South Atlantic States Research Articles

Excess natural-cause mortality in US counties and its association with reported COVID-19 deaths

In the United States, estimates of excess deaths attributable to the COVID-19 pandemic have consistently surpassed reported COVID-19 death counts. Excess deaths reported to non-COVID-19 natural causes may represent unrecognized COVID-19 deaths, deaths caused by pandemic health care interruptions, and/or deaths from the pandemic's socioeconomic impacts. The geographic and temporal distribution of these deaths may help to evaluate which explanation is most plausible. We developed a Bayesian hierarchical model to produce monthly estimates of excess natural-cause mortality for US counties over the first 30 mo of the pandemic. From March 2020 through August 2022, 1,194,610 excess natural-cause deaths occurred nationally [90% PI (Posterior Interval): 1,046,000 to 1,340,204]. A total of 162,886 of these excess natural-cause deaths (90% PI: 14,276 to 308,480) were not reported to COVID-19. Overall, 15.8 excess deaths were reported to non-COVID-19 natural causes for every 100 reported COVID-19 deaths. This number was greater in nonmetropolitan counties (36.0 deaths), the West (Rocky Mountain states: 31.6 deaths; Pacific states: 25.5 deaths), and the South (East South Central states: 26.0 deaths; South Atlantic states: 25.0 deaths; West South Central states: 24.2 deaths). In contrast, reported COVID-19 death counts surpassed estimates of excess natural-cause deaths in metropolitan counties in the New England and Middle Atlantic states. Increases in reported COVID-19 deaths correlated temporally with increases in excess deaths reported to non-COVID-19 natural causes in the same and/or prior month. This suggests that many excess deaths reported to non-COVID-19 natural causes during the first 30 mo of the pandemic in the United States were unrecognized COVID-19 deaths.

A nowcast model to predict outdoor flea activity in real time for the contiguous United States.

The cat flea (Ctenocephalides felis), a parasite commonly found on both dogs and cats, is a competent vector for several zoonotic pathogens, including Dipylidium caninum (tapeworms), Bartonella henselae (responsible for cat scratch disease) and Rickettsia felis (responsible for flea-borne spotted fever). Veterinarians recommend that both cats and dogs be routinely treated with medications to prevent flea infestation. Nevertheless, surveys suggest that nearly one third of pet owners do not routinely administer appropriate preventatives. A mathematical model based on weighted averaging over time is developed to predict outdoor flea activity from weather conditions for the contiguous United States. This 'nowcast' model can be updated in real time as weather conditions change and serves as an important tool for educating pet owners about the risks of flea-borne disease. We validate our model using Google Trends data for searches for the term 'fleas.' This Google Trends data serve as a proxy for true flea activity, as validating the model by collecting fleas over the entire USA is prohibitively costly and time-consuming. The average correlation (r) between the nowcast outdoor flea activity predictions and the Google Trends data was moderate: 0.65, 0.70, 0.66, 0.71 and 0.63 for 2016, 2017, 2018, 2019 and 2020, respectively. However, there was substantial regional variation in performance, with the average correlation in the East South Atlantic states being 0.81 while the average correlation in the Mountain states was only 0.45. The nowcast predictions displayed strong seasonal and geographic patterns, with predicted activity generally being highest in the summer months. The nowcast model is a valuable tool by which to educate pet owners regarding the risk of fleas and flea-borne disease and the need to routinely administer flea preventatives. While it is ideal for domestic cats and dogs to on flea preventatives year-round, many pets remain vulnerable to flea infestation. Alerting pet owners to the local increased risk of flea activity during certain times of the year may motivate them to administer appropriate routine preventives.

The impact of race and ethnicity on survival in primary liver cancer: A propensity-adjusted analysis.

