Journal of Rural Health最新文献

{"title":"Weaving the rural health safety net: Voices from the field","authors":"Jessica Riley MS, Eileen M. Dryden PhD, Catherine M. P. Dawson MD, Meaghan A. Kennedy MD, MPH, Lauren R. Moo MD, Camilla B. Pimentel PhD, William Hung MD","doi":"10.1111/jrh.70080","DOIUrl":"10.1111/jrh.70080","url":null,"abstract":"","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":"41 4","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145187395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The roles of COVID-19 pandemic exposure and telehealth in prenatal care access for rural and racial minority communities in the United States: A retrospective cohort study","authors":"Peiyin Hung PhD,&nbsp;Jiani Yu PhD,&nbsp;Adiba B. Promiti MS,&nbsp;Berry A. Campbell MD, MFM,&nbsp;Nansi S. Boghossian PhD,&nbsp;Anirban Chatterjee MD,&nbsp;Bo Cai PhD,&nbsp;Jihong Liu ScD,&nbsp;the National COVID Cohort Collaborative Consortium","doi":"10.1111/jrh.70077","DOIUrl":"10.1111/jrh.70077","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>To examine how COVID-19 public health emergency (PHE) exposure during pregnancy and telehealth use were associated with rural-urban and racial/ethnic differences in prenatal care initiation timing and frequency.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This retrospective cohort study of 349,682 pregnancies to birthing individuals who received both prenatal and intrapartum care at the 75 health systems in the United States contributing to the National Clinical Cohort Collaborative (N3C) from 6/1/2018 through 5/31/2022. Outcomes included prenatal care initiation timing and the number of prenatal care visits. Prenatal periods were categorized into 3 PHE exposure groups: (1) never, (2) partially, and (3) fully exposed to the PHE. The full-exposure group was further categorized into telehealth users and those with exclusively in-person care.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Findings</h3>\u0000 \u0000 <p>The full-exposure group with telehealth uptake had the earliest prenatal care initiation (median: 9 weeks [interquartile range: 7-13]) and the most visits (19 visits [12-20]). In contrast, the full-exposure group <i>without</i> telehealth use initiated care the latest (11 weeks [8-21]) and had the fewest visits (13 visits [6-22]). Rural-urban disparities persisted; however, telehealth users in both groups had earlier initiation and more visits. Racial and ethnic disparities in timeliness to initiation were most pronounced among the full-exposure group with telehealth (Black-White: adjusted hazard ratio [aHR]: 0.76, 95% CI, 0.70-0.83; Hispanic-White: aHR: 0.62, 95% CI, 0.58-0.68), compared to the full-exposure group with exclusively in-person care (Black-White: 0.95 [0.93-0.94]; Hispanic-White: 0.80 [0.80-0.81]).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Prenatal telehealth care improved early initiation but also exacerbated racial/ethnic disparities in the timeliness of prenatal care access. However, rural-urban disparities persisted.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":"41 4","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12481008/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145193700","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Differences in the travel burden for care between rural and urban patients with opioid use disorder by insurance type","authors":"C. Holly A. Andrilla MS,&nbsp;Sara C. Woolcock MPH,&nbsp;Lisa A. Garberson PhD,&nbsp;Janessa M. Graves PhD","doi":"10.1111/jrh.70078","DOIUrl":"10.1111/jrh.70078","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>To compare the time and distance travel burden to access care for rural and urban Medicaid and commercially insured patients with opioid use disorder (OUD), and to understand where they travel for care.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We used Medicaid and the Health Care Cost Institute commercial insurance administrative claims data from 2019 to examine the travel burden to health care for adults ages 18 years and older with OUD. We calculated the one-way driving distance and travel time between the enrollee's residence and the provider's location. We used the 2013 Urban Influence Codes (UIC) to classify enrollees as either urban (UIC 1–2) or rural (UIC 3–12) based on the patient's residence county.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Findings</h3>\u0000 \u0000 <p>The median distance traveled for a visit by a rural Medicaid or rural commercially insured enrollee was more than twice as far as their urban counterparts (rural Medicaid: 45.9 miles, urban Medicaid: 13.9 miles; rural commercially insured: 32.9 miles, urban commercially insured: 12.4 miles). When we imputed zeros for care provided in the same ZIP Code as an enrollee's residence, these differences persisted. Rural Medicaid enrollees carried the largest travel burden spending an average of more than 60 min traveling to care, about 30 min more than rural commercially insured enrollees. Urban enrollees, regardless of insurance type received almost all of their care in an urban location while rural Medicaid and commercially insured patients traveled to an urban location for about half their visits.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Rural and urban Medicaid and commercially insured enrollees experience different time and distance travel burdens.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":"41 4","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145187373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adverse childhood experiences and preventive health care among rural US children: A cross-sectional examination of 2022 National Health Interview Survey data","authors":"Mary Labuhn MPH,&nbsp;Andrew Williams MPH, PhD","doi":"10.1111/jrh.70081","DOIUrl":"https://doi.org/10.1111/jrh.70081","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>Rural-residing children have poor access to preventive health care due to geographic and socioeconomic issues, yet the role of adverse childhood experiences (ACEs) in preventive care for rural children has been understudied. It is hypothesized that among rural-residing children, those with ≥1 ACE will have lower utilization of preventive health care, with differences by sex.