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.