Rural-urban disparities in the prevalence of diabetes and coronary heart disease

Burdens of type 2 diabetes and cardiovascular disease attributable to sugar-sweetened beverages in 184 countries

The consumption of sugar-sweetened beverages (SSBs) is associated with type 2 diabetes (T2D) and cardiovascular diseases (CVD). However, an updated and comprehensive assessment of the global burden attributable to SSBs remains scarce. Here we estimated SSB-attributable T2D and CVD burdens across 184 countries in 1990 and 2020 globally, regionally and nationally, incorporating data from the Global Dietary Database, jointly stratified by age, sex, educational attainment and urbanicity. In 2020, 2.2 million (95% uncertainty interval 2.0-2.3) new T2D cases and 1.2 million (95% uncertainty interval 1.1-1.3) new CVD cases were attributable to SSBs worldwide, representing 9.8% and 3.1%, respectively, of all incident cases. Globally, proportional SSB-attributable burdens were higher among men versus women, younger versus older adults, higher- versus lower-educated adults, and adults in urban versus rural areas. By world region, the highest SSB-attributable percentage burdens were in Latin America and the Caribbean (T2D: 24.4%; CVD: 11.3%) and sub-Saharan Africa (T2D: 21.5%; CVD: 10.5%). From 1990 to 2020, the largest proportional increases in SSB-attributable incident T2D and CVD cases were in sub-Saharan Africa (+8.8% and +4.4%, respectively). Our study highlights the countries and subpopulations most affected by cardiometabolic disease associated with SSB consumption, assisting in shaping effective policies and interventions to reduce these burdens globally.

Rural-Urban Disparities in State-Level Diabetes Prevalence Among US Adults, 2021

Introduction

We assessed state-level disparities in diabetes prevalence among adults in rural and urban areas in the United States.

Methods

We estimated state-specific diabetes prevalence in rural and urban areas in 41 states with applicable data from the 2021 Behavioral Risk Factor Surveillance System. Rural areas were defined based on the 2013 National Center for Health Statistics Urban-Rural Classification Scheme. We estimated diabetes odds ratios (ORs) in rural versus urban areas in each state by using logistic regressions adjusted for sociodemographic characteristics and obesity status. Analyses were conducted in 2023.

Results

In rural areas, diabetes prevalence was 14.3%, ranging from 8.4% in Colorado to 21.3% in North Carolina. In urban areas, the prevalence was 11.2%, ranging from 6.9% in Colorado to 15.5% in West Virginia. Unadjusted diabetes ORs in rural versus urban areas were significant (P < .05) and greater than 1 for 19 states. After adjusting for age, sex, race, and ethnicity, the ORs were significant and greater than 1 for 7 states (Florida, Illinois, Kentucky, Maryland, North Carolina, Oregon, and Virginia). With additional adjustment for education, income, and obesity status, diabetes ORs in rural versus urban areas remained significant and greater than 1 for 2 states (North Carolina and Oregon).

Conclusion

Our findings reveal significant geographic disparities in diabetes prevalence between rural and urban areas in 19 states. The differences in most states may have been explained by rural-urban differences in sociodemographic characteristics and obesity rates. Our findings could inform decision makers to identify effective ways to reduce rural-urban disparities within states.

Measuring the Impact of Healthcare Provider Availability on Quality of Care and Disease Burden in Ohio: A Cross-Sectional Study

BACKGROUND

Chronic lower respiratory disease, heart disease, and diabetes have a higher prevalence in rural areas. Previous studies raise concerns that a lower supply of physicians is associated with negative outcomes.

OBJECTIVE

To assess disease burden across the 88 counties in Ohio, including Appalachian and non-Appalachian counties, and examine associations with the number of healthcare providers.

METHODS

We utilized data sourced from the Centers for Medicare & Medicaid Services (CMS) and the Mapping Medicare Disparities tool. We conducted ANOVA to compare the mean number of primary care physicians (PCP), specialty physicians, advanced practice providers (APP), and other healthcare providers for Ohio counties. We calculated mean prevalence, principal cost, and prevention quality indicator (PQI) by health condition. We analyzed the relationship between healthcare providers and the PQI across counties, and examined differences in healthcare providers and disease burden between Appalachian and non-Appalachian regions.

RESULTS

The mean number of providers per 100,000 people significantly differed between PCP, specialty physicians, APP, and other healthcare providers (F = 13.9, P < 0.001). The prevalence of hypertension (mean = 67.0, SD = 2.2) and diabetes (mean = 27.1, SD = 2.4) was the highest of the selected conditions. The number of preventable hospitalizations from chronic conditions (mean = 2024.9, SD = 526.8) was significantly higher (P < 0.001) than the number of preventable hospitalizations from acute conditions (mean = 851.6, SD = 262.2). The multivariate mixed effects model of PCP*Specialist*APP*Other was the best predictive model for all health conditions (P < 0.001). COPD (mean = 17.4, SD = 2.8) and diabetes (mean = 28.4, SD = 2.3) in Appalachian counties were significantly higher (P < 0.001) than COPD (mean = 13.7, SD = 1.9) and diabetes (mean = 26.2, SD = 2.1) in non-Appalachian counties.

