Inflammatory markers and body mass index amoung hispanic children.

BACKGROUND AND OBJECTIVES: Body mass index (BMI) is inversely proportional with adiponectin levels among adults, while insulin, C-reactive protein (CRP), interleukin 6 (IL-6), resistin and tumor necrosis factor-alpha (TNF-α) have been linked with elevated BMI. The role and relation of these biomarkers with BMI among a Hispanic pediatric population are less known. Thus, the objective of this study was to examine the association of inflammatory markers with the odds of overweight/obesity while controlling for several sociodemographic factors among a Hispanic youth population in Northeast Tennessee. METHODS: Height, weight, demographic information, and blood samples were collected from 107 Hispanic children aged 2 to 10 years recruited at a large community health center in 2015-2016 in Northeast Tennessee. Data for this research were accessed and analyzed in 2022. Multivariable logistic regression was conducted to assess the relations between adiponectin, insulin, resistin, CRP, TNF-α, and IL-6, and overweight/obesity vs. having a healthy (normal) weight. RESULTS: Adiponectin levels were significantly lower among overweight/obese Hispanic children (p = 0.0144) compared to healthy weight children. The odds of overweight/obesity decreased by 4% for every one-unit increase in serum adiponectin. Insulin levels were significantly higher among overweight/obese Hispanic children compared to healthy weight children (p = 0.0048). The odds of overweight/obesity increased by 7% for every one-unit increase in serum insulin. Resistin, IL-6, TNF-α, and CRP were not significantly associated with overweight/obesity in this population. CONCLUSION: Adiponectin behaves similarly in Hispanic youth as it does in other pediatric populations, possibly making it a valuable marker when examining metabolic health status in this population.

Modification of the Priority Risk Index: Adapting to Emergency Management Accreditation Program standards for institutes of higher learning hazard mitigation plans.

The Priority Risk Index is increasingly used as a methodology for quantifying jurisdictional risk for hazard mitigation planning purposes, and it can evolve to meet specific community needs. The index incorporates probability, impact, spatial extent, warning time, and duration when assessing each hazard, but it does not explicitly integrate a vulnerability and consequence analysis into its final scoring. To address this gap, a new index was developed-the Enhanced Priority Risk Index (EPRI). The new index adds a sixth category, vulnerability, calculated from a vulnerability and consequence analysis of the impacts on seven sectors identified in Standard 4.1.2 of the Emergency Management Accreditation Program (EMAP). To obtain a vulnerability score, impacts are ranked by sector from low (1) to very high (4), then a weighting factor is applied to each sector. The vulnerability score is added to the EPRI and provides risk levels based on the number of exploitable weaknesses and countermeasures identified within a specific jurisdiction. The vulnerability score and resulting EPRI are scalable and can be applied across jurisdictions, providing a transferable methodology that improves the hazard identification and risk assessment process and provides an approach for meeting EMAP accreditation standards.

Storm sampling to assess inclement weather impacts on water quality in a karst watershed: Sinking Creek, Watauga watershed, East Tennessee.

Sinking Creek (HUC 06010103046), in the Watauga watershed of northeast Tennessee, is impaired due to Escherichia coli. To assess how E. coli and other water quality parameters fluctuated during storm events, water samples were collected with automated samplers during eight storms at two locations: Sinking Creek and a feeder spring. Turbidity and electrical conductivity data loggers were deployed in the creek, and dissolved oxygen (DO) was measured in situ. The presence of optical brighteners, used in detergents and an indicator of residential wastewater, was assessed using cotton fabric deployed at both sites and analyzed by an external laboratory. The Colilert Quanti-Tray method was used to process water samples for E. coli. Relationships between water quality parameters and lagged precipitation were assessed using cross-correlation. At the creek, E. coli and turbidity increased within 2 h of precipitation, exceeding the single sample water quality standard of 941 cfu 100 ml-1 during the storm. At the spring, E. coli became elevated more quickly than at the stream, within 30 min of precipitation, and decreased below the standard during the event. Electrical conductivity decreased within 1.5 h of the storm at the creek, and DO levels were higher at the creek than at the spring. Optical brightener analysis indicated possible presence of residential wastewater during one of two sampled storms. Targeted sampling and dye tracing are recommended to validate this hypothesis. These results may be used to inform field methods in similar storm sampling studies and will be useful in watershed restoration efforts in Sinking Creek.

