The Faith, Activity, and Nutrition (FAN) dissemination and implementation study: changes in and maintenance of organizational practices over 24 months in a statewide initiative.

BACKGROUND: Few studies have examined the impact of ecological health promotion interventions on organizational practices over time, especially in faith-based settings. This statewide dissemination and implementation study examined change in organizational practices and their predictors across a 24-month period, as well as maintenance of change. METHODS: Using a pre-post quasi-experimental design, church coordinators from 92 United Methodist Churches in South Carolina (42% predominantly African American congregations) completed surveys at baseline, and immediate, 12-, and 24-months post-training regarding physical activity (PA) and healthy eating (HE) organizational practices consistent with the Faith, Activity, and Nutrition (FAN) program (opportunities, policies, pastor support, messages) and possible predictors. The study was guided by the RE-AIM framework and the Consolidated Framework for Implementation Research (CFIR). Mixed model repeated measures analyses examined change in organizational practices over time. Regression models examined CFIR predictors of 24-month PA and HE organizational practices, controlling for baseline practices. Churches were also classified as maintainers (implemented at 12 and 24 months), non-sustained implementers (implemented at 12 but not 24 months), delayed implementers (implemented at 24 but not 12 months), and low implementers (implemented at neither 12 nor 24 months) for each FAN component. RESULTS: PA and HE organizational practices increased over time (p < .0001). CFIR domains (and constructs within) of intervention characteristics (adaptability, relative advantage, cost/time), inner setting (relative priority, organizational rewards, readiness, congregant needs), characteristics of the implementer (self-efficacy, perceived benefits), and implementation process (engaging opinion leaders, engaging champions) were important predictors of 24-month PA and HE organizational practices. Over half of churches implementing PA policies, PA messages, HE policies, and HE opportunities at 12 months were maintainers at 24 months, and one-third were maintainers for PA opportunities, HE messages, and PA and HE pastor support. Furthermore, 16% of 12-month non-implementers were delayed implementers at 24 months for PA policies and 31% were delayed implementers for HE policies. CONCLUSIONS: This study makes important contributions to the faith-based health promotion literature by including a large sample of churches, testing an ecological intervention approach, and assessing organizational practices over a 24-month period. Study findings can guide technical assistance and program adaptations over time. TRIAL REGISTRATION: This study was registered in clinicaltrials.gov NCT02868866 on August 16, 2016.

Assessing the Walkability Environments of Churches in a Rural Southeastern County of the United States.

CONTEXT: Churches can serve as important health promotion partners, especially in rural areas. However, little is known about the built environment surrounding churches in rural areas, including how these environments may impact opportunities for physical activity (PA) and may differ by neighborhood income levels. OBJECTIVE: This study described walkability around churches in a rural county and examined differences in church walkability between high-, medium-, and low-income neighborhoods. DESIGN: As part of the Faith, Activity, and Nutrition study, trained data collectors conducted a windshield survey of adjacent street segments within a half-mile of churches. SETTING: Churches (N = 54) in a rural southeastern county in the United States. MAIN OUTCOME MEASURE: A summary walkability score (eg, presence of sidewalks, safety features, low traffic volume) was created with a possible range from 0 to 7. Analysis of variance was used to assess differences in walkability of churches by neighborhood income levels. RESULTS: Walkability scores ranged from 0 to 6 (M = 2.31, SD = 1.23). Few churches had sidewalks, shoulders or buffers, or amenities nearby. In contrast, most churches had low traffic volume and no environmental incivilities. While not statistically significant, churches in low-income neighborhoods scored higher for walkability than churches in medium- and high-income neighborhoods. CONCLUSIONS: This study used low-cost environmental audits to analyze walkability in a sample of churches in a rural area and examined differences by neighborhood income. While churches may improve reach of people living in underserved and rural communities, a lack of environmental supports may limit effective PA promotion activities. Partnerships focused on improving existing areas or providing alternative PA opportunities for church and community members may be needed, especially in African American communities.

Exploring Disparities in Youth Physical Activity Environments by Income and Non-Hispanic White Population Across the United States.