CONCLUSION

This study found higher PQI scores for chronic conditions than acute conditions, indicating the need for higher-quality outpatient care to prevent avoidable hospital admissions. Further, Appalachian counties had fewer other healthcare providers and many counties lacked specialist physicians, highlighting significant disparities in healthcare access in Appalachian Ohio.

A closer examination of the "rural mortality penalty": Variability by race, region, and measurement

BACKGROUND

Racial health disparities are well documented and pervasive across the United States. Evidence suggests there is a "rural mortality penalty" whereby rural residents experience poorer health outcomes than their urban counterparts. However, whether this penalty is uniform across demographic groups and U.S. regions is unknown.

OBJECTIVE

To assess how rural-urban differences in mortality differ by race (Black vs. White), U.S. region, poverty status, and how rural-urban status is measured.

METHODS

Age-standardized mortality rates (ASMRs)/100,000 by U.S. county (2015-2019) were obtained by race (Black/White) from the CDC Wonder National Vital Statistics System (2015-2019) and were merged with county-level social determinants from the US Census Bureau and County Health Rankings. Multivariable generalized linear models assessed the associations between rurality (index of relative rurality [IRR] decile, rural-urban continuum codes, and population density) and race-specific ASMR, overall, and by Census region and poverty level.

RESULTS

Overall, average ASMR was significantly higher in rural areas than urban areas for both Black (rural ASMR = 949.1 per 100,000 vs. urban ASMR = 857.7 per 100,000) and White (rural ASMR = 903.0 per 100,000 vs. urban ASMR = 791.6 per 100,000) populations. The Black-White difference was substantially higher (p < 0.001) in urban than in rural counties (65.1 per 100,000 vs. 46.1 per 100,000). Black-White differences and patterns in ASMR varied notably by poverty status and U.S. region.

CONCLUSION

Policies and interventions designed to reduce racial health disparities should consider and address key contextual factors associated with geographic location, including rural-urban status and socioeconomic status.

A descriptive examination of rurality in the Environmental influences on Child Health Outcomes Cohort: Implications, illustrations, and future directions

PURPOSE

The Environmental influences on Child Health Outcomes (ECHO) Cohort has enrolled over 60,000 children to examine how early environmental factors (broadly defined) are associated with key child health outcomes. The ECHO Cohort may be well-positioned to contribute to our understanding of rural environments and contexts, which has implications for rural health disparities research. The present study examined the outcome of child obesity to not only illustrate the suitability of ECHO Cohort data for these purposes but also determine how various definitions of rural and urban populations impact the presentation of findings and their interpretation.

METHODS

This analysis uses data from children in the ECHO Cohort study who had residential address information between January 2010 and October 2023, including a subset who also had height and weight data. Several rural-urban classification schemes were examined with and without collapsing into binary rural/urban groupings (ie, the Rural-Urban Continuum Codes, 2010 Rural-Urban Commuting Area [RUCA] Codes, and Urban Influence Codes).

FINDINGS

Various rural/urban definitions and classification schemes produce similar obesity prevalence (17%) when collapsed into binary categories (rural vs urban) and for urban participants in general. When all categories within a classification scheme are examined, however, the rural child obesity prevalence ranges from 5.8% to 24%.

CONCLUSIONS

Collapsing rural-urban classification schemes into binary groupings erases nuance and context needed for interpreting findings, ultimately impacting health disparities research. Future work should leverage both individual- and community-level datasets to provide context, and all categories of classification schemes should be used when examining rural populations.

Transforming education for rural health equity: Lessons from a rural and underserved health scholars program

BACKGROUND AND PURPOSE

Rural and underserved areas are in desperate need of improved access to healthcare services to enhance the well-being of patients. In an effort to increase students' healthcare access and exposure to the knowledge and skills of healthcare professionals in this area, a specialized certificate program on the care of rural and underserved patients was created. The purpose of this article is to describe the design, implementation, and assessment of this program.

EDUCATIONAL ACTIVITY AND SETTING

The Rural and Underserved Health Scholars Program (RUHSP) is offered to pharmacy and nursing students in the last three years of their professional program with 4 seminar courses and practice experiences in rural and underserved care. Students focus on challenges and opportunities in rural and underserved care, project development, health outcomes, leadership development, community service, and professional service. The culmination of the project is a community-based project the students develop in conjunction with a local agency.

