Browsing by Author "Wilson, Jeffrey S."
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Item Accelerometer and GPS Analysis of Trail Use and Associations With Physical Activity(Human Kinetics, 2018-07) Tamura, Kosuke; Wilson, Jeffrey S.; Puett, Robin C.; Klenosky, David B.; Harper, William A.; Troped, Philip J.; Geography, School of Liberal ArtsBackground: Concurrent use of accelerometers and global positioning system (GPS) data can be used to quantify physical activity (PA) occurring on trails. This study examined associations of trail use with PA and sedentary behavior (SB) and quantified on trail PA using a combination of accelerometer and GPS data. Methods: Adults (N = 142) wore accelerometer and GPS units for 1–4 days. Trail use was defined as a minimum of 2 consecutive minutes occurring on a trail, based on GPS data. We examined associations between trail use and PA and SB. On trail minutes of light-intensity, moderate-intensity, and vigorous-intensity PA, and SB were quantified in 2 ways, using accelerometer counts only and with a combination of GPS speed and accelerometer data. Results: Trail use was positively associated with total PA, moderate-intensity PA, and light-intensity PA (P < .05). On trail vigorous-intensity PA minutes were 346% higher when classified with the combination versus accelerometer only. Light-intensity PA, moderate-intensity PA, and SB minutes were 15%, 91%, and 85% lower with the combination, respectively. Conclusions: Adult trail users accumulated more PA on trail use days than on nontrail use days, indicating the importance of these facilities for supporting regular PA. The combination of GPS and accelerometer data for quantifying on trail activity may be more accurate than accelerometer data alone and is useful for classifying intensity of activities such as bicycling.Item Accelerometer and GPS Data to Analyze Built Environments and Physical Activity(Taylor & Francis, 2019-09) Tamura, Kosuke; Wilson, Jeffrey S.; Goldfeld, Keith; Puett, Robin C.; Klenosky, David B.; Harper, William A.; Troped, Philip J.; Geography, School of Liberal ArtsPurpose: Most built environment studies have quantified characteristics of the areas around participants' homes. However, the environmental exposures for physical activity (PA) are spatially dynamic rather than static. Thus, merged accelerometer and global positioning system (GPS) data were utilized to estimate associations between the built environment and PA among adults. Methods: Participants (N = 142) were recruited on trails in Massachusetts and wore an accelerometer and GPS unit for 1-4 days. Two binary outcomes were created: moderate-to-vigorous PA (MVPA vs. light PA-to-sedentary); and light-to-vigorous PA (LVPA vs. sedentary). Five built environment variables were created within 50-meter buffers around GPS points: population density, street density, land use mix (LUM), greenness, and walkability index. Generalized linear mixed models were fit to examine associations between environmental variables and both outcomes, adjusting for demographic covariates. Results: Overall, in the fully adjusted models, greenness was positively associated with MVPA and LVPA (odds ratios [ORs] = 1.15, 95% confidence interval [CI] = 1.03, 1.30 and 1.25, 95% CI = 1.12, 1.41, respectively). In contrast, street density and LUM were negatively associated with MVPA (ORs = 0.69, 95% CI = 0.67, 0.71 and 0.87, 95% CI = 0.78, 0.97, respectively) and LVPA (ORs = 0.79, 95% CI = 0.77, 0.81 and 0.81, 95% CI = 0.74, 0.90, respectively). Negative associations of population density and walkability with both outcomes reached statistical significance, yet the effect sizes were small. Conclusions: Concurrent monitoring of activity with accelerometers and GPS units allowed us to investigate relationships between objectively measured built environment around GPS points and minute-by-minute PA. Negative relationships between street density and LUM and PA contrast evidence from most built environment studies in adults. However, direct comparisons should be made with caution since most previous studies have focused on spatially fixed buffers around home locations, rather than the precise locations where PA occurs.Item ACCESS TO SERVICES FOR THE HOMELESS(Office of the Vice Chancellor for Research, 2012-04-13) Bozzo, Anthony; Wilson, Jeffrey S.My project is based on research done in the anthropology and geography departments by myself, Dr. Zimmerman and Courtney Singleton pertaining to homeless encampments in Indianapolis. This poster presentation illustrates locations of selected encampments and their access to service providers. Geographic information system (GIS) technologies were used to conduct a network analysis that visually shows access to services and quantifies travel time and network distance to selected service