Transportation Factors and Postoperative Attendance and Weight Loss Through 24 Months.

PURPOSE: Transportation, access to follow-up care, and association with weight loss are understudied in the bariatric population. The objective of this study was to determine how transportation variables associate with postoperative attendance and weight loss through 24 months. MATERIALS AND METHODS: Seven hundred eighty-seven patients (81.3% female; 59.1% White) who had primary surgery (48.6% gastric bypass) from 2015 to 2019 were included. Sidewalk coverage and number of bus stops from patients' homes, driving distance in miles and minutes from patients' homes to the nearest bus stop and the clinic were measured. Bivariate analyses were conducted with the transportation variables and attendance and %TWL at 2 or 3, 6, 12, and 24 months. One mixed multilevel model was conducted with dependent variable %TWL over 24 months with visits as the between-subjects factor and covariates: race, insurance, surgical procedure, and driving distance to the clinic in minutes, attendance, and %TWL over 24 months; an interaction between distance, attendance, and visits. RESULTS: There were no significant differences between the majority of the transportation variables and postoperative attendance or %TWL. Patients who had perfect attendance had improved %TWL at 12 months [t(534)=-1.92, p=0.056] and 24 months [t(393)=-2.69, p=0.008] compared to those who missed at least one appointment. Patients with perfect attendance and who had shorter driving times (under 20 min) to the clinic had greater weight loss through 24 months [F(10, 1607.50)=2.19, p=0.016)]. CONCLUSIONS: Overall, transportation factors were not associated with attendance and weight loss, with the exception of the interaction between shorter driving minutes to follow-up and perfect attendance.

Understanding the spatiotemporal evolution of opioid overdose events using a regionalized sequence alignment analysis.

BACKGROUND: Opioid overdose events and deaths have become a serious public health crisis in the United States, and understanding the spatiotemporal evolution of the disease occurrences is crucial for developing effective prevention strategies, informing health systems policy and planning, and guiding local responses. However, current research lacks the capability to observe the dynamics of the opioid crisis at a fine spatial-temporal resolution over a long period, leading to ineffective policies and interventions at the local level. METHODS: This paper proposes a novel regionalized sequential alignment analysis using opioid overdose events data to assess the spatiotemporal similarity of opioid overdose evolutionary trajectories within regions that share similar socioeconomic status. The model synthesizes the shape and correlation of space-time trajectories to assist space-time pattern mining in different neighborhoods, identifying trajectories that exhibit similar spatiotemporal characteristics for further analysis. RESULTS: By adopting this methodology, we can better understand the spatiotemporal evolution of opioid overdose events and identify regions with similar patterns of evolution. This enables policymakers and health researchers to develop effective interventions and policies to address the opioid crisis at the local level. CONCLUSIONS: The proposed methodology provides a new framework for understanding the spatiotemporal evolution of opioid overdose events, enabling policymakers and health researchers to develop effective interventions and policies to address this growing public health crisis.

COVID-19 exacerbates unequal food access.

Inequality to food access has always been a serious problem, yet it became even more critical during the COVID-19 pandemic, which exacerbated social inequality and reshaped essential travel. This study provides a holistic view of spatio-temporal changes in food access based on observed travel data for all grocery shopping trips in Columbus, Ohio, during and after the state-wide stay-at-home period. We estimated the decline and recovery patterns of store visits during the pandemic to identify the key socio-economic and built environment determinants of food shopping patterns. The results show a disparity: during the lockdown, store visits to dollar stores declined the least, while visits to big-box stores declined the most and recovered the fastest. Visits to stores in low-income areas experienced smaller changes even during the lockdown period. A higher percentage of low-income customers was associated with lower store visits during the lockdown period. Furthermore, stores with a higher percentage of white customers declined the least and recovered faster during the reopening phase. Our study improves the understanding of the impact of the COVID-19 crisis on food access disparities and business performance. It highlights the role of COVID-19 and similar disruptions on exposing underlying social problems in the US.

311 service requests as indicators of neighborhood distress and opioid use disorder.

Opioid use disorder and overdose deaths is a public health crisis in the United States, and there is increasing recognition that its etiology is rooted in part by social determinants such as poverty, isolation and social upheaval. Limiting research and policy interventions is the low temporal and spatial resolution of publicly available administrative data such as census data. We explore the use of municipal service requests (also known as "311" requests) as high resolution spatial and temporal indicators of neighborhood social distress and opioid misuse. We analyze the spatial associations between georeferenced opioid overdose event (OOE) data from emergency medical service responders and 311 service request data from the City of Columbus, OH, USA for the time period 2008-2017. We find 10 out of 21 types of 311 requests spatially associate with OOEs and also characterize neighborhoods with lower socio-economic status in the city, both consistently over time. We also demonstrate that the 311 indicators are capable of predicting OOE hotspots at the neighborhood-level: our results show code violation, public health, and street lighting were the top three accurate predictors with predictive accuracy as 0.92, 0.89 and 0.83, respectively. Since 311 requests are publicly available with high spatial and temporal resolution, they can be effective as opioid overdose surveillance indicators for basic research and applied policy.

Changes in bicycling over time associated with a new bike lane: relations with kilocalories energy expenditure and body mass index.

Although bicycling has been related to positive health indicators, few studies examine health-related measures associated with non-competitive community cycling before and after cycling infrastructure improvements. This study examined cycling changes in a neighborhood receiving a bike lane, light rail, and other "complete street" improvements. Participants wore accelerometers and global positioning system (GPS) data loggers for one week in both 2012 and 2013, pre- and post- construction completion. Participants sampled within 2 km of the complete street improvements had the following patterns of cycling: never cyclists (n=434), continuing cyclists (n= 29), former cyclists (n=33, who bicycled in 2012 but not 2013), and new cyclists (n=40, who bicycled in 2013 but not 2012). Results show that all three cycling groups, as identified by GPS/accelerometry data, expended more estimated kilocalories (kcal) of energy per minute during the monitoring week than those who were never detected cycling, net of control variables. Similar but attenuated results emerged when cycling self-report measures were used. BMI was not related to cycling group but those who cycled longer on the new path had lower BMI. Although cyclists burn more calories than non-cyclists across the week, among cyclists, their cycling days involved more calories expended than their non-cycling days. The new cyclists account for 39% of the cyclists identified in this study and former cyclists account for 32% of cyclists. These results suggest that cycling is healthy, but that sustaining rates of cycling will be an important goal for future policy and research.