FINDINGS

The RUHSP has successfully recruited 4 cohorts of students, totaling 42 participants. RUHSP participants have designed and implemented 13 community-based research projects through the program. Preliminary pre/post survey results indicate the program impacted participants' knowledge, skills, abilities, confidence, readiness, and interest in rural/underserved settings. Participants completing the program indicated the program was highly valued and impactful.

SUMMARY

Rural and underserved areas have a continued need for enhanced healthcare access and quality care; rural health training programs are one way to fill care gaps in these areas with confident, prepared, and passionate providers.

Health behaviours and mobile intervention use in patients recruited from general practitioners' practices in rural Bavaria

Introduction: Individuals living in rural areas report poorer health outcomes, including obesity, compared to individuals living in urban areas. Amongst others, this is due to restricted access to opportunities for healthy eating and physical activity. Interventions are urgently needed to address this gap. It is yet unclear whether digital interventions are suited for this purpose. The present dataset provides information on adults residing in rural Germany regarding their health status, perceived access to opportunities for healthy eating and physical activity, and digital device ownership and intervention use. Materials and methods: A pen-and-paper survey was conducted in winter 2022/2023 among patients of five general practitioners' practices in rural Bavaria. Materials and data are openly available for future use. Data description: The dataset contains responses from N = 273 individuals (54.9% women, 44.8% men, 0.4% diverse; age M = 51.3, SD = 16.7; BMI M = 29.1, SD = 15.9). On average, 30.6 participants failed to respond to any given item (SD = 33.0; range 1-136). Eighty-four percent had access to the internet and a computer and 91.4% owned a smartphone, but the majority (58.5%/ 84.2%) had no prior experience with mobile physical activity or dietary interventions, respectively. Discussion: This dataset provides insights into barriers and facilitators to healthy eating and physical activity in rural populations and digital (health) technology use. It provides starting points for behavioural weight management interventions in rural areas.

Trends in coronary artery disease mortality among adults with diabetes: Insights from CDC WONDER (1999-2020)

BACKGROUND

Coronary artery disease (CAD) in diabetes mellitus (DM) is a significant cause of mortality among US adults. This study investigates trends in CAD-related mortality in adults aged 25 and older with DM, focusing on geographic, gender, and racial/ethnic disparities from 1999 to 2020.

METHODS

A retrospective analysis was conducted using death certificate data from the CDC WONDER database from 1999 to 2020. Age-adjusted mortality rates (AAMRs), annual percent change (APC), and average annual percentage change (AAPC) were calculated per 100,000 persons, stratified by year, sex, race/ethnicity, and geographical region.

RESULTS

CAD in DM accounted for 1,462,279 deaths among US adults aged 25+. Most deaths occurred in medical facilities (44.2 %) and at home (29.3 %). The overall AAMR for CAD in DM-related deaths decreased from 36.3 in 1999 to 31.7 in 2020, with an AAPC of -0.96 (95 % CI: -1.29 to -0.77, p < 0.000001). Men had higher AAMRs (41.6) compared to women (22.6), with a more significant decrease in women (AAPC: -2.10, p < 0.000001) than in men (AAPC: -0.34, p = 0.001200). Racial/ethnic disparities showed the highest AAMRs in American Indians/Alaska Natives (43.6), followed by Blacks (37.8), Hispanics (33.8), Whites (29.7), and Asians/Pacific Islanders (22.5). The most significant decrease was in Hispanics (AAPC: -1.64, p < 0.000001). Geographically, AAMRs ranged from 13.7 in Nevada to 51.3 in West Virginia, with the highest mortality observed in the Midwest (AAMR: 34.5). Nonmetropolitan areas exhibited higher AAMRs (35.2) than metropolitan areas (29.7), with a more pronounced decrease in metropolitan areas (AAPC: -1.22, p < 0.000001) compared to nonmetropolitan areas (AAPC: -0.03, p = 0.854629).

CONCLUSION

The notable increase in mortality rates associated with CAD among patients with DM from 2018 to 2020 presents a substantial concern that necessitates targeted public health interventions to ensure equitable access to cardiovascular care.

Clinician Distribution and Type in Rural and Urban Areas of the National Health Services Corps

This cross-sectional study assesses long-term trends in clinician distribution between rural and urban areas and whether the trends differ by clinician discipline and type.

