This study investigates the significant disparities between urban and rural areas in China, particularly in terms of health status, which are driven by economic inequality and the uneven distribution of healthcare resources. Chronic diseases are a major threat to the health of Chinese residents, and this study explores how these diseases contribute to the disparity in self-rated health between urban and rural populations. Using data from the 2021 Chinese General Social Survey, various data analysis methods, including descriptive, regression, and decomposition analyses, were employed. The results reveal substantial disparities in self-rated health between urban and rural residents, with chronic diseases playing a significant role in explaining these disparities. Approximately 39% of the urban-rural disparity in self-rated health can be explained by differences in chronic disease prevalence, with additional factors such as age, socio-economic status, social participation, and sleep quality also contributing. This study identified the correlation between chronic diseases and the disparity in self-rated health, and limitations may arise from the use of self-reported health and the complexity of urban-rural health disparities. The findings suggest that the urban-rural disparity in chronic diseases is the primary driver of the health disparity, and that policymakers should focus on improving health education, promoting chronic disease prevention and management, and emphasizing preventive healthcare in rural areas.

BackgroundDelivering rehabilitation services to meet the requirements of rural inhabitants necessitates more than simply augmenting the quantity of healthcare professionals.ObjectiveThis study delved into the perspectives of rehabilitation professionals regarding the provision of rehabilitation services in rural settings, the challenges encountered, perceived facilitators and barriers to implementation, and their recommendations for delivering effective rehabilitation care.MethodsWe conducted individual semi-structured interviews with a purposefully sampled multi-disciplinary rehabilitation team in the Lucknow district of Uttar Pradesh in this qualitative study. We used interpretive description to examine transcripts inductively through broad-level coding, and consolidated the results into interpretive categories.ResultsThe study involved thirty-two rehabilitation professionals and 27 interviews. We identified three themes: the state of rural rehabilitation, which fosters the social aspects of rehabilitation through either a multi-disciplinary or trans-disciplinary model due to limitations in coverage and capacity; challenges ranging from the lack of rehabilitation guidelines to manpower shortages, as well as policy and administrative issues and ethical dilemmas; and key procedures for effective rural practice, including establishing partnerships, organizing awareness programs for public representatives and physicians, and facilitating access to continuing professional development programs. Barriers and facilitators within themes were affected by the resources and support from local community leaders, as well as the availability or lack of good communication tools with patients, carers, and multidisciplinary team members.ConclusionTo meet the rehabilitation requirements of rural environments, tailored approaches are required, including modifications to education, practice, and policy to address human resource limitations and increased investment in rehabilitation.

This study aims to explore the determinants of gross motor function in ambulatory children with spastic cerebral palsy (CP).

Sixty-eight children diagnosed with spastic CP type were included in the study. Sociodemographic and clinical information of children with CP and their families was recorded. Children's gross motor function level was classified using the Gross Motor Function Classification System; gross motor function was assessed using the Gross Motor Function Measure-66 (GMFM-66); and parental quality of life was assessed using the Paediatric Quality of Life Scale Family Effects Module (PedsQL-FIM).

No significant differences were observed in gross motor function or parental quality of life between hemiparetic and diparetic CP groups. However, children residing in urban areas showed significantly higher gross motor function and parental quality of life compared to those in rural areas (p < 0.05). Moderate correlations were found between gross motor function and physical functioning as well as place of residence (p < 0.05). Multiple regression indicated that physical functioning and urban residence were significant predictors of gross motor function, accounting for 37.9% of the variance in the GMFM-66 score.

This study shows that the quality of life of parents of children and residence in the urban area are independent predictors of gross motor function in children with CP. These findings highlight the importance of considering family well-being and environmental factors when developing interventions to improve gross motor function outcomes in children with CP.

NCT06439446.

Individuals who walk regularly are more likely to meet recommended physical activity guidelines than non-walkers; however, rural US adults walk less than urban adults. The built and social environment, perceived walkability and walking are bidirectionally related with each other.

This study's purpose was to assess the associations of physical activity-related social norms and frequency of walking in the neighborhood with perceived walkability among rural adults.

The data for this cross-sectional analysis comes from a randomized trial with 18 rural Oregon libraries. As part of baseline assessment, participants completed surveys on physical activity-related social norms, perceived walkability, frequency of walking in the neighborhood, and demographic items. We assessed bivariate correlations and ran linear regression models with perceived walkability as the outcome and social norms (social environment) and frequency of walking in the neighborhood (built environment experience) as predictors with covariates of age, gender and income.

Adult residents of 18 rural communities in Oregon.

Of the 313 participants who completed the survey, 60% were 65 and older, 92% white and 86% women; 17% reported walking in the neighborhood less than once a month and 5% reported walking 5 or more days/week. We found positive correlations between perceived walkability and frequency of walking in the neighborhood (r = .23, p < .01), and social norms (r = .47, p < .01). The linear regression model explained 28% of the variance in perceived walkability (adj r-squared = 0.26). Social norms (unstandardized coefficient = 0.37, 95% CI: 0.28,0.46) and frequency of walking in the neighborhood, (unstandardized coefficient = 0.06, 95% CI: 0.02, 0.10) were positively associated with perceived walkability.

Among a group of rural adults social norms had a greater influence on perceived walkability than frequency of walking in the neighborhood. Intervening in the social environment could impact perceived walkability and ultimately walking among rural adults.

As the population ages, the health of rural older adults is of increasing concern to society. Pain, decreased activity of daily living, depression, and sleep are important factors affecting the quality of life of older adults. This study aimed to explore the complex relationship between pain, activity of daily living, depression, and sleep in rural older adults, with the goal of providing new perspectives and intervention strategies to improve sleep quality.

This study was based on the data from the 2020 China Health and Retirement Longitudinal Study, and rural older adults aged 60 years and above were selected as the study subjects, with a final sample size of 5,352. Stata 18.0 and SPSS 27.0 software were used for statistical analysis, and t-tests, analysis of variance (ANOVA), and Pearson correlation analyses were used for one-way analyses, and PROCESS 4.2 was used for mediation effect analysis and testing.

Pain in older adults was negatively correlated with sleep duration (r = -0.212) and positively correlated (p < 0.001) with impairment to activity of daily living (r = 0.339) and depression (r = 0.355). The mediation test reported that pain in older adults had a direct effect on sleep duration (95% CI: -0.076 to -0.043), with activity of daily living (95% CI: -0.014 to -0.004) and depression (95% CI: -0.026 to -0.017) acting as chained mediators between the two.

This study reveals the interrelationships between pain, activity of daily living, depression and sleep in rural older adults. It is recommended that medical resources be strengthened, health awareness be increased, community care services be improved, recreational activities be provided, and family emotional support be encouraged to improve the health and quality of life of older adults.