This study investigated relationships between youth physical activity (PA) environments and income and non-Hispanic White population across the United States, stratified by US Census region and urban-rural designation. For all counties (n = 3142), publicly accessible data were used for sociodemographic indicators (ie, median household income and percent non-Hispanic White population) and a composite PA environment index (including exercise opportunities, violent crime incidence, walkability, and access to public schools). One-way analysis of variance was used to examine differences in PA environment index values according to income and non-Hispanic White population tertiles. There were significant differences in PA environments according to tertiles of income (F = 493.5, P < .001) and non-Hispanic White population (F = 58.6, P < .001), including variations by region and urban-rural designation. Public health practice and policy initiatives, such as joint use agreements, Safe Routes to School programs, and targeted funding allocations, should be used to address more pronounced income-based disparities in Southern and metropolitan counties and race-based disparities in rural and micropolitan counties.

Estimates of Childhood Overweight and Obesity at the Region, State, and County Levels: A Multilevel Small-Area Estimation Approach.

Local-level childhood overweight and obesity data are often used to implement and evaluate community programs, as well as allocate resources to combat overweight and obesity. The most current substate estimates of US childhood obesity use data collected in 2007. Using a spatial multilevel model and the 2016 National Survey of Children's Health, we estimated childhood overweight and obesity prevalence rates at the Census regional division, state, and county levels using small-area estimation with poststratification. A sample of 24,162 children aged 10-17 years was used to estimate a national overweight and obesity rate of 30.7% (95% confidence interval: 27.0%, 34.9%). There was substantial county-to-county variability (range, 7.0% to 80.9%), with 31 out of 3,143 counties having an overweight and obesity rate significantly different from the national rate. Estimates from counties located in the Pacific region had higher uncertainty than other regions, driven by a higher proportion of underrepresented sociodemographic groups. Child-level overweight and obesity was related to race/ethnicity, sex, parental highest education (P < 0.01 for all), county-level walkability (P = 0.03), and urban/rural designation (P = 0.02). Overweight and obesity remains a vital issue for US youth, with substantial area-level variability. The additional uncertainty for underrepresented groups shows surveys need to better target diverse samples.

Incongruency of youth food and physical activity environments in the United States: Variations by region, rurality, and income.

Local environments are increasingly the focus of health behavior research and practice to reduce gaps between fruit/vegetable intake, physical activity (PA), and related guidelines. This study examined the congruency between youth food and PA environments and differences by region, rurality, and income across the United States. Food and PA environment data were obtained for all U.S. counties (N = 3142) using publicly available, secondary sources. Relationships between the food and PA environment tertiles was represented using five categories: 1) congruent-low (county falls in both the low food and PA tertiles), 2) congruent-high (county falls in both the high food and PA tertiles), 3) incongruent-food high/PA low (county falls in high food and low PA tertiles), 4) incongruent-food low/PA high (county falls in low food and high PA tertiles), and 5) intermediate food or PA (county falls in the intermediate tertile for food and/or PA). Results showed disparities in food and PA environment congruency according to region, rurality, and income (p < .0001 for each). Nearly 25% of counties had incongruent food and PA environments, with food high/PA low counties mostly in rural and low-income areas, and food low/PA high counties mostly in metropolitan and high-income areas. Approximately 8.7% of counties were considered congruent-high and were mostly located in the Northeast, metropolitan, and high-income areas. Congruent-low counties made up 10.0% of counties and were mostly in the South, rural, and low-income areas. National and regional disparities in environmental obesity determinants were identified that can inform targeted public health interventions.

Spatial clustering patterns and regional variations for food and physical activity environments across the United States.

This study examined spatial patterns of obesogenic environments for US counties. We mapped the geographic dispersion of food and physical activity (PA) environments, assessed spatial clustering, and identified food and PA environment differences across U.S. regions and rurality categories. Substantial low food score clusters were located in the South and high score clusters in the Midwest and West. Low PA score clusters were located in the South and high score clusters in the Northeast and Midwest (p < .0001). For region, the South had significantly lower food and PA environment scores. For rurality, rural counties had significantly higher food environment scores and metropolitan counties had significantly higher PA environment scores (p < .0001). This study highlights geographic clustering and disparities in food and PA access nationwide. State and region-wide environmental inequalities may be targeted using structural interventions and policy initiatives to improve food and PA access.

