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S. Morgan Hughey, Marilyn E. Wende, Ellen W. Stowe, Andrew T. Kaczynski, Jasper Schipperijn, and J. Aaron Hipp

associated with higher park use and PA levels. 14 – 16 Other studies have focused on PA patterns within parks among park users, utilizing direct observation and in-park surveys. 17 – 19 For example, the first national study of neighborhood parks used systematic observation to estimate the number of weekly

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Mika R. Moran, Perla Werner, Israel Doron, Neta HaGani, Yael Benvenisti, Abby C. King, Sandra J. Winter, Jylana L. Sheats, Randi Garber, Hadas Motro, and Shlomit Ergon

, Werner, Amburgey, & Szalay, 2007 ; Christensen, Mikkelsen, Nielsen, & Harder, 2011 ; Holt, Spence, Sehn, & Cutumisu, 2008 ; Montemurro et al., 2011 ; Spessot, 2015 ; Strath, Isaacs, & Greenwald, 2007 ), and most of those studies relied on the home-neighborhood approach. This approach seeks to

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Greg Lindsey, Yuling Han, Jeffrey Wilson, and Jihui Yang


To model urban trail traffic as a function of neighborhood characteristics and other factors including weather and day of week.


We used infrared monitors to measure traffic at 30 locations on five trails for periods ranging from 12 months to more than 4 y. We measured neighborhood characteristics using geographic information systems, satellite imagery, and US Census and other secondary data. We used multiple regression techniques to model daily traffic.


The statistical model explains approximately 80% of the variation in trail traffic. Trail traffic correlates positively and significantly with income, neighborhood population density, education, percent of neighborhood in commercial use, vegetative health, area of land in parking, and mean length of street segments in access networks. Trail traffic correlates negatively and significantly with the percentage of neighborhood residents in age groups greater than 64 and less than 5.


Trail traffic is significantly correlated with neighborhood characteristics. Health officials can use these findings to influence the design and location of trails and to maximize opportunities for increases in physical activity.

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Fuzhong Li, K. John Fisher, Adrian Bauman, Marcia G. Ory, Wojtek Chodzko-Zajko, Peter Harmer, Mark Bosworth, and Minot Cleveland

Over the past few years, attention has been drawn to the importance of neighborhood influences on physical activity behavior and the need to consider a multilevel analysis involving not only individual-level variables but also social-and physical-environment variables at the neighborhood level in explaining individual differences in physical activity outcomes. This new paradigm raises a series of issues concerning systems of influence observed at different hierarchical levels (e.g., individuals, neighborhoods) and variables that can be defined at each level. This article reviews research literature and discusses substantive, operational, and statistical issues in studies involving multilevel influences on middle-aged and older adults’ physical activity. To encourage multilevel research, the authors propose a model that focuses attention on multiple levels of influence and the interaction among variables characterizing individuals, among variables characterizing neighborhoods, and across both levels. They conclude that a multilevel perspective is needed to increase understanding of the multiple influences on physical activity.

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Ka-Man Leung, Pak-Kwong Chung, Tin-Lok Yuen, Jing Dong Liu, and Donggen Wang

, encouragement, role models, and neighborhood social cohesion. Companionship refers to people walking with partners instead of walking alone. Cleland et al. ( 2010 ) found that engaging in PA with friends or colleagues increased women’s participation in both leisure-time and transport-related PA. Encouragement

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Gohei Kato, Tomoyuki Arai, Yasuhiro Morita, and Hiroaki Fujita

facilitation domains of the Japanese version of Home and Community Environment ( Kato, Tamiya, Kashiwagi, & Akasaka, 2010 ; Keysor et al., 2005 ) were used to assess the subjective factors of the built environment at a neighborhood level. Objective built environmental factors Existences of built environment

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Venurs H.Y. Loh, Jerome N. Rachele, Wendy J. Brown, Fatima Ghani, and Gavin Turrell

Residents of socioeconomically disadvantaged neighborhoods have significantly poorer physical function than their counterparts residing in more advantaged neighborhoods. 1 Physical function is defined as one’s ability to perform various activities that require physical capacity, ranging from

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Yu-Tzu Wu, Natalia R. Jones, Esther M.F. van Sluijs, Simon J. Griffin, Nicholas J. Wareham, and Andrew P. Jones

We examine the relative importance of both objective and perceived environmental features for physical activity in older English adults. Self-reported physical activity levels of 8,281 older adults were used to compute volumes of outdoor recreational and commuting activity. Perceptions of neighborhood environment supportiveness were drawn from a questionnaire survey and a geographical information system was used to derive objective measures. Negative binominal regression models were fitted to examine associations. Perceptions of neighborhood environment were more associated with outdoor recreational activity (over 10% change per standard deviation) than objective measures (5–8% change). Commuting activity was associated with several objective measures (up to 16% change). We identified different environmental determinants of recreational and commuting activity in older adults. Perceptions of environmental supportiveness for recreational activity appear more important than actual neighborhood characteristics. Understanding how older people perceive neighborhoods might be key to encouraging outdoor recreational activity.

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Javier Molina-García and Ana Queralt

Active commuting to school (ACS) significantly contributes to physical activity levels and health in children 1 ; however, ACS is declining due to the increasing use of motorized vehicles. 2 , 3 According to ecological models of health behavior, 4 neighborhood type is a particularly important

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Bradley M. Appelhans and Hong Li


This study tested associations of organized sports participation and unstructured active play with overall moderate and vigorous physical activity (MVPA) in low-income children and examined factors associated with participation frequency.


Research staff visited 88 low-income Chicago households with children ages 6–13 years. MVPA was assessed through 7-day accelerometry. Researchers documented the home availability of physical activity equipment. Caregivers reported on child participation in organized sports and unstructured active play, family support for physical activity, perceived neighborhood safety, and access to neighborhood physical activity venues.


Despite similar participation in organized sports and unstructured active play, boys accumulated more MVPA than girls. MVPA was predicted by an interaction between gender and unstructured active play. Boys accumulated 23–45 additional minutes of weekday MVPA and 53–62 additional minutes of weekend MVPA through unstructured active play, with no such associations in girls. Higher reported neighborhood safety and family support for physical activity were associated with engagement in unstructured active play for both genders, and with participation in organized sports for girls.


Physical activity interventions for low-income, urban children should emphasize unstructured active play, particularly in boys. Fostering family support for physical activity and safe play environments may be critical intervention components.