Diagnosing, managing, and studying long-COVID syndromes in children and adolescents in rural and underserved populations

The COVID-19 pandemic has arguably had its greatest impact in rural and other historically hard-to-reach populations. Families in rural and underserved communities experienced COVID-19 infections at a higher rate than did their peers in other groups and experienced disproportionate morbidity and mortality. Without careful design and implementation of resources, children in these areas are also at risk of being disproportionately affected by long-term sequelae of SARS-CoV-2 infections, such as "long COVID" syndromes. Increased frequency and severity of COVID-19 infections, decreased access to health care and supporting services, environmental and social structure factors that exacerbate post-acute sequelae of COVID-19, and increased baseline frequency of health disorders that may complicate post-COVID issues, such as higher rates of obesity, asthma, diabetes, and mental health disorders, all place children and adolescents in under-resourced areas at significant risk. Unfortunately, children and adolescents in these areas have been historically under-represented in clinical research. Not only are fewer studies published with participants in rural and underserved communities, but these studies more often exhibit lower quality, with fewer randomized controlled trials and multicenter studies. This gap not only deprives people in rural and underserved areas of the country of access to cutting-edge therapy, but it also risks "evidence-based" solutions that are not generalizable because they cannot be implemented in the areas disproportionately affected by many health conditions such as long COVID. These factors significantly impede our ability to provide appropriate medical care for underserved communities. This review will discuss the impact of COVID-19 in rural and underserved communities and the factors that must be considered in designing evidence-based long-COVID solutions for children and adolescents in these areas.

Weight status underestimation and weight management goals among adults in the rural South of the United States

PURPOSE

To examine factors associated with weight status underestimation and the relationship between weight status underestimation and weight loss as a weight management goal among adults living in the rural South.

METHODS

An anonymous survey was distributed at six primary care clinics and two churches in rural, South Carolina counties. Weight status underestimation was determined based on the difference between perceived weight status using standard body mass index (BMI) categories (underweight, normal weight, overweight, and obese) and BMI category from self-reported height and weight. Participants reported whether their weight management goal was to lose, maintain, or gain weight. Chi-square and binary logistic regressions were used for data analysis.

FINDINGS

A total of 185 respondents (76% female) at least partially completed the survey. Nearly 60% underestimated their weight status. Increasing BMI was associated with higher odds of weight status underestimation (OR: 1.10, 95%: 1.04, 1.15) and perceptions of being in fair or poor health was associated with lower odds of weight status underestimation relative to perceiving health as good or better (OR: 0.21, 95% CI: 0.06, 0.66). Among those with overweight and obesity, the association between underestimating weight status and having weight loss as a weight management goal was strong but not statistically significant (OR: 0.20, 95% CI: 0.04, 1.04).

CONCLUSIONS

Underestimating weight status was common among adults in the rural US South and was related to BMI and health status. Research is needed to determine if improving the accuracy of weight perceptions can promote weight management in the rural South.

Prevalence of Self-Reported Diagnosed Diabetes Among Adults, by County Metropolitan Status and Region, United States, 2019-2022

Introduction

Previous research suggests that rural-urban disparities in diabetes mortality, hospitalization, and incidence rates may manifest differently across US regions. However, no studies have examined disparities in diabetes prevalence by metropolitan residence and region.

Methods

We used data from the 2019-2022 National Health Interview Survey to compare diabetes status, socioeconomic characteristics, and weight status among adults in each census region (Northeast, Midwest, South, West) according to county metropolitan status of residence (large central metro, large fringe metro, small/medium metro, and nonmetro). We used χ2 tests and logistic regression models to assess the association of metropolitan residence with diabetes prevalence in each region.

Results

Diabetes prevalence ranged from 7.0% in large fringe metro counties in the Northeast to 14.8% in nonmetro counties in the South. Compared with adults from large central metro counties, those from small/medium metro counties had significantly higher odds of diabetes in the Midwest (age-, sex-, and race and ethnicity-adjusted odds ratio [OR] = 1.24; 95% CI, 1.06-1.45) and South (OR = 1.15; 95% CI, 1.02-1.30). Nonmetro residence was also associated with diabetes in the South (OR = 1.62 vs large central metro; 95% CI, 1.43-1.84). After further adjustment for socioeconomic and body weight status, small/medium metro associations with diabetes became nonsignificant, but nonmetro residence in the South remained significantly associated with diabetes (OR = 1.22; 95% CI, 1.07-1.39).

Conclusion

The association of metropolitan residence with diabetes prevalence differs across US regions. These findings can help to guide efforts in areas where diabetes prevention and care resources may be better directed.

Rural-urban residence and life expectancies with and without pain

This paper analyzes rural-urban disparities in life expectancy with and without pain among upper-middle age and older adults. Data are from the nationally representative Health and Retirement Study, 2000-2018, N = 18,160, age 53+. Interpolated Markov Chain software, based on the multistate life tables, is used to calculate absolute and relative pain expectancies by age, sex, rural-suburban-urban residence and U.S. regions. Results show significant rural disadvantages versus those in urban and often suburban areas. Example: males at 55 in rural areas can expect to live 15.1 years, or 65.2 percent pain-free life, while those in suburban areas expect to live 1.7 more years, or 2.6 percentage points more, pain-free life and urban residents expect to live 2.4 more year, or 4.7 percentage points more. The rural disadvantage persists for females, with differences being a little less prominent. At very old age (85+), rural-urban differences diminish or reverse. Rural-urban pain disparities are most pronounced in the Northeast and South regions, and least in the Midwest and West. The findings highlight that rural-urban is an important dimension shaping the geography of pain. More research is needed to disentangle the mechanisms through which residential environments impact people's pain experiences.