Atrial fibrillation (AF) is the most common sustained arrhythmia and associated with increased morbidity and mortality. Differences have been identified between medical care delivered in urban and rural settings, and rurality-based disparities may exist in AF care. We performed a systematic review investigating the effect of rurality on AF care and outcomes in the United States. PubMed was queried for entries on AF and rurality: ("atrial fibrillation" OR "atrial flutter") AND ("rural" OR "urban" OR "rurality" OR "metro" OR "metropolitan") AND ("united states" OR "US" OR "U.S.") published up to September 24, 2023. Anticoagulation, rhythm control, settings of care, outcomes, and all-cause mortality were reviewed in relevant studies. The search identified 395 total articles. After screening, 14 relevant articles were included in the review. These studies ranged from 1993 to 2020 and analyzed approximately 41.7 million AF patient encounters. The use of catheter ablation for AF per electrophysiologist was similar across the rural-urban spectrum. Patients with AF and rural residence were less likely to receive a direct oral anticoagulant and more likely to remain on warfarin (relative risk, 0.90 [95% CI, 0.88-0.92]). Patients in rural communities were less likely to receive non-emergent AF care (odds ratio [OR], 0.96 [95% CI, 0.93-0.98]). In-hospital mortality for patients with AF admitted to rural hospitals was higher than urban hospitals (OR, 1.19 [95% CI, 1.01-1.39)]. Measurable differences exist in both treatments and outcomes of patients with AF between rural and urban settings in the United States. These differences should inform future investigations and strategies to improve health in people with AF.

To improve understanding of influenza and rurality, we investigated differences in influenza testing and anti-viral treatment rates between micropolitan (muSAs) and metropolitan statistical areas (MSAs) using national medical claims data over multiple influenza seasons.

Using billing data from the Centers for Medicare and Medicaid Services for those aged 65 years and older, we estimated weekly rates of ordered rapid influenza diagnostic tests (RIDT) and antivirals (AV) among Medicare enrollees by core-based statistical areas (CBSAs) during 2010-2016. We used Negative Binomial generalized mixed models to estimate adjusted rate ratios (aRR) between MSAs and muSAs, adjusting for clustering by CBSA plus explanatory variables. We ran models for all weeks and only high influenza activity weeks.

For all weeks, the unadjusted rate of RIDTs was 1.97 per 10,000 people in MSAs compared with 2.69 in muSAs (Rate ratio (RR) = 0.73, 95% Confidence Interval (CI): 0.73-0.74) and of AVs was 1.85 in MSAs compared with 1.40 in muSAs (RR = 1.32, CI: 1.31-1.32). From the multivariate model, aRR for RIDTs was 0.82 (0.73-0.94) and for AVs was 1.12 (1.04-1.22) in MSAs versus muSAs. For high influenza activity weeks, aRR for RIDTs was 0.82 (0.73-0.92) and for AVs was 1.15 (1.06-1.24). All models found influenza testing rates higher in muSAs and treatment rates higher in MSAs.

Our study found lower testing and higher treatment in U.S. metropolitan versus micropolitan areas from 2010 to 2016 for those aged 65 years and older in our population. Identifying differences in influenza rates by rurality may improve public health response. Further research into the relationship of rurality and health disparities is needed.

Place matters for health. In Texas, growing rural populations face a variety of structural, social, and economic disparities that position them for potentially worse health outcomes. The current study contributes to understanding rural health disparities in a state-specific context.

Using 2023 County Health Rankings data from the University of Wisconsin Population Health Institute, the study analyzes rural/non-rural county differences in Texas across six composite indexed domains of health outcomes (length of life, quality of life) and health factors (health behavior, clinical care, socioeconomic factors, physical environment) with a chi-square test of significance and logistic regression.

Quartile ranking distributions of the six domains differed between rural and non-rural counties. Rural Texas counties were significantly more likely to fall into the bottom quartile(s) in the domains of length of life and clinical care and less likely to fall into the bottom quartile(s) in the domains of quality of life and physical environment. No differences were found in the domains of health behavior and socioeconomic factors. Findings regarding disparities in length of life and clinical care align with other studies examining disease prevalence and the unavailability of many health services in rural Texas. The lack of significant differences in other domains may relate to indicators that are not present in the dataset, given studies that find disparities relating to other underlying factors.

Texas County Health Rankings data show differences in health outcomes and factors between rural and non-rural counties. Limitations of findings relate to the study's cross-sectional design and parameters of the secondary data source. Ultimately, results can help state health stakeholders, especially those in community or operational contexts with limited resources or access to more detailed health statistics, to use the CHR dataset to consider more relevant local interventions to address rural health disparities.

Cigarette smoking prevalence is higher for rural than urban adults, yet digital access to cessation programming is reduced. We aim to investigate digital access interventions to promote engagement with an online evidence-based cessation treatment (EBCT) program among rural adults.

This pilot trial used a pragmatic, three-arm, randomized, parallel-group design (ClinicalTrials.gov: NCT05209451). Inclusion criteria included being aged ≥18, Mayo Clinic Midwest patient, rural residency, and currently smokes cigarettes. All participants received an online, 12-week EBCT program and were randomized to receive one of three digital access interventions: print materials (control, n = 30); print materials + loaner iPad device with data plan coverage (n = 30); or print materials + loaner device + up to six, 15-20-minute motivational interviewing-based coaching calls to support technology needs (n = 30). A composite score of trial engagement (primary outcome) and self-reported smoking abstinence and use of EBCT resources (secondary outcomes) were assessed online at 4 and 12 weeks. Qualitative interviews were used to assess patient experience. Neither participants nor outcome assessors were blinded to group assignment.

Results are reported for all 30 participants in each group. The average age of participants is 51.0 years and 61% are women. We show no significant arm differences for the trial engagement composite score (p = 0.30). We also find coaching support is significantly (p < 0.05) associated with enhanced smoking-related treatment response, including cigarette abstinence and use of EBCT resources, and participants reported positive experiences with the intervention.

The coaching intervention to support technology needs is acceptable and shows preliminary evidence of its efficacy in smoking-related treatment response. Further studies could refine and implement the coaching intervention for trial engagement and long-term cessation.

Due to substantial regional variability in available caregiving services and supports, culture and health status among informal caregivers in the USA, the study objective was to explore how rural-urban differences in aspects of caregiving-caregiving intensity, distance to care recipient, caregiver burden, caregiver health and caregiving support-vary by US Census region (Northeast, South, Midwest and West) after accounting for other social determinants of health.

This study was a secondary analysis of multiwave, cross-sectional study data.

The data were collected on a representative sample of informal, unpaid caregivers to older adults.

A sample of n=3551 informal caregivers from the National Study of Caregiving identified by older adult care recipients from waves 1 (2011) and 5 (2015) of the National Health and Aging Trends Study.

Primary outcome measures were caregiving intensity (provided support for/with the number of activities of daily living (ADLs) and instrumental ADL (IADLs)) caregiver assisted with, hours of caregiving per month), caregiver burden (physical, emotional and financial), support services sought (types and total number), caregivers' self-reported health and health status (individual comorbidities and a total number of comorbidities). Analyses were stratified by US Census region and rural-urban status, as defined by the US Census Bureau, of census tract of caregiver residence.

