14-08 Big Data Analytics to Aid Developing Livable Communities

In transportation, ubiquitous deployment of low-cost sensors combined with powerful computer hardware and high-speed network makes big data available. USDOT defines big data research in transportation as a number of advanced techniques applied to the capture, management and analysis of very large and diverse volumes of data. Data in transportation are usually well organized into tables and are characterized by relatively low dimensionality and yet huge numbers of records. Therefore, big data research in transportation has unique challenges on how to effectively process huge amounts of data records and data streams. The purpose of this study is to conduct research on the problems caused by large data volume and data streams and to develop applications for data analysis in transportation. To process large number of records efficiently, we have proposed to aggregate the data at multiple resolutions and to explore the data at various resolutions to balance between accuracy and speed. Techniques and algorithms in statistical analysis and data visualization have been developed for efficient data analytics using multiresolution data aggregation. Results will be helpful in setting up a primitive stage towards a rigorous framework for general analytical processing of big data in transportation

Epigenetics of Delirium and Aging: Potential Role of DNA Methylation Change on Cytokine Genes in Glia and Blood Along With Aging

Background: Delirium in elderly patients is common and dangerous. Major risk factors include aging and exogenous insults, such as infection or surgery. In animal models, aging enhances pro-inflammatory cytokine release from microglia in response to exogenous insults. The epigenetic mechanism DNA methylation (DNAm) regulates gene expression and changes with age. Older individuals may have methylation changes that influence the increased cytokine upon insult, but the degree to which aging affects DNAm of cytokine genes is not fully understood.Methods: The relationship between DNAm and aging of pro-inflammatory cytokine genes (TNF-alpha, IL1-beta, IL-6) was investigated using methylation array data in two cohorts. Brain and blood samples were collected from a neurosurgery cohort (NSG) of 21 subjects who underwent brain resection. A second cohort, the Grady Trauma Project (GTP), included blood samples from 265 subjects.Results: In the NSG cohort, a significant negative correlation between age and DNAm in brain was found at a CpG in IL-6. With the GTP dataset, significant negative correlations between age and DNAm were seen at most of the CpGs in TNF-alpha. Also, TNF-Alpha expression increases with age. These GTP DNAm correlations were also nominally significant in NSG blood samples. In neuronal negative NSG brain tissue, a similar negative trend was observed.Conclusions: With aging, a decrease in DNAm of cytokines gene CpGs in glia and blood was seen. As this can affect their expression, additional research is needed to fully elucidate the role of DNAm in aging and how it may influence the pathogenesis of delirium

Risk Factors for Overweight/Obesity in Preschool Children: An Ecological Approach

Background—Identification of risk factors is critical to preventing the childhood obesity epidemic. Risk factors that contribute to obesity are multifactorial. However, limited research has focused on identifying obesity risk factors using an ecological approach. Methods—Baseline self-report survey data from the STRONG Kids program were used. The sample consisted of 329 parent-child dyads recruited from childcare programs in east-central Illinois. Child height and weight were measured and converted to age- and sex-specific z-scores using standard growth charts. An ecological model provided the theoretical framework for the selection of 22 previously reported childhood obesity risk factors. Multiple logistic regression analyses were used to identify risk factors. Results—Of 22 potential risk factors, three were found to be significantly associated with child overweight/obesity. These included child nighttime sleep duration (χ2=8.56; p=0.003), parent BMI (χ2=5.62; p=0.01), and parental restrictive feeding for weight control (χ2=4.77; p=0.02). Children who slept for 8 hours and less were 2.2 times more likely to be overweight/obese [95% confidence interval (CI): 1.3–3.7), whereas children with an overweight/obese parent were 1.9 times more likely to be overweight/obese (95% CI: 1.12–3.2). Finally, children whose parents used restrictive feeding practices were 1.75 times more likely to be overweight/obese (95% CI: 1.06–2.9). Conclusions—Using an ecological approach, we conclude that childhood obesity prevention efforts may benefit from targeting the key risk factors of child sleep duration, parent BMI, and parental restrictive feeding practices as focus areas for obesity prevention

Perinatal determinants of growth trajectories in children born preterm.

