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Dietary Reference Intakes for Sodium and Potassium (2019)

Chapter: 3 Methodological Considerations

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Suggested Citation:"3 Methodological Considerations." National Academies of Sciences, Engineering, and Medicine. 2019. Dietary Reference Intakes for Sodium and Potassium. Washington, DC: The National Academies Press. doi: 10.17226/25353.
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3

Methodological Considerations

The Dietary Reference Intakes (DRIs) are derived from evidence on relationships between nutrient intake and indicators, which can include clinical endpoints, surrogate markers, biomarkers, and risk factors for a chronic disease. A number of complex methodological considerations are integral to the critical evaluation and interpretation of studies that examine these relationships. This chapter summarizes the committee’s review and interpretation of four methodological considerations related to deriving the DRIs for potassium and sodium: relevant biological roles of potassium and sodium, methods for estimating potassium and sodium intake, interactions of potassium and sodium, and evidence on subpopulations.

RELEVANT BIOLOGICAL ROLES OF POTASSIUM AND SODIUM

The first step of the DRI organizing framework is to review evidence on all potentially relevant indicators of adequacy, toxicity, and chronic disease risk in order to identify the indicators that inform the derivation of the DRI values. Final selection of indicators is guided by the strength of the evidence and their public health significance. The scientific literature includes evaluation of relationships between potassium or sodium intakes and a variety of indicators, but not all indicators are necessarily relevant or have a sufficiently robust evidence base on which to establish a DRI. The committee considered the biological plausibility of relationships between potassium and sodium and selected health outcomes and surrogate markers to determine a final list of indicators that could potentially be relevant for establishing DRI values. A brief discussion of the interrelated physiological

Suggested Citation:"3 Methodological Considerations." National Academies of Sciences, Engineering, and Medicine. 2019. Dietary Reference Intakes for Sodium and Potassium. Washington, DC: The National Academies Press. doi: 10.17226/25353.
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roles and regulation of these two nutrients provides context for the selection of indicators for the potassium and sodium DRIs.

Potassium

Approximately 98 percent of total body potassium is found within cells (Russo et al., 2005). Maintenance of this gradient across the cell membrane is important for vital processes, including establishment of the cellular membrane potential, contraction of muscles, control of cardiac conduction, and transmission of nerve signals within and between cells (Kowey, 2002). Potassium also plays a role in regulating water balance and acid–base balance in the blood and tissues (Kowey, 2002).

The imbalance between intracellular and extracellular potassium concentrations is central to how potassium functions in the body, and is therefore tightly regulated through homeostatic mechanisms. Serum potassium concentration is maintained within a narrow range, normally 3.5 to 5.0 mmol/L, over a wide range of potassium intakes. For example, average usual potassium intake among both U.S. and Canadian adults is approximately 2,700 mg/d (69 mmol/d),1 whereas reported intake among isolated populations is as high as 5,943 mg/d (152 mmol/d) (Oliver et al., 1975); these differences in potassium intake do not typically result in serum potassium concentrations outside of the normal reference range.

The kidney plays a principle role in regulating potassium homeostasis and extracellular potassium concentrations. Potassium is filtered by the glomerulus; bulk potassium reabsorption occurs in the proximal convoluted tubule and, to a lesser degree, in the ascending limb of Henle’s loop. Fine regulation of potassium balance occurs in the collecting duct and is regulated by serum potassium concentrations, aldosterone, and acid–base status (Gumz et al., 2015). The gastrointestinal tract also participates in potassium homeostasis, where adaptive changes in the colon can promote potassium secretion via potassium channels for elimination in feces (Batlle et al., 2015). It is likely that additional factors influence potassium homeostasis and communication between the intestines and kidneys.

Mineralocorticoids, principally aldosterone, are important regulators of potassium homeostasis. High serum potassium concentrations activate aldosterone release, and low serum potassium concentrations suppress it. Aldosterone is activated by angiotensin II via activation of the renin-angiotensin-aldosterone system (RAAS) (Lumbers, 1999). Aldosterone promotes potassium excretion, sodium reabsorption, and hydrogen ion

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1 Estimates of mean usual potassium intake for U.S. and Canadian adults 19 years of age and older is 2,721 and 2,697 mg/d, respectively (for details regarding intake distribution evidence sources, see Appendix G).

Suggested Citation:"3 Methodological Considerations." National Academies of Sciences, Engineering, and Medicine. 2019. Dietary Reference Intakes for Sodium and Potassium. Washington, DC: The National Academies Press. doi: 10.17226/25353.
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excretion, resulting in alkalosis. These actions lead to extracellular fluid expansion, increased blood pressure, and decreased serum potassium to within normal ranges. The effects of endogenous hormones and medications also contribute to this homeostatic regulation. Stimulation of the insulin receptor promotes movement of potassium from the extracellular to the intracellular space (McDonough and Youn, 2017). Similar effects are observed with medications that stimulate adrenergic receptors and by increasing systemic pH.

Inadequate potassium intake upregulates the sodium hydrogen exchange 3 (NHE3) protein in the proximal tubule, causing excessive sodium retention, expansion of the extracellular fluid volume, and hypertension. The NHE3 protein is a critical part of the apparatus regulating bulk sodium reabsorption in the proximal tubule, where approximately 60 percent of filtered sodium is reabsorbed. In animal models, potassium depletion promotes adaptive increases in NHE3 activity and sodium transport (Soleimani et al., 1990). Potassium depletion activates the sodium chloride cotransporter in the distal convoluted tubule (Terker et al., 2015); this transporter is inhibited by thiazide-type diuretics. Increased potassium intake acutely increases urinary sodium excretion until a new steady state is reached. When this is achieved, sodium excretion is approximately equivalent to intake. In general, sodium intake does not affect potassium excretion, but net losses of potassium have been documented at very high levels of sodium intake (6,900 mg/d [300 mmol/d]) (Weinberger et al., 1982).

Potassium concentrations may have direct effects on the arterial wall. High potassium concentrations hyperpolarize endothelial cells, causing endothelium-dependent vasodilation, whereas experimental potassium depletion inhibits endothelium-dependent vasodilation (Amberg et al., 2003; Haddy et al., 2006). Low extracellular potassium concentrations have been implicated in stimulating hypertrophy of vascular smooth muscle cells found in the tunica media of the arterial wall (McCabe and Young, 1994). High potassium intake may have favorable and independent cardiovascular effects because of the inhibition of vascular smooth muscle cell proliferation, arterial thrombosis, platelet aggregation, and cytochrome C release (Young et al., 1995).

Potassium status has been linked to other systems of the body. For instance, potassium deficiency may contribute to alterations in glycemic control. Early research indicated that potassium depletion inhibits insulin secretion, whereas potassium infusion has the opposite effect (Dluhy et al., 1972; Rowe et al., 1980). Potassium intake has also been related to urinary calcium excretion. A prominent theory posits a mechanism related to the acid–base balance; diets high in noncarbonic acid–producing foods (e.g., animal protein, cereal grains) and low in potassium-rich foods that provide bicarbonate precursors (e.g., fruits and vegetables) may lead to

Suggested Citation:"3 Methodological Considerations." National Academies of Sciences, Engineering, and Medicine. 2019. Dietary Reference Intakes for Sodium and Potassium. Washington, DC: The National Academies Press. doi: 10.17226/25353.
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diet-induced, low-grade acidosis. Prolonged exposure to such a diet may involve osteoclast mechanisms and the use of skeletal alkaline calcium salts to buffer the acidic pH. The resulting hypercalciuria could potentially have a negative effect on bone health. Additionally, hypercalciuria is a primary risk factor for the formation of calcium-containing kidney stones (Corbetta et al., 2005; Curhan and Taylor, 2008).

Sodium

Approximately 95 percent of the body’s total sodium content is extracellular (IOM, 2005). Sodium, along with chloride, has an important role in the maintenance of extracellular volume and plasma osmolality. Sodium is also a critical determinant of cellular membrane potentials and the active transport of molecules across cell membranes.

