Journal of Rural Health最新文献

{"title":"Excess deaths associated with COVID-19 by rurality and demographic factors in the United States","authors":"Katherine A. Ahrens MPH, PhD,&nbsp;Lauren M. Rossen PhD,&nbsp;Carly Milkowski MPH,&nbsp;Catherine Gelsinger RN, MPH,&nbsp;Erika Ziller PhD","doi":"10.1111/jrh.12815","DOIUrl":"10.1111/jrh.12815","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>To estimate percent excess deaths during the COVID-19 pandemic by rural-urban residence in the United States and to describe rural-urban disparities by age, sex, and race/ethnicity.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Using US mortality data, we used overdispersed Poisson regression models to estimate monthly expected death counts by rurality of residence, age group, sex, and race/ethnicity, and compared expected death counts with observed deaths. We then summarized excess deaths over 6 6-month time periods.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Findings</h3>\u0000 \u0000 <p>There were 16.9% (95% confidence interval [CI]: 16.8, 17.0) more deaths than expected between March 2020 and February 2023. The percent excess varied by rurality (large central metro: 18.2% [18.1, 18.4], large fringe metro: 15.6% [15.5, 15.8], medium metro: 18.1% [18.0, 18.3], small metro: 15.5% [15.3, 15.7], micropolitan rural: 16.3% [16.1, 16.5], and noncore rural: 15.8% [15.6, 16.1]). The percent excess deaths were 20.2% (20.1, 20.3) for males and 13.6% (13.5, 13.7) for females, and highest for Hispanic persons (49% [49.0, 49.6]), followed by non-Hispanic Black persons (28% [27.5, 27.9]) and non-Hispanic White persons (12% [11.6, 11.8]). The 6-month time periods with the highest percent excess deaths for large central metro areas were March 2020-August 2020 and September 2020-February 2021; for all other areas, these time periods were September 2020-February 2021 and September 2021-February 2022.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Percent excess deaths varied by rurality, age group, sex, race/ethnicity, and time period. Monitoring excess deaths by rurality may be useful in assessing the impact of the pandemic over time, as rural-urban patterns appear to differ.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2023-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138572491","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":"Assessing the relationship between census tract rurality and severe maternal morbidity in California (1997-2018)","authors":"Rachel L. Berkowitz DrPH, MPH,&nbsp;Peiyi Kan MS,&nbsp;Xing Gao PhD, MPH,&nbsp;Elleni M. Hailu PhD, MPH,&nbsp;Christine Board MPH,&nbsp;Audrey Lyndon PhD, RNC, FAAN,&nbsp;Mahasin Mujahid PhD, MS, FAHA,&nbsp;Suzan L. Carmichael PhD, MS","doi":"10.1111/jrh.12814","DOIUrl":"10.1111/jrh.12814","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>Recent studies have demonstrated an increased risk of severe maternal morbidity (SMM) for people living in rural versus urban counties. Studies have not considered rurality at the more nuanced subcounty census-tract level. This study assessed the relationship between census-tract-level rurality and SMM for birthing people in California.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We used linked vital statistics and hospital discharge records for births between 1997 and 2018 in California. SMM was defined by at least 1 of 21 potentially fatal conditions and lifesaving procedures. Rural-Urban Commuting Area codes were used to characterize census tract rurality dichotomously (2-category) and at 4 levels (4-category). Covariates included sociocultural-demographic, pregnancy-related, and neighborhood-level factors. We ran a series of mixed-effects logistic regression models with tract-level clustering, reporting risk ratios and 95% confidence intervals (CIs). We used the STROBE reporting guidelines.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Findings</h3>\u0000 \u0000 <p>Of 10,091,415 births, 1.1% had SMM. Overall, 94.3% of participants resided in urban/metropolitan and 5.7% in rural tracts (3.9% micropolitan, 0.9% small town, 0.8% rural). In 2-category models, the risk of SMM was 10% higher for birthing people in rural versus urban tracts (95% CI: 6%, 13%). In 4-category models, the risk of SMM was 16% higher in micropolitan versus metropolitan tracts (95% CI: 12%, 21%).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>The observed rurality and SMM relationship was driven by living in a micropolitan versus metropolitan tract. Increased risk may result from resource access inequities within suburban areas. Our findings demonstrate the importance of considering rurality at a subcounty level to understand locality-related inequities in the risk of SMM.