Urban caregivers provided higher levels of ADL support in the Northeast (beta=0.19, 95% CI 0.03, 0.35) and West (beta=0.15, 95% CI 0.05,0.26) regions. Urban caregivers provided significantly higher levels of ADL support (p=0.020), IADL support (p=0.033) and total ADLs plus IADLs (p=0.013) than rural caregivers. Caregivers living in the South had higher amounts of monthly hours spent caregiving, ADL support, IADL support and combined ADLs plus IADLs and were more likely to have obesity, report poor or fair health, have heart conditions and experience emotional difficulty from caregiving (all p<0.001).

Study findings underscore caregiving's multifaceted and complex nature and identify important urban-rural and regional differences in caregiving in the USA. Healthcare providers and healthcare organisations can have an important role in identifying and mitigating the negative impacts of caregiving on caregivers' overall health. Interventions and support should be tailored to caregivers' demographic backgrounds, addressing regional differences.

Although there is a need for evidence-based physical activity programs in rural communities, evaluating such programs is often challenging due to access-related barriers and measurement tools that are not designed for rural contexts. This study aimed to explore and better understand the day-to-day experiences of rural-dwelling children using wrist-worn PA trackers as part of a study to develop a health promotion program.

Ten caregivers and child dyads were enrolled (n = 20). The children wore accelerometers pre- and post-intervention. Semi-structured interviews were completed post-intervention and were audio recorded, transcribed, and summary reports were generated based on recurring themes.

The children had a mean age of 8.7 (SD = 1.4) years and the majority were male (80%). The caregivers were female, white, and had a mean age of 43.6 (SD = 8.5) years, with an annual income of ≥USD 40,000. Factors contributing to device wear times included low caregiver burden, device functioning as a watch, and device interactivity. The children reported that the devices were acceptable, but may have changed their physical activity behaviors, with children regularly checking their step count. The caregivers preferred devices that monitored the children's activity levels without sharing location data.

Identifying acceptable and feasible strategies to measure physical activity is vital to developing effective health promotion efforts. The lessons learned may help develop evaluation plans for implementing rural physical activity programming.

The scarcity of resources and available caregiving services in rural areas in the United States has been well documented. However, less research has compared unmet service needs between caregivers of people with Alzheimer's disease and related dementias (ADRD) in rural versus urban areas.

Using semistructured interviews guided by theories of health service use and dependent care, we interviewed 20 family caregivers residing in rural areas of Western North Carolina and 18 caregivers within the urban setting of Houston, Texas, and compared their unmet service needs and contextual factors that facilitate their service use.

Thematic analyses revealed similar unmet service needs among rural and urban caregivers; however, the ways they approached and solved their challenges differed. Caregivers in rural areas wished for more information and caregiver support whereas urban caregivers looked for information they needed until they found the answers. Rural caregivers expressed guilt about using services because they felt they were limited and zero-sum whereas urban caregivers shared available resources so that other caregivers could use them as well. Unmet service needs for urban caregivers included more racially and ethnically specific services for people with ADRD in their ethnic-specific languages and foods while rural caregivers' cultural needs were not racially and ethnically specific but for more place-specific services.

Recommendations for rural caregivers included utilizing online and virtual opportunities and expanding their reach across the United States. For urban caregivers, increasing culturally tailored service options would likely increase access and use.

Patient experience and satisfaction are the keystones in evaluating the effectiveness of clinical care in musculoskeletal medicine. Although all orthopedic settings work on the same principles of providing safe and quality health care, community hospitals represent a unique environment. There may be key differences with regard to patient experience between these settings. Accessibility to care, choices of provider, personalized care, availability of and access to resources, cultural and social variances, and waiting times are a few of the many elements that may impact patient experience and satisfaction. This narrative review aims to explore the core differences in these settings and how they can reflect on patient experience and satisfaction.

Emerging adults (EAs; age 18-30 years) with type 1 diabetes (T1D) have more challenges with diabetes management and glycemic control than other age groups. Living in a rural community introduces additional unique diabetes care challenges due to limited access to specialty care and ancillary support services. Yet, few interventions have been developed to improve diabetes management in rural-dwelling EAs with T1D.

This study aimed to understand the diabetes management experiences of older adolescents and EAs (age 16-25 years) with T1D living in a rural area and to assess their perceptions of the acceptability of 4 fully automated mobile health (mHealth) interventions to support diabetes management.

EAs were identified by clinical staff through convenience sampling. In total, 8 EAs participated in 1 focus group and 1 EA completed an individual interview; all data were collected over Zoom. Facilitators explored EAs' experiences living in a rural community with T1D and discussed EAs' impressions of, feedback on, and recommendations for improving 4 mHealth interventions to meet the specific needs of EAs with T1D living in rural communities. Discussions were transcribed and analyzed using conventional content analysis.

In total, 9 EAs (aged 18.8, SD 2.7 years; 5, 56% men; 8, 89% White) with a duration of diabetes of 8.6 (SD 4.3) years participated. They described experiences with diabetes stigma (attributing diabetes to poor lifestyle choices) and feelings of self-consciousness (hyperawareness) in their rural communities. They attributed these experiences to the small size of their communities ("everyone knows") and community members' lack of knowledge about diabetes (unable to differentiate between type 1 and type 2 diabetes). In contrast, EAs reported high levels of social support for diabetes and diabetes care from family, friends, and other community members, but low support for medical needs. The location of their diabetes care providers and the limited accessibility of diabetes-specific and general medical care services in their local community created a challenging medical care context. Overall, EAs found mHealth interventions appealing due to their digital delivery and highlighted features that increased accessibility (voiceovers and simple, jargon-free language), individualization (ability to tailor intervention content and delivery), and applicability to their own lives and other EAs with T1D (relatability of vignettes and other content). EAs suggestions for improving the interventions included more opportunities to tailor the interventions to their preferences (greater frequency and duration, ability to adapt content to emerging needs), increasing opportunities for peer support within the interventions (friend and significant other as identified support person, connecting with peers beyond their local community), and making the tone of intervention components more casual and engaging.

mHealth interventions aligned with EAs' needs and preferences are a promising strategy to support EAs in communities where social support and resources might be limited.

N/A, not a clinical trial.

Racialized economic segregation, a key metric that simultaneously accounts for spatial, social and income polarization in communities, has been linked to adverse health outcomes, including morbidity and mortality. Due to the spatial nature of this metric, the association between health outcomes and racialized economic segregation could also change with space. Most studies assessing the relationship between racialized economic segregation and health outcomes have always treated racialized economic segregation as a fixed effect and ignored the spatial nature of it. This paper proposes a two-stage Bayesian statistical framework that provides a broad, flexible approach to studying the spatially varying association between premature mortality and racialized economic segregation while accounting for neighborhood-level latent health factors across US counties. The two-stage framework reduces the dimensionality of spatially correlated data and highlights the importance of accounting for spatial autocorrelation in racialized economic segregation measures, in health equity focused settings.

