Ohio Counties Research Articles

Probability of crop response to phosphorus and potassium fertilizer: Lessons from 45 years of Ohio trials

AbstractSoil test phosphorus (P) and potassium (K) and the associated soil test critical values (CSTVs) are widely used as the primary diagnostic tool to determine if a crop needs P and K fertilizer. However, identifying robust and predictive CSTVs requires a large number of field trials in representative soils and environments to assess crop fertilizer responses. From 1976 to 2021, a total of 457 P trials and 458 K trials were conducted in corn (Zea mays), soybean (Glycine max), and wheat (Triticum aestivum) across 40 counties in Ohio. The trials consisted of both multi‐rate, multi‐year trials and single‐year, single‐rate and large strip trials. Across all crops, grain yield responded to P and K fertilizer in 23.4% and 25.3% of trials, with average yield increases of 8.8% and 11.0%, respectively. Corn yield was more responsive to P and K fertilizer (∼30% of P and K trials) than soybean yield (14% of P trials, 20% of K trials). Several models were run to identify CSTVs, but models imparted systematic bias in CSTVs, and a superior model was not identified due to poor model fit and indiscernible criteria to guide model selection. Instead of a single CSTV, data were classified into five discrete categories based on relative yields and Mehlich‐3 soil test values. These classifications provided a useful and consistent framework for assessing the probability of crop response to P and K fertilizer. Ohio soils with Mehlich‐3 values greater than 20 mg P kg−1 and 130 mg K kg−1 have a low probability of responding to P or K fertilizer application.

Impact of an Asynchronous Training for the Early Intervention and Childcare Workforce Addressing the Developmental Impact of the Opioid Crisis on Young Children.

The US opioid epidemic contributes to a growing population of children experiencing neonatal abstinence syndrome (NAS) and adverse childhood experiences (ACEs). A review of the developmental impacts of the opioid crisis highlights that both prenatal exposure to teratogens and ACEs can result in developmental delay and disabilities. Training for the early intervention/early childhood (EI) systems is needed to enable them to meet the needs of this growing population. To address this, an IRB-approved online training on best practices for NAS, developmental monitoring and referral, and trauma-informed care was created for Ohio EI providers who provided informed consent to participate. The feasibility of utilizing an online training was assessed. Knowledge on opioid addiction, NAS, ACEs, and early intervention provider characteristics were collected for 2973 participants. Within 6 months, the training reached providers in all Ohio counties and seventeen other states. 57% of providers reported caring for one or more children with a caregiver who has confirmed opioid use. 31% reported these children had experienced four or more ACEs. Providers' ACEs awareness was moderately associated with their experiences with prenatally-exposed youth. There was a significant increase in knowledge following training. Differences in post-training knowledge differed only by county-level opioid death rates, where those providers with low-medium opioid death rates reported more awareness of children with prenatal opioid exposure compared to participants who lived in a county with medium and medium-high opioid death rates. Online-training is feasible for closing gaps in the early intervention system.

High-throughput soil health assessment to predict corn agronomic performance

Developing high-throughput methods to quantify soil health can support decision making to minimize soil constraints for crop growth and increase sustainability in agroecosystems. This study evaluated the ability of soil health assessment conducted at the beginning of the crop growing season to predict corn agronomic performance in nutrient fertilization trials. We compared different methods to assess soil health, from the most traditional approach of measuring individual soil biochemical indicators to more novel approaches using diffuse reflectance infrared Fourier transform spectroscopy (mid-DRIFTS). Soil health was quantified using: I) traditional and emerging biochemical soil health indicators (up to 20 soil indicators), II) mineral and organic functional groups abundances estimated as peak areas in mid-DRIFTS, and III) mid-DRIFTS with partitioned spectra and partial least squares regression. Corn response to fertilizer was evaluated in a) phosphorus, potassium, and sulfur omission trials (2016–2018; 41 sites across 17 Ohio counties) as well as in b) N rates trials (2016–2017; 25 fields across 14 Ohio counties). Modeling using either biochemical soil health indicators or mid-DRIFTS accurately predicted corn yield across nutrient treatments in omission trials (R2V=0.61–0.84 in validation sets) and unfertilized controls in N rates trials (R2V=0.68–0.81) as well as corn N-driven yield gap (i.e., delta yield defined as grain yield at agronomic optimum N rate minus grain yield of the control, R2V=0.64–0.76) in N rates trials. Mid-DRIFTS approaches equaled or outperformed the predictive ability of measured biochemical soil health indicators in estimating crop performance (up to 38 % improvement in R2V), unveiling a promising method to more efficiently assess soil health. Early season soil health assessment via mid-DRIFTS has potential to directly estimate corn agronomic performance.