Development of a national childhood obesogenic environment index in the United States: differences by region and rurality.

BACKGROUND: Diverse environmental factors are associated with physical activity (PA) and healthy eating (HE) among youth. However, no study has created a comprehensive obesogenic environment index for children that can be applied at a large geographic scale. The purpose of this study was to describe the development of a childhood obesogenic environment index (COEI) at the county level across the United States. METHODS: A comprehensive search of review articles (n = 20) and input from experts (n = 12) were used to identify community-level variables associated with youth PA, HE, or overweight/obesity for potential inclusion in the index. Based on strength of associations in the literature, expert ratings, expertise of team members, and data source availability, 10 key variables were identified - six related to HE (# per 1000 residents for grocery/superstores, farmers markets, fast food restaurants, full-service restaurants, and convenience stores; as well as percentage of births at baby (breastfeeding)-friendly facilities) and four related to PA (percentage of population living close to exercise opportunities, percentage of population < 1 mile from a school, a composite walkability index, and number of violent crimes per 1000 residents). Data for each variable for all counties in the U.S. (n = 3142) were collected from publicly available sources. For each variable, all counties were ranked and assigned percentiles ranging from 0 to 100. Positive environmental variables (e.g., grocery stores, exercise opportunities) were reverse scored such that higher values for all variables indicated a more obesogenic environment. Finally, for each county, a total obesogenic environment index score was generated by calculating the average percentile for all 10 variables. RESULTS: The average COEI percentile ranged from 24.5-81.0 (M = 50.02,s.d. = 9.01) across US counties and was depicted spatially on a choropleth map. Obesogenic counties were more prevalent (F = 130.43,p < .0001) in the South region of the U.S. (M = 53.0,s.d. = 8.3) compared to the Northeast (M = 43.2,s.d. = 6.9), Midwest (M = 48.1,s.d. = 8.5), and West (M = 48.4,s.d. = 9.8). When examined by rurality, there were also significant differences (F = 175.86,p < .0001) between metropolitan (M = 46.5,s.d. = 8.4), micropolitan (M = 50.3,s.d. = 8.1), and rural counties (M = 52.9,s.d. = 8.8) across the U.S. CONCLUSION: The COEI can be applied to benchmark obesogenic environments and identify geographic disparities and intervention targets. Future research can examine associations with obesity and other health outcomes.

Healthy and unhealthy food environments are linked with neighbourhood socio-economic disadvantage: an innovative geospatial approach to understanding food access inequities.

OBJECTIVE: This study examined the separate relationships between socio-economic disadvantage and the density of multiple types of food outlets, and relationships between socio-economic disadvantage and composite food environment indices. DESIGN: Cross-sectional data were analysed using geospatial kernel density techniques. Food outlet data included convenience stores, discount stores, fast-food and fast casual restaurants, and grocery stores. Controlling for urbanicity and race/ethnicity, multivariate linear regression was used to examine the relationships between socio-economic disadvantage and density of food outlets. SETTING: This study occurred in a large Southeastern US county containing 255 census block groups with a total population of 474 266, of which 77·1 % was Non-Hispanic White, the median household income was $48 886 and 15·0 % of residents lived below 125 % of the federal poverty line. PARTICIPANTS: The unit of analysis was block groups; all data about neighbourhood socio-economic disadvantage and food outlets were publicly available. RESULTS: As block group socio-economic disadvantage increased, so too did access to all types of food outlets. The total food environment index, calculated as the ratio of unhealthy food outlets to all food outlets, decreased as block group disadvantage increased. CONCLUSIONS: Those who reside in more disadvantaged block groups have greater access to both healthy and unhealthy food outlets. The density of unhealthy establishments was greater in more disadvantaged areas; however, because of having greater access to grocery stores, disadvantaged populations have less obesogenic total food environments. Structural changes are needed to reduce access to unhealthy food outlets to ensure environmental injustice and reduce obesity risk.