500 Background: Primary liver cancer is the fifth most common malignancy and the second most frequent cause of cancer-related death worldwide. Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer, followed by Intrahepatic cholangiocarcinoma (ICC), and the incidence of liver cancer is rapidly rising in the United States. Race and ethnicity affect the outcomes in many solid cancers; therefore, we aimed to study the effect of race and ethnicity on overall survival (OS) in primary liver cancer. Methods: We selected adult patients who had primary liver cancer (HCC and ICC) diagnosed between 2004 and 2016 using the NCDB database. We stratified the patients into two groups as white and black. We performed the Kaplan-Meier method for median overall survival (OS), and the Cox regression method for multivariate analyses after adjusting for clinically significant confounding variables. Also, we used 1:1 nearest neighbor propensity score matching to reduce selection bias. Results: A total of 122,049 patients, 83.1% was white, 16.9% was black. Black patients were more likely to be young ( p<.001), to live in the metropolitan area ( p<.001) and South Atlantic states ( p<.001), to be treated academic/research facility ( p<.001), to be uninsured ( p<.001). In contrast, white patients were most frequently to be highly educated ( p<.001), to have higher income ( p<.001), to travel longer distances (≥50 miles) for treatment ( p<.001). Also, black patients had a higher rate of HCC ( p<.001), advanced stage ( p<.001), high metastasis rate ( p<.001), whereas white patients had a higher rate of ICC ( p<.001), higher comorbidity ( p<.001), high treatment rate (surgery, chemotherapy, and radiotherapy) ( p<.001). The gender percentage was similar in both groups. In unmatched groups, white patients had significantly better median OS compared to black (9.9 vs. 8.4 months, p<.001), but this difference did not continue after adjusted for age, sex, facility type, insurance status, income, education, rurality, travel distance, comorbidity, metastatic rate, treatment receipt (surgery, chemotherapy, radiotherapy), primary site (HR=1.01 95% CI: 0.99-1.03, p=.18). In ethnic groups, Hispanics had significantly improved OS compared to non-Hispanic white (NHW) and non-Hispanic black patients (NHB) (median OS 12 vs. 9.7 vs. 8.5 months, respectively, p<.001), and this significance was persisted with multivariate analysis (HR=0.80 95% CI: 0.78-0.82, p<.001). After propensity score matching, white and black patients were similar OS (p=NS) but Hispanics were still significantly improved OS versus NHW and NHB patients (HR=0.76 95% CI: 0.71-0.80, p<.001). Conclusions: Black patients had a higher stage, percentage of metastasis and lower treatment rate, but they had a similar OS compared to white patients. Hispanics had significantly improved OS than others, even after adjusted for clinically important confounding variables.

Soil carbon in the South Atlantic United States: Land use change, forest management, and physiographic context

Evidence-based forest carbon (C) management requires identifying baseline patterns and drivers of soil organic carbon (SOC) stocks, and their responses to land use change and management, at scales relevant to landowners and resource professionals. The growth of datasets related to SOC, which is the largest terrestrial C pool, facilitates use of synthesis techniques to assess SOC stocks and changes at management-relevant scales. We report results from a synthesis using meta-analysis of published studies, as well as two large databases, in which we identify baseline patterns and drivers, quantify influences of land use change and forest management, and provide ecological context for distinct management regimes and their SOC impacts. We conducted this, the fourth in a series of ecoregional SOC assessments, for the South Atlantic States, which are disproportionately important to the national-scale forest C sink and forest products industry in the U.S. At the ecoregional level, baseline SOC stocks vary with climatic, topographic, and soil physical factors such as temperature and precipitation, slope gradient and aspect, and soil texture. Land use change and forest management modestly influence SOC stocks. Reforestation on previously cultivated lands increases SOC stocks, while deforestation for cultivation has the opposite effect; for continuously forested lands, harvesting is associated with SOC increases and prescribed fire with SOC declines. Effects of reforestation are large and positive for upper mineral soils (+30%) but not detectable in lower mineral soils. Negative effects of prescribed fire are due to significant C losses from organic horizons (-46%); fire and harvest have no impacts on upper mineral soils but both increase SOC in lower mineral soils (+8.2 and +46%, respectively, with high uncertainty in the latter). Inceptisols are generally more negatively impacted by prescribed fire or harvest than Ultisols, and covariance between inherent factors (including soil taxonomy) and management impacts indicates how interior vs. coastal physiographic sections differ in their management regimes and SOC trends. In the cooler, wetter, topographically rugged interior hardwood forests, which have larger baseline SOC stocks, prescribed fire and even light harvesting generally decrease SOC; in contrast, intensively managed coastal plain pine plantations begin with small initial SOC stocks, but exhibit rapid gains over even a single rotation. This covariance between place (physiography) and practice (management regime) suggests that distinct approaches to forest C management may be complementary to other ecological or production goals, when implemented as part of wider (e.g., state-level) forest C or climate policy.