The study aimed to determine the feasibility of remotely delivered exercise (tele-exercise) for older, rural cancer survivors and to explore the effects of tele-exercise on physical function, physical activity, and patient-reported outcomes.

Participants were rural cancer survivors age ≥ 60 years (79% female; mean age 70.4 ± 5.7) randomly assigned to the remotely delivered EnhanceFitness (tele-EF) exercise program, inclusive of aerobic, strength, and balance training and led by American Council on Exercise certified instructors for 1 h, 3 days/week for 16 weeks (n = 20) or to a waitlist control group (n = 19). We assessed feasibility, physical function, accelerometer-measured physical activity, and patient-reported outcomes at baseline and post intervention.

Among those screened as eligible, 44 (64%) consented to participate with 39 randomized after completing baseline measures. Attrition was equivalent between groups (n = 1, each) with 95% completing the study. The median class attendance rate was 86.9% (interquartile range: 79-94%). Compared to controls, tele-EF participants had statistically significant improvement in the five-time sit-to-stand test (- 3.4 vs. - 1.1 s, p = 0.03, effect size = 0.44), mean daily light physical activity (+ 38.5 vs 0.5 min, p = 0.03, effect size = 0.72) and step counts (+ 1977 vs. 33, p = 0.01, effect size = 0.96). There were no changes in self-efficacy for exercise, fatigue, or sleep disturbance between groups.

Findings indicate that tele-EF is feasible in older, rural cancer survivors and results in positive changes in physical function and physical activity.

Tele-EF addresses common barriers to exercise for older, rural cancer survivors, including limited accessible opportunities for professional instruction and supervision.

Gender gaps in physical activity (PA) exist with women being less active than men. Multiple cultural and psychosocial factors influence women's ability to successfully negotiate barriers to PA and other health promoting behaviors. The goal of this exploratory descriptive study was to better understand the daily experiences of mothers in making health promoting decisions for themselves and their families. Semi-structured interviews (N = 17) were conducted with rural dwelling mothers who were the primary caregivers of children in the home. Participants were asked to share their experiences with PA and other health behaviors, focusing on their motivators, barriers, and facilitators. Interviews were audio-recorded, transcribed verbatim, and analyzed using thematic content analysis. Emerging themes focused on 1) feeling internal and external pressures to prioritize family's needs over one's health, 2) family exerting both positive and negative influences on health choices, and 3) living in a rural community often resulting in a lack of opportunities to engage in physical activity and feelings of being isolated from social networks. To close the gender gap in PA, interventions should support mothers in navigating their multiple roles and competing demands while engaging in health promoting behaviors such as physical activity.

Primary care health professional shortage areas (HPSAs) lack sufficient primary care providers to meet their health care needs, which contributes to worse health outcomes within underserved populations. Community pharmacies are commonly located in HPSAs and provide nondispensing services that can help address unmet health care needs. However, there is limited data on the nature, scope, and reimbursement for community pharmacy services.

Using survey data from the state of Wisconsin, this study compares the prevalence of and reimbursement for services provided by community pharmacies in primary care HPSAs and non-HPSAs and describes barriers to pharmacy service implementation.

A survey tool on pharmacy services, reimbursement, and barriers to service implementation was developed, pilot tested, and administered to every community pharmacy in Wisconsin. Data were collected via mail and online over two waves of survey administration from November 2021 to May 2022. Pearson's chi-squared and t tests were used to compare the prevalence of and reimbursement for services between HPSA and non-HPSA pharmacies. Content analysis was used to identify themes that described barriers to pharmacy service implementation.

Responses were received from 287 of 774 eligible community pharmacies (37.1%). HPSA pharmacies were significantly more likely to be in rural areas. Regardless of pharmacy location, community pharmacies reported commonly providing a variety of services, but reimbursement for these services was considerably less frequent. The prevalence of reimbursement was <50% for two-thirds of services. Pharmacy staffing, time, and financial issues were the most commonly reported barriers to service implementation.

Community pharmacies provide a diverse set of services to meet the health care needs of their patients, but often do so with inadequate staffing or reimbursement. Action is needed to support community pharmacies in meeting the health care needs of their communities and to ensure patient access to medications and pharmacy services.

Health and health care access in the United States are plagued by high inequality. While machine learning (ML) is increasingly used in clinical settings to inform health care delivery decisions and predict health care utilization, using ML as a research tool to understand health care disparities in the United States and how these are connected to health outcomes, access to health care, and health system organization is less common. We utilized over 650 variables from 24 different databases aggregated by the Agency for Healthcare Research and Quality in their Social Determinants of Health (SDOH) database. We used k-means-a non-hierarchical ML clustering method-to cluster county-level data. Principal factor analysis created county-level index values for each SDOH domain and 2 health care domains: health care infrastructure and health care access. Logistic regression classification was used to identify the primary drivers of cluster classification. The most efficient cluster classification consists of 3 distinct clusters in the United States; the cluster having the highest life expectancy comprised only 10% of counties. The most efficient ML clusters do not identify the clusters with the widest health care disparities. ML clustering, using county-level data, shows that health care infrastructure and access are the primary drivers of cluster composition.

Cardiovascular disease (CVD) is a leading cause of morbidity and mortality worldwide, the global burden of which is rising. It is still unclear the extent to which prediabetes contributes to the risk of CVD in various age brackets among adults. To develop a focused screening plan and treatment for Chinese adults with prediabetes, it is crucial to identify variations in the connection between prediabetes and the risk of CVD based on age.

To examine the clinical features of prediabetes and identify risk factors for CVD in different age groups in China.

The cross-sectional study involved a total of 46239 participants from June 2007 through May 2008. A thorough evaluation was conducted. Individuals with prediabetes were categorized into two groups based on age. Chinese atherosclerotic CVD risk prediction model was employed to evaluate the risk of developing CVD over 10 years. Random forest was established in both age groups. SHapley Additive exPlanation method prioritized the importance of features from the perspective of assessment contribution.

In total, 6948 people were diagnosed with prediabetes in this study. In pre-diabetes, prevalences of CVD were 5 (0.29%) in the younger group and 148 (2.85%) in the older group. Overall, 11.11% of the younger group and 29.59% of the older group were intermediate/high-risk of CVD for prediabetes without CVD based on the Prediction for ASCVD Risk in China equation in ten years. In the younger age group, the 10-year risk of CVD was found to be more closely linked to family history of CVD rather than lifestyle, whereas in the older age group, resident status was more closely linked.

The susceptibility to CVD is age-specific in newly diagnosed prediabetes. It is necessary to develop targeted approaches for the prevention and management of CVD in adults across various age brackets.

To evaluate differences in emergency department (ED) utilization and quality of care for migraine in patients with rural and nonrural residences.