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Data for 425 (weighted n = 3,949,102) children (aged 9-17) residing in “nonmetropolitan” (2013 NCHS Urban-Rural Classification) were drawn from the 2022 National Health Interview Survey. Physician visit in the past 12 months (yes/no), dental visit in the past 12 months (yes/no), COVID-19, flu, and HPV vaccination (yes/no) were self-reported. Participants self-reported (yes/no) to 6 ACEs (high ACEs ≥1). Logistic regression estimated odds ratios and 95% confidence intervals for associations between ACEs and preventive health outcomes, adjusted for demographic and health care factors. This manuscript adheres to STROBE guidelines.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Findings</h3>\u0000 \u0000 <p>Children with ≥1 ACE were 81% more likely (OR = 1.81, 95% CI 1.04, 3.18) to receive a flu vaccination and 184% (OR = 2.84, 95% CI 1.66, 4.85) more likely to receive an HPV vaccination compared to children with 0 ACEs. No significant associations were found between ACEs and other preventive health care. Boys with ≥1 ACE had decreased odds (OR = 0.34, 95% CI 0.13, 0.94) of visiting a dentist, while girls with ≥1 ACE had increased odds (OR = 3.87, 95% CI 1.56, 9.60) of receiving an HPV vaccination.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Children with ≥1 ACE were more likely to receive a flu vaccination and HPV vaccination. The effect of ACEs on preventive health care may differ by sex among rural residents, yet additional research is warranted to inform prevention efforts in rural communities.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":"41 4","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jrh.70081","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145181585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Skill mix versus flexibility: Decoding nurse staffing impacts on critical access hospitals","authors":"Dinesh R. Pai PhD,&nbsp;Esmaeil Bahalkeh PhD","doi":"10.1111/jrh.70075","DOIUrl":"https://doi.org/10.1111/jrh.70075","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>This study examines the effect of nurse staffing (skill mix and flexibility) on the financial sustainability, efficiency, and quality of care in Pennsylvania's critical access hospitals (CAHs) from 2000 to 2023.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This retrospective longitudinal study utilized unbalanced panel data from Pennsylvania's CAHs (n = 357 hospital-year observations). We employed 2-way fixed effects regression models to analyze the relationship between nurse staffing variables (skill mix and flexibility) and hospital performance outcomes (total margin, cost per adjusted discharge [CPAD], cost per adjusted patient day [CPPD], average length of stay [ALOS], and readmission index). We controlled for hospital-specific, socioeconomic, and demographic factors.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>A higher registered nurse (RN) skill mix significantly reduced log(winsorized(CPAD)) (<i>β</i> = −0.495, <i>p</i>&lt;0.01) and log(ALOS) (<i>β</i> = −0.571, <i>p</i>&lt;0.01), indicating improved cost efficiency and patient throughput. Increased nurse flexibility significantly increased log(ALOS) (<i>β</i> = 0.315, <i>p</i>&lt;0.05) but reduced the readmission index (<i>β</i> = −0.895, <i>p</i>&lt;0.01). No significant associations were found between skill mix and total margin, CPPD, or readmission index, nor between flexibility and financial metrics.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Discussion</h3>\u0000 \u0000 <p>A richer RN skill mix enhances efficiency by reducing costs and length of stay, while increased staffing flexibility reduces readmissions but extends ALOS. These findings emphasize the complex interplay between nurse staffing and CAH performance. Strategic management of RN skill mix and flexibility is crucial for optimizing resource use and improving patient outcomes in rural hospitals.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Policymakers and CAH administrators should strategically balance RN expertise and staffing flexibility to ensure both financial viability and clinical excellence in these essential rural health care institutions.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":"41 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jrh.70075","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144910186","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rural and urban differences in treatment on demand for substance use treatment involving medications for opioid use disorder","authors":"Ryan J. Lofaro PhD,&nbsp;Robert M. Bohler PhD,&nbsp;Robert Spurgeon BA,&nbsp;William A. Mase DrPH","doi":"10.1111/jrh.70076","DOIUrl":"https://doi.org/10.1111/jrh.70076","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>Research has found that the use of medications for opioid use disorder (MOUD) varies across the rural-urban divide; however, relationships between rurality, MOUD, and substance use treatment wait times remain underexplored. This study analyzes associations between rurality, MOUD usage, and immediate access to outpatient treatment—that is, “treatment on demand”—in the United States.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Using 2021-2022 Treatment Episode Data Set Admissions (TEDS-A) data on outpatient treatment centers, we employ logistic regression to analyze treatment on demand (0-day wait time) as the outcome and rurality as the key predictor in models disaggregated into patients who utilized MOUD at intake and those who did not. Analyses are also disaggregated by Census region and division of the country.