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Additional file2: Figure S2-1. Directed Acyclic Graph (DAG) of proposed associations between environmental characteristics and children’s moderate-to-vigorous physical activity. This particular example shows the effect of neighborhood self-selection (relevant to leisure PA) on MVPA and its potential confounders (in red)

Supplementary Material 1

Additional file 1.

Additional file 4: Table S4-1. Effects of environmental attributes on children’s physical activity at T1 (using multiple imputations). Table S4-2. Moderating effects of child’s sex and child’s age on the association between environmental attribute and child’s MVPA from multiple imputations. Figure S4-1. Marginal means for moderate-to-vigorous physical activity (MVPA) at Times 1 and 2 where there were significant interaction effects of environmental attributes on the association between timeand child’s MVPA

Additional file 3: Table S3-1. Estimation of total and direct effects of environmental attributes on child’s MVPA at T1. Table S3-2. Moderating effects of child’s sex and child’s age on the association between environmental attribute and child’s MVPA. Table S3-3. Interaction effects of environmental attributes on the association between time and child’s MVPA.

ObjectivesTo describe the use of a Theory of Change to meaningfully engage community members from or support underserved communities in two National Institutes of Health-funded implementation science projects aimed at promoting equitable access to COVID-19 testing and vaccination for underserved communities.Study settingBoth projects focused on Latino, Black, and immigrant and refugee communities in South/Central San Diego and/or individuals accessing care at a federally qualified health center near the US/Mexico border during December 2020-April 2021.Study designBy using a participatory action research design, Community Advisory Boards (CABs) were established for each project with 11 and 22 members. CAB members included community organizers, promotores de salud (community health workers), clinic providers and administrators, and public health researchers. The CABs were guided through a seven-session Theory of Change process, focused on identifying necessary conditions that must exist to eliminate COVID-19 disparities along with specified actions to create those conditions and a blueprint for assessing the impact of those actions.Data collectionEach session lasted 2h hosted virtually and was augmented by interactive web-based activities. There was a live interpreter who facilitated the participation of Spanish-speaking CAB members. A Theory of Change for each project was completed in approximately 4months.Principal findingsNine necessary conditions were identified related to (1) accessible and available services; (2) culturally and linguistically competent programming; (3) investment in trusted community and faith leaders; (4) social safety nets to provide ancillary services. Corresponding actions to create these conditions and measures to indicate success in creating these conditions were operationalized by the CAB.ConclusionsWhile resource-intensive, a CAB-led Theory of Change process yielded a rich opportunity to engage diverse groups that typically are not invited to inform these processes.

Additional file 1. PALMS User Guide. Includes a technical guide regarding the integration of GPS and accelerometer information.

Additional file 4.

Additional file 5. STROBE Statement—checklist of items that should be included in reports of observational studies. STROBE Checklist for the study.

Additional file 1.

Additional file 2: Supplementary Table 1. Items categorized by scales and indices. Includes table which was too long to submit in the manuscript text.

Additional file 4: Supplementary Table 3. Partial correlations between physical activity and sedentary time within locations. Includes partial correlations for outcome variables as supplemental information.

Additional file 3: Supplementary Table 2. Descriptive statistics for psychosocial and environmental subscales comprising the indices. Includes table as supplemental information.

Additional file 5.

Additional file 2.

Additional file 3.

Additional file 3. Title of data: STROBE-nut Statement—checklist of items that should be included in reports of observational studies. Description of data: Includes STROBE-nut Checklist for the study.

Additional file 1: Table S2. Differences in physical activity behaviors across school, home, and other locations.

Additional file 2: Table S3. Differences in dietary behaviors across school, home, and other locations.