Approximately 98 percent of consumed sodium is absorbed across a wide range of dietary intakes. It was thought that in a steady state, daily urinary sodium excretion was roughly equal to the amount consumed, but emerging evidence suggests that sodium storage pools may exist in the skin and muscle (Wang et al., 2017). In animal models, high sodium intake results in increased sodium content in skin, thought to be caused by the dysregulation of skin lymphatic expansion. Studies with 23Na-MRI have shown that skin sodium content is related to the blood pressure levels in patients with resistant hypertension (Kopp et al., 2013).2 Furthermore, recent data suggest that urinary sodium excretion does not mirror sodium intake on a day-to-day basis (Kopp et al., 2013; Lerchl et al., 2015; Rakova et al., 2013; Weaver et al., 2016). If corroborated, these findings suggest that urinary sodium excretion does not necessarily reflect short-term dietary intake.

Sodium balance is influenced by the RAAS, the sympathetic nervous system, the kallikrein-kinin system, atrial natriuretic peptide, mechanisms that regulate renal and medullary blood flow, and intrarenal mechanisms (IOM, 2005). Stimulation of the RAAS occurs with low sodium intake, low blood pressure, or low blood volume. Angiotensin is a strong vasoconstrictor that regulates the proximal tubule of the nephron, promoting sodium retention and stimulating the release of aldosterone from the adrenal cortex. In the distal tubule of the nephron, renal reabsorption of sodium is promoted by aldosterone via a mineralocorticoid receptor-mediated exchange for hydrogen and potassium ions. Likewise, the sympathetic nervous system is activated by short-term, severe sodium restriction

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2 Resistant hypertension is described as blood pressure that remains above goal despite concurrent use of three antihypertensive agents of different classes, one of which should be a diuretic (Calhoun et al., 2008).

Suggested Citation:"3 Methodological Considerations." National Academies of Sciences, Engineering, and Medicine. 2019. Dietary Reference Intakes for Sodium and Potassium. Washington, DC: The National Academies Press. doi: 10.17226/25353.
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and is suppressed by high sodium intake. Intrarenal mechanisms that are hypothesized to regulate the sympathetic nervous system and renal circulation include locally released prostaglandins, angiotensin, kinins, and endothelial relaxing factor. Meta-analyses have concluded that sodium reduction interventions lead to increases in renin and aldosterone concentrations, but changes in noradrenaline and adrenaline concentrations were not consistently observed (Aburto et al., 2013b; Graudal et al., 2017; He et al., 2013).

Given its relationship with blood pressure, excessive sodium intake is thought to be one mechanism that contributes to the development of hypertension and, eventually, subclinical and clinical cardiovascular disease. Increased left ventricular mass is considered to be a structural adaptation of the heart as a compensatory mechanism in response to high blood pressure and wall stress. Factors that are associated with blood pressure, such as potassium and sodium intake, are also associated with elevated left ventricular mass (Rodriguez et al., 2011). High sodium intake may be associated with elevated left ventricular mass and cardiovascular disease, independent of its association with blood pressure (Jin et al., 2009; Mills et al., 2016).

Increasing sodium intake has been shown to increase urinary calcium excretion (Breslau et al., 1982; Lin et al., 2003). Evidence on the effect of a hypernatremic environment on mouse and human osteoclastogenesis suggests that there may be a cell-mediated effect promoting bone resorption as well as urinary calcium excretion (Wu et al., 2017). This relationship may have implications for bone health.

Implications for the Committee’s Review of the Evidence

Potassium and sodium’s physiological functions appear to be primarily mediated through blood pressure, which has a strong relationship with cardiovascular disease. Accordingly, the committee focused the indicator review on relationships between potassium and sodium intakes and blood pressure and cardiovascular disease outcomes. Given links between both nutrients and urinary calcium excretion, reviewing evidence on relationships with bone health (particularly bone mineral density and the chronic disease endpoint of osteoporosis) was also warranted. The committee also considered evidence on the relationships between potassium and sodium intake and kidney disease to be potentially informative. Finally, the committee viewed the relationship between potassium and glycemic control as one of possible interest.

Suggested Citation:"3 Methodological Considerations." National Academies of Sciences, Engineering, and Medicine. 2019. Dietary Reference Intakes for Sodium and Potassium. Washington, DC: The National Academies Press. doi: 10.17226/25353.
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METHODS FOR ESTIMATING POTASSIUM AND SODIUM INTAKE

The accuracy of nutrient intake assessments affects multiple steps in the DRI organizing framework. After the committee selects indicators that reflect a causal relationship between intakes and the outcome of interest (first step of the DRI organizing framework), it assesses the evidence on intake–response relationships for each indicator (second step of the DRI organizing framework). The committee then compares the established DRI values with current population intake levels (third step of the DRI organizing framework), which provides context for the public health implications of the selected reference values. The DRI values refer to average daily nutrient intake over time. Thus, the accurate assessment of usual dietary intake—the long-run average daily nutrient intake—is applicable to multiple steps in deriving DRI values.

The accuracy of potassium and sodium intake estimates is critical, as it can affect the strength of diet–indicator relationships, the strength of intake–response relationships, the accuracy of quantitative estimates of the intake–response relationship, and accuracy of the estimation of usual intake distribution for a population. All measures of potassium and sodium intake are subject to random and systematic measurement errors. Specifically, random measurement error leads to estimates of diet–health relationships that are weaker than what actually exists, diminishes the statistical power to detect these relationships, and overestimates the prevalence of low and high population or group intakes. When systematic errors occur, means, distributions, and effect sizes may not be correctly estimated, and the direction of the effect of the error on estimated relationships is not always predictable.

Carefully designed and conducted controlled feeding studies, particularly those that chemically analyze the diets to obtain quantitative compositional information on the nutrient of interest, can clarify the association between potassium and sodium intake and excretion and help validate other instruments that measure intake. However, controlled feeding studies are often challenging to conduct, particularly for extended periods of time, so researchers typically use other methods to assess nutrient intake. The following sections review the strengths and limitations (including potential measurement errors) of commonly used methods to assess potassium and sodium intake.

Urinary Measures

24-Hour Urine

Potassium and sodium intake can be estimated by measuring their excretion in the urine over a 24-hour period. A strength of this approach is

Suggested Citation:"3 Methodological Considerations." National Academies of Sciences, Engineering, and Medicine. 2019. Dietary Reference Intakes for Sodium and Potassium. Washington, DC: The National Academies Press. doi: 10.17226/25353.
×

that it is an objective measure without reliance on food composition databases or self-reported dietary intake. Collecting complete urine specimens can be challenging; inaccuracies can occur unless collection is monitored and subject to quality-control methods, such as exclusion of participants who self-report incomplete collection or who are outliers for measures that indicate inaccurate collection (e.g., based on urinary volume, specific gravity, collection duration, para-aminobenzoic acid, creatinine index). Because it can affect the accuracy, it is important to distinguish between 24-hour urine specimens that use quality-control methods and other collection methods that lack these controls.

Sodium excretion varies day to day within individuals, reflecting random error depending on the day or days a specimen is collected (Cogswell et al., 2015; Dyer et al., 1994). Even with random day-to-day variation in excretion, in the absence of systematic error, unbiased (though imprecise) estimates of average usual intakes can be obtained because each measurement of sodium taken on a day reflects true intake plus some random error. A more accurate estimate of the true average intake can be obtained by collecting at least two measurements and by using a statistical model. To estimate attributes of the usual intake distribution of sodium other than the mean (e.g., variability, percentiles), the use of statistical methods to adjust for measurement error is necessary. If no statistical adjustments are applied, a large number of samples (10 or more for each individual), collected on both weekdays and weekends, may be needed to obtain an accurate estimate of the distribution of usual sodium intake in the group that has the correct variance (Dyer et al., 1997; Liu and Stamler, 1984; Luft et al., 1982). Potassium appears to have a greater reliability index than sodium, indicating that fewer replicates may be needed (Sun et al., 2017; Tasevska et al., 2006).

Both potassium and sodium excretion may have infradian rhythms (i.e., lasting longer than 1 day) rather than circadian rhythms (Rakova et al., 2013). Sampling during infradian rhythms is expected to be random across participants and to reflect random error in sampling and unbiased estimates across a population (Freedman et al., 2015). For these reasons, measures of 24-hour urinary potassium and sodium are generally accepted to be recovery biomarkers, meaning that on average they accurately reflect usual dietary intakes and are not subject to systematic bias from personal characteristics.