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Findings</h3>\u0000 \u0000 <p>Results show that rurality reduces the odds of treatment on demand in both MOUD (OR = .513, <i>P</i> &lt;.001) and non-MOUD (OR = .593, <i>P</i> &lt;.001) models, with slightly stronger effects in the former. Associations with rurality vary substantially by region of the country. MOUD models in the Midwest, West, and South show rurality has a significant negative effect; these negative associations held for non-MOUD models only in the South. Further, differences across Census divisions highlight rurality's spatial disparities at a more granular level.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Understanding barriers to treatment on demand for evidence-based treatments is a crucial aspect of ensuring people who have opioid use disorder in rural regions receive the care they need. Policies should focus on increasing access to treatment to avoid delays while considering regional differences.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":"41 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144897593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Trends in mental health care utilization in rural and nonrural areas, 2019-2023","authors":"Bryce J. Stanley PhD","doi":"10.1111/jrh.70074","DOIUrl":"https://doi.org/10.1111/jrh.70074","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>The recent increase in mental health care providers offering telehealth may improve access by reducing travel costs, particularly for those in rural areas. This paper seeks to understand how mental health care utilization changed from 2019 to 2023 for rural and nonrural areas.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This study uses data from the National Health Interview Survey for 2019 and 2021-2023 (n = 118,652). To adjust the utilization rates for sociodemographic factors, a probit model with survey weights is used. For each year, the adjusted percentage of rural and nonrural populations receiving any mental health care in the past year is reported. Changes in demographic characteristics of those receiving care are also discussed.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Findings</h3>\u0000 \u0000 <p>This study finds that both rural and nonrural populations experienced large increases in adjusted mental health care utilization rates from 2019 to 2023. Utilization rates in rural areas grew 3.72 percentage points, from 9.35% (95% CI: 8.85-9.84) in 2019 to 13.07% (95% CI: 12.86-13.28) in 2023. For nonrural areas, utilization rates increased 4.40 percentage points, from 12.06% (95% CI: 11.79-12.74) in 2019 to 16.46% (95% CI: 15.82-17.11) in 2023.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Rural populations utilize less mental health care than nonrural populations, but both saw a substantial increase from 2019 to 2023. While telehealth may particularly benefit rural areas, these data suggest a larger increase in utilization for nonrural respondents. Future work is needed to better understand remote mental health care and rural populations.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":"41 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jrh.70074","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144891600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rural patients’ experiences with diagnosis and treatment of endometrial cancer","authors":"Victoria M. Petermann PhD, RN,&nbsp;Brianna D. Taffe MPH,&nbsp;Blen M. Biru MSc,&nbsp;Jennifer Leeman DrPH, MPH, MDiV,&nbsp;Ashley Leak Bryant PhD, RN, OCN, FAAN,&nbsp;Benjamin B. Albright MD, MS,&nbsp;Stephanie B. Wheeler PhD, MPH,&nbsp;Victoria L. Bae-Jump MD, PhD,&nbsp;Lanneau Grainger MD,&nbsp;Lisa P. Spees PhD","doi":"10.1111/jrh.70065","DOIUrl":"https://doi.org/10.1111/jrh.70065","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Rural endometrial cancer (EC) patients are less likely to receive lymph node evaluation, high-quality surgical care, and adjuvant therapy compared to urban patients. Developing interventions to effectively address barriers to quality care requires understanding patient experiences across the cancer care continuum. Our objective was to understand the diagnostic and treatment experiences of rural EC patients.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We conducted semistructured interviews with 23 participants (22 patients, one caregiver) from rural counties in North Carolina. We developed a semistructured interview guide to examine the experiences of patients during diagnosis and treatment. Initial codes were derived from a multilevel conceptual framework of rural cancer control, and transcribed interviews were analyzed using thematic analysis.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>We identified six themes reflecting determinants of diagnosis and seven themes for treatment of EC for rural patients. Provider knowledge of EC symptoms, patient symptom normalization, and fear were all discussed as major factors impacting delays in EC diagnosis. Participants noted that social networks influenced them to seek care for symptoms they did not otherwise see as concerning. During treatment, participants experienced financial burdens, and many reported significant challenges traveling to treatment. Social networks were critical for financial support and transportation to and from treatment. Personal health care experiences and community perceptions about rural cancer care also influenced decisions about where to seek gynecologic cancer treatment.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>This study highlights the need to improve rural provider adherence to guidelines for EC detection, increase symptom knowledge among rural communities, and implement comprehensive assessments of unmet needs of rural patients during treatment.