Baton Rouge Area Research Articles

Unstructured-grid approach to develop high-fidelity groundwater model to understand groundwater flow and storage responses to excessive groundwater withdrawals in the Southern Hills aquifer system in southeastern Louisiana (USA)

Study regionThe Southern Hills aquifer system (SHAS) in the Louisiana Capital Area Groundwater Conservation District (CAGCD), USA. Study focusThe SHAS provides abundant groundwater for public and industrial supplies in the CAGCD. Groundwater depletion, saltwater intrusion, and land subsidence are potential concerns due to prolonged excessive groundwater withdrawals. This study develops a high-fidelity groundwater flow model utilizing a complex unstructured grid to investigate groundwater flow and storage responses to excessive groundwater withdrawals for the SHAS in the CAGCD. The groundwater model incorporates the Mississippi River alluvial aquifer down to the Miocene sands extending to depths around 1 km. New hydrological insightsGroundwater modeling results indicate large cones of depression in the Evangeline and Jasper formations in the Baton Rouge area due to prolonged groundwater withdrawals. Low-permeability faults are inferred by significant groundwater level difference across the faults. While local groundwater storage depletion in deeper aquifers is evident, overall estimated groundwater storage changes of the SHAS in the CAGCD are close to zero in the past two decades, indicating insignificant groundwater storage changes. This is attributed to dominant interactions between the major rivers and the shallower alluvial aquifer. In addition, the simulated groundwater storage changes exhibit patterns similar to those derived by the Gravity Recovery and Climate Experiment (GRACE) model that has been used in evaluation of groundwater depletion in many regional studies.

Assessing the Impact of Land Use and Land Cover Change on Air Quality in East Baton Rouge—Louisiana Using Earth Observation Techniques

There has been significant research in recent decades on Land use Land cover (LULC) changes and their influence on biodiversity but little to no research on its impact on air quality. This research seeks to demonstrate how geospatial technologies such as geographic information system (GIS) and remote sensing can be used to assess the effects of LULC changes on particulate matter emissions and their impact on air quality in the East Baton Rouge area. In pursuit of these objectives, this study uses LANDSAT imageries from the past 30 years specifically Landsat Thematic Mapper (TM C2L2) and Landsat 8 Operational Land Imager/Thermal Infrared (OLI/TIRS C2L2) covering 1991, 2001, 2011 and 2021 were collected, processed, and analyzed for the LULC change analysis using QGIS software. Additionally, Sentinel 5P and the Air quality index from the U.S. Environmental Protection Agency (EPA) were used to assess the air quality trend over the years to establish the correlation between LULC and air quality. Results showed an increasing trend in air quality over the past 3 decades with concentrations of CO, NO2, and PM2.5 abruptly falling however, urbanization and the population expanded throughout the time. The paper concludes by outlining a policy recommendation in the form of encouraging Louisiana residents to use alternative renewable energies rather than the over-dependence on coal-fired electric generating plants that have an impact on the environment.

