Kansas Counties Research Articles

P-472. Development of a Local HIV Care Continuum for the Kansas City Metropolitan Area (KCMA)

Abstract Background There were 36,136 new HIV diagnoses in the USA in 2021. Still, an estimated 13% of persons living with HIV (PLHIV) are unaware of their infection. The status of the HIV epidemic can be better understood by constructing an HIV care continuum.Figure 1.Diagnosis-Based KCMA HIV Care Continuums 2019-2022Local diagnosis-based care continuums for 2019-2022 compared with the most recent national HIV surveillance data. Methods HIV surveillance data reported to the Kansas Department of Health and Environment (KDHE) and Missouri Department of Health and Senior Services (DHSS) were utilized to create diagnosis-based HIV care continuums for 2019-2022. This included data from Johnson, Wyandotte, and Leavenworth counties in Kansas, and Jackson, Clay, and Platte counties in Missouri. Prevalence-based care continuums were constructed for Kansas City, Missouri for 2019-2021 utilizing the CD4-depletion model employed by CDC. Diagnosis, receipt of care, retention in care and viral suppression are per CDC definitions.Figure 2.Prevalence-Based Kansas City, MO HIV Care Continuums 2019-2021Local prevalence-based care continuums for 2019-2021 compared with the most recent national HIV surveillance data. Results From 2019 to 2021, receipt of HIV care in KCMA remained stable, while retention in care (49% to 41.6%) and HIV viral suppression (65.6% to 57.2%) decreased (Figure 1). From 2019 to 2021, HIV diagnosis rates in the 3 counties of Kansas City, Missouri, remained stable at about 87%, but receipt of care rates decreased (41.7% to 35.9%), with stable viral suppression rates (∼54%) (Figure 2). Linkage to care improved from 70% to 75% for the 6-county KCMA from 2019 to 2022 (Figure 3).Figure 3.KCMA Linkage to HIV Care 2019-2022Local linkage to HIV care estimates compared with the most recent national linkage to care estimates. Conclusion Knowledge of status appeared to approximate national estimates. However, linkage to care was significantly lower (70-75% vs 82%), which likely negatively impacted downstream stages of the continuum. Local estimates for receipt of care, retention in care, and viral suppression were consistently below national levels. This highlights the importance of ongoing initiatives targeted at the more proximal stages. Reaching undiagnosed PLHIV requires a robust public health infrastructure which utilizes innovative diagnostic approaches to meet at-risk individuals in the spaces where they live and interact. Optimizing more distal stages of the continuum is contingent upon ongoing efforts to ensure all diagnosed PLHIV are efficiently linked to care and started on antiretroviral therapy (ART) in a timely fashion. Disclosures Wissam El Atrouni, MD, ViiV Healthcare: Advisor/Consultant

High-Throughput Oxford Nanopore Sequencing Unveils Complex Viral Population in Kansas Wheat: Implications for Sustainable Virus Management.

Wheat viruses are major yield-reducing factors, with mixed infections causing substantial economic losses. Determining field virus populations is crucial for effective management and developing virus-resistant cultivars. This study utilized the high-throughput Oxford Nanopore sequencing technique (ONT) to characterize wheat viral populations in major wheat-growing counties of Kansas from 2019 to 2021. Wheat leaves exhibiting virus-like symptoms were collected, total RNA was extracted, and cDNA libraries were prepared using a PCR-cDNA barcoding kit, then loaded onto ONT MinION flow cells. Sequencing reads aligned with cereal virus references identified eight wheat virus species. Tritimovirus tritici (wheat streak mosaic virus, WSMV), Poacevirus tritici (Triticum mosaic virus, TriMV), Bromovirus BMV (brome mosaic virus, BMV), as well as Emaravirus tritici, Luteovirus pavhordei, L. sgvhordei, Bymovirus tritici, and Furovirus tritici. Mixed infections involving two to five viruses in a single sample were common, with the most prevalent being WSMV + TriMV at 16.7% and WSMV + TriMV + BMV at 11.9%. Phylogenetic analysis revealed a wide distribution of WSMV isolates, including European and recombinant variants. A phylogenetic analysis of Emaravirus tritici based on RNA 3A and 3B segments and whole-genome characterization of Furovirus tritici were also conducted. These findings advance understanding of genetic variability, phylogenetics, and viral co-infections, supporting the development of sustainable management practices through host genetic resistance.

