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The map accompanying this brief report depicts spatial variation in viewshed characteristics of urban pedestrian trails in the city of Indianapolis, Indiana, USA. Visual openness and visual magnitude were modeled for approximately 50 kilometers of the Indianapolis Greenway Trail System using geographic information system and light detection and ranging (LiDAR) technologies. Viewshed data also were integrated with high resolution satellite imagery to estimate greenness perceived by trail users. The primary map was designed at scale of 1:32,000 and shows visual magnitude overlaid on aerial photography and LiDAR surface height layers. Inset maps illustrate viewshed integration with high resolution satellite imagery to estimate perception of greenness. We have reported statistically significant relationships between pedestrian trail traffic and viewshed characteristics along trail segments as estimated with multivariate regression models that control for other variables, including weather variation, month, day of week, and social and physical attributes of surrounding neighborhoods. In previous studies we also found higher satellite-based estimates of greenness were associated with improved self-reported perception of neighborhood walking environments by children and their families. We note here both current limitations of existing technologies and potential for emerging technologies to improve measurement of pedestrian viewshed characteristics. [ABSTRACT FROM AUTHOR]

Purpose. This study examines relationships between overweight in children and two environmental factors--amount of vegetation surrounding a child's place of residence and proximity of the child's residence to various types of food retail locations. We hypothesize that living in greener neighborhoods, farther from fast food restaurants, and closer to supermarkets would be associated with lower risk of overweight. Design. Cross-sectional study. Setting. Network of primary care pediatric clinics in Marion County, Indiana. Subjects. We acquired data for 7334 subjects, ages 3 to 18 years, presenting for routine well-child care. Measures. Neighborhood vegetation and proximity to food retail were calculated using geographic information systems for each subject using circular and network buffers. Child weight status was defined using body mass index percentiles. Analysis. We used cumulative logit models to examine associations between an index of overweight, neighborhood vegetation, and food retail environment. Results. After controlling for individual socio-demographics and neighborhood socioeconomic status, measures of vegetation and food retail significantly predicted overweight in children. Increased neighborhood vegetation was associated with decreased risk for overweight, but only for subjects residing in higher population density regions. Increased distance between a subject's residence and the nearest large brand name supermarkets was associated with increased risk of overweight, but only for subjects residing in lower population density regions. Conclusions. This research suggests that aspects of the built environment are determinants of child weight status, ostensibly by influencing physical activity and dietary behaviors. [ABSTRACT FROM AUTHOR]

Potential driving forces and environmental impacts of urban and suburban development of rural lands were investigated in a 44-county study region located in the central portion of the state of Indiana. Land-cover dynamics were quantified through classification and change detection analysis of Landsat satellite imagery acquired in the early 1990s and in 1999–2000. Satellite-based measurements of land-cover change were found to be significantly related to socioeconomic processes, including population change, financial investment in the built environment, and the extent of preexisting developed land cover. The results indicate that efficiency in per capita use of developed land decreased over the temporal scope of the study. Changes in per capita developed land cover were found to be significantly related to the total amount of growth that occurred, suggesting that areas that experienced more growth were less efficient consumers of rural land. The results also show that changing spatial structures of land-cover configuration resulted in varying degrees of loss of different rural land-cover types, increased fragmentation of agricultural lands, and increased sensible heat exchange between surface and atmosphere. [ABSTRACT FROM AUTHOR]

The influence of zoning on Normalized Difference Vegetation Index (NDVI) and radiant surface temperature (Ts) measurements is investigated in the City of Indianapolis, IN, USA using data collected by the Enhanced Thematic Mapper Plus (ETM+) remote sensing system. Analysis of variance indicates statistically significant differences in mean Ts and NDVI values associated with different types of zoning. Multiple comparisons of mean Ts and NDVI values associated with specific pairings of individual zoning categories are also shown to be significantly different. An inverse relationship between Ts and NDVI was observed across the city as a whole and within all but one zoning category. A range of environmental influences on sensible heat flux and urban vegetation was detected both within and between individual zoning categories. Examples for implementing these findings in urban planning applications to find examples of high and low impact development are demonstrated. [Copyright &y& Elsevier]

Discusses the use of Geographic Information Systems to integrate historic maps of vegetation and soils with more digital soils and wetland maps and multi-spectral satellite imagery to estimate changes in the area and distribution of natural areas in Indianapolis-Marion County, Indiana. Details of the mapping tree cover in urban environments; Details of the pre-European settlement vegetation communities.

Background: Opioid use and abuse in the United States continues to expand at an alarming rate. In this study, we examine the county-level determinants of the availability and abuse of prescription opioids to better understand the socio-ecological context, and in particular the role of the healthcare delivery system, on the prescription drug abuse epidemic., Methods: We use community-level information, data from Indiana's prescription drug monitoring program in 2011, and geospatial regression methods to identify county-level correlates of the availability and abuse of prescription opioids among Indiana's 92 counties., Results: The findings suggest that access to healthcare generally, and to dentists and pharmacists in particular, increases the availability of prescription opioids in communities, which, in turn, is associated with higher rates of opioid abuse., Conclusions: The results suggest that the structure of the local healthcare system is a major determinant of community-level access to opioids adding to a growing body of evidence that the problem of prescription opioid abuse is, at least in part, an "iatrogenic epidemic.", (Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.)

