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Nutritional Epidemiology

Urinary Potassium Is as Reliable as Urinary Nitrogen for Use as a Recovery Biomarker in Dietary Studies of Free Living Individuals¹

Nataa Tasevska, Shirley A. Runswick and Sheila A. Bingham²

Medical Research Council Dunn Human Nutrition Unit, Cambridge, CB2 2XY, UK

² To whom correspondence should be addressed. E-mail: sab{at}mrc-dunn.cam.ac.uk.

	ABSTRACT

TOP ABSTRACT MATERIALS AND METHODS RESULTS DISCUSSION LITERATURE CITED

 
Twenty-four-hour urinary nitrogen (UN) is commonly used to validate dietary assessment methods. Potassium is more widespread in food than nitrogen, but the role of 24-h urinary potassium (UK) as a biomarker has been less studied and characterized. To investigate the performance of UK as a recovery biomarker compared with UN in subjects consuming their normal diet, 7 males and 6 females consumed known amounts of food based on their habitual varying diet (assessed beforehand from 4 consecutive 7-d food diaries) for 30 d in a metabolic suite. All daily urine samples and dietary duplicates were collected, and N and K were measured. Stool K was determined in 5-d pooled samples. Thirty-day mean analyzed K intake was 121.3 ± 25.1 (mean ± SD) mmol/d. Overall, 77 ± 6.7% of K in the diet was excreted in urine and 18 ± 5% in stool. Dietary K was correlated with UK (r = 0.89; P < 0.001). UN was 77.7 ± 6.6% of N intake and was correlated with N in the diet (r = 0.87; P < 0.001). When 16 d of intake and 8 d of urine-collection measurements were randomly selected from the 30-d measurements, correlations were significant for both K (r = 0.86; P < 0.001) and N (r = 0.92; P < 0.001). The high correlations between UK and K in the diet show that UK is a reliable recovery biomarker for use in studies of dietary measurement error. Factors for use of urinary N as a recovery biomarker are also confirmed.

KEY WORDS: • dietary biomarkers • diet • urine potassium • stool potassium • urine nitrogen

Twenty-four hour urinary nitrogen (UN)³ is a well-known and well-established recovery biomarker for protein intake (1,2). In the United Kingdom diet, most of the protein consumed is derived from 3 main food groups (36% from meats and meat products, 23% from cereals and cereal products, and 16% from milk and milk products), which are also major energy contributors (3). Hence, the use of UN to adjust for nutrient intake other than protein and energy may be limiting, assuming there is a substantial difference in the level of misreporting different foods, thus, nutrients (4–7). Potassium is a nutrient present in a greater variety of foods than nitrogen. Different food groups contribute more or less equally to K intake (18% from potatoes, 17% from fruits and vegetables, 15% from meat and meat products, 15% from drinks, and 13% each from cereal and milk products). The use of 24-h urinary K (UK) as a biomarker would be a useful additional biomarker to UN.

Generally, in studies where both biomarkers have been used to examine the performance of various concurrent dietary assessment methods, similar estimates of the ability of each dietary method to measure both N and K intake were obtained (8–14). However, in a recent study by Freedman et al. (15) assessing the validity of the food frequency questionnaire and 24-h recalls against UN, doubly labeled water, and UK biomarkers, both dietary methods performed poorly in estimating usual protein and energy intake distributions, but performed well in estimating K intake, respectively. Freedman et al. (15) suggested that this might be due to much less underreporting of K-containing foods than energy and protein foods, or to the possibility that the proportion correction for K applied in the study (0.80) might not be valid, and, if too large, might have created a false impression that K intake was not underreported.

UK as a biomarker has been less well established than UN. Although studies investigating the association between dietary and UK reported very good agreement between the two (16–20), the percentage recovery of K in urine has been shown to be more variable among individuals (16,21) and among different studies (16,18–20,22). Furthermore, day-to-day within-subject variability in K excretion was found to be 2 times greater than for N (17,23), which would suggest that UK is a less reproducible biomarker, and therefore a longer validation protocol would be needed to overcome effects of variability. However, methodological limitations of these studies make it difficult for any definite conclusions to be made, because the completeness of the 24-h urine collections was not validated (16,18,20–22), self-reported dietary intake was used (19,20), or few dietary and/or urinary measurements were available (18,20). As has been suggested before, larger controlled feeding studies linking potassium intake to potassium excretion are needed to establish more clearly the extent of individual variation in the intake/excretion ratio and its dependence, if any, on the level of potassium intake and other factors (15).

