Socioeconomic Discrepancies in Children’s Access to Physical Activity Facilities: Activity Space Analysis

2016 ◽  
Vol 2598 (1) ◽  
pp. 11-18 ◽  
Author(s):  
Léa Ravensbergen ◽  
Ron N. Buliung ◽  
Kathi Wilson ◽  
Guy Faulkner
Keyword(s):  
Physical Activity ◽  
Activity Space ◽  
Space Analysis ◽  
Physical Activity Facilities

scholarly journals Use of Activity Space in a Tuberculosis Outbreak: Bringing Homeless Persons Into Spatial Analyses

2017 ◽  
Vol 4 (1) ◽  
Author(s):  
Mary Claire Worrell ◽  
Michael Kramer ◽  
Aliya Yamin ◽  
Susan M. Ray ◽  
Neela D. Goswami
Keyword(s):  
Health Department ◽  
Homeless Persons ◽  
Activity Space ◽  
Exposure Science ◽  
Activity Spaces ◽  
Space Analysis ◽  
Location Data ◽  
Density Methods ◽  
Us Cities ◽  
Traditional Surveillance

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.

Abstract MP38: Local Population Income, Geographic Space and Interactions Predict Increased Presence of Physical Activity Facilities in New York City Metropolitan Area Census Tracts, 1990-2010

Circulation ◽  
2015 ◽  
Vol 131 (suppl_1) ◽  
Author(s):  
David M Wutchiett ◽  
Tanya K Kaufman ◽  
Daniel M Sheehan ◽  
Kathryn M Neckerman ◽  
Andrew G Rundle ◽  
...  
Keyword(s):  
Physical Activity ◽  
New York ◽  
New York City ◽  
Cross Validation ◽  
Local Population ◽  
Median Income ◽  
Census Tracts ◽  
Interaction Terms ◽  
Physical Activity Facility ◽  
Physical Activity Facilities

Introduction: Physical activity is associated with improved health and is supported, in part, by the presence of facilities that provide space and equipment to pursue a variety of physical activities. We assessed the hypothesis that socio-geographic characteristics predict increased local availability of commercial physical activity facilities over time. Longitudinal examination of physical activity facility distribution can inform our response to current disparities in access to public and private physical activity venues. Methods: We used data from the National Establishment Time-Series (NETS), a longitudinal database of U.S. businesses, focusing on 4528 census tracts (23 counties) in the New York City metropolitan area and on decennial intervals for which population data were also available through the Census or American Community Survey (1990, 2000, 2010). Commercial physical activity facilities (e.g., gyms, tennis courts, martial arts studios) were defined based on Standard Industrial Classification (SIC) codes and name searches. Facility counts were aggregated to 2010 census tract boundaries and linked to local population characteristics. Comparisons across decennial intervals were used to define increasing count of physical activity facilities and shifting population demographics. Associations were evaluated using lasso logistic regression to estimate relationships with predictor variables and their interactions with model shrinkage and variable subset selection through 10-fold cross-validation for minimization of test set model deviance. Results: Census tracts with at least one physical activity facility increased over time (1990=1172, 2000=2295, 2010=2365). Greater tract-level median income, larger land area, and higher previous total physical activity facilities at start of decade were positively associated with greater odds for local increase in physical activity facilities (OR=1.27 per SD median income; OR=1.30 per SD land area; OR=1.14 per SD lagged facility count). Inclusion of two-way interaction terms increased R2 estimates from 0.30 to 0.33, suggesting explanation of an additional 3% of the variation in facility count increase. Subset selection through lasso to minimize cross-validation error resulted in retention of 11 of 21 possible two-way predictor interactions. The association between 10-year increase in median income with increased physical activity facility count was stronger in geographically larger census tracts (interaction OR=1.05); similarly, a stronger relationship was found for 10-year population count increase with physical facility count increase in larger census tracts (interaction OR=1.05). Conclusion: Local population, geographic, and business environment characteristics are associated with change in physical activity facilities. Inclusion of interaction terms improved prediction.

scholarly journals Public open spaces and physical activity: disparities of resources in Florianópolis