A Dynamic Spatial Factor Model to Describe the Opioid Syndemic in Ohio.

The opioid epidemic has been ongoing for over 20 years in the United States. As opioid misuse has shifted increasingly toward injection of illicitly produced opioids, it has been associated with HIV and hepatitis C transmission. These epidemics interact to form the opioid syndemic. We obtain annual county-level counts of opioid overdose deaths, treatment admissions for opioid misuse, and newly diagnosed cases of acute and chronic hepatitis C and newly diagnosed HIV from 2014 to 2019. Aligned with the conceptual framework of syndemics, we develop a dynamic spatial factor model to describe the opioid syndemic for counties in Ohio and estimate the complex synergies between each of the epidemics. We estimate three latent factors characterizing variation of the syndemic across space and time. The first factor reflects overall burden and is greatest in southern Ohio. The second factor describes harms and is greatest in urban counties. The third factor highlights counties with higher than expected hepatitis C rates and lower than expected HIV rates, which suggests elevated localized risk for future HIV outbreaks. Through the estimation of dynamic spatial factors, we are able to estimate the complex dependencies and characterize the synergy across outcomes that underlie the syndemic. The latent factors summarize shared variation across multiple spatial time series and provide new insights into the relationships between the epidemics within the syndemic. Our framework provides a coherent approach for synthesizing complex interactions and estimating underlying sources of variation that can be applied to other syndemics.

Understanding Location and Density: A Spatial Analysis of Cuyahoga County Ohio’s Nonprofit Sector

Theories of density dependence emphasize the role of competition and legitimation in organizational life. However, agglomerative configurations and ecological processes vary substantially over space, resulting in heterogeneous sub-populations which organizations select into by choosing locations. Using geostatistical data constructed from form-990 submissions and the American Community Survey, this article studies the role of location and density in the operations of nonprofits using generalized additive models. After controlling for organizational and neighborhood features, the results show substantial variation in the effect of location on total and contributed revenue. Nonprofit density is positively associated with the location effects across a range of distances. The results suggest organizations benefit greatly from locating in high-density regions and may be most sensitive to variation in density in their immediate proximity. The study emphasizes location dependence through the importance of location and the intra-county distribution of nonprofits.

Generating Small Areal Synthetic Microdata from Public Aggregated Data Using an Optimization Method

Small area microdata contain attributes and locations of individual members of a population in small census geographies. This type of data is critical in research and policymaking, but it is often not publicly available due to confidentiality concerns. The limited access to small area microdata can result in insufficient data for certain research (data scarcity). Even for researchers qualified to access the small area microdata, their research can hardly be reproduced by others (method irreproducibility). To address these issues, we develop a method to generate small area synthetic microdata (SASM) that is suitable for public use. Specifically, an optimization approach is proposed to minimize the difference between published census tables and the SASM. Two counties in Ohio are used as case studies to test the efficacy of the proposed method and the validity of the resulting SASM. The results show that the SASM aligns not only with the census tables, but also with an external data source that contains a sample of the small area microdata. We also illustrate how the SASM can be used to address data scarcity and method irreproducibility in demographic research.