Migraine is a significant problem in the United States with direct health-care utilization cost amounting to US $4.2 billion annually. A considerable portion of this cost is attributed to more than 4 million annual ED visits for migraine and headache. Previous research has documented health disparities among rural populations in other disease states, which can be influenced by factors such as socioeconomic status and health-care access. Given these associations, it was hypothesized that patients with rural residence in a national sample would have increased ED utilization for migraine compared to patients with nonrural residence.

This was a cross-sectional epidemiologic study to evaluate rural disparities in ED utilization and quality of care for migraine in the United States in 2019. ED encounter data were collected from the Healthcare Cost and Utilization Project (HCUP) Nationwide Emergency Department Sample (NEDS) and Kentucky State Emergency Department Database (KY-SEDD). The primary outcome was crude and age-adjusted rates of ED encounters for migraine per 10,000 population. ED encounters were included if they had a primary International Classification of Diseases, Tenth Revision, Clinical Modification diagnosis code of G43.xx. ED encounters lacking sufficient data to classify into a geographic group were excluded. Secondary outcomes examined differences in quality of care, including mean ED charges and the proportion of encounters with medication administration, imaging, and nerve block service codes between groups.

One hundred eighty-three thousand two hundred eleven national ED discharges were classified as rural patient encounters and 627,176 were classified as nonrural. The rural group had significantly higher crude and age-adjusted rates of ED utilization for migraine (crude: rural 39.8, 95% confidence interval [CI] 36.9-42.7; nonrural 22.2, 95% CI 21-23.5 and age-adjusted: rural 41.8, 95% CI 38.8-44.8; nonrural 23.4, 95% CI 22.1-24.7). Opioid utilization was higher in rural encounters (rural n = 26,764, 14.6%; nonrural n = 50,367, 8%; p < 0.001). A Kentucky sub-analysis found 5210 ED discharges were classified as Appalachian and 12,551 as non-Appalachian. The Appalachian group had significantly higher ED utilization rates for migraine compared to the non-Appalachian and national rural groups (crude: Appalachian 44.9, 95% CI 43.7-46.2; age-adjusted: Appalachian 47.4, 95% CI 46.1-48.8). The Kentucky Appalachian group also demonstrated significantly higher opioid analgesia use compared to the national rural group (Appalachian n = 1031, 19.8%; p < 0.001).

This study suggests rural populations, particularly in Appalachia, may experience significantly higher ED utilization for migraine compared to nonrural patients. Moreover, rural populations were more likely to receive suboptimal migraine management with opioid analgesia. Multimodal health-care interventions should be developed to improve access to outpatient migraine care and further investigate potential risk factors in the rural population. With high ED utilization, the Appalachian population may benefit most from such an intervention.

While rural-urban disparities in health and health outcomes have been demonstrated, because of their impact on (and intervenability to improve) health and health outcomes, we sought to examine cross-sectional and longitudinal inequities in health, clinical care, health behaviors, and social determinants of health (SDOH) between rural and non-rural counties in the pre-pandemic era (2015 to 2019), and to present a Health Equity Dashboard that can be used by policymakers and researchers to facilitate examining such disparities. Therefore, using data obtained from 2015-2022 County Health Rankings datasets, we used analysis of variance to examine differences in 33 county level attributes between rural and non-rural counties, calculated the change in values for each measure between 2015 and 2019, determined whether rural-urban disparities had widened, and used those data to create a Health Equity Dashboard that displays county-level individual measures or compilations of them. We followed STROBE guidelines in writing the manuscript. We found that rural counties overwhelmingly had worse measures of SDOH at the county level. With few exceptions, the measures we examined were getting worse between 2015 and 2019 in all counties, relatively more so in rural counties, resulting in the widening of rural-urban disparities in these measures. When rural-urban gaps narrowed, it tended to be in measures wherein rural counties were outperforming urban ones in the earlier period. In conclusion, our findings highlight the need for policymakers to prioritize rural settings for interventions designed to improve health outcomes, likely through improving health behaviors, clinical care, social and environmental factors, and physical environment attributes. Visualization tools can help guide policymakers and researchers with grounded information, communicate necessary data to engage relevant stakeholders, and track SDOH changes and health outcomes over time.

The effects of the COVID-19 pandemic have been more pronounced for socially disadvantaged populations. We sought to determine how access to SARS-CoV-2 testing and the likelihood of testing positive for COVID-19 were associated with demographic factors, socioeconomic status (SES) and social determinants of health (SDH) in three Canadian provinces.

An observational population-based cross-sectional study was conducted for the provinces of Ontario, Manitoba and New Brunswick between March 1, 2020 and April 27, 2021, using provincial health administrative data. After excluding residents of long-term care homes, those without current provincial health insurance and those who were tested for COVID-19 out of province, records from provincial healthcare administrative databases were reviewed for 16,900,661 healthcare users. Data was modelled separately for each province in accordance to a prespecified protocol and follow-up consultations among provincial statisticians and collaborators. We employed univariate and multivariate regression models to examine determinants of testing and test results.

After adjustment for other variables, female sex and urban residency were positively associated with testing, while female sex was negatively associated with test positivity. In New Brunswick and Ontario, individuals living in higher income areas were more likely to be tested, whereas in Manitoba higher income was negatively associated with both testing and positivity. High ethnocultural composition was associated with lower testing rates. Both high ethnocultural composition and high situational vulnerability increased the odds of testing positive for SARS-CoV-2.

We observed that multiple demographic, income and SDH factors were associated with SARS-CoV-2 testing and test positivity. Barriers to healthcare access identified in this study specifically relate to COVID-19 testing but may reflect broader inequities for certain at-risk groups.

Using the 2021 Occupational Employment and Wage Statistics (OEWS) dataset, we calculate the ratio of direct care workers relative to the population of older adults (ages 65+) across rural and urban areas in the US. We find that there are, on average, 32.9 home health aides per 1000 older adults (age 65+) in rural areas and 50.4 home health aides per 1000 older adults in urban areas. There are, on average, 20.9 nursing assistants per 1000 older adults in rural areas and 25.3 nursing assistants per 1000 older adults in urban areas. There is substantial regional variation. Greater investment needs to be made in improving wages and job quality for direct care workers to attract workers to these critical occupations, especially in rural areas where the need for direct care is greater.

Human exposure to greenness is associated with COVID-19 prevalence and severity, but most relevant research has focused on the relationships between greenness and COVID-19 infection rates. In contrast, relatively little is known about the associations between greenness and COVID-19 hospitalizations and deaths, which are important for risk assessment, resource allocation, and intervention strategies. Moreover, it is unclear whether greenness could help reduce health inequities by offering more benefits to disadvantaged populations. Here, we estimated the associations between availability of greenness (expressed as population-density-weighted normalized difference vegetation index) and COVID-19 outcomes across the urban-rural continuum gradient in the United States using generalized additive models with a negative binomial distribution. We aggregated individual COVID-19 records at the county level, which includes 3,040 counties for COVID-19 case infection rates, 1,397 counties for case hospitalization rates, and 1,305 counties for case fatality rates. Our area-level ecological study suggests that although availability of greenness shows null relationships with COVID-19 case hospitalization and fatality rates, COVID-19 infection rate is statistically significant and negatively associated with more greenness availability. When performing stratified analyses by different sociodemographic groups, availability of greenness shows stronger negative associations for men than for women, and for adults than for the elderly. This indicates that greenness might have greater health benefits for the former than the latter, and thus has limited effects for ameliorating COVID-19 related inequity. The revealed greenness-COVID-19 links across different space, time and sociodemographic groups provide working hypotheses for the targeted design of nature-based interventions and greening policies to benefit human well-being and reduce health inequity. This has important implications for the post-pandemic recovery and future public health crises.