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2023-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138488871","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":"Differences in use of Veterans Health Administration and non-Veterans Health Administration hospitals by rural and urban Veterans after access expansions","authors":"Matthew P. Dizon MD,&nbsp;Kenneth W. Kizer MD, MPH,&nbsp;Michael K. Ong MD, PhD,&nbsp;Ciaran S. Phibbs PhD,&nbsp;Megan E. Vanneman PhD,&nbsp;Emily P. Wong MPH, MPA,&nbsp;Yue Zhang PhD,&nbsp;Jean Yoon PhD, MHS","doi":"10.1111/jrh.12812","DOIUrl":"10.1111/jrh.12812","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>To examine changes in rural and urban Veterans’ utilization of acute inpatient care in Veterans Health Administration (VHA) and non-VHA hospitals following access expansion from the Veterans Choice Act, which expanded eligibility for VHA-paid community hospitalization.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Using repeated cross-sectional data of VHA enrollees’ hospitalizations in 9 states (AZ, CA, CT, FL, LA, MA, NY, PA, and SC) between 2012 and 2017, we compared rural and urban Veterans’ probability of admission in VHA and non-VHA hospitals by payer over time for elective and nonelective hospitalizations using multinomial logistic regression to adjust for patient-level sociodemographic features. We also used generalized linear models to compare rural and urban Veterans’ travel distances to hospitals.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Findings</h3>\u0000 \u0000 <p>Over time, the probability of VHA-paid community hospitalization increased more for rural Veterans than urban Veterans. For elective inpatient care, rural Veterans’ probability of VHA-paid admission increased from 2.9% (95% CI 2.6%-3.2%) in 2012 to 6.5% (95% CI 5.8%-7.1%) in 2017. These changes were associated with a temporal trend that preceded and continued after the implementation of the Veterans Choice Act. Overall travel distances to hospitalizations were similar over time; however, the mean distance traveled decreased from 39.2 miles (95% CI 35.1-43.3) in 2012 to 32.3 miles (95% CI 30.2-34.4) in 2017 for rural Veterans receiving elective inpatient care in VHA-paid hospitals.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Despite limited access to rural hospitals, these data demonstrate an increase in rural Veterans’ use of non-VHA hospitals for acute inpatient care and a small reduction in distance traveled to elective inpatient services.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138464004","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 patient perceptions of care toward rural and urban hospitals in the United States: 2014-2019","authors":"Zhong Li PhD,&nbsp;Vivian Ho BA,&nbsp;Melinda A. Merrell PhD,&nbsp;Peiyin Hung PhD","doi":"10.1111/jrh.12813","DOIUrl":"10.1111/jrh.12813","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>Understanding rural-urban disparities in patient satisfaction is critical to identify gaps for improvement in patient-centered care and tailor interventions to specific patient needs, especially those in the Frontier and Remote areas (FAR). This study aimed to examine disparities in patient perceptions of care between urban, rural non-FAR, and FAR hospitals between 2014 and 2019.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This is a retrospective longitudinal study using 2014-2019 Hospital Consumer Assessment of Healthcare Providers and Systems data linked to American Hospital Annual Survey data (3,524 hospitals in 2014 and 3,440 hospitals in 2019). Multivariable linear regression models were used to identify differential trends in patient perceptions of care by hospital rurality over 2014-2019, adjusting hospital- and county-level characteristics.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Findings</h3>\u0000 \u0000 <p>In 2014, patients at rural non-FAR and FAR hospitals had <i>lower</i> percentages of willingness to definitely recommend these hospitals than urban hospitals (average percentage difference, 95% CI: −4.0% [−4.5%, −3.5%]; −2.0% [−2.8%, −1.2%]); yet, over the study period, rural hospitals experienced steeper increases in patient willingness to recommend (0.2% [0.07%, 0.4%]; 0.4% [0.08%, 0.7%]). FAR hospitals also showed improvements in patient experience in a clean environment, communication with nurses, communication about medicines, and responsiveness of staff. Communication with doctors showed slight decreases across hospital locations.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Patient perceptions of care were generally improved in all US hospitals from 2014 to 2019, except communications with doctors. These findings highlight the potential for enhancing patient satisfaction and experience in urban hospitals and suggest the need to improve patient willingness to recommend in rural FAR hospitals.