Factors Related to Drug Overdose Deaths in Ohio

Background: Drug overdoses have had a devastating impact on public health in Ohio. Improving our understand-ing of the relationships between factors that are associated with drug overdose deaths can enhance the quality of public policy and health care reach in Ohio. Methods: Utilizing data from the Centers for Disease Control and Prevention (CDC) and University of Wisconsin Population Health Institute, this research seeks to quantify the associations between the drug overdose rate for counties in Ohio with various factors via statistical regressions. Results: The overwhelming majority of drug/alcohol overdose deaths during the years 2017-2019 were uninten-tional. Drug overdose deaths and life expectancy are strongly associated. Communities with higher overdose rates have lower life expectancies. Socioeconomic status and health care factors, such as mental distress and physical inactivity, are significantly correlated with increased drug overdose deaths. Household income is significantly correlated with increased access to health care, implying that communities of lower socioeconomic status may lack adequate access to quality care and suffer from increased overdose deaths. Conclusion: The data indicate the importance of access to health care and health care providers in response to drug overdoses in Ohio. Health care access is currently proportional to income; higher income households have a greater proportion of insured, as well as a greater number of primary care physicians. Thus, implementing policies that support health care infrastructure should be prioritized to increase the capacity of treatment in under-resourced (low-income and low socioeconomic status) communities.

Schoolhouses above the Rock: The Shale Gas Rush and School Funding in Appalachian Ohio

Abstract This research article draws attention to how the shale gas rush phenomenon is creating path dependence and threatening community viability. The article features an instrumental case that includes school districts across seven Appalachian Ohio counties: Belmont, Carroll, Columbiana, Guernsey, Harrison, Monroe, and Noble. There, it has become commonplace for public schools to lease oil and gas rights; to factor revenue from ad valorem taxes, industry-related construction, and pipeline construction into district budgets; and to engage in tax negotiations for natural gas-fired power plants and affiliated industrial growth. The case is prefaced by a review of school funding norms in the United States and a discussion of the influence that path dependence has on school funding in the Appalachian region. Following this, the case of eastern Ohio schools is presented. The article culminates with a list of actions stakeholders can take to foster public school and community viability in Appalachia.

Understanding Social Disorganization and the Nonprofit Infrastructure: An Ecological Study of Child Maltreatment Rates

Advocates and researchers have emphasized the role of disorder in neighborhood processes, with serious consequences for families, however, neighborhood structures may also support families and reduce child maltreatment. Nonprofits maintain a range of strategies to support nearby families, including direct services, facilitation of social networks, and formalizing advocacy for increased attention from government. Using agency data on child maltreatment, nonprofit locations, and indicators of social disorganization, this article studies the role of nonprofit organizations in the spatial distribution of child maltreatment among Cuyahoga County Ohio census tracts ( N = 442). Accounting for spatially structured and tract-specific variation with a hierarchical Poisson model implemented through a Bayesian methodology, the results indicate the presence of nonprofits is a protective factor: negatively associated with child maltreatment (posterior mean: −0.18, CI: −0.34, −0.03), with heterogeneity by type. The study highlights neighborhoods as a propitious site of intervention and emphasizes the intra-county distribution of nonprofits.

A Computational Framework for Preserving Privacy and Maintaining Utility of Geographically Aggregated Data: A Stochastic Spatial Optimization Approach

Geographically aggregated data are often considered to be safe because information can be published by group as population counts rather than by individual. Identifiable information about individuals can still be disclosed when using such data, however. Conventional methods for protecting privacy, such as data swapping, often lack transparency because they do not quantify the reduction in disclosure risk. Recent methods, such as those based on differential privacy, could significantly compromise data utility by introducing excessive error. We develop a methodological framework to address the issues of privacy protection for geographically aggregated data while preserving data utility. In this framework, individuals at high risk of disclosure are moved to other locations to protect their privacy. Two spatial optimization models are developed to optimize these moves by maximizing privacy protection while maintaining data utility. The first model relocates all at-risk individuals while minimizing the error (hence maximizing the utility). The second model assumes a budget that specifies the maximum error to be introduced and maximizes the number of at-risk individuals being relocated within the error budget. Computational experiments performed on a synthetic population data set of two counties of Ohio indicate that the proposed models are effective and efficient in balancing data utility and privacy protection for real-world applications.