Return to school is key for community re-integration after a traumatic brain injury (TBI). School support facilitates and ensure a successful transition back to school. However, access to school services is not uniform among U.S. children.

To describe school services for children with TBI from minoritized backgrounds and highlight population-specific risk factors and facilitators for accessing services.

Narrative review of the literature including studies on return to school after a mild-complicated, moderate, or severe TBI, among children enrolled in the U.S. school system. We describe receipt of services, enabling and risk factors, and outcomes, for minority children.

There is a gap in knowledge regarding return to school among minoritized children with TBIs. Studies have few participants from racial and ethnic minority backgrounds, or low income or rural communities. Transgender and non-binary youth are not represented in present research efforts. Studies highlight larger barriers to receipt of school services among minority children and additional barriers associated with their minority status.

Diversity in the U.S pediatric population is increasing. Minoritized populations are at increased risk for TBI and poor outcomes. Research focused on the needs of these populations is required to optimize school return after TBI hospitalization and overall post-discharge care.

Perinatal health outcomes are influenced by a variety of socioeconomic, behavioral, and economic factors that reduce access to health services. Despite these observations, rural communities continue to face barriers, including a lack of resources and the fragmentation of health services.

To evaluate patterns in health outcomes, health behaviors, socioeconomic vulnerability, and sociodemographic characteristics across rural and nonrural counties within a single health system catchment area.

Socioeconomic vulnerability metrics, health care access as determined by licensed provider metrics, and behavioral data were obtained from FlHealthCHARTS.gov and the County Health Rankings. County-level birth and health data were obtained from the Florida Department of Health. The University of Florida Health Perinatal Catchment Area (UFHPCA) was defined as all Florida counties where ≥5% of all infants were delivered at Shands Hospital between June 2011 and April 2017.

The UFHPCA included 3 nonrural and 10 rural counties that represented more than 64,000 deliveries. Nearly 1 in 3 infants resided in a rural county, and 7 out of 13 counties did not have a licensed obstetrician gynecologist. Maternal smoking rates (range 6.8%-24.8%) were above the statewide rate (6.2%). Except for Alachua County, breastfeeding initiation rates (range 54.9%-81.4%) and access to household computing devices (range 72.8%-86.4%) were below the statewide rate (82.9% and 87.9%, respectively). Finally, we found that childhood poverty rates (range 16.3%-36.9%) were above the statewide rate (18.5%). Furthermore, risk ratios suggested negative health outcomes for residents of counties within the UFHPCA for each measure, except for infant mortality and maternal deaths, which lacked sample sizes to adequately test.

The health burden of the UFHPCA is characterized by rural counties with increased maternal death, neonatal death, and preterm birth, as well as adverse health behaviors that included increased smoking during pregnancy and lower levels of breastfeeding relative to nonrural counties. Understanding perinatal health outcomes across a single health system has potential to not only estimate community needs but also facilitate planning of health care initiatives and interventions in rural and low-resource communities.

The purpose of this scoping literature review was to understand what is known about how the rural profile influences beliefs regarding telehealth utilization. Rural nursing theory (RNT) provided a framework for the review. Search criteria were limited to peer-reviewed studies conducted in Europe, the United States, Canada, Australia, and New Zealand. A variety of search terms related to patient telehealth perceptions generated 213 unique articles, of which 10 met the inclusion criteria. Included studies incorporated qualitative methodologies and were from Australia, Canada, Sweden, or the United States. The review highlighted four themes related to the rural profile's influence on telehealth beliefs: importance of familiar relationships, concerns with privacy and confidentiality, acceptance of limited access to care, and resourcefulness and frugality. These themes echo concepts within RNT. Nurses and other health professionals must acknowledge the rural profile's influence on a person's decision to use telehealth in order to provide optimal care.

To further promote the effective governance of rural human settlements in China, it is necessary to summarize and organize the research on rural human settlements that has been undertaken in the last decade. This paper analyzes the current status of rural human settlements research from the perspectives of Chinese literature and English literature. It takes the core documents included in WOS (Web of Science) and CNKI (Chinese National Knowledge Infrastructure) as samples, and produces a visual analysis of the authors, institutions, disciplines, and research hotspots for rural human settlements research with the help of CiteSpace V and other measurement software, focus on identifying the similarities and differences between CNKI and WOS in the study of rural human settlements. The results show that the number of papers is increasing; cooperation between Chinese researchers and institutions needs to be further strengthened; the existing research has achieved interdisciplinary integration; the research hotspots are converging, but China pays more attention to the study of the hard environment, such as the macro level of rural human settlements and the natural ecological environments of residence, and lacks insight into the soft environment, such as the main body of residences, social relations, and individual needs in the urban fringe. This study is conducive to promoting the integrated development of urban and rural areas in China, promoting the revitalization and development of rural areas in China, and achieving social equity.

This study aimed to analyze the effect of sociodemographic characteristics on COVID-19 in-hospital mortality in Ecuador from March 1 to December 31, 2020. This retrospective longitudinal study was performed with data from publicly accessible registries of the Ecuadorian National Institute of Statistics and Censuses (INEC). Data underwent a competing risk analysis with estimates of the cumulative incidence function (CIF). The effect of covariates on CIFs was estimated using the Fine-Gray model and results were expressed as adjusted subdistribution hazard ratios (SHR). The analysis included 30,991 confirmed COVID-19 patients with a mean age of 56.57±18.53 years; 60.7% (n = 18,816) were men and 39.3% (n = 12,175) were women. Being of advanced age, especially older than or equal to 75 years (SHR = 17.97; 95%CI: 13.08-24.69), being a man (SHR = 1.29; 95%CI: 1.22-1.36), living in rural areas (SHR = 1.18; 95%CI: 1.10-1.26), and receiving care in a public health center (SHR = 1.64; 95%CI: 1.51-1.78) were factors that increased the incidence of death from COVID-19, while living at an elevation higher than 2,500 meters above sea level (SHR = 0.69; 95%CI: 0.66-0.73) decreased this incidence. Since the incidence of death for individuals living in rural areas and who received medical care from the public sector was higher, income and poverty are important factors in the final outcome of this disease.

Women who use drugs (WWUD) have low rates of contraceptive use and high rates of unintended pregnancy. Drug use is common among women in rural U.S. communities, with limited data on how they utilize reproductive, substance use disorder (SUD), and healthcare services.

