Deriving neighborhood-level diet and physical activity measurements from anonymized mobile phone location data for enhancing obesity estimation.

BACKGROUND: Obesity is a serious public health problem. Existing research has shown a strong association between obesity and an individual's diet and physical activity. If we extend such an association to the neighborhood level, information about the diet and physical activity of the residents of a neighborhood may improve the estimate of neighborhood-level obesity prevalence and help identify the neighborhoods that are more likely to suffer from obesity. However, it is challenging to measure neighborhood-level diet and physical activity through surveys and interviews, especially for a large geographic area. METHODS: We propose a method for deriving neighborhood-level diet and physical activity measurements from anonymized mobile phone location data, and examine the extent to which the derived measurements can enhance obesity estimation, in addition to the socioeconomic and demographic variables typically used in the literature. We conduct case studies in three different U.S. cities, which are New York City, Los Angeles, and Buffalo, using anonymized mobile phone location data from the company SafeGraph. We employ five different statistical and machine learning models to test the potential enhancement brought by the derived measurements for obesity estimation. RESULTS: We find that it is feasible to derive neighborhood-level diet and physical activity measurements from anonymized mobile phone location data. The derived measurements provide only a small enhancement for obesity estimation, compared with using a comprehensive set of socioeconomic and demographic variables. However, using these derived measurements alone can achieve a moderate accuracy for obesity estimation, and they may provide a stronger enhancement when comprehensive socioeconomic and demographic data are not available (e.g., in some developing countries). From a methodological perspective, spatially explicit models overall perform better than non-spatial models for neighborhood-level obesity estimation. CONCLUSIONS: Our proposed method can be used for deriving neighborhood-level diet and physical activity measurements from anonymized mobile phone data. The derived measurements can enhance obesity estimation, and can be especially useful when comprehensive socioeconomic and demographic data are not available. In addition, these derived measurements can be used to study obesity-related health behaviors, such as visit frequency of neighborhood residents to fast-food restaurants, and to identify primary places contributing to obesity-related issues.

Operational challenges that may affect implementation of evidence-based mobile market interventions.

INTRODUCTION: Mobile produce markets are becoming an increasingly prevalent, accepted, and effective strategy for improving fruit and vegetable (F&V) access and consumption across underserved and lower-income communities. However, there is limited published research on mobile market operations. The goal of this research is to identify the challenges mobile markets face and ways to potentially mitigate those challenges. We will also discuss implications of our findings for future implementation of evidence-based food access interventions. METHODS: We conducted 21 semi-structured key informant (KI) interviews to assess common practices of mobile market organizations that had been operating for 2 + years. We asked KIs about their organizational structure, operations, procurement and logistics, evaluation efforts, marketing and community engagement, success and challenges. A primary qualitative analysis involved deductive coding using qualitative software. A secondary qualitative analysis identified subthemes related to common challenges and remedial practices. A deductive coding process was applied to match identified challenges to the appropriate Consolidated Framework for Implementation Research (CFIR). RESULTS: The leading challenges cited by KIs correspond to the CFIR domains of inner setting (e.g., funding and resources), outer setting (e.g., navigating regulations), and process (e.g., engaging community partnership). Practices that may mitigate challenges include maximizing ancillary services, adopting innovative volunteer and staffing structures, and formalizing agreements with community partners. CONCLUSION: Common and persistent challenges ought to be addressed to ensure and enhance the positive public health impacts of mobile produce markets. Contextual factors, particularly organizational factors, that impact implementation should also be considered when implementing an evidence-based intervention at a mobile market. Further research is needed to determine which innovative solutions are the most effective in mitigating challenges, improving implementation, and enhancing sustainability of mobile markets.

Human mobility data demonstrates increase in park visitation since start of COVID-19 pandemic in Buffalo, New York.

Background: The COVID-19 pandemic highlighted the importance of urban parks to provide safe places to visit and recreate. Recent research has suggested that park visitation over this time may not have occurred equitably, which may exacerbate existing health disparities. However, usual methods of estimating park visitation are labor intensive, requiring better solutions.. The objective of this study was to assess how park visitation changed in Buffalo, New York after the start of the COVID-19 pandemic utilizing human mobility data. Methods: Monthly mobile phone location data from January 2018 through October of 2021 from residents of Buffalo were analyzed to estimate total park visits for each census tract. A generalized linear mixed effect model was utilized to examine if selected factors affected park visitation. Factors examined included demographic, health, park, and crime data at the census tract level. Results: Across 587,487 park visits that were captured in the 79 census tracts, park visitation increased by 25% since March 2020. In our regression model, having cancer and currently smoking had negative effects on park visitation. The start of the COVID-19 pandemic positively affected park visitation. Season (of the year), was the other statistically significant variable that affected park visitation. Conclusions: Anonymous mobile phone data demonstrated that park visitation has increased by 25% since the beginning of the pandemic when we looked at census tract level data. While some data limitations must be addressed, mobile phone data is a novel method that can be used to understand behavioral and public health trends.

Using implementation mapping to refine strategies to improve implementation of an evidence-based mobile market intervention: a study protocol.

