2013 Conference of the International Medical Geology Association (25–29 August 2013)

Paper No. 6
Presentation Time: 12:00 PM-11:55 PM


SCHWARCZ, Leilani, WAMSLEY, Miriam, TOTH, Barbara and KRAPFL, Heidi, New Mexico Department of Health, 1190 St. Francis Drive N-1320, Santa Fe, NM 87505, miriam.wamsley@state.nm.us

Background: In New Mexico, along the Rio Grande Rift Valley, arsenic concentrations in groundwater range from < 1 µg/L to 600 µg/L. Approximately 90% of New Mexico’s drinking water supply is from groundwater. The presence of arsenic in drinking water is a potential public health concern in areas of New Mexico where concentrations in groundwater are above the EPA maximum contaminant level (MCL) of 10 µg/L. The objective of this meta-analysis was to evaluate the association between arsenic in drinking water concentrations and arsenic body burden as measured by urinary arsenic levels among participants of biomonitoring projects in New Mexico.

Methods: We utilized data from three New Mexico Department of Health biomonitoring projects conducted from 2004 through 2012, which included volunteer participants residing in 76 communities. For this meta-analysis, 1013 adults were identified as eligible participants. They provided samples of their drinking water, a spot urine sample and completed an exposure assessment survey. Drinking water and urine samples were analyzed for total arsenic. Sample collections and analytical methods applied were similar among the biomonitoring projects, therefore, the testing results were pooled for meta-analysis. A multiple regression model was developed to evaluate the effect of drinking water arsenic concentration on urinary arsenic concentration, with adjustment for potential variables such as age, sex, dietary supplement use, tobacco use, fish/seafood consumption, and daily water consumption.

Results: The final regression model is presented, including adjustment for variables along with correlation coefficients, and assumptions.

Conclusions: Exposure to arsenic through drinking water can be controlled and minimized by consumers’ health behavior changes. Future groundwater arsenic mapping or predictive arsenic groundwater transport models are needed to identify potential excessive arsenic exposure from groundwater sources used for drinking water.