We determined contraceptive use prevalence among WWUD in rural communities then compared estimates to women from similar rural areas. We investigated characteristics of those using contraceptives, and associations between contraceptive use and SUD treatment, healthcare utilization, and substance use.

Rural Opioids Initiative (ROI) - cross-sectional survey using respondent-driven sampling (RDS) involving eight rural U.S. regions (January 2018-March 2020); National Survey on Family Growth (NSFG) - nationally-representative U.S. household reproductive health survey (2017-2019).

Women aged 18-49 with prior 30-day non-prescribed opioid and/or non-opioid injection drug use; fecundity determined by self-reported survey responses.

Unweighted and RDS-weighted prevalence estimates of medical/procedural contraceptive use; chi-squared tests and multi-level linear regressions to test associations.

Of 855 women in the ROI, 36.8% (95% CI 33.7-40.1, unweighted) and 38.6% (95% CI 30.7-47.2, weighted) reported contraceptive use, compared to 66% of rural women in the NSFG sample. Among the ROI women, 27% had received prior 30-day SUD treatment via outpatient counseling or inpatient program and these women had increased odds of contraceptive use (aOR 1.50 [95% CI 1.08-2.06]). There was a positive association between contraception use and recent medications for opioid use disorder (aOR 1.34 [95% CI 0.95-1.88]) and prior 6-month primary care utilization (aOR 1.32 [95% CI 0.96-1.82]) that did not meet the threshold for statistical significance.

WWUD in rural areas reported low contraceptive use; those who recently received SUD treatment had greater odds of contraceptive use. Improvements are needed in expanding reproductive and preventive health within SUD treatment and primary care services in rural communities.

US federal, state, and local governments implemented numerous COVID-19 shelter-in-place orders (lockdowns) starting in March 2020 to ensure social distancing regulations and help stop the spread of COVID-19. It is important to know how these lockdowns affected businesses, such as restaurants, in regions that vary in terms of poverty status and geography. In this paper, we analyze the differential changes in rural and urban restaurant visits by the restaurants' NAICS codes following the COVID-19 lockdowns. Our analysis contributes to the public policy literature and helps operational planning for food distribution during a pandemic.

Since urban and rural consumer behavior and food resources are significantly different, it is crucial to conduct a comparative analysis. Our study applies a difference-in-differences model to capture the differential effects lockdowns have on urban and rural restaurants.

We find that restaurant visits declined significantly in both rural and urban counties after shelter-at-home orders. The decrease in total restaurant visits was almost twice as high in urban counties as in rural counties. We also find that visits to fast-food restaurants increased in rural counties during shelter-at-home orders.

These results contribute to previous studies on the dearth of healthy food in rural and poorer regions, and inform important public policy response in the wake of the COVID-19 pandemic.

Opioid overdoses within the United States continue to rise and have been negatively impacting the social and economic status of the country. In order to effectively allocate resources and identify policy solutions to reduce the number of overdoses, it is important to understand the geographical differences in opioid overdose rates and their causes. In this study, we utilized data on emergency department opioid overdose (EDOOD) visits to explore the county-level spatio-temporal distribution of opioid overdose rates within the state of Virginia and their association with aggregate socio-ecological factors. The analyses were performed using a combination of techniques including Moran's I and multilevel modeling. Using data from 2016-2021, we found that Virginia counties had notable differences in their EDOOD visit rates with significant neighborhood-level associations: many counties in the southwestern region were consistently identified as the hotspots (areas with a higher concentration of EDOOD visits) whereas many counties in the northern region were consistently identified as the coldspots (areas with a lower concentration of EDOOD visits). In most Virginia counties, EDOOD visit rates declined from 2017 to 2018. In more recent years (since 2019), the visit rates showed an increasing trend. The multilevel modeling revealed that the change in clinical care factors (i.e., access to care and quality of care) and socio-economic factors (i.e., levels of education, employment, income, family and social support, and community safety) were significantly associated with the change in the EDOOD visit rates. The findings from this study have the potential to assist policymakers in proper resource planning thereby improving health outcomes.

The number of Chinese oldest-old (aged 80+) is growing rapidly and some studies have shown that the health status is unequal among older persons in different regions. However, to the best of our knowledge, no study to date has analyzed health inequalities among the oldest-old in urban and rural areas in China. This study therefore aimed to examine the correlation between health inequalities among the oldest-old in urban and rural areas of China. From the 8th wave of the Chinese Longitudinal Health Longevity Survey (CLHLS), we selected 8124 oldest-old participants who met the requirements of the study. Chi-square tests were used to analyze the distribution characteristics of indicators and a logistic model was performed to determine the factors associated with different self-rated health (SRH). The Fairlie model was adopted to decompose the causes and related contributions to health inequality. Our results found that of the Chinese oldest-old, 46.57% were in good health. Urban residents reported significantly better SRH than rural residents (50.17% vs. 45.13%). Variables associated with good and poor SRH had different distribution characteristics. The logistic model suggested that marital status, alcohol consumption, and annual income were important factors underlying the SRH differences. Our decomposition analysis indicated that 76.64% of the SRH differences were caused by observational factors, and validated that the difference in SRH between urban and rural areas was significantly (P<0.05) associated with exercise status (45.44%), annual income (37.64%), social activity status (3.75%), age (-5.27%), and alcohol consumption (-2.66%). Therefore, socioeconomic status and individual lifestyle status were the main factors underlying the health inequality between urban and rural Chinese oldest-old.

This paper first explores spatial distributions and patterns of COVID-19 case rates (cases/100,000 people) and mortality rates (deaths/100,000 people) and their disparities between urban and rural counties in the contiguous US. A county-level social vulnerability index was created using principal component analysis. Social vulnerability components were regressed against both county case and mortality rates. Results suggest that hotspots of case and mortality rates are clustered in Midwest and Upper-Midwest US. We found substantial disparities in case and mortality rates between urban and rural counties. County social vulnerability was positively correlated with both case and mortality rates suggesting counties with higher social vulnerability had higher case and mortality rates. Relationships between social vulnerability components and case and mortality rates vary across the conterminous US. Additionally, counties with increased racial and ethnic minorities, higher percentages of minors, and lower median household income are associated with higher COVID-19 case and mortality rates.

Tooth loss is an oral health condition with high prevalence and negative impact on quality of life. It is the result of the history of oral diseases and their treatment as well as provision of dental care and access to dental services. Socioeconomic characteristics are determinants of tooth loss and living in rural areas is also a risk factor for its incidence.

To identify contextual and individual factors associated with self-reported tooth loss among adults and elderly people living in rural riverside areas.