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":"41 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jrh.70065","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144891704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hearing aid acquisition patterns among US Veterans who use VA health care","authors":"Laura Coco PhD, AuD,&nbsp;Loretta Shields PhD,&nbsp;Rachel Phillips MS,&nbsp;Stephanie Pesa AuD,&nbsp;Matthew Hamilton-Sutherland AuD,&nbsp;Kathleen F. Carlson PhD, MS,&nbsp;Dawn L. Konrad-Martin PhD,&nbsp;Kelly M. Reavis PhD, MS, MPH","doi":"10.1111/jrh.70068","DOIUrl":"https://doi.org/10.1111/jrh.70068","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>The primary objective of this observational study was to describe the population of Veterans who did and did not receive a hearing aid following an incident hearing loss diagnosis during the 12-year study period. We also sought to measure the relationship between hearing loss severity and hearing aid acquisition and explore how this association differs according to Veterans’ urban/rural residential status. Understanding associations of clinical or demographic characteristics with hearing aid acquisition by US Veteran health care users may contribute to more effective treatment of hearing loss.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Method</h3>\u0000 \u0000 <p>We examined all Veteran electronic health records to identify participants with an incident (new) hearing loss diagnosis between January 2011 and June 2023. Hearing loss was identified using International Classification of Diseases diagnosis codes and audiogram results. Hearing aid fittings were identified using Current Procedural Terminology codes. Poisson regression models were used to compute rate ratios and 95% confidence intervals of hearing aid acquisition.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Among 256,409 Veterans with an incident hearing loss diagnosis, the prevalence of hearing aid acquisition was 81% (<i>n</i> = 206,438) during the study period. Among Veterans who received hearing aids, a greater proportion were older, male, White, non-Hispanic, married, and from higher income groups. The average number of days between hearing loss diagnosis and hearing aid fitting was less than 1 year (<i>M</i> = 200 days; SD = 502 days). The association between hearing loss severity and hearing aid acquisition was stronger among urban Veterans compared to rural Veterans, and there was a significant interaction between hearing loss severity and urban/rural status (<i>p</i> &lt; .0001).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>This large, national cohort study provides the first description of hearing aid acquisition patterns among Veterans using VA health care. Hearing aid uptake was high overall but varied by demographic and geographic factors. The observed differences may reflect structural challenges or variations in perceived need. These findings can help inform targeted VA programs aimed at improving timely uptake of hearing care, particularly among rural Veteran populations.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":"41 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144861652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Tobacco retailer density and rurality across four US states: California, Connecticut, North Carolina, and Ohio","authors":"Emerson Webb MS,&nbsp;Peter F. Craigmile PhD,&nbsp;Meghan E. Morean PhD,&nbsp;Grace Kong PhD,&nbsp;Joseph G. L. Lee PhD,&nbsp;Ryan J. Martin PhD,&nbsp;Jessica Barrington-Trimis PhD,&nbsp;Rui Qiang PhD,&nbsp;Vitoria Borges Spinola DDS,&nbsp;Megan E. Roberts PhD","doi":"10.1111/jrh.70073","DOIUrl":"https://doi.org/10.1111/jrh.70073","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>Research has demonstrated many types of disparities in tobacco retailer density (TRD), but these analyses often fail to explore rural disparities. Given the substantial burden of rural tobacco use in the USA, this is a critical gap. The purpose of the present study was to estimate rural disparities in TRD across four US states.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>For the states of California, Connecticut, North Carolina, and Ohio, we used spatial statistical methods to model per capita TRD at the census tract level. Rurality was defined by the US Department of Agriculture Rural-Uran Commuting Area (RUCA) codes and categorized into Metropolitan, Micropolitan, Small Town, and Rural.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Findings</h3>\u0000 \u0000 <p>Tobacco retailer count was highest in California (22,533), but TRD was highest in Connecticut (1.23 retailers per 1000 residents). In models for California, North Carolina, and Ohio (but not Connecticut), there was an association between rurality and TRD, such that rural census tracts had greater TRD than metropolitan census tracts. Micropolitan and small town (vs. metropolitan) census tracts also had greater TRD, although the association was not as strong. Models further showed associations between TRD and census tract poverty, racial and ethnic composition, and Appalachian designation.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Although there are notable state-level differences, TRD is clearly associated with rurality. Given the literature on the impacts of living in tobacco-retailer-dense areas, rural disparities in TRD likely contribute to rural disparities in tobacco use. There is a need for further policies in rural areas of the USA that address the tobacco retailer environment.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":"41 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jrh.70073","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144853806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}