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jrh.12813","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138464005","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":"Community engagement through social media: A promising low-cost strategy for rural recruitment?","authors":"Sarah C. Vos PhD,&nbsp;Reuben Adatorwovor PhD,&nbsp;Michelle K. Roberts MS,&nbsp;Deanna Lee Sherman MA,&nbsp;Delaney Bonds MPH,&nbsp;Madeline N. Dunfee MEd, MPH, PhD,&nbsp;Bonnie Spring PhD,&nbsp;Nancy E. Schoenberg PhD","doi":"10.1111/jrh.12809","DOIUrl":"10.1111/jrh.12809","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>For the same reasons that rural telehealth has shown promise for enhancing the provision of care in underserved environments, social media recruitment may facilitate more inclusive research engagement in rural areas. However, little research has examined social media recruitment in the rural context, and few studies have evaluated the feasibility of using a free social media page to build a network of rural community members who may be interested in a research study. Here, we describe the rationale, process, and protocols of developing and implementing a social media approach to recruit rural residents to participate in an mHealth intervention.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Informed by extensive formative research, we created a study Facebook page emphasizing community engagement in an mHealth behavioral intervention. We distributed the page to local networks and regularly posted recruitment and community messages. We collected data on the reach of the Facebook page, interaction with our messages, and initiations of our study intake survey.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Findings</h3>\u0000 \u0000 <p>Over 21 weeks, our Facebook page gained 429 followers, and Facebook users interacted with our social media messages 3,080 times. Compared to messages that described desirable study features, messages that described community involvement resulted in higher levels of online interaction. Social media and other recruitment approaches resulted in 225 people initiating our in-take survey, 9 enrolling in our pilot study, and 26 placing their names on a waiting list.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>A standalone social media page highlighting community involvement shows promise for recruiting in rural areas.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2023-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138177750","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 impact of rural general hospital closures on communities—A systematic review of the literature","authors":"Carol A. Mills PhD, MS, RN,&nbsp;Valerie A. Yeager DrPH,&nbsp;Kathleen T. Unroe MD, MHA,&nbsp;Ann Holmes PhD,&nbsp;Justin Blackburn PhD","doi":"10.1111/jrh.12810","DOIUrl":"10.1111/jrh.12810","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>To compile the literature on the effects of rural hospital closures on the community and summarize the evidence, specifically the health and economic impacts, and identify gaps for future research.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A systematic review of the relevant peer-reviewed literature, published from January 2005 through December 2021, included in the EMBASE, CINAHL, PubMed, EconLit, and Business Source Complete databases, as well as “gray” literature published during the same time period. A total of 21 articles were identified for inclusion.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Findings</h3>\u0000 \u0000 <p>Over 90% of the included studies were published in the last 8 years, with nearly three-fourths published in the last 4 years. The most common outcomes studied were economic outcomes and employment (76%), emergent, and non-emergent transportation, which includes transport miles and travel time (42.8%), access to and supply of health care providers (38%), and quality of patient outcomes (19%). Eighty-nine percent of the studies that examined economic impacts found unfavorable results, including decreased income, population, and community economic growth, and increased poverty. Between 11 and 15.7 additional minutes were required to transport patients to the nearest emergency facility after closures. A lack of consistency in measures and definition of rurality challenges comparability across studies.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The comprehensive impact of rural hospital closures on communities has not been well studied. Research shows predominantly negative economic outcomes as well as increased time and distance required to access health care services. Additional research and consistency in the outcome measures and definition of rurality is needed to characterize the downstream impact of rural hospital closures.