Implementation characteristics that may promote sustainability of a rural physical activity initiative: examination of Play Streets through the lens of community implementers

BACKGROUND

Play Streets, which are community-based environmental initiatives where public spaces/streets are temporarily closed to create safe, low-cost physical activity opportunities, have demonstrated feasibility and physical activity benefit in rural US areas. Yet, information is needed to identify implementation characteristics that may promote sustainability. This study examined rural Play Streets implementation characteristics that could impact sustainability from local partners' perspectives.

METHODS

Sixteen Play Streets implementation team members in rural Maryland, North Carolina, Oklahoma, and Texas, USA, participated in interviews. Semi-structured in-person individual and group interviews were conducted in the fall of 2018 (after Play Streets implementation in 2017 and 2018), recorded, and transcribed verbatim. Transcripts were analyzed using iterative, content analyses. Coding frameworks were based on the Public Health Program Capacity for Sustainability Framework, and emergent themes were also identified.

RESULTS

Interviewees' perceived characteristics for facilitating Play Streets implementation aligned with the Public Health Program Capacity for Sustainability Framework: funding stability, political support, partnerships, organizational capacity, program adaption, and communication. Interviewees also noted the importance of cultural alignment/support and the reciprocal impact of community connectedness/engagement.

CONCLUSIONS

Future research should examine the reciprocal role of public health impacts, as both outcomes and factors which may influence sustainability.

Identifying multilevel predictors of behavioral outcomes like park use: A comparison of conditional and marginal modeling approaches

This study compared marginal and conditional modeling approaches for identifying individual, park and neighborhood park use predictors. Data were derived from the ParkIndex study, which occurred in 128 block groups in Brooklyn (New York), Seattle (Washington), Raleigh (North Carolina), and Greenville (South Carolina). Survey respondents (n = 320) indicated parks within one half-mile of their block group used within the past month. Parks (n = 263) were audited using the Community Park Audit Tool. Measures were collected at the individual (park visitation, physical activity, sociodemographic characteristics), park (distance, quality, size), and block group (park count, population density, age structure, racial composition, walkability) levels. Generalized linear mixed models and generalized estimating equations were used. Ten-fold cross validation compared predictive performance of models. Conditional and marginal models identified common park use predictors: participant race, participant education, distance to parks, park quality, and population >65yrs. Additionally, the conditional mode identified park size as a park use predictor. The conditional model exhibited superior predictive value compared to the marginal model, and they exhibited similar generalizability. Future research should consider conditional and marginal approaches for analyzing health behavior data and employ cross-validation techniques to identify instances where marginal models display superior or comparable performance.

Unearthing Inequities in the Relationship between Multiple Sociodemographic Factors and Diverse Elements of Park Availability and Quality in a Major Southern Metropolitan Region

Parks are critical components of healthy communities. This study explored neighborhood socioeconomic and racial/ethnic inequalities in park access and quality in a large U.S. southeastern metropolitan region. A total of 241 block groups were examined, including 77 parks. For each block group, we obtained multiple sociodemographic indicators, including unemployment rate, education level, renter-occupied housing, poverty rate, and racial/ethnic minority composition. All parks were mapped using geographical information systems and audited via the Community Park Audit Tool to evaluate their features and quality. We analyzed seven diverse elements of park quality (transportation access, facility availability, facility quality, amenity availability, park aesthetics, park quality concerns, and neighborhood quality concerns), as well as an overall park quality score by calculating the mean for all parks within each block group. The mean percent of residents below 125% of the poverty level and the percentage of renter-occupied housing units were significantly higher among block groups with any parks in comparison to block groups with no parks. In addition, there were significant positive associations between park transportation access scores and both the percentage of residents with less than high school education and the percent identifying as non-Hispanic white. Moreover, there was a significant negative association between park amenity availability and the block group's unemployed population. Further, a significant negative association between park aesthetics and the population with a lower than high school education percentage was observed. Revealed differences in park availability, park acreage, and park quality dimensions emphasized the need for targeted policy, programmatic, and infrastructure interventions to improve park access and quality and address health disparities.

