Background Geographic information systems (GIS) offer powerful techniques for epidemiologists. Geocoding is an important step in the use of GIS in epidemiologic research, and the validity of epidemiologic studies using this methodology depends, in part, on the positional accuracy of the geocoding process. Methods We conducted a study comparing the validity of positions geocoded with a commercially available program to positions determined by Global Positioning System (GPS) satellite receivers. Addresses (N = 200) were randomly selected from a recently completed case–control study in Western New York State. We geocoded addresses using ArcView 3.2 on the GDT Dynamap/2000 U.S. Street database. In addition, we measured the longitude and latitude of these addresses with a GPS receiver. The distance between the locations obtained by these two methods was calculated for all addresses. Results The distance between the geocoded point and the GPS point was within 100 m for the majority of subject addresses (79%), with only a small proportion (3%) having a distance greater than 800 m. The overall median distance between GPS points and geocoded points was 38 m (90% confidence interval [CI] = 34–46). Distances were not different for cases and controls. Urban addresses (median = 32 m; CI = 28–37) were slightly more accurate than nonurban addresses (median = 52 m; CI = 44–61). Conclusions. This study indicates that the suitability of geocoding for epidemiologic research depends on the level of spatial resolution required to assess exposure. Although sources of error in positional accuracy for geocoded addresses exist, geocoding of addresses is, for the most part, very accurate.

Polycyclic aromatic hydrocarbons (PAH) are ubiquitous in the environment. We hypothesized that early life exposure to PAHs may have particular importance in the etiology of breast cancer. We conducted a population-based, case-control study of ambient exposure to PAHs in early life in relation to the risk of breast cancer. Total suspended particulates (TSP), a measure of ambient air pollution, was used as a proxy for PAHs exposure. Cases (n = 1,166) were women with histologically confirmed, primary, incident breast cancer. Controls (n = 2,105) were frequency matched by age, race, and county of residence to cases. Annual average TSP concentrations (1959-1997) by location were obtained from the New York State Department of Environmental Conservation for Erie and Niagara Counties. Based on the monitor readings, prediction maps of TSP concentrations were generated with ArcGIS 8.0 (ESRI, Inc., Redlands, CA) using inverse distance squared weighted interpolation. Unconditional logistic regression was used to estimate odds ratios and 95% confidence intervals. In postmenopausal women, exposure to high concentrations of TSP (>140 μg/m3) at birth was associated with an adjusted odds ratio of 2.42 (95% confidence interval, 0.97-6.09) compared with exposure to low concentrations (<84 μg/m3). However, in premenopausal women, where exposures were generally lower, the results were inconsistent with our hypothesis and in some instances were suggestive of a reduction in the risk of breast cancer. Our study suggests that exposure in early life to high levels of PAHs may increase the risk of postmenopausal breast cancer; however, other confounders related to geography cannot be ruled out.

To determine the extent to which neighborhood needs (socioeconomic deprivation and vehicle availability) are associated with two criteria of food environment access: 1) distance to the nearest food store and fast food restaurant and 2) coverage (number) of food stores and fast food restaurants within a specified network distance of neighborhood areas of colonias, using ground-truthed methods. Data included locational points for 315 food stores and 204 fast food restaurants, and neighborhood characteristics from the 2000 U.S. Census for the 197 census block group (CBG) study area. Neighborhood deprivation and vehicle availability were calculated for each CBG. Minimum distance was determined by calculating network distance from the population-weighted center of each CBG to the nearest supercenter, supermarket, grocery, convenience store, dollar store, mass merchandiser, and fast food restaurant. Coverage was determined by calculating the number of each type of food store and fast food restaurant within a network distance of 1, 3, and 5 miles of each population-weighted CBG center. Neighborhood need and access were examined using Spearman ranked correlations, spatial autocorrelation, and multivariate regression models that adjusted for population density. Overall, neighborhoods had best access to convenience stores, fast food restaurants, and dollar stores. After adjusting for population density, residents in neighborhoods with increased deprivation had to travel a significantly greater distance to the nearest supercenter or supermarket, grocery store, mass merchandiser, dollar store, and pharmacy for food items. The results were quite different for association of need with the number of stores within 1 mile. Deprivation was only associated with fast food restaurants; greater deprivation was associated with fewer fast food restaurants within 1 mile. CBG with greater lack of vehicle availability had slightly better access to more supercenters or supermarkets, grocery stores, or fast food restaurants. Increasing deprivation was associated with decreasing numbers of grocery stores, mass merchandisers, dollar stores, and fast food restaurants within 3 miles. It is important to understand not only the distance that people must travel to the nearest store to make a purchase, but also how many shopping opportunities they have in order to compare price, quality, and selection. Future research should examine how spatial access to the food environment influences the utilization of food stores and fast food restaurants, and the strategies used by low-income families to obtain food for the household.

While there are quite consistent data regarding associations of body weight and postmenopausal breast cancer, there are now accumulating data that would indicate that weight gain in adult life is more predictive of risk than absolute body weight. There is, however, little known about the relative impact of timing of weight gain in adult life as well as other characteristics of the weight and breast cancer association that might provide insight into the mechanism of the observation. We conducted a population‐based case control study of breast cancer (1996–2001), the Western New York Exposures and Breast Cancer Study. Included were 1,166 women with primary, histologically confirmed, incident breast cancer and 2,105 controls frequency‐matched on age, race and county of residence. Unconditional logistic regression was used to estimate odds ratios and 95% confidence intervals. We found increased risk of breast cancer associated with lifetime adult weight gain among post‐ but not premenopausal women, and there was a 4% increase in risk for each 5 kg increase in adult weight. Further there was a tendency toward a stronger association for those with higher waist circumference and those with positive estrogen or progesterone status, and who had never used HRT. We also found an association with risk for weight gain since first pregnancy and for weight gain between the time of the first pregnancy and menopause, independent of body mass index and lifetime adult weight gain. Our results suggest that there are time periods of weight gain that have greater impact on risk, and that central body fat, receptor status and hormone replacement therapy may all affect the observed association.