Emergence of COVID-19 and Patterns of Early Transmission in an Appalachian Sub-Region.

Background: In mid-March 2020, very few cases of COVID-19 had been confirmed in the Central Blue Ridge Region, an area in Appalachia that includes 47 jurisdictions across northeast Tennessee, western North Carolina, and southwest Virginia. Authors described the emergence of cases and outbreaks in the region between March 18 and June 11, 2020. Methods: Data were collected from the health department websites of Tennessee, North Carolina, and Virginia beginning in mid-March for an ongoing set of COVID-19 monitoring projects, including a newsletter for local healthcare providers and a Geographic Information Systems (GIS) dashboard. In Fall 2020, using these databases, authors conducted descriptive and geospatial cluster analyses to examine case incidence and fatalities over space and time. Results: In the Central Blue Ridge Region, there were 4432 cases on June 11, or 163.22 cases per 100,000 residents in the region. Multiple days during which a particularly high number of cases were identified in the region were connected to outbreaks reported by local news outlets and health departments. Most of these outbreaks were linked to congregate settings such as schools, long-term care facilities, and food processing facilities. Implications: By examining data available in a largely rural region that includes jurisdictions across three states, authors were able to describe and disseminate information about COVID-19 case incidence and fatalities and identify acute and prolonged local outbreaks. Continuing to follow, interpret, and report accurate and timely COVID-19 case data in regions like this one is vital to residents, businesses, healthcare providers, and policymakers.

Niche modeling for the genus Pogona (Squamata: Agamidae) in Australia: predicting past (late Quaternary) and future (2070) areas of suitable habitat.

BACKGROUND: As the climate warms, many species of reptiles are at risk of habitat loss and ultimately extinction. Locations of suitable habitat in the past, present, and future were modeled for several lizard species using MaxEnt, incorporating climatic variables related to temperature and precipitation. In this study, we predict where there is currently suitable habitat for the genus Pogona and potential shifts in habitat suitability in the past and future. METHODS: Georeferenced occurrence records were obtained from the Global Biodiversity Information Facility, climate variables (describing temperature and precipitation) were obtained from WorldClim, and a vegetation index was obtained from AVHRR satellite data. Matching climate variables were downloaded for three different past time periods (mid-Holocene, Last Glacial Maximum, and Last Interglacial) and two different future projections representative concentration pathways (RCPs 2.6 and 8.5). MaxEnt produced accuracy metrics, response curves, and probability surfaces. For each species, parameters were adjusted for the best possible output that was biologically informative. RESULTS: Model results predicted that in the past, there was little suitable habitat for P. henrylawsoni and P. microlepidota within the areas of their current range. Past areas of suitable habitat for P. barbata were predicted to be similar to the current prediction. Pogona minor and P. nullarbor were predicted to have had a more expansive range of suitable habitat in the past, which has reduced over time. P. vitticeps was predicted to have less suitable habitat in the past when examining the region of their known occurrence; however, there was predicted growth in suitable habitat in Western Australia. Both 2070 models predict a similar distribution of habitat; however, the model produced using the 2070 RCP 8.5 climate change projection showed a larger change, both in areas of suitable habitat gain and loss. In the future, P. henrylawsoni and P. microlepidota might gain suitable habitat, while the other four species could possibly suffer habitat loss. DISCUSSION: Based on the model results, P. henrylawsoni and P. microlepidota had minimal areas of suitable habitat during the Last Glacial Maximum, possibly due to changes in tolerance or data/model limitations, especially since genetic analyses for these species suggest a much earlier emergence. The predicted late Quaternary habitat results for all species of Pogona are conservative and should be compared to the fossil record which is not possible at the moment due to the current inability to identify fossil Pogona to the species level. P. nullarbor and P. vitticeps future models predict substantial habitat loss. P. nullarbor could potentially be considered vulnerable in the present since it already has a restricted range, and a conservation plan may need to be considered.

