• Data Sharing Agreements result in accessible, relevant, and timely community data. • Stakeholder data training workshops support communities in surveillance efforts. • Surveillance as standard educational practice yields local population PA estimates. • Local data can drive community decisions regarding youth PA opportunities.

Background: Communities are wellness landscapes of geospatially and temporally bound settings where children spend their time. Improving population physical activity (PA) requires investigating available community settings for children, such as classrooms and sport teams, and the dynamic social interactions producing PA. This protocol describes a multiscale community wellness landscape monitoring and feedback system of adult-led organized group settings and PA outcomes for children. Methods: The data system assessed organized groups for third- through sixth-grade children in 2 rural communities within seasons (fall 2018–2019). Within each season, groups were identified, sampled, and recruited. Sampled group meetings were assessed for children’s PA (accelerometry) and meeting routines (video observation). A data processing protocol time-segmented data into meetings and meeting routines into smaller units (sessions). A purpose code was assigned to each meeting (eg, classroom, sport) and session (eg, academic, PA). Group accelerometer data were paired with the coded segments. Multiscale metrics (season, meeting, and session) were generated and provided to the communities in tailored reports. Results: A total of 94 groups were recruited, and 73 groups with 1302 participants were included in the data system. Data were collected from 213 meetings and 844 sessions. Most participants (83.1%) consented to link their accelerometer data with demographic data from school enrollment records. Conclusions: The community data system identified available organized group settings for children and collected video and PA data from these settings. Incorporating setting data into local data systems provides detailed accounts of whole-of-community PA social systems to inform population health improvement efforts.

Whole-of-community interventions delivered across entire geospatial areas show promise for improving population health for youth cancer prevention. The aims of this scoping review were to synthesize the whole-of-community intervention literature on six modifiable risk factors in youth for cancer prevention (alcohol use, diet, obesity, physical activity, sun exposure, tobacco use) and to develop and apply a typology describing the inclusion of fundamental control system functional characteristics. A systematic search was conducted in PubMed, Cumulative Index to Nursing and Allied Health Literature, Embase, PsycINFO, and Scopus for studies published to the end of 2019. Eligible studies included a geospatially defined whole-of-community intervention; youth 0-18 years; and at least one of the six cancer risk factor outcomes. An iterative process was undertaken to create a typology describing the functions for whole-of-community interventions guided by systems theory, and the typology was used to code the included interventions. A total of 41 interventions were included. Most interventions (43.9%) assessed multiple cancer risk factors. Few interventions provided fundamental functions necessary for community system coordination: sensor, controller, effector. Although communities are a patchwork quilt of microsystems where individuals interact in geographically bounded places nested within larger whole systems of influence, a control systems approach has not been used to frame the literature. Whole-of-community interventions can be characterized by the fundamental system functions necessary for coordinating population health improvement. Future whole-of-community intervention efforts should draw on fundamental knowledge of how systems operate and test whether adoption of the key functions is necessary for whole-of-community population health improvement.

• A community systems approach is important to identify social and geographic health impacts. • Community stakeholders residing within the city had higher trust and collective efficacy scores. • These stakeholders had roles directly leading physical activity opportunities for youth. • Youth physical activity was greater in the community with stakeholders in administrative roles. • Unique community variables should be studied to elucidate system drivers of physical activity.

This scoping review synthesizes studies examining community-level variability in physical activity resource (assets) and opportunity (organized group physical activity services) availability by community sociodemographic characteristics to describe methodologies for measuring resources/opportunities, indicators characterizing availability, and associations between community-level sociodemographic characteristics and availability. A systematic search was conducted in MEDLINE, CINAHL, PsycINFO, and Scopus for literature through 2022. Eligible studies quantitatively examined measures of physical activity resource/opportunity availability by community-level racial, ethnic, and/or socioeconomic characteristics within geospatially defined communities. Extracted data included: community geospatial definitions, sociodemographic characteristics assessed, methodologies for measuring and indicators of community physical activity resource/opportunity availability, and study findings. Among the 46 included studies, community geospatial units were defined by 28 different community boundaries (e.g., town), and 13% of studies were conducted in rural areas. Nearly all (98%) studies measured community-level socioeconomic status, and 45% of studies measured race/ethnicity. A total of 41 indicators of physical activity resource/opportunity availability were identified. Most studies (91%) assessed built environment resources (e.g., parks), while 8.7% of studies assessed opportunities (e.g., programs). Of 141 associations/differences between community sociodemographic characteristics and resource/opportunity availability, 29.8% indicated greater availability in communities of higher socioeconomic status or lower prevalence of minority populations. The remaining findings were in the opposite direction (9.2%), non-significant (36.9%), or mixed (24.1%). Variability in physical activity resources/opportunities by community sociodemographic characteristics was not consistently evident. However, the indicators synthesized may be useful for informing population health improvement efforts by illuminating the physical and social conditions impacting population physical activity outcomes.

Background: Community-based coalitions are a common strategy for community engagement efforts targeting the improvement of a variety of population health outcomes. The typical processes that coalitions follow to organize efforts include steps that are sequential, slow, and time intensive. These processes also limit local decision-making to the selection of evidence-based policies or programs. Methods: We present a process control theory-based Community Action Process, Investigate-Design-Practice-Reflect (IDPR), where community hubs (i.e., coalitions) organize agile efforts in a non-sequential, rapid, and efficient manner to harness local assets and data to make decisions regarding the provision and production of population health services. Using qualitative methods, we illustrate and analyze the use of IDPR in a one community case study as part of Wellscapes, a Type 3-hybrid implementation-effectiveness community randomized controlled trial to improve children’s population health physical activity. Results: We found community members followed the IDPR Community Action Process to rapidly design, organize, deliver, and receive feedback on a community-based, children’s population physical activity prototype, an afterschool Play-in-the-Park opportunity for all children. Discussion: Following IDPR afforded the community coalition timely learning through feedback within a process that coordinated decisions regarding what community services met community needs (provision decisions) and how to organize the production of the population health services (production decisions).