Background: GIS-based walkability measures designed to explain active travel fail to capture “playability” and proximity to healthy food. These constructs should be considered when measuring potential child obesogenic environments. Purpose: The aim of this study was to describe the development of GIS-based multicomponent physical activity and nutrition environment indicators of child obesogenic environments in the San Diego and Seattle regions. Methods: Block group–level walkability (street connectivity, residential density, land-use mix, and retail floor area ratio) measures were constructed in each region. Multiple sources were used to enumerate parks (∼900–1600 per region) and food establishments (∼10,000 per region). Physical activity environments were evaluated on the basis of walkability and presence and quality of parks. Nutrition environments were evaluated based on presence and density of fast-food restaurants and distance to supermarkets. Four neighborhood types were defined using high/low cut points for physical activity and nutrition environments defined through an iterative process dependent on regional counts of fast-food outlets and overall distance to parks and grocery stores from census block groups where youth live. Results: To identify sufficient numbers of children aged 6–11 years, high physical activity environment block groups had at least one high-quality park within 0.25 miles and were above median walkability, whereas low physical activity environment groups had no parks and were below median walkability. High nutrition environment block groups had a supermarket within 0.5 miles, and fewer than 16 (Seattle) and 31 (San Diego) fast-food restaurants within 0.5 miles. Low nutrition environments had either no supermarket, or a supermarket and more than 16 (Seattle) and 31 (San Diego) fast-food restaurants within 0.5 miles. Income, educational attainment, and ethnicity varied across physical activity and nutrition environments. Conclusions: These approaches to defining neighborhood environments can be used to study physical activity, nutrition, and obesity outcomes. Findings presented in a companion paper validate these GIS methods for measuring obesogenic environments.

Background: Identifying neighborhood environment attributes related to childhood obesity can inform environmental changes for obesity prevention. Purpose: To evaluate child and parent weight status across neighborhoods in King County (Seattle metropolitan area) and San Diego County differing in GIS-defined physical activity environment (PAE) and nutrition environment (NE) characteristics. Methods: Neighborhoods were selected to represent high (favorable) versus low (unfavorable) on the two measures, forming four neighborhood types (low on both measures, low PAE/high NE, high PAE/low NE, and high on both measures). Weight and height of children aged 6–11 years and one parent (n=730) from selected neighborhoods were assessed in 2007–2009. Differences in child and parent overweight and obesity by neighborhood type were examined, adjusting for neighborhood-, family-, and individual-level demographics. Results: Children from neighborhoods high on both environment measures were less likely to be obese (7.7% vs 15.9%, OR=0.44, p=0.02) and marginally less likely to be overweight (23.7% vs 31.7%, OR=0.67, p=0.08) than children from neighborhoods low on both measures. In models adjusted for parent weight status and demographic factors, neighborhood environment type remained related to child obesity (high vs low on both measures, OR=0.41, p < 0.03). Parents in neighborhoods high on both measures (versus low on both) were marginally less likely to be obese (20.1% vs 27.7%, OR=0.66, p=0.08), although parent overweight did not differ by neighborhood environment. The lower odds of parent obesity in neighborhoods with environments supportive of physical activity and healthy eating remained in models adjusted for demographics (high vs low on the environment measures, OR=0.57, p=0.053). Conclusions: Findings support the proposed GIS-based definitions of obesogenic neighborhoods for children and parents that consider both physical activity and nutrition environment features.

Background: Relationships between several built environment factors and physical activity and walking behavior are well established, but internationally-comparable built environment measures are lacking. The Microscale Audit of Pedestrian Streetscapes (MAPS)-Global is an observational measure of detailed streetscape features relevant to physical activity that was developed for international use. This study examined the inter-observer reliability of the instrument in five countries. Methods: MAPS-Global was developed by compiling concepts and items from eight environmental measures relevant to walking and bicycling. Inter-rater reliability data were collected in neighborhoods selected to vary on geographic information system (GIS)-derived macro-level walkability in five countries (Australia, Belgium, Brazil, Hong Kong-China, and Spain). MAPS-Global assessments (n = 325) were completed in person along a ≥ 0.25 mile route from a residence toward a non-residential destination, and a commercial block was also rated for each residence (n = 82). Two raters in each country rated each route independently. A tiered scoring system was created that summarized items at multiple levels of aggregation, and positive and negative valence scores were created based on the expected effect on physical activity. The intraclass correlation coefficient (ICC) was computed for scales and selected items using one-way random models. Results: Overall, 86.6% of individual items and single item indicators showed excellent agreement (ICC ≥ 0.75), and 13.4% showed good agreement (ICC = 0.60–0.74). All subscales and overall summary scores showed excellent agreement. Six of 123 items were too rare to compute the ICC. The median ICC for items and scales was 0.92 with a range of 0.50–1.0. Aesthetics and social characteristics showed lower ICCs than other sub-scales, but reliabilities were still in the excellent range (ICC ≥ 0.75). Conclusion: Evaluation of inter-observer reliability of MAPS-Global across five countries indicated all items and scales had “good” or “excellent” reliability. The results demonstrate that trained observers from multiple countries were able to reliably conduct observations of both residential and commercial areas with the new MAPS-Global instrument. Next steps are to evaluate construct validity in relation to physical activity in multiple countries and gain experience with using MAPS-Global for research and practice applications.