2019 ◽  
Vol 53 ◽  
pp. 112
Author(s):  
Sofia Wolker Manta ◽  
Rodrigo Siqueira Reis ◽  
Tânia Rosane Bertoldo Benedetti ◽  
Cassiano Ricardo Rech
Keyword(s):  
Physical Activity ◽  
Low Income ◽  
High Income ◽  
Sociodemographic Characteristics ◽  
Open Spaces ◽  
High Quality ◽  
Census Tracts ◽  
Physical Activity Facilities ◽  
Public Open Spaces

ABSTRACT OBJECTIVE: To analyze the association between sociodemographic characteristics of census tracts and the presence/quality of public open spaces and physical activity facilities. METHODS: A cross-sectional study was conducted in 643 census tracts in Florianópolis, Brazil, the presence and quality of public open spaces and physical activity facilities were objectively analyzed and the data by census tracts using Geographic Information Systems was treated. Outcomes were analyzed considering the census tracts as having: ≥ 1 public open spaces; ≥ 1 public open spaces with high quality; ≥ 2 physical activity facilities and high-quality physical activity facilities. Sociodemographic characteristics were the independent variables. Logistic regression analysis was performed. RESULTS: Census tracts with a medium-income (OR = 1.8; 95%CI 1.1–3.0) and high-income (OR = 2.4; 95%CI 1.4–4.0), in those with medium (OR = 1.7; 95%CI 1.0–2.7) and high residential density (OR = 2.0; 95%CI 1,2–3.3), and with higher proportions of older adults (OR = 3.3; 95%CI 1.9–5.7) had a higher proportion of public open spaces. Census tracts with higher proportions of children/adolescents (OR = 0.3; 95%CI 0.2–0.6) and non-white residents (OR= 0.6; 95%CI 0.3–0.9) were less likely to contain public open spaces. The tracts with medium (OR = 4.0; 95%CI 1.4–11.3) and high-income (OR = 3.6; 95%CI 1.2–10.2) were more likely to contain public open spaces with ≥ 2 structures for physical activity, compared with those with low-income. We observed the inverse in sectors with a high proportion of non-white residents (OR = 0.3; 95%CI 0.1–0.9). CONCLUSIONS: Census tracts with higher proportions of children or adolescents, non-white individuals and those in the low-income strata had lower odds of containing public open spaces and physical activity facilities.

ADA Compliance and the Accessibility of Physical Activity Facilities in Western Oregon

2003 ◽  
Vol 17 (3) ◽  
pp. 197-201 ◽  
Author(s):  
Bradley J. Cardinal ◽  
Marc D. Spaziani
Keyword(s):  
Physical Activity ◽  
Customer Service ◽  
Geographic Region ◽  
Limiting Factors ◽  
Structural Domains ◽  
Service Desk ◽  
Direct Observations ◽  
Physical Measurements ◽  
Title Iii ◽  
Physical Activity Facilities

Objectives. One of the mandates of Title III of the Americans With Disabilities Act (ADA) is to address the accessibility of public facilities for all people. The aim of this study was to determine how compliant physical activity facilities in western Oregon were with regard to Title III of the ADA. Comparisons were also made with the findings of a study conducted 5 years prior in a different geographic region. Methods. On the basis of direct observations and physical measurements taken during on-site visits to 50 physical activity facilities located in western Oregon during 2000–2001, facility compliance with Title III of the ADA was characterized in terms of 10 structural domains. Results. No facility was found to be 100% ADA-compliant. Exterior entrance/doors (90%) and telephone accessibility (88%) were the areas where compliance was highest, whereas accessibility to and around exercise equipment (8%) and customer service desk (37%) were areas lowest in compliance. Relative to a previously published study, the facilities in western Oregon showed greater rates of ADA compliance in six of the 10 structural domains evaluated. Conclusions. There is an on-going need and legal mandate for increasing the accessibility of physical activity facilities. Furthermore, from a social-ecological perspective, the environmental constraints identified in this study might be limiting factors in efforts aimed at increasing individuals with disabilities' physical activity involvement.

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