Geographic access to cardiac rehabilitation and cardiovascular disease outcomes: A study of rural United States counties

Prior studies have examined rural-urban disparities in access to cardiac rehabilitation (CR). However, few have examined the relationship between disparate access to CR and cardiovascular disease outcomes in rural areas. In this analysis of 1975 nonmetro United States counties, we investigated the relationship between number of hospitals with CR and Medicare-population hospitalization rates (per 1000 adults ≥65 years) and county-population mortality rates (per 100,000 adults ≥18 years) due to coronary heart disease (CHD), heart failure (HF), or stroke, using multivariable linear-regression-modeling adjusting for socio-demographic and comorbid conditions. Median CHD hospitalization (13.0 vs. 12.2), HF hospitalization (16.1 vs. 13.3), HF death (114.2 vs. 110.9), stroke hospitalization (12.0 vs. 10.9), and stroke death (39.6 vs. 37.1) rates were higher in nonmetro counties without versus with a CR facility (p-values< 0.001). There were inverse correlations between number of hospitals with CR and CHD (r= -0.161), HF (r= -0.261) and stroke (r= -0.237) hospitalization rates, and stroke mortality (r= -0.144) rates (p-values< 0.001). After adjustment, as the number of hospitals with CR increased, there were decreases in hospitalization rates of 1.78 for CHD, 7.20 for HF, and 2.43 for stroke, per 1000 in the population (p-values < 0.001) and decreases in stroke deaths of 9.17 per 100,000 in the population (p= 0.02). Access to hospitals with CR in US nonmetro counties is inversely related to CHD, HF, and stroke hospitalization, and stroke mortality. Our findings call for reducing barriers to CR in nonmetro communities and further exploring the relationship between CR and stroke outcomes.

Demographic and geographic distribution of diabetes and pre-diabetes risk in rural settings: results from a cross-sectional, countywide rural health survey in Sullivan County, New York

OBJECTIVE

To perform a detailed characterisation of diabetes burden and pre-diabetes risk in a rural county with previously documented poor health outcomes in order to understand the local within-county distribution of diabetes in rural areas of America.

DESIGN, SETTING, AND PARTICIPANTS

In 2021, we prospectively mailed health surveys to all households in Sullivan County, a rural county with the second-worst health outcomes of all counties in New York State. Our survey included questions on demographics, medical history and the American Diabetes Association's Pre-diabetes Risk Test.

PRIMARY OUTCOME AND METHODS

Our primary outcome was an assessment of diabetes burden within this rural county. To help mitigate non-response bias in our survey, raking adjustments were performed across strata of age, sex, race/ethnicity and health insurance. We analysed diabetes prevalence by demographic characteristics and used geospatial analysis to assess for clustering of diagnosed diabetes cases.

RESULTS

After applying raking procedures for the 4725 survey responses, our adjusted diagnosed diabetes prevalence for Sullivan County was 12.9% compared with the 2019 Behavioural Risk Factor Surveillance System (BRFSS) estimate of 8.6%. In this rural area, diagnosed diabetes prevalence was notably higher among non-Hispanic Black (21%) and Hispanic (15%) residents compared with non-Hispanic White (12%) residents. 53% of respondents without a known history of pre-diabetes or diabetes scored as high risk for pre-diabetes. Nearest neighbour analyses revealed that hotspots of diagnosed diabetes were primarily located in the more densely populated areas of this rural county.

CONCLUSIONS

Our mailed health survey to all residents in Sullivan County demonstrated higher diabetes prevalence compared with modelled BRFSS estimates that were based on small telephone samples. Our results suggest the need for better diabetes surveillance in rural communities, which may benefit from interventions specifically tailored for improving glycaemic control among rural residents.

Key influences on dysglycemia across Fujian's urban-rural divide

BACKGROUND

Screening and treatment of dysglycemia (prediabetes and diabetes) represent significant challenges in advancing the Healthy China initiative. Identifying the crucial factors contributing to dysglycemia in urban-rural areas is essential for the implementation of targeted, precise interventions.

METHODS

Data for 26,157 adults in Fujian Province, China, were collected using the Social Factors Special Survey Form through a multi-stage random sampling method, wherein 18 variables contributing to dysglycemia were analyzed with logistic regression and the random forest model.

OBJECTIVE

Investigating urban-rural differences and critical factors in dysglycemia prevalence in Fujian, China, with the simultaneous development of separate predictive models for urban and rural areas.

