99.6%) had follow-up information available (95% completed at

least one follow-up visit). The study was coordinated by the Population Health Research

Institute, Hamilton Health Sciences, Hamilton, Ontario, Canada.

Exposure Assessments

A morning fasting mid-stream urine sample was collected from each participant, frozen at -20ºC

to -70ºC, and shipped to a central laboratory in Canada, China, India or Turkey. All urine

samples were shipped at ambient temperature using the STP 250 ambient specimen shipping

box. A description of the methods used for performing urinary analyses is provided in the

Supplementary Appendix. The Kawasaki formula was used to estimate 24-hour urinary sodium

and potassium excretion, and these estimates have been validated previously versus measured

with 24-hour urine collection.30, 31

Therefore, we used the estimates derived from fasting

morning urine as surrogates for sodium and potassium intake in the whole study. (Supplementary

appendix provides summary details of validation of this approach).

Ascertainment of Outcomes

Standardized case report forms were used to capture major cardiovascular events (myocardial

infarction, stroke and heart failure), cancer and death on follow-up, which were adjudicated

using standardized definitions.32

For the current analysis, we included all adjudicated outcome

events in the PURE database through September 2017. The primary composite outcome was all-

cause mortality, myocardial infarction, stroke and heart failure. Secondary outcome were

individual component of the primary composite, and new diagnosis of cancer on follow-up.

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Ascertainment of Covariates

Baseline standardised questionnaires were completed by all participants, which included detailed

information on age, sex, lifestyle risk factors (e.g. smoking, diet, physical activity, alcohol

intake), co-morbidities (e.g. prior history of diabetes, hypertension, cardiovascular disease)

physical measurements (blood pressure, heart rate, body mass index [BMI], waist-to-hip ratio)

and laboratory measurement of lipoproteins. A modified alternative healthy eating index score

(mAHEI) was used to measure overall diet quality, with higher score indicating a healthier diet.33

Patient Involvement

No patients were involved in setting the research question, outcome measures or design and

implementation of the study.

Statistical Analyses

Baseline differences in characteristics between study participants in different categories of

estimated sodium and potassium excretion have been reported previously, and included in

Supplementary Appendix.16

Restricted cubic spline plots were used to explore the shape of

association between estimated sodium and potassium excretion and outcomes, fitting a restricted

cubic spline function with four knots (5th

, 35th

, 65th

and 95th

percentiles).34

Our primary outcome

measure was the composite of all-cause mortality and major cardiovascular events

(cardiovascular death, stroke, myocardial infarction and heart failure). Secondary outcome

included individual components of the primary outcome.

Based on our restricted cubic spline plots for the primary outcome, and the results of

previous analyses10,16

, we selected 4 to 4.99 g/day as the reference category for sodium excretion

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and less than 1.5 g/day for potassium excretion. We modelled the time to event outcome using

multivariable Cox regression proportional hazards analysis with mixed effect (centre included as

a random effect variable to account for clustering by research site) to determine the association

between estimated urinary sodium and potassium excretion and outcomes, using three sequential

models. Model 1 (the primary model) adjusted for age (included as spline function), sex,

education, current and former alcohol intake (units per week), diabetes mellitus, body mass index

(BMI), physical activity, history of cardiovascular events, use of cardiovascular medications

(blood pressure lowering, statins or diabetes), history of tuberculosis, cancer, HIV, and current

and former smoking, which constituted our primary multivariable model (with an additional

model that included low-density lipoprotein [LDL] cholesterol/high-density lipoprotein [HDL]

cholesterol ratio). Model 2 also included caloric intake, estimated potassium (or sodium)

excretion, waist to hip ratio and modified alternative healthy eating index (mAHEI). Model 3

also included history of hypertension and baseline systolic and diastolic blood pressure and heart

rate, which are in the putative causal pathway. We performed an analysis of the combined effects

of sodium and potassium, in which we generated six categories with sodium excretion into low

(<3g/day), moderate (3-5g/day) and high sodium (>5g/day) excretion, and potassium excretion

above and below median (2.1g/day). Three categories were selected for sodium excretion, as the

estimated association was J-shaped, while two categories were selected for potassium excretion,

as the association was linear in analyses. We also completed a stratified subgroup analysis of the

association of sodium excretion and outcomes, stratified by groups of urinary potassium

excretion and mAHEI divided at their tertiles. We tested for interactions between sodium

excretion and potassium excretion and between sodium excretion and mAHEI score. As the

association of sodium excretion and composite outcome was non-linear, we test for interaction

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above and below median sodium excretion (i.e. four tests for interaction) modelling the log

hazard ratio as a piece-wise linear function of sodium excretion; two connected lines above and

below the median sodium excretion with different slopes with were allowed to interact with the

potassium and mAHEI subgroups.

To minimize the potential for reverse causation, we conducted analyses that excluded

participants who had a final follow-up or outcome event within the first 3 years of baseline. All

analyses were conducted using R Version 3.4.4 (R Foundation for Statistical Computing, Vienna,

Austria).

RESULTS

Study Participants and Outcomes

In total, 103,570 participants were included, of which 42% were from China. In the overall

population, mean estimated 24-hour sodium excretion was 4.93 g and mean estimated potassium

excretion 2.12 g. (Supplementary Table 1) After a mean duration of 8.2 years (IQR 6.0-9.4) there

were 4,524 deaths, 4,889 with a major CVD event (1893 myocardial infarctions, 2,526 strokes,

534 heart failure, and 1,293 CVD deaths) and 7,884 had either a CVD event or death, and 3,263

were diagnosed with cancer.

Estimated Sodium Excretion with Mortality and Cardiovascular Events

Compared with estimated sodium excretion of 4 to 4.99 g/day (the reference group), higher

estimated sodium excretion (more than 7 g/day) was associated with a greater risk of the primary

composite outcome (hazard ratio [HR] 1.23; 95% confidence interval [CI] 1.12 to 1.34), all-

cause mortality (HR 1.36; 95% CI 1.20 to 1.53), major cardiovascular events (HR 1.20; 95% CI

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1.08 to 1.34), cardiovascular death (OR 1.49; 95% CI 1.21 to 1.84), and fatal stroke (HR 1.76;

95% CI 1.28 to 2.41) on multivariable analysis (Table 1, Supplementary Table 2, Figure 2).

Compared with estimated sodium excretion of 4 to 4.99 g/day, lower estimated sodium excretion

(less than 3 g/day) was associated with a greater risk of the primary composite outcome (HR

1.19; 95% CI 1.09 to 1.30), all-cause mortality (HR 1.26; 95% CI 1.12 to 1.41), major

cardiovascular events (HR 1.19; 95% CI 1.06 to 1.33), cardiovascular mortality (HR 1.35; 95%

CI 1.09 to 1.69) and stroke (HR 1.24; 95% CI 1.05 to 1.46). (Supplementary Table 2). There was

no association of sodium excretion with cancer or cancer mortality (Supplementary Table 2).

Estimated Potassium Excretion with Mortality and Cardiovascular Events

Compared to estimated potassium excretion of less than 1.5 g/day, higher estimated potassium

excretion was associated with lower risk of mortality and cardiovascular events (HR 0.83; 95%

CI 0.73 to 0.94 for more than 3g/day) on multivariable analysis (Figure 3, Supplementary Table

3). This association was more related to a lower mortality risk (HR 0.71; 95% CI 0.60 to 0.85),

than major cardiovascular events (HR 0.87; 0.75-1.02). There was no association of potassium

excretion with cancer or cancer mortality (Supplementary Table 3).

Combined Sodium and Potassium Excretion with Mortality and Cardiovascular Events

Table 2 shows the association of sodium excretion with the primary composite outcome,

categorised by joint sodium and potassium excretion (6 categories). The lowest risk of death and

cardiovascular events occurred in the group with moderate sodium excretion (3-5g/day) and

higher potassium excretion (21.9% of cohort). Compared to this reference group, the

combinations of low potassium with low sodium excretion (HR 1.23; 1.11-1.37; 7.4% of cohort)

and low potassium with high sodium excretion (HR 1.21; 1.11-1.32; 13.8% of cohort) were

associated with the highest risk, followed by high sodium excretion (HR 1.10; 1.02-1.18 [29.6%

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of cohort]) and low sodium excretion (HR 1.19; 1.02-1.38 [3.3% of cohort]) among those with

potassium excretion above median. Moderate sodium excretion with low potassium excretion

was associated with an increased risk of the primary outcome (HR 1.10; 1.01-1.19, 24.0% of

cohort), compared to reference. There were very few individuals (0.001%) with both very low

sodium excretion (<2g/day) and high potassium excretion (>3.5g/day)-a target recommended by

nutrition guidelines-so that the risk in this subgroup could not be estimated reliably (0.2% for

potassium >2.63g/day, assuming that about 75% of potassium is excreted in the urine35

and

sodium excretion <2.3g/day). Figure 1b reports results of a heat-map that combines multivariable

cubic splines of the association of both sodium excretion and potassium excretion with the

primary outcome, with median excretion as reference category. Table 3 and Figure 4 shows a

stratified analysis by potassium excretion tertiles, supporting a lower relative risk associated with

higher sodium excretion among those with higher potassium excretion. Test for interaction of

higher sodium excretion (above median) and potassium excretion was significant (P=0.007) but

for lower sodium excretion and potassium excretion was not significant (P=0.939).

