scholarly journals Evaluation of Personal and Built Environment Attributes to Physical Activity: A Multilevel Analysis on Multiple Population-Based Data Sources

2012 ◽  
Vol 2012 ◽  
pp. 1-9 ◽  
Author(s):  
Wei Yang ◽  
Karen Spears ◽  
Fan Zhang ◽  
Wai Lee ◽  
Heidi L. Himler
Keyword(s):  
Physical Activity ◽  
Air Quality ◽  
Spatial Analysis ◽  
Population Density ◽  
Built Environment ◽  
Data Sources ◽  
Environment Factors ◽  
Multiple Data ◽  
Commute Time ◽  
Level Data

Background. Studies have documented that built environment factors potentially promote or impede leisure time physical activity (LTPA). This study explored the relationship between multiple built environment factors and individual characteristics on LTPA.Methods. Multiple data sources were utilized including individual level data for health behaviors and health status from the Nevada Behavioral Risk Factor Surveillance System (BRFSS) and community level data from different data sources including indicators for recreation facilities, safety, air quality, commute time, urbanization, population density, and land mix level. Mixed model logistic regression and geographic information system (GIS) spatial analysis were conducted.Results. Among 6,311 respondents, 24.4% reported no LTPA engagement during the past 30 days. No engagement in LTPA was significantly associated with (1) individual factors: older age, less education, lower income, being obesity, and low life satisfaction and (2) community factors: more commute time, higher crime rate, urban residence, higher population density, but not for density and distance to recreation facilities, air quality, and land mix.Conclusions. Multiple data systems including complex population survey and spatial analysis are valuable tools on health and built environment studies.

scholarly journals Everyday Walking Among Older Adults and the Neighborhood Built Environment: A Comparison Between Two Cities in North America

2020 ◽  
Vol 8 ◽  
Author(s):  
Florian Herbolsheimer ◽  
Atiya Mahmood ◽  
Yvonne L. Michael ◽  
Habib Chaudhury
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Population Density ◽  
Built Environment ◽  
Healthy Aging ◽  
Cross Sectional ◽  
Walking Behavior ◽  
Metro Vancouver ◽  
Walkable Neighborhood ◽  
Neighborhood Built Environment

A walkable neighborhood becomes particularly important for older adults for whom physical activity and active transportation are critical for healthy aging-in-place. For many older adults, regular walking takes place in the neighborhood and is the primary mode of mobility. This study took place in eight neighborhoods in Metro Portland (USA) and Metro Vancouver (Canada), examining older adults' walking behavior and neighborhood built environmental features. Older adults reported walking for recreation and transport in a cross-sectional telephone survey. Information on physical activity was combined with audits of 355 street segments using the Senior Walking Environmental Audit Tool-Revised (SWEAT-R). Multi-level regression models examined the relationship between built environmental characteristics and walking for transport or recreation. Older adults [N = 434, mean age: 71.6 (SD = 8.1)] walked more for transport in high-density neighborhoods and in Metro Vancouver compared to Metro Portland (M = 12.8 vs. M = 2.2 min/day; p < 0.001). No relationship was found between population density and walking for recreation. Older adults spent more time walking for transport if pedestrian crossing were present (p = 0.037) and if parks or outdoor fitness amenities were available (p = 0.022). The immediate neighborhood built environment supports walking for transport in older adults. Comparing two similar metropolitan areas highlighted that high population density is necessary, yet not a sufficient condition for walking in the neighborhood.

scholarly journals Spatial clustering of physical activity and obesity in relation to built environment factors among older women in three U.S. states

2014 ◽  
Vol 14 (1) ◽  
Author(s):  
Kosuke Tamura ◽  
Robin C Puett ◽  
Jaime E Hart ◽  
Heather A Starnes ◽  
Francine Laden ◽  
...  
Keyword(s):  
Physical Activity ◽  
Built Environment ◽  
Older Women ◽  
Spatial Clustering ◽  
Environment Factors

scholarly journals Neighborhood green spaces, facilities and population density as predictors of activity participation among 8-year-olds: a cross-sectional GIS study based on the Norwegian mother and child cohort study