Association between state-specific reimbursement and Medicaid acceptance for Mohs micrographic surgery

To the Editor: Medicaid patients face considerable barriers to dermatologic care and suffer worse outcomes.1Mazmudar R.S. Gupta N. Desai B.J. Bordeaux J.S. Scott J.F. Dermatologist appointment access and waiting times: A comparative study of insurance types.J Am Acad Dermatol. 2020; 83: 1468-1470Google Scholar, 2Creadore A. Desai S. Li S.J. et al.Insurance acceptance, appointment wait time, and dermatologist access across practice types in the US.JAMA Dermatol. 2021; 157: 181-188Google Scholar, 3Alghothani L. Jacks S.K. Vander Horst A. Zirwas M.J. Disparities in access to dermatologic care according to insurance type.Arch Dermatol. 2012; 148: 956-957Google Scholar, 4Abdel-Rahman O. Prognostic impact of socioeconomic status among patients with malignant melanoma of the skin: a population-based study.J Dermatolog Treat. 2020; 31: 571-575Google Scholar Mohs micrographic surgery (MMS) is the preferred treatment for many skin cancers, and its demand in the Medicaid population has increased alongside the incidence of skin cancers. Understanding the factors that influence Medicaid acceptance among Mohs surgeons is important to improve access and minimize health disparities in this population. In this cross-sectional analysis of Mohs surgeons in the United States, we sought to determine if state-specific Medicaid reimbursement for MMS was associated with Medicaid acceptance. Physicians billing more than 10 MMS procedures based on the 2017 Medicare Provider Utilization Data, as well as MMS fellowship graduates from 2017 to 2020, were included. We determined Medicaid acceptance status by utilizing state-specific Medicaid directories and calling physician practices to verify acceptance. State-specific Medicaid and Medicare reimbursement rates for MMS Current Procedural Terminology (CPT) codes 17311-17314 were compiled from publicly-available fee schedules. Medicaid-to-Medicare ratios for each CPT code were used to enable relative comparisons across fees.5Zuckerman S. Laura S. Marni E. Medicaid physician fees after the ACA primary care fee bump. Urban Institute, 2017https://www.urban.org/sites/default/files/publication/88836/2001180-medicaid-physician-fees-after-the-aca-primary-care-fee-bump_0.pdfDate accessed: December 20, 2021Google Scholar Linear regressions were performed to assess the relationship between fee ratios and the proportion of Medicaid acceptance in each state. Medicaid acceptance by Mohs surgeons varied considerably between states. Many states in the Mountain and West North Central divisions had high Medicaid-to-Medicare fee ratios and Medicaid acceptance rates. However, several East South Central, and South Atlantic states had lower Medicaid acceptance rates despite having high fee ratios (Fig 1). Across all states, the correlation between fee ratios for all MMS procedures (CPT 17311–17314) and Medicaid acceptance was weak (r2 = 0.087) but significant (P = .036). The specific correlation between MMS of the trunk and extremities (CPT 17313–17314) and Medicaid acceptance reached significance (P = .029), whereas that for MMS of the head and neck (CPT 17311–17312) did not (P = .054) (Fig 2).Fig 2Linear regressions of state-specific Medicaid-to-Medicare fee ratios and statewide Medicaid acceptance rates. Linear regressions were generated using (A) mean fee ratio for Current Procedural Terminology (CPT) codes 17311–17312, (B) mean fee ratio for CPT codes 17313–17314, and (C) mean fee ratio of CPT codes 17311–17314. States are represented by individual points.View Large Image Figure ViewerDownload Hi-res image Download (PPT) These results suggest that reimbursement is not overall a reliable predictor of Medicaid acceptance and poorly explains the variation in Medicaid acceptance among Mohs surgeons. However, the significant relationship between reimbursement and Medicaid acceptance in certain MMS code combinations, including all codes combined, suggests that reimbursement may influence acceptance in certain scenarios. Such weak correlations could be explained by the various factors impacting Medicaid acceptance, including physician and practice characteristics and state Medicaid expansion. High Medicaid acceptance may exist in areas with relatively modest reimbursement, such as academic medical centers and hospitals requiring Medicaid acceptance. Enrollment in Medicaid may be avoided by Mohs surgeons and practices concerned about higher administrative burdens, delayed remuneration, and lower reimbursement rates for non-MMS CPT codes. Medicaid acceptance is critical to fill care gaps, and higher reimbursement, among other factors, may incentivize participation, especially in states with fewer Mohs surgeons.3Alghothani L. Jacks S.K. Vander Horst A. Zirwas M.J. Disparities in access to dermatologic care according to insurance type.Arch Dermatol. 2012; 148: 956-957Google Scholar This study is limited by potentially inaccurate capture of Medicaid acceptance status, use of fee-for-service rates in states with managed care plans, and lack of longitudinal trends. Despite these limitations, this study highlights the correlation between remuneration and Medicaid acceptance for MMS. Future research is needed to contextualize these findings with additional factors influencing Medicaid acceptance among Mohs surgeons. Author Feng has consulted for Cytrellis Biosystems, Inc and Soliton, Inc. Authors Beltrami, Hooper, Kodumudi, and Gronbeck have no conflicts of interest to declare.