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2023-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jrh.12810","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138177751","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":"Cross-sectional population-based estimates of a rural-urban disparity in prevalence of long COVID among Michigan adults with polymerase chain reaction-confirmed COVID-19, 2020-2022","authors":"Colleen L. MacCallum-Bridges PhD, MS,&nbsp;Jana L. Hirschtick PhD, MPH,&nbsp;Kristi L. Allgood PhD, MPH,&nbsp;Soomin Ryu PhD, MA,&nbsp;Robert C. Orellana PhD, MPH,&nbsp;Nancy L. Fleischer PhD, MPH","doi":"10.1111/jrh.12807","DOIUrl":"10.1111/jrh.12807","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>To (1) assess whether residential rurality/urbanicity was associated with the prevalence of 30- or 90-day long COVID, and (2) evaluate whether differences in long COVID risk factors might explain this potential disparity.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We used data from the Michigan COVID-19 Recovery Surveillance Study, a population-based probability sample of adults with COVID-19 (n = 4,937). We measured residential rurality/urbanicity using dichotomized Rural-Urban Commuting Area codes (metropolitan, nonmetropolitan). We considered outcomes of 30-day long COVID (illness duration ≥30 days) and 90-day long COVID (illness duration ≥90 days). Using Poisson regression, we estimated unadjusted prevalence ratios (PRs) to compare 30- and 90-day long COVID between metropolitan and nonmetropolitan respondents. Then, we adjusted our model to account for differences between groups in long COVID risk factors (age, sex, acute COVID-19 severity, vaccination status, race and ethnicity, socioeconomic status, health care access, SARS-CoV-2 variant, and pre-existing conditions). We estimated associations for the full study period (Jan 1, 2020-May 31, 2022), the pre-vaccine era (before April 5, 2021), and the vaccine era (after April 5, 2021).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Findings</h3>\u0000 \u0000 <p>Compared to metropolitan adults, the prevalence of 30-day long COVID was 15% higher (PR = 1.15 [95% CI: 1.03, 1.29]), and the prevalence of 90-day long COVID was 27% higher (PR = 1.27 [95% CI: 1.09, 1.49]) among nonmetropolitan adults. Adjusting for long COVID risk factors did not reduce disparity estimates in the pre-vaccine era but halved estimates in the vaccine era.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Our findings provide evidence of a rural-urban disparity in long COVID and suggest that the factors contributing to this disparity changed over time as the sociopolitical context of the pandemic evolved and COVID-19 vaccines were introduced.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2023-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jrh.12807","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136400099","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":"Substance use among rural adolescents with incarcerated parents: Evidence from a state-wide sample","authors":"Luke Muentner PhD, MSW,&nbsp;Katie K. McLaughlin JD,&nbsp;Rebecca Shlafer PhD, MPH","doi":"10.1111/jrh.12806","DOIUrl":"10.1111/jrh.12806","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>Incarceration rates are highest in rural communities, disproportionately exposing rural children to parental incarceration (PI). Substance use is a pressing public health issue—and a key driver of incarceration—in rural areas, yet limited research has examined PI as a social determinant of health for adolescent alcohol and drug use. This study links exposure to PI with rural adolescent substance use and examines the role of coresidence with parents in these associations.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Data come from the 2019 Minnesota Student Survey, including 18,820 rural adolescents. Respondents self-reported experiences of PI (current, former, never), whether they lived with the parent at the time of incarceration, and past-year alcohol, marijuana, cocaine, heroin, and methamphetamine use.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Findings</h3>\u0000 \u0000 <p>Over 22% of rural adolescents experienced PI. In adjusted logistic regression models, current PI was associated with greater past-year alcohol (aOR = 2.20), marijuana (aOR = 4.08), cocaine (aOR = 3.61), heroin (aOR = 4.96), and methamphetamine (aOR = 5.43) use compared to peers who never experienced PI. Current PI was also associated with greater counts of use. Associations between coresidence and substance use were largely nonsignificant.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The elevated risk for substance use in the context of rural PI and its adverse sequelae call for expanded prevention and intervention strategies that support adolescent health alongside targeted decarceration efforts in rural communities that reduce the number of families put in the potentially compromising situation of PI.