Improving obstructive sleep apnea competency of primary care clinicians through online education.

Obstructive sleep apnea (OSA) is an often overlooked, widespread disease and a public health concern. Evidence-based practice guidelines do not exist to guide primary care clinicians' OSA screening practices. Clinicians must be competent in OSA; however, clinicians lack competency about this disease. Elevated rates of undiagnosed OSA potentially exist in two rural and one suburban counties in Kansas, as indicated by the increased weight and elevated chronic disease prevalence in these counties' populations. A one-cohort, pretest-posttest, quasi-experimental design was used for this quality-improvement project implemented over 11 weeks. Clinicians' competencies on OSA were measured before and after the intervention using the Obstructive Sleep Apnea Knowledge and Attitude Survey. A brief educational video on OSA was developed for this project. Definition, risk factors and complications, screening methods, definitive diagnosis, and treatment options were covered in this video. Participants (N = 14) showed improved OSA competency after watching the educational video. Participants improved OSA competency after watching the interventional video (M = 16.3, SE = 0.194) versus preintervention (M = 14.2, SE = 0.318). Participants also improved OSA attitude scores postintervention. Primary care clinician OSA competency scores improved after engaging in a brief educational video intervention when measured using the OSA knowledge and attitude survey. Practicing clinicians can benefit from participating in education about the disease.

Community Organizations, Local Health Equity Action Teams, and a Learning Collaborative to Address COVID-19 Disparities in Urban and Rural Communities.

Rapid Acceleration of Diagnostics-Underserved Populations (RADx-UP) Kansas worked with 10 Kansas counties from November 2020 through June 2022 to form local health equity action teams (LHEATs), develop COVID-19 testing strategies, foster communication about COVID-19, and share best practices through a learning collaborative. Participating counties documented 693 distinct COVID-19 testing and 178 communication activities. Although the intervention was not associated with changes in the proportion of positive COVID-19 tests, LHEATs in the learning collaborative implemented new testing strategies and responded to emerging COVID-19 challenges. (Am J Public Health. Published online ahead of print August 22, 2024:e1-e5. https://doi.org/10.2105/AJPH.2024.307771).

Large-scale integration of remotely sensed and GIS road networks: A full image-vector conflation approach based on optimization and deep learning

Road networks play an important role in the sustainable development of human society. Conventionally, there are two sources of road data acquisition: road extraction from Remote Sensing (RS) imagery and GIS based map production. Each method has its limitations. The RS road extraction methods are primarily raster-based and the extracted roads are not directly usable in GIS due to their fragmented and noisy nature, while vector-based methods cannot utilize rich raster information. Further more, the vector and raster data can have discrepancies for various reasons. Efficient road data production requires an image-vector conflation process that can match and combine raster and vector-based road data automatically.In this study, we propose a full image-vector conflation framework that directly integrates image and vector road data by appropriately transforming extracted roads from imagery and establishing a match relation between these roads and a credible target GIS road dataset. Based on analyzing these match relations, we propose new metrics for measuring the degree of agreement between the raster and vector road data. The proposed framework combines state-of-the-art deep learning methods for image segmentation and optimization-based models for object matching. We prepared a large-scale high-resolution road dataset covering two counties in Kansas, US. Using trained models from one of the two counties, we were able to extract road segments in the other county and match them to the TIGER/Line roads.Our experiments show that conventional performance metrics for road extraction (e.g. IoU) are insufficient for measuring the degree of agreement between image and vector roads as they are pixel-based and are too sensitive to spatial displacement. Instead, the newly defined vector-based agreement metrics are needed for image-vector conflation purposes. Experiments show that, by the vector-based metrics, nearly 90% of GIS road lengths in the study area were extracted and over 90% of extracted roads matched the target GIS roads. The new framework streamlines raster-vector conflation of roads and can potentially expedite relevant geospatial analyses regarding change detection, disaster monitoring and GIS data production, among others.

