Social vulnerability and traumatic brain injury hospitalizations from sports and recreation among pediatric patients in the United States.

PURPOSE: This study examined the associations between individual as well as neighborhood social vulnerability and sports and recreation-related traumatic brain injury (SR-TBI) hospitalizations among pediatric patients in the U.S. METHODS: We obtained 2009, 2010 and 2011 hospitalization data in the U.S. from the National Inpatient Sample (NIS) database, linked it to 2010 neighborhood social vulnerability index (SVI) data from the Centers for Disease Prevention and Control (CDC), and assigned U.S. hospitals to one of four SVI quartiles. SR-TBI outcomes studied include: odds of hospitalization, length of stay (LOS), and discharge to post-acute care (DTPAC). RESULTS: We found associations between race/ethnicity and all SR-TBI outcomes; however, sex, primary payer, and neighborhood overall SVI were only associated with LOS. Compared to White children, Native American children had almost three times higher odds of hospitalization for SR-TBI (OR: 2.82, 95% CI: 1.30, 6.14), 27% longer LOS (ß: 27.06, 95% CI: 16.56, 38.51), but 99.9% lower odds of DTPAC (OR: 0.001, 95% CI: 0.00, 0.01). Compared to children with private insurance, children with public insurance had 11% longer LOS (ß: 10.83, 95% CI: 8.65, 13.05). Hospitalization in neighborhood with higher overall SVI was associated with longer LOS (p < 0.0001). CONCLUSIONS: These findings suggest that individual and neighborhood social vulnerability can have a significant impact on the health outcomes of children, especially in the context of SR-TBI.

flEECe, an energy use and occupant behavior dataset for net-zero energy affordable senior residential buildings.

The behaviors of building occupants have continued to perplex scholars for years in our attempts to develop models for energy efficient housing. Building simulations, project delivery approaches, policies, and more have fell short of their optimistic goals due to the complexity of human behavior. As a part of a multiphase longitudinal affordable housing study, this dataset represents energy and occupant behavior attributes for 6 affordable housing units over nine months in Virginia, USA which are not performing to the net-zero energy standard they were designed for. This dataset provides researchers the ability to analyze the following variables: energy performance, occupant behaviors, energy literacy, and ecological perceptions. Energy data is provided at a 1 Hz sampling rate for four circuits: main, hot water heater, dryer, and HVAC. Building specifications, occupancy, weather data, and neighboring building energy use data are provided to add depth to the dataset. This dataset can be used to update building energy use models, predictive maintenance, policy frameworks, construction risk models, economic models, and more.