Sodium Excretion and Diet Quality (mAHEI)

Figure 4b and Table 3 reports a stratified analysis by mAHEI tertiles, which demonstrates a

lower magnitude of risk the association of sodium excretion with mortality and cardiovascular

events among those with higher diet quality scores, although P for interactions were not

significant (P=0.868 for below median excretion and P=0.297 above median excretion).

Sensitivity Analyses

Exclusion of participants who had events in the first three years of follow-up, and excluding

those with baseline cardiovascular disease, cancer (or cancer on first year of follow-up, diabetes

and were current smoker), did not materially affect findings. (Table 1)

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DISCUSSION

In this large international prospective cohort study, we investigated the joint association of

estimated sodium and potassium urinary excretion (surrogates for intake) and clinical outcomes

over a mean follow-up of 8.1 years. Overall, the lowest risk of death and adverse clinical events

was seen in individuals with estimated sodium excretion between 3 and 5 g/day, and with the

highest potassium excretions (Table 2, Figure 1). Both higher and lower levels of estimated

sodium excretion were associated with higher cardiovascular risk, thereby describing a J-shaped

association curve, while the association of potassium excretion and mortality/cardiovascular risk

was inverse and linear. Higher potassium intake attenuated the increased cardiovascular risk

associated with high sodium intake, and the association of high sodium excretion with

cardiovascular risk was most prominent in patients with low potassium intake.

Comparison with Other Studies

Potassium, the most abundant intracellular cation, and sodium, the most abundant extracellular

cation, are inextricably linked, with their exchange required for membrane potential of cells (Na-

K-ATPase) and their inter-reliance on diet and kidneys to maintain homeostasis.2,3

We found that

the association of higher sodium excretion with cardiovascular risk was lower among those with

higher urinary potassium excretion. While prior studies have reported that higher potassium

intake diminishes the association of higher sodium intake with increased blood pressure, no prior

study has been sufficiently large to demonstrate a significant modifying effect of sodium and

potassium intake with cardiovascular events and mortality.19-24

As illustrated in Figure 1b and

Table 2, extremes of sodium excretion (both high and low) in a setting of low potassium

excretion are associated with the highest risk of death and CV events. Low potassium intake not

only results in potassium retention from the kidneys, but also induces sodium retention, even in

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individuals with high sodium intake and in those with increased aldosterone levels.36, 37

Renal

conservation of sodium in the setting of low potassium diets, is mediated through WNK kinases

activating the thiazide-sensitive NACl cotransporter (NCC), leading to greater increases in blood

pressure with salt intake.38, 39

Low potassium intake may also reflect poorer diet quality,

particularly lower intake of fruits and vegetables, and the association of sodium intake with

cardiovascular risk may be confounded by foods that independently increase CV risk. Our

subgroup analysis by diet quality (mAHEI) would lend some support to this contention, whereby

the magnitude of association of sodium excretion with cardiovascular risk was lower among

those consuming the highest third of diet quality, although formal tests of interaction were not

significant. (Table 3) Therefore, higher potassium intake may directly affect cardiovascular and

mortality risks or is a marker of increased intake of healthier food items that are rich in

potassium (e.g. fruit, vegetables, nuts), or a combination of both. The DASH-Sodium trial

reported a lower antihypertensive effect of reducing sodium intake, in the setting of higher

potassium intake.40

A small cluster randomised controlled trial (5 centres), which replaced table

salt with low sodium salt substitute (partially replaced with potassium chloride) reported reduced

risk of cardiovascular risk in those centres randomized to salt substitution, although findings

were not conclusive due to methodologic limitations of the trial.41

An ongoing large cluster

randomized controlled trial in China, evaluating use of salt substitutes (KCl substituted for NaCl)

is expected to provide a more definitive answer.42

However, these trials are evaluating

simultaneous increased potassium intake with reduction of high sodium intake to moderate

intake levels, and it is unlikely to inform whether very low sodium (<2.0g/day) is beneficial or

harmful. Finally, increased cardiovascular risk may also be mediated through activation of

numerous adaptive renal and neuroendocrine mechanisms to maintain balance of both

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electrolytes, in response to low potassium and low sodium dietary, especially activation of the

renin-aldosterone-angiotensin system, whose activation is known to increase cardiovascular risk.

Collectively, these data suggest that the health impact of these two cations cannot be easily

assessed separately. Prior studies have reported on use of sodium-to-potassium ratio to predict

cardiovascular events and mortality, and most have reported a significant association. However,

our findings would argue against an isolated use of a ratio, because of the J-shaped association of

sodium intake and clinical outcomes and does not take account for absolute intake levels. For

example, the combination of moderate intake of sodium and potassium is associated with lower

cardiovascular risk than combined low intake of both sodium and potassium intake, despite the

same sodium-to-potassium ratio.

Public Health Implications

Guidelines for dietary recommendations, targeting the entire population, should be both feasible

and based on clear high-quality evidence of improved health outcomes.4,5

Our results suggest

that a combined strategy of low sodium intake (<2.0g/day), while simultaneously increasing

potassium intake to >3.5g/day, is unrealistic, as only 0.001% of the population were in this range

(0.2% for potassium excretion of 2.62g/day, if we assume that about 75% of potassium is

excreted in urine). These estimates are consistent with reports from studies in the UK (0.1%), US

(0.3%), Mexico (0.15%) and France (0.5%).7 This finding also meant that we were unable to

evaluate the association of these joint dietary intake levels at extreme intake levels with health

outcomes, as there were insufficient numbers of participants despite the large sample size.

Moreover, we observed a linear relationship between increased sodium and potassium intake, a

consistent finding of other studies.7,20

These findings question the feasibility of increasing

potassium intake while achieving very low sodium intake through modifying diets. While small

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Phase II clinical trials, such as DASH-Sodium trial40

, have achieved these targets in the short-

term, they required complete control of dietary intake (by providing all meals), which is

impractical in free living populations. In contrast, the PREDIMED study43

, which promoted

increased potassium-containing foods (fruit, vegetables, nuts) with greater adherence to the

Mediterranean diet, without focusing on low sodium intake, reported a significant reduction in

CVD and mortality, and adherence to a Mediterranean diet does not appear to correlate with

sodium intake44

. In addition, a recent analysis of the NHANES study reported that sodium intake

>2.3g/day was associated with better diet quality, compared to diets consuming less than

2.3g/day, meaning that improving dietary quality is likely to be easier to achieve within a

moderate sodium intake range.45

These considerations raise considerable doubts about the

feasibility, and assumed cardiovascular effects, of current recommendations to reduce sodium

intake to very low levels (<2g/day), which may counteract achieving dietary targets of dietary

intake and improving overall dietary quality.

Strengths and Limitations of Study

Our estimate of sodium intake is based on a baseline measurement of sodium intake, derived

from fasting morning urine, rather than repeated 24-hour urinary collections which would be

considered the reference standard for estimating usual sodium and potassium intake. However,

our approach has been validated in an international study, against actual 24-hour urine estimates

of sodium and potassium excretion.31

Reverse causation has been a criticism of prospective

cohort studies evaluating the association of diet and clinical outcomes, which may also occur

when individuals with reduce their sodium intake due to illness or medical recommendations.

Alternatively, it may occur where individuals with prior cardiovascular disease or risk factors,

who are at increased cardiovascular risk, reduce their sodium intake due to medical

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recommendations. In the PURE study, a minority of participants had a previous cardiovascular

disease, and our findings are not materially altered with their exclusion. Moreover, in the current

analyses, the exclusion of participants with cancer, diabetes, current smoking, or participants

who had events in the first three years of follow-up did not materially alter findings.

Additionally, we did not find an increased risk of death due to cancer with low sodium intake.

Finally, given the observational nature of the study, residual confounding is a potential

limitation. However, we adjusted for all major confounders of the association of sodium and

potassium intake and cardiovascular events. Strengths of our study include the large

representative international population in the PURE study, completeness of follow-up, rigorous

approach to measurement of baseline variables and adjudicated outcome clinical events.

CONCLUSIONS

In conclusion, our findings suggest that a simultaneous target of low sodium (<2g/day) with high

potassium intake (>3.5g/day) in the population is unlikely to be feasible. The combination of

moderate sodium intake (3-5g/day) with high potassium intake is associated with lowest risk of

mortality and cardiovascular events, while extremes of sodium intake combined with low

potassium urinary excretion were associated with the highest cardiovascular risk. Our data

support population-wide increases in dietary potassium intake, with a population-specific (i.e.

those consuming sodium intakes over 5g/day) reduction of sodium intake, embedded within an

overall healthy dietary pattern.

