Healthy food delivery for type 2 diabetes management in rural clinics' patients: A comparative effectiveness randomized controlled trial protocol.

BACKGROUND: Rural populations experience a higher prevalence of both food insecurity and type 2 diabetes mellitus (T2DM) than metropolitan populations and face many challenges in accessing resources essential to optimal T2DM self-management. This study aims to address these challenges by delivering a T2DM-appropriate food box and recipes directly to rural participants' homes. METHODS: This is a comparative effectiveness randomized controlled trial including 400 English- or Spanish-speaking rural adult participants with T2DM (HbA1c ≥6.5%) experiencing food insecurity. Participants are randomly assigned to a 3-month Healthy Food Delivery Intervention (HFDI) plus one 60-min virtual consultation with a diabetes educator or consultation only. The HFDI includes a weekly food box delivery with recipes. Data are collected at pre-intervention, 3-months (post-intervention), 9-months, and 15-months. The primary outcome is change in HbA1c, with secondary measures including diet quality (Healthy Eating Index-2015, calculated from one 24-h dietary recall at each data collection time point), cardio-metabolic risk factors (i.e., blood pressure, lipids, body mass index, glucose), and patient-centered outcomes (e.g., T2DM self-efficacy, T2DM-related distress). Process evaluation data (e.g., successful food box deliveries, diabetes educator consultation attendance, intervention satisfaction) are collected during and post-intervention (3-months). A cost-effectiveness analysis based on traditional cost per quality-adjusted life year gain thresholds will be conducted to estimate the incremental cost-effectiveness between HFDI plus consultation and consultation alone. CONCLUSION: Findings from this study will provide evidence regarding the effectiveness of an intervention that promotes participant adherence and improves access to healthy food. CLINICAL TRIAL REGISTRATION: NCT04876053.

Association of Hospice Agency Location and Neighborhood Socioeconomic Disadvantage in the U.S.

BACKGROUND: Despite the growing increase in the utilization of hospice in the U.S, disparities exist in the utilization of hospice. Accumulating evidence has shown that neighborhood characteristics have an impact on availability of hospice agencies. OBJECTIVE: To assess the association between neighborhood social vulnerability and hospice agency availability. METHODS: Using the Medicare Post-Acute Care and Hospice Provider Utilization and Payment Public Use Files (PAC PUF) for 2019. Hospice agency addresses were geocoded to the census tract level. Multivariable Poisson regression models were used to assess the association between socioeconomic status SVI theme and hospice agency availability adjusting for number of home health agencies, primary care health profession shortage, per cent Black, and Percent Hispanic at the census tract level and rurality. RESULTS: The socioeconomic status SVI subtheme was associated with decreased likelihood of hospice agency availability (adjusted IRR (aIRR), .56; 95% CI, .50- .63; P < .001). Predominantly Black, and predominantly Hispanic neighborhoods had lower rates of hospice agency availability (aIRR, .48; 95% CI, .39-.59; P < .001 and aIRR, .29; 95% CI, .24-.36; P < .001), respectively. CONCLUSION: Neighborhood socioeconomic disadvantage was associated with lower availability of hospice agencies. Policies aimed at increasing access to hospice should be cognizant of neighborhood socioeconomic disadvantage.

Socioeconomic Determinants of Remote Patient Monitoring Implementation Among Rural and Urban Hospitals.

Introduction: Remote patient monitoring (RPM) is a form of telehealth that improves quality of care for chronic disease treatment and reduces hospital readmission rates. Geographical proximity to health care is important for individuals of low socioeconomic status (SES) who face additional financial and transportation barriers. The goal of this study was to assess the association between social determinants of health and adoption of RPM. Methods: This cross-sectional study analyzed data from hospitals that responded to the American Hospital Association's Annual Survey (2018) and spatially linked census tract-level environmental and social determinants of health obtained from the Social Vulnerability Index (2018). Results: A total of 4,206 hospitals (1,681 rural and 2,525 urban hospitals) met study criteria. Rural hospitals near households in the lower middle quartile SES were associated with a 33.5% lower likelihood of having adopted RPM for chronic care management compared with rural hospitals near households in the highest quartile SES (adjusted odds ratios [aOR] = 0.665; 95% confidence interval [CI]: 0.453-0.977). Urban hospitals near households in the lowest quartile SES were associated with a 41.9% lower likelihood of having adopted RPM for chronic care management compared with urban hospitals near households in the highest quartile SES (aOR = 0.581; 95% CI: 0.435-0.775). Similar trends in accessibility were found with RPM for postdischarge services among urban hospitals. Conclusion: Our findings highlight the importance of hospital responsibility and state and federal policy approaches toward ensuring equitable access to RPM services for patients characterized by lower SES.