In Case You Haven't Heard…

On Feb. 15, The Wall Street Journal ran a story about two Ohio counties and what they will do with drug settlement money. Apparently, there is so much money that they don't know what to do with it. Of course, many requests are coming in, but one county may have to hire someone to dole it out. There was one treatment center with 30 beds built. Overdose deaths have not gone down. Kudos to the reporters for honing in on this. The question ‘why did you ask for it if you don't know what to do with it’ comes to mind. One thing is clear, however: To their credit, both counties want to avoid having the money used to offset budget gaps in the general fund, which is what happened with the tobacco settlement money (https://onlinelibrary.wiley.com/doi/epdf/10.1002/adaw.20080).

Soil degradation and crop yield declines persist 5 years after pipeline installations

AbstractDegradation of natural resources, including increased soil compaction, soil horizon mixing, and decreased crop yields have been common outcomes of underground pipeline installation. However, most of the research documenting the impacts of pipeline installation on soil and crops was conducted before contemporary best management practices were developed and implemented. The objective of this study was to evaluate the impact of pipeline installation on soils and field crops after a 4‐ to 5‐year remediation period, coinciding with the end of landowner compensation and when sites are considered fully remediated by pipeline companies. We report soil properties and corn (Zea mays L.) and soybean [Glycine max (L.) Merr.] yields from three independently operated pipelines at 29 sites across 8 Ohio counties. We observed significant degradation in soil physical properties, such as surface penetration resistance (15.3% increase) and mean weight diameter of soil aggregates (13.6% decrease) in right‐of‐way (ROW) areas compared with adjacent (ADJ) areas, respectively. Soils in ROW showed evidence of soil horizon mixing, with 25.0 g kg−1 higher clay compared with ADJ areas. Soil degradation resulted in decreases of 23.8% and 19.5% in corn yields and 7.4% and 12.5% in soybean yields during 2020 and 2021, respectively. Widespread disturbance persisted 5 years following pipeline installation in soil physical, chemical, and biological properties. Current best management practices of pipeline installation and remediation employed by three companies were insufficient to combat widespread soil degradation and crop yield loss.

Social Determinants and Health Disparities Pertaining to Diabetes in Appalachia.

Diabetes poses a significant threat to public health in the United States, with an estimated total prevalence of 37.3 million individuals in 2019, of which 28.7 million were diagnosed and 8.5 million remained undiagnosed. The high prevalence of diabetes imposes a considerable economic burden on the U.S. healthcare system. Appalachian Ohio is disproportionately impacted with southeastern Ohio exhibiting a diabetes prevalence that exceeds the national average by more than twofold and a critical shortage of healthcare providers. To quantify the associations between diabetes prevalence and incidence in Ohio counties, considering various factors that impact health and quality-of-life outcomes. The data used in this study were obtained from the United States Diabetes Surveillance System (USDSS) on the 88 counties in Ohio. Pearson correlation tests were employed to investigate the relationship between diabetes (prevalence and incidence) and social determinants of health. A t-test and multivariate analysis of variance (MANOVA) test were performed to analyze the disparities in diabetes and social determinants between Appalachian and non-Appalachian counties. The results of this study demonstrate notable disparities in diabetes prevalence between Appalachian and non-Appalachian counties (P < .001, α = .05). Furthermore, the MANOVA test revealed significant differences between these 2 groups regarding social determinants of health (P < .05). These findings suggest that Appalachian counties may face a disproportionate impact from health-related factors and experience limited access to healthcare services. The data highlight the need for focused efforts to address the specific challenges faced by Appalachian counties. Improving access to healthcare services in the Appalachian region is paramount to ensure equitable healthcare and enhance the overall health outcomes of affected communities.