A cross-sectional household-based survey was conducted in 2019 with rural riverside communities on the left bank of the Rio Negro River, Manaus, Amazonas. These communities are covered by a fluvial health team and two riverside health teams. Interviews were conducted in a representative random sample of dwellers aged ≥ 18 years, using electronic forms to obtain information on oral health conditions, demographic and socioeconomic characteristics, and use of and access to health services. The outcome was self-reported tooth loss. After the descriptive analysis of the data, a multilevel Poisson regression analysis was performed to estimate the prevalence ratio for the outcome. Variables with p-value ≤0.20 in the bivariate analyses were included in the multiple analysis considering the hierarchy between individual and contextual variables in the multilevel model. Variables with p-value ≤0.10 were kept in the final model and the significance level adopted was 0.05.

603 individuals from 357 households were assessed (mean age 44.1 years). The average number of missing teeth was 11.2 (±11.6); 27.4% of individuals had lost more than 20 teeth (non-functional dentition) and 12.1% were completely edentulous. Contextual characteristic of primary healthcare offered was associated with the outcome. The tooth loss was lower in territories covered by riverside health teams. At individual level, tooth loss was greater in older individuals who had experienced dental pain over the past six months and whose sugar consumption was high. Black or brown individuals, individuals whose household income was higher, those who were on the Bolsa Família cash transfer program, those who consulted a dentist over the past year, and those who reported satisfaction with their teeth/oral health reported less tooth loss.

Tooth loss was associated with contextual territorial factors related to the healthcare service and individual demographic, behavioral, socioeconomic, and service-related characteristics as well as self-perceived oral health conditions. The findings suggest that actions focused on the oral health of these populations involve not only changes in the healthcare service organization, but also intersectoral policies that contribute to reducing social inequalities.

To investigate whether rural-urban differences in quality of care for Medicare Advantage (MA) enrollees vary between females and males.

Data for this study came from the 2019 Healthcare Effectiveness Data and Information Set. Linear regression was used to investigate urban-rural differences in individual MA enrollee scores on 34 clinical care measures grouped into 7 categories, and how those differences varied by sex (through evaluation of statistical interactions).

Across all 7 categories of measures, scores for rural residents were worse than scores for urban residents. For 4 categories-care for patients with (suspected) chronic obstructive pulmonary disease, avoiding prescription misuse, behavioral health, and diabetes care-the average difference across measures in the category was greater than 3 percentage points. Across all 34 measures, there were 15 statistically significant rural-by-sex interactions that exceeded 1 percentage point. In 11 of those cases, the deficit associated with living in a rural area was greater for males than for females. In 3 cases, the deficit associated with living in a rural area was larger for females than for males. In 1 case involving Follow-up After Hospitalization for Mental Illness, rural residents had an advantage, and it was larger for males than for females.

Interventions may help address patient- (eg, health literacy and patient activation), provider- (eg, workforce recruitment and retention), and structural-level issues contributing to these disparities, especially for rural males.

Large-scale longitudinal studies evaluating influences of the built environment on risk for type 2 diabetes (T2D) are scarce, and findings have been inconsistent.

To evaluate whether land use environment (LUE), a proxy of neighborhood walkability, is associated with T2D risk across different US community types, and to assess whether the association is modified by food environment.

The Veteran's Administration Diabetes Risk (VADR) study is a retrospective cohort of diabetes-free US veteran patients enrolled in VA primary care facilities nationwide from January 1, 2008, to December 31, 2016, and followed longitudinally through December 31, 2018. A total of 4,096,629 patients had baseline addresses available in electronic health records that were geocoded and assigned a census tract-level LUE score. LUE scores were divided into quartiles, where a higher score indicated higher neighborhood walkability levels. New diagnoses for T2D were identified using a published computable phenotype. Adjusted time-to-event analyses using piecewise exponential models were fit within four strata of community types (higher-density urban, lower-density urban, suburban/small town, and rural). We also evaluated effect modification by tract-level food environment measures within each stratum.

In adjusted analyses, higher LUE had a protective effect on T2D risk in rural and suburban/small town communities (linear quartile trend test p-value <0.001). However, in lower density urban communities, higher LUE increased T2D risk (linear quartile trend test p-value <0.001) and no association was found in higher density urban communities (linear quartile trend test p-value = 0.317). Particularly strong protective effects were observed for veterans living in suburban/small towns with more supermarkets and more walkable spaces (p-interaction = 0.001).

Among veterans, LUE may influence T2D risk, particularly in rural and suburban communities. Food environment may modify the association between LUE and T2D.

Rural US populations face a chronic shortage of physicians and an increasing gap in life expectancy compared to urban US populations, creating a need to understand how to increase residency graduates' desire to practice in such areas.

This study quantifies associations between the amount of rural training during family medicine (FM) residencies and subsequent rural work.

American Medical Association (AMA) Masterfile, AMA graduate medical education (GME) supplement, American Board of Family Medicine certification, Accreditation Council for Graduate Medical Education (ACGME), and Centers for Medicare and Medicaid Services hospital costs data were merged and analyzed. Multiple logistic regression measured associations between rural training and rural or urban practice in 2018 by all 12 162 clinically active physicians who completed a US FM residency accredited by the ACGME between 2008 and 2012. Analyses adjusted for key potential confounders (age, sex, program size, region, and medical school location and type) and clustering by resident program.

Most (91%, 11 011 of 12 162) residents had no rural training. A minority (14%, 1721 of 12 162) practiced in a rural location in 2018. Residents with no rural training comprised 80% (1373 of 1721) of those in rural practice in 2018. Spending more than half of residency training months in rural areas was associated with substantially increased odds of rural practice (OR 5.3-6.3). Only 4% (424 of 12 162) of residents spent more than half their training in rural locations, and only 5% (26 of 436) of FM training programs had residents training mostly in rural settings or community-based clinics.

There is a linear gradient between increasing levels of rural exposure in FM GME and subsequent rural work.

Cigarette smoking prevalence is higher among rural compared with urban adults, yet access to cessation programming is reduced. The Increasing Digital Equity and Access (IDEA) study aims to evaluate three digital access and literacy interventions for promoting engagement with an online evidence-based smoking cessation treatment (EBCT) program among rural adults.

The pilot trial will use a pragmatic, three-arm, randomized, parallel-group design with participants recruited from a Midwest community-based health system in Minnesota, Wisconsin, and Iowa. All participants will receive an online, 12-week, EBCT program, and written materials on digital access resources. Participants will be stratified based on state of residence and randomly assigned with 1:1:1 allocation to one of three study groups: (1) Control Condition-no additional study intervention (n = 30); (2) Loaner Digital Device-Bluetooth enabled iPad with data plan coverage loaned for the study duration (n = 30); (3) Loaner Digital Device + Coaching Support-loaner device plus up to six, 15-20 min motivational interviewing-based coaching calls to enhance participants' digital access and literacy (n = 30). All participants will complete study assessments at baseline and 4- and 12-weeks post-randomization. Outcomes are cessation program and trial engagement, biochemically confirmed smoking abstinence, and patient experience.

A rural community advisory committee was formed that fostered co-design of the study protocol for relevance to rural populations, including the trial design and interventions.

Study findings, processes, and resources may have relevance to other health systems aiming to foster digital inclusion in smoking cessation and chronic disease management programs and clinical trials in rural communities.