Regression equation predicts dietary phosphorus intake from estimate of dietary protein intake

Objective: To develop a predictive equation for dietary phosphorus intake. Design: In this clinic-based, cross-sectional study, a dietitian- administered food frequency questionnaire provided dietary intake estimates for a population of patients with chronic renal failure. A prediction equation for dietary phosphorus intake was developed and was validated on another sample of patients with CRF from the same clinic. Subjects: Outpatients treated for chronic renal failure at the E. Wolfson Medical Center Institute of Nephrology in Holon, Israel, participated in the study (N=104, 73 men and 31 women, mean age=65.6 years). The validation sample consisted of 53 outpatients with chronic renal failure (38 men and 15 women, mean age=64.2 years) from the same clinic. Main outcome measures: Dietary variables (ie, energy, protein, carbohydrate, fat, phosphorus) were examined in terms of crude intake; as percentage of total energy intake, and per kilogram of body weight: Statistical analyses performed: Stepwise linear regression analysis and Student's t tests were used to examine relationships between dietary phosphorus and other variables. Results: Dietary phosphorus (milligrams)=128+14 (protein intake [grams]) was the best-fitting equation and explained 84% of the variance in dietary phosphorus intake. Applications: The prediction equation for dietary phosphorus intake is especially useful for renal dietitians who calculate patient diets by hand.