Physical Activity Policy, Systems, and Environment Change Through Extension SNAP-Ed: A Multistate Perspective

The Supplemental Nutrition Assistance Program-Education (SNAP-Ed) provides nutrition education and support for healthy living in SNAP-qualifying communities. SNAP-Ed supports policy, systems, and environmental (PSE) efforts to make the healthy choice an easier choice. SNAP-Ed implementers have widely adopted healthy eating PSE supports. However, physical activity (PA) PSE strategies are less common, with limited awareness between states of how other SNAP-Ed implementers approach PA-focused PSE work. Physical Activity Policy, Research, and Evaluation Network (PAPREN) Rural Active Living Workgroup project members sought to explore how Extension-based SNAP-Ed implements PA-focused PSE approaches. A sample of Extension-based SNAP-Ed program (n = 8) leaders were purposefully recruited from eligible universities in six of the seven SNAP-Ed regions. An interview guide to systematically collect information about current Extension SNAP-Ed implementation focused on PA PSE strategies was developed iteratively by the PAPREN Rural Active Living Workgroup Extension PA PSE project team. PA PSE Extension SNAP-Ed implementation efforts occurred at the state, county, and community levels and/or within local organizations. PA PSEs included school PA policy change, shared-use agreements, active transportation promotion, park development, walking challenges, and PA-promoting signage. All interviews highlighted the importance of partnerships at local, county, and state levels for PSE efforts. Extension-based SNAP-Ed shows potential to bring community partners together to plan and implement PA-focused PSE approaches. With a focus on SNAP-eligible people and substantial geographic reach, Extension SNAP-Ed is uniquely situated as a public health partner to broadly implement PA PSE changes.

Depressive Symptoms and Their Longitudinal Impact on Physical Activity and Sedentary Behaviors Among Mexican-Heritage Youth

The purpose of this study is to examine the longitudinal impact of depressive symptoms on physical activity (PA) levels, sedentary behavior, and screen time among first-generation, Mexican-heritage youth. Mexican-heritage families were recruited by promotoras de salud from colonias in Hidalgo County, Texas. Participants (n = 200 youth, 116 families in final sample) completed at-home, interviewer-administered surveys once during the summer (June-July) and once during the fall (August-December). Youth PA and sedentary behaviors were assessed using a validated 7-day recall instrument. The validated Center for Epidemiology Studies-Depression Child scale was used to assess depression symptoms. Linear mixed-effects models were used to analyze the relationships of PA and sedentary behavior with depressive symptoms. Results showed that those depression symptoms were significantly associated with decreased number of self-reported minutes of sitting and screen time over time in the full sample and among male youth. Depression symptoms also significantly decreased the number of self-reported active and moderate to vigorous PA minutes over time among male youth. Researchers can build on our findings by identifying the mechanisms driving the relationships between depression and PA/sedentary behavior. Public health-programing efforts should intentionally consider the impact that depressive symptoms have on PA.

Neighborhood Socioeconomic Status, Green Space, and Walkability and Risk for Falls Among Postmenopausal Women: The Women's Health Initiative

PURPOSE

This study estimated associations between neighborhood socioeconomic status (NSES), walkability, green space, and incident falls among postmenopausal women and evaluated modifiers of these associations, including study arm, race and ethnicity, baseline household income, baseline walking, age at enrollment, baseline low physical functioning, baseline fall history, climate region, and urban-rural residence.

METHODS

The Women's Health Initiative recruited a national sample of postmenopausal women (50-79 years) across 40 U.S. clinical centers and conducted yearly assessments from 1993 to 2005 (n = 161,808). Women reporting a history of hip fracture or walking limitations were excluded, yielding a final sample of 157,583 participants. Falling was reported annually. NSES (income/wealth, education, occupation), walkability (population density, diversity of land cover, nearby high-traffic roadways), and green space (exposure to vegetation) were calculated annually and categorized into tertiles (low, intermediate, high). Generalized estimating equations assessed longitudinal relationships.