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What is already known on this topic

Current dietary guidelines recommend sodium restriction (<2.0g/day recommended by the

WHO) but increased potassium intake (>3.5g/day recommended by the WHO). Studies

evaluation the association of sodium intake have reported inconsistent findings, but many report

a J-shaped association, while those evaluating potassium intake generally report a linear

reduction in mortality with increasing potassium intake. Most observational studies have

reported on the effects of sodium and potassium intake separately, although some have reported

on the association of sodium-potassium ratio with clinical outcomes.

What this study adds

Our findings suggest that the simultaneous target of low sodium (<2g/day) with high potassium

intake (>3.5g/day) is not associated with lowest cardiovascular risk and is not feasible, as it is

consumed by a very small proportion of an international population. Moreover, we observed the

combination of moderate sodium intake (3-5g/day) with higher potassium intake to be associated

with the lowest risk of mortality and cardiovascular events. Our study findings also argue against

use of sodium-potassium ratio, as the association of sodium intake with cardiovascular risk was

J-shaped. Higher potassium intake significantly diminished the association of high sodium intake

with cardiovascular events and mortality. Our data support a dietary target of moderate sodium

intake (2-5g/day) with higher potassium intake, embedded within improved overall dietary

quality.

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Contributors: SY conceived and started the overall Prospective Urban Rural Epidemiology

(PURE) study, SR coordinated the study, and KT was the co-principal investigator. MOD, SY

and AM designed and SY supervised the present study. NOL and JF did the statistical analysis.

MOD, SY and AM wrote the first draft of the manuscript. SY supervised the study conduct and

data analysis and provided critical comments on all drafts of the manuscript. All other authors

coordinated the study and collected the data in their respective countries and provided comments

on drafts of the manuscript. All authors reviewed and provided critical comments on drafts. All

authors have approved the submitted version.

Funders: The funders of the study had no role in its design or conduct, in the collection,

analysis, or interpretation of the data, or in the writing of the manuscript. The current analyses is

supported by funding from the European Research Council (COSIP grant) and Heart and Stroke

Foundation of Ontario. Dr S Yusuf is supported by the Mary W Burke endowed chair of the

Heart and Stroke Foundation of Ontario. The PURE Study is an investigator-initiated study that

is funded by the Population Health Research Institute, the Canadian Institutes of Health

Research, Heart and Stroke Foundation of Ontario, Support from CIHR’s Strategy for Patient

Oriented Research, through the Ontario SPOR Support Unit, as well as the Ontario Ministry of

Health and Long-Term Care and through unrestricted grants from several pharmaceutical

companies [with major contributions from Astra Zeneca (Canada), Sanofi-Aventis (France and

Canada), Boehringer Ingelheim (Germany & Canada), Servier, and GSK], and additional

contributions from Novartis and King Pharma and from various national or local organizations in

participating countries. These include: Argentina: Fundacion ECLA; Bangladesh: Independent

University, Bangladesh and Mitra and Associates; Brazil: Unilever Health Institute, Brazil;

Canada: Public Health Agency of Canada and Champlain Cardiovascular Disease Prevention

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Network, Canadian Institutes of Health Research (Catalyst Grant: eHealth Innovations-grant

number: 126524); Chile: Universidad de La Frontera (Internal Registry DI13-PE11); China:

National Center for Cardiovascular Diseases; Colombia: Colciencias, Grant number:6566-04-

18062; India: Indian Council of Medical Research; Malaysia: Ministry of Science, Technology

and Innovation of Malaysia Grant Nbr 100 - IRDC / BIOTEK 16/6/21 (13/2007), Grant

Number 07-05-IFN-BPH 010, Ministry of Higher Education of Malaysia Grant Nbr 600 -

RMI/LRGS/5/3 (2/2011), Universiti Teknologi MARA, Faculty of Medicine, Universiti

Kebangsaan Malaysia, Kuala Lumpur Malaysia. CRIM, University Kebangsaan Malaysia;

Occupied Palestinian Territory: The United Nations Relief and Works Agency for Palestine

Refugees in the Near East (UNRWA), occupied Palestinian territory; International Development

Research Centre (IDRC), Canada; Peru: National Heart, Lung and Blood Institute

(HHSN268200900033C), National Cancer Institute (1P20CA217231), Wellcome

(103994/Z/14/Z); Philippines: Philippine Council for Health Research & Development

(PCHRD); Poland: Polish Ministry of Science and Higher Education grant Nr 290/W-

PURE/2008/0, Wroclaw Medical University, Wroclaw Medical University, statutory activity

Saudi Arabia: The Deanship of Scientific Research at King Saud University, Riyadh, Saudi

Arabia (Research group number: RG -1436-013); South Africa: The North-West University,

SANPAD (SA and Netherlands Programme for Alternative Development), National Research

Foundation, Medical Research Council of SA, The SA Sugar Association (SASA), Faculty of

Community and Health Sciences (UWC); Sweden: Grants from the Swedish state under the

Agreement concerning research and education of doctors; the Swedish Heart and Lung

Foundation; the Swedish Research Council; the Swedish Council for Health, Working Life and

Welfare, King Gustaf V:s and Queen Victoria Freemason’s Foundation, AFA Insurance;

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Tanzania: Pamoja Tunaweza Health Research Centre (Tanzania), Queen's University,

Department of Medicine; Turkey: Metabolic Syndrome Society, Astra Zeneca, Turkey; UAE:

Sheikh Hamdan Bin Rashid Al Maktoum Award for Medical Sciences and Dubai Health

Authority, Dubai UAE.

Competing interests: All authors have completed the Unified Competing Interest form at

www.icmje.org/coi_disclosure.pdf (available on request from the corresponding author) and

declare no support from any additional organisation for the submitted work. A detailed list of

funders is provided in the supplementary appendix. Role of Sponsor: The funders and sponsors

had no role in the design and conduct of the study; in the collection, analysis, and interpretation

of the data; in the preparation, review, or approval of the manuscript; or in the decision to submit

the manuscript for publication.

Ethical Approval: The study was approved by research ethics committees at all participating

centres and at Hamilton Health Sciences, Hamilton, Ontario, Canada.

Data Sharing: No additional data available.

Transparency: The lead author (MO’D) affirms that the manuscript is an honest, accurate, and

transparent account of the study being reported; that no important aspects of the study have been

omitted and that any discrepancies from the study as planned have been explained.

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40. Sacks FM, Svetkey LP, Vollmer WM et al. Effects on blood pressure of reduced dietary sodium

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42. Li N, Yan LL, Niu W et al. A large-scale cluster randomized trial to determine the effects of

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Confidential: For Review Only27

Table 1 Association of Estimated Urinary Sodium Excretion with Mortality and Cardiovascular Events

OR=Odds ratio, CI=confidence intervals. Primary model includes the following covariates at baseline: age, sex, education, alcohol intake, diabetes mellitus, body mass index,

a history of cardiovascular events, cancer and COPD, cardiovascular medication at baseline, HIV, tuberculosis or Chagas, physical activity level and smoking status and

dosage. Dietary variables: addition of caloric intake, potassium intake, waist-to-hip ratio, and mAHEI. Blood pressure variables: baseline systolic blood pressure and history

of hypertension. LDL/HDL ratio available in 88% of cohort. *univariate analysis using Cox proportional hazards model with a random effect for study centre (to address

clustering of data), includes 103,200 participants with follow-up data. † adjusted for variables in primary model **major cardiovascular events includes CV mortality,

myocardial infarction, stroke and heart failure. **Primary multivariable model included 90% of all participants in univariate model, 10% of participants had missing data for

at least one covariate, we did not undertake imputation for missing data.

