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© 2006 American Society for Nutrition J. Nutr. 136:1203-1208, May 2006

Nutrient Physiology, Metabolism, and Nutrient-Nutrient Interactions

Anthropometrics Provide a Better Estimate of Urinary Organic Acid Anion Excretion than a Dietary Mineral Intake-Based Estimate in Children, Adolescents, and Young Adults1

Shoma Berkemeyer2 and Thomas Remer

Research Institute of Child Nutrition, Dortmund, Germany

2 To whom correspondence should be addressed. Email: berkemeyer{at}fke-do.de.


   ABSTRACT
TOP
 ABSTRACT
SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 LITERATURE CITED
 
The role of elevated net endogenous acid production (NEAP) in the causation of osteoporosis, muscle wasting, and kidney stones is currently under discussion. The aim of this study was to examine whether urinary organic acid anion excretion, a major component of NEAP, is predicted primarily by anthropometric- (OAanthro) or diet- (OAdiet) based estimates. Dietary intakes, anthropometric data, and 24-h urinary excretion rates of organic acids (24h-OAurine) were determined cross sectionally in healthy children (6–7 y; n = 217), adolescents (13–14 y; n = 91), and young adults (18–22 y; n = 82). OAanthro was computed from body surface area and OAdiet calculated using a published algorithm based on dietary intakes of mineral anions and cations. There was a significant increase (P < 0.0001) in 24h-OAurine across the age groups that was no longer discernible after correction for body surface area. In almost all sex-stratified subsamples, OAanthro had a higher correlation with 24h-OAurine than OAdiet. Multiple regression analyses, using energy-corrected diet variables, revealed that OAanthro was consistently the primary predictor of 24h-OAurine (R2 varying from 0.15 to 0.39) and dietary fat and protein were sporadic predictors. In accordance with the observed age independency of 24h-OAurine after body surface area correction, our findings indicate that OAanthro is a better estimate of 24h-OAurine in healthy children, adolescents, and young adults than OAdiet. This further confirms that the (principally diet-dependent) NEAP comprises a component, i.e., organic acid anions, that is reasonably predictable by anthropometrics. Consequently, the other component, i.e., the potential renal acid load, appears to be the primary parameter that characterizes the diet-induced acid load.

KEY WORDS: • organic acid estimates • dietary potential renal acid load • 24-hour urine • healthy subjects • acid-base

Organic acid anions are important because they are a component of the body's total acid load (1). Acid-base homeostasis is crucial to health, and imbalances in that homeostasis have been linked to disturbances in bone health, muscle wasting, and nephrolithiasis (2–7). Consequently, methodological estimations of acid load and organic acid anions have direct implications. However, although acid-base studies are researched extensively (5–9), organic acid anions have not received as much attention.

Organic acid anions, which can be analyzed as a total fraction in urine samples by a titration method (1,10–12), comprise a wide spectrum of single analytes including citric acid, oxalic acid, malic acid, succinic acid, and lactic acid as well as the anionic amino acids, glutamic and aspartic acid. The amounts of these organic acid anions in 24-h urine samples (24h-OAurine)3 are thus important contributors to total acid excretion, measurable as net acid excretion (NAE). Because NAE and 24h-OAurine measurements in urine samples are very time-consuming, these urinary fractions are more often estimated. For organic acid anions, 2 estimates are currently in use, a diet-based estimate (OAdiet) (13) and an anthropometrics-based estimate (OAanthro) (14). Either of the 2 estimates is required for a final estimation of net endogenous acid production (NEAP) (9,12,15,16) which, as mentioned above, can be quantified analytically as NAE (11).

NEAP is composed of a nonorganic acid and an organic acid fraction, with the latter estimated either from anthropometrics (OAanthro) or diet (OAdiet). The OAdiet estimate was first provided by Kleinman and Lemann (13) as a function of the dietary unmeasured anions, which is a summation of dietary anionic and cationic minerals, excluding sulfur, and without considering mineral absorption. However, the dietary unmeasured anions are used not only to estimate the organic acid fraction of NEAP, but are also required to calculate the nonorganic acid fraction, whereby mineral absorption coefficients are taken into account. There is consensus in the literature about using absorbed dietary unmeasured anions for the nonorganic acid fraction. Remer and Manz (15) refer to it as potential renal acid load (PRAL) and Sebastian et al. (16) refer to it as "potential bicarbonate + potential sulfuric acid."

