Quantifying the Food and Physical Activity Environments in Rural, High Obesity Communities

The built environment contributes to an individual’s health, and rural geographies face unique challenges for healthy eating and active living. The purpose of this descriptive study was to assess the nutrition and physical activity environments in rural communities with high obesity prevalence. One community within each of six high obesity prevalence counties in a rural Midwest state completed the Nutrition Environment Measures Survey for Stores (NEMS-S) and the Rural Active Living Assessment (RALA). Data were collected by trained community members and study staff. All communities had at least one grocery store and five had at least one convenience store. Grocery stores had higher mean total NEMS-S scores than convenience stores (26.6 vs. 6.0, p < 0.001), and higher scores for availability (18.7 vs. 5.3, p < 0.001) and quality (5.4 vs. 0, p < 0.001) of healthful foods (higher scores are preferable). The mean RALA town-wide assessment score across communities was 56.5 + 15.6 out of a possible 100 points. The mean RALA program and policy assessment score was 40.8 + 20.4 out of a possible 100 points. While grocery stores and schools are important for enhancing food and physical environments in rural areas, many opportunities exist for improvements to impact behaviors and address obesity.

261Can a physical activity supportive environment reduce socioeconomic inequities in incident coronary heart disease?

Background This research aims to: (1) explore the contribution of physical activity supportive environments to income inequities in coronary heart disease (CHD) incidence, and (2) investigate whether income inequities in CHD incidence are modified by physical activity supportive environments. Methods We used data from the REGARDS study, which recruited US-residents aged 45 or older between 2003 and 2007. Our analyses included participants at risk for incident CHD (n = 20808), followed until December 31st 2014. We categorized household income and treated it as ordinal: (1) $75,000+, (2) $35,000-$74,000, (3) $20,000-$34,000, and (4) &lt;$20,000. We operationalized physical activity supportive environments within a 1-km residential buffer as density of walkable destinations and physical activity facilities, and proportion green land cover. Cox models were estimated the adjusted association of income with incident CHD, and tested effect modification by environment variables. Results We found a 17% (95% CI 8% to 25%) increased hazard of CHD per decrease in household income category. After adjusting for physical activity environments, the HR was attenuated by 3% (HR = 1.15), and the income-CHD association was stronger in areas lacking walking destinations (HR = 1.54 vs 1.16). Conclusions Physical activity supportive environments, especially those with walking destinations, may moderate associations between household income and CHD. Key messages Low-income individuals have greater risk of developing CHD, however, the built environment has a small moderating effect on this association. Income inequities in CHD were also noted to be higher in areas with no walking destinations

Development and Interrater Reliability of an Observational School Environment Checklist: A Practical, Comprehensive Tool to Assess Healthy Eating and Physical Activity Opportunities in Schools

Introduction Comprehensive, objective assessment of schools’ eating and physical activity environments is critical to developing and evaluating policies and interventions to reduce pediatric obesity inequities; however, few tools exist that describe the entire school comprehensively and are feasible with restricted resources. This study describes development and reliability of the observational school environment checklist (OSEC), a comprehensive observational audit tool. Method We developed the OSEC through iterative adaptations of existing instruments and pilot testing. The tool assesses four focus areas: cafeteria, lobby/hallway, gym, and outdoor areas. For reliability testing, two trained auditors independently completed the OSEC and met to resolve disagreements. For items with poor agreement, a third independent coder coded photographs taken during auditing. Percent agreement and Cohen’s kappa were calculated for all items and across four evidence-based constructs: atmosphere, accessibility, attractiveness, and advertising. Results After iterative development, the 88-item OSEC was tested for reliability in 18 schools. Items with poor (<80%) agreement or redundancy were discarded or reworded ( n = 16 items). All four constructs had acceptable agreement, ranging by focus area: 72.3% (attractiveness), 86.3% to 97.1% (atmosphere), 82.9% to 100% (accessibility), and 92.9% (advertising). Cohen’s kappa ranges were acceptable: 0.66–0.91 (atmosphere), 0.60–1.00 (accessibility), 0.46 (attractiveness), and 0.77 (advertising). After adding similar items across domains ( n = 49) to improve comprehensiveness, the final tool contained 121 binary items. Implications The OSEC reliably and comprehensively captures the school environment. It requires few resources or expertise to administer, has acceptable reliability, and can assess atmosphere, accessibility, attractiveness, and advertising in school areas where students engage in eating and physical activity.