A Regional Study to Evaluate the Impact of Coal-fired Power Plants on Lung Cancer Incident Rates.

Lung cancer is the leading cause of cancer related deaths. In Kansas, where coal-fired power plants account for 34% of power, we investigated whether hosting counties had higher age-adjusted lung cancer incidence rates. We also examined demographics, poverty levels, percentage of smokers, and environmental conditions using spatial analysis. Data from the Kansas Health Matters, and the Behavioral Risk Factor Surveillance System (2010-2014) for 105 counties in Kansas were analyzed. Multiple Linear Regression (MLR) assessed associations between potential risk factors and age-adjusted lung cancer incidence rates while Geographically Weighted Regression (GWR) examined regional risk factors. Moran's I test confirmed spatial autocorrelation in age-adjusted lung cancer incidence rates (p<0.0003). MLR identified percentage of smokers, population size, and proportion of elderly population as significant predictors of age-adjusted lung cancer incidence rates (p<0.05). GWR showed positive associations between percentage of smokers and age-adjusted lung cancer incidence rates in over 50% of counties. Contrary to our hypothesis, proximity to a coal-fired power plant was not a significant predictor of age-adjusted lung cancer incidence rates. Instead, percentage of smokers emerged as a consistent global and regional risk factor. Regional lung cancer outcomes in Kansas are influenced by wind patterns and elderly population.

“Sex Out of Boredom”: Key Stakeholders’ Perspectives on Teen Pregnancy Prevention in Emerging Immigrant Latino Rural Communities

Abstract Introduction Teen pregnancy (TP) rates are 1.5 times higher among Latina youth than the United States national average and one-third times higher in rural counties. The Socio-Ecological framework recognizes the myriad of issues that impact TP, including four bidirectional levels of influence on teenagers’ behaviors: macro, community, institutional, and interpersonal levels. We aim to fill critical knowledge gaps regarding the influence of key community stakeholders living in rural, Latino-majority communities shaping Latino/a, immigrant adolescents’ TP-related environments. Methods A purposive sample of 48 key stakeholders was drawn from three rural counties (Finney, Ford, and Seward) in southwestern Kansas from 2016 to 2017; participants completed a brief demographic survey and a semi-structured qualitative interview. Qualitative data analysis followed grounded theory within a Socio-Ecological framework, and we used descriptive statistics to analyze survey data. Results Respondents (N = 48) included 5 public health department staff, 8 community health workers, 8 healthcare workers, 9 community members, and 18 high school/college administrators. The mean age was 43 years (SD = 15.5) and 50% self-identified as Latino/a. Recommendations included developing TP prevention education programs for parents, utilizing ongoing events and familiar venues, and keeping content consistent with local culture and norms. Conclusions Key stakeholders’ perceptions regarding TP are often unaccounted for but play a role in shaping youth’s decision-making environments. Policy Implications This information could inform the development of culturally specific TP prevention interventions, especially considering the controversial politics centered on immigration to the U.S. and its negative impact on the overall health of Immigrant Latinos living in the U.S.

Feasibility and Resolution of Shallow Seismic-reflection Techniques in Northwestern Franklin, Southeastern Douglas, and Osage Counties in Kansas

Feasibility and Resolution of Shallow Seismic-reflection Techniques in Northwestern Franklin, Southeastern Douglas, and Osage Counties in Kansas

Correlative ecological niche model applications to predicting landscape-scale woody plant encroachment in Kansas tallgrass prairie systems.

Woody plant encroachment (WPE) in grassland ecosystems has been a pervasive process across the Great Plains, yet a predictive understanding of where it will occur has been elusive. As an exploration of tools of potential utility in this challenge, we mapped WPE processes over the years 2015-2021 in a set of 9 counties in central Kansas. We developed and tested two correlative models based on landscape features: one that assessed distribution of evergreen trees in 2015, and another that assessed areas of WPE in succeeding years. Both models were successful, being able to predict 2015 forest distributions and being able to predict WPE during 2015-2021, as functions of characteristics of landscapes. These simple, correlative models will certainly not be able to predict WPE processes globally, or even regionally, but provide first proof-of-concept explorations for the central Great Plains region.