Iron and Manganese in Groundwater: Using Kriging and GIS to Locate High Concentrations in Buncombe County, North Carolina.

For health, economic, and aesthetic reasons, allowable concentrations (as suggested by the United States Environmental Protection Agency) of the secondary contaminants iron (Fe) and manganese (Mn) found present in drinking water are 0.3 and 0.05 mg/L, respectively. Water samples taken from private drinking wells in rural communities within Buncombe County, North Carolina contain concentrations of these metals that exceed secondary water quality criteria. This study predicted the spatial distribution of Fe and Mn in the county, and evaluated the effect of site environmental factors (bedrock geology, ground elevation, saprolite thickness, and drinking water well depth) in controlling the variability of Fe and Mn in groundwater. A statistically significant correlation between Fe and Mn concentrations, attributable to bedrock geology, was identified. Prediction models were created using ordinary kriging and cokriging interpolation techniques to estimate the presence of Fe and Mn in groundwater where direct measurements are not possible. This same procedure can be used to estimate the trend of other contaminants in the groundwater in different areas with similar hydrogeological settings.

Assessing shoreline exposure and oyster habitat suitability maximizes potential success for sustainable shoreline protection using restored oyster reefs.

Oyster reefs provide valuable ecosystem services that contribute to coastal resilience. Unfortunately, many reefs have been degraded or removed completely, and there are increased efforts to restore oysters in many coastal areas. In particular, much attention has recently been given to the restoration of shellfish reefs along eroding shorelines to reduce erosion. Such fringing reef approaches, however, often lack empirical data to identify locations where reefs are most effective in reducing marsh erosion, or fully take into account habitat suitability. Using monitoring data from 5 separate fringing reef projects across coastal Louisiana, we quantify shoreline exposure (fetch + wind direction + wind speed) and reef impacts on shoreline retreat. Our results indicate that fringing oyster reefs have a higher impact on shoreline retreat at higher exposure shorelines. At higher exposures, fringing reefs reduced marsh edge erosion an average of 1.0 m y(-1). Using these data, we identify ranges of shoreline exposure values where oyster reefs are most effective at reducing marsh edge erosion and apply this knowledge to a case study within one Louisiana estuary. In Breton Sound estuary, we calculate shoreline exposure at 500 random points and then overlay a habitat suitability index for oysters. This method and the resulting visualization show areas most likely to support sustainable oyster populations as well as significantly reduce shoreline erosion. Our results demonstrate how site selection criteria, which include shoreline exposure and habitat suitability, are critical to ensuring greater positive impacts and longevity of oyster reef restoration projects.

Old health risks in new places? An ecological niche model for I. ricinus tick distribution in Europe under a changing climate.

Climate change will likely have impacts on disease vector distribution. Posing a significant health threat in the 21st century, risk of tick-borne diseases may increase with higher annual mean temperatures and changes in precipitation. We modeled the current and future potential distribution of the Ixodes ricinus tick species in Europe. The Genetic Algorithm for Rule-set Prediction (GARP) was utilized to predict potential distributions of I. ricinus based on current (1990-2010 averages) and future (2040-2060 averages) environmental variables. A ten model best subset was created out of a possible 200 models based on omission and commission criteria. Our results show that under the A2 climate change scenario the potential habitat range for the I. ricinus tick in Europe will expand into higher elevations and latitudes (e.g., Scandinavia, the Baltics, and Belarus), while contracting in other areas (e.g., Alps, Pyrenees, interior Italy, and northwestern Poland). Overall, a potential habitat expansion of 3.8% in all of Europe is possible. Our results may be used to inform climate change adaptation efforts in Europe.