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UTILIZING INFORMATION COLLECTED UNDER THE CLEAN WATER ACT FOR PUBLIC HEALTH ANALYSIS
Citation:
JAGAI, J. S., B. J. Rosenbaum, S. M. Pierson, L. C. Messer, K. Rapazzo, E. N. Naumova, AND D. T. LOBDELL. UTILIZING INFORMATION COLLECTED UNDER THE CLEAN WATER ACT FOR PUBLIC HEALTH ANALYSIS. Presented at Water and Health: Where Science Meets Policy Conference, Chapel Hill, NC, October 25 - 26, 2010.
Impact/Purpose:
We obtained the impairment data collected under Section 303(d) of the Clean Water Act and merged it with stream hydrology information from the National Hydrography Dataset Plus and EPA's Reach Attribute Database to estimate percent of stream length intended for drinking water and recreational water that is impaired per county in the U.S.
Description:
The Clean Water Act was established to "restore and maintain the chemical, physical, and biological integrity of the Nation's waters". Under Section 303(d) of the Clean Water Act, the U.S.Environmental Protection Agency collects information from each state regarding the intended use of each stream in the state and whether the stream waters are impaired for that use. This is a potentially valuable dataset which has not been explored for use in public health analysis. We hypothesized that counties with waters impaired for drinking and recreational activities have higher rates of gastrointestinal infections. We obtained the impairment data collected under Section 303(d) ofthe Clean Water Act and merged it with stream hydrology information from the National Hydrography Dataset Plus and EPA's Reach Attribute Database to estimate percent of stream length intended for drinking water and recreational water that is impaired per county in the U.S. This analysis was conducted on a national level and we considered all counties in the U.S. (over 3000). For example, in 2002, Wake County, North Carolina had 2064 streams representing a total of2131 kilometers (km); 476 km ofstream were intended for drinking water ofwhich 35 km (7.4%) were impaired and 104km of stream were intended for recreational water ofwhich 35 km (34%) were impaired. For health outcome, we utilized hospitalization records from the Center for Medicare and Medicaid Services (CMS) from 2000 to 2004. We abstracted cases with diagnoses of gastrointestinal infections and cases were aggregated according to diagnosis codes and county of residence. We calculated annual rates ofhospitalization for gastrointestinal infections in the elderly per county. Using regression analysis, we assessed county-level associations between percent of impaired waters and rates of gastrointestinal infections controlling for county level parameters, such as population density, average household size, and median income. This analysis demonstrates the value of utilizing data collected under broader policy objectives for public health analysis. (This abstract does not necessarily reflect EPA policy.)