Are we saving water? Simple methods for assessing the effectiveness of groundwater conservation measures

Substantial storage reductions by irrigation pumping in many of the world’s major aquifers jeopardize future food production. As a result, new conservation measures are being utilized to reduce pumping and extend aquifer lifespans. The key question is how effective are these practices in attaining true water conservation (i.e., water use reduction) for a given area? Relationships between pumping and precipitation help provide an answer, as precipitation explains most of the variation in annual irrigation water use for aquifers in semi-arid to sub-humid climates when surface water supplies are limited. Our objective is to utilize correlations between radar precipitation and irrigation groundwater use at a range of spatial scales to assess the effectiveness of conservation approaches in the High Plains aquifer in the central USA. Linear regressions between pumping and precipitation for a conservation area established in 2013 in northwest Kansas indicate that water use and water use per irrigated area were over 27 % less and 25 % less, respectively, during 2013–2021 compared to the same climatic conditions during 2005–2012. Similar regressions found over a 38 % reduction and 23 % reduction in irrigation water use and use per irrigated area, respectively, during 2018–2021 compared to the same conditions during 2005–2017 in a west-central Kansas county with conservation areas. A decrease in irrigated area accounted for most of the difference between these reductions. Higher R2 values after conservation area establishment imply that irrigation tracks precipitation better due to use of soil moisture sensors and other measures as part of increased irrigation efficiency and enhanced water management. The precipitation and water use relationships, which are statistically significant for a wide range of spatial scales, have great potential for assessing the effectiveness of conservation practices in areas with high-quality water use and precipitation data.

2021 Annual Report of the Kansas Poison Control Center at The University of Kansas Health System.

This is the 2021 Annual Report of the Kansas Poison Control Center (KSPCC) at The University of Kansas Health System. The KSPCC serves the state of Kansas 24-hours a day, 365 days a year with certified specialists in poison information and clinical and medical toxicologists. Encounters reported to the KSPCC from January 1, 2021 through December 31, 2021 were analyzed. Data recorded includes caller demographics, exposure substance, nature and route of exposure, interventions, medical outcome, disposition, and location of care. The KSPCC logged 18,253 total encounters in 2021, including calls from every county in Kansas. A majority of human exposure cases (53.6%) were female. Approximately 59.8% were pediatric exposures (defined as 19 years of age or less). Most encounters occurred at a residence (91.7%) and most were managed there (70.5%). Unintentional exposures were the most common reason for exposures (70.5%). The most common reported substance in pediatric encounters was household cleaning products (n = 815) and cosmetics/personal care products (n = 735). For adult encounters, analgesics (n = 1,241) and sedative/ hypnotics/antipsychotics (n = 1,013) were the most frequently reported. Medical outcomes were 26.0% no effect, 22.4% minor effect, 10.7% moderate effect, and 2.7% major effects. There were 22 deaths. The 2021 KSPCC annual report demonstrated that cases were received from the entire state of Kansas. Pediatric exposures remained most common but cases with serious outcomes continued to increase. This report supported the continued value of the KSPCC to both public and health care providers in the state of Kansas.

A Cross-sectional Survey to Assess Awareness of Syndromic Surveillance by Clinicians Practicing Emergency Medicine: An Opportunity for Education and Collaboration.

