Air Quality Criteria for Lead Volume II of II - (NEPIS)(EPA) - US ...

AX6-135
Table AX6-5.1 (cont’d). Effects of Lead on Blood Pressure and Hypertension
Reference,
Study
Location, and
Period Study Description Pb Measurement Findings, Interpretation
United States (cont’d)
Hu et al. (1996)
U.S.-Boston-
Normative
Aging Study-
VA
1991-1994
590 males (over 98% white), mean age
around 67 yrs, divided into 146
hypertensives (systolic >160 mm Hg,
diastolic >95 mm Hg, or daily
antihypertensive medication) and 444 nonhypertensives.
Linear blood Pb, tibia and
patella bone Pb added separately to logistic
regression model containing forced
covariates of age, race, BMI, family history
of hypertension, pack-yrs smoking, alcohol
ingestion dietary sodium and calcium. Then,
a backward elimination procedure starting
with all covariates, including all Pb
variables, resulted in a model in which only
significant covariates were retained.
Hypertensives:
Arithmetic mean (SD)
blood Pb:
6.9 µg/dL (4.3)
Mean tibia Pb:
23.7 µg/g (14.0)
Mean patella Pb:
35.1 µg/g (19.5)
Non-hypertensives:
Arithmetic mean (SD)
blood Pb:
6.1 µg/dL (4.0)
Mean tibia Pb:
20.9 µg/g (11.4)
Mean patella Pb:
31.1 µg/g (18.3)
Logistic regression model with all forced covariates revealed no significant Pb
effects when the three Pb variables were forced into the model separately. After
backward elimination, the only significant covariates left were BMI and family
history of hypertension. Of all the Pb variables, only tibia Pb remained in the
model. With each increase of 10 µg/g of tibia Pb, odds of being classified
hypertensive rose (OR = 1.21; 95% CI: 1.04, 1.43).
Stepwise regression, backward or forward, involves multiple testing with the same
data set, capitalizes on chance occurrence in the data set, and gives over-optimistic
probability values. No model diagnostic testing reported.