Investigating Socioeconomic Disparities in the Potential Healthy Eating and Physical Activity Environments of Churches.

Faith-based settings have the potential to improve health in underresourced communities, but little research has quantified and compared health-promoting elements in church environments. This study examines the number of potential indoor and outdoor physical activity opportunities, healthy eating opportunities, healthy living media, and total environmental resources present in churches (n = 54) in a rural, southeastern US county and the relationship between these resources and neighborhood income. In our sample, most churches offered potential indoor and outdoor opportunities for physical activity and healthy eating opportunities, with more variability in the number of healthy living media items on display compared to other environmental components. Common potential opportunities present in churches for physical activity included a fellowship hall and green/open space, while potential opportunities for healthy eating frequently included a refrigerator and sink. Compared to those in medium- and high-income neighborhoods, churches in low-income neighborhoods scored higher on measures of potential outdoor physical activity opportunities and lower on measures of total potential environment resources, healthy eating opportunities, healthy living media, and indoor physical activity opportunities, though only indoor physical activity opportunities reached statistical significance. Potential opportunities for using existing resources in and around churches for health promotion should be investigated further, particularly in rural areas.

Personal network characteristics and body mass index: the role of education among Black Americans.

BACKGROUND: Personal (i.e. egocentric) network characteristics are associated with health outcomes, including overweight and obesity. Previous research suggests educational attainment may interact with network characteristics to buffer these relationships. Limited research has examined the personal network characteristics of Black Americans, who have increased risk of overweight and obesity. The purpose of the current study was to examine associations between network characteristics and body mass index (BMI), and whether educational attainment modified these associations among Black Americans. METHODS: In 2014, using respondent-driven sampling, we recruited 430 adult residents of eight low-income neighborhoods in Greenville, SC. Self-administered questionnaires assessed structural and compositional characteristics (i.e. size, density) of respondents' personal networks, socio-demographic characteristics, and health-related behaviors and conditions. Multilevel regression models with robust sandwich estimation accounted for clustering within respondent chains. RESULTS: Among Black adults overall, network density-the number of connections among network members-was positively associated with BMI. Higher education moderated this relationship; among Black adults with a college degree, higher network density was inversely associated with BMI. CONCLUSIONS: Our data suggest low educational attainment may reflect more homogenous and less resourceful networks. Multiple pathways are discussed for how education interacts with network density on BMI among Black Americans.

'We need a safe, walkable way to connect our sisters and brothers': a qualitative study of opportunities and challenges for neighborhood-based physical activity among residents of low-income African-American communities.

OBJECTIVE: The purpose of this study was to explore perceptions of the benefits of and influencing factors for neighborhood-based physical activity (PA), and elicit suggestions for increasing neighborhood-based PA among primarily Black residents living in lower income neighborhoods. DESIGN: Eight focus groups were conducted in low-income, predominantly Black neighborhoods (n = 8) in Greenville, SC during Spring 2014. Using a semi-structured focus group guide with open-ended questions, residents were asked to describe benefits of PA, neighborhood factors associated with PA, and ways to increase PA within their neighborhoods. Trained research assistants transcribed audio recordings verbatim. Using grounded theory and an ecological perspective, emergent coding was employed to generate initial categories with open and axial coding used to achieve consensus on themes. RESULTS: Primarily Black (95%), female (72%), and older (M = 61.5 years) residents (N = 76) participated in the study. Seven themes were identified across the three main focus group topics: physical and mental health benefits of neighborhood PA, safety/hazards and social factors as influencing neighborhood PA, and improving safety, structural opportunities, and programing support to improve neighborhood PA. Most participants reported walking within their communities, despite describing several community-level barriers (e.g. drugs, safety). Residents desired structured neighborhood-based opportunities for increasing PA, including walking tracks and walking groups, and reported social benefits to being active, including increased awareness within the community and trust. Participants conveyed that walking strengthened the social environment of their community as well as the health of residents. CONCLUSION: Few studies of contextual factors and PA have focused on African-American, low-income neighborhoods. Despite diverse environmental constraints, residents reported walking within their communities as part of a healthy lifestyle. Social ecological interventions tailored to promote PA and reduce health disparities among residents of low-income communities should highlight neighborhood-based opportunities for PA, focusing on personal and collective social benefits of neighborhood walking.