In this study, we assessed the validity and reproducibility of UK as a recovery biomarker in subjects consuming their habitual diet in a strictly controlled environment. The characteristics of UK as a biomarker of intake were also compared with UN, which has been more extensively studied and is a well-established marker. The contribution of fecal K and its effect on individual variation in urinary recovery were also investigated. As the usefulness of biomarkers depends not only on the validity of the biomarker but also on the accuracy of food tables used to calculate the intakes from the dietary methods, both the calculated and the analyzed potassium intakes from duplicates of diets were assessed.

	MATERIALS AND METHODS

TOP ABSTRACT MATERIALS AND METHODS RESULTS DISCUSSION LITERATURE CITED

 
Subjects

A total of 13 healthy subjects (7 males and 6 females) aged 23–66 y (43.2 ± 15.9 y) from Cambridgeshire were recruited with local advertisements. They were of different social backgrounds and occupations. Prior to the study, all were examined by a medical practitioner. Upon entry to the study, all subjects gave their full informed written consent. The study was approved by the Cambridge Local Research Ethics Committee (LREC No. 02/323).

Diets

This was a 30-d study in which the subjects lived in the volunteer suite of the MRC Dunn Human Nutrition Unit while consuming their usual diet. To assess their usual diet, the subjects were asked to keep 7-d estimated food diaries for 4 wk while living at home. More detailed information, including brand names, was obtained at a weekly interview with one of the investigators. Data from the food diaries was then used to replicate the usual daily diets of each subject with their usual diet during the study period. From approximately two-and-a-half times the amount of food expected to be eaten by the subject, one-half was prepared and one-half was kept for the preparation of a duplicate meal. The prepared half was weighed to the nearest gram, labeled with the name and the day, and left in a separate refrigerator for each individual. During the day, subjects helped themselves and returned the uneaten food to the containers in the refrigerator. The next day, the uneaten food was weighed out and the amount of food eaten was calculated.

Dietary intake was calculated from the UK food-composition tables using DINER (Data Into Nutrients for Epidemiological Research) (24). Tea and coffee were consumed freely during the course of the study, but subjects were asked to keep their intake consistent and estimated intake was included in the data analysis. Five of the subjects occasionally consumed alcohol, which was not permitted in the volunteer suite. These subjects were allowed to consume alcohol outside the premises but the amount and type had to be recorded in their study diary. The calculated dietary intake for alcoholic drinks was also added into the consumption data obtained in the study.

On a daily basis during the study, for each subject, a replicate of the diet consumed the previous day was made from foods reserved for this purpose. All food and drink items (excluding coffee, tea, alcoholic drinks, water, added salt, and pepper) were weighed to the nearest 1 g, chopped up and crushed, mixed with a weighed amount of boiling deionized water, and homogenized with a Magimix 5100 automatic food processor, usually for 10–15 min, until a smooth emulsion was obtained. Aliquots of each duplicate (390 in total) were stored at –20°C for further analysis of K and N. Estimated K content of tea and coffee was added to the daily analyzed K intake.

Specimen collection, handling, and storage

Continuous urine and stool collections were made throughout the study.

    Urine collections. Upon beginning the study, subjects were instructed on the technique of 24-h urine collection. More details on the procedure for urine collection for this study have been reported elsewhere (25). The completeness of the 24-h urine was assessed by urinary recovery of three 80 mg tablets of para-aminobenzoic acid (PABA) (PABAcheck, Laboratories for Applied Biology) given to the subjects to take with their meals (26). Urine collections, with >85% recovery of the oral dose of PABA at the beginning of the collection period and >90% on succeeding days of the collection, were considered complete and kept for further analyses. When there was confusion over 2 succeeding 24-h collections (e.g., low marker recovery on one day followed by a high marker recovery the next day), the average of the 2 collections was used in the statistical analysis. Subjects recorded the time of taking PABA tablets or any missed urine collection in a diary, together with taking any medication.