Frequency of Symptoms and Asymptomatic SARS-CoV-2 Infection in Louisiana, USA

Background: While many surveillance studies of seroprevalence to SARS-CoV-2 rely on remnant blood samples obtained as medical waste, representative, prospective collection allows for analysis of a representative cross-section of symptomatic and asymptomatic presentation of infection in the community. Louisiana, and particularly New Orleans, were hard-hit in the early phase of the pandemic, and an ongoing outbreak was occurring in Baton Rouge throughout July.Methods: A representative, cross-sectional sample of subjects from two cities in Louisiana were sent to testing sites to complete a verbal consent, survey, nasopharyngeal swab, and blood draw. Swabs were tested for active viral shedding (PCR) and blood was tested for immunoglobulin G (IgG) specific to SARS-CoV-2.Findings: Anosmia was extremely predictive for a positive test (40·6% of those with anosmia tested positive, OR: 13·6; CI 10·1, 18·3) and 47·3% of the sample experienced no symptoms at all. A lower quantity of virus was noted during the contagious phase of infection in asymptomatic compared to symptomatic individuals. Symptom presentation clustered into three groups; low/no symptoms (0·4±0·9 symptoms on average), highly symptomatic (7·5±1·9) or moderately symptomatic (4·0±1·5). The probability of reporting symptoms changed with age; those under age 60 had a >50% probability of reporting symptoms while those 60 years and older had Interpretation: Anosmia should be used as a screening criterion to differentiate from other illnesses, and, given the high ratio of asymptomatic individuals, mask mandates should be enforced. Asymptomatic individuals should be tested with cause.Funding: This study was funded by ReNOLA, Ochsner Health, the Baton Rouge Area Foundation, Louisiana COVID-19 Health Equity Task Force, and The Humana Foundation, the Blue Cross and Blue Shield of Louisiana Foundation, Healthy Blue, the Huey and Angelina Wilson Foundation, and the Irene W. and C.B. Pennington Foundation.Declaration of Interests: The authors have no other conflicts of interest to report.Ethics Approval Statement: This study was approved by the Ochsner Clinic Foundation Institutional Review Board #2020·163.

Bayesian set pair analysis and machine learning based ensemble surrogates for optimal multi-aquifer system remediation design

Surrogate models are often adopted to substitute computationally intensive groundwater simulation models for aquifer management due to their high effectiveness and computing efficiency. However, solutions of using only one surrogate model are prone to large prediction uncertainty. This study compares individual surrogate models and an ensemble surrogate model in an optimal groundwater remediation design problem. Three machine learning based surrogate models (response surface regression model, artificial neural network and support vector machine) were developed to replace a high-fidelity solute transport model for predicting saltwater intrusion and assisting saltwater scavenging design. An optimal Latin hypercube design was employed to generate training and testing datasets. Set pair analysis was employed to construct a more reliable ensemble surrogate and to address prediction uncertainty arising from individual surrogate models. Bayesian set pair weights were derived by utilizing full information from both training and testing data and improved typical set pair weights. The individual and ensemble surrogate models were applied to the salinization remediation problem in the Baton Rouge area, southeast Louisiana. The optimal remediation design includes two conflicting objectives: minimizing total groundwater extraction from a horizontal scavenger well while maximizing chloride concentration difference to the MCL (maximum contamination level) at monitoring locations. NSGA-II (Non-dominated Sorting Genetic Algorithm II) was employed to solve the nonlinear optimization model and obtain Pareto-optimal pumping schedules. The optimal pumping schedules from ensemble surrogate models and individual surrogate models were verified by the solute transport model. The study found that Bayesian set pair analysis builds robust ensemble surrogates and accounts for model prediction uncertainty. The ensemble-surrogate-assisted optimization model provides stable and reliable solutions while considerably alleviating computational burden.

Medicaid Utilization Before and After a Natural Disaster in the 2016 Baton Rouge–Area Flood

Objectives. To understand changes in behavioral health services utilization and expenditures before and after natural disaster with an adult Medicaid population affected by the Baton Rouge, Louisiana-area flood (August 2016).Methods. We examined de-identified behavioral health claims data for Medicaid-insured adults in the affected region for 10 months before and after flooding (October 2015-June 2017). This constituted 273 233 provider claims for 22 196 individuals. Claims data included patient gender, behavioral health diagnoses, treatment dates, and costs. We made adjustments for Medicaid expansion by using monthly enrollment data.Results. Overall, most male patient behavioral health care visits were for substance use disorders (33.6%) and most female patient behavioral health care visits were for depression-related disorders (30%). Both diagnostic categories increased after the flood by 66% and 44%, respectively. Expansion accounted for a 4% increase in claims. Postflood claims reflected 8% to 10% higher costs.Conclusions. Greater amounts of behavioral health care services were sought in all 10 months of the postflood study period. We observed gender differences in use of services and diagnoses. Behavioral health care services following natural disasters must be extended longer than traditionally expected, with consideration for specific population needs.