locations. The analysis presented is based on data collected by my colleagues from subjects in one specific camp describing preferred travel routes, distances traveled and services needed- prescription medication for example. I plan to apply this analytical method to other encampments to create a model of hypothetical routes based upon tow paths, walking trails and street networks.Item Adolescent Health-Risk Behavior and Community Disorder(2013-11) Wiehe, Sarah E.; Kwan, Mei-Po; Wilson, Jeffrey S.; Fortenberry, J. DennisBackground Various forms of community disorder are associated with health outcomes but little is known about how dynamic context where an adolescent spends time relates to her health-related behaviors. Objective Assess whether exposure to contexts associated with crime (as a marker of community disorder) correlates with self-reported health-related behaviors among adolescent girls. Methods Girls (N = 52), aged 14–17, were recruited from a single geographic urban area and monitored for 1 week using a GPS-enabled cell phone. Adolescents completed an audio computer-assisted self-administered interview survey on substance use (cigarette, alcohol, or marijuana use) and sexual intercourse in the last 30 days. In addition to recorded home and school address, phones transmitted location data every 5 minutes (path points). Using ArcGIS, we defined community disorder as aggregated point-level Unified Crime Report data within a 200-meter Euclidian buffer from home, school and each path point. Using Stata, we analyzed how exposures to areas of higher crime prevalence differed among girls who reported each behavior or not. Results Participants lived and spent time in areas with variable crime prevalence within 200 meters of their home, school and path points. Significant differences in exposure occurred based on home location among girls who reported any substance use or not (p 0.04) and sexual intercourse or not (p 0.01). Differences in exposure by school and path points were only significant among girls reporting any substance use or not (p 0.03 and 0.02, respectively). Exposure also varied by school/non-school day as well as time of day. Conclusions Adolescent travel patterns are not random. Furthermore, the crime context where an adolescent spends time relates to her health-related behavior. These data may guide policy relating to crime control and inform time- and space-specific interventions to improve adolescent health.Item Analysing Urban Air Pollution Using Low-Cost Methods and Community Science(2022-12) Heintzelman, Asrah; Filippelli, Gabriel; Moreno-Madriñan, Max J.; Wilson, Jeffrey S.; Wang, Lixin; Druschel, Gregory K.Rise in air pollution resulting in negative health externalities for humans has created an urgent need for cities and communities to monitor it regularly. At present we have insufficient ground passive and active monitoring networks in place which presents a huge challenge. Satellite imagery has been used extensively for such analysis, but its resolution and methodology present other challenges in estimating pollution burden. The objective of this study was to propose three low-cost methods to fill in the gaps that exist currently. First, EPA grade sensors were used in 11 cities across the U.S. to examine NO2. This is a simplistic way to assess the burden of air pollution in a region. However, this technique cannot be applied to fine scale analysis, which resulted in the next two components of this research study. Second, a citizen science network was established on the east side of Indianapolis, IN who hosted 32 Ogawa passive sensors to examine NO2 and O3 at a finer scale. These low-cost passive sensors, not requiring power, and very little maintenance, have historically tracked very closely with Federal Reference Monitors. Third, a low-cost PurpleAir PA-II-SD active sensors measuring PM2.5 were housed with the citizen scientists identified above. This data was uploaded via Wi-Fi and available via a crowd sourced site established by PurpleAir. These data sets were analyzed to examine the burden of air pollution. The second and third research studies enabled granular analyses utilizing citizen science, tree canopy data, and traffic data, thus accommodating some of the present limitations. Advancement in low-cost sensor technology, along with ease of use and maintenance, presents an opportunity for not just communities, but cities to take charge of some of these analyses to help them examine health equity impacts on their citizens because of air pollution.Item Association Between Residential Greenness and Cardiovascular Disease Risk(Wiley, 2018-12-05) Yeager, Ray; Riggs, Daniel W.; DeJarnett, Natasha; Tollerud, David J.; Wilson, Jeffrey S.; Conklin, Daniel J.; O'Toole, Timothy E.; McCracken, James; Lorkiewicz, Pawel; Xie, Zhengzhi; Zafar, Nagma; Krishnasamy, Sathya