E-Media Use and Preferences for Physical Activity and Public Health Information: Results of a Web-Based Survey.

CONTEXT: As social media (eg, Twitter) continues to gain widespread popularity, health research and practice organizations may consider combining it with other electronic media (e-media) channels (eg, Web sites, e-newsletters) within their communication plans. However, little is known about added benefits of using social media when trying to reach public health audiences about physical activity. OBJECTIVE: Learn about current use and preference for e-media communication channels among physical activity researchers and practitioners. DESIGN: A Web-based survey was used, open for responses from August 20, 2015, through January 5, 2016. Survey participation was voluntary and anonymous. The survey was advertised through multiple channels targeting physical activity researchers and practitioners, including announcements on professional listservs and in e-newsletters, Twitter, and posts on Facebook pages of public health organizations. SETTING AND PARTICIPANTS: A total of 284 survey respondents had complete data. MAIN OUTCOME MEASURES: Typical use of e-media to receive, seek out, and share information about physical activity and health and what appeals to researchers and practitioners for professional use. RESULTS: Most respondents preferred non-social media channels to social media and these preferences did not differ widely when examining subgroups such as researchers versus practitioners or social media users versus nonusers. There were few differences by respondent demographics, though younger respondents reported using social media more than older respondents. However, limiting analyses to respondents who identified as social media users, only about 1% of respondents ranked social media sources as their preferred channels for information; thus, most people would continue to be reached if communication remained largely via non-social media e-media channels. CONCLUSIONS: The present study supports growing evidence that careful surveying of a target audience should be undertaken when considering new communication channels, as preference and use may not support the effort required to create and maintain resource-intensive strategies like social media.

Spatial clustering patterns of child weight status in a southeastern US county.

Youth obesity is a major public health concern due to associated physical, social, and psychological health consequences. While rates and disparities of youth obesity levels are known, less research has explored spatial clustering patterns, associated correlates of spatial clustering, comparing patterns in urban and rural areas. Therefore, this study 1) examined spatial clustering of youth weight status, 2) investigated sociodemographic correlates of spatial clustering patterns, and 3) explored spatial patterns by level of urbanization. This study occurred in a southeastern US county (pop:474,266) in 2013. Trained physical education teachers collected height and weight for all 3rd-5th grade youth (n = 13,469) and schools provided youth demographic attributes. BMI z-scores were calculated using standard procedures. Global Moran's Index and Anselin's Local Moran's I (LISA) were used detect global and local spatial clustering, respectively. To examine correlates of spatial clustering, BMI z-score residuals from a series of four linear regression models were spatially analyzed, mapped, and compared. SAS 9.4 and GeoDA were used for analyses; ArcGIS was used for mapping. Significant, positive global clustering (Index = 0.04,p < 0.001) was detected. LISA results showed that about 4.7% (n = 635) and 7.9% (n = 1058) of the sample were identified as high and low obesity localized spatial clusters (p < 0.01), respectively. Individual and neighborhood sociodemographic characteristics accounted for the majority of spatial clustering and differential patterns were observed by level of urbanization. Identifying geographic areas that contain significant spatial clusters is a powerful tool for understanding the location of and exploring contributing factors to youth obesity.

Understanding differences between summer vs. school obesogenic behaviors of children: the structured days hypothesis.

