Bone Lead Level Prediction Models and Their Application to Examine the Relationship of Lead Exposure and Hypertension in the Third National Health and Nutrition Examination Survey

Abstract

Objective: 

We developed prediction models for bone lead using blood lead levels and other standard covariates in a community-based cohort of older men.

Methods: 

Participants having bone lead levels measured by K X-ray fluorescence were included in the model selection process (n = 825). Predictors of each tibia and patella lead were identified in three quarters of the population and then predicted the bone lead levels in the remaining one quarter and in the Community Lead Study.

Results: 

Eighteen predictors were selected for tibia (blood lead, age, education, occupation, smoking status, pack-years of cigarette, serum levels of phosphorus, uric acid, calcium, creatinine and total and high-density lipoprotein cholesterols, hematocrit, body mass index, systolic and diastolic blood pressure, and diagnoses of cancer and diabetes; R² = 0.32) and 16 for patella lead (among the predictors included in the tibia model diagnosis of cancer, serum levels of calcium, and total cholesterol were not included in patella lead model, but diagnosis of hypertension was included; R² = 0.34), respectively. The correlation coefficients between the observed and predicted values were 0.43 to 0.50 for tibia and 0.52 to 0.58 for patella lead in internal and external validation. We applied these predicted bone lead models to the Third National Health and Nutrition Examination Survey (NHANES-III) to examine associations with hypertension and found relatively more significant associations compared with blood lead.

Conclusions: 

This study suggests that the prediction equations may be used to predict bone lead levels in other community-based cohorts with reasonable accuracy.