Pantry clients and Supplemental Nutrition Assistance Program-Education practitioners' perspectives on factors influencing healthy eating policy, system and environmental interventions in food pantries.

The Supplemental Nutrition Assistance Program-Education identified food pantries as a targeted setting for policy, system, and environmental (PSE) interventions to promote healthy eating among households who rely on pantries to supplement their food needs. The present study sought to identify factors influencing capacity and readiness to implement healthy eating PSE interventions in food pantries. Qualitative interviews were conducted via zoom with twenty-six community residents with experience receiving SNAP benefits and twelve SNAP-Ed staff in rural and urban counties in Ohio to identify themes and indicators related to community/organisational capacity and readiness to implement healthy eating PSE interventions in food pantries. Themes and related indicators generated based on inductive and deductive coding of interview transcripts were prioritised and weighted by eleven community nutrition experts during a virtual consensus conference. Five themes emerged; expert-derived weights (scaled low, 0 to high, 1) reflect the perceived importance of each to implementation of healthy eating PSE interventions in food pantries: food pantry capacity and logistics [0⋅252], networks and relationships [0⋅228], community nutrition practitioner capacity [0⋅212], food pantry user characteristics [0⋅156], and stigma and stereotypes [0⋅1⋅52]. Overall, seventeen indicators were identified reflecting these themes. Successful and sustained PSE interventions at food pantries will require a tailored approach that considers food pantries' capacity, needs and opportunities within the community, and capacity of community nutrition practitioners. The themes and indicators identified provide guidance for responsive PSE approaches in food pantries that meet communities where they are.

Freeman Center for intellectual and developmental disabilities: Patient-centered interdisciplinary care

ObjectivesAdults with intellectual or developmental disabilities (IDD) face substantial barriers to accessing high-quality, patient-centered care. This paper describes the development and evolution of the Freeman Center, an integrated, interdisciplinary center developed using feedback from adults with IDD and their family members. MethodsWe evaluated the reach of the Freeman Center services and described the patient population. ResultsAs of November, 2022, 1068 patients were seen at the Freeman Center. These patients represent about 5 % of all people with IDD in Hamilton County Ohio, where the Freeman Center is located. On average in 2022, the Freeman Center provided approximately 380 primary care visits, 47 psychiatry visits, and 85 combined primary care and psychiatry service visits per month. ConclusionsPatient demographic characteristics are largely consistent with the general population of Hamilton County, indicating patients are representative of the county the clinic primarily serves. Further work is needed to evaluate patient outcomes at the Freeman Center.

Barriers to Native Plantings in Private Residential Yards

In urban areas, private yards can make up large portions of the available “green space” which can be used to provide resources for many species, including birds, and pollinators. If residents are persuaded or willing to plant certain native plants, the aggregate effect of these plantings could be hugely beneficial for key pollinator species. The objectives of this study are to uncover impediments to adding different types of pollinator-beneficial plants to private yards, as well as ascertain which incentives to plant these native plants might be most persuasive, and finally determine if there are procedural knowledge gaps in how to plant, care for, or where to purchase three pollinator-beneficial plants. In this study, we randomly selected properties in two counties in southwestern Ohio along two gradients: parcel size and parcel valuation (as a proxy for income). Two hundred surveys were distributed and 113 were returned (57% response rate). We find that, in aggregate, respondents do not have a strong intent to plant these native plants, especially Asclepias syriaca (a milkweed that serves as host plant to the iconic monarch butterfly; Danaus plexippus) and, surprisingly, the intent to plant these does not differ statistically even when help with costs, labor, or the provision of online resources are offered. We also find that the reported knowledge of where to purchase wildflowers is significantly higher than how to care for them and how to plant them. Lastly, respondents are much more confident in how to take care of trees compared to the three pollinator-beneficial plants shown in the survey. We discuss the implications of these findings for outreach and extension purposes.