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Emma Charlott Andersson Nordbø ◽  
Ruth Kjærsti Raanaas ◽  
Helena Nordh ◽  
Geir Aamodt
Keyword(s):  
Physical Activity ◽  
Cohort Study ◽  
Population Density ◽  
Built Environment ◽  
Leisure Time ◽  
Green Spaces ◽  
Current Evidence ◽  
Activity Participation ◽  
Social Activities ◽  
Mother And Child

Abstract Background A rapidly growing body of research suggests that qualities of the built environment can promote active living among children and youth. Nevertheless, shortcomings in the current evidence for understanding which built environment characteristics provide opportunities for taking part in activities in childhood remain. This study aimed to examine whether population density, green spaces, and facilities/amenities are associated with participation in leisure-time physical activity (PA), organized activities, and social activities with friends and peers in Norwegian 8-year-olds. Methods Data from a sample of 23,043 children from the Norwegian Mother and Child Cohort Study (MoBa) were linked with geospatial data about the built environment. The questionnaire data reported by mothers provided information on the children’s leisure activities. We computed exposure to neighborhood population density and access to green spaces and facilities/amenities within 800- and 5000-m radii of the participants’ home addresses using geographic information systems. Associations were estimated using logistic regression models. Results We found beneficial associations between having a park within 800-m and more leisure-time PA during the summer. Furthermore, children living in neighborhoods with higher proportions of green space participated in more PA during the winter. More densely populated areas and access to facilities were associated with participation in organized and social activities. Specifically, we observed that more playgrounds/sport fields in the neighborhood were the strongest and most consistent correlate of activity participation in Norwegian 8-year-olds by being related to more socialization with friends and peers. Conclusion This population-based study underscores the importance of access to a variety of venues and opportunities for different activities in the immediate neighborhood surroundings and in the greater community to support participation in physical activity and organized and social activities in childhood.

scholarly journals An ERA-Based Study of Built Environment Factors Affecting Lung Cancer Incidence Rate among Chinese Women

2020 ◽  
Author(s):  
Hongjie Xie ◽  
Qiankun Wang ◽  
Yiping Yang ◽  
Xu Zhang ◽  
Peng zhang
Keyword(s):  
Lung Cancer ◽  
Air Quality ◽  
Built Environment ◽  
Incidence Rate ◽  
Cancer Incidence ◽  
Chinese Women ◽  
Lung Cancer Incidence ◽  
Quality Factors ◽  
Cancer Incidence Rate ◽  
Environment Factors

Objective: Application of ERA methods to investigate the atmospheric pollution and built environment factors influencing lung cancer incidence rate in Chinese women. Methods: Lung cancer incidence rate among Chinese women at 339 cancer registries were obtained from the China Cancer Registry Annual Report 2017, air quality and built environment data were obtained from the Greenpeace and China Construction Yearbook. After multiple covariates variables were eliminated, an exploratory regression analysis was performed using the world standardized population incidence rate as the dependent variable. Air quality and built environment factors as the independent variable. Results: Shandong Peninsula, Hebei and Liaoning are high incidence rate areas of female lung cancer in China, with significant regional aggregation. In addition to air quality factors such as industrial smoke emission data, the association between built environmental factors such as urbanization rate, development LUI, population density and greening coverage of built-up areas and female lung cancer incidence rate is statistically significant. Conclusion: In addition to air quality factors, urban spatial factors can also significantly affect respiratory health. The LUI is positively while urbanization rates and population density are negatively correlated with the incidence rate of lung cancer. The role of green space for respiratory health has not been proven. In addition, there is little relationship between income and health, and similar findings are found for indicators such as the public transportation and roads network.

scholarly journals Interactions between psychosocial and built environment factors in explaining older adults' physical activity

2012 ◽  
Vol 54 (1) ◽  
pp. 68-73 ◽  
Author(s):  
Jordan A. Carlson ◽  
James F. Sallis ◽  
Terry L. Conway ◽  
Brian E. Saelens ◽  
Lawrence D. Frank ◽  
...  
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Built Environment ◽  
Environment Factors