What is under debate is the reuse of the dietary unmeasured anions (absorption coefficients not included) to estimate the organic NEAP component, i.e., 24h-OAurine (17,18). Instead of using the dietary unmeasured anions components twice for NEAP calculations, Remer et al. (11,12,15) estimated the organic acid fraction from body surface area. Although the initial publication of Kleinman and Lemann (13) found no association between anthropometrics (specifically body weight) and 24h-OAurine, other studies (11,12,14,19) found organic acids to be reasonably estimated by body surface area. The present study examines these seemingly inconsistent results in calculating OAdiet and OAanthro in the same subjects in different age groups, along with measuring the subject's actual 24h-OAurine to determine whether both estimates function as reliable and consistent 24h-OAurine predictors. Different age groups were examined because growth could interfere with the organic acid estimates.


   SUBJECTS AND METHODS
TOP
 ABSTRACT
 SUBJECTS AND METHODS
RESULTS
 DISCUSSION
 LITERATURE CITED
 
    Subjects. Study subjects were healthy participants in the ongoing Dortmund Nutritional and Anthropometric Longitudinally Designed (DONALD) study (20). DONALD is an open cohort study collecting data on anthropometric measurements, 3-d weighed dietary records, and 24-h urine collections. The participants were trained by both oral and written instructions on how to collect 24-h urine samples and the 3-d weighed dietary records. In addition, they were provided with weighing scales to measure the food quantities. At a later date, a dietician visited the participants at home to collect their 24-h urine samples, 3-d weighed dietary records, and the weighing scales; the dietician conducted an oral and visual check of data provided and discussed compliance with the participants and/or their caregivers. From the DONALD cohort, 3 age groups, 6–7 y (n = 233), 13–14 y (n = 123), and 18–22 y (n = 112), were selected to cover different developmental stages. All subjects of appropriate age whose 24-h urine was collected in parallel to the dietary food record were initially eligible for the study. The dietary record began 2 d before the 24-h urine collection, so that the third and final day of the dietary record corresponded to the urine collection day. The calculated daily intakes of each day of the 3-d records were then averaged to obtain the mean daily intakes before and at the time of the 24-h urine collection. Subjects with implausible dietary records, eight 6–7 y olds, and 27 each from the 13- to 14- and 18- to 22-y-old groups, were excluded from analysis, using the ratio of individual energy intake divided by individual basal metabolic rate, latter calculated according to Schofield et al. (21), and comparing this ratio with published cut-offs (22,23). Subjects with urine samples having a daily creatinine excretion of <0.1 mmol/(kg·d), eight 6- to7-y olds, five 13- to 14-y olds, and three 18- to 22-y olds, were also excluded from the study to minimize errors in 24-h urine collection (24). Thus, the final sample sizes of the present study were 217 (104 males and 113 females) for the 6- to 7-y olds, 91 (53 males and 38 females) for the 13- to 14-y olds, and 82 (34 males and 48 females) for the 18- to 22-y olds. All examinations and assessments were performed with parental and children's consent. The study was approved by the institutional review board of the Research Institute for Child Nutrition Dortmund.

    Dietary intakes and diet-derived parameters. Dietary intakes of energy, calcium, potassium, magnesium, phosphorus, and the macronutrients were calculated as mean values of the 3-d weighed dietary records from the institute's own nutrient database LEBTAB (25). OAdiet (mEq/d) was calculated from the original equation of Kleinman and Lemann [32.9 + (0.15·dietary unmeasured anions)] (13), which does not consider absorption coefficients of the minerals included in the dietary unmeasured anion term. Dietary unmeasured anions (mEq/d) alone were calculated from the formula [({Sigma} Na+ + K+ + Ca2+ + Mg2+) – ({Sigma} Cl– + 1.8 PO4)] (13). This formula for organic acids does not take sulfate into account because sulfate is a primary component of the other nonorganic fraction of the diet-dependent NEAP, i.e., PRAL (11,12,15) or "potential bicarbonate + potential sulfuric acid" (16), for which absorption coefficients are considered.

