A population-based model for predicting blood pressure.

Multiple regression analysis were used to investigate the relationship between blood pressure and age, sex, relative weight, antihypertensive medication, diabetes mellitus, diet (low-salt, low-cholesterol, and weight-reducing regimens), cigarette smoking, coffee drinking, and aerobic exercise among a stratified random sample of the population of Rochester, Minnesota, 35 years of age or older. Age, sex, relative weight, antihypertensive medication, and cigarette smoking were significantly correlated with blood pressure and were incorporated in regression models of systolic and diastolic pressure. These models were used to predict average (geometric mean) blood pressure values for the adult population of Rochester and to predict age-, sex-, and relative weight-specific blood pressure percentiles.