Particular matter prediction using synergy of multiple source urban big data in smart cities

2021 ◽  
pp. 1-15
Author(s):  
Ali Reza Honarvar ◽  
Ashkan Sami
Keyword(s):  
Air Pollution ◽  
Big Data ◽  
Air Quality ◽  
Smart Cities ◽  
Data Sources ◽  
Quality Data ◽  
Data Set ◽  
Multiple Data Sources ◽  
Multiple Data ◽  
Air Quality Data

At present, the issue of air quality in populated urban areas is recognized as an environmental crisis. Air pollution affects the sustainability of the city. In controlling air pollution and protecting its hazards from humans, air quality data are very important. However, the costs of constructing and maintaining air quality registration infrastructure are very expensive and high, and air quality data recording at one point will not be generalizable to even a few kilometers. Some of the gains come from the integration of multiple data sources, which can never be achieved through independent single-source processing. Urban organizations in each city independently produce and record data relevant to the organization’s goals and objectives. These issues create separate data silos associated with an urban system. These data are varied in model and structure, and the integration of such data provides an appropriate opportunity to discover knowledge that can be useful in urban planning and decision making. This paper aims to show the generality of our previous research, which proposed a novel model to predict Particulate Matter (PM) as the main factor of air quality in the regions of the cities where air quality sensors are not available through urban big data resources integration, by extending the model and experiments with various configuration for different settings in smart cities. This work extends the evaluation scenarios of the model with the extended dataset of city of Aarhus, in Denmark, and compare the model performance against various specified baselines. Details of removing the heterogeneity of multiple data sources in the Multiple Data Set Aggregator & Heterogeneity Remover (MDA&HR) and improving the operation of Train Data Splitter (TDS) part of the model by focusing on the finding more similar pattern of air quality also are presented in this paper. The acceptable accuracy of the results shows the generality of the model.

scholarly journals Association between private and public places and practice of physical activity in adults

2016 ◽  
Vol 18 (3) ◽  
pp. 297 ◽  
Author(s):  
Priscila Missaki Nakamura ◽  
Inaian Pignatti Teixeira ◽  
Adriano Akira F Hino ◽  
Jacqueline Kerr ◽  
Eduardo Kokubun
Keyword(s):  
Physical Activity ◽  
Built Environment ◽  
Leisure Time ◽  
Leisure Time Physical Activity ◽  
Adult Population ◽  
Moderate Intensity ◽  
Environment Factors ◽  
Negatively Associated ◽  
Moderate Intensity Physical Activity ◽  
Intensity Physical Activity

DOI: http://dx.doi.org/10.5007/1980-0037.2016v18n3p297 There are some studies that showed the relationship between built environment with practice of physical activity during leisure-time and active transportation in the adult population. However, this relationship may be influence by type and intensity of physical activity. The aim of this study was to verify association between public and private places for engaging in different types of physical activity in adults of Rio Claro City, Brazil. Cross sectional study with representative sample of 1588 adults with a mean age of 45.7±17.0 years completed the IPAQ-long form. Geographic Information System data were employed to assess the built environment. The time to different physical activity types were divided in actives (≥10 min/week) and inactive (<10 min/week). Poisson Multilevel Regression Analysis was performed in the Stata version 12.0. After adjusting for confounders, walking during leisure-time was positively associated with São Paulo’s Social Vulnerability Index (SSVI) categories of 1 (PR=2.77) through 5 (PR=1.94) and negatively associated with population density higher than 68 km/m2 (PR=0.70). Vigorous intensity physical activity was negatively associated with distance greater than 596 metes of private places to practice physical activity (PR=0.50). Total leisure time physical activity was positively associated with SSVI 1 (PR=2.48) and 5 (RP=1.89). Moderate intensity physical activity was not associated with built environment factors. There were differents associations between the built environment factors with leisure time PA except to moderate intensity physical activity.

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