Syndromic surveillance (SyS) is an important public health tool using de-identified healthcare discharge data from emergency department (ED) and urgent care settings to rapidly identify new health threats and provide insight into current community well-being. While SyS is directly fed by clinical documentation such as chief complaint or discharge diagnosis, the degree to which clinicians are aware their documentation directly influences public health investigations is unknown. The primary objective of this study was to evaluate the degree to which clinicians practicing in Kansas EDs or urgent care settings were aware that certain de-identified aspects of their documentation are used in public health surveillance and to identify barriers to improved data representation. We distributed an anonymous survey August-November 2021 to clinicians practicing at least part time in emergency or urgent care settings in Kansas. We then compared responses from emergency medicine (EM)-trained physicians to non-EM trained physicians. Descriptive statistics were used for analysis. A total of 189 respondents across 41 Kansas counties responded to the survey. Of those surveyed, 132 (83%) were unaware of SyS. Knowledge did not differ significantly by specialty, practice setting, urban region, age, nor by experience level. Respondents were unaware of which aspects of their documentation were visible to public health entities, or how quickly records were retrievable. When asked about improving documentation for SyS, lack of clinician awareness (71.5%) was perceived as a greater barrier than electronic health record platform usability or time available to document (61% and 59%, respectively). This survey suggests that most practitioners in EM have not heard of SyS and are unaware of the invaluable role certain aspects of their documentation play in public health. Critical information that would be captured and coded into a key syndrome is often missing, but clinicians are unaware of what types of information may be most useful in their documentation, and where to document that information. Lack of knowledge or awareness was identified by clinicians as the single greatest barrier to enhancing surveillance data quality. Increased awareness of this important tool may lead to enhanced utility for timely and impactful surveillance through improved data quality and collaboration between EM practitioners and public health.

Brome mosaic virus detected in Kansas wheat co-infected with other common wheat viruses.

Wheat breeders are developing new virus-resistant varieties; however, it is assumed that only a few viruses or well-known viruses are present in the field. New sequencing technology is allowing for better determination of natural field virus populations. For three years, 2019-2021, Kansas wheat field surveys were conducted to determine the constituents of natural field virus populations using nanopore sequencing. During analysis, brome mosaic virus (BMV) was identified for the first time in Kansas but was in association with other wheat viruses. Brome mosaic virus was identified from 29 out of 47 different Kansas counties sampled and 44% of the total samples. BMV was found co-infected with wheat streak mosaic virus (WSMV) and Triticum mosaic virus (TriMV) in 27.8% of the samples, with WSMV only (13.9%) and co-infected with WSMV + TriMV + High Plains wheat mosaic emaravirus (HPWMoV) (13.9%). RNA genomes of Kansas BMV isolates had 99.4 to 100% nucleotide and amino acid sequence identity, respectively, to each other. RNA2a possessed relatively high divergence (π = 0.01) compared to RNA1a and RNA3a (π = 0.004). Coding regions of all BMV RNAs were considered negative for purifying selection pressure as nonsynonymous and synonymous nucleotide ratio was less than one (dNs/dS >1). The identification of BMV in Kansas virus populations adds another layer of complexity to plant breeding. This work provides information to improve tools to aid in monitoring, detecting, and determining the variation within BMV.

Spatial wind speed interpolation using Isoparametric shape functions for structural loading

This study developed a spatial interpolation technique using Isoparametric finite element shape functions to derive wind speed records for all unsampled Kansas counties from actual data recorded at 17 city locations within and around Kansas. A computational method using the Kaimal spectrum is presented for generating artificial time histories of wind speeds. This is done to extract wind-cycle distribution using the Rainflow counting technique, which can be used as input for fatigue analysis procedures of highway sign structures. Comprehensive validation, verification and benchmarking has been performed in this paper at all spatial and time span levels to guarantee the accuracy and efficiency of the algorithm developed. The comparison of the validation measures strongly suggests a very accurate interpolation scheme that can be confidently used in further fatigue computations and analysis. A user-friendly software was designed using C# to extract wind-speed cycles for all Kansas counties related to different time spans. This software is expected to facilitate fatigue-life prediction because it generates a full range of wind-loading.