In experimental diet studies with a manageable number of foods, the sodium and chloride can be estimated reasonably. In the present study, characterized by free-living subjects with a huge variety of food consumption, along with the intake of numerous processed foods, realistic data on true sodium and chloride intakes are difficult to obtain. The food tables referred to by LEBTAB either do not have chloride data consistently or the reported data for processed (salted) foods deviate frequently and unrealistically (± 10%) from their expected approximate 1:1 molar sodium to chloride ratio (by more than ± 10%). This limitation was overcome, in that sodium and chloride were assumed to be equal on a molar basis, which was proven appropriate in recent estimations of dietary acid loads (12) and was further corroborated by the present study's finding of a mean urinary sodium:chloride ratio of 1.02 ± 0.16.

    Anthropometry and anthropometrics derived parameters. Standing height was measured using a digital telescopic wall-mounted stadiometer (Harpenden) to the nearest 0.1 cm and weight on an electronic scale (Seca 753E; Seca Weighing and Measuring System) to the nearest 0.1 kg. From these measurements, body surface area was calculated according to the formula of Du Bois and Du Bois as follows (26): body surface area (m2) = [0.007184·height (cm)0.725·weight (kg)0.425]. OAanthro was calculated as [(body surface area··41)/1.73] where 41 is the median daily organic acid anions excretion (mEq/d) at an average body surface area of 1.73 m2 for healthy subjects (14). BMI was calculated from weight/height2 (kg/m2).

    Laboratory procedures. The 24-h urine samples were analyzed for organic acids, creatinine, sodium, and chloride. Organic acid anions were measured according to the established (1,11–13,27,28) Van Slyke and Palmer titration method (10) and creatinine according to the kinetic Jaffé procedure (29) using the Beckman-2 creatinine analyzer (Beckman Instruments). Sodium was measured by atom absorption flame spectrometry (Perkin Elmer) and chloride by ion-exchange chromatography (Dionex). The 24h-OAurine was obtained by multiplying the analyzed concentration value of organic acid anions by the respective 24-h urine volume.

    Statistical analysis. All statistical analyses were carried out with SAS® procedures (Version 8.2, Statistical Analysis System) with data presentation as means ± SD. For a gross characterization of the study sample (Table 1), the influence of age and sex were tested using 2-way ANOVA (without interaction terms) to obtain the main effects. No further post hoc comparisons of subgroups were performed. For an appropriate analysis for the outcome variable, 24h-OAurine, a preliminary covariance analysis was run to determine whether there were any significant predictor variable x sex interactions. Due to significant interactions in most cases (P < 0.05), all subsequent Pearson's correlations and multiple stepwise regression analyses were run with stratification by sex. For the regression analysis, dietary protein, fat, and carbohydrates, and the diet estimate, OAdiet, were corrected for total energy intake by division of the individual dietary value by the individual energy intake (30,31).


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  		TABLE 1 Baseline characteristics including anthropometrics, dietary intakes, 24-h urinary organic acid excretion and its estimates in children, adolescents, and adults1

 

   RESULTS
TOP
 ABSTRACT
 SUBJECTS AND METHODS
 RESULTS
DISCUSSION
 LITERATURE CITED
 
The anthropometric, dietary, and urinary data of the 3 age groups is presented in Table 1. All variables increased significantly with age (main effects: P < 0.0001). An exception to this was 24h-OAurine after body surface area correction (P = 0.29 for the factor age). OAanthro and OAdiet estimated absolute daily renal organic acid excretion (mean values) in the range of 21.1 to 45.7 and 40.1 to 46.0 mmol/d, respectively, whereas the analyzed 24h-OAurine ranged from 22.5 to 54.4 mmol/d for the total sample.