BACKGROUND: Although the scientific community has acknowledged modest improvements can be made to weight status and obesogenic behaviors (i.e., physical activity, sedentary/screen time, diet, and sleep) during the school year, studies suggests improvements are erased as elementary-age children are released to summer vacation. Emerging evidence shows children return to school after summer vacation displaying accelerated weight gain compared to the weight gained occurring during the school year. Understanding how summer days differ from when children are in school is, therefore, essential. DISCUSSION: There is limited evidence on the etiology of accelerated weight gain during summer, with few studies comparing obesogenic behaviors on the same children during school and summer. For many children, summer days may be analogous to weekend days throughout the school year. Weekend days are often limited in consistent and formal structure, and thus differ from school days where segmented, pre-planned, restrictive, and compulsory components exist that shape obesogenic behaviors. The authors hypothesize that obesogenic behaviors are beneficially regulated when children are exposed to a structured day (i.e., school weekday) compared to what commonly occurs during summer. This is referred to as the 'Structured Days Hypothesis' (SDH). To illustrate how the SDH operates, this study examines empirical data that compares weekend day (less-structured) versus weekday (structured) obesogenic behaviors in U.S. elementary school-aged children. From 190 studies, 155 (~80%) demonstrate elementary-aged children's obesogenic behaviors are more unfavorable during weekend days compared to weekdays. CONCLUSION: In light of the SDH, consistent evidence demonstrates the structured environment of weekdays may help to protect children by regulating obesogenic behaviors, most likely through compulsory physical activity opportunities, restricting caloric intake, reducing screen time occasions, and regulating sleep schedules. Summer is emerging as the critical period where childhood obesity prevention efforts need to be focused. The SDH can help researchers understand the drivers of obesogenic behaviors during summer and lead to innovative intervention development.

"We actually care and we want to make the parks better": A qualitative study of youth experiences and perceptions after conducting park audits.

This study explored youths' experiences and perceptions about community engagement as a result of participating in a community-based data collection project using paper and mobile technology park environmental audit tools. In July 2014, youth (ages 11-18, n=50) were recruited to participate in nine focus groups after auditing two parks each using paper, electronic, or both versions of the Community Park Audit Tool in Greenville County, SC. The focus groups explored the youths' experiences participating in the project, changes as a result of participation, suggested uses of park audit data collected, and who should use the tools. Four themes emerged related to youths' project participation experiences: two positive (fun and new experiences) and two negative (uncomfortable/unsafe and travel issues). Changes described as a result of participating in the project fell into four themes: increased awareness, motivation for further action, physical activity benefits, and no change. Additionally, youth had numerous suggestions for utilizing the data collected that were coded into six themes: maintenance & aesthetics, feature/amenity addition, online park information, park rating/review system, fundraising, and organizing community projects. Finally, six themes emerged regarding who the youth felt could use the tools: frequent park visitors, community groups/organizations, parks and recreation professionals, adults, youth, and everyone. This study revealed a wealth of information about youth experiences conducting park audits for community health promotion. Understanding youth attitudes and preferences can help advance youth empowerment and civic engagement efforts to promote individual and community health.

Green and lean: Is neighborhood park and playground availability associated with youth obesity? Variations by gender, socioeconomic status, and race/ethnicity.

Parks and park features are important for promoting physical activity and healthy weight, especially for low-income and racial/ethnic minority youth who have disproportionately high obesity rates. This study 1) examined associations between neighborhood park and playground availability and youth obesity, and 2) assessed whether these associations were moderated by youth race/ethnicity and socioeconomic status (SES). In 2013, objectively measured height and weight were collected for all 3rd-5th grade youth (n=13.469) in a southeastern US county to determine body mass index (BMI) percentiles. Enumeration and audits of the county's parks (n=103) were concurrently conducted. Neighborhood park and playground availability were calculated as the number of each facility within or intersecting each youth's Census block group. Multilevel linear regression models were utilized to examine study objectives. For boys, no main effects were detected; however, SES moderated associations such that higher park availability was associated with lower BMI percentile for low-SES youth but higher BMI percentile for high-SES youth. For girls, the number of parks and playgrounds were significantly associated with lower BMI (b=-2.2, b=-1.1, p<0.05, respectively) and race/ethnicity and SES moderated associations between playground availability and BMI percentile. Higher playground availability was associated with lower BMI percentile for White and high-SES girls but higher BMI percentile for African American and low-SES girls. Considerable variation was detected in associations between park and playground availability and youth obesity by SES and race/ethnicity, highlighting the importance of studying the intersection of these characteristics when exploring associations between built environment features and obesity.

An Initiative to Facilitate Park Usage, Discovery, and Physical Activity Among Children and Adolescents in Greenville County, South Carolina, 2014.