Health Communication Blindspot: A Case Study of Harmful Algal Blooms in the South Atlantic States

A Harmful Algal Bloom (HAB) is a complex natural event that occurs when algae reach a critical biomass and create one or more toxins harmful to biological life or the environment. By definition, HABs create both ecological and public health challenges. Because governments are the entities most often tasked with the responsibility for shared resources, this case study represents a snapshot of current governmental messaging about HABs in the South Atlantic states. The objective of this online content analysis is to determine the readability of both state and federal government online communications regarding HABs using the Simple Measures of Gobbledygook (SMOG) test. Sources for this study were obtained using a targeted search of both South Atlantic state websites and federal agencies concerned with HABs and their effects on human health. In total, 90 webpages were identified from state (n=38) and federal agencies (n=42), as well as nongovernmental organizations (n=10). The average SMOG score of all 90 sources is an 11th grade reading level (10.7). This content analysis reflects the complexity of scientific communication. However, as evaluation and improvement are the final steps in any public health programming, evaluation needs to be undertaken in all environmental health communications in order to properly inform the public about known toxicological and environmental health risks.

In the face of climate change and exhaustive exercise: the physiological response of an important recreational fish species.

Cobia (Rachycentron canadum) support recreational fisheries along the US mid- and south-Atlantic states and have been recently subjected to increased fishing effort, primarily during their spawning season in coastal habitats where increasing temperatures and expanding hypoxic zones are occurring due to climate change. We therefore undertook a study to quantify the physiological abilities of cobia to withstand increases in temperature and hypoxia, including their ability to recover from exhaustive exercise. Respirometry was conducted on cobia from Chesapeake Bay to determine aerobic scope, critical oxygen saturation, ventilation volume and the time to recover from exhaustive exercise under temperature and oxygen conditions projected to be more common in inshore areas by the middle and end of this century. Cobia physiologically tolerated predicted mid- and end-of-century temperatures (28–32°C) and oxygen concentrations as low as 1.7–2.4 mg l−1. Our results indicated cobia can withstand environmental fluctuations that occur in coastal habitats and the broad environmental conditions their prey items can tolerate. However, at these high temperatures, some cobia did suffer post-exercise mortality. It appears cobia will be able to withstand near-future climate impacts in coastal habitats like Chesapeake Bay, but as conditions worsen, catch-and-release fishing may result in higher mortality than under present conditions.

Using Social Media to Track Geographic Variability in Language About Diabetes: Analysis of Diabetes-Related Tweets Across the United States.