Lessons Learned from Community Health Providers in Posthurricane Receiving Communities

Abstract There is an accumulating body of research on behavioral health, temporary displacement, and social connectedness after disasters; however, less is known about perceptions of providers regarding services and the effectiveness of the services that are offered. The purpose of this study is to provide an in-depth analysis of reflections from providers who worked immediately after Hurricane Katrina in the Greater Baton Rouge area, which was one of the largest receiving communities. This study provides a response legacy framework with findings that emphasize collaboration, improved understanding of cultural differences, disaster planning and readiness, improved understanding of trauma informed care, self-care, and policy changes. The study also provides ways to support disaster response professionals in their efforts toward increasing social justice and fostering of community resilience. Our study found that providers were satisfied with their postdisaster work and feel that evidence informed changes t...

Market Surveys to Determine Availability of Reduced Glycemic Load/High Fiber Products

ABSTRACTAvailability of prepared foods in today’s market that provide healthy diets for consumers 65 and older is lacking. A general market survey, covering nine grocery stores and approximately 400 items in the greater Baton Rouge area, was conducted on snack foods, frozen meals, and dry products. Two other surveys included a survey of pasta items and a blind consumer survey targeting consumers ages 65 and older. In each survey, products were categorized as high, medium, or low in fiber and low, medium, or high glycemic load. Prepared meals with high levels of dietary fiber and low glycemic loads were found to be rare. Results from the blind consumer survey found that key unsatisfactory characteristics in commercial products were texture and color. Our research suggests that there is a need for the development of healthier prepared meals in the grocery store market.

Modeling complex aquifer systems: a case study in Baton Rouge, Louisiana (USA)

This study targets two challenges in groundwater model development: grid generation and model calibration for aquifer systems that are fluvial in origin. Realistic hydrostratigraphy can be developed using a large quantity of well log data to capture the complexity of an aquifer system. However, generating valid groundwater model grids to be consistent with the complex hydrostratigraphy is non-trivial. Model calibration can also become intractable for groundwater models that intend to match the complex hydrostratigraphy. This study uses the Baton Rouge aquifer system, Louisiana (USA), to illustrate a technical need to cope with grid generation and model calibration issues. A grid generation technique is introduced based on indicator kriging to interpolate 583 wireline well logs in the Baton Rouge area to derive a hydrostratigraphic architecture with fine vertical discretization. Then, an upscaling procedure is developed to determine a groundwater model structure with 162 layers that captures facies geometry in the hydrostratigraphic architecture. To handle model calibration for such a large model, this study utilizes a derivative-free optimization method in parallel computing to complete parameter estimation in a few months. The constructed hydrostratigraphy indicates the Baton Rouge aquifer system is fluvial in origin. The calibration result indicates hydraulic conductivity for Miocene sands is higher than that for Pliocene to Holocene sands and indicates the Baton Rouge fault and the Denham Springs-Scotlandville fault to be low-permeability leaky aquifers. The modeling result shows significantly low groundwater level in the “2,000-foot” sand due to heavy pumping, indicating potential groundwater upward flow from the “2,400-foot” sand.

Law enforcement perceptions of their relationship with community: Law enforcement surveys and community focus groups

ABSTRACTThe Baton Rouge Area Violence Elimination (BRAVE) Project is a group violence reduction strategy based on the Boston Gun Project’s Operation Ceasefire. This violence reduction model is predicated on the idea that violence can be dramatically reduced when community members and law enforcement join together to directly engage with criminal groups. In Baton Rouge, selected law enforcement officers have received specialized training regarding the implementation of the BRAVE Project and additional training with regard to working with residents in the community. To that end, surveys and focus groups were administered to residents in the intervention target area to identify their perceptions of crime, law enforcement, and leaders in their community. In addition, law enforcement officers completed surveys that focused on their perceptions of crime and other problems in the target area and their thoughts about whether this intervention could be successful. Results suggest that law enforcement and community members agree on what the problems are but disagree on who is responsible for them and how to solve them. Follow-up surveys and focus groups have been administered to determine whether residents in the target area have changed their perceptions of law enforcement. This article discusses the results of those surveys, the implications of such a violence reduction model, and recommendations for similar models in other cities.