RESULT

The detection rate of dysglycemia among adults was 35.26%, with rates of 34.1% in urban areas and 35.8% in rural areas. Common factors influencing dysglycemia included education, age, BMI, hypertension, and dyslipidemia. For rural residents, higher income (OR = 0.80, 95% CI [0.74, 0.87]), average sleep quality (OR = 0.89, 95% CI [0.80, 0.99]), good sleep quality (OR = 0.89, 95% CI [0.80, 1.00]), and high physical activity (PA) (OR = 0.87, 95% CI [0.79, 0.96]) emerged as protective factors. Conversely, a daily sleep duration over 8 hours (OR = 1.46, 95% CI [1.03, 1.28]) and middle income (OR = 1.12, 95% CI [1.03, 1.22]) were specific risk factors. In urban areas, being male (OR = 1.14, 95% CI [1.02, 1.26]), cohabitation (OR = 1.18, 95% CI [1.02, 1.37]), and central obesity (OR = 1.35, 95% CI [1.19, 1.53]) were identified as unique risk factors. Using logistic regression outcomes, a random forest model was developed to predict dysglycemia, achieving accuracies of 75.35% (rural) and 76.95% (urban) with ROC areas of 0.77 (rural) and 0.75 (urban).

CONCLUSION

This study identifies key factors affecting dysglycemia in urban and rural Fujian residents, including common factors such as education, age, BMI, hypertension, and dyslipidemia. Notably, rural-specific protective factors are higher income and good sleep quality, while urban-specific risk factors include being male and central obesity. These findings support the development of targeted prevention and intervention strategies for dysglycemia, tailored to the unique characteristics of urban and rural populations.

Where Patients Live Matter in Emergency Department Visits in Home Health Care: Rural/Urban Status and Neighborhood Socioeconomic Status

An increasing body of evidence highlights the importance of an individual's place of residence on their health and functional outcomes. This study is based on Outcome and Assessment Information Set data to assess the differences in emergency department visits among Medicare home health care patients by patients' residence location (rural/urban status and neighborhood socioeconomic status). Compared to urban patients, a disproportionately higher proportion of rural patients lived in more or most disadvantaged neighborhoods (83.9% vs. 41.3%). Using linear probability regression models, patients in rural areas (coefficient = .02, p < .001) and disadvantaged neighborhoods (less disadvantaged: coefficient = .02, p < .001; more disadvantaged: coefficient = .034, p < .001; most disadvantaged: coefficient = .042, p < .001) were more likely to experience emergency department visits. Policymakers should consider utilizing area-based target interventions to mitigate gaps in home health care. Also, given that the majority of rural patients reside in disadvantaged neighborhoods, neighborhood characteristics should be considered in addressing rural-urban disparities and improving home health care.

County Rurality and Incidence and Prevalence of Diagnosed Diabetes in the United States

OBJECTIVE

To examine differences in the incidence and prevalence of diagnosed diabetes by county rurality.

PATIENTS AND METHODS

This observational, cross-sectional study used US Centers for Disease Control and Prevention data from 2004 through 2019 for county estimates of incidence and prevalence of diagnosed diabetes. County rurality was based on 6 levels (large central metro counties [most urban] to noncore counties [most rural]). Weighted least squares regression was used to relate rurality with diabetes incidence rates (IRs; per 1000 adults) and prevalence (percentage) in adults aged 20 years or older after adjusting for county-level sociodemographic factors (eg, food environment, health care professionals, inactivity, obesity).

RESULTS

Overall, in 3148 counties and county equivalents, the crude IR and prevalence of diabetes were highest in noncore counties. In age and sex ratio-adjusted models, the IR of diabetes increased monotonically with increasing rurality (P<.001), whereas prevalence had a weak, nonmonotonic but statistically significant increase (P=.002). Further adjustment for sociodemographic factors including food environment, health care professionals, inactivity, and obesity attenuated differences in incidence across rurality levels, and reversed the pattern for prevalence (prevalence ratios [vs large central metro] ranged from 0.98 [95% CI, 0.97 to 0.99] for large fringe metro to 0.94 [95% CI, 0.93 to 0.96] for noncore). In region-stratified analyses adjusted for sociodemographic factors including inactivity and obesity, increasing rurality was inversely associated with incidence in the Midwest and West only and inversely associated with prevalence in all regions.

CONCLUSION

The crude incidence and prevalence of diagnosed diabetes increased with increasing county rurality. After accounting for sociodemographic factors including food environment, health care professionals, inactivity, and obesity, county rurality showed no association with incidence and an inverse association with prevalence. Therefore, interventions targeting modifiable sociodemographic factors may reduce diabetes disparities by region and rurality.