Estimated Sodium Excretion g/day

<3 g/d

(n=11,002)

3-3.99 g/d

(n=21,417)

4-4.99 g/d

(n=26,012)

5-5.99g/d

(n=21,093)

6-6.99 g/d

(n=12,458)

≥ 7 g/d

(n=11,218)

OR (95%CI) OR (95%CI) OR (95%CI) OR (95%CI) OR (95%CI) OR (95%CI)

Mortality and Cardiovascular

Events

949 (8.6%) 1562 (7.3%) 1816 (7.0%) 1640 (7.8%) 964 (7.7%) 953 (8.5%)

Univariate* 1.23 (1.14-1.34) 1.05 (0.98-1.12) 1.00 1.09 (1.02-1.17) 1.07 (0.99-1.16) 1.16 (1.07-1.26)

Multivariable (Primary)** 1.19 (1.09-1.30) 1.06 (0.99-1.14) 1.00 1.08 (1.00-1.16) 1.07 (0.98-1.16) 1.23 (1.12-1.34)

Multivariable (+ Diet) 1.16 (1.05-1.27) 1.06 (0.98-1.14) 1.00 1.09 (1.01-1.17) 1.08 (0.99-1.18) 1.26 (1.15-1.39)

Multivariable (+Blood

pressure/Heart Rate)

1.15 (1.04-1.28) 1.06 (0.98-1.14) 1.00 1.08 (1.00-1.16) 1.06 (0.96-1.16) 1.17 (1.06-1.28)

Multivariable† (Excluding events in

first 3 years)

1.20 (1.07-1.33) 1.11 (1.02-1.21) 1.00 1.12 (1.03-1.21) 1.09 (0.99-1.20) 1.17 (1.06-1.30)

Multivariable† (Primary +Lipids) 1.17 (1.06-1.29) 1.06 (0.98-1.15) 1.00 1.07 (0.99-1.16) 1.05 (0.96-1.15) 1.24 (1.13-1.36)

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Table 2 Association of Joint Urinary Sodium and Potassium Excretion with Mortality and Cardiovascular Events

Sodium <3g/day Sodium 3-5g/day Sodium >5g/day

Potassium (<Median) HR 1.23 (1.11-1.37)

716/7582 (9.4%)*

HR 1.10 (1.01-1.19)

1924/24741 (7.8%)*

HR 1.21 (1.11-1.32)

1260/14259 (8.8%)*

Potassium (≥Median) HR 1.19 (1.02-1.38)

233/3420 (6.8%)*

HR 1.00 (Reference)

1454/22688 (6.4%)*

HR 1.10 (1.02-1.18)

2297/30510 (7.5%)*

Adjusted for age (included as spline function), sex, education, current and former alcohol intake (units per week), diabetes mellitus, body mass index (BMI),

physical activity, history of cardiovascular events, use of cardiovascular medications (blood pressure lowering, statins or diabetes), history of tuberculosis,

cancer, HIV, and current and former smoking. *Event proportion for composite outcome of major cardiovascular events or mortality.

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Table 3 Association of Estimated Urinary Sodium Excretion with Mortality and Cardiovascular Events (Subgroup Analysis)


<3 g/d

(n=11,002)

3-3.99 g/d

(n=21,417)

4-4.99 g/d

(n=26,012)

5-5.99g/d

(n=21,093)

6-6.99 g/d

(n=12,458)

≥ 7 g/d

(n=11,218)

OR (95%CI) OR (95%CI) OR (95%CI) OR (95%CI) OR (95%CI) OR (95%CI) P-interaction

Potassium Excretion (Tertiles)

<1.8g/day 1.14 (1.00-1.30) 1.02 (0.91-1.14) 1.00 1.02 (0.89-1.16) 1.15 (0.97-1.36) 1.27 (1.04-1.54) P=0.929 (Below Median

Sodium Excretion)

P=0.007 (Above Median

Sodium Excretion)

1.8-2.3g/day 1.16 (0.97-1.38) 1.11 (0.97-1.26) 1.00 1.16 (1.03-1.31) 1.17 (1.01-1.36) 1.47 (1.26-1.71)

>2.3g/day 1.12 (0.91-1.39) 1.02 (0.88-1.18) 1.00 1.08 (0.95-1.22) 1.01 (0.88-1.16) 1.11 (0.96-1.27)

Modified Alternative Healthy Eating Index (mAHEI) (Tertiles)

<31.3 1.18 (1.01-1.38) 1.10 (0.97-1.25) 1.00 1.11 (0.98-1.25) 1.07 (0.92-1.25) 1.47 (1.26-1.73) P=0.868 (Below Median

Sodium Excretion)

P=0.297 (Above Median

Sodium Excretion)

31.3-38.4 1.24 (1.06-1.46) 1.09 (0.96-1.25) 1.00 1.14 (1.01-1.30) 1.12 (0.97-1.30) 1.22 (1.05-1.43)

>38.4 1.09 (0.92-1.29) 1.03 (0.90-1.17) 1.00 1.00 (0.88-1.14) 0.99 (0.85-1.14) 1.06 (0.91-1.23)

Adjusted for age (included as spline function), sex, education, current and former alcohol intake (units per week), diabetes mellitus, body mass index (BMI), physical activity, history of

cardiovascular events, use of cardiovascular medications (blood pressure lowering, statins or diabetes), history of tuberculosis, cancer, HIV, and current and former smoking.

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Figure 1 Scatterplot of Sodium and Potassium Urinary Excretion

Legend: Figure 1A reports scatterplot of estimated 24-hour urinary sodium and potassium excretion in the PURE population. Grey box indicates target guideline intake for combined sodium and potassium intake.

Figure demonstrates correlation of increasing sodium and potassium intake. Clustering of intake at 0.5g/day of potassium is related to lower limit of lab measurement in one laboratory (India). Figure 1B reports a heat

map of risk of risk of composite of cardiovascular events or death that indicates lowest risk in region of moderate sodium intake 3-5g/day and higher potassium intake. Highest risk occurs in regions of extremes of

sodium excretion and low potassium excretion. Changes in hazard for various outcomes with changes jointly in both sodium and potassium excretion/intake were modelled using two-dimensional natural cubic splines.

For each of sodium and potassium, 2 knot points were selected at the tertiles of the variable’s sample distribution. This resulted in a grid of 4 knot points on the two-dimensional (sodium and potassium) spline surface.

For a given outcome, the Cox proportional hazard model then included (along with other covariates) natural cubic spline variables for both sodium and potassium separately and also interaction terms between these

spline variables. To visualise the two-dimensional relationship, and the putative interaction effect between sodium and potassium on hazards of a given outcome, estimated hazard ratios were evaluated and plotted on a

sampling grid (0.01g apart) within the range of observed sodium and potassium was evaluated. The reference hazard for these hazard ratios was set at a value of sodium daily excretion/intake of 5.00g and potassium

daily excretion/intake of 2.25g (median excretion of sodium and potassium), marked as ‘X’ in Figure 1b.

R=0.34

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Figure 2 Association of Estimated 24-hour Urinary Sodium Excretion with Mortality and Major Cardiovascular Event

Composite Outcome Mortality Major CVD

Figure 2a, restricted cubic spline plot of association of estimated 24-hour urinary sodium excretion (X-axis) with composite of all-cause mortality and major cardiovascular

events. Spline curve truncated at 10 g per day.

Figure 2b, restricted cubic spline plot of association of estimated 24-hour urinary sodium excretion (X-axis) with mortality. Spline curve truncated at 10 g per day.

Figure 2c, restricted cubic spline plot of association of urinary sodium excretion (X-axis) with major cardiovascular events (which is a composite of cardiovascular death,

myocardial infarction, stroke and heart failure). Spline curve truncated at 10 g per day.

All plots adjusted for age (included as spline function), sex, education, current and former alcohol intake (units per week), diabetes mellitus, body mass index (BMI), physical

activity, history of cardiovascular events, use of cardiovascular medications (blood pressure lowering, statins or diabetes), history of tuberculosis, cancer, HIV, and current

and former smoking. Dashed lines indicate 95% confidence intervals (CI). Median intake is reference standard (4.91g/day). Salt approximates 2.5 X sodium g per day.

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Figure 3 Association of Estimated 24-hour Urinary Potassium Excretion with Mortality and Major Cardiovascular Events

Composite Outcome Mortality Major CVD

Figure 3a, restricted cubic spline plot of association of estimated 24-hour urinary potassium excretion (X-axis) with composite of all-cause mortality and major

cardiovascular events. Spline curve truncated at 4 g per day.

Figure 3b, restricted cubic spline plot of association of estimated 24-hour urinary potassium excretion (X-axis) with mortality. Spline curve truncated at 4 g per day.

Figure 3c, restricted cubic spline plot of association of urinary potassium excretion (X-axis) with major cardiovascular events (which is a composite of cardiovascular death,

myocardial infarction, stroke and heart failure). Spline curve truncated at 4 g per day.

All plots adjusted for age (included as spline function), sex, education, current and former alcohol intake (units per week), diabetes mellitus, body mass index (BMI), physical

activity, history of cardiovascular events, use of cardiovascular medications (blood pressure lowering, statins or diabetes), history of tuberculosis, cancer, HIV, and current

and former smoking.

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Figure 4a Association of Estimated 24-hour Urinary Sodium Excretion with Composite Outcome, Stratified by Potassium Excretion

Potassium <1.8g/day Potassium 1.8-2.3g/day Potassium >2.3g/day

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Figure 4b Association of Estimated 24-hour Urinary Sodium Excretion with Composite Outcome, Stratified by mAHEI

T1 mAHEI T2 mAHEI T3 mAHEI

Figure 4 reports association of urinary sodium excretion and composite of mortality and major cardiovascular events, by subgroups of urinary potassium excretion and

mAHEI score. Top panel demonstrates association of urinary sodium excretion within tertiles of urinary potassium excretion. P-interaction is significant (P=0.007) for

urinary potassium excretion*urinary sodium excretion above median intake, with lower magnitude of association with higher urinary potassium excretion. Lower panel

demonstrates association of urinary sodium excretion within tertiles of mAHEI. P-interactions not significant. All plots adjusted for age (included as spline function), sex,

education, current and former alcohol intake (units per week), diabetes mellitus, body mass index (BMI), physical activity, history of cardiovascular events, use of

cardiovascular medications (blood pressure lowering, statins or diabetes), history of tuberculosis, cancer, HIV, and current and former smoking.