    Stool collection. Subjects collected all the fecal samples produced during their 30-d stay. Upon entering the study, they were instructed on the collection procedure and were given a frame for the toilet seat to which plastic bags were attached for collecting the stool. After collection, the plastic bag was sealed immediately, labeled, and stored at –20°C.

To ensure completeness of the fecal samples, all subjects received 30 radio-opaque markers daily to take with meals (27). The completeness of the stool was assessed by the percentage of marker recovery. Those with >95% recovery were considered complete. Mean transit time (the mean time markers take to pass through the system) was calculated from the number of recovered markers in each stool and time of the stool sample collection (27,28).

Physical activity and body weight assessment

Physical activity was recorded in the study diary, on a daily basis, as the amount of time (min) engaged in different types of exercise. A 4-level score (inactive, moderately inactive, moderately active, and active) was assigned by combining occupational physical activity with time participating in higher-intensity physical activities such as cycling, aerobics, exercising at a gym on a regular basis, swimming, jogging, etc. (29). Subjects weighed themselves daily on an electric balance without shoes and in light clothing and recorded their body weight in the study diary.

Analytical methods

PABA concentration in urine was measured by a colorimetric technique described elsewhere (26).

UK was determined using an IL 943 flame photometer (Instrumentation Laboratory). Calibrators and internal standards were included in every run. Only runs in which the internal standard was within the required range were accepted.

The method for measuring K in the diet and in the fecal samples was based on the method reported by Cummings et al. (30). Homogenized diet was freeze dried, ground into powder, and well mixed. Three-hundred mg of the powder was then digested in 8 mL of 2 mol/L nitric acid for 1 h. Stool samples were weighed, allowed to thaw, and homogenized while still cold. The samples were diluted 1:6 with ultra-pure (MilliQ) water and thoroughly mixed on a Stomacher 3500 for 30 min. Aliquots of 6 mL of homogenates were prepared, using a 15-mL falcon tube, and 3 mL of 2 mol/L nitric acid were added. The mixtures were digested by inverting the tubes every 15 min for at least 1 h. Thereafter, the digestion products of both diet and fecal samples were processed in the same way. The digestion product was centrifuged at 3400 x g for 10 min. Aliquots of 1.5 mL supernatant were microfuged at 14000 x g for 5 min. Then, 200 µL of the supernatant solution was pipetted into a sample cup and analyzed on the flame photometer. Results from the stool samples of 5 consecutive days were pooled together and expressed as units per day.

To ensure consistency of the results, a stool quality-control (QC) procedure was included in every run. Interassay and intraassay CV for the QC was 1.3 and 0.5%, respectively. Interassay and intraassay CV for the diet QC was 1.2 and 1.0%, respectively.

Urinary and diet N were measured by the Kjeldahl technique, using a Tecator Kjeltec 1035 analyzer (Foss). Urine and diet QCs were prepared from a single source and included in every run. Interassay and intraassay CV were 3.1 and 1.4% for the urine QC and 1.3 and 1.3% for the diet QC, respectively.

Statistical methods

SPSS Version 11 for Windows was used for data analysis. Values are presented as means ± SD. Differences were considered significant at P < 0.05. Individuals' body weights at the beginning and at the end of the studies were compared by paired t test. To compare body weight between men and women, an independent t test was used. In this small group, there was no significant difference in K intake between men and women (P = 0.22) nor in N intake (P = 0.314), hence means are presented for the group as a whole. A paired t test was used to compare levels of calculated and analyzed intakes for both K and N.

Daily measurements of urinary and dietary N and K were skewed, hence they were log_e transformed. Individuals' means of analyzed and calculated K and N intake and UK were also skewed, and log₁₀ transformation was applied on the first 4 variables, and log_e transformation on the latter, to normalize the data. Individuals' means of stool K were normalized using inverse transformation, whereas means of urinary N were normally distributed. Randomization was done for each subject by randomly selecting 16 d of the 30 d of diet, and then randomizing 8 d of the 16 d of urine. The same types of transformations were applied to the corresponding means of the randomized measurements.