Bayesian experimental design for identification of model propositions and conceptual model uncertainty reduction

The lack of hydrogeological data and knowledge often results in different propositions (or alternatives) to represent uncertain model components and creates many candidate groundwater models using the same data. Uncertainty of groundwater head prediction may become unnecessarily high. This study introduces an experimental design to identify propositions in each uncertain model component and decrease the prediction uncertainty by reducing conceptual model uncertainty. A discrimination criterion is developed based on posterior model probability that directly uses data to evaluate model importance. Bayesian model averaging (BMA) is used to predict future observation data. The experimental design aims to find the optimal number and location of future observations and the number of sampling rounds such that the desired discrimination criterion is met. Hierarchical Bayesian model averaging (HBMA) is adopted to assess if highly probable propositions can be identified and the conceptual model uncertainty can be reduced by the experimental design. The experimental design is implemented to a groundwater study in the Baton Rouge area, Louisiana. We design a new groundwater head observation network based on existing USGS observation wells. The sources of uncertainty that create multiple groundwater models are geological architecture, boundary condition, and fault permeability architecture. All possible design solutions are enumerated using a multi-core supercomputer. Several design solutions are found to achieve an 80%-identifiable groundwater model in 5 years by using six or more existing USGS wells. The HBMA result shows that each highly probable proposition can be identified for each uncertain model component once the discrimination criterion is achieved. The variances of groundwater head predictions are significantly decreased by reducing posterior model probabilities of unimportant propositions.

Bayesian Chance-Constrained Hydraulic Barrier Design under Geological Structure Uncertainty.

The groundwater community has widely recognized geological structure uncertainty as a major source of model structure uncertainty. Previous studies in aquifer remediation design, however, rarely discuss the impact of geological structure uncertainty. This study combines chance-constrained (CC) programming with Bayesian model averaging (BMA) as a BMA-CC framework to assess the impact of geological structure uncertainty in remediation design. To pursue this goal, the BMA-CC method is compared with traditional CC programming that only considers model parameter uncertainty. The BMA-CC method is employed to design a hydraulic barrier to protect public supply wells of the Government St. pump station from salt water intrusion in the "1500-foot" sand and the "1700-foot" sand of the Baton Rouge area, southeastern Louisiana. To address geological structure uncertainty, three groundwater models based on three different hydrostratigraphic architectures are developed. The results show that using traditional CC programming overestimates design reliability. The results also show that at least five additional connector wells are needed to achieve more than 90% design reliability level. The total amount of injected water from the connector wells is higher than the total pumpage of the protected public supply wells. While reducing the injection rate can be achieved by reducing the reliability level, the study finds that the hydraulic barrier design to protect the Government St. pump station may not be economically attractive.

A Hierarchical Bayesian Model Averaging Framework for Groundwater Prediction under Uncertainty

Groundwater prediction models are subjected to various sources of uncertainty. This study introduces a hierarchical Bayesian model averaging (HBMA) method to segregate and prioritize sources of uncertainty in a hierarchical structure and conduct BMA for concentration prediction. A BMA tree of models is developed to understand the impact of individual sources of uncertainty and uncertainty propagation to model predictions. HBMA evaluates the relative importance of different modeling propositions at each level in the BMA tree of model weights. The HBMA method is applied to chloride concentration prediction for the "1,500-foot" sand of the Baton Rouge area, Louisiana from 2005 to 2029. The groundwater head data from 1990 to 2004 is used for model calibration. Four sources of uncertainty are considered and resulted in 180 flow and transport models for concentration prediction. The results show that prediction variances of concentration from uncertain model elements are much higher than the prediction variance from uncertain model parameters. The HBMA method is able to quantify the contributions of individual sources of uncertainty to the total uncertainty.