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Supplementary Table 1 Baseline Characteristics of Participants by Estimated Sodium and Potassium Excretion Groups

All

Groups: Estimated Sodium and Potassium Excretion g/day

Sodium <3 g/d Sodium 3-5 g/d Sodium >5 g/d

Potassium

≤2g/day

Potassium

>2g/day

Potassium

≤2g/day

Potassium

>2g/day

Potassium

≤2g/day

Potassium

>2g/day

Participants, n (%) 103,570 7621 (7.4) 3434 (3.3) 24834 (24.0) 22751 (22.0) 14313 (13.8) 30617 (29.6)

Estimated Sodium Excretion, mean

(SD), g/d

4.9 (1.7) 2.4 (0.5) 2.5 (0.4) 4.0 (0.6) 4.1 (0.5) 6.2 (1.2) 6.6 (1.4)

Estimated Potassium Excretion,

mean (SD), g/d

2.1 (0.6) 1.5 (0.4) 2.4 (0.3) 1.6 (0.3) 2.5 (0.4) 1.7 (0.3) 2.6 (0.5)

Age, mean (SD), years 51.0 ( 9.7) 51.5 (10.2) 53.5 (9.2) 50.6 (10.0) 52.0 (9.5) 50.8 ( 9.9) 50.2 (9.4)

Male, n (%) 44287 (42.8) 2162 (28.4) 1129 (32.9) 8612 (34.7) 9597 (42.2) 6375 (44.5) 16412 (53.6)

Systolic BP, mean(SD), mmHg 131.6 (21.7) 127.9 (22.4) 127.8 (19.0) 129.7 (22.0) 129.9 (20.1) 136.0 (23.3) 133.7 (21.5)

Diastolic BP, mean(SD), mmHg 82.0 (12.4) 80.1 (12.7) 80.2 (11.4) 80.8 (12.5) 81.4 (11.7) 83.9 (13.0) 83.2 (12.4)

History of CVD, n (%) 15666 (15.1) 1271 (16.7) 754 (22.0) 3250 (13.1) 4208 (18.5) 1753 (12.2) 4430 (14.5)

Diabetes mellitus, n (%) 1.1 (0.5) 1.2 (0.5) 1.1 (0.5) 1.1 (0.4) 1.1 (0.5) 1.1 (0.4) 1.1 (0.5)

BMI ≥ 30, n (%) 18864 (18.3) 1183 (15.6) 789 (23.0) 3609 (14.6) 4832 (21.3) 2076 (14.5) 6375 (20.9)

Physical Activity (Low Level) (%)* 13678 (14.2) 952 (14.0) 340 (10.8) 3336 (14.5) 2677 (12.6) 2134 (15.8) 4239 (14.7)

Caloric intake, mean(SD), kcal 2117.1 (780.0) 2110.5 (846.0) 2220.3 (812.1) 2088.6 (783.0) 2180.5 (804.0) 2045.0 (735.9) 2118.0 (755.5)

mAHEI score, mean (SD) 34.9 (8.3) 34.1 (8.4) 36.8 ( 9.7) 33.6 (8.1) 35.6 (8.8) 34.7 (7.8) 35.7 (8.0)

Alcohol (Current), n (%) 30914 (30.0) 1934 (25.4) 1682 (49.1) 6248 (25.3) 8703 (38.4) 3534 (24.9) 8813 (29.1)

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Percentages are of the columns, i.e. the group based on particular levels of estimated sodium excretion. *defined as < 600 METS/week. For conversion from estimated

sodium excretion g per day to salt intake g per day, multiply estimated sodium excretion X 2.5.Abbreviations: BMI, body mass index; BP, blood pressure; CVD,

cardiovascular disease; Categorical variables cells are reported as No. (%) and continuous variables are reported as mean (SD). Missing data for age (0%), sex (0%),

(0.49%), a history of cardiovascular events (0.14%), diabetes mellitus (0%), body mass index (0.40%), physical activity (7%), dietary variables (4.5%) alcohol intake

(0.37%). BMI is calculated as the weight in kilograms divided by height in meters squared. .

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Supplementary Table 2 Association between Estimated Urinary Sodium Excretion and Mortality and Cardiovascular Events


<3 g/d

(n=11,002)

3-3.99 g/d

(n=21,417)

4-4.99 g/d

(n=26,012)

5-5.99g/d

(n=21,093

6-6.99 g/d

(n=12,458)

≥ 7 g/d

(n=11,218)

HR (95%CI) HR (95%CI) HR (95%CI) HR (95%CI) HR (95%CI) HR (95%CI)

Major Cardiovascular events 529 (4.8%) 915 (4.3%) 1120 (4.3%) 1036 (4.9%) 641 (5.1%) 648 (5.8%)

Univariate 1.21 (1.08-1.34) 1.03 (0.94-1.12) 1.00 1.08 (0.99-1.17) 1.07 (0.97-1.19) 1.13 (1.02-1.25)

Multivariable (Primary model) 1.19 (1.06-1.33) 1.07 (0.97-1.17) 1.00 1.07 (0.98-1.17) 1.09 (0.98-1.21) 1.20 (1.08-1.34)

Primary (+Diet*) 1.16 (1.02-1.31) 1.06 (0.97-1.17) 1.00 1.07 (0.97-1.17) 1.08 (0.97-1.20) 1.22 (1.09-1.37)

Primary (+Diet + BP/HR) 1.16 (1.02-1.32) 1.05 (0.96-1.17) 1.00 1.05 (0.96-1.16) 1.03 (0.92-1.15) 1.09 (0.97-1.22)

CV Mortality 181 (1.6%) 249 (1.2%) 295 (1.1%) 243 (1.2%) 156 (1.3%) 169 (1.5%)

Univariate 1.46 (1.21-1.77) 1.02 (0.87-1.21) 1.00 1.01 (0.85-1.19) 1.10 (0.91-1.34) 1.39 (1.15-1.70)

Multivariable (Primary) 1.35 (1.09-1.69) 1.06 (0.88-1.27) 1.00 0.98 (0.82-1.18) 1.12 (0.91-1.38) 1.49 (1.21-1.84)

Primary (+Diet) 1.27 (1.00-1.62) 1.03 (0.85-1.24) 1.00 0.99 (0.82-1.19) 1.13 (0.91-1.41) 1.56 (1.25-1.95)


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Supplementary Table 2 Association between Estimated Urinary Sodium Excretion and Mortality and Cardiovascular Events


<3 g/d

(n=11,002)

3-3.99 g/d

(n=21,417)

4-4.99 g/d

(n=26,012)

5-5.99g/d

(n=21,093

6-6.99 g/d

(n=12,458)

≥ 7 g/d

(n=11,218)


Stroke 252 (2.3%) 418 (2.0%) 577 (2.2%) 548 (2.6%) 345 (2.8%) 386 (3.4%)

Univariate 1.29 (1.11-1.50) 0.98 (0.86-1.11) 1.00 1.02 (0.91-1.15) 0.98 (0.85-1.12) 1.02 (0.89-1.16)


Primary (+Diet) 1.20 (1.01-1.43) 0.98 (0.85-1.12) 1.00 1.02 (0.90-1.16) 1.03 (0.89-1.19) 1.16 (1.00-1.34)


Myocardial Infarction 210 (1.9%) 402 (1.9%) 443 (1.7%) 384 (1.8%) 248 (2.0%) 206 (1.8%)

Univariate 1.10 (0.93-1.30) 1.09 (0.95-1.25) 1.00 1.07 (0.93-1.22) 1.18 (1.01-1.38) 1.17 (0.99-1.39)


Primary (+Diet) 1.07 (0.87-1.30) 1.16 (1.00-1.34) 1.00 1.05 (0.90-1.22) 1.07 (0.90-1.27) 1.19 (0.99-1.44)


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<3 g/d

(n=10,810)

3-3.99 g/d

(n=21,131)

4-4.99 g/d

(n=26,012)

5-5.99g/d

(n=21,093)

6-6.99 g/d

(n=12,324)

≥ 7 g/d

(n=11,017)


Heart Failure 67 (0.6%) 114 (0.5%) 118 (0.5%) 117 (0.6%) 55 (0.4%) 63 (0.6%)

Univariate 1.19 (0.88-1.61) 1.12 (0.86-1.45) 1.00 1.28 (0.99-1.45) 1.08 (0.78-149) 1.52 (1.11-2.09)

Multivariable (Primary) 1.15 (0.81-1.63 1.20 (0.90-1.59) 1.00 1.30 (0.99-1.72) 1.09 (0.77-1.54) 1.34 (0.94-1.91)

Primary (+Diet) 1.19 (0.83-1.72) 1.17 (0.87-1.57) 1.00 1.33 (1.00-1.77) 1.09 (0.76-1.56) 1.38 (0.95-2.00)