In the 6 subgroups, OAanthro usually correlated higher (r = 0.39–0.63, P < 0.01–P < 0.0001), with 24h-OAurine compared with OAdiet (r = 0.13–0.48, P = 0.47–P < 0.01) (Table 2). The 24h-OAurine and energy intake did not correlate significantly in the 6- to 7-y olds females (P = 0.15) and in the 18- to 22-y-old males (P = 0.17). This association was highly significant in only 1 case (13- to 14-y-old males). In contrast, OAdiet and energy intake were significantly correlated in all cases (highly significant in 4 of 6 cases) (Table 2). The high correlations between energy intake and the diet-derived parameters (dietary protein, fat, and carbohydrates, and OAdiet) required these variables to be energy corrected before they were entered into the regression analysis as predictors of 24h-OAurine. In all cases, OAanthro was highly correlated with the anthropometric parameter BMI, whereas 24h-OAurine was significantly correlated with BMI in 5 cases and the OAdiet in only 3 cases.


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  		TABLE 2 Cross correlations for 24-h organic acid anion excretion (24h-OAurine), its anthropometric (OAanthro) and diet (OAdiet) estimates, and energy and nutrient intakes in children, adolescents, and adults

 
In support of the correlation results in the regression analysis (Table 3), OAanthro was a consistently significant predictor of 24h-OAurine in all the sex-stratified groups (mainly P < 0.0001), whereas the other anthropometric-based parameter, BMI, did not enter the regression. From the potential dietary predictors (energy-corrected carbohydrates, protein, fat, and OAdiet) only protein in the case of 18- to 22-y-old males (P < 0.05) and fat in the case of 13- to 14-y-old males (P < 0.05) entered the model additionally. OAdiet did not predict 24h-OAurine in any of the sex-stratified groups (Table 3).


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  		TABLE 3 Anthropometric and dietary predictors of 24h-OAurine in children, adolescents, and adults1

 

   DISCUSSION
TOP
 ABSTRACT
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
LITERATURE CITED
 
The interest in organic acid quantification in healthy subjects arose with its role as an important contributor to the body's acid load. Traditionally, measurements of specific organic acids have served in the diagnosis of pathophysiological conditions such as diabetic ketosis, congenital organic acidemias, or drug- or chemically induced metabolic acidosis (32–34). In the present study, 2 existing estimates of total organic acid excretion, the OAdiet (13,16) and the OAanthro (11,12,14,19), for healthy subjects under normal physiological conditions were examined. Both, OAdiet and OAanthro estimated the absolute average daily 24h-OAurine reasonably well, with the exception of the group of 6- to 7-y olds in which OAdiet overestimated 24h-OAurine by ~54%. A reason for this could be that the formula used by Kleinman et al. (13) was derived from experimental settings only in adults and thus did not take growth into account. However, the basis of the anthropometric estimate OAanthro, which is body surface area, considers growth automatically. In addition, body surface area at least partly encompasses basal energy requirements (35), whereas OAdiet, due to the nature of the mineral-related estimation formula, depends stronger on energy intake. Whether varying absorption of cations and anions during growth may have additional consequences for the accuracy of the OAdiet estimate cannot be fully excluded.

One of the major reasons why OAanthro (i.e., body surface area) is more closely associated with the analyzed 24h-OAurine than OAdiet could be the fact that the primary kidney function, i.e., glomerular filtration rate, is very closely associated with the body's lean mass (36), which itself is highly correlated with body surface area. In addition, techniques to measure this kidney function improve when individual body surface area is considered (37). Several downstream kidney functions such as tubular reabsorption of amino acids and organic molecules, are to a large extent saturable processes (38) or only moderately varying processes (39), implying a considerable constancy in renal losses of amino acids and metabolizable anions, under normal physiological conditions (40). Consequently, body surface area determines total urinary organic acid output more consistently than OAdiet.

Furthermore, the dietary mineral intake–based calculation of organic acids is based on an estimate (dietary unmeasured anions) and not on measured parameters, thus also contributing to the higher explained variability of 24h-OAurine by OAanthro compared with OAdiet.