BackgroundSocial media posts about diabetes could reveal patients’ knowledge, attitudes, and beliefs as well as approaches for better targeting of public health messages and care management.ObjectiveThis study aimed to characterize the language of Twitter users’ posts regarding diabetes and describe the correlation of themes with the county-level prevalence of diabetes.MethodsA retrospective study of diabetes-related tweets identified from a random sample of approximately 37 billion tweets from the United States from 2009 to 2015 was conducted. We extracted diabetes-specific tweets and used machine learning to identify statistically significant topics of related terms. Topics were combined into themes and compared with the prevalence of diabetes by US counties and further compared with geography (US Census Divisions). Pearson correlation coefficients are reported for each topic and relationship with prevalence.ResultsA total of 239,989 tweets from 121,494 unique users included the term diabetes. The themes emerging from the topics included unhealthy food and drink, treatment, symptoms/diagnoses, risk factors, research, recipes, news, health care, management, fundraising, diet, communication, and supplements/remedies. The theme of unhealthy foods most positively correlated with geographic areas with high prevalence of diabetes (r=0.088), whereas tweets related to research most negatively correlated (r=−0.162) with disease prevalence. Themes and topics about diabetes differed in overall frequency across the US geographical divisions, with the East South Central and South Atlantic states having a higher frequency of topics referencing unhealthy food (r range=0.073-0.146; P<.001).ConclusionsDiabetes-related tweets originating from counties with high prevalence of diabetes have different themes than tweets originating from counties with low prevalence of diabetes. Interventions could be informed from this variation to promote healthy behaviors.

Socioeconomic risk factors for fatal opioid overdoses in the United States: Findings from the Mortality Disparities in American Communities Study (MDAC).

Understanding relationships between individual-level demographic, socioeconomic status (SES) and U.S. opioid fatalities can inform interventions in response to this crisis. The Mortality Disparities in American Community Study (MDAC) links nearly 4 million 2008 American Community Survey responses to the 2008-2015 National Death Index. Univariate and multivariable models were used to estimate opioid overdose fatality hazard ratios (HR) and 95% confidence intervals (CI). Opioid overdose was an overrepresented cause of death among people 10 to 59 years of age. In multivariable analysis, compared to Hispanics, Whites and American Indians/Alaska Natives had elevated risk (HR = 2.52, CI:2.21-2.88) and (HR = 1.88, CI:1.35-2.62), respectively. Compared to women, men were at-risk (HR = 1.61, CI:1.50-1.72). People who were disabled were at higher risk than those who were not (HR = 2.80, CI:2.59-3.03). Risk was higher among widowed than married (HR = 2.44, CI:2.03-2.95) and unemployed than employed individuals (HR = 2.46, CI:2.17-2.79). Compared to adults with graduate degrees, those with high school only were at-risk (HR = 2.48, CI:2.00-3.06). Citizens were more likely than noncitizens to die from this cause (HR = 4.62, CI:3.48-6.14). Compared to people who owned homes with mortgages, those who rented had higher HRs (HR = 1.36, CI:1.25-1.48). Non-rural residents had higher risk than rural residents (HR = 1.46, CI:1.34, 1.59). Compared to respective referent groups, people without health insurance (HR = 1.30, CI:1.20-1.41) and people who were incarcerated were more likely to die from opioid overdoses (HR = 2.70, CI:1.91-3.81). Compared to people living in households at least five-times above the poverty line, people who lived in poverty were more likely to die from this cause (HR = 1.36, CI:1.20-1.54). Compared to people living in West North Central states, HRs were highest among those in South Atlantic (HR = 1.29, CI:1.11, 1.50) and Mountain states (HR = 1.58, CI:1.33, 1.88). Opioid fatality was associated with indicators of low SES. The findings may help to target prevention, treatment and rehabilitation efforts to vulnerable groups.

A Machine-Learning Model for Zonal Ship Flow Prediction Using AIS Data: A Case Study in the South Atlantic States Region

Predicting traffic flow is critical in efficient maritime transportation management, coordination, and planning. Scientists have proposed many prediction methods, most of which are designed for specific locations or for short-term prediction. For the purpose of management, methods that enable long-term prediction for large areas are highly desirable. Therefore, we propose developing a spatiotemporal approach that can describe and predict traffic flows within a region. We designed the model based on a multiple hexagon-based convolutional neural network (mh-CNN) model that takes both the flow dynamics and environmental conditions into account. This model is highly flexible in that it predicts zonal traffic flow within variable time windows. We applied the method to measure and predict the daily and hourly traffic flows in the South Atlantic States region by taking the impacts of extreme weather events into consideration. Results show that our method outperformed other methods in daily prediction during normal days and hourly prediction during hurricane events. Based on the results, we also provide some recommendations regarding the future usage and customization of the model.