Fatal Stroke 67 (0.06%) 83 (0.04%) 112 (0.04%) 102 (0.05%) 58 (0.05%) 82 (0.07%)

Univariate 1.56 (1.14-2.12) 0.94 (0.71-1.25) 1.00 1.06 (0.8-1.39) 0.99 (0.72-1.36) 1.54 (1.14-2.07)


Primary (+Diet) 1.27 (0.86-1.90) 0.94 (0.68-1.29) 1.00 1.06 (0.79-1.44) 1.11 (0.78-1.58) 1.89 (1.36-2.63)


Fatal Myocardial Infarction 90 (0.08%) 131 (0.06%) 137 (0.05%) 105 (0.05%) 77 (0.06%) 67 (0.06%)

Univariate 1.49 (1.13-1.95) 1.12 (0.88-1.43) 1.00 0.97 (0.75-1.25) 1.25 (0.95-1.66) 1.33 (0.98-1.80)


Primary (+Diet) 1.38 (0.98-1.94) 1.14 (0.87-1.50) 1.00 0.91 (0.68-1.20) 1.17 (0.85-1.61) 1.47 (1.05-2.05)


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<3 g/d

(n=10,810)

3-3.99 g/d

(n=21,131)

4-4.99 g/d

(n=26,012)

5-5.99g/d

(n=21,093)

6-6.99 g/d

(n=12,324)

≥ 7 g/d

(n=11,017)


All-cause Mortality 637 (5.8%) 939 (4.4%) 1045 (4.05) 897 (4.3%) 504 (4.0%) 502 (4.5%)

Univariate 1.33 (1.20-1.47) 1.06 (0.97-1.15) 1.00 1.09 (0.99-1.19) 1.07 (0.96-1.19) 1.30 (1.16-1.45)


Primary (+Diet) 1.21 (1.07-1.38) 1.06 (0.96-1.17) 1.00 1.09 (0.99-1.21) 1.11 (0.98-1.25) 1.44 (1.27-1.63)


Cancer 443 (4.0%) 765 (3.6%) 863 (3.0%) 612 (2.9%) 329 (2.6%) 251 (2.2%)

Univariate 1.01 (0.90-1.13) 0.97 (0.88-1.07) 1.00 0.99 (0.89-1.10) 1.00 (0.88-1.13) 0.92 (0.88-1.13)


Primary (+Diet) 0.99 (0.86-1.12) 0.98 (0.88-1.09) 1.00 1.00 (0.89-1.11) 1.03 (0.89-1.18) 0.99 (0.84-1.16)

Cancer Mortality 117 (1.1%) 218 (1.0%) 269 (1.0%) 243 (1.2%) 139 (1.1%) 124 (1.1%)

Univariate 1.08 (0.86-1.35) 0.99 (0.83-1.19) 1.00 1.12 (0.94-1.33) 1.10 (0.89-1.35) 1.09 (0.87-1.36)


Primary (+Diet) 1.10 (0.85-1.41) 1.00 (0.82-1.21) 1.00 1.12 (0.93-1.35) 1.15 (0.92-1.44) 1.16 (0.91-1.47)

OR=Odds ratio, CI=confidence intervals. Primary model: age, sex, education, alcohol intake, diabetes mellitus, body mass index, a history of cardiovascular events and current smoking. Diet,

adjusted for caloric intake, potassium excretion, mAHEI score and waist-to-hip ratio. BP=blood pressure, HR=heart rate.

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Supplementary Table 3 Association between Estimated Urinary Potassium Excretion and Mortality and Cardiovascular Events

Estimated Potassium Excretion g/day

<1.5 g/d

(n=14,817)

1.5-1.99 g/d

(n=31,765)

2-2.49 g/d

(n=31,202)

2.5-3 g/d

(n=17,257)

>3 g/d

(n=8,159)

HR (95%CI) HR (95%CI) HR (95%CI) HR (95%CI) HR (95%CI)

Mortality and Cardiovascular

Events

1351 (9.1%) 2549 (8.0%) 2295 (7.4%) 1193 (6.95) 496 (6.1%)

Univariate* 1.00 0.96 (0.90-1.03) 0.91 (0.84-0.97) 0.89 (0.82-0.96) 0.80 (0.72-0.89)

Multivariable (Primary) 1.00 0.99 (0.91-1.06) 0.91 (0.84-0.99) 0.95 (0.86-1.04) 0.83 (0.73-0.94)

Primary (+Diet) 1.00 0.99 (0.92-1.08) 0.91 (0.84-1.00) 0.93 (0.84-1.03) 0.80 (0.70-0.91)

Primary (+Diet + BP/HR) 1.00 1.03 (0.94-1.12) 0.98 (0.89-1.07) 1.03 (0.92-1.14) 0.90 (0.79-1.04)

Major Cardiovascular events 674 (4.5%) 1571 (4.9%) 1503 (4.8%) 794 (4.6%) 347 (4.3%)

Univariate* 1.00 1.03 (0.93-1.13) 0.98 (0.89-1.08) 0.96 (0.86-1.07) 0.92 (0.80-1.06)


Primary (+Diet) 1.00 0.98 (0.89-1.09) 0.92 (0.82-1.03) 0.92 (0.81-1.05) 0.85 (0.72-1.00)


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<1.5 g/d

(n=14,267)

1.5-1.99 g/d

(n=31,473)

2-2.49 g/d

(n=30,964)

2.5-3 g/d

(n=17,173)

>3 g/d

(n=8,068)


CV Mortality 250 (1.7%) 439 (1.4%) 373 (1.2%) 164 (1.0%) 67 (0.8%)

Univariate* 1.00 0.93 (0.79-1.09) 0.87 (0.74-1.04) 0.74 (0.60-0.91) 0.66 (0.50-0.88)


Primary (+Diet) 1.00 0.95 (0.78-1.15) 0.87 (0.70-1.07) 0.79 (0.61-1.02) 0.61 (0.43-0.87)


Stroke 369 (2.5%) 808 (2.5%) 811 (2.6%) 381 (2.2%) 157 (1.9%)

Univariate* 1.00 0.94 (0.83-1.07) 0.95 (0.84-1.08) 0.87 (0.75-1.01) 0.85 (0.70-1.03)


Primary (+Diet) 1.00 0.92 (0.83-1.11) 0.94 (0.81-1.08) 0.89 (0.75-1.06) 0.85 (0.68-1.07)


Myocardial Infarction 226 (1.5%) 618 (1.9%) 566 (1.8%) 328 (1.9%) 155 (1.9%)

Univariate* 1.00 1.25 (1.06-1.46) 1.12 (0.95-1.32) 1.16 (0.97-1.39) 1.14 (0.91-1.41)


Primary (+Diet) 1.00 1.14 (0.96-1.36) 1.00 (0.83-1.21) 1.05 (0.85-1.30) 0.97 (0.75-1.26)


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<1.5 g/d

(n=14,267)

1.5-1.99 g/d

(n=31,473)

2-2.49 g/d

(n=30,964)

2.5-3 g/d

(n=17,173)

>3 g/d

(n=8,068)


Heart Failure 69 (0.5%) 160 (0.5%) 163 (0.5%) 103 (0.6%) 39 (0.5%)

Univariate* 1.00 0.91 (0.69-1.22) 0.90 (0.67-1.21) 0.98 (0.71-1.35) 0.73 (0.48-1.10)


Primary (+Diet) 1.00 0.90 (0.64-1.26) 0.78 (0.55-1.11) 0.87 (0.59-1.29) 0.62 (0.37-1.02)


Fatal Stroke 98 (0.7%) 172 (0.5%) 155 (0.5%) 56 (0.3%) 23 (0.3%)

Univariate* 1.00 0.92 (0.71-1.19) 0.92 (0.70-1.20) 0.66 (0.47-0.94) 0.64 (0.40-1.03)


Primary (+Diet) 1.00 0.92 (0.68-1.25) 0.98 (0.71-1.35) 0.71 (0.47-1.07) 0.56 (0.31-1.00)


Fatal Myocardial Infarction 111 (0.7%) 215 (0.7%) 178 (0.6%) 73 (0.4%) 30 (0.4%)

Univariate* 1.00 1.04 (0.82-1.31) 0.95 (0.74-1.23) 0.75 (0.54-1.02) 0.65 (0.43-1.00)


Primary (+Diet) 1.00 1.06 (0.80-1.41) 0.92 (0.68-1.26) 0.81 (0.55-1.18) 0.63 (0.38-1.06)


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<1.5 g/d

(n=14,267)

1.5-1.99 g/d

(n=31,473)

2-2.49 g/d

(n=30,964)

2.5-3 g/d

(n=17,173)

>3 g/d

(n=8,068)


All-cause Mortality 966 (6.5%) 1492 (4.7%) 1245 (4.0%) 590 (3.4%) 231 (2.8%)