After correcting 24h-OAurine for body surface area, this ratio no longer showed a significant association with age, which underscores the potential of body surface area as an important 24h-OAurine predictor. Another advantage of body surface area is that it at least partly reflects growth. In agreement, using multiple regression analysis, OAanthro, the body surface area derived estimate, proved to be the principal predictor of 24h-OAurine in all age groups. Dietary fat and protein were sporadic predictors in males only, explaining between 5 and 10% of variability, whereas the OAdiet did not predict 24h-OAurine in any subgroup. Thus, the dietary effect on NEAP appears not to be caused primarily by alterations in the fraction of renally excreted daily organic acid anions. The observations of the present study are for a more-or-less typical, mixed diet. An extreme protein-rich diet would likely result in higher organic acid excretion (19) due to a higher renal loss of the acidic amino acids. Proteins generally show an excess of acidic amino acids compared with basic. Another extreme case would be vegan diets, which would produce markedly negative PRAL and NEAP, and which could lead to an underestimation of the actual organic acid excretion by OAdiet. However, this area requires future research.

The arguments favoring the OAdiet estimate as a predictor of 24h-OAurine are rooted in the basic consideration that an increase in alkali load (and systemic pH) through a higher consumption of foods such vegetables, tubers, and roots results in a markedly elevated metabolism of intestinally absorbed (and bicarbonate generating) potassium, sodium, magnesium, and calcium salts of organic acid anions (13,16,31). As dietary intake and metabolism of such organic acid anions increase, so also [according to Sebastian (18) and Kleinman (13)] does the spillover of organic acid anions into the urine. Actually, excretion of organic acid anions of the tricarboxy acid cycle, especially citrate, usually increases when higher amounts of base precursors or potential bicarbonate are ingested (41–44). The higher the potential base-precursors in the diet, the higher the urinary citric acid excretion. However, as indicated by data from Chalmers et al. (45), dietary changes associated with large increases in urinary citric acid anion and tartaric acid anion excretion are accompanied by decreases in other organic acid compounds, e.g., 4-deoxytetronic acid anions. This would explain why increases in organic acid anions excretion after a switch of the diet from a high diet acid load to a low diet acid load were not observed in our earlier findings (11) and those of others in controlled diet experiments (27,28). Low dietary acid loads resulting in lower NAE and PRAL (the diet-dependent component of NEAP), imply decreases in urinary calcium losses (7); however, they do not per se result in decreases in the organic acid anions component of NEAP (27,28).

The question remains why Kleinman and Lemann (13) did not find a significant relation between anthropometry (i.e., body weight; body surface area was not checked) and 24h-OAurine. Although speculative, it could be due to the fact that the authors (13) combined results of several partially experimental studies using acidifying or alkalizing agents such as ammonium chloride or magnesium hydroxide. This may have led to a failure to find a relation with anthropometry. In addition, energy intake, which in the present study was shown to be a confounder of the OAdiet estimate, was not controlled in the studies cited by Kleinman and Lemann (13). Again, it should be mentioned that the OAdiet in all groups correlated significantly with total energy intake (see Table 2), indicating that accounting for energy intake is necessary when using OAdiet as a predictor of organic acid anion excretion. Furthermore, the evidence in support of a body surface area–dependent predictor (OAanthro) of 24h-OAurine was reported in several studies (11,12,14,19) and is also confirmed in this study.

In conclusion, the present study confirms an existing association between OAdiet (not corrected for energy intake) and 24h-OAurine, but identifies OAanthro as a better estimate of 24h-OAurine in healthy subjects than OAdiet after allowing for energy intake. This indicates that NEAP comprises a reasonably, anthropometrically predictable component in addition to the dietary predictor, which can be determined as PRAL (12,15). In future studies, focusing on the PRAL component of NEAP to determine the diet-dependent effects of acid loads will become even more important.


   ACKNOWLEDGMENTS
 
We thank Monika Friedrich and Brigitte Nestler for performing the 24-h urine analyses.


   FOOTNOTES
 
1 Supported by the Ministry of Science and Research North Rhine-Westphalia, Germany and funded by a research grant from Protina Pharm. GmbH to T.R. No author had any conflict of interest with Protina Pharm. GmbH. Back

3 Abbreviations used: DONALD Study, Dortmund Nutritional and Anthropometric Longitudinally Designed Study; 24h-OAurine, 24-h organic acid anion excretion; OAanthro, anthropometric organic acid estimate, OAdiet, dietary organic acid estimate; NAE, net acid excretion; NEAP, net endogenous acid production; PRAL, potential renal acid load. Back

Manuscript received 3 November 2005. Initial review completed 15 December 2005. Revision accepted 6 February 2006.


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 DISCUSSION
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