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2023-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jrh.12806","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"107592698","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":"The Women Farmer Stress Inventory: Examining women farmer stress in the United States Corn Belt","authors":"Carly E. Nichols PhD,&nbsp;Jonathan Davis PhD","doi":"10.1111/jrh.12808","DOIUrl":"10.1111/jrh.12808","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>While women identifying as primary farmers have increased in the United States, there has not been research focused on the antecedents of stress and quality of life among women farmers in particular. This study set out to construct a Women Farmer Stress Inventory (WFSI), test its dimensionality, and assess its criterion-related validity by looking at its relationship with subjective wellbeing as measured by the Satisfaction with Life Scale (SWLS). We then examined sociodemographic and farm-level correlates to assess their relationship with stress.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We utilized responses from a random sample of 592 Iowan women farmers who responded to a mailout survey that included the WFSI. We conducted exploratory factor analysis to identify the factorial structure of the WFSI, and used linear regression to evaluate how sociodemographic and farm-level characteristics were related to each factor.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The analysis revealed 5 unique factors that reflected different aspects of women farmer stress: time pressures and workload, environmental concern, external stressors from governments and market, interpersonal relationships, and rural amenities. All factors except rural amenities had high levels of internal consistency (Cronbach's alpha &gt;0.80) and were validated using the external criteria of SWLS measures. Young age, being married, and engagement in off-farm work, and smaller farm size were associated with greater levels of stress across most domains.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>The WFSI is a promising tool that shows high internal consistency and is validated with life satisfaction. Our study also finds certain sociodemographic and farm characteristics associated with different stress domains, which could inform both future research and community-based interventions.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2023-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jrh.12808","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"92157146","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":"Locations of COVID-19 vaccination provision: Urban-rural differences","authors":"Grace W. Ryan PhD,&nbsp;Amanda R. Kahl MS,&nbsp;Don Callaghan BS,&nbsp;Bethany Kintigh RN,&nbsp;Natoshia M. Askelson PhD","doi":"10.1111/jrh.12811","DOIUrl":"10.1111/jrh.12811","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>Our goal was to compare locations of COVID-19 vaccine provision in urban and rural communities over the course of the pandemic.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We used the Iowa Immunization Registry Information System (IRIS) to identify the organizations providing COVID-19 vaccines (eg, pharmacies, public health departments, and medical providers). Proportions of first-dose vaccines by organization type and patient census-based statistical area were generated. We calculated Chi-square tests to assess differences among metropolitan, micropolitan, and noncore communities.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Findings</h3>\u0000 \u0000 <p>IRIS data revealed that 64% (n = 2,043,251) of Iowans received their first COVID-19 vaccine between December 14, 2020, and December 31, 2022. For metropolitan-dwelling individuals, most first doses were administered at pharmacies (53%), with similar trends observed for micropolitan (49%) and noncore (42%) individuals. The second most common location for metropolitan individuals was medical practices (17%); public health clinics and departments were the second most common provider for micropolitan (26%) and noncore (33%) individuals. These trends shifted over time. In December 2020, hospitals were the most common vaccine provider for everyone, but by December 2022, medical providers were the most common source for metropolitan individuals, and pharmacies were most common for micropolitan and noncore individuals.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Trends in the type of vaccine provider differentiated metropolitan residents from micropolitan and noncore residents. For the latter groups, local public health departments played a more significant role. Across all groups, pharmacists emerged as a critical vaccine provider. Our findings can be used to plan for seasonal vaccine campaigns as well as potential future mass vaccination campaigns.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2023-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"92157145","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}