Univariate* 1.00 0.90 (0.83-0.98) 0.84 (0.77-0.92) 0.77 (0.69-0.86) 0.65 (0.56-0.75)


Primary (+Diet) 1.00 0.99 (0.89-1.09) 0.89 (0.80-1.00) 0.87 (0.76-1.00) 0.67 (0.56-0.81)


Cancer 331 (2.2%) 912 (2.9%) 998 (3.2%) 700 (4.1%) 322 (3.9%)

Univariate* 1.00 1.06 (0.93-1.20) 1.00 (0.87-1.14) 1.06 (0.92-1.22) 0.90 (0.76-1.06)

Primary (+Diet) 1.00 1.00 (0.87-1.15) 0.90 (0.78-1.04) 1.02 (0.87-1.18) 0.85 (0.71-1.01)


Cancer Mortality 148 (1.0%) 363 (1.1%) 338 (1.1%) 188 (1.1%) 73 (0.9%)

Univariate* 1.00 1.13 (0.93-1.37) 1.07 (0.87-1.31) 1.04 (0.83-1.31) 0.83 (0.62-1.11)

Primary (+Diet) 1.00 1.09 (0.89-1.35) 1.02 (0.82-1.27) 1.09 (0.85-1.40) 0.82 (0.60-1.14)


OR=Odds ratio, CI=confidence intervals. Primary model: age, sex, education, alcohol intake, diabetes mellitus, body mass index, a history of cardiovascular events and current smoking. Diet,

adjusted for caloric intake, potassium excretion, mAHEI score and waist-to-hip ratio. BP=blood pressure, HR=heart rate.

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Appendix 1: The Prospective Urban Rural Epidemiological Study (PURE Study) Design

The Prospective Urban Rural Epidemiological Study (PURE Study) enrolled 168,067 individuals

between 35 and 70 years of age from 21low, middle and high-income countries (1,2). The study

includes population samples from 664communities from 21countries from 5 continents representing a

broad range of economic and social circumstances (1,2).PURE includes countries in four income

strata based on World Bank classification in 2006: five low-income countries (Bangladesh, India,

Pakistan, Tanzania, and Zimbabwe), five lower middle-income countries (China, Colombia, Iran,

Occupied Palestinian Territory, and the Philippines), seven upper middle-income countries

(Argentina, Brazil, Chile, Malaysia, Poland, South Africa, and Turkey), and four high-income

countries (Canada, Saudi Arabia, Sweden, and United Arab Emirates). Recruitment began on Jan 1,

2003, and was completed in the first wave of 18 countries by March 31, 2013. The second

wave of three countries (Philippines, Saudi Arabia, and Tanzania) began on January 1, 2012

and was completed by June 2014. The study is coordinated by the Population Health Research

Institute, Hamilton Health Sciences and McMaster University, Canada.

Participant Selection Methodology as Excerpted from Teo et al. (1)

Selection of Countries

The choice and number of countries selected in PURE reflects a balance between involving a large

number of communities in countries at different economic levels, with substantial heterogeneity in

social and economic circumstances and policies, and the feasibility of centers to successfully achieve

long-term follow-up. Thus, PURE included sites in which investigators are committed to collecting

good-quality data for a low-budget study over the planned 10-year follow-up period and did not aim

for a strict proportionate sampling of the entire world.

Selection of Communities

Within each country, urban and rural communities were selected based on broad guidelines. A

common definition for “community” that is applicable globally is difficult to establish (3). In PURE, a

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community was defined as a group of people who have common characteristics and reside in a

defined geographic area. A city or large town was not usually considered to be a single community,

rather communities from low-, middle-, and high-income areas were selected from sections of the city

and the community area defined according to a geographical measure (e.g., a set of contiguous postal

code areas or a group of streets or a village). The primary sampling unit for rural areas in many

countries was the village. The reason for inclusion of both urban and rural communities is that for

many countries, urban and rural environments exhibit distinct characteristics in social and physical

environment, and hence, by sampling both, we ensured considerable variation in societal factors

across PURE communities. The number of communities selected in each country varied, with the aim

to recruit communities with substantial heterogeneity in social and economic circumstances balanced

against the capacity of local investigators to maintain follow-up. In some countries (e.g. India, China,

Canada, and Colombia), communities from several states/provinces were included to capture regional

diversity, in policy, socioeconomic status, culture, and physical environment. In other countries (e.g.,

Iran, Poland, Sweden, and Zimbabwe), fewer communities were selected.

Selections of Households and Individuals

Within each community, sampling was designed to achieve a broadly representative sample of that

community of adults aged between 35 and 70 years. The choice of sampling frame within each centre

was based on both “representativeness” and feasibility of long-term follow-up, following broad study

guidelines. Once a community was identified, where possible, common and standardized approaches

were applied to the enumeration of households, identification of individuals, recruitment procedures,

and data collection. The method of approaching households differed between regions. For example, in

rural areas of India and China, a community announcement was made to the village through contact of

a community leader, followed by in-person door-to-door visits of all households. In contrast in

Canada, initial contact was by mail followed by telephone inviting members of the households to a

central clinic. For each approach, at least 3 attempts at contact were made. Households were eligible if

at least 1 member of the household was between the ages of 35 and 70 years and the household

members intended to continue living in their current home for a further 4 years. All individuals within

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these households between 35 and 70 years providing written informed consent were enrolled. When a

household refused to participate, demographics and simple self-report risk factor data were recorded

in a non-responder form.

References

1. Teo K, Chow CK, Vaz M, Rangarajan S, Yusuf S; PURE Investigators-Writing Group. The

Prospective Urban Rural Epidemiology (PURE) study: examining the impact of societal influences on

chronic noncommunicable diseases in low-, middle-, and high-income countries. Am Heart J

2009;158:1-7.e1.

2. Yusuf S, Islam S, Chow CK, et al.; Prospective Urban Rural Epidemiology (PURE) Study

Investigators. Use of secondary prevention drugs for cardiovascular disease in the community in high-

income, middle-income, and low-income countries (the PURE Study): a prospective epidemiological

survey. Lancet 2011;378:1231-43.

3. MacQueen KM, McLellan E, Metzger DS, et al. What is community? An evidence-based definition

for participatory public health. Am J Public Health 2001;91:1929-38.

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Appendix 2. The Kawasaki method for estimating sodium intake

We used the Kawasaki formula (1) to estimate24-h urinary excretion of sodium and

potassium (in grams /d) from a fasting morning specimen. Previous studies (1,2) and our

validation of the method in 11 countries,(3) showed that the estimated sodium excretion from

the morning urine specimen shows a good correlation with direct measures of sodium

excretion from the actual 24-h urine collection (intra-class correlation coefficient of 0.70;95%

CI 0.61–0.77]. The BP change per g of sodium was 2.11/0.78 mm Hg,(4) which is consistent

with the results of a meta-analysis of randomised controlled trials of sodium lowering in

which sodium intake was measured using repeated 24 hour urine collections (5)(see summary

Table below).

Summary of validity, degree of bias, and reliability results for different methods of estimated 24-

hour sodium excretion versus measured excretion (From Mente A, et al, 2014. J Hypertens 32:1005-

14) (3).

24-hour measured excretion Kawasaki method

Mean (±SD) sodium excretion, mg/day 4116± 1978 4430 ± 1253 †

Degree of bias (95% CI), mg/day Reference 313 (182 to 444)

Validation ICC (95% CI)

All Reference 0.71 (0.65 to 0.76)

Excluding anti-

hypertensive

medication

Reference 0.73 (0.65 to 0.79)

Test-retest ICC (95% CI)

All 0.72 (0.65 to 0.77) 0.68 (0.58 to 0.75)

Excluding anti-

hypertensive

medication

0.76 (0.68 to 0.81) 0.70 (0.59 to 0.77)

Pearson correlation coefficient vs. BP

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Systolic BP 0.14 (0.06 to 0.22) 0.16 (0.08 to 0.24)

Diastolic BP 0.18 (0.10 to 0.26) 0.19 (0.11 to 0.27)

ICC, intraclass correlation coefficient; BP, blood pressure.

† Significantly higher than 24-hour measured excretion.

‡ Significantly lower than 24-hour measured excretion and Kawasaki estimated excretion.

* Significantly greater bias than Kawasaki estimated excretion.

Measured vs. Kawasaki Sodium

Intraclass correlation coefficient (ICC) = 0.71 (95% CI: 0.65 to 0.76) (p<0.0001)

Figure. Scatter plot of estimated versus measured 24-hour urinary sodium excretion.

(From Mente A, et al, 2014. J Hypertens 32:1005-14) (3).

References

1. Kawasaki T, Itoh K, Uezono K, Sasaki H. Simple method for estimating 24 h urinary

sodium and potassium excretion froms econd morning voiding urine specimen in adults. Clin

Exp Pharmacol Physiol 1993; 20: 7–14.

2. Han W, Sun N, Chen Y, Wang H, Xi Y, Ma Z. Validation of the spot urine in evaluating

24-hour sodium excretion in Chinese hypertension patients. Am J Hypertens 2015; 28: 1368–

75.

