Background: A growing body of literature argues the value of park and playground access to pediatric health outcomes. These findings have not been examined broadly across the United States in a single study that combines physical and mental health outcomes. Objective: To determine whether access to a neighborhood parks and playgrounds predicts differences in physical activity, BMI, depression or anxiety in children and adolescents. Methodology: We examined a large national random sample (N=49,146) of children ages 0-17 in the US conducted in 2016. Parents reported access to a neighborhood park or playground, physical activity (days per week with 60 minutes of exercise), overweight (BMI), and current physician-diagnosed anxiety or depression for one randomly selected child per family. Results: Approximately 24% of children in America (n=11,791) live in neighborhoods with no park access; 30% (N=8,810) live in a major city; 9.8% (N=4,929) live below the federal poverty level, 5.6% ( N=2,812) did not play or exercise even one day in the last week, 13% (N=6,575) of children ages 10 -17 were either overweight or obese; 10% (N=4,358) have a physician-diagnosed anxiety; 5% (N=2,142) have physician-diagnosed depression. Living in a major city is not a meaningful predictor of park access (RR=.97, p=.581); living below the federal poverty limit leads to an increased odds of living in a neighborhood with no park (OR=1.25, p<.001). Lack of a neighborhood park/playground predicted whether a child was inactive each week (OR=1.5, p<.001), overweight (RR=1.17, p<.001), had a diagnosis of anxiety (OR 1.13, p<.001) or depression (OR=1.23, p<0.000). The findings held after adjustment for family income, parental education, sex, age, and race/ethnicity of the child. Conclusions: Park access has a modest association with child physical activity, BMI, depression and anxiety. Provision of parks and playgrounds in neighborhoods could be a feasible intervention to improve pediatric health.

Background: Urban parks provide access to natural environments for expanding urban populations. The International Federation of Parks and Recreation Administration (IFPRA) concluded in their 2013 report “Benefits of Urban Parks” that parks promote health indirectly through increased physical activity and may contribute to reduced obesity. Other health benefits showed positive trends, but more research was needed to strengthen the evidence.

Objectives: To support decision-making concerning a new city-wide park, we conducted a rapid review of the literature published from January 2010 to January 2019 to extend findings from the 2013 IFPRA report on the health benefits of urban parks.

Methods: We conducted systematic searches on the Web of Science and Scopus databases, retrieving a total of 8,970 articles. Focusing on over 300 “review” articles, after title and abstract screening, we selected 32 articles for full-text analysis.

Results: Reflecting the trends in original research, a large number of reviews were published in the last decade. However, many reviews were not systematic (e.g., lacked study quality evaluation) and few focused on urban parks. Limitations in study design and quality were noted, including predominance of cross-sectional studies, small sample sizes, and lack of accounting for individual access and preferences. Recent reviews reported that urban natural environments were associated with decreased all-cause and cardiovascular mortality, improved mental health and well-being, benefits to birth weight, improved overall health and cognitive development of children, improved disability-related impairments (when parks were accessible), and benefits for sleep. There were mixed findings regarding beneficial effects on physical activity and obesity.

Conclusion: Since the 2013 IFPRA report, evidence for health benefits of urban parks is stronger, but studies with improved research designs and overall quality are needed to clarify associations.

Background. Greater community mobility and participation among individuals with disabilities are associated with better health-related outcomes. Past studies have generally used self-report measures of community participation, which have numerous limitations. More recently, researchers have attempted to employ tools like Global Positioning Systems (GPS) to measure mobility and participation, and there is some preliminary evidence for the validity of these measures. However, GPS tracking over a long period of time involves considerable costs and participant burden, and the data analyses are time intensive. The current study aims to examine whether using GPS to track individuals over shorter periods of time will yield similar, and valid, estimates of mobility and participation.

Methods. 120 individuals with serious mental illnesses residing in Southeastern Pennsylvania were tracked with GPS-enabled cell phones at 1-minute intervals over a 13 day period. We used a spatiotemporal data mining algorithm to identify the total 1) number of destinations; 2) time spent outside of home; and 3) total distance traveled. These variables were calculated for the entire 13 day study period, and for randomly selected portions of this period consisting of 10, 7, 5 and 3 days. In addition, individuals were asked to complete a self-report community participation questionnaire, from which we computed the total amount of participation. Pearson correlations will be used to examine the extent to which GPS variables calculated for the 13-, 10-, 7-, 5- and 3- day periods were associated with one another, and with the self-reported community participation measure.

Results. Analyses will be completed by August 2019.

Implications. These results will provide recommendations on the optimal duration of the GPS tracking period. For example, if shorter tracking periods are appropriate, then this will help avoid unnecessary research costs and participant burden. Furthermore, issues related to missing data will be discussed.

In a previous study conducted by Cook County Department of Public Health (CCDPH), Benedictine University, and Loyola University of Chicago, we investigated quantifiable measures that characterize the possible decline or ascent of neighborhoods, consisting of sociodemographic, built environment, and health outcome indicators. We derived a single numerical value reflecting the current conditions of a given neighborhood for a given period of time (e.g., year), defined as the “Desertion Index” (DI), in which higher and lower values suggest a higher and lower probability of deserting, respectively, and tested this algorithmic approach using simulated hypothetical neighborhoods based on publicly available data from the American Community Survey. We further investigated the statistical properties of the DI statistic utilizing actual data across 125 communities within Cook County.

Methodology: We selected the DI statistic data inputs from the CCDPH 2006-2008 Community Profiles database to represent a wide spectrum of neighborhoods comprising surrounding suburbs of Chicago within Cook County, for a total of 125 neighborhoods. We applied the DI statistic across all neighborhoods to generate a visual histogram and descriptive statistics to characterize the DI for this geographic area. In addition, we employed principal component analysis (PCA) on these neighborhood data to compare the first principal component with our DI statistic. Results: We showed that the DI statistic provides insightful analytics as compared to traditional PCA analysis, and that the DI is robust across a wide range of neighborhoods, particularly in the far tails of the spectrum.

Conclusion: The DI statistic is a practical, novel and powerful metric in identifying neighborhoods that have a high likelihood of deserting, as well as neighborhoods that are thriving or stable, accessible to public health and government officials, community leaders, business owners, citizens, and all community stakeholders in creating initiatives and legislation for the health and well-being of neighborhoods.