RESULTS

NSES was associated with falling before adjustment (high vs. low, odds ratio, 1.01; 95% confidence interval, 1.00-1.01). Walkability was significantly associated with falls after adjustment (high vs. low, odds ratio, 0.99; 95% confidence interval, 0.98-0.99). Green space was not associated with falling before or after adjustment. Study arm, race and ethnicity, household income, age, low physical functioning, fall history, and climate region modified the relationship between NSES and falling. Race and ethnicity, age, fall history, and climate region modified relationships between walkability and green space and falling.

CONCLUSIONS

Our results did not show strong associations of NSES, walkability, or green space with falling. Future research should incorporate granular environmental measures that may directly relate to physical activity and outdoor engagement.

Urban-rural disparities in childhood obesogenic environments in the United States: Application of differing rural definitions

BACKGROUND

Research is needed that identifies environmental resource disparities and applies multiple rural definitions. Therefore, this study aims to examine urban-rural differences in food and physical activity (PA) environment resource availability by applying several commonly used rural definitions. We also examine differences in resource availability within urban-rural categories that are typically aggregated.

METHODS

Six food environment variables (access to grocery/superstores, farmers' markets, fast food, full-service restaurants, convenience stores, and breastfeeding-friendly facilities) and 4 PA environment variables (access to exercise opportunities and schools, walkability, and violent crimes) were included in the childhood obesogenic environment index (COEI). Total COEI, PA environment, and food environment index scores were generated by calculating the average percentile for related variables. US Department of Agriculture Urban Influence Codes, Office of Management and Budget codes, Rural-Urban Continuum Codes, Census Bureau Population Estimates for percent rural, and Rural Urban Commuting Area Codes were used. One-way ANOVA was used to detect urban-rural differences.

RESULTS

The greatest urban-rural disparities in COEI (F=310.2, P<.0001) and PA environment (F=562.5, P<.0001) were seen using RUCC codes. For food environments, the greatest urban-rural disparities were seen using Census Bureau percent rural categories (food: F=24.9, P<.0001). Comparing remote rural categories, differences were seen for food environments (F=3.1, P=.0270) and PA environments (F=10.2, P<.0001). Comparing metro-adjacent rural categories, differences were seen for PA environment (F=4.7, P=.0090).

CONCLUSION

Findings inform future research on urban and rural environments by outlining major differences between urban-rural classifications in identifying disparities in access to health-promoting resources.

Developing criteria for research translation decision-making in community settings: a systematic review and thematic analysis informed by the Knowledge to Action Framework and community input

Background

There is a pressing need to translate empirically supported interventions, products, and policies into practice to prevent and control prevalent chronic diseases. According to the Knowledge to Action (K2A) Framework, only those interventions deemed “ready” for translation are likely to be disseminated, adopted, implemented, and ultimately institutionalized. Yet, this pivotal step has not received adequate study. The purpose of this paper was to create a list of criteria that can be used by researchers, in collaboration with community partners, to help evaluate intervention readiness for translation into community and/or organizational settings.

Methods

The identification and selection of criteria involved reviewing the K2A Framework questions from the “decision to translate” stage, conducting a systematic review to identify characteristics important for research translation in community settings, using thematic analysis to select unique research translation decision criteria, and incorporating researcher and community advisory board feedback.

Results

The review identified 46 published articles that described potential criteria to decide if an intervention appears ready for translation into community settings. In total, 17 unique research translation decision criteria were identified. Of the 8 themes from the K2A Framework that were used to inform the thematic analysis, all 8 were included in the final criteria list after research supported their importance for research translation decision-making. Overall, the criteria identified through our review highlighted the importance of an intervention’s public health, cultural, and community relevance. Not only are intervention characteristics (e.g., evidence base, comparative effectiveness, acceptability, adaptability, sustainability, cost) necessary to consider when contemplating introducing an intervention to the “real world,” it is also important to consider characteristics of the target setting and/or population (e.g., presence of supporting structure, support or buy-in, changing sociopolitical landscape).