BackgroundA growing amount of evidence indicates in utero and early life growth has profound, long-term consequences for an individual's health throughout the life course; however, there is limited data in preterm infants, a vulnerable population at risk for growth abnormalities.ObjectiveTo address the gap in knowledge concerning early growth and its determinants in preterm infants.MethodsA retrospective cohort study was performed using a population of preterm (ResultsThirteen variables, including maternal race, hypertension during pregnancy, preeclampsia, first trimester body mass index, multiple status, gestational age, birth weight, birth length, head circumference, year of birth, length of birth hospitalization stay, total parenteral nutrition, and dextrose treatment, were significantly associated with growth rates of preterm infants in univariate analyses. A small percentage (1.32% - 2.07%) of the variation in the growth of preterm infants can be explained in a joint model of these perinatal factors. In extremely preterm infants, additional variation in growth trajectories can be explained by conditions whose risk differs by degree of prematurity. Specifically, infants with periventricular leukomalacia or retinopathy of prematurity experienced decelerated rates of growth compared to infants without such conditions.ConclusionsFactors found to influence growth over time in children born at term also affect growth of preterm infants. The strength of association and the magnitude of the effect varied by gestational age, revealing that significant heterogeneity in growth and its determinants exists within the preterm population

A Novel Risk-Adjusted Metric to Compare Hospitals on Their Antibiotic Prescribing at Hospital Discharge

BackgroundAntibiotic overuse at hospital discharge is common, but there is no metric to evaluate hospital performance at this transition of care. We built a risk-adjusted metric for comparing hospitals on their overall post-discharge antibiotic use.MethodsThis was a retrospective study across all acute-care admissions within the Veterans Health Administration during 2018-2021. For patients discharged to home, we collected data on antibiotics and relevant covariates. We built a zero-inflated negative binomial mixed-model with two random intercepts for each hospital to predict post-discharge antibiotic exposure and length of therapy (LOT). Data were split into training and testing sets to evaluate model performance using absolute error. Hospital performance was determined by the predicted random intercepts.Results1,804,300 patient-admissions across 129 hospitals were included. Antibiotics were prescribed to 41.5% while hospitalized and 19.5% at discharge. Median LOT among those prescribed post-discharge antibiotics was 7 (IQR 4-10). The predictive model detected post-discharge antibiotic use with fidelity, including accurate identification of any exposure (area under the precision-recall curve=0.97) and reliable prediction of post-discharge LOT (mean absolute error = 1.48). Based on this model, 39 (30.2%) hospitals prescribed antibiotics less often than expected at discharge and used shorter LOT than expected. Twenty-eight (21.7%) hospitals prescribed antibiotics more often at discharge and used longer LOT.ConclusionA model using electronically-available data was able to predict antibiotic use prescribed at hospital discharge and showed that some hospitals were more successful in reducing antibiotic overuse at this transition of care. This metric may help hospitals identify opportunities for improved antibiotic stewardship at discharge

Comparison of Virulence between Two Main Clones (ST11 and ST307) of Klebsiella pneumoniae Isolates from South Korea

In this study, we investigate the characteristics of two main clones of carbapenemase-producing Klebsiella pneumoniae isolates from South Korea, ST11 and ST307, including carbapenem-susceptible isolates. Antibiotic susceptibility, serotype or wzi allelic type, the presence of virulence genes, and virulence with respect to serum resistance and macrophage internalization were determined for ST11 and ST307 isolates. ST11 isolates had a wide range of characteristics, including serotype and virulence, compared with those of homogeneous ST307 isolates. The wzi14 or K14 type had higher virulence than that of other serotypes among the ST11 isolates, and the homogeneous ST307 isolates showed similar virulence level as that of the wzi14-type ST11 isolates. Our data suggest that it is necessary to monitor not only the introduction and spread of a specific clone, but also its detailed serotype