Destination Areas (DAs)

Permanent URI for this community

https://hdl.handle.net/10919/78629
Destination Areas provide faculty and students with new tools to identify and solve complex, 21st-century problems in which Virginia Tech already has significant strengths and can take a global leadership role. The initiative represents the next step in the evolution of the land-grant university to meet economic and societal needs of the world. DAs connect the full span of relevant knowledge necessary for addressing issues comprehensively. Humanistic, scientific, and technological perspectives are addressed in relationship to one another and they are treated as complementary to overcome traditional academic boundaries, such as those that separate the STEM fields and liberal arts. [http://provost.vt.edu/destination-areas.html]

Browse

Browsing Destination Areas (DAs) by Department "Center for Biostatistics and Health Data Science"

Now showing 1 - 3 of 3
  • Thumbnail Image
    Altered toxicological endpoints in humans from common quaternary ammonium compound disinfectant exposure
    Hrubec, Terry C.; Seguin, Ryan P.; Xu, L.; Cortopassi, G. A.; Datta, S.; Hanlon, Alexandra L.; Lozano, A. J.; McDonald, V. A.; Healy, C. A.; Anderson, T. C.; Musse, N. A.; Williams, R. T. (Elsevier, 2021-01-01)
    Humans are frequently exposed to Quaternary Ammonium Compounds (QACs). QACs are ubiquitously used in medical settings, restaurants, and homes as cleaners and disinfectants. Despite their prevalence, nothing is known about the health effects associated with chronic low-level exposure. Chronic QAC toxicity, only recently identified in mice, resulted in developmental, reproductive, and immune dysfunction. Cell based studies indicate increased inflammation, decreased mitochondrial function, and disruption of cholesterol synthesis. If these findings translate to human toxicity, multiple physiological processes could be affected. This study tested whether QAC concentrations could be detected in the blood of 43 human volunteers, and whether QAC concentrations influenced markers of inflammation, mitochondrial function, and cholesterol synthesis. QAC concentrations were detected in 80 % of study participants. Blood QACs were associated with increase in inflammatory cytokines, decreased mitochondrial function, and disruption of cholesterol homeostasis in a dose dependent manner. This is the first study to measure QACs in human blood, and also the first to demonstrate statistically significant relationships between blood QAC and meaningful health related biomarkers. Additionally, the results are timely in light of the increased QAC disinfectant exposure occurring due to the SARS-CoV-2 pandemic. Main Findings: This study found that 80 % of study participants contained QACs in their blood; and that markers of inflammation, mitochondrial function, and sterol homeostasis varied with blood QAC concentration.
  • Thumbnail Image
    Breakfast Consumption Habits at Age 6 and Cognitive Ability at Age 12: A Longitudinal Cohort Study
    Liu, Jianghong; Wu, Lezhou; Um, Phoebe; Wang, Jessica S.; Kral, Tanja V. E.; Hanlon, Alexandra L.; Shi, Zumin (MDPI, 2021-06-17)
    This study aimed to assess the relationship between breakfast composition and long-term regular breakfast consumption and cognitive function. Participants included 835 children from the China Jintan Cohort Study for the cross-sectional study and 511 children for the longitudinal study. Breakfast consumption was assessed at ages 6 and 12 through parental and self-administered questionnaires. Cognitive ability was measured as a composition of IQ at age 6 and 12 and academic achievement at age 12, which were assessed by the Chinese versions of the Wechsler Intelligence Scales and standardized school reports, respectively. Multivariable general linear and mixed models were used to evaluate the relationships between breakfast consumption, breakfast composition and cognitive performance. In the longitudinal analyses, 94.7% of participants consumed breakfast ≥ 4 days per week. Controlling for nine covariates, multivariate mixed models reported that compared to infrequent breakfast consumption, regular breakfast intake was associated with an increase of 5.54 points for verbal and 4.35 points for full IQ scores (p < 0.05). In our cross-sectional analyses at age 12, consuming grain/rice or meat/egg 6–7 days per week was significantly associated with higher verbal, performance, and full-scale IQs, by 3.56, 3.69, and 4.56 points, respectively (p < 0.05), compared with consuming grain/rice 0–2 days per week. Regular meat/egg consumption appeared to facilitate academic achievement (mean difference = 0.232, p = 0.043). No association was found between fruit/vegetable and dairy consumption and cognitive ability. In this 6-year longitudinal study, regular breakfast habits are associated with higher IQ. Frequent grain/rice and meat/egg consumption during breakfast may be linked with improved cognitive function in youth.
  • Thumbnail Image
    County-level social distancing and policy impact in the United States: A dynamical systems model
    McKee, Kevin L.; Crandell, Ian C.; Hanlon, Alexandra L. (JMIR Publications, 2020-10-01)
    Background: Social distancing and public policy have been crucial for minimizing the spread of SARS-CoV-2 in the United States. Publicly available, county-level time series data on mobility are derived from individual devices with global positioning systems, providing a variety of indices of social distancing behavior per day. Such indices allow a fine-grained approach to modeling public behavior during the pandemic. Previous studies of social distancing and policy have not accounted for the occurrence of pre-policy social distancing and other dynamics reflected in the long-term trajectories of public mobility data. Objective: We propose a differential equation state-space model of county-level social distancing that accounts for distancing behavior leading up to the first official policies, equilibrium dynamics reflected in the long-term trajectories of mobility, and the specific impacts of four kinds of policy. The model is fit to each US county individually, producing a nationwide data set of novel estimated mobility indices. Methods: A differential equation model was fit to three indicators of mobility for each of 3054 counties, with T=100 occasions per county of the following: distance traveled, visitations to key sites, and the log number of interpersonal encounters. The indicators were highly correlated and assumed to share common underlying latent trajectory, dynamics, and responses to policy. Maximum likelihood estimation with the Kalman-Bucy filter was used to estimate the model parameters. Bivariate distributional plots and descriptive statistics were used to examine the resulting county-level parameter estimates. The association of chronology with policy impact was also considered. Results: Mobility dynamics show moderate correlations with two census covariates: population density (Spearman r ranging from 0.11 to 0.31) and median household income (Spearman r ranging from -0.03 to 0.39). Stay-at-home order effects were negatively correlated with both (r=-0.37 and r=-0.38, respectively), while the effects of the ban on all gatherings were positively correlated with both (r=0.51, r=0.39). Chronological ordering of policies was a moderate to strong determinant of their effect per county (Spearman r ranging from -0.12 to -0.56), with earlier policies accounting for most of the change in mobility, and later policies having little or no additional effect. Conclusions: Chronological ordering, population density, and median household income were all associated with policy impact. The stay-at-home order and the ban on gatherings had the largest impacts on mobility on average. The model is implemented in a graphical online app for exploring county-level statistics and running counterfactual simulations. Future studies can incorporate the model-derived indices of social distancing and policy impacts as important social determinants of COVID-19 health outcomes.