Conclusions

Our research translation decision criteria provide a holistic list for identifying important barriers and facilitators for research translation that should be considered before introducing an empirically supported intervention into community settings. These criteria can be used for research translation decision-making on the individual and organizational level to ensure resources are not wasted on interventions that cannot be effectively translated in community settings to yield desired outcomes.

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.

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.

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.

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.

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.

Gestational weight gain disparities in South Carolina: Temporal trends, 2004-2015

BACKGROUND

Few studies have examined secular trends in gestational weight gain (GWG) and findings are inconsistent. Parallel to increasing trends in pre-pregnancy obesity, we hypothesised similar increasing GWG trends.

OBJECTIVES

The study examined trends in GWG in South Carolina (SC), using methods to reduce bias. We also examined whether the 12-year trends in GWG varied according to race/ethnicity and pre-pregnancy weight.

METHODS

Data came from SC birth certificates, 2004 to 2015. We calculated standardised GWG z-scores (GWGZ), using smoothed reference values to account for gestational age and pre-pregnancy body mass index. Quantile regression was used to examine trends in GWGZ, adjusting for pre-pregnancy weight status, race/ethnicity, parity, WIC participation, smoking during pregnancy, residence, age, and birth cohort.

RESULTS

Among 615 093 women, the mean GWGZ was -0.4 (SD = 1.3), which increased from -0.4 in 2004-2005 to -0.2 in 2014-2015. GWGZ increased at the 5th, 10th, 25th, 50th, and 75th percentiles (ranging 0.04 to 0.73 units), with differential trends observed in sub-groups by pre-pregnancy weight and racial/ethnic group. Notably, non-Hispanic White women showed larger increasing trends (0.89 units) compared to non-Hispanic Black (0.55 units) and Hispanic (0.76 units) women in the 5th percentile. Decreasing trends were seen overall for the 90th (-0.02) and 95th percentile (-0.06 units) but positive trends were not seen among women experiencing obese class 1 (no change in 90th and 95th), and 2 (0.01 units in 90th, -0.02 units in 95th).

CONCLUSIONS

This study shows increasing GWGZ trends from the 5th to the 75th percentiles and decreasing trends in 90th and 95th percentiles in SC for the last decade. Racial/ethnic and pre-pregnancy weight disparities did not improve over the study period. Future research is needed to confirm these findings in other states and to develop strategies to narrow racial and pre-pregnancy weight disparities at the highest and lowest percentiles.

ParkIndex: Validation and application of a pragmatic measure of park access and use

Composite metrics integrating park availability, features, and quality for a given address or neighborhood are lacking. The purposes of this study were to describe the validation, application, and demonstration of ParkIndex in four diverse communities. This study occurred in Fall 2018 in 128 census block groups within Seattle(WA), Brooklyn(NY), Raleigh(NC), and Greenville County(SC). All parks within a half-mile buffer were audited to calculate a composite park quality score, and select households provided data about use of proximal parks via an online, map-based survey. For each household, the number of parks, total park acreage, and average park quality score within one half-mile were calculated using GIS. Logistic regression was used to identify a parsimonious model predicting park use. ParkIndex values (representing the probability of park use) were mapped for all study areas and after scenarios involving the addition and renovation/improvement of parks. Out of 360 participants, 23.3% reported visiting a park within the past 30 days. The number of parks (OR = 1.36, 95% CI = 1.15-1.62), total park acreage (OR = 1.13, 95% CI = 1.07-1.19), and average park quality score (OR = 1.04, 95% CI = 1.01-1.06) within one half-mile were all associated with park use. Composite ParkIndex values across the study areas ranged from 0 to 100. Hypothetical additions of or renovations to study area parks resulted in ParkIndex increases of 22.7% and 19.2%, respectively. ParkIndex has substantial value for park and urban planners, citizens, and researchers as a common metric to facilitate awareness, decision-making, and intervention planning related to park access, environmental justice, and community health.

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.