Background: Observational field audits are recommended for public health research to collect data on built environment characteristics. A reliable, standardized alternative to field audits that uses publicly available information could provide the ability to efficiently compare results across different study sites and time., Purpose: This study aimed to assess inter-rater reliability of built environment audits conducted using Google Street View imagery., Methods: In 2011, street segments from St. Louis and Indianapolis were geographically stratified to ensure representation of neighborhoods with different land use and socioeconomic characteristics in both cities. Inter-rater reliability was assessed using observed agreement and the prevalence-adjusted bias-adjusted kappa statistic (PABAK)., Results: The mean PABAK for all items was 0.84. Ninety-five percent of the items had substantial (PABAK ≥ 0.60) or nearly perfect (PABAK ≥ 0.80) agreement., Conclusions: Using Google Street View imagery to audit the built environment is a reliable method for assessing characteristics of the built environment.

Background: Indiana University School of Medicine (IUSM) employs eight regional basic science campuses, where half of the students complete their first two years of medical school. The other half complete all four years at the main campus in Indianapolis. The authors tested the hypothesis that training at regional campuses influences IUSM students to pursue primary care careers near the regional campuses they attended., Methods: Medical school records for 2,487 graduates (classes of 1988-1997) were matched to the 2003 American Medical Association Physician Masterfile to identify the medical specialty and practice location of each graduate. Multivariate logistic regression was performed to assess the effect of regional campus attendance on students' choice of medical specialty and practice location, while simultaneously adjusting for several covariates thought to affect these career outcomes., Results: Compared to Indianapolis students, those who attended a regional campus were somewhat more likely to be white, have parents with middle class occupations, and score slightly lower on the Medical College Admission Test. Any such differences were adjusted for in the regression models, which predicted that four of the regional campuses were significantly more likely than Indianapolis to produce family practitioners, and that five of the regional campuses were significantly more likely than the others to have former students practicing in the region. When analyzed collectively, attendance at any regional campus was a significant predictor of a primary care practice located outside the Indianapolis metropolitan area., Conclusion: Attending a regional campus for preclinical training appears to increase the likelihood of practicing primary care medicine in local communities.

Background: Available studies of the built environment and the BMI of children and youth suggest a contemporaneous association with neighborhood greenness in neighborhoods with high population density. The current study tests whether greenness and residential density are independently associated with 2-year changes in the BMI of children and youth., Methods: The sample included children and youth aged 3-16 years who lived at the same address for 24 consecutive months and received well-child care from a Marion County IN clinic network within the years 1996-2002 (n=3831). Multiple linear regression was used to examine associations among age- and gender-specific BMI z-scores in Year 2, residential density, and a satellite-derived measure of greenness, controlling for baseline BMI z-scores and other covariates. Logistic regression was used to model associations between an indicator of BMI z-score increase from baseline to Time 2 and the above-mentioned predictors., Results: Higher greenness was significantly associated with lower BMI z-scores at Time 2 regardless of residential density characteristics. Higher residential density was not associated with Time 2 BMI z-scores in models regardless of greenness. Higher greenness was also associated with lower odds of children's and youth's increasing their BMI z-scores over 2 years (OR=0.87; 95% CI=0.79, 0.97)., Conclusions: Greenness may present a target for environmental approaches to preventing child obesity. Children and youth living in greener neighborhoods had lower BMI z-scores at Time 2, presumably due to increased physical activity or time spent outdoors. Conceptualizations of walkability from adult studies, based solely on residential density, may not be relevant to children and youth in urban environments.

Objective: This study examines the influence of a physician's hometown location on the choice of practice location, adjusting for confounding variables., Methods: Medical school records for 2,487 Indiana University graduates (classes of 1988--1997) were matched to the American Medical Association's Masterfile data to identify the graduates' current practice locations and specialties. Urban influence codes were assigned to each county in Indiana for the purposes of defining metro or nonmetro locations. Physician practice locations were mapped using ArcGIS software. Chi-square tests, logistic regression, and analysis of variance were used to examine the influence of hometown on choice of practice location., Results: Chi-square tests revealed significant associations between physician hometown and current practice location. Logistic regression, controlling for age and gender, predicted physicians (all specialties) from nonmetro hometowns were 4.7 times as likely to locate their practice in a nonmetro location as compared to their peers from metro hometowns. Similarly, family physicians from nonmetro hometowns were 4.4 times as likely to choose a nonmetro practice location. There was not a significant difference in the mean distance between hometown and practice location for physicians from nonmetro hometowns compared to those from metro hometowns., Conclusions: This study underscores the influence of physicians' hometown on their choice of practice location.