The Role of Third States in the EU Maritime Security Strategy: A Case Study of the South Atlantic States

The Role of Third States in the EU Maritime Security Strategy: A Case Study of the South Atlantic States

Hepatocellular carcinoma: Impact of academic setting and hospital volume on patient survival

Background and objectivesTo assess the impact of academic setting and hospital on overall survival in patient with hepatocellular carcinoma (HCC). MethodsThe 2004–2015 NCDB was queried for HCC. First line treatment was stratified as liver transplant, surgical resection, interventional oncology (IO) and chemotherapy. Hospital volume was stratified as high (ranking among top 10% in case numbers) and low volume. Overall survival was assessed via multivariable Cox regressions. Results63,877 patients treated at 1261 hospital systems were included (transplant n = 10,596, surgical resection n = 11,132, IO n = 12,286, chemotherapy n = 29,863; academic centers n = 226, non-academic n = 1035). Younger African American patients with private insurance, high income and education were more likely treated at academic centers. US geographical discrepancies were evident, with highest academic center treatment rates in New England states (83.6%) and lowest in South Atlantic states (48.6%). Overall survival was superior for academic versus non-academic centers (HR = 0.89, 95% CI: 0.87–0.91, p < 0.001) and high versus low volume centers (HR = 0.79, 95% CI: 0.77–0.81, p < 0.001), after multivariable adjustment for potential confounders. These effects were evident among all HCC treatment modalities. ConclusionsHCC treatment in academic centers shows distinct patterns according to patient demographics and US geography. Longest patient survival is observed in high-volume academic centers.

Projecting Urbanization and Landscape Change at Large Scale Using the FUTURES Model

Increasing population and rural to urban migration are accelerating urbanization globally, permanently transforming natural systems over large extents. Modelling landscape change over large regions, however, presents particular challenges due to local-scale variations in social and environmental factors that drive land change. We simulated urban development across the South Atlantic States (SAS), a region experiencing rapid population growth and urbanization, using FUTURES—an open source land change model that uses demand for development, local development suitability factors, and a stochastic patch growing algorithm for projecting alternative futures of urban form and landscape change. New advances to the FUTURES modelling framework allow for high resolution projections over large spatial extents by leveraging parallel computing. We simulated the adoption of different urban growth strategies that encourage settlement densification in the SAS as alternatives to the region’s increasing sprawl. Evaluation of projected patterns indicate a 15% increase in urban lands by 2050 given a status quo development scenario compared to a 14.8% increase for the Infill strategy. Status quo development resulted in a 3.72% loss of total forests, 2.97% loss of highly suitable agricultural land, and 3.69% loss of ecologically significant lands. An alternative Infill scenario resulted in similar losses of total forest (3.62%) and ecologically significant lands (3.63%) yet consumed less agricultural lands (1.23% loss). Moreover, infill development patterns differed qualitatively from the status quo and resulted in less fragmentation of the landscape.

Renewable resources of the northern half of the United States: potential for 100% renewable electricity

We previously presented a model for deep penetration of renewables in the electricity sector of the southern half of the United States (Khoie and Yee in Clean Technol Environ Policy 17(4):957–971, 2015). In this paper, we present a strategy for the northern half of the United States to utilize its available renewable resources to gradually decrease its reliance on fossil fuels in electricity generation and develop energy portfolios with increasing share of renewables. Using the electricity generation data from the US EIA (Electricity, electric power monthly, 2019d. https://www.eia.gov/electricity/monthly/ ), and the renewable resource maps produced by NREL (Geospatial data science, 2018a. http://www.nrel.gov/gis/solar.html ; Geospatial data science, 2018b. http://www.nrel.gov/gis/wind.html ), we develop strategies for the states in the northern half of the USA. We group these states into seven regions: West Coast, Mountain States, Middle West States, Lake States, Mid-Atlantic, South Atlantic, and New England states. For each region, we determine when and if the electricity generation from renewables will meet the region’s electricity need while accounting for a 1% annual increase in electricity demand. The renewable resources included in our models are solar (rural, urban, and rooftop photovoltaic), wind (onshore), hydro, biomass, and geothermal which vary greatly from region to region. We also include nuclear, coal, natural gas, and petroleum. Our results show that the West Coast, Mountain, and Middle West regions have the potential to become 100% renewable in the years 2041, 2039, and 2038, respectively. Additionally, our results show that the four regions of Lake, Mid-Atlantic, South Atlantic, and New England states may not be able to produce 100% of their electricity demand from their renewable resources.