Reproducibility of intake and excretion measures was assessed by the within-subject variability and the intraclass correlation coefficient. The ratio of within- to between-subject variance (²_WS/²_BS) was used to assess the ability to characterize individuals with regard to their intake and excretion measures and to assess the attenuation effect of variability on the association between intake and excretion or to any other variable. An ANOVA random effect model was employed to quantify within- and between-subject variance components in K and N excretion and intake to calculate ²_WS/²_BS. Intraclass correlation coefficient was calculated as the ratio of between-subject variance and the sum of within- and between-subject variance [²_BS/(²_BS + ²_WS)]. To compare variability estimates to other studies, the coefficient of variation (% CV; SD/Mean x 100) was also used to estimate within- and between-subject variability in intake and excretion.

The Pearson correlation coefficient was used to examine the association between dietary and urinary measurements and among other variables. A multiple regression model, adjusted for sex, was fitted with subjects' mean of analyzed K intake as a dependent, and the mean of K in the urine as an independent, variable. No effect of age, physical activity, or body weight was detected; thus, these were not included in the analysis. Another multivariate regression model with stool K as an independent variable was fitted to investigate its contribution toward explaining the variance of intake alongside UK. A linear regression model was also fitted, using the individuals' mean of analyzed N intake as the dependent variable and the mean N in the urine as the independent variable. No effect of sex, age, body weight, or physical activity was detected; thus, they were not included in the analyses.

	RESULTS

TOP ABSTRACT MATERIALS AND METHODS RESULTS DISCUSSION LITERATURE CITED

 
Study compliance

    PABA recovery. A total of 390 daily urine samples were collected, 30 for each subject. Only 4 urine collections had unacceptable PABA recovery and were excluded from the analysis. One collection was incomplete, 2 were excluded due to spillage, and 1 was excluded because the subject failed to take the daily PABA dose.

    Marker recovery and transit time. Of the 900 markers given, per subject during 30 d, the count of the recovered markers ranged from 872 to 897. The mean recovery for the group was 98 ± 0.9%, indicating high compliance in terms of stool collections. The mean transit time for the group during the last 5 d of the study, when the stool was collected to be analyzed for K, was 49 ± 19 h, ranging from 32.2 to 100.7 h.

Subjects

All 13 subjects completed the study and remained healthy throughout. There was a change of body weight of 1 kg in 7 of the subjects during the course of the study: 4 gained weight, 2 lost weight, and weight fluctuated in 1 of the subjects. However, the mean body weight did not change in the group as a whole, with 76.2 ± 15.1 kg at the start and 76.3 ± 15.0 kg at the end of the study (P = 0.533). There was no difference in body weight between men and women (P = 0.185).

During the study, subjects pursued their normal occupational and recreational engagements. Two of the subjects were physically inactive, 3 moderately inactive, 3 moderately inactive to moderately active, and 5 moderately active to active. The most practiced physical activities were cycling, swimming, exercising at the gym, badminton, and squash.

Fiber intake (as nonstarch polysaccharides) was 24.2 ± 8.0 g/d, ranging from 11.3 to 36.2 g/d (Table 1). The energy and other macronutrient intakes of this group, while consuming their usual diet, have been reported elsewhere (25).

Subjects' 30-d mean K intake, calculated using the food tables, was very similar to the K analyzed in the duplicate diets (P = 0.73) (Table 1) with a correlation of 0.98 (P < 0.001). Day-to-day within-subject variability in analyzed K intake was 18.4% with a variance ratio of 1 (Table 2). Overall, 77 ± 6.7% (95% CI = 72.8–81.0%) of analyzed K intake was excreted in the urine (range 63–88%) (Table 1). There was a high day-to-day variability in K excretion in the group (mean CV_WS = 19.0%). The variability of K output between subjects was similar to the within-subject variability generating a variance ratio of 1 (see Table 2).

