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

Abstract

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.