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Bioelectromagnetics. 2001;Suppl 5:S58-68.

A case-control pilot study of traffic exposures and early childhood leukemia using a geographic information system.

Author information

1
California Department of Health Services, Environmental Health Investigations Branch, Oakland 94612, USA. preynold@dhs.ca.gov

Abstract

The scientific debate on risk relationships between proximity to electric and magnetic fields and the development of childhood leukemia has recently focused on the role of other factors that may be strongly correlated with power lines. Proximity to high traffic density, as defined by major roadways or automobile counts, and associated socioeconomic neighborhood characteristics have been suggested as potentially important confounders. For traffic or socioeconomic status (SES) to confound any EMF effect these factors would need to have their own independent impact on leukemia risk. This study was designed to use geographic information system (GIS) technology to empirically examine the relationship between traffic density and socioeconomic indicators to early childhood leukemia in an urban area of California. Ninety cases of childhood leukemia diagnosed under the age of five between 1988 and 1994 among children born in San Diego County were matched by gender and birth date to a total of 349 children also born in the county and not known to have developed any cancer. Case-control differences were assessed via conditional logistic regression. No significant differences were observed for the neighborhood median family income of the birth residences. When comparing neighborhoods with median annual income > or = $56,000 to those with incomes < or = $18,000 the odds ratio was 0.86 (95% confidence interval 0.31, 2.38). Traffic density was measured using a variety of methods, including information on average daily traffic counts and road characteristics. None of the measures of traffic were associated with case status. Neither SES or traffic density near the birth address as assessed with GIS methods are strong enough risk factors for leukemia to be confounders which could totally explain the effect of another variable (such as wire code). Associations with the diagnosis address or with more direct exposure measures may differ from those reported here.

PMID:
11170118
[Indexed for MEDLINE]

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