A Culture of Fire: Identifying Community Risk Perceptions Surrounding Prescribed Burning in the Flint Hills, Kansas

In the Flint Hills region of eastern Kansas, there is a long tradition of spring prescribed burns. However, air quality concerns in downwind communities have sparked conversation regarding the environmental and social impacts of these burns. This study aimed to identify the risk perceptions associated with prescribed burns using two theoretical frameworks: the social amplification of risk framework and the protective action decision model. In April 2022, we conducted 18 in-depth, semi-structured interviews with Flint Hills community members from different social stations. Participants identified several benefits of prescribed burns: cattle production gains, invasive species management, prairie ecological health maintenance, and wildfire prevention. Some participants viewed prescribed burning as a protective response. However, risk perceptions differed between rural and urban participants: rural community members were primarily concerned with prescribed fires that went out of control, while those in downwind cities were primarily concerned with smoke exposure. Participants sometimes used protective actions to mitigate their risks, but also explained the complexities of changing burn practices that are integral to the local culture, economies, and greater society. Additionally, formal communication of health and safety risks from prescribed burns is not uniform across Kansas counties. We therefore recommend systematic county and statewide communication of burn practices and protective behaviors. Understanding community perceptions of the risks and effects of prescribed burns, and any protective actions taken, can inform how professional communicators approach burning in similar agricultural and ranching communities.

Assessing Social Needs and Engaging Community Health Workers in Underserved Kansas Counties: Insights From Primary Care Providers and Clinic Managers.

Rural and under-resourced urban communities face unique challenges in addressing patients' social determinants of health needs (SDoH). Community health workers (CHWs) can support patients experiencing social needs, yet little is known about how rural and under-resourced primary care clinics are screening for SDoH or utilizing CHWs. Interviews were conducted with primary care clinic providers and managers across a geographically large and predominately rural state to assess screening practices for SDoH and related community resources, and perspectives on using CHWs to address SDoH. Interviews were conducted by phone, recorded, and transcribed. Data were analyzed using thematic analysis. We completed interviews with 27 respondents (12 providers and 15 clinic managers) at 26 clinics. Twelve (46.1%) clinics had a standardized process for capturing SDoH, but this was primarily limited to Medicare wellness visits. Staffing and time were identified as barriers to proper SDoH screening. Lack of transportation and affordable medication were the most cited SDoH. While respondents were all aware of CHWs, only 8 (30.8%) included a CHW on their care team. Perceived barriers to engaging CHWs included cost, space, and availability of qualified CHWs. Perceived benefits of engaging CHWs in their practice were: assisting patients with navigating resources and programs, relieving clinical staff of non-medical tasks, and bridging language barriers. Rural and under-resourced primary care clinics need help in identifying and addressing SDoH. CHWs could play an important part in addressing social needs and promoting preventive care if financial constraints could be addressed and local CHWs could be trained.

Analysis of the Prairie Dog Creek Alluvial Aquifer in Northwest Kansas

The geosciences department at Fort Hays State University and the Kansas Department of Health and Environment (KDHE) determined the extent of mineral contamination in three aquifers in northwest Kansas. The contaminant results from the Prairie Dog Creek alluvial aquifer were used for this study. Forty wells spanning across the Kansas counties of Phillips, Norton, and Decatur allowed for statistical and spatial examination of the contamination. Groundwater flow direction was determined from elevation data and well water depth records. A correlation between possible contaminant buildup and groundwater altitude was investigated but did not yield a significant correlation. Since there is no overall buildup in any of the contaminants, very localized sources in geology or land use are affecting individual wells. A large part of this study focuses on communicating the importance of clean drinking water.

The Adequacy of Prenatal Care in Rural Kansas Related to Distance Traveled.