Indicator geostatistics for reconstructing Baton Rouge aquifer-fault hydrostratigraphy, Louisiana, USA

The complex siliciclastic aquifer system underneath the Baton Rouge area, Louisiana (USA), is fluvial in origin and is characterized by strongly binary heterogeneity of sand units and mudstones as pervious and impervious hydrofacies. The east–west trending Baton Rouge fault and Denham Springs-Scotlandville fault cut across East Baton Rouge Parish and play an important role in groundwater flow and aquifer salinization. This study reconstructs the Baton Rouge aquifer-fault system architecture for a Miocene-Pliocene depth interval that consists of the 1,200-foot sand to the 2,000-foot sand. The results show the spatial extent of sand units, their interconnections, and flow paths within each sand unit. The regional-scale formation dip, the sand unit offset on the faults, and the volumetric spatial extent of individual sand units are quantified. The study reveals the complexity of the Baton Rouge aquifer-fault system where the sand deposition is non-uniform, different sand units are interconnected, the sand unit displacement on the faults is significant, and the spatial distribution of flow pathways through the faults is sporadic. The identified locations of flow pathways through the Baton Rouge fault provide useful information on possible windows for saltwater intrusion from the south.

A school wellness program combined with repeated taste exposures increased preferences for fruits and vegetables in fourth and fifth grade children

Children's food preferences are major determinants of their consumption. The present study aimed to increase children's preferences for fruits and vegetables (FV) through a school wellness program combined with cafeteria vegetable tasting. A total of 250 fourth and fifth grade students (41% boys; 63% fourth graders) attending low‐income, public elementary schools in southeastern Louisiana participated. The 15‐week intervention included a classroom curriculum that emphasized benefits and consumption of FV and a cafeteria‐based vegetable tasting program (four vegetables). After participating in the intervention, children's knowledge of the benefits of eating FV increased (p < .01). Nutrition knowledge was greater among fifth graders as compared to fourth graders (p < .01) and girls compared to boys (p < .01). Children's preferences for baked potatoes, greens, and green beans increased (p < .01) and fourth graders had higher preferences for apples, oranges, pineapple, strawberries, and tangerines than fifth graders (p = .02). For broccoli, carrots, celery, cabbage, corn, lettuce, and spinach fifth grader's preferences were increased while fourth grader's preferences dropped following the intervention (p = .03). This school wellness program increased children's nutrition knowledge and preferences for a variety of FV. Funding: Baton Rouge Area and Blue Cross and Blue Shield of Louisiana FoundationsGrant Funding Source: Baton Rouge Area and Blue Cross and Blue Shield of Louisiana Foundations

Bayesian model averaging assessment on groundwater management under model structure uncertainty

This study introduces Bayesian model averaging (BMA) to deal with model structure uncertainty in groundwater management decisions. A robust optimized policy should take into account model parameter uncertainty as well as uncertainty in imprecise model structure. Due to a limited amount of groundwater head data and hydraulic conductivity data, multiple simulation models are developed based on different head boundary condition values and semivariogram models of hydraulic conductivity. Instead of selecting the best simulation model, a variance-window-based BMA method is introduced to the management model to utilize all simulation models to predict chloride concentration. Given different semivariogram models, the spatially correlated hydraulic conductivity distributions are estimated by the generalized parameterization (GP) method that combines the Voronoi zones and the ordinary kriging (OK) estimates. The model weights of BMA are estimated by the Bayesian information criterion (BIC) and the variance window in the maximum likelihood estimation. The simulation models are then weighted to predict chloride concentrations within the constraints of the management model. The methodology is implemented to manage saltwater intrusion in the “1,500-foot” sand aquifer in the Baton Rouge area, Louisiana. The management model aims to obtain optimal joint operations of the hydraulic barrier system and the saltwater extraction system to mitigate saltwater intrusion. A genetic algorithm (GA) is used to obtain the optimal injection and extraction policies. Using the BMA predictions, higher injection rates and pumping rates are needed to cover more constraint violations, which do not occur if a single best model is used.

