Association between blood lead levels and proximity to industrial facilities

INTRODUCTION: Lead is released into the environment as a by-product of numerous industrial processes. This pollutant was measured in the Bio-Madrid Project, a bio-monitoring study to assess environmental exposures among pregnant women and their parents in Madrid (Spain). The objective was to investigate the association between blood lead levels (B-Ld) and residential proximity to industrial facilities included in the European Pollutant Release and Transfer Register (E-PRTR).

METHODS: Bio-Madrid is a cross-sectional study in which 145 pregnant women and their couples donated peripheral blood samples and answered an epidemiological questionnaire. E-PRTR data were used to identify facilities releasing lead in the vicinity of participant’s residence. Google Earth was used to geocode home addresses and to validate the geographic coordinates of the E-PRTR facilities. Population exposure to industrial lead emissions was estimated on the basis of “distance” from the residence to pollutant sources. The distance used to detect differences in mean B-Ld was estimated using the sum of squared errors (SSE) of prediction from a model including only “distance” (Un-adjusted model). Linear models were used to assess the association between B-Ld and distance to the nearest industry, adjusting for sex, age, tobacco, traffic, alcohol and health district (Adjusted Model). All analyses were also stratified by sex.  

RESULTS: The distance selected to assess exposure to lead emissions that minimize the SSE was 2900 meters for both sexes (Un-adjusted-OR=1.23 (1.04-1.44)). People living in the proximity of industrial facilities that release lead showed higher B-Ld (Adjusted-OR=1.18 (1.02-1.37)). Geometric mean lead levels (μg/l) in the industrial exposure/no exposure zones were 26.60 (24.80-28.59) and 21.61 (18.84-24.77) respectively. Similar results were found stratifying by sex.

CONCLUSIONS: Information registered in E-PRTR can be useful to investigate the relationship between industrial pollution and exposure to environmental pollutants improving the risk factors models for population biomonitoring.