Relationship of blood lead levels to blood pressure in battery workers.
The effect of lead exposure on blood pressure in the modern industrial setting is controversial. In this study, we followed 67 workers in a lead-battery plant for 6-10 y, and blood pressure and blood lead levels were measured every 6 mo. Weight, height, alcohol intake, cigarette smoking, and age were recorded. Partial correlation coefficients showed that initial systolic blood pressure, age, and body mass index (i.e., weight/height squared) accounted for 25%, 30.9%, and 20.2%, respectively, of the variance in systolic blood pressure (p < .001 in all cases). Conversely, average blood lead levels (13 +/- 3 tests/worker) accounted for only 0.4% of the variance (not significant). Repeated-measures analysis of variance showed a small--but significant--association between blood lead levels and systolic blood pressure. There was a negative correlation between blood lead levels and diastolic blood pressure. There were 18 men with average blood lead levels that were less than 30 micrograms/dl (average = 25 +/- 3 micrograms/dl), and 32 men had levels of 40 micrograms/dl or more (average = 47 +/- 6 micrograms/dl). The mean final systolic blood pressure, adjusted for age, and initial systolic blood pressure were 117 +/- 13 mm Hg and 114 +/- 11 mm Hg, respectively. We concluded that blood lead levels had no clinically significant effect on blood pressure in lead-battery workers. The main predictors of the follow-up systolic blood pressure were age, body mass index, and initial systolic blood-pressure measurements.
Navah
U
U
Institute for Workers Health and Rehabilitation, Tel Aviv University, Ramat Aviv, Israel.
Froom
P
P
Kristal-Boneh
E
E
Moschovitch
B
B
Ribak
J
J
D000328:Adult; D000704:Analysis of Variance; D001794:Blood Pressure / Q000187:drug effects*; D015331:Cohort Studies; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D007557:Israel; D007854:Lead / Q000009:adverse effects / Q000097:blood*; D008297:Male; D016273:Occupational Exposure / Q000009:adverse effects* / Q000032:analysis / Q000706:statistics & numerical data; D011446:Prospective Studies; D013997:Time Factors
D007854:Lead