INTRODUCTION: Parks are important settings for increasing population-level physical activity (PA). The objective of this study was to evaluate Park Hop, an incentivized scavenger-hunt-style intervention designed to influence park usage, discovery, park-based PA, and perceptions of parks among children and adolescents in Greenville County, South Carolina. METHODS: We used 2 data collection methods: matched preintervention and postintervention parent-completed surveys and in-park observations during 4 days near the midpoint of the intervention. We used paired-samples t tests and logistic regression to analyze changes in park visitation, perceptions, and PA. RESULTS: Children and adolescents visited an average of 12.1 (of 19) Park Hop parks, and discovered an average of 4.6 venues. In a subset of participants, from preintervention to postintervention, the mean number of park visits increased from 5.0 visits to 6.1 visits, the proportion of time engaged in PA during the most recent park visit increased from 77% to 87%, and parents reported more positive perceptions of the quality of park amenities. We observed more children and adolescents (n = 586) in the 2 intervention parks than in the 2 matched control parks (n = 305). However, the likelihood of children and adolescents engaging in moderate-to-vigorous PA was significantly greater in the control parks (74.3%) than in Park Hop parks (64.2%). CONCLUSION: Park Hop facilitated community-collaboration between park agencies and positively influenced park usage, park discovery, time engaged in PA during park visits, and perceptions of parks. This low-cost, replicable, and scalable model can be implemented across communities to facilitate youth and family-focused PA through parks.

The Effects of a Park Awareness Campaign on Rural Park Use and Physical Activity.

To examine the effects of a park awareness campaign on park use in 6 community parks. One-group pretest-posttest design. Six community parks located in a South Carolina county. Children, adolescents, and adults observed in community parks. A 1-month awareness campaign that culminated in single 1.5-hour events at 6 parks in April 2011 and May 2011. The System for Observing Play and Recreation in Communities was used to objectively measure park use in May 2010 (baseline) and May 2011 (postcampaign). Zero-inflated Poisson models tested whether the number of total park users and the number of park users engaged in sedentary, walking, and vigorous activities differed by observation date. Park use was significantly greater at baseline than postcampaign (97 vs 84 users, respectively; χ = 4.69, P = .03). There were no significant differences in the number of park users engaged in sedentary (χ = 2.45, P = .12), walking (χ = 0.29, P = .59), and vigorous (χ = 0.20, P = .65) activities between baseline and postcampaign. Although only 97 and 84 people were observed across all parks at baseline and postcampaign, a total of 629 people were observed during the 6 separate 1.5-hour campaign park events. This suggests that there is potential for greater park utilization in these communities, and important questions remain on how to conduct effective awareness campaigns and how to harness interest in park events for the purpose of contributing to future community-wide physical activity and health promotion efforts.

ParkIndex: Development of a standardized metric of park access for research and planning.

OBJECTIVE: A lack of comprehensive and standardized metrics for measuring park exposure limits park-related research and health promotion efforts. This study aimed to develop and demonstrate an empirically-derived and spatially-represented index of park access (ParkIndex) that would allow researchers, planners, and citizens to evaluate the potential for park use for a given area. METHODS: Data used for developing ParkIndex were collected in 2010 in Kansas City, Missouri (KCMO). Adult study participants (n=891) reported whether they used a park within the past month, and all parks in KCMO were mapped and audited using ArcGIS 9.3 and the Community Park Audit Tool. Four park summary variables - distance to nearest park, and the number of parks, amount of park space, and average park quality index within 1mile were analyzed in relation to park use using logistic regression. Coefficients for significant park summary variables were used to create a raster surface (ParkIndex) representing the probability of park use for all 100m×100m cells in KCMO. RESULTS: Two park summary variables were positively associated with park use - the number of parks and the average park quality index within 1 mile. The ParkIndex probability of park use across all cells in KCMO ranged from 17 to 77 out of 100. CONCLUSION: ParkIndex represents a standardized metric of park access that combines elements of both park availability and quality, which was developed empirically and can be represented spatially. This tool has both practical and conceptual significance for researchers and professionals in diverse disciplines.