Urban-Rural Differences in the Prevalence of Diabetes Among Adults in Haryana, India: The ICMR-INDIAB Study (ICMR-INDIAB-18)

INTRODUCTION

Diabetes is a multifactorial disease with far-reaching consequences. Environmental factors, such as urban or rural residence, influence its prevalence and associated comorbidities. Haryana-a north Indian state-has undergone rapid urbanisation, and part of it is included in the National Capital Region (NCR). The primary aim of the study is to estimate the prevalence of diabetes in Haryana with urban-rural, NCR and non-NCR regional stratification and assess the factors affecting the likelihood of having diabetes among adults.

METHODS

This sub-group analysis of the Indian Council of Medical Research-India Diabetes (ICMR-INDIAB) study (a nationally representative cross-sectional population-based survey) was done for Haryana using data from 3722 participants. The dependent variable was diabetes, while residence in NCR/non-NCR and urban-rural areas were prime independent variables. Weighted prevalence was estimated using state-specific sampling weights and standardized using National Family Health Survey-5 (NFHS-5) study weights. Associations were depicted using bivariate analysis, and factors describing the likelihood of living with diabetes were explored using a multivariable binary logistic regression analysis approach.

RESULTS

Overall, the weighted prevalence of diabetes in Haryana was higher than the national average (12.4% vs. 11.4%). The prevalence was higher in urban (17.9%) than in rural areas (9.5%). The prevalence of diabetes in rural areas was higher in the NCR region, while that of prediabetes was higher in rural non-NCR region. Urban-rural participants' anthropometric measurements and biochemical profiles depicted non-significant differences. Urban-rural status, age and physical activity levels were the most significant factors that affected the likelihood of living with diabetes.

CONCLUSIONS

The current analysis provides robust prevalence estimates highlighting the urban-rural disparities. Urban areas continue to have a high prevalence of diabetes and prediabetes; rural areas depict a much higher prevalence of prediabetes than diabetes. With the economic transition rapidly bridging the gap between urban and rural populations, health policymakers should plan efficient strategies to tackle the diabetes epidemic.

Investigation of geographic disparities of diabetes-related hospitalizations in Florida using flexible spatial scan statistics: An ecological study

BACKGROUND

Hospitalizations due to diabetes complications are potentially preventable with effective management of the condition in the outpatient setting. Diabetes-related hospitalization (DRH) rates can provide valuable information about access, utilization, and efficacy of healthcare services. However, little is known about the local geographic distribution of DRH rates in Florida. Therefore, the objectives of this study were to investigate the geographic distribution of DRH rates at the ZIP code tabulation area (ZCTA) level in Florida, identify significant local clusters of high hospitalization rates, and describe characteristics of ZCTAs within the observed spatial clusters.

METHODS

Hospital discharge data from 2016 to 2019 were obtained from the Florida Agency for Health Care Administration through a Data Use Agreement with the Florida Department of Health. Raw and spatial empirical Bayes smoothed DRH rates were computed at the ZCTA level. High-rate DRH clusters were identified using Tango's flexible spatial scan statistic. Choropleth maps were used to display smoothed DRH rates and significant high-rate spatial clusters. Demographic, socioeconomic, and healthcare-related characteristics of cluster and non-cluster ZCTAs were compared using the Wilcoxon rank sum test for continuous variables and Chi-square test for categorical variables.

RESULTS

There was a total of 554,133 diabetes-related hospitalizations during the study period. The statewide DRH rate was 8.5 per 1,000 person-years, but smoothed rates at the ZCTA level ranged from 0 to 101.9. A total of 24 significant high-rate spatial clusters were identified. High-rate clusters had a higher percentage of rural ZCTAs (60.9%) than non-cluster ZCTAs (41.8%). The median percent of non-Hispanic Black residents was significantly (p < 0.0001) higher in cluster ZCTAs than in non-cluster ZCTAs. Populations of cluster ZCTAs also had significantly (p < 0.0001) lower median income and educational attainment, and higher levels of unemployment and poverty compared to the rest of the state. In addition, median percent of the population with health insurance coverage and number of primary care physicians per capita were significantly (p < 0.0001) lower in cluster ZCTAs than in non-cluster ZCTAs.

CONCLUSIONS

This study identified geographic disparities of DRH rates at the ZCTA level in Florida. The identification of high-rate DRH clusters provides useful information to guide resource allocation such that communities with the highest burdens are prioritized to reduce the observed disparities. Future research will investigate determinants of hospitalization rates to inform public health planning, resource allocation and interventions.

Physical Activity According to Diabetes and Metropolitan Status, U.S., 2020 and 2022

INTRODUCTION

Physical activity can reduce morbidity and mortality among adults with diabetes. Although rural disparities in physical activity exist among the general population, it is not known how these disparities manifest among adults with diabetes.

