Neighborhood land use diversity and physical activity in adjacent parks

Department of Kinesiology, Community Health Institute, Kansas State University, Manhattan, KS 66506, USA.
Health & Place (Impact Factor: 2.44). 11/2009; 16(2):413-5. DOI: 10.1016/j.healthplace.2009.11.004
Source: PubMed

ABSTRACT Park availability and land use diversity (LUD) are independent environmental correlates of physical activity (PA). This paper investigated whether parks were more likely to be used for PA if surrounded by greater LUD, as well as the interaction of LUD with the number of facilities in the park for predicting use of the park for PA. Facilities in 32 parks from 4 neighborhoods were audited and LUD around each park was calculated based on the residential, commercial, and institutional hectares within a 500 m polygon buffer. Physical activity log data from 384 adults in the 4 neighborhoods were used to determine which parks were used (18) or not used (14) for PA during the study week. Parks were categorized into four groups (e.g., high LUD/high facilities) using the medians for LUD and number of facilities. Unexpectedly, greater LUD within a park's buffer was related to a lesser likelihood of the park being used for PA. Parks with low LUD and a higher number of facilities were most likely to be used for PA. Some elements contributing to higher LUD around parks may deter PA therein (e.g., commercial areas with busy streets), but greater surrounding LUD may be related to PA in parks among younger or older populations or to other non-active park behaviors.

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    ABSTRACT: We investigated whether a higher number of fast-food outlets in an individual's home neighbourhood is associated with increased prevalence of type 2 diabetes mellitus and related risk factors, including obesity.
    Public Health Nutrition 10/2014; DOI:10.1017/S1368980014002316 · 2.48 Impact Factor
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    ABSTRACT: Introduction: Abundant evidence shows regular physical activity (PA) and time outdoors are effective strategies for preventing obesity and stress in people of all ages. Characteristics of neighborhood environments are a common barrier to PA. The present project analyzes existing, online public web data feeds to assess differences in outdoor PA by neighborhood (census tracts) socio-economic status (SES) in St. Louis, MO. Methods: We are analyzing participant-defined PA routes submitted by users of This website enables participants to track their walking and running routes online, by uploading data from a GPS navigation device. We are visually illustrating the routes using Geographic Information Systems and overlaying routes with indicators of neighborhood SES to examine spatial access and use of parklands and public infrastructure (i.e., sidewalks) for outdoor PA. Results: Pending results from this study can improve technical capability in measuring rates of PA by identifying neighborhood preferences for outdoor walking and running. This can inform land use policy decisions, particularly in inaccessible neighborhood environments, which ought to be structured in ways that can provide residents with resources and opportunities to easily incorporate PA into daily routines. Conclusions: We present a novel effort combining expertise of researchers in urban planning, public health, and communication technology by using inexpensive, unobtrusive, and publicly available web data feeds (i.e., crowd-sourcing) to evaluate neighborhood PA. Understanding neighborhood factors that influence PA have broader urban design and public health implications, especially for vulnerable populations living in neighborhoods with limited or no accessibility to outdoor PA resources.
    141st APHA Annual Meeting and Exposition 2013; 11/2013
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    ABSTRACT: BackgroundParks are valuable resources for physical activity (PA) given their widespread availability and low cost to maintain and use. Both proximity to parks and the availability of particular features are important correlates of PA. However, few studies have explored multiple measures of proximity simultaneously or the specific facilities associated with park use and park-based PA among adults, let alone differences across socio-demographic characteristics. The purpose of this study was to examine associations between park proximity and park facilities and adults? park use and park-based PA, while also exploring differences by gender, age, race, and income.MethodsData on monthly park use and weekly amount of PA undertaken in parks were collected via a mail survey of adults from randomly-selected households (n?=?893) in Kansas City, Missouri (KCMO) in 2010?2011. Three measures of park proximity were calculated within 1 mile of participating households: distance to the closest park, number of parks, and total park area. All parks in KCMO were audited using the Community Park Audit Tool to determine the availability of 14 park facilities within 1 mile of each participant (e.g., trail, playground, tennis court). Multilevel logistic regression was used to examine the relationship between each of park use and park-based PA and 1) three measures of park proximity, and 2) the availability of 14 park facilities within 1 mile of participants. Separate analyses were conducted by gender, age, race, and income, while controlling for all socio-demographic characteristics and BMI.ResultsAcross all sub-samples, distance to the closest park was not significantly related to either park use or park-based PA. However, numerous significant associations were found for the relationship of number of parks and amount of park space within 1 mile with both outcomes. As well, diverse facilities were associated with park use and park-based PA. For both park proximity and facilities, the significant relationships varied widely across gender, age, race, and income groups.ConclusionsBoth park proximity and park facilities are related to park use and park-based PA. Understanding how such associations vary across demographic groups is important in planning for activity-friendly parks that are responsive to the needs of neighborhood residents.
    International Journal of Behavioral Nutrition and Physical Activity 12/2014; 11(1):146. DOI:10.1186/s12966-014-0146-4 · 3.68 Impact Factor


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