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3. Mente A, O’Donnell MJ, Dagenais G, et al. Validation and comparison of three formulae

to estimate sodium and potassium excretion from a single morning fasting urine compared to

24-hmeasures in 11 countries. J Hypertens 2014; 32: 1005–14.

4. Mente A, O’Donnell MJ, Rangarajan S, et al; PURE Investigators. Association of urinary

sodium and potassium excretion with blood pressure. N Engl J Med 2014; 371: 601–11.

5. He FJ, Li J, Macgregor GA. Effect of longer-term modest salt reduction on blood pressure.

Cochrane Database Syst Rev 2013;4: CD004937.

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PURE Project Office Staff, National Coordinators, Investigators, and Key Staff:

Project office (Population Health Research Institute, Hamilton Health Sciences and

McMaster University, Hamilton, Canada): S Yusuf* (Principal Investigator).

S Rangarajan (Program Manager Manager); K K Teo, C K Chow, M O’Donnell, A Mente, D

Leong, A Smyth, P Joseph, A Merchant, O Kurmi, S Islam (Statistician), M Zhang

(Statistician), W Hu (Statistician), C Ramasundarahettige (Statistician), G Wong

(Statistician), S Bangdiwala, L Dyal, A Casanova, M Dehghan (Nutrition Epidemiologist), G

Lewis (Associate Program Manager), D Agapay, A Aliberti, N Aoucheva, A Arshad, A

Reyes, B Bideri, R Buthool, S Chin, M Di Marino, R Frances, S Gopal, D Hari, M

Jakymyshn, N Kandy, I Kay, J Lindeman, G McAlpine, E McNeice, M(a) Mushtaha, M(o)

Mushtaha, R Patel, S Ramacham, E Ramezani, J Rimac, F Shifaly, J Swallow, M Trottier, S

Trottier, R Solano, A Zaki, B Zhang, V Zhang

Core Laboratories: M McQueen, K Hall, J Keys (Hamilton), X Wang (Beijing, China), J

Keneth, A Devanath (Bangalore, India).

Argentina: R Diaz*, A Orlandini, P Lamelas, M L Diaz, A Pascual, M Salvador, C Chacon;

Bangladesh: O Rahman*, R Yusuf*, S A K S. Ahmed, T Choudhury, M Sintaha, A Khan, O

Alam, N, Nayeem, S N Mitra, S Islam, F Pasha; Brazil: A Avezum*, C S Marcilio, A C

Mattos, G B Oliveira; Canada: K Teo*, S Yusuf*, A Arshad, B Bideri, I Kay, J Rimac, R

Buthool, S Trottier, G Dagenais, P Poirier, G Turbide, D Auger, A LeBlanc De Bluts, M C

Proulx, M Cayer, N Bonneville, S Lear, V de Jong, A N Saidy, V Kandola, E Corber, I

Vukmirovich, D Gasevic, A Wielgosz, A Pipe, A Lefebvre, A Pepe, A Auclair, A Prémont, A

S Bourlaud; Chile: F Lanas*, P Serón, M J Oliveros, F Cazor, Y Palacios; China: Li Wei*,

Liu Lisheng*, Chen Chunming, Wang Xingyu, Zhao Wenhua, Zhang Hongye, JiaXuan, Hu

Bo, Sun Yi, Bo Jian, Zhao Xiuwen, Chang Xiaohong, Chen Tao, Chen Hui, Chang Xiaohong,

Deng Qing, Cheng Xiaoru, Deng Qing, He Xinye, Hu Bo, JiaXuan, Li Jian, Li Juan,Liu Xu,

Ren Bing, Sun Yi, Wang Wei, Wang Yang, Yang Jun, Zhai Yi, Zhang Hongye, Zhao

Xiuwen,Zhu Manlu, Lu Fanghong, Wu Jianfang, Li Yindong, Hou Yan, Zhang Liangqing,

Guo Baoxia, Liao Xiaoyang, Zhang Shiying, BianRongwen, TianXiuzhen, Li Dong, Chen Di,

Wu Jianguo, Xiao Yize, Liu Tianlu, Zhang Peng, Dong Changlin, Li Ning, Ma Xiaolan,

Yang Yuqing, Lei Rensheng, Fu Minfan, He Jing, Liu Yu, Xing Xiaojie, Zhou Qiang,;

Colombia: P Lopez-Jaramillo*, P A Camacho-Lopez, J Otero-Wandurraga, D I Molina, C

Cure-Cure, M Perez, E Hernandez, E Arcos, C Narvaez, A Sotomayor, H Garcia, G Sanchez,

F Cotes, A Rico, M Duran, C Torres; India: P Mony *, M Vaz*, S Swaminathan, A V

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Kurpad, K G Jayachitra, N Kumar, H A L Hospital, V Mohan*, M Deepa, K Parthiban, R M

Anjana, R. Dhanasekar and S. Sureshkumar, D Anitha, K Sridevi, R Gupta*, I Mohan, R

Bhargava, R Kumar, J S Thakur, B Patro, R Mahajan, P Chaudary, V Raman Kutty, K

Vijayakumar*, K Ajayan, G Rajasree, AR Renjini, A Deepu, B Sandhya, S Asha, H S

Soumya, R Kumar*, M Kaur, P V M Lakshmi, V Sagar, Iran: R Kelishadi*, A Bahonar, N

Mohammadifard, H Heidari, Kazakhstan: K Davletov*, B Assembekov, B Amirov;

Kyrgyzstan: E Mirrakhimov*, S Abilova, U Zakirov, U Toktomamatov; Malaysia: K

Yusoff*, R Ismail, T S T Ismail, K K Ng, A Devi, N M Nasir, M M Yasin, M Miskan, E A

Rahman, M K M Arsad, F Ariffin, S A Razak, F A Majid, N A Bakar, M Y Yacob, N Zainon,

R Salleh, M K A Ramli, N A Halim, S R Norlizan, N M Ghazali, M N Arshad, R Razali, S

Ali, H R Othman, C W J C W Hafar, A Pit, N Danuri, F Basir, S N A Zahari, H Abdullah, M

A Arippin, N A Zakaria, I Noorhassim, M J Hasni, M T Azmi, M I Zaleha, K Y Hazdi, A R

Rizam, W Sazman, A Azman; Occupied Palestinian Territory: R Khatib*, U Khammash, R

Giacaman; Pakistan: R Iqbal*, R Khawaja, I Azam, K Kazmi; Peru: J Miranda*, A Bernabe

Ortiz, W Checkley, R H Gilman, L Smeeth, R M Carrillo, M de los Angeles, C Tarazona

Meza; Philippines: A Dans*, H U Co, J T Sanchez, L Pudol, C Zamora-Pudol, L A M

Palileo-Villanueva, M R Aquino, C Abaquin, SL Pudol, K Manguiat, S Malayang; Poland:

W Zatonski*, A Szuba, K Zatonska, R Ilow#, M Ferus, B Regulska-Ilow, D Różańska, M

Wolyniec; Saudi Arabia: KF AlHabib*, M Alshamiri, HB Altaradi, O Alnobani, N Alkamel,

M Ali, M Abdulrahman, R Nouri; South Africa: L Kruger*, A Kruger

#, P Bestra, H H

Voster, A E Schutte, E Wentzel-Viljoen, FC Eloff, H de Ridder, H Moss, J Potgieter, A A

Roux, M Watson, G de Wet, A Olckers, J C Jerling, M Pieters, T Hoekstra, T Puoane, R

Swart*, E Igumbor, L Tsolekile, K Ndayi, D Sanders, P Naidoo, N Steyn, N Peer, B Mayosi,

B Rayner, V Lambert, N Levitt, T Kolbe-Alexander, L Ntyintyane, G Hughes, J Fourie, M

Muzigaba, S Xapa, N Gobile , K Ndayi, B Jwili, K Ndibaza, B Egbujie; Sweden A

Rosengren*, K Bengtsson Boström, A Rawshani, A Gustavsson, M Andreasson, L

Wirdemann; Tanzania: K Yeates*, M Oresto, N West Turkey: A Oguz*, N Imeryuz, Y

Altuntas, S Gulec, A Temizhan, K Karsidag, K B T Calik, A A K Akalin, O T Caklili, M V

Keskinler, K Yildiz; United Arab Emirates: A H Yusufali, F Hussain, M H S

Abdelmotagali, D F Youssef, O Z S Ahmad, F H M Hashem, T M Mamdouh, F M

AbdRabbou, S H Ahmed, M A AlOmairi, H M Swidan, M M Omran, N A Monsef ;

Zimbabwe: J Chifamba*, T Ncube, B Ncube, C Chimhete, G K Neya, T Manenji, L

Gwaunza, V Mapara, G Terera, C Mahachi, P Murambiwa, R Mapanga, A Chinhara

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*National Coordinator

# Deceased

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joint association of urinary sodium and potassium · confidential: for review only 4 abstract...

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