Because not all consumed potassium and sodium is absorbed and excreted via urine, assumptions are made regarding their absorptive bioavailability. Assumptions vary among studies for the percent of potassium or sodium absorbed that is available for excretion in urine, which affects the estimated distribution of usual intake using these methods. Approximately 77 percent of consumed potassium is excreted in urine, which sug-

Suggested Citation:"3 Methodological Considerations." National Academies of Sciences, Engineering, and Medicine. 2019. Dietary Reference Intakes for Sodium and Potassium. Washington, DC: The National Academies Press. doi: 10.17226/25353.
×

gests approximately 77 percent of dietary potassium is absorbed (Aburto et al., 2013a; Tasevska et al., 2006). If the proportion recovered in urine is consistent across population subgroups, inflating biomarker estimates for incomplete recovery is mathematically simple, and the inflated value could be considered an unbiased estimate of intake. However, some evidence suggests that potassium excretion may differ systematically across subgroups or by other dietary intakes (Turban et al., 2013; Weaver et al., 2016). These types of differences would be expected to result in systematic bias (unless statistical adjustment is performed for all known factors that can lead to differences) and would not support the use of potassium as a recovery biomarker; more research is needed to determine if there are systematic biases in 24-hour urinary potassium measurements.

Compared to potassium, a greater proportion of consumed sodium is recovered in the urine. A meta-analysis of data from 35 trials estimated that 92.8 percent of sodium ([95% confidence interval {CI}: 90.7, 95.0], I2 = 95.1 percent) is excreted in urine (Lucko et al., 2018). Although cautious interpretation of these results is needed because there is a large amount of unexplained heterogeneity, the meta-analysis provides support for using 24-hour urine collections to estimate average sodium intake and recommends multiple 24-hour urine samples to determine an individual’s usual sodium intake (Lucko et al., 2018). Therefore, multiple 24-hour urine samples carefully collected with quality-control methods are currently considered to be the best method for assessing long-term intakes of sodium and potassium. Obtaining multiple urines or using statistical methods may adjust for random error from within-person variation in these measures.

Overnight Urine

The challenges of collecting complete 24-hour urine specimens lead some investigators to collect urinary excretion during an overnight period of 8 hours. In one analysis, intra- and interindividual variation in sodium excretion was greater for 8-hour, first-void collections than for 24-hour collections (Ji et al., 2012). There is also potential for systematic error because of greater excretion of sodium overnight than during the day for some individuals, which may differ by factors such as age, sex, or hypertension status (Dyer et al., 1987). Strong correlations between 24-hour and 8-hour sodium excretions have been reported (He et al., 1993; Liu et al., 1979, 1986, 1987), but a more recent systematic review concluded that such correlations vary widely, leaving the validity of this method unclear (Ji et al., 2012).

Suggested Citation:"3 Methodological Considerations." National Academies of Sciences, Engineering, and Medicine. 2019. Dietary Reference Intakes for Sodium and Potassium. Washington, DC: The National Academies Press. doi: 10.17226/25353.
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Spot Urine

Some investigators estimate 24-hour potassium or sodium excretion based on a single (“spot”) urine collection. This is the least burdensome urinary measure for participants, but is subject to greater bias owing to the temporal variability in urine tonicity and nutrient excretion between and within individuals (Ji et al., 2012). Factors that may influence variation in sodium concentration in the spot sample includes meal timing and composition, fluid intake, diuretic use, and intense exercise (Mann and Gerber, 2010). Bias can also arise because of the customary approach of indexing spot urine sodium to urine creatinine, which is influenced by urine tonicity and muscle mass, which, in turn, is influenced by age, sex, body weight, and race/ethnicity (Ix et al., 2011). Among healthy individuals, sodium excretion appears to be at its maximum during midday (Cogswell et al., 2015). Accuracy of spot urine estimates may be improved if individual intakes are near the population mean (Mill et al., 2015) or with the collection of multiple spot urines to estimate usual intake (Wang et al., 2015).

Various equations exist to estimate 24-hour potassium or sodium excretion from spot urine samples, including Tanaka, INTERSALT, Kawasaki, Mage, Nerbass, Arithmetic, PAHO, and Danish (Brown et al., 2013; Ji et al., 2014; Kawasaki et al., 1993; Mage et al., 2008; Nerbass et al., 2014; Tanaka et al., 2002; Toft et al., 2014; WHO/PAHO, 2010). Correlations between spot urine samples and measured 24-hour urine excretion are often poor (i.e., < 0.4), exhibit various biases, and vary in reliability by sex and race/ethnicity (Allen et al., 2017; Cogswell et al., 2013; Ji et al., 2014; Mercado et al., 2018). A systematic review comparing spot urine estimates to 24-hour excretion of sodium found correlations to range widely (from 0.17 to 0.86) depending on the timing and number of spot urine samples (Ji et al., 2012).

A single spot urine sample is unlikely to be useful in estimating long-term intake and exposure, particularly at the individual level, given the variation in excretion within and among days as well as the documented issues of measurement bias. Recent evidence suggests that spot urine collections overestimate excretion when intake is low and underestimate excretion when intake is high (He et al., 2018; Huang et al., 2016; Mente et al., 2014), in both healthy individuals and patients with kidney disease (Dougher et al., 2016). These systematic biases may explain, in part, why studies evaluating 24-hour urine sodium tend to have linear relationships with health outcomes (e.g., cardiovascular disease, mortality), whereas those using spot specimens often observe J- or U-shaped relationships (He et al., 2018; Olde Engberink et al., 2017). Although a single spot urine may not provide an unbiased estimate of intake–health relationships, it may be possible to obtain reliable estimates of sodium and potassium to character-

Suggested Citation:"3 Methodological Considerations." National Academies of Sciences, Engineering, and Medicine. 2019. Dietary Reference Intakes for Sodium and Potassium. Washington, DC: The National Academies Press. doi: 10.17226/25353.
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ize usual intake distributions for a population, using excretion obtained from a single or multiple spot urines and using a subset of participants with multiple spot urines as a calibration sample for measurement error adjustment (Wang et al., 2015).

Self-Reported Dietary Intake Assessments

All self-reported dietary assessment methods rely on food composition databases to estimate intake. This method is problematic for sodium, as only about 14 percent of sodium consumed is naturally occurring in unprocessed foods (Harnack et al., 2017). The majority of sodium consumed comes from foods prepared outside the home. To accurately measure sodium intake, consideration must be given to the variability in sodium content across specific brands of foods, limited information for restaurant-prepared food, and the precision and currency of food composition databases to estimate intakes, as well as systemic underreporting of total intake. Furthermore, self-reported dietary assessment methods do not always capture sodium added during cooking or at table, which is estimated to account for 6 and 5 percent of intake, respectively (Harnack et al., 2017). Low reliability among record coders or assumptions made about recipes can also introduce errors.

Every instrument for collecting self-reported dietary intake exhibits misreporting of energy, most commonly in the direction of underreporting for both children and adults. Underreporting of energy appears to be most pronounced among adults when intake is assessed using food frequency questionnaires, compared with energy estimates from doubly labeled water (Freedman et al., 2014).3 Two major causes of energy underreporting are underestimation of portion size and omission of foods relatively high in energy and low in nutrient density (Millen et al., 2009). The issue of energy underreporting may be more pronounced for respondents who are overweight or obese (Freisling et al., 2012; Lissner et al., 2007). Given that sodium and energy intake are highly correlated (USDA/ARS/FSRG, 2010), it is likely that underreporting of energy results in underreporting of sodium.

24-Hour Dietary Recall

Dietary intake can be estimated through 24-hour dietary recalls in which respondents report all foods and beverages consumed throughout 1 day. This method does not rely on respondent literacy (if interviewer

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3 Doubly labeled water is a technique that can be used to assess energy expenditure under free-living conditions. Individuals consume a dose of water labeled with stable isotopes (2H218O) and the disappearance rate of the isotopes can be used to calculate energy expenditure.

