scholarly journals Black activity spaces in Shaker Heights

Author(s):  
Alan V. Grigsby
Author(s):  
Dustin T. Duncan ◽  
Seann D. Regan ◽  
Basile Chaix

Defining neighborhoods for health research continues to be challenging. This chapter discusses different methods to operationalize neighborhood boundaries, including self-report, administrative definitions, geographic information system buffers and activity spaces, including global positioning system (GPS)–defined activity spaces. It discusses the strengths and limitations of each method of examining neighborhood boundaries (e.g., spatial misclassification, technical difficulties, assumptions). Readers are provided with examples of neighborhood definitions frequently applied in the epidemiology and population health literature. In addition, the chapter provides a rigorous overview of theories for selecting neighborhood definitions, including spatial polygamy theory for GPS-defined activity space neighborhoods.


Author(s):  
Bridget Freisthler ◽  
Nancy J. Kepple ◽  
Jennifer Price Wolf ◽  
Leslie Carson
Keyword(s):  

1987 ◽  
Vol 19 (6) ◽  
pp. 735-748 ◽  
Author(s):  
S Hanson ◽  
M Schwab

This paper contains an examination of the fundamental assumption underlying the use of accessibility indicators: that an individual's travel behavior is related to his or her location vis-à-vis the distribution of potential activity sites. First, the conceptual and measurement issues surrounding accessibility and its relationship to travel are reviewed; then, an access measure for individuals is formulated. Using data from the Uppsala (Sweden) Household Travel Survey and controlling for sex, automobile availability, and employment status, the authors explore the relationship between both home- and work-based accessibility and five aspects of an individual's travel: mode use, trip frequencies and travel distances for discretionary purposes, trip complexity, travel in conjunction with the journey to work, and size of the activity space. From the results it can be seen that although all of these travel characteristics are related to accessibility to some degree, the travel–accessibility relationship is not as strong as deductive formulations have implied. High accessibility levels are associated with higher proportions of travel by nonmotorized means, lower levels of automobile use, reduced travel distances for certain discretionary trip purposes, and smaller individual activity spaces. Furthermore, the density of activity sites around the workplace affects the distances travelled by employed people for discretionary purposes. Overall, accessibility level has a greater impact on mode use and travel distance than it does on discretionary trip frequency. This result was unexpected in light of the strong trip frequency–accessibility relationship posited frequently in the literature.


2016 ◽  
Vol 27 (3) ◽  
pp. 422-450 ◽  
Author(s):  
MOHAMMAD A. TAYEBI ◽  
UWE GLÄSSER ◽  
MARTIN ESTER ◽  
PATRICIA L. BRANTINGHAM

Crime reduction and prevention strategies are vital for policymakers and law enforcement to face inevitable increases in urban crime rates as a side effect of the projected growth of urban population by the year 2030. Studies conclude that crime does not occur uniformly across urban landscapes but concentrates in certain areas. This phenomenon has drawn attention to spatial crime analysis, primarily focusing on crime hotspots, areas with disproportionally higher crime density. In this paper, we present CrimeTracer1, a personalized random walk-based approach to spatial crime analysis and crime location prediction outside of hotspots. We propose a probabilistic model of spatial behaviour of known offenders within their activity spaces. Crime Pattern Theory concludes that offenders, rather than venture into unknown territory, frequently select targets in or near places they are most familiar with as part of their activity space. Our experiments on a large real-world crime dataset show that CrimeTracer outperforms all other methods used for location recommendation we evaluate here.


Author(s):  
R. K. Rai ◽  
Michael Balmer ◽  
Marcel Rieser ◽  
V. S. Vaze ◽  
Stefan Schönfelder ◽  
...  

2018 ◽  
Vol 33 (1) ◽  
Author(s):  
Andrew C. Pickett ◽  
George B. Cunningham

Given societal body ideals praising thinness and muscularity, physical activity spaces can bedifficult to navigate for those in larger bodies. Thus, stigma serves as a strong barrier to participation. Inthis study, the authors explore ways that body stigma affects larger individuals’ participation in physicalactivity. This authors employed qualitative, semi-structured interviews (N = 9), regarding personal experi-ences of body weight stigma. Results suggest that body stigma is common and that various discriminatoryexperiences led participants away from participating. Given the prevalence of prejudicial behaviors, whichexclude larger individuals, the authors argue for more inclusive physical activity spaces and practices.


2017 ◽  
Vol 4 (1) ◽  
Author(s):  
Mary Claire Worrell ◽  
Michael Kramer ◽  
Aliya Yamin ◽  
Susan M. Ray ◽  
Neela D. Goswami

Abstract Background Tuberculosis (TB) causes significant morbidity and mortality in US cities, particularly in poor, transient populations. During a TB outbreak in Fulton County, Atlanta, GA, we aimed to determine whether local maps created from multiple locations of personal activity per case would differ significantly from traditional maps created from single residential address. Methods Data were abstracted for patients with TB disease diagnosed in 2008–2014 and receiving care at the Fulton County Health Department. Clinical and activity location data were abstracted from charts. Kernel density methods, activity space analysis, and overlay with homeless shelter locations were used to characterize case spatial distribution when using single versus multiple addresses. Results Data were collected for 198 TB cases, with over 30% homeless US-born cases included. Greater spatial dispersion of cases was found when utilizing multiple versus single addresses per case. Activity spaces of homeless and isoniazid (INH)-resistant cases were more spatially congruent with one another than non-homeless and INH-susceptible cases (P < .0001 and P < .0001, respectively). Conclusions Innovative spatial methods allowed us to more comprehensively capture the geography of TB-infected homeless persons, who made up a large portion of the Fulton County outbreak. We demonstrate how activity space analysis, prominent in exposure science and chronic disease, supports that routine capture of multiple location TB data may facilitate spatially different public health interventions than traditional surveillance maps.


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