Contemporary Trends in Clinical Outcomes among Dialysis Patients with Medicare Coverage

Background: The dialysis patient population in the United States continues to grow. Trends in rates of death and hospitalization among dialysis patients have important consequences for outpatient dialysis capacity and Medicare spending. Objectives: To estimate contemporary trends in rates of death and hospitalization among dialysis patients in the United States, overall and within subgroups. Methods: We used Medicare Limited Data Sets (100% sample) in 2014–2017 to estimate trends in rates of death and hospitalization among dialysis patients with Medicare Parts A and B enrollment. We used seasonal autoregressive integrated moving average models to identify secular trends in the incidence of outcomes. Results: There were 631,075 unique patients; 222,924 deaths; and 1,876,779 hospital admissions. Weekly risks of both death and hospitalization exhibited strong seasonality. However, overall weekly risks of death were 34.9, 35.4, 35.2, and 35.7 deaths per 10,000 patients in 2014–2017, respectively (p = 0.47, from a likelihood ratio test of secular trend). The overall weekly risk of hospitalization was 3.08, 3.05, 3.11, and 3.11% in 2014, 2015, 2016, and 2017, respectively (p = 0.30). There were significant secular trends in risk of death in subgroups defined by black race and residency in South Atlantic states (p < 0.05). There were also secular trends in risk of hospitalization in subgroups defined by age 20–44 years, concurrent enrollment in Medicaid, and residency in South Central states. Conclusion: For the first time since the beginning of this century, rates of both death and hospitalization among dialysis patients with Medicare fee-for-service coverage have stagnated. The reasons for this change are unknown and require detailed assessment. Persistent lack of change in clinical outcomes may alter the future expectations about dialysis patient population growth.

Impact of hospital volume and type on survival in hepatocellular carcinoma: Results from the National Cancer Database.

417 Background: To assess the impact of hospital volume and type on survival in patients with hepatocellular carcinoma (HCC). Methods: Patients with histopathological or imaging-based diagnosis of HCC were identified from the 2003-2015 National Cancer Database (NCDB). First-line treatment was stratified as liver transplant, surgical resection, interventional oncology (IO) and chemotherapy. Hospital volume was stratified as high (ranking among top 10% in case numbers) and low volume, separately for each treatment modality. Hospital type was categorized as academic and non-academic. Overall survival was assessed using multivariable Cox proportional hazards models. Results: A total of 63,877 patients were included (transplant n = 10,596, surgical resection n = 11,132, IO n = 12,286, chemotherapy n = 29,863). Of 1,261 hospitals systems which treated HCC, 226 (17.9%) were academic centers and 1,035 (82.1 %) were non-academic centers. Mean number of cases treated annually was higher in academic centers (55.2; 34.6; 40.7; 79.9) versus non-academic centers (10.7; 6.25; 6.6; 11.9 for transplant; surgical resection; IO and chemotherapy; p &lt; 0.001, respectively). Young African American patients and those with private insurance, high income and education were more likely to receive treatment at academic centers. Geographical difference were evident among US regions, with highest proportion of HCC treated at academic centers in New England states (83.6%) and lowest in South Atlantic states (48.6%). Overall survival was superior for academic versus non-academic centers (HR = 0.89, 95% CI: 0.87-0.91, p &lt; 0.001) and high versus low volume centers (HR = 0.79, 95% CI: 0.77-0.81, p &lt; 0.001), after multivariable adjustment for potential confounders. These effects were evident among all HCC treatment modalities. Conclusions: HCC treatment in academic centers shows distinct patterns according to patient demographics and US geography. Among all treatment modalities, both academic setting and hospital volume independently affected HCC outcomes, with highest patient survival observed in high-volume academic centers.