Suggested Citation:"3 Methodological Considerations." National Academies of Sciences, Engineering, and Medicine. 2019. Dietary Reference Intakes for Sodium and Potassium. Washington, DC: The National Academies Press. doi: 10.17226/25353.
×

administered) and it is a relatively low burden for the respondent. The data collected reflect cultural or regional food choices and dietary patterns. Given its retrospective nature, respondents may be less influenced to change their behavior due to observation (i.e., owing to the Hawthorne effect), although the advanced scheduling of the recall may mitigate this benefit. Twenty-four-hour dietary recalls capture details of diet but are short-term instruments, collecting only 1 day of intake; assessment of long-term, or usual, intake is typically of greater interest. This limitation can be reduced by using multiple 24-hour dietary recalls, particularly collected on both weekdays and weekends, and estimating usual intakes using statistical methods (Nusser et al., 1996; Tooze et al., 2006).

Twenty-four-hour dietary recalls attempt to capture usual daily intake, which is subject to both within- and between-person variability. An analysis that evaluated differences in the estimates of the distributions of usual potassium intake (e.g., estimating the prevalence of the population below a cutoff value) using two 24-hour recalls compared with two 24-hour urinary measures found prevalence estimates varied by 7 to 40 percent, with the largest differences in the middle of the distribution (Crispim et al., 2011). Coefficients of variation tend to be greater for sodium than for potassium (Hamdan et al., 2014). Thus, if the mean of 24-hour dietary recalls for an individual is used to estimate usual intake, more replicate recalls would be necessary for the measurement of sodium intake than for potassium intake, preferably including both weekend and weekday data. However, with 2 or more days of data and collection of recalls from both weekend days and weekdays on at least a subset of the population, methods to adjust for measurement errors can be used to estimate the distribution of usual intake of sodium and potassium in populations (Nusser et al., 1996; Thompson et al., 1986; Tooze et al., 2006).

Validation studies have compared 24-hour dietary recall results for potassium and sodium with those of other methods for estimating intake, including urinary biomarkers (Cogswell et al., 2018; Crispim et al., 2011; Freedman et al., 2015; Mossavar-Rahmani et al., 2017; Trijsburg et al., 2015). The level of adjustment for loss appears to be an important consideration when interpreting the results. For example, 24-hour dietary recalls were compared with 24-hour urine excretions for sodium and potassium in an analysis that pooled data from five U.S. studies (Freedman et al., 2015). When urinary potassium was adjusted for 20 percent loss, no bias was identified for men and a –4 percent bias (i.e., underreporting) was identified for women for the 24-hour dietary recall; no significant effects of personal characteristics on reporting bias were identified. When urinary sodium was adjusted for 14 percent loss, bias for sodium was –4 percent for men and –13 percent for women for the 24-hour dietary recall; underreporting of sodium was positively correlated with higher body mass index. In a study

Suggested Citation:"3 Methodological Considerations." National Academies of Sciences, Engineering, and Medicine. 2019. Dietary Reference Intakes for Sodium and Potassium. Washington, DC: The National Academies Press. doi: 10.17226/25353.
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of healthy, weight-stable participants 30–69 years of age, the ratio of mean sodium intake estimated from 24-hour dietary recalls to 24-hour urinary excretions was at least 0.90 at the population level (across sex, age, and weight categories), assuming 86 percent of consumed sodium was excreted in the urine (Rhodes et al., 2013); the ratio was highest among those with a body mass index less than 25 kg/m2. Taken together, these studies illustrate that, in general, bias for estimating mean potassium intake from 24-hour recall is generally small; bias for sodium intake is slightly greater and may be related to body mass index. Bias in estimating sodium intake, but not potassium intake, has been noted to improve with energy adjustment (+5 to +8 percent) (Freedman et al., 2015).

Estimates of potassium and sodium intake obtained from 24-hour dietary recalls have also been compared to estimates from 24-hour urinary excretions using data from the National Health and Nutrition Examination Survey (NHANES). In 2014, 24-hour urinary samples were collected from a subsample of nonpregnant adult NHANES participants, 20–69 years of age, in addition to other measures including 24-hour dietary recalls. For both the urinary sample and the dietary recall, a replicate measurement was collected from a subset of selected participants. The collection of replicate measurements allowed for usual intake distributions of potassium and sodium to be estimated by applying the National Cancer Institute method, which removes the effect of within-person variability, and by estimating standard errors using the balanced repeated replication method and 24-hour urine sample weights.

The committee was provided with distributions of usual potassium and sodium intake based on the 24-hour urinary samples and 24-hour dietary recall data from the NHANES 2014 subsample (n = 779).4Figures 3-1 and 3-2 summarize the estimated usual intake distributions for potassium and sodium, respectively, obtained by three measures of daily nutrient intake: 24-hour dietary recalls, 24-hour urinary excretion, and 24-hour urine excretion adjusted for rate of recovery. The relative error associated with the mean, median, and other quantiles of the distribution of potassium and sodium intakes are approximately at or below 7 and 12 percent, respectively, indicating that intake measured using 24-hour recalls resulted in relatively high accuracy. Potassium intake was estimated to be 20 percent higher by 24-hour dietary recall compared with unadjusted 24-hour urinary potassium excretion; adjusting the mean for 20 percent loss of potassium would result in a bias of –4 percent. A separate analysis of the NHANES 2014 data found no significant difference between mean intake

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4 Distribution tables are available by request from the National Academies of Sciences, Engineering, and Medicine’s Public Access Records Office. For more information, email PARO@nas.edu.

Suggested Citation:"3 Methodological Considerations." National Academies of Sciences, Engineering, and Medicine. 2019. Dietary Reference Intakes for Sodium and Potassium. Washington, DC: The National Academies Press. doi: 10.17226/25353.
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Image
FIGURE 3-1 Mean and quantiles of the estimated usual potassium intake or excretion distributions among 20- to 69-year-olds of both sexes (N = 779).
NOTES: The dark blue bars represent amounts of potassium excreted in 24-hour urine samples. The light blue bars represent excretion after correction for percent recovered. The red bars represent potassium intake measured using 24-hour dietary recalls. In all cases, usual intake estimates are adjusted for within-person variability using the National Cancer Institute method.
SOURCE: NHANES, 2014 (unpublished).
Image
FIGURE 3-2 Mean and quantiles of the estimated usual sodium intake or excretion distributions among 20- to 69-year-olds of both sexes (N = 779).
NOTES: The dark blue bars represent amounts of sodium excreted in 24-hour urine samples. The light blue bars represent excretion after correction for percent recovered. The red bars represent sodium intake measured using 24-hour dietary recalls. In all cases, usual intake estimates are adjusted for within-person variability using the National Cancer Institute method.
SOURCE: NHANES, 2014 (unpublished).
Suggested Citation:"3 Methodological Considerations." National Academies of Sciences, Engineering, and Medicine. 2019. Dietary Reference Intakes for Sodium and Potassium. Washington, DC: The National Academies Press. doi: 10.17226/25353.
×

of sodium estimated by 24-hour dietary recall and 24-hour urine excretion not adjusted for recovery (Cogswell et al., 2018). These analyses illustrate in a sample of nonpregnant adults representative of the U.S. population that it is appropriate to use 24-hour dietary recalls to describe the usual intake distributions of potassium and sodium for comparing established population intake levels, as prescribed in the third step of the DRI organizing framework.

Measurement error in potassium and sodium intake generally attenuates the diet–health relationship. This effect can be assessed as an attenuation factor (the slope of the regression of truth on self-report), which ranges from 0 to 1. Attenuation factors of at least 0.4 are preferred to distinguish a relationship from a null (Freedman et al., 2015). Attenuation factors for potassium and sodium are higher when more days of 24-hour dietary recall are collected. For potassium, the attenuation factors for 1, 2, and 3 days of 24-hour dietary recalls were estimated to be 0.30, 0.42, and 0.49, respectively, for males and 0.35, 0.47, and 0.51, respectively, for females (Freedman et al., 2015). For sodium, the attenuation factors for 1, 2, and 3 days of 24-hour dietary recalls were estimated to be 0.24, 0.30, and 0.33, respectively, for males and 0.14, 0.22, and 0.32, respectively, for females. Attenuation factors also increased after adjustment for energy (Freedman et al., 2015).

Although the true biological effect of a nutrient is generally attenuated in the presence of measurement error, the test of the null hypothesis of the relationship is usually valid. However, measurement error can also lead to loss of statistical power to detect the diet–health relationship compared to use of true intake. Correlation of a measure with truth can be used to describe the loss of statistical power, with the effective sample size being equal to the actual sample size times the squared correlation (Kaaks et al., 1995). Correlations in the range of 0.52 to 0.59 for two or three 24-hour dietary recalls for potassium, and 0.28 to 0.42 for sodium have been estimated (Freedman et al., 2015). Others have estimated positive correlations between dietary recall results and urinary potassium and sodium excretion (Crispim et al., 2011; Ferrari et al., 2009; Mercado et al., 2015). Correlations of this magnitude indicate that studies in the order of 2.1 to 12.7 times larger would be needed to detect the relationship found with an error-prone 24-hour dietary recall compared with true intake.

To obtain a measurement-error corrected estimate of the relationship between diet and health outcomes, an alternate approach is to use regression calibration to obtain the estimated true value of an individual’s usual intake, and then to use this estimate in the diet–health regression model (Rosner et al., 1989). For potassium and sodium, calibration equations can be estimated assuming that the 24-hour urinary biomarkers exhibit only random error, and allowing 24-hour dietary recalls to be calibrated to true

Suggested Citation:"3 Methodological Considerations." National Academies of Sciences, Engineering, and Medicine. 2019. Dietary Reference Intakes for Sodium and Potassium. Washington, DC: The National Academies Press. doi: 10.17226/25353.
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intakes (Freedman et al., 2015; Huang et al., 2014; Mossavar-Rahmani et al., 2017). Although this method will produce deattenuated estimates of diet–health relationships, it cannot restore loss of statistical power.

Although 24-hour dietary recalls are subject to bias for both potassium and sodium, differences in the recovery estimates for the amount of the nutrients excreted in urine vary across studies. This makes it difficult to precisely quantify the degree of bias in estimating the distributions of intakes using 24-hour recalls for potassium and sodium. However, the analysis presented in Figures 3-1 and 3-2 indicates that the estimates of the usual intake distributions measured using 24-hour recalls resulted in relatively high accuracy, which supports the use of recall estimates based on 24-hour dietary recalls for comparison with current population levels (third step of the DRI organizing framework). To assess diet–health relationships, the degree of attenuation expected using 24-hour recalls is large enough that measurement-error correction methods would be beneficial to obtain unbiased estimates of the association, and power would be diminished compared to true intake or the use of multiple 24-hour urine samples.

Food Record

Food records are detailed, respondent-provided descriptions of the types and amounts of foods, beverages, and supplements consumed over a specified period of time. Like 24-hour dietary recalls, food records can be used to obtain detailed information on dietary intake, and they can capture cultural and regional differences in dietary patterns across participants. Participant burden is high and may require both respondent and staff training to promote record quality and ensure appropriate coding of reported foods. Another limitation is underestimation resulting from intentional or unintentional unreported foods and beverages. Food records are infrequently used and studied compared with 24-hour dietary recalls and food frequency questionnaires, which may be attributable, in part, to respondent and investigator burden.

Compared with 24-hour urinary excretions in adults, food records have underestimated mean sodium intake by 2 to 8 percent and varied from mean potassium intake by –4 to +3 percent (Lassale et al., 2015). In an analysis using a comparison to 12-hour overnight urine, mean sodium was 25 percent lower and mean potassium was 28 percent higher on food records (Pereira et al., 2016). Intake estimates from food records were correlated with 24-hour urinary excretions in the range of 0.48 to 0.62 for potassium and 0.17 to 0.48 for sodium (Lassale et al., 2015; McKeown et al., 2001); compared to 12-hour urinary excretions, food record estimates had correlations of 0.30 for potassium and 0.19 for sodium (Pereira et al., 2016). Limited data on children suggest overestimation of potassium on

Suggested Citation:"3 Methodological Considerations." National Academies of Sciences, Engineering, and Medicine. 2019. Dietary Reference Intakes for Sodium and Potassium. Washington, DC: The National Academies Press. doi: 10.17226/25353.
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food records with moderate to strong correlations with urinary potassium excretion (r = 0.58 to 0.78) (Krupp et al., 2012; Lietz et al., 2002).

Food Frequency Questionnaire

Food frequency questionnaires contain a finite list of foods and beverages, or groups of foods and beverages, often paired with an indicator of serving size. Respondents report the frequency with which they consume the foods and beverages over a given reference period (e.g., per month, per year). Respondents may also be asked to estimate the portion size typically consumed. This method benefits from low respondent burden, it is typically self-administered, and it attempts to capture usual, long-term intake through a single assessment. Food frequency questionnaires have some notable limitations. Compared with 24-hour dietary recalls and food records, which capture specific days of intake, food frequency questionnaires ask users to estimate their usual intake over a long period of time, which can be challenging and can potentially lead to systematic bias, particularly for foods influenced by seasonal availability. The focus on broad food categories instead of specific food products is likely to be particularly problematic for sodium, given the wide variation in sodium content that has been observed in some products within food categories.

On average, potassium intakes are underestimated on food frequency questionnaires by 5 to 8 percent in adults, compared with 24-hour urinary biomarkers using a measurement error model (Freedman et al., 2015; Trijsburg et al., 2015). One study reported a 96 percent overestimate of potassium when food frequency questionnaire data were compared with 12-hour urinary excretion (Pereira et al., 2016). Correlation coefficients of potassium between food frequency questionnaires and urinary excretion in adults are low, ranging from 0.26 to 0.29 (McKeown et al., 2001; Pereira et al., 2016). In British schoolchildren 11–13 years of age, potassium was overestimated by more than 100 percent when food frequency questionnaire data were compared with 24-hour urinary excretion; the two measures were not significantly correlated (r = –0.04) (Lietz et al., 2002).

Sodium intake estimated from food frequency questionnaires compared with urinary measures is generally reported to be underestimated by 4–42 percent (Freedman et al., 2015; Kelly et al., 2015; Li et al., 2014; Pereira et al., 2016; Trijsburg et al., 2015), although overestimation has also been reported (Murakami et al., 2012). Bias in reporting has been associated with race, education, and gender (Freedman et al., 2015). Adjustment for energy intake may improve the underreporting bias in sodium intake (Freedman et al., 2015). Correlation coefficients tend to be low between food frequency questionnaire data and urinary sodium excretion, rang-

Suggested Citation:"3 Methodological Considerations." National Academies of Sciences, Engineering, and Medicine. 2019. Dietary Reference Intakes for Sodium and Potassium. Washington, DC: The National Academies Press. doi: 10.17226/25353.
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ing from negligible to 0.37 (McKeown et al., 2001; McLean et al., 2017; Pereira et al., 2016; Sasaki et al., 2003).

Studies assessing the reproducibility of food frequency questionnaires—whether via assessment of kappa coefficients, Pearson correlation, or intra-class correlation—have reported satisfactory reliability across multiple assessments (Barrett and Gibson, 2010; Collins et al., 2015; Ferreira-Sae et al., 2009; McKeown et al., 2001; Mirmiran et al., 2010; Shiraishi et al., 2017). A wide variety of food frequency questionnaires exist, and some are designed for a specific population or dietary pattern or to capture intake of certain nutrients (Apovian et al., 2010; Cheng et al., 2008; Collins et al., 2015; Hamdan et al., 2014).

Food frequency questionnaires are limited in their ability to estimate absolute intake (Carithers et al., 2009; Fayet et al., 2011; Lietz et al., 2002). The evidence suggests that 24-hour dietary recalls are more accurate than food frequency questionnaires for estimating the absolute intakes of both potassium and sodium intake (Ferrari et al., 2009; Freedman et al., 2015; Trijsburg et al., 2015), particularly when 24-hour dietary recalls are administered by phone interview compared with a self-administered Web-based platform (Trijsburg et al., 2015). A systematic review commissioned by the International Consortium for Quality Research on Dietary Sodium/Salt concluded that food frequency questionnaires should not be used to assess absolute sodium intake (McLean et al., 2017).

Implications for the Committee’s Review of the Evidence

The various methods for assessing potassium and sodium intake are limited in their comparability and accuracy. Evidence from individual studies examining the relationship between potassium and sodium—particularly absolute intakes—and health outcomes must be interpreted in context of the method used to estimate intake.

The most accurate method to measure usual sodium intake is multiple 24-hour urine collections that use quality control measures. Although a smaller proportion of consumed potassium is excreted in urine, multiple 24-hour urine collections appear to be an accurate measurement approach for assessing usual potassium intake. Self-reported dietary assessment methods, particularly multiple 24-hour recalls, may also provide reasonably accurate measurements of usual potassium intake. Adjustment for measurement error using statistical methods is important, particularly when estimating the distribution of usual sodium or potassium intakes or assessing diet–health relationships.

To operationalize these key methodological considerations, the committee used the approach taken in the Agency for Healthcare Research and Quality systematic review, Sodium and Potassium Intake: Effects on

Suggested Citation:"3 Methodological Considerations." National Academies of Sciences, Engineering, and Medicine. 2019. Dietary Reference Intakes for Sodium and Potassium. Washington, DC: The National Academies Press. doi: 10.17226/25353.
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Chronic Disease Outcomes and Risks (AHRQ Systematic Review), which embedded intake ascertainment as one of the domains in the risk-of-bias tool (Newberry et al., 2018). For both sodium and potassium, randomized controlled trials that collected at least one 24-hour urinary analysis with reported quality control measures were rated as having low risk of bias for the intake ascertainment domain.5 For potassium, observational studies that collected multiple days (more than 4, preferably nonconsecutive) of 24-hour urine samples with reported quality control measures or multiple (more than 4, nonconsecutive) 24-hour dietary recalls or food records were considered at low risk of bias for the intake ascertainment domain. For sodium, observational studies that collected multiple days (more than 4 on average, preferably nonconsecutive) of 24-hour urine samples with reported quality control measures were considered at low risk of bias for that domain. Other methods for assessing potassium and sodium intake had higher risk-of-bias ratings for this domain. Annex C-1 in Appendix C presents the full list of the risk-of-bias domains and criteria used in the AHRQ Systematic Review.

INTERACTIONS OF POTASSIUM AND SODIUM

Determinants of dietary intake are multidimensional, which refers to “the numerous attributes of dietary intake and the inherent complexities of interdependence and synergy” (Reedy et al., 2018). The multidimensionality of dietary intake can make for a tenuous determination of an association between a single nutrient and health outcome. Approaches to capturing, analyzing, and synthesizing data that characterize these complex interactions are relatively nascent, and efforts are under way to overcome these methodological challenges (Reedy et al., 2018). Nevertheless, the best data available must be used to interpret evidence of the relationship between individual nutrient intake and indicators of health and chronic disease.

One aspect of this complexity is the interactions of nutrients with other food components. Although studying individual nutrients provides fundamental information about underlying biological mechanisms, individual nutrients have complex relationships with other dietary constituents. With respect to deriving DRIs, there are four possible scenarios of interactions to consider:

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5 For potassium other methodologies rated as having low risk of bias for the intake ascertainment domain included “chemical analysis of diet or food diary with intervention/exposure adherence measure, or composition of potassium supplement with intervention/exposure adherence measure” (Newberry et al., 2018, p. E-4).

Suggested Citation:"3 Methodological Considerations." National Academies of Sciences, Engineering, and Medicine. 2019. Dietary Reference Intakes for Sodium and Potassium. Washington, DC: The National Academies Press. doi: 10.17226/25353.
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  1. Modulation of the nutrient’s effect by another nutrient;
  2. Competition of nutrients at the physiological level (i.e., absorption or transport);
  3. Substitutions and changes in other dietary components through modulating dietary intake of one nutrient; and
  4. Dependency of intake of one nutrient on energy intake (NASEM, 2017).

Consideration of these interactions has implications for the committee’s approach to each step of the DRI organizing framework. In the first step, metabolic interactions between nutrients may affect the nature of the relationship observed, and collinearity between nutrients may limit the ability to attribute a relationship to a single nutrient. Similar considerations relate to assessing the intake–response relationship. In the last two steps of the DRI organizing framework, risk can be characterized in context of the interactions and special considerations related to such relationships are explained. To inform its review of the evidence, the committee considered potassium and sodium’s interactions with each other, with other nutrients, and with energy intake.

Interactions with Each Other

Measures of potassium and sodium are affected by measurement error, and these are often correlated, which can have a profound effect on observational associations (Cook et al., 1998; Day et al., 2001; Espeland et al., 2001). Although a negative correlation in the diet may be anticipated because high potassium typically represents a good-quality diet and high sodium can reflect a poor-quality diet, the measures are usually positively correlated. This may be partially attributable to dependence on the reported kilocalories consumed or to the collection quality of urine specimens. Despite the positive correlation, the effect of including both nutrients in models for blood pressure or cardiovascular disease can strengthen the association (Cook et al., 1998, 2009). For example, including negatively correlated predictors with positive effect sizes, or positively correlated predictors with opposite effect sizes, can be beneficial in predictive models (Demler et al., 2013). Short-term measurements that include substantial measurement error, however, can distort the underlying relationship with an outcome in observational data (Espeland et al., 2001). Randomized trials specifically designed to intervene on one or both of these measures, however, may offer additional insight.

Some studies have reported that consumption of potassium-containing salts increase urinary sodium excretion and that blood pressure is more highly correlated with the sodium-to-potassium ratio than to intake of

Suggested Citation:"3 Methodological Considerations." National Academies of Sciences, Engineering, and Medicine. 2019. Dietary Reference Intakes for Sodium and Potassium. Washington, DC: The National Academies Press. doi: 10.17226/25353.
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either electrolyte alone (Khaw and Barrett-Connor, 1988). The Dietary Reference Intakes for Water, Potassium, Sodium, Chloride, and Sulfate (2005 DRI Report) discussed this evidence but concluded that the data were insufficient to establish a recommendation based on the sodium-to-potassium ratio (IOM, 2005).

There is continued interest in the relationship between the sodium-to-potassium ratio and health outcomes, and in the potential use of this ratio as a practical way to derive dietary advice (Chmielewski and Carmody, 2017; Filippini et al., 2017; Iwahori et al., 2017). The AHRQ Systematic Review included key questions that explored whether potassium modulates sodium’s relationships with health outcomes (see Chapter 1, Box 1-3). Two randomized controlled trials were identified that assessed whether potassium modified the effect of sodium on cardiovascular disease and total mortality. One study compared the effect of counseling to achieve a low-sodium, high-potassium diet to the effect of counseling to achieve a low-sodium diet (HPTRG, 1990). There was no added effect on blood pressure when the counseling included increased potassium intake versus sodium reduction alone. Another study examined the effects of potassium-enriched salt on cardiovascular disease mortality (Chang et al., 2006). The potassium-enriched salt was 49 percent sodium chloride, 49 percent potassium chloride, and 2 percent other additives. After 31 months, the group consuming the potassium-enriched salt had a significant reduction in cardiovascular disease mortality (age-adjusted hazard ratio = 0.59 [95% CI: 0.37, 0.95]). However, this was compared to usual intake and there was no sodium-reduction-only comparison group. In a 10–15-year posttrial follow-up to Trials of Hypertension Prevention I and II, a higher sodium-to-potassium ratio measured by 24-hour urine collections showed a stronger association with increased risk of cardiovascular disease than either sodium or potassium alone (Cook et al., 2009).

The majority of evidence identified in the AHRQ Systematic Review on potassium intake modulating the effect of sodium intake assessed blood pressure. Various types of interventions have been used to explore this question (e.g., increasing dietary potassium intake with foods or different potassium salt substitutes), under the assumption that the effect size of sodium-to-potassium ratio on blood pressure is stronger than that of sodium or potassium alone.

Five studies were identified that compared the effects of a low-sodium diet with and without potassium enrichment (Chalmers et al., 1986; Charlton et al., 2008; Grimm et al., 1988, 1990; HPTRG, 1990; Langford et al., 1991; Nowson and Morgan, 1988). The AHRQ Systematic Review concluded that, based on a low strength of evidence, there is no significant moderating effect of potassium intake on the effects of sodium intake on systolic or diastolic blood pressure. The random-effects meta-analysis showed an overall mean difference for systolic blood pressure of –0.56 mm Hg

Suggested Citation:"3 Methodological Considerations." National Academies of Sciences, Engineering, and Medicine. 2019. Dietary Reference Intakes for Sodium and Potassium. Washington, DC: The National Academies Press. doi: 10.17226/25353.
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[95% CI: –2.94, 1.81]. Changes in sodium-to-potassium ratios in these studies were achieved by changing the diet or by dietary counseling alone. Changing the diet to increase potassium intake requires changes that likely increase the consumption of nutrient-rich foods that will increase intakes of other nutrients while also possibly resulting in lower sodium intakes, thus contributing to an improvement in blood pressure. With these types of interventions, it is not possible to discern the independent contribution of the sodium-to-potassium ratio on changes in blood pressure, because multiple, often undefined, dietary changes (e.g., other food components, concomitant dietary compensations) are simultaneously occurring.

The AHRQ Systematic Review included 13 randomized controlled trials that explored the effect of potassium-containing salt substitutes (Barros et al., 2015; Charlton et al., 2008; CSSSCG, 2007; Geleijnse et al., 1994; Gilleran et al., 1996; Li et al., 2016; Little et al., 2004; Mu et al., 2009; Sarkkinen et al., 2011; Suppa et al., 1988; Zhao et al., 2014; Zhou et al., 2009, 2016). In these interventions, the sodium-to-potassium ratio was expected to decrease by replacing some of the regular salt (sodium chloride) with a potassium-containing salt substitute (such as potassium chloride or potassium citrate). From this body of evidence, the AHRQ Systematic Review concluded that there is a moderate strength of evidence that the use of potassium-containing salt substitutes lowers systolic blood pressure and diastolic blood pressure. The random-effects meta-analysis estimated a mean difference of −5.58 mm Hg ([95% CI: −7.08, −4.09], I2 = 74 percent) for systolic blood pressure and −2.88 mm Hg ([95% CI: −3.93, −1.83], I2 = 78 percent) for diastolic blood pressure. The committee has reservations about the interpretation of these results because the meta-analysis included studies that increased potassium intake with interventions that also increased magnesium and/or calcium intake (Charlton et al., 2008; CSSSCG, 2007; Geleijnse et al., 1994; Mu et al., 2009; Sarkkinen et al., 2011; Zhou et al., 2009, 2016), and these minerals might also affect blood pressure and confound the independent effect of potassium. One study of individuals with type 2 diabetes (Gilleran et al., 1996) and one study of individuals who were randomized to receive health education (Li et al., 2016) were also included in the meta-analysis. The implications of these particular designs in the results of the meta-analysis are unknown.

Studies exploring the modulating effects of potassium have been published since the release of the AHRQ Systematic Review. Some of these studies used salt substitutes that include magnesium and calcium (Hu et al., 2018; Yang et al., 2018) and therefore have the same limitations described above. One study allowed for the independent moderating effects of potassium to be evaluated. Janda et al. (2018) explored the effect of adding Kardisal (60 percent sodium chloride, 40 percent

Suggested Citation:"3 Methodological Considerations." National Academies of Sciences, Engineering, and Medicine. 2019. Dietary Reference Intakes for Sodium and Potassium. Washington, DC: The National Academies Press. doi: 10.17226/25353.
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potassium chloride) to the Dietary Approaches to Stop Hypertension (DASH) diet for 3 months in 60 adolescents with prehypertension.6 In the group consuming the potassium-containing salt substitute (n = 26), systolic blood pressure decreased significantly from 138 to 129 mm Hg, whereas diastolic blood pressure also decreased, but the reduction was not statistically significant. In the group consuming the DASH diet (n = 25) the systolic blood pressure decreased significantly from 135 to 132 mm Hg, and the diastolic blood pressure decreased significantly from 85 to 79 mm Hg.7 The authors concluded that the use of a low-sodium salt did not decrease blood pressure beyond the DASH diet alone. A systematic review and meta-analysis on the relationship between potassium intake and blood pressure reported that potassium supplementation had a stronger lowering effect on blood pressure in trials with a higher achieved sodium-to-potassium ratio (≥ 1) than in trials in which the achieved ratio was less than 1, but the authors noted uncertainties in the data (Filippini et al., 2017). One issue not addressed is whether a potassium supplement within the context of high habitual sodium intakes would have a significant effect on blood pressure.

Interactions with Other Nutrients and Energy

Potassium and sodium are each correlated with other dietary components. For example, an analysis of day-one 24-hour dietary recall data from NHANES 2005–2006 participants 2 years of age and older found energy to be strongly correlated with both potassium intake (r = 0.72) and sodium intake (r = 0.80) (USDA/ARS/FSRG, 2010). The relationship between sodium and energy intake has also been demonstrated in the intake distributions of the U.S. and Canadian populations. In both countries, males consumed more sodium than females; the greater sodium intake among males was largely attributed to higher energy intake, as intake of sodium per kilocalorie consumed did not significantly differ between the sexes.8 In the DASH-Sodium trial, a feeding trial that examined the effect of sodium intake on blood pressure, individuals were provided diets at low, intermediate, and high sodium levels based on their energy intake. An analysis of the trial data showed that the blood pressure response to sodium intake varied with energy intake (Murtaugh et al., 2018).

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6 The DASH diet is rich in potassium, magnesium, and calcium.

7 Different final diastolic blood pressure values for this group were reported in the publication. This value was drawn from the narrative text description of the results.

8 For additional information regarding sources of evidence for potassium and sodium intake distributions, see Appendix G.

Suggested Citation:"3 Methodological Considerations." National Academies of Sciences, Engineering, and Medicine. 2019. Dietary Reference Intakes for Sodium and Potassium. Washington, DC: The National Academies Press. doi: 10.17226/25353.
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Potassium intake is correlated with intake of other nutrients (Adebamowo et al., 2015; Hermann et al., 1992; Larsson et al., 2011). For instance, based on 24-hour dietary recalls collected at baseline and follow-up during a dietary intervention study, Nowson and Morgan (1988) reported that dietary potassium intake was strongly correlated with magnesium intake (r = 0.82). The AHRQ Systematic Review found insufficient evidence to assess the moderating effects of calcium or magnesium on the effects of potassium or sodium intake with any of the indicators reviewed (i.e., systolic and diastolic blood pressure, cardiovascular disease morbidity and mortality, and kidney disease). The AHRQ Systematic Review found no trials that met its inclusion criteria that assessed the modifying effects of calcium or magnesium on the effect of sodium on any of the indicators reviewed. Two trials assessed the modifying effects of calcium or magnesium on the effect of potassium on blood pressure. Rahimi et al. (2007) randomized participants into a control arm, a high-potassium diet, a high-calcium diet, or a high-potassium and high-calcium diet, and reported significant declines in systolic blood pressure for each of the intervention groups as compared to the control group. A crossover study of potassium plus magnesium supplementation did not reduce systolic or diastolic blood pressure more than potassium supplementation alone (Patki et al., 1990). With only these two trials, the AHRQ Systematic Review characterized the strength of evidence of a moderating effect as insufficient.

Implications for the Committee’s Review of the Evidence

The multidimensional and dynamic nature of dietary intake presents challenges in assessing the relationship between a single nutrient and a health outcome. Potassium and sodium are not consumed in isolation and intakes vary over time. Although there are approaches and methodologies that partly address some of these inherent issues, there are gaps in the evidence on sodium and potassium’s interactions with each other, their interactions with other food components, and their contributions to health.

Evidence on the modulating effect of potassium (or other minerals) on the blood pressure effects of sodium intake is insufficient at this time, as is the evidence that high sodium intakes might be mitigated by increasing potassium intakes (through food or supplements). Based on its synthesis of the evidence provided in the AHRQ Systematic Review, the committee did not derive DRI values based on the sodium-to-potassium ratio. The committee was concerned that establishing a DRI value as a sodium-to-potassium ratio might lead to the misimpression that altering the ratio with the use of a potassium supplement will result in a beneficial health outcome, on option that has not yet been explored. Furthermore, the committee excluded from consideration studies in which salt

Suggested Citation:"3 Methodological Considerations." National Academies of Sciences, Engineering, and Medicine. 2019. Dietary Reference Intakes for Sodium and Potassium. Washington, DC: The National Academies Press. doi: 10.17226/25353.
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substitutes included other minerals because there is insufficient evidence on if and how other minerals might modulate the effects of sodium or potassium.

Sodium and energy intakes are closely linked, and the sodium-to-energy ratio may be an informative measure (Murtaugh et al., 2018). Despite this relationship, most studies do not administer, report, or analyze intakes on an energy-adjusted basis. Given this limitation of the evidence, the committee deemed it not appropriate to adjust a large number of study results based on either assumed or group mean energy intakes. In addition, the consideration of populations with energy intakes greater than the estimated energy requirements would be a challenge, especially in light of the high prevalence of overweight and obesity in the North American populations. At present, only the macronutrients (which themselves contribute to energy intake) and fiber have DRI values indexed to energy intake (IOM, 2002/2005). The committee was concerned that not only is there insufficient evidence to establish a DRI value as a sodium-to-energy ratio, there are also potential public health ramifications for doing so.

To account for the complexities of dietary intake in the review of the evidence, the committee assessed how studies accounted for factors such as interactions and confounders in their design (e.g., participant inclusion/exclusion criteria, frequency and timing of intake assessment) and analyses (e.g., statistical adjustments, type of dietary exposure used).

EVIDENCE ON SUBPOPULATIONS

The DRI age, sex, and life-stage groups allow for the nutrient reference values to vary, as applicable. With the introduction of DRIs based on chronic disease, opportunity exists to further specify the applicable population group or groups. The AHRQ Systematic Review included subquestions to determine if characteristics such as sex, age, race/ethnicity, or comorbidity affected the relationship between sodium or potassium intake and chronic disease outcomes and risk. With the exception of hypertension status, there was largely insufficient evidence to determine if there was an effect modification.

One characteristic that played a substantial role in establishing the potassium AIs in the 2005 DRI Report was salt sensitivity. The AHRQ Systematic Review did not assess the evidence by salt sensitivity status. To that end, the committee considered the extent to which this characteristic could inform a DRI value.

Suggested Citation:"3 Methodological Considerations." National Academies of Sciences, Engineering, and Medicine. 2019. Dietary Reference Intakes for Sodium and Potassium. Washington, DC: The National Academies Press. doi: 10.17226/25353.
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Salt Sensitivity

Salt sensitivity is a continuous variable, and arbitrary criteria have been developed for diagnostic purposes.9 Salt sensitivity has been defined as

the extent of blood pressure change in response to a change in salt intake. The term “salt sensitive blood pressure” applies to those individuals or subgroups that experience the greatest change in blood pressure from a given change in salt intake. (IOM, 2005, p. 8)

Many phenotypic characteristics have been observed and used to explain salt sensitivity, including diminished urinary endothelin (which is negatively correlated with a salt load independent of blood pressure status), a deficit in nitric oxide (which increases in response to salt loading), impaired responses to a salt load by the sympathetic nervous system, differences in atrial natriuretic peptides (which increase in response to dietary salt supplementation), and hyperinsulinemia. Salt sensitivity has been identified as a potential risk factor for cardiovascular disease. Hence, this trait would have importance in public health advice and the clinical management of blood pressure (salt-sensitive versus salt-resistant individuals).

Characterizing salt sensitivity remains challenging. The existing criteria have varying ranges of high and low sodium intake levels, durations, and sequences of approach. There continues to be a lack of reproducibility of the acute blood pressure responses to sodium challenges that are indicative of salt sensitivity. For data to be comparable among studies, standard protocols need to be used consistently, and other challenges that impede the identification of salt-sensitive individuals must be addressed.

An alternative approach to identify salt-sensitive individuals is the identification of a valid biomarker. Twenty-four-hour pulse rates and nocturnal dipping of arterial blood pressure have been investigated as biomarkers of salt sensitivity. A promising yet insufficiently explored approach includes identifying urinary biomarkers related to proximal tubular cells or renal exomes that reflect salt sensitivity.10 No such biomarker has been identified to date.

Another innovative approach is to identify individuals with genetic variants associated with salt sensitivity. Several gene or gene products related to salt sensitivity have been identified in animals, including those that affect the RAAS, the sympathetic nervous system, the endothelin system,

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9 There are various definitions of salt sensitivity. Definitions include a change in blood pressure of 5–10 mm Hg in response to a change in salt intake, or an increase in mean arterial pressure of at least 4 mm Hg with an increase in salt intake.

10 Exomes are small vesicles that contain mRNA, proteins, and other cell components. The characteristics of those components might be associated with salt sensitivity.

Suggested Citation:"3 Methodological Considerations." National Academies of Sciences, Engineering, and Medicine. 2019. Dietary Reference Intakes for Sodium and Potassium. Washington, DC: The National Academies Press. doi: 10.17226/25353.
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natriuretic peptides, oxidative stress, angiogenesis factors, and inflammation. However, interpretation of animal studies and their implications for humans is complex. In humans, evidence of heritability of salt sensitivity comes from family studies. Although genomewide linkage studies have identified many variants related to blood pressure sensitivity, sample sizes are insufficient to identify significant genetic variants. A recent publication suggests a single nucleotide polymorphism as a promising biomarker (Zhang et al., 2018).

Implications for the Committee’s Review of the Evidence

Challenges in characterizing salt sensitivity limit its use for establishing potassium and sodium DRI values at this time. One consideration is the generalizability of the evidence. The DRI values have broad applications across different domains, and the importance and applicability of subgroup differences are considered when establishing DRI values. Depending on the evidence, effect modification may be central to selecting an indicator and establishing the DRI value (the first two steps of the DRI organizing framework) or may be most appropriately handled when characterizing special considerations and vulnerable population groups (fourth step of the DRI organizing framework). The Guiding Principles for Developing Dietary Reference Intakes Based on Chronic Disease (Guiding Principles Report) recommended, “extrapolation of intake–response data for chronic disease DRIs only to populations that are similar to studied populations in the underlying factors related to the chronic disease of interest” (NASEM, 2017, p. 214). As such, consideration of differential effects has even greater prominence in the DRI process. Throughout its evidence review, the committee notes where there is evidence of effect modification by a population characteristic.

SUMMARY

In preparation for its review of the evidence, the committee examined a range of methodological considerations that are central to evaluating and interpreting studies assessing the relationship between potassium and sodium intake and indicators. Box 3-1 provides a summary of the implications for the evidence that is reviewed in this report.

Suggested Citation:"3 Methodological Considerations." National Academies of Sciences, Engineering, and Medicine. 2019. Dietary Reference Intakes for Sodium and Potassium. Washington, DC: The National Academies Press. doi: 10.17226/25353.
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Suggested Citation:"3 Methodological Considerations." National Academies of Sciences, Engineering, and Medicine. 2019. Dietary Reference Intakes for Sodium and Potassium. Washington, DC: The National Academies Press. doi: 10.17226/25353.
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Suggested Citation:"3 Methodological Considerations." National Academies of Sciences, Engineering, and Medicine. 2019. Dietary Reference Intakes for Sodium and Potassium. Washington, DC: The National Academies Press. doi: 10.17226/25353.
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Dietary Reference Intakes for Sodium and Potassium Get This Book
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As essential nutrients, sodium and potassium contribute to the fundamentals of physiology and pathology of human health and disease. In clinical settings, these are two important blood electrolytes, are frequently measured and influence care decisions. Yet, blood electrolyte concentrations are usually not influenced by dietary intake, as kidney and hormone systems carefully regulate blood values.

Over the years, increasing evidence suggests that sodium and potassium intake patterns of children and adults influence long-term population health mostly through complex relationships among dietary intake, blood pressure and cardiovascular health. The public health importance of understanding these relationships, based upon the best available evidence and establishing recommendations to support the development of population clinical practice guidelines and medical care of patients is clear.

This report reviews evidence on the relationship between sodium and potassium intakes and indicators of adequacy, toxicity, and chronic disease. It updates the Dietary Reference Intakes (DRIs) using an expanded DRI model that includes consideration of chronic disease endpoints, and outlines research gaps to address the uncertainties identified in the process of deriving the reference values and evaluating public health implications.

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