The relationship between the home environment and child adiposity: a systematic review

Background Extensive research has demonstrated the role of the Home Environment (HE) in shaping children’s energy balance behaviours. Less is known about direct relationships with bodyweight. This review examines associations between the social and physical aspects of three pre-defined Home Environment domains (food, physical activity and media) and adiposity measures in children ≤12 years. Methods Six electronic databases (PubMed, Medline, EBSCO CINAHL, EMBASE, Web of Science, PsycInfo) were systematically searched up to October 2020. Studies reporting at least one physical and/or social aspect of the food, physical activity and/or media domains of the Home Environment in relation to child adiposity outcomes were included (n = 62). Results Most studies examined one (n = 41) or two domains (n = 16). Only five studies assessed all three domains of the Home Environment. Most consistent relationships were observed for physical aspects of the home media environment; with greater availability of electronic devices associated with higher child adiposity (21/29 studies). Findings were less consistent for the smaller number of studies examining physical aspects of the home food or physical activity environments. 8/15 studies examining physical food environments reported null associations with adiposity. Findings were similarly mixed for physical activity environments; with 4/7 reporting null associations, 2/7 reporting negative associations and 1/7 reporting positive associations between access to physical activity equipment/garden space and adiposity. Fewer studies assessed social aspects (e.g. caregiver modelling or limit setting) of the Home Environment in relation to child adiposity and findings were again mixed; 9/16 media environment, 7/11 food environment and 9/13 physical activity environment studies reported null associations with child adiposity outcomes. Conclusions The home media environment was most consistently associated with adiposity in childhood. Findings were less consistent for the home food and physical activity environments. Greater agreement on definitions and the measurement of the obesogenic home environment is required in order to clarify the strength and direction of relationships with child adiposity. Robust longitudinal research using comprehensive measures of the holistic home environment is needed to better identify which aspects contribute to excess weight gain in childhood. Trial registration PROSPERO Systematic review registration number: CRD42018115139.

Relationship between primary school healthy eating and physical activity promoting environments and children’s dietary intake, physical activity and weight status: a longitudinal study in the West Midlands, UK

ObjectiveWe aimed to examine the association between food and physical activity environments in primary schools and child anthropometric, healthy eating and physical activity measures.DesignObservational longitudinal study using data from a childhood obesity prevention trial.SettingState primary schools in the West Midlands region, UK.Participants1392 pupils who participated in the WAVES (West Midlands ActiVe lifestyle and healthy Eating in School children) childhood obesity prevention trial (2011–2015).Primary and secondary outcome measuresSchool environment (exposure) was categorised according to questionnaire responses indicating their support for healthy eating and/or physical activity. Child outcome measures, undertaken at three time points (ages 5–6, 7–8 and 8–9 years), included body mass index z-scores, dietary intake (using a 24-hour food ticklist) and physical activity (using an Actiheart monitor over 5 days). Associations between school food and physical activity environment categories and outcomes were explored through multilevel models.ResultsData were available for 1304 children (94% of the study sample). At age 8–9 years, children in 10 schools with healthy eating and physical activity-supportive environments had a higher physical activity energy expenditure than those in 22 schools with less supportive healthy eating/physical activity environments (mean difference=5.3 kJ/kg body weight/24 hours; p=0.05). Children in schools with supportive physical activity environments (n=8) had a lower body mass index z-score than those in schools with less supportive healthy eating/physical activity environments (n=22; mean difference=−0.17, p=0.02). School food and physical activity promoting environments were not significantly associated with dietary outcomes.ConclusionsSchool environments that support healthy food and physical activity behaviours may positively influence physical activity and childhood obesity.Trial registration numberISRCTN97000586.

An app-based quick assessment tool for childcare PA environments and practices

Background Childcare centers are settings with a huge impact on children's health and health behavior and should therefore be encouraged to implement policies and practices to promote physical activity (PA). The project “QueB 2 - developing quality with and through physical activity” aims at exploring how stakeholders can be involved to identify childcare centers with need for action. For this purpose, an app-based quick assessment tool is developed. Methods We conducted two group discussions with stakeholders working with childcare centers (consultants, supervisors) about requirements in terms of applicability and criteria that are important and easily verifiable. Based on the results of the discussions and building on scientific evidence and existing frameworks, a quick assessment checklist was created and developed as a web app. The tool is tested by stakeholders and evaluated in further group discussions. Results Stakeholders require a simple assessment tool that can be used in counseling with small expenditure and is combined with information material. The developed app-based assessment tool consists of 20 items in 7 categories (indoor space, outdoor space, play equipment, activities, childcare center culture, professional development, network). It incorporates a simple scoring system with a total score ranging from 0 to 126. Based on the score, the tool shows a feedback window stating whether there is little, some or much need for action and providing additional information. Conclusions Stakeholders can be involved to sensitize childcare centers to the issue of physical activity environments and practices with the help of an app-based quick assessment tool. This is an important step before possible interventions can be implemented in childcare centers. Key messages An app-based assessment tool for childcare physical activity environments and practices is developed. It will enable stakeholders to identify childcare centers with need for action and offer support.