Background: The process of geocoding produces output coordinates of varying degrees of quality. Previous studies have revealed that simply excluding records with low-quality geocodes from analysis can introduce significant bias, but depending on the number and severity of the inaccuracies, their inclusion may also lead to bias. Little quantitative research has been presented on the cost and/or effectiveness of correcting geocodes through manual interactive processes, so the most cost effective methods for improving geocoded data are unclear. The present work investigates the time and effort required to correct geocodes contained in five health-related datasets that represent examples of data commonly used in Health GIS.

Recent studies have produced inconsistent results in their examination of the potential association between proximity to healthcare or mammography facilities and breast cancer stage at diagnosis. Using a multistate dataset, we re-examine this issue by investigating whether travel time to a patient's diagnosing facility or nearest mammography facility impacts breast cancer stage at diagnosis. We studied 161,619 women 40 years and older diagnosed with invasive breast cancer from ten state population based cancer registries in the United States. For each woman, we calculated travel time to their diagnosing facility and nearest mammography facility. Logistic multilevel models of late versus early stage were fitted, and odds ratios were calculated for travel times, controlling for age, race/ethnicity, census tract poverty, rural/urban residence, health insurance, and state random effects. Seventy-six percent of women in the study lived less than 20 min from their diagnosing facility, and 93 percent lived less than 20 min from the nearest mammography facility. Late stage at diagnosis was not associated with increasing travel time to diagnosing facility or nearest mammography facility. Diagnosis age under 50, Hispanic and Non-Hispanic Black race/ethnicity, high census tract poverty, and no health insurance were all significantly associated with late stage at diagnosis. Travel time to diagnosing facility or nearest mammography facility was not a determinant of late stage of breast cancer at diagnosis, and better geographic proximity did not assure more favorable stage distributions. Other factors beyond geographic proximity that can affect access should be evaluated more closely, including facility capacity, insurance acceptance, public transportation, and travel costs.

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Soil moisture is an important variable in the climate system that integrates the combined influence of the atmosphere, land surface, and soil. Soil moisture is frequently used for drought monitoring and climate forecasting. However, in situ soil moisture observations are not systematically archived and there are relatively few national soil moisture networks. The lack of observed soil moisture data makes it difficult to characterize long-term soil moisture variability and trends. The North American Soil Moisture Database (NASMD) is a new high-quality observational soil moisture database. It includes over 1,800 monitoring stations in the United States, Canada, and Mexico, making it the largest collections of in situ soil moisture observations in North America. Data are collected from multiple sources, quality controlled, and integrated into an online database (soilmoisture.tamu.edu). Here we describe the development of the database, including quality control/quality assurance, standardization, and collection of metadata. The utility of the NASMD is demonstrated through an analysis of the inter- and intraannual variability of soil moisture from multiple networks. The NASMD is a useful tool for drought monitoring and forecasting, calibrating/validating satellites and land surface models, and documenting how soil moisture influences the climate system on seasonal to interannual time scales.

Geographic barriers to optimal breast cancer treatment remain a valid concern, though most women traveling long distances to receive mastectomies are doing so after bypassing local options.

In a population-based case-control study in California's intensely agricultural Central Valley (2005-2006), the authors investigated relations between environmental pesticide/fungicide exposure and prostate cancer. Cases (n = 173) were obtained from a population-based cancer registry, and controls (n = 162) were obtained from Medicare listings and tax assessor mailings. Past ambient exposures to pesticides/fungicides were derived from residential history and independently recorded pesticide and land-use data, using a novel geographic information systems approach. In comparison with unexposed persons, increased risks of prostate cancer were observed among persons exposed to compounds which may have prostate-specific biologic effects (methyl bromide (odds ratio = 1.62, 95% confidence interval: 1.02, 2.59) and a group of organochlorines (odds ratio = 1.64, 95% confidence interval: 1.02, 2.63)) but not among those exposed to other compounds that were included as controls (simazine, maneb, and paraquat dichloride). The authors assessed the possibility of selection bias due to less-than-100% enrollment of eligible cases and controls (a critical methodological concern in studies of this kind) and determined that there was little evidence of bias affecting the estimated effect size. This study provides evidence of an association between prostate cancer and ambient pesticide exposures in and around homes in intensely agricultural areas. The associations appear specific to compounds with a plausible biologic role in prostate carcinogenesis.

Theoretical considerations and mathematical tools to analyze multidimensional transient infiltration from a trickle source have been developed. Two mathematical models were considered: (i) a plane flow model involving the Cartesian coordinates x and z; and (ii) a cylindrical flow model described by the cylindrical coordinates r and z. The diffusion‐ type water flow equation in unsaturated soil was solved numerically by an approach that combines the noniterative ADI difference procedure with Newton's iterative method. The numerical results have been compared with Wooding's solution for steady infiltration from a circular pond and with a simple one‐dimensional solution. These comparisons indicate that the method is reliable and can be used with confidence. Typical results are demonstrated to show the effect of trickle discharge on the water content field, the saturated water entry zone, and the water flux at the soil surface.

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