View larger version (10K): [in this window] [in a new window]   FIGURE 1  Regression and 95% CI of the means of analyzed potassium intake and urinary excretion in 13 subjects consuming a 30-d habitual diet. Means of 30-d dietary and urinary potassium measurements (A); means of randomly selected 16-d dietary and 8-d urinary potassium measurements (B).

In the regression model, after controlling for sex, stool K accounted for a further 20% of the variance in K intake, but still did not make the model significant (adjusted R² = 0.25; P = 0.09). Adding UK into the model explained the greatest proportion of the variance, identifying UK as the main predictor of K intake (adjusted R² = 0.85; P < 0.001).

Nitrogen

Subjects' mean N intakes calculated from food tables were not different from the analytical values (P = 0.26), with a correlation of 0.86 (P < 0.001) between the two. Daily analyzed and calculated values were also correlated in all subjects, but less significantly, when compared with the correlation of their 30-d means (Table 3). Day-to-day variation of analyzed N intake was 25.0% (CV_ws) and was higher than the between-subjects variation (Table 2).

The mean of the subjects' correlation coefficients between daily urinary N and dietary N was only 0.4, due to the high variability of daily intake (Table 3). However, the correlation of the subjects' 30-d means of N output was significant with both the analyzed (r = 0.87; P < 0.001) (Fig. 2A) and calculated N intake (r = 0.86; P < 0.001). In the linear regression model, UN output explained 74% of the variability in N intake (adjusted R² = 0.74; P < 0.001). No effect of age, sex, body weight, or physical activity was found; thus they were not included in the analyses.

View larger version (10K): [in this window] [in a new window]   FIGURE 2  Regression and 95% CI of the means of analyzed nitrogen intake and urinary excretion in 13 subjects consuming a 30-d habitual diet. Means of 30-d dietary and urinary nitrogen measurements (A); means of randomly selected 16-d dietary and 8-d urinary nitrogen measurements (B).

In studies using the UN and UK markers to validate dietary assessments, the recommended number of 24-h urine samples collected from each subject is 8 for comparison with dietary information about usual diet obtained from diet history methods, or 16 d of dietary records (1,14). Therefore, 16 d of intake data and 8 d of corresponding urinary measurements of N and K were randomly selected for each subject. The intention was to see how well estimates from the number of daily observations usually used in practice agreed with estimates from 30-d observations.

The correlation between K intake and excretion was almost as high as that obtained in the 30-d sample (r = 0.86; P < 0.001) (Fig. 1B). Similarly, calculated intake, as estimated from the 16 daily measurements, correlated well with excretion (r = 0.83, P < 0.001) and, also, with the analyzed intakes (r = 0.94, P < 0.001). Furthermore, the size and between-subject variability in percentage of K recovery in urine remained similar (78.5 ± 7.3%). In the multiple regression model controlled for sex, age, and physical activity, UK accounted for a similar proportion of the variance in K intake to the model of the nonrandomized sample (adjusted R² = 0.80; P = 0.001).

The correlation between analyzed intake and output of N was of the similar range as in the nonrandomized sample (r = 0.92, P < 0.001) (Fig. 2B). Calculated intake, as estimated from the 16 daily measurements, correlated well with excretion (r = 0.84, P < 0.001) and, also, with the analyzed intakes (r = 0.82, P < 0.001). A similar percentage recovery in urine was estimated (78.1 ± 6.0%), using the means of these fewer measurements. Linear regression gave similar estimates of predictability of analyzed diet N to UN (adjusted R² = 0.83; P < 0.001).