Library experiences of Hurricane Katrina and New Orleans flood survivors

Abstract More than one million residents were displaced by Hurricane Katrina and the New Orleans Flood. Uprooted from their lives and dispersed across the country, survivors found themselves hundreds of miles away from home. Some found comfort and much needed information in public libraries. This article discusses the library experiences of survivors as revealed through an online survey and in-depth interviews. The study, conducted from August to October of 2006, found that nearly one-half of survey respondents and 40% of interviewees used libraries following the disasters. The reasons for their visits included Internet access, information and technology assistance, mental escape, and refuge. Participants also discussed how the destruction of libraries added to their sense of loss and how the restoration of libraries gave them a sense of hope. Keywords: Hurricane Katrina, New Orleans Flood, Evacuees, Public Libraries, Information Needs, Disasters, Disaster Communication Introduction Hurricane Katrina and the New Orleans Flood1 destroyed more than 200,000 homes and 18,000 businesses, and scattered over a million people throughout the United States (CNN, 2005; Louisiana Recovery Authority, 2006a). Evacuees who thought they would be home within a matter of days instead found themselves in shelters and hotel rooms for months. A year after Hurricane Katrina and the Flood, fifty percent of residents still had not returned home (Greater New Orleans Community Data Center, 2008). These disasters caused the most massive and prolonged displacement of American citizens in recent memory (Nigg, Barnshaw, & Torres, 2006). For the people living through these catastrophic events, accessing information and communicating with others became difficult. Survivors often could not contact family, friends, neighbors, or employers (LRA, 2006b). Desperate to reach loved ones and find vital information about the status of their hometowns, many people visited the one place that is open to everyone, offers free services, and exists in almost all communities-the public library. This article reports the library use and library experiences of survivors following the Hurricane Katrina and New Orleans Flood (the Flood) disasters as discovered by a study in 2006 comprised of an online survey and in-depth interviews. The study finds that libraries played important roles in assisting survivors find and access information, and in helping to provide a refuge and an escape. The article advocates for librarians to take an active interest in discovering ways to assist in disaster situations. It also suggests that libraries should be considered a vital source to citizens and the disaster planning community before, during, and after natural and man-made disasters. Several key points regarding how librarians can help disaster survivors are provided. Literature Review At the time of this study the library literature contained numerous articles which focused on how librarians provided services during and after Hurricane Katrina and the Flood. Fletcher (2006) discussed how medical librarians quickly organized, sent requests for donations, selected materials, and delivered them to doctors working at shelters in the Baton Rouge area. She found that resources for use in shelter clinics should be print based and portable, brief, prescriptive, and of course current. Librarians in Louisiana and surrounding states reported how they issued library cards, assisted with completion of disaster relief forms, gave referrals to government agencies, and provided books and local information to evacuees (Albanese, Blumenstein, Oder, & Rogers, 2005). Dickerson (2007) discussed how he, as director of the Jefferson Parish Library (JPL), reorganized the library, removed barriers to access, and served thousands of residents from neighboring parishes. In the months following Katrina, JPL distributed more than 3,600 library cards and co-sponsored programming sessions such as chainsaw and mold safety, and medical and psychological awareness. …

Bayesian model averaging for groundwater head prediction and uncertainty analysis using multimodel and multimethod

This study introduces a Bayesian model averaging (BMA) method that incorporates multiple groundwater models and multiple hydraulic conductivity estimation methods to predict groundwater heads and evaluate prediction uncertainty. BMA is able to distinguish prediction uncertainty arising from individual models, between models, and between methods. Moreover, BMA is able to identify unfavorable models even though they may present small prediction uncertainty. Uncertainty propagation, from model parameter uncertainty to model prediction uncertainty, can also be studied through BMA. This study adopts a variance window to obtain reasonable BMA weights for the best models, which are usually exaggerated by Occam's window. Results from a synthetic case study show that BMA with the variance window can provide better head prediction than individual models, or at least can obtain better predictions close to the best model. The BMA was applied to predicting groundwater heads in the “1500‐foot” sand of the Baton Rouge area in Louisiana. Head prediction uncertainty was assessed by the BMA prediction variance. BMA confirms that large head prediction uncertainty occurs at areas lacking head observations and hydraulic conductivity measurements. Further study in these areas is necessary to reduce head prediction uncertainty.