S.; Srivastava, Sanjay; Finch, Jordan; Keith, Rachel J.; DeFilippis, Andrew; Rai, Shesh N.; Liu, Gilbert; Bhatnagar, Aruni; Department of Geography, School of Liberal ArtsBackground Exposure to green vegetation has been linked to positive health, but the pathophysiological processes affected by exposure to vegetation remain unclear. To study the relationship between greenness and cardiovascular disease, we examined the association between residential greenness and biomarkers of cardiovascular injury and disease risk in susceptible individuals. Methods and Results In this cross‐sectional study of 408 individuals recruited from a preventive cardiology clinic, we measured biomarkers of cardiovascular injury and risk in participant blood and urine. We estimated greenness from satellite‐derived normalized difference vegetation index (NDVI) in zones with radii of 250 m and 1 km surrounding the participants’ residences. We used generalized estimating equations to examine associations between greenness and cardiovascular disease biomarkers. We adjusted for residential clustering, demographic, clinical, and environmental variables. In fully adjusted models, contemporaneous NDVI within 250 m of participant residence was inversely associated with urinary levels of epinephrine (−6.9%; 95% confidence interval, −11.5, −2.0/0.1 NDVI) and F2‐isoprostane (−9.0%; 95% confidence interval, −15.1, −2.5/0.1 NDVI). We found stronger associations between NDVI and urinary epinephrine in women, those not on β‐blockers, and those who had not previously experienced a myocardial infarction. Of the 15 subtypes of circulating angiogenic cells examined, 11 were inversely associated (8.0–15.6% decrease/0.1 NDVI), whereas 2 were positively associated (37.6–45.8% increase/0.1 NDVI) with contemporaneous NDVI. Conclusions Independent of age, sex, race, smoking status, neighborhood deprivation, statin use, and roadway exposure, residential greenness is associated with lower levels of sympathetic activation, reduced oxidative stress, and higher angiogenic capacity.Item Association Between Residential Greenness and Cardiovascular Disease Risk(American Heart Association, 2018-12-18) Yeager, Ray; Riggs, Daniel W.; DeJarnett, Natasha; Tollerud, David J.; Wilson, Jeffrey S.; Conklin, Daniel J.; O'Toole, Timothy E.; McCracken, James; Lorkiewicz, Pawel; Xie, Zhengzhi; Zafar, Nagma; Krishnasamy, Sathya S.; Srivastava, Sanjay; Finch, Jordan; Keith, Rachel J.; DeFilippis, Andrew; Rai, Shesh N.; Liu, Gilbert; Bhatnagar, Aruni; Geography, School of Liberal ArtsBackground Exposure to green vegetation has been linked to positive health, but the pathophysiological processes affected by exposure to vegetation remain unclear. To study the relationship between greenness and cardiovascular disease, we examined the association between residential greenness and biomarkers of cardiovascular injury and disease risk in susceptible individuals. Methods and Results In this cross-sectional study of 408 individuals recruited from a preventive cardiology clinic, we measured biomarkers of cardiovascular injury and risk in participant blood and urine. We estimated greenness from satellite-derived normalized difference vegetation index ( NDVI ) in zones with radii of 250 m and 1 km surrounding the participants' residences. We used generalized estimating equations to examine associations between greenness and cardiovascular disease biomarkers. We adjusted for residential clustering, demographic, clinical, and environmental variables. In fully adjusted models, contemporaneous NDVI within 250 m of participant residence was inversely associated with urinary levels of epinephrine (-6.9%; 95% confidence interval, -11.5, -2.0/0.1 NDVI ) and F2-isoprostane (-9.0%; 95% confidence interval, -15.1, -2.5/0.1 NDVI ). We found stronger associations between NDVI and urinary epinephrine in women, those not on β-blockers, and those who had not previously experienced a myocardial infarction. Of the 15 subtypes of circulating angiogenic cells examined, 11 were inversely associated (8.0-15.6% decrease/0.1 NDVI ), whereas 2 were positively associated (37.6-45.8% increase/0.1 NDVI ) with contemporaneous NDVI . Conclusions Independent of age, sex, race, smoking status, neighborhood deprivation, statin use, and roadway exposure, residential greenness is associated with lower levels of sympathetic activation, reduced oxidative stress, and higher angiogenic capacity.Item Beyond Food Deserts: Assessing the Impact of Public Transit Availability Change on Spatial Access to Food(2021-03) Katz, Brandon P.; Wilson, Jeffrey S.; Johnson, Daniel P.; Thapa, Bhuwan; Dwyer, Owen J., IIIFood access is a dimension of food security that many struggle with even in high- income countries, which is a contributing factor to chronic diet-related