Fuel poverty in the US: Evidence using the 2009 Residential Energy Consumption Survey

Fuel poverty has received less attention in the US than in parts of Europe, particularly Northern Europe. We use data from the 2009 US Residential Energy Consumption Survey to illustrate the extent of the problem and to contrast homeowners and renters who differ in both income and energy expenditure. Narrowing the focus to homeowners on the east coast of the country, we use a logit model to look for differences in predictors of fuel poverty in the relatively cold Northeast states versus warmer South Atlantic states. Overall, there are more similarities than differences in these predictors. Insulation standards differ regionally and this is important for the South Atlantic states where respondents who self-report having adequate insulation are less likely to be in fuel poverty by our definition.

Linking small fruit and vegetable farmers and institutional foodservice operations: marketing challenges and considerations

AbstractThe centralized nature of the United States food production, processing and distribution system makes it difficult for small fruit and vegetable farmers to serve as suppliers to institutional foodservice operations (IFOs), such as schools and hospitals. Due to age, economic and/or health status, it is often the clients of these foodservice operations who would benefit from increasing their consumption of locally grown fruits and vegetables. Unfortunately, institutions are often limited in their resources and food preparation infrastructure, and lack market-based incentives to incorporate locally grown foods into their menus. This study identifies and suggests solutions to barriers that limit the ability of small fruit and vegetable farmers to serve as suppliers to IFOs. Data were collected through an extensive series of focus group meetings held with small-scale fruit and vegetable farmers in three South-Atlantic states. From these meetings, practical marketing considerations, such as payment terms, and processing, packaging and delivery requirements of supplying institutional foodservice buyers, were identified as obstacles to the efficient function of this market channel. Food safety challenges, including the related issues of obtaining (food) products liability insurance and food safety certifications, were also acknowledged among top concerns. A majority of the identified challenges were similar to those reported in other studies, but several were complicated by characteristics of farm production, limited food system infrastructure and marketing experiences in the study region. Several practical solutions to overcoming some of these marketing constraints are offered.

Residential House Prices, Commercial Real Estate and Bank Failures

The Great Recession resulted in bank failures that exceeded the savings and loan (S&L) crisis in terms of percentage of institutions and the volume of assets of banks that failed. While much of the literature focuses “subprime” mortgages and its role in this financial crisis, we focus on the effects of residential housing prices. While construction and development loans have typically been a major cause of bank failures, we show that regional residential house prices and construction and land development loans are significant in explaining bank failures through 2011 but the regional residential house price movements have been significant through 2015. Furthermore, we show how the regional residential house price index (HPI) values have significant effects over the Great Recession, particularly in the South Atlantic and Pacific states (better known as the “sand states”).

Relationship Between Piercing-Sucking Insect Control and Internal Lint and Seed Rot in Southeastern Cotton (Gossypium hirsutum L.).

In 1999, crop consultants scouting for stink bugs (Hemiptera spp.) in South Carolina discovered a formerly unobserved seed rot of cotton that caused yield losses ranging from 10 to 15% in certain fields. The disease has subsequently been reported in fields throughout the southeastern Cotton Belt. Externally, diseased bolls appeared undamaged; internally, green fruit contain pink to dark brown, damp, deformed lint, and necrotic seeds. In greenhouse experiments, we demonstrated transmission of the opportunistic bacterium Pantoea agglomerans by the southern green stink bug, Nezara viridula (L.). Here, green bolls were sampled from stink bug management plots (insecticide protected or nontreated) from four South Atlantic coast states (North Carolina, South Carolina, Georgia, and Florida) to determine disease incidence in the field and its association with piercing-sucking insects feeding. A logistic regression analysis of the boll damage data revealed that disease was 24 times more likely to occur (P = 0.004) in bolls collected from plots in Florida, where evidence of pest pressure was highest, than in bolls harvested in NC with the lowest detected insect pressure. Fruit from plots treated with insecticide, a treatment which reduced transmission agent numbers, were 4 times less likely to be diseased than bolls from unprotected sites (P = 0.002). Overall, punctured bolls were 125 times more likely to also have disease symptoms than nonpunctured bolls, irrespective of whether or not plots were protected with insecticides (P = 0.0001). Much of the damage to cotton bolls that is commonly attributed to stink bug feeding is likely the resulting effect of vectored pathogens.