Prenatal care is essential for optimizing the health of a woman and her baby. Multiple factors have created barriers in the access to prenatal care in rural Kansas. Over 120 rural hospitals in the United States have closed since 2010, 5 in Kansas. Seventy-seven of the 105 Kansas counties do not have maternity care services. This study investigated differences in prenatal care received by women in rural Kansas counties related to distance traveled. Differences in timing of initiation of care, number of visits, and services received were compared between two cohorts: those who drove < 19 miles and those who drove ≥ 20 miles for prenatal care. A survey was distributed to women who had delivered a child in the last three years in rural Kansas at participating clinics. Measures of adequacy of prenatal care were determined with questions regarding timing of first prenatal visit, number of prenatal visits, and services received at visits. An index was created using these variables and compared between the two cohorts using two-tailed t-tests for continuous data and chi square analysis for categorical data. Women who traveled ≥ 20 miles for prenatal care received statistically significant less services, and had less prenatal care visits in the second trimester and overall in their pregnancy compared to women who traveled < 19 miles for prenatal care. Rurality did not impact adequacy of prenatal care. Women traveling ≥ 20 miles to receive prenatal care had significantly fewer prenatal visits during their second trimester and overall in pregnancy and self-reported less prenatal care services. These results indicated the importance of lessening barriers to prenatal care in rural Kansas, such as transportation and financial barriers.

Birth Outcomes Related to Distance in Rural and Frontier Kansas.

IntroductionWomen from rural communities must travel greater distances to secure obstetrical care. This study sought the extent to which distance traveled by mothers for obstetrical services affects birth outcomes in rural and frontier counties of Kansas.MethodsMedical students invited women over the age of 18 to participate in a recall survey regarding their children under three years old. Participants were a sample of convenience, and the length of data collection was a month. A bivariate analysis was performed on the responses gathered regarding obstetrical measures as a function of self-reported distance traveled to the hospital of delivery.ResultsEighty-five women completed the survey, but only 76 satisfied all eligibility requirements. No statistical difference in birth outcomes were found between women who travel more than or less than 20 miles. However, when correlating data to that of the Kansas Hospital Association and the Kansas Department of Health and Environment, counties without birth facilities had a higher percentage of very low birth weights (< 1,500 grams) and more babies born at full-term when compared to counties that offer birth facilities. Babies born to mothers who reside in counties with obstetrical services were born at an earlier gestational age than those without birth facilities. Lastly, babies born into a family with income less than $50,000 weighed less and had a shorter gestational age than those from a more affluent household.ConclusionsThe results revealed counterintuitive findings that deserve to be explored further by a study with greater statistical power.

Yield Gap Analysis of Alfalfa Grown under Rainfed Condition in Kansas

The yield and production of alfalfa (Medicago sativa L.) have not been significantly improved in Kansas for the last 30 years even though farmers are using improved varieties. We have noted a significant yield difference between average alfalfa yield reported by farmers and researchers. The magnitude of yield gap in Kansas and its underlying factors are still unknown. Thus, understanding of potential yield is essential to meet the future forage demand with the limited production resources. The main objective of this study was, therefore, to quantify the current yield gap and identify the main yield-limiting factor for rainfed alfalfa grown in Kansas. To achieve this objective, we selected 24 counties in Kansas based on the rainfed production area and total production, and used county-level yield, daily temperature, and rainfall data from the past 30 yrs (1988–2017) of those selected counties. We applied four statistical approaches: (i) probability distribution function to delineate county-level alfalfa growing season, (ii) stochastic frontier yield function to estimate optimum growing season rainfall (GSR) and attainable yield, (iii) linear boundary function to estimate minimum water loss, water use efficiency, and water-limited potential yield, and (iv) conditional inference tree to identify the major yield contributing weather variables. The probability distribution function delineated the alfalfa growing season starting from mid-March to mid-November in Kansas. The frontier model estimated the attainable yield of 9.2 Mg ha−1 at an optimum GSR of 664 mm, generating a current yield gap of 18%. The linear boundary function estimated the water-limited potential yield of 15.5 Mg ha−1 at an existing GSR of 624 mm, generating a yield gap of 50%. The conditional inference tree revealed that 24% of the variation in rainfed alfalfa yield in Kansas was explained by weather variables, mainly due to GSR followed minimum temperature. However, we found only 7% GSR deficit in the study area, indicating that GSR is not the only cause for such a wide yield gap. Thus, further investigation of other yield-limiting management factors is essential to minimize the current yield gap. The statistical models used in this study might be particularly useful when yield estimation using remote sensing and crop simulation models are not applicable in terms of time, resources, facilities, and investments.