Background Though park presence and access disparities are well studied for their associations with physical activity (PA), disparities in the availability and quality of amenities and facilities within parks have been infrequently examined. Methods Five hundred forty-three parks from 472 block groups in the Seattle, WA and Baltimore, MD regions were audited using the Environmental Assessment of Public Recreation Spaces (EAPRS) to assess presence and quality (e.g., condition, cleanliness) of amenities (e.g., restrooms, seating) and facilities (e.g., fields, courts). General linear model regressions investigated Census 2000-derived neighborhood race/ethnicity and income main effect and interactive relationships with 7 park quality summary scores: 1) trails, 2) open space, 3) sports facilities, 4) PA facilities count, 5) PA facilities quality, 6) aesthetics, and 7) overall amenities, controlling for park size. The regions were analyzed separately due to differing race/ethnicity distributions. Results In the Seattle region, neighborhood income was significantly negatively associated with sports quality score (p

(1) Background: Findings from observational studies of relations between neighborhood environments and health outcomes underscore the importance of both objective and perceived experiences of those environments. A clearer understanding of the factors associated with discrepancies between these two assessment approaches is needed to tailor public health interventions to specific populations. This study examined how individual and neighborhood characteristics affect perceptions of supermarket distance, particularly when perceptions do not match objective measures. (2) Methods: Participants were older adults (n = 880) participating in the Senior Neighborhood Quality of Life Study in the Seattle/King County, WA or Baltimore/Washington, DC regions. Two main analyses were conducted. The primary outcome for Analysis I was participants’ geographic information systems (GIS)-based objective network distance to the closest supermarket. Generalized linear mixed models with block group-level random effects were used to assess associations between objective supermarket distance and individual/neighborhood characteristics. The primary outcome for Analysis II was a categorical “accuracy” variable, based on participants’ perceived distance to the nearest supermarket/grocery store relative to the objective distance, assuming a walking speed of 1.0 m/s. Multivariate log-linear models fit neural networks were used to assess influential covariates. (3) Results: Several significant associations with objective distance to the nearest supermarket were observed, including a negative relationship with body mass index (BMI) (95% CI = −45.56, −0.23), having walked to the supermarket in the last 30 days (−174.86, −59.42), living in a high-walkability neighborhood, and residing in Seattle/King County (−707.69, −353.22). In terms of participants’ distance accuracy, 29% were classified as accurate, 33.9% were “Underestimators”, 24.0% “Overestimators”, and 13.2% responded “Don’t Know”. Compared to Accurate participants, Overestimators were significantly less likely to have walked to the supermarket in the last 30 days, and lived objectively closer to a supermarket; Underestimators perceived significantly higher pedestrian safety and lived objectively further from a supermarket; and Don’t Know were more likely to be women, older, not living independently, and not having recently walked to the supermarket. (4) Conclusions: Both modifiable and nonmodifiable factors influence the accuracy of older adults’ perceptions of their proximity to the nearest supermarket. Recent experience in walking to the closest supermarket, along with personal safety, represent potentially modifiable perceived environmental factors that were related to older adults’ accuracy of perceptions of their neighborhood food environment.