Cognitive Behavioral Therapy for Postdisaster Distress: A Community Based Treatment Program for Survivors of Hurricane Katrina

Many disaster survivors suffer from postdisaster distress regardless of whether or not they meet criteria for specific psychiatric diagnoses. Cognitive Behavior Therapy for Postdisaster Distress (CBT-PD), a ten-session manualized intervention, was developed to address a range of cognitive, emotional, and behavioral reactions to disaster. Trained community-based therapists provided CBT-PD to adult survivors of Hurricane Katrina as part of InCourage, a program sponsored by the Baton Rouge Area Foundation. Participants (n = 88) who were assessed at referral, pretreatment, intermediate treatment, and posttreatment showed significant and large improvements. The overall pre-post effect size was 1.4 in intention-to-treat analyses. Improvements were comparable for persons with more severe distress and persons with moderate distress at referral. Benefits were maintained at follow-up for the 66 adults who have been assessed.

Repeated taste exposure increases preferences for vegetables in elementary school aged children

Children's food preferences play a major role in their food choices and consumption. This study aimed to increase children's preferences for fruit and vegetables by offering repeated opportunities to taste less liked vegetables. A total of 370 fourth and fifth grade students (44% boys; 61% fourth graders) attending low‐income, public elementary schools in southeastern Louisiana volunteered to participate. Once a week for 10 weeks children were given a taste of carrots, peas, tomatoes and bell peppers, and then asked to record their preference for each vegetable using a Likert‐type response scale. The percent of children that tasted all 10 times was 26% for carrots, 20.3% for peas, 19% for tomatoes, and 18.5% for bell peppers. Repeated measures ANOVAs indicated that repeated tasting improved preferences for all four vegetables: carrots (p<0.01); peas (p<0.01); tomatoes (p<0.01); bell peppers (p<0.05). A minimum of 6 tastings were needed to observe a change in preference score. At the end of 10 opportunities to taste, the percentage of children who had tasted at least 6 times was 74% for carrots, 70% for peas, 63% for tomatoes, and 60% for bell peppers. Repeated taste exposure is a promising strategy for promoting liking of less liked vegetables in children. This project was funded by the Baton Rouge Area Foundation, Blue Cross and Blue Shield of Louisiana Foundation, and the LSU AgCenter.Grant Funding SourceBaton Rouge Area Foundation adn Blue Cross Blue Shield of Louisiana

A regional human services authority’s rapid needs assessment of evacuees following natural disasters

The Atlantic hurricane season of 2005 was not an ordinary season, and Hurricane Katrina was not an ordinary hurricane. Hurricane Katrina damaged more than 93,000 square miles of Gulf of Mexico coastline, displaced more than 1 million residents from New Orleans, and flooded more than 80 percent of New Orleans for weeks, which killed more than 1,300 people, mostly New Orleanians. Inland regional state and local healthcare and human services agencies rushed to assist evacuees, most of whom were uninsured or displaced without employer healthcare coverage. The initial evacuation brought more than 350,000 evacuees seeking shelter to the greater Baton Rouge area, LA, 80 miles north of New Orleans, the closest high ground. This investigation describes the rapid needs assessment developed and conducted by the Capital Area Human Services District of the greater Baton Rouge area, a quasi-governmental human services authority, the regional provider of state-funded mental health, addictive disorders, and developmental disabilities services, on a sample of 6,553 Katrina evacuees in the greater Baton Rouge area. In the event of catastrophic natural and manmade disasters, state and federal decision makers should follow the National Incident Management System and support local designated lead agencies with additional resources as requested. They must rely on designated lead agencies to use their knowledge of the locale, local resources, and relationships with other providers and volunteers to respond rapidly and efficiently to evacuee needs identified through a designated, concise tool that is singularly utilized across the impacted region by all providers to determine the needed response.