Local context and post‐crisis social venture creation

AbstractResearch summaryWe investigate the effects of local market and government failure on the creation of social ventures in the context of post‐crisis recovery during the period following the dot‐com crisis and ending before the housing bubble burst across all Ohio counties. Drawing on social embeddedness theory, we posit that social venture creation rates vary across local contexts and are higher in communities characterized by market and government failures. Longitudinal contextual data from 88 Ohio counties indicates that situations characterized by failures of both types are especially conducive to the creation of local social enterprises. We address the shortage of longitudinal quantitative studies focused on the emergence of social entrepreneurship and identify conditions where the relationship between local context and social venture creation is important.Managerial summaryThe purpose of this article is to examine how local context affects the rate of social venture creation in the United States. We study these rates in every county in Ohio in the aftermath of a crisis and find that local government responses and local market conditions singly and in combination lead to increased rates of local social venture creation. Fewer social ventures emerge when transfer (welfare) payments are high. However, rates rise in response to high unemployment, even when welfare payments are high, and are greater when welfare payments are low. This means the extent and type of local market and government failures influence the rate of local social venture creation. Findings advance the study of domestic social entrepreneurship in the aftermath of crises.

Factors associated with the accurate self-report of cancer screening behaviors among women living in the rural Midwest region of the United States

This study examines the accuracy of the self-report of up-to-date cancer screening behaviors (Mammography, Papanicolaou (Pap)/Human Papillomavirus (HPV) tests, Fecal Occult Blood Test (FOBT)/Fecal Immunochemical Test (FIT), Colonoscopy) compared to medical record documentation prior to eligibility determination and enrollment in a randomized controlled trial of an intervention to increase cancer screening among women living in rural counties of Indiana and Ohio. Women (n = 1,641) completed surveys and returned a medical record release form from November 2016-June 2019. We compared self-report to medical records for up-to-date cancer screening behaviors to determine the validity of self-report. Logistic regression models identified variables associated with accurate reporting. Women were up-to-date for mammography (75 %), Pap/HPV test (54 %), colonoscopy (53 %), and FOBT/FIT (6 %) by medical record. Although 39.6 % of women reported being up-to-date for all three anatomic sites (breast, cervix, and colon), only 31.8 % were up to date by medical records. Correlates of accurate reporting of up-to-date cancer screening varied by screening test. Approximately-one-third of women in rural counties in the Midwest are up-to-date for all three anatomic sites and correlates of the accurate reporting of screening varied by test. Although most investigators use medical records to verify completion of cancer screening behaviors as the primary outcome of intervention trials, they do not usually use medical records for the routine verification of study eligibility. Study results suggest that future research should use medical record documentation of cancer screening behaviors to determine eligibility for trials evaluating interventions to increase cancer screening.

The Impact of Shale Energy on Population Dynamics, Labor Migration, and Employment

This paper is designed to determine whether producing oil and gas via shale has an economically significant effect on population migration dynamics and on the labor market in terms of the number of employed individuals, the number of establishments, total wages, and average annual pay per person in twenty-six counties in Ohio and Pennsylvania, USA. The analysis incorporates migration inflow and outflow between producing and nonproducing counties. The results of the analysis show that the counties that engage in shale gas extraction saw a negative impact on net migration but a much larger positive impact on labor market outcomes. Specifically, the number of jobs is higher by 2.4%, the number of establishments is higher by 1.1%, total wages are 3% more and the average annual pay is 1.5% more in producing counties after shale. The analysis reveals a small but statistically significant negative impact on migration, as shale regions experienced some migration outflows.

Assessing Readiness for Telehealth in Rural Communities.

As rural communities often lack access to quality, affordable healthcare, telehealth has the potential to reduce healthcare gaps for rural residents. Qualitative research with interpretive phenomenology through use of the Health Promotion Model and Appreciative Inquiry was used to create and pilot a telehealth survey about residents' readiness in using telehealth. The survey of three rural counties in southern Ohio identified three themes: a knowledge gap related to telehealth; infrastructure; and a desire for easier access to healthcare. Telehealth can be considered a viable, cost-effective alternative for rural populations.