Objectives: The Veggie Van model is a mobile market model that is efficacious in increasing fruit and vegetable consumption for lower-income participants. The model is currently being evaluated for its effectiveness in a multi-state trial. Preliminary implementation data, collected through process measures surveys and implementation interviews, indicate that there are several barriers to implementation among partner organizations and implementation fidelity to the Veggie Van model was low. Consideration and planning for implementation ought to occur early and often throughout the research process order to ensure Veggie Van model effectiveness. This paper describes the step-by-step process for creating strategies to enhance implementation of Veggie Van model components. Methods: Implementation mapping is a systematic process to develop implementation strategies through engagement with key stakeholders. We conducted a series of interviews (n = 31 representatives) with partner organizations (n = 8) to identify facilitators and barriers to Veggie Van model implementation. We then applied interview findings to an Implementation Mapping process to develop theory and practice-driven strategies to be integrated into existing implementation tools and technical assistance. Results: We identified implementation outcomes (e.g., staff implement the Veggie Van model component of nutrition education with fidelity) and performance objectives (e.g., offer nutrition education, in the form of food lessons and/or food demonstrations, at least bi-weekly) to achieve them. We conducted a secondary qualitative analysis of the findings from implementation interviews with partner organizations to identify behavioral determinants (e.g., attitudinal beliefs, social support) which were combined with the performance objectives to generate change objectives (e.g., view the Veggie Van model as advantageous to an organization and communities served). To achieve the change objectives, we developed implementation strategies that would be integrated into existing Veggie Van training resources including an online toolkit, webinars and trainings, an annual mobile market conference, and technical assistance. Conclusion: The development of theory and practice-driven implementation strategies will enable us to improve our implementation tools, thereby improving fidelity to the Veggie Van model among organizations and increasing the likelihood of its effectiveness. Detailing the design of a multifaceted implementation strategy using Implementation Mapping also provides a model to design similar strategies for other community-based interventions.

Impacts of the COVID-19 Pandemic on Mobile Produce Market Operations: Adaptations, Barriers, and Future Directions for Increasing Food Access.

BACKGROUND: Mobile produce markets were increasingly recognized as an effective and accepted approach to improving access to fruits and vegetables in lower-income and at-risk communities during the first year of the COVID-19 pandemic in the United States. This study provides insights into how mobile market operations were impacted by, and evolved in response to, challenges posed by the pandemic. METHODS: A survey evaluating impacts of the pandemic on mobile markets was distributed to a database of mobile market operators in the United States. Respondents were asked to describe impacts to their mobile market's operations, and what adaptations were needed to continue to effectively serve their communities during 2020. RESULTS: Surveys representing 48 unique mobile markets were collected from March to July 2021. Of the respondents, 63% reported an increase in demand for mobile market services from community members. Furthermore, 65% increased the amount of produce they distributed in 2020 as compared to 2019, often through adopting low or no-cost models or participating in pandemic government programs. DISCUSSION: Emergency adaptations employed by mobile markets can inform long-term operational modifications for not only mobile markets, but also other food access programs, beyond the COVID-19 pandemic.

Variation of Traditional Biomarkers of Liver Injury After an Ultramarathon at Altitude.

BACKGROUND: Significant elevations of traditional biomarkers of liver injury can occur as a result of running an ultramarathon. HYPOTHESIS: Traditional serum biomarker levels of liver injury will significantly increase as the result of participating in this 161-km race at altitude. STUDY DESIGN: Prospective cross-sectional study. LEVEL OF EVIDENCE: Level 3. METHODS: A total of 64 (before) and 83 (after) volunteer runners participated in a prospective observational field-based study at the Leadville 100 ultramarathon race. Changes in serum aspartate aminotransferase (AST), alanine aminotransferase (ALT), alkaline phosphatase (ALP), creatine kinase (CK), and bilirubin levels were measured. RESULTS: Of 669 athletes who started the race, 352 successfully completed the race within the 30-hour cutoff (53%). Of 36 runners who had pre- and postrace blood samples taken, the mean ALT, AST, and bilirubin levels were increased from 23 ± 10 U/L, 23 ± 5 U/L, and 0.60 ± 0.29 mg/dL to 117 ± 106 U/L, 485 ± 500 U/L, and 1.60 ± 0.61 mg/dL, respectively (all P < 0.001). There was no change in the mean ALP level ( P = 0.11). There were no significant correlations between postrace ALT, AST, ALP, lactate dehydrogenase (LDH), and bilirubin levels and athletes' age, sex, body mass index, or finishing time. Significant positive linear correlations between AST, ALT, and LDH with CK were seen. Athletes in this study did not seek medical attention after the race based on an electronic survey (92% response rate). CONCLUSION: Significant elevations of traditional biomarkers of liver injury occurred as a result of running an ultramarathon at altitude. These correlated with CK, a marker of muscle injury. CLINICAL RELEVANCE: When reviewing laboratory studies of traditional biomarkers of liver injury in athletes after an ultramarathon, significant elevations may be seen from baseline but are likely to be of no clinical consequence.