Potential Renal Acid Load of Foods and its Influence on Urine pH

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Abstract

The purpose of this study was to calculate the potential renal acid load (PRAL) of selected, frequently consumed foods. A physiologically based calculation model was recently validated to yield an appropriate estimate of renal net acid excretion (NAE); the model depends primarily on nutrient intake data. When nutrient data from actual food composition tables were used, the calculation model yielded PRAL values that ranged from an average maximum of 23.6 mEq/100 g for certain hard cheeses over 0 mEq/100 g for fats and oils to an average minimum of approximately −3 mEq/100 g for fruits and fruit juices and vegetables. By means of these PRAL data (summed according to the amounts of foods and beverages consumed daily and by an estimate of excretion of organic acids [based on body size]), the daily NAE can be calculated. This calculation methodology, primarily based on PRAL, allows an appropriate prediction of the effects of diet on the acidity of urine. For practical applicability in dietetic prevention of recurrent urolithiasis or in other fields of dietetics, the additionally determined correlation (r=.83; P<.001) between NAE and urine pH can be used to ascertain NAE target values for a desired urine pH modification. J Am Diet Assoc. 1995; 95:791-797.

Section snippets

Calculation Model

The method used for calculation of the PRAL of foods is based on the calculation model we developed for prediction of NAE from nutrient intake data (4). The directly determined NAE (based on urine analyses) is calculated in the conventional manner as the sum of titratable acid and ammonium minus bicarbonate (Fig. 1). As is discernible from Fig. 1, NAE can also be determined indirectly from the difference of the sum of the remaining important urinary anions — chloride, phosphorus, sulfate, and

Results

The calculated acid-forming potential (or base-forming potential) of more than 100 frequently consumed foods and beverages is listed along with postabsorptive urinary determinants, sulfate, phosphorus excess, and alkali excess, according to nine main food groups in Table 2. The calculation model yielded PRAL values ranging from a maximum of 34.2 mEq/100 g (parmesan cheese) over 0 mEq/100 g for fat and oils to a minimum of −21 mEq/100 g (raisins). Among the raw (ie, nondried) fruits, the

Discussion

According to the calculation model described, negative PRAL values (indicating an excess of the base-forming potential of foods) were nearly exclusively found in the vegetable and fruit groups. In contrast, the highest acid loads originated in cheese, followed by meat, fish, and grain products. Similar trends, although with marked deviations for individual foods, were observed by other investigators whose calculations were based on acid-alkaline ash analyses (13), (14) or on current food tables

Implications and Applications

A formula for the prediction of urine pH using nutrient intake data has been developed for cats (15), a species with a high incidence of struvite stones. To our knowledge no such prognostic method has been available hitherto for human beings consuming normal mixed diets. Based on PRAL values presented herein, which consider mean intestinal absorption rates for individual nutrients and postabsorptive metabolism of sulfur-containing amino acids, it is possible to estimate the diet-dependent

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