Hidden Costs of the COVID-19 Pandemic Response.

"First, do no harm" [...].

Temporal Variations in Seroprevalence of Severe Acute Respiratory Syndrome Coronavirus 2 Infections by Race and Ethnicity in Arkansas.

Background: The aim of this study was to estimate severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection rates in the small rural state of Arkansas, using SARS-CoV-2 antibody prevalence as an indicator of infection. Methods: We collected residual serum samples from adult outpatients seen at hospitals or clinics in Arkansas for non-coronavirus disease 2019 (COVID-19)-related reasons. A total of 5804 samples were identified over 3 time periods: 15 August-5 September 2020 (time period 1), 12 September-24 October 2020 (time period 2), and 7 November-19 December 2020 (time period 3). Results: The age-, sex-, race-, and ethnicity-standardized SARS-CoV-2 seroprevalence during each period, from 2.6% in time period 1 to 4.1% in time period 2 and 7.4% in time period 3. No statistically significant difference in seroprevalence was found based on age, sex, or residence (urban vs rural). However, we found higher seroprevalence rates in each time period for Hispanics (17.6%, 20.6%, and 23.4%, respectively) and non-Hispanic Blacks (4.8%, 5.4%, and 8.9%, respectively) relative to non-Hispanic Whites (1.1%, 2.6%, and 5.5%, respectively). Conclusions: Our data imply that the number of Arkansas residents infected with SARS-CoV-2 rose steadily from 2.6% in August to 7.4% in December 2020. There was no statistical difference in seroprevalence between rural and urban locales. Hispanics and Blacks had higher rates of SARS-CoV-2 antibodies than Whites, indicating that SARS-CoV-2 spread disproportionately in racial and ethnic minorities during the first year of the COVID-19 pandemic.

Geospatial Assessment of Pesticide Concentration in Ambient Air and Colorectal Cancer Incidence in Arkansas, 2013-2017.

Exposure to various agricultural pesticides has been linked to colorectal cancer (CRC), mostly among farmworkers and applicators. Given the potential pesticide drift in ambient air, residents near farmland may be exposed to carcinogenic pesticides even if they are not actively engaged in pesticide application. Pesticide air pollution at the county level was estimated using the 2014 National Air Toxics Assessment. CRC incidence data were acquired from the Arkansas Central Cancer Registry for 2013-2017. We ran ordinary least squares (OLS) regression models, finding significant spatial autocorrelation of residuals for most models. Using geographically weighted regression (GWR) we found age-adjusted CRC incidence rates vary in an increasing west-to-east gradient, with the highest rates in the Arkansas Delta region. A similar gradient was observed in the distribution of the population living below the poverty line and the population percentage of Black people. Significant associations between Trifluralin (crude model only), Carbon Tetrachloride, and Ethylene Dibromide with CRC incidence rates in OLS models only explained 5-7% of the variation and exhibited spatial autocorrelation of residuals. GWR models explained 24-32% (adjusted r2 9-16%) of CRC incidence rate variation, suggesting additional factors may contribute to the association between pesticides and CRC.

Impact of nonphysician providers on spatial accessibility to primary care in Iowa.

OBJECTIVE: To assess the impact of nonphysician providers on measures of spatial access to primary care in Iowa, a state where physician assistants and advanced practice registered nurses are considered primary care providers. DATA SOURCES: 2017 Iowa Health Professions Inventory (Carver College of Medicine), and minor civil division (MCD) level population data for Iowa from the American Community Survey. STUDY DESIGN: We used a constrained optimization model to probabilistically allocate patient populations to nearby (within a 30-minute drive) primary care providers. We compared the results (across 10 000 scenarios) using only primary care physicians with those including nonphysician providers (NPPs). We analyze results by rurality and compare findings with current health professional shortage areas. DATA COLLECTION/EXTRACTION METHODS: Physicians and NPPs practicing in primary care in 2017 were extracted from the Iowa Health Professions Inventory. PRINCIPAL FINDINGS: Considering only primary care physicians, the average unallocated population for primary care was 222 109 (7 percent of Iowa's population). Most of the unallocated population (86 percent) was in rural areas with low population density (< 50/square mile). The addition of NPPs to the primary care workforce reduced unallocated population by 65 percent to 78 252 (2.5 percent of Iowa's population). Despite the majority of NPPs being located in urban areas, most of the improvement in spatial accessibility (78 percent) is associated with sparsely populated rural areas. CONCLUSIONS: The inclusion of nonphysician providers greatly reduces but does not eliminate all areas of inadequate spatial access to primary care.