METHODS

Data from the 2020 and 2022 National Health Interview Survey were analyzed in 2023 to assess the prevalence of meeting aerobic and muscle-strengthening recommendations according to the 2018 Physical Activity Guidelines for Americans during leisure time. Physical activity prevalence was computed by diabetes status, type of physical activity, and urban/rural residence (large central metropolitan, large fringe metropolitan, medium/small metropolitan, and nonmetropolitan). Logistic regression models were used to estimate prevalence and prevalence ratios of meeting physical activity recommendations by urban/rural residence across diabetes status.

RESULTS

Among adults with diabetes in nonmetropolitan counties, only 23.8% met aerobic, 10.9% met muscle-strengthening, and 6.2% met both physical activity recommendations. By contrast, among adults with diabetes in large fringe metropolitan counties, 32.1% met aerobic, 19.7% met strengthening, and 12.0% met both guidelines. Multivariable adjusted prevalence of meeting muscle-strengthening recommendations was higher among participants with diabetes in large fringe metropolitan than among large central metropolitan counties (prevalence ratio=1.27; 95% CI=1.03, 1.56). Among those without diabetes, adjusted prevalence of meeting each recommendation or both was lower in nonmetropolitan and small/medium metropolitan than in large central metropolitan counties.

CONCLUSIONS

Adults with diabetes are less likely to meet the physical activity recommendations than those without, and differences exist according to urban/rural status. Improving physical activity among rural residents with diabetes may mitigate disparities in diabetes-related mortality.

Telehealth Trends and Hypertension Management Among Rural and Medicaid Patients After COVID-19

Objective: Examine the associations between rurality and low income with primary care telehealth utilization and hypertension outcomes across multiple years pre- and post-COVID-19 pandemic onset. Methods: We compiled electronic health record data from the mixed rural/urban Dartmouth Health system in New Hampshire, United States, on patients with pre-existing hypertension or diabetes receiving primary care in the period before (January 2018-February 2020) and after the transition period to telehealth during the COVID-19 Pandemic (October 2020-December 2022). Stratifying by rurality and Medicaid enrollment, we examined changes in synchronous (office and telehealth visits, including audio/video use) and asynchronous (patient portal or telephone message) utilization, and control of mean systolic blood pressure (SBP) <140. Results: Analysis included 46,520 patients, of whom 8.2% were Medicaid enrollees, 42.7% urban residents. Telehealth use rates were 12% for rural versus 6.4% for urban, and 15% for Medicaid versus 8.4% non-Medicaid. The overall postpandemic telehealth visit rate was 0.29 per patient per year. Rural patients had a larger increase in telehealth use (additional 0.21 per year, 95% CI, 0.19-0.23) compared with urban, as did Medicaid (0.32, 95% CI 0.29-0.36) compared with non-Medicaid. Among the 38,437 patients with hypertension, SBP control worsened from 83% to 79% of patients across periods. In multivariable analysis, rurality corresponded to worsened control rates compared with urban (additional 2.4% decrease, 95% CI 2.1-2.8%); Medicaid and telehealth use were not associated with worsened control. Conclusions: Telehealth expansion enabled a higher shift to telehealth for rural and low-income patients without impairing hypertension management.

Rural versus urban outcomes following transcatheter aortic valve implantation: The importance of the heart team

BACKGROUND

Rural patients face known healthcare disparities and worse cardiovascular outcomes compared to urban residents due to inequitable access and delayed care. Few studies have assessed rural-urban differences in outcomes following Transcatheter Aortic Valve Implantation (TAVI). We compared short-term post-TAVI outcomes between rural and urban patients.

METHODS

We performed a retrospective analysis of n = 413 patients who underwent TAVI at our large academic medical center, between 2011 and 2020 (rural/urban patients = 93/320. Rural/urban males = 53/173). Primary outcomes were all-cause mortality and cardiovascular mortality. Secondary outcomes included stroke/transient ischemic attack, myocardial infarction, atrial fibrillation, acute kidney injury, bleeding, vascular complications, and length of stay.

RESULTS

The mean age in years was 77 [IQR 70-82] for rural patients and 78 [IQR 72-84] for urban patients. Baseline characteristics were similar between groups, except for a greater frequency of active smokers and diabetics as well as a greater body mass index in the rural group. There were no statistically significant differences in all-cause or cardiovascular mortality between the groups. There was also no statistically significant difference in secondary outcomes.

CONCLUSION

Rural and urban patients had no statistically significant difference in all-cause mortality or cardiovascular mortality following TAVI. Given its minimally invasive nature and quality-centric, multidisciplinary care provided by the TAVI Heart Teams, TAVI may be the preferred modality for the treatment of severe aortic stenosis in rural populations.

Clinical correlates of negative health events and disparities among adults with epilepsy enrolled in a self-management clinical trial

AIMS

Despite advances in care, people with epilepsy experience negative health events (NHEs), such as seizures, emergency department (ED