disease. Inequalities in economic access to food has been addressed in public policy for several decades, but spatial access to food has only been seriously studied and addressed by policy for the past twenty-five years. After the food desert metaphor emerged, it was promptly accepted as a standard measure of food access for governments and a basis for policies created to address inequalities. Conceptual criticisms and methodological limitations of the metaphor have led the study of spatial access to food towards newer methods that measure food access more realistically and assist in the development and assessment of intervention strategies to inform policy decisions. This thesis describes the history of the food desert metaphor from its emergence until its adoption in US public policy, the conceptual criticisms and methodological limitations that surround it, and offers an analysis that measures the impact of change in the availability of public transportation on spatial access to food for various population subgroups that are more at risk of food insecurity in Marion County, Indiana. Results demonstrate that policies and plans designed without consideration for food access have an impact on it nevertheless, and that policymakers and planners can leverage such strategies to better coordinate efforts across government to reduce inequalities in spatial access to food and food insecurity overall.Item The built environment predicts observed physical activity(2014-05) Kelly, Cheryl; Wilson, Jeffrey S.; Schootman, Mario; Clennin, Morgan; Baker, Elizabeth A.; Miller, Douglas K.; Department of Geography, School of Liberal ArtsBackground: In order to improve our understanding of the relationship between the built environment and physical activity, it is important to identify associations between specific geographic characteristics and physical activity behaviors. Purpose: Examine relationships between observed physical activity behavior and measures of the built environment collected on 291 street segments in Indianapolis and St. Louis. Methods: Street segments were selected using a stratified geographic sampling design to ensure representation of neighborhoods with different land use and socioeconomic characteristics. Characteristics of the built environment on-street segments were audited using two methods: in-person field audits and audits based on interpretation of Google Street View imagery with each method blinded to results from the other. Segments were dichotomized as having a particular characteristic (e.g., sidewalk present or not) based on the two auditing methods separately. Counts of individuals engaged in different forms of physical activity on each segment were assessed using direct observation. Non-parametric statistics were used to compare counts of physically active individuals on each segment with built environment characteristic. Results: Counts of individuals engaged in physical activity were significantly higher on segments with mixed land use or all non-residential land use, and on segments with pedestrian infrastructure (e.g., crosswalks and sidewalks) and public transit. Conclusion: Several micro-level built environment characteristics were associated with physical activity. These data provide support for theories that suggest changing the built environment and related policies may encourage more physical activity.Item Challenges in Monitoring Regional Trail(Sage, 2019) Lindsey, Greg; Singer-Berk, Lila; Wilson, Jeffrey S.; Oberg, Eric; Hadden-Loh, Tracy; Geography, School of Liberal ArtsThis study reports traffic monitoring results at 30 locations on a 972-mi shared-use trail network across the east-central United States. We illustrate challenges in adapting the principles in the Federal Highway Administration’s Traffic Monitoring Guide to a regional trail network. We make four contributions: 1) we use factor analysis and k-means clustering to implement a stratified random process for selecting monitoring sites; 2) we illustrate quality assurance procedures and the challenges of obtaining valid results from a multi-state monitoring system; 3) we describe variation in trail traffic volumes across five land use classes in response to daily weather and seasons; and 4) we report two performance measures for the network: annual average daily trail traffic and trail miles traveled. The Rails to Trails Conservancy deployed passive infrared traffic monitors in 2015 through 2017. Site-specific regression models were used to impute missing daily traffic volumes. The effects of weather were consistent across land use classes but the effects of temporal variables, including weekend and season of year, varied. A plan for short-duration monitoring is presented. Results confirm the FHWA monitoring principles and the difficulties of implementing them regionally.