	DISCUSSION

TOP ABSTRACT MATERIALS AND METHODS RESULTS DISCUSSION LITERATURE CITED

 
In this study of subjects consuming their habitual diet in a strictly controlled environment, where all intake was measured for 30 d, the mean K intake was 121.3 mmol/d and was comparable to the amount of K intake measured in studies of a similar design (17). The mean intake of K and of dietary fiber was somewhat higher than in a dietary and nutrition survey of a representative sample of British adults that used 7-d weighed food records to assess the intake (3). The mean daily intake of K was 3.34 g/d (85.4 mmol/d) in males and 2.66 g/d (68.0 mmol/d) in females, whereas fiber intake was 15.2 g/d in males and 12.6 g in females. However, a doubly labeled water validation substudy, carried out to assess the validity of the dietary method used in the survey, indicated a certain level of underreporting. The fact that no weight was lost or gained, on average, over the study period of 1 mo, suggested that the intake achieved in our study was a valid reflection of usual dietary habits in these volunteers. No significant differences in intake were shown between men and women, but the study size was not designed to investigate population differences. There was no difference in body weight between men and women, therefore no difference in energy intake would have been expected.

The percentage of N recovery observed here was comparable to the estimate reported by Bingham and Cummings (1) of 81 ± 5% for a similar study design and metaanalyses of 5 studies that estimated individual ratios should fall between 70 and 90%, with a mean ratio of 83.5% (31). The percentage of K recovery in urine was similar to that reported in other studies that collected at least 7 urinary and dietary measurements (16,17,19,21). In this group of subjects, the within-subject variability in K intake of 18.4% was lower than the 35–40% reported elsewhere from a variety of sources (32,33). Others report a higher within-subject than between-subject variability in K intake (33–35), whereas Hunt et al. (36) reported a ²_WS/²_BS ratio of a similar magnitude as in our study: 0.9 for men and 1.2 for women. In the present study, the intake was analyzed and strictly controlled, making our estimates more reliable than studies where intake was assessed by different dietary methods.

UK was found to have similar variability estimates to the analyzed K intake. In a study of a similar design, the within- and between-subject variations were comparable to our study (17); whereas, in studies where fewer urinary collections were available, poorer reproducibility (37) and higher variance ratios were reported (38,39). For UN, variability components and ratios of a similar magnitude were reported in a N balance study (CV_WS = 13%; CV_BS = 21%) (1). The variance ratio for UK was less favorable than for UN (K, ²_WS/²_BS = 1.0 vs. N, ²_WS/²_BS = 0.7), which means that more urine collections would be needed to distinguish between individuals with different urinary excretion of K than would be needed for N.

Nevertheless, despite this variability, the means of urinary and dietary K and N did not change when only 8-d urinary and 16-d dietary measurements were randomized from the 30-d data. The correlations of r = 0.89 and 0.86 for UK and r = 0.87 and 0.92 for UN were >0.6 required for validation studies assessing measurement error (40) but would be attenuated with fewer days of measurements to as low as 0.11 for a single collection (Table 1).

We also investigated the contribution of fecal K excretion in K balance and its possible effect on individual variation in urinary recovery and found that fecal K was 18 ± 5% of intake, and was related to fiber intake, as shown elsewhere (30). Fecal K increases in response to increased fiber intake due to colonic bacterial proliferation, so that greater losses of K in the fecal output, to up to 30%, might occur in nonwestern populations with high fiber intake (19,41). However in this western population, fecal K was not a significant predictor of K intake, despite the 3-fold range in fiber intake from 11.3 to 36.2 g/d.

In conclusion, these 2 biomarkers are comparable in their performances as biomarkers of intake and cover different food groups. When both are measured in 24-h urine collections, they will offer a more comprehensive basis for comparison with dietary intake estimates in validation studies.

	ACKNOWLEDGMENTS

 
We thank Katharina Nimptsch and Rachna Kumar for helping with the analysis of N in urine, Graham Roberts for analyzing K in the diets, and Alison McTaggart and the EPIC team for the support in processing dietary data on the DINER software. We also thank Judith Wills and Valerie Church at the MRC Dunn Human Nutrition Unit for preparing the study diets and taking care of the volunteers.

	FOOTNOTES

 
¹ Supported by grants from the World Cancer Research Fund and U.K. Medical Research Council.

³ Abbrevations used: PABA, para-aminobenzoic acid; QC, quality control; UK, urinary potassium; UN, urinary nitrogen.

Manuscript received 28 September 2005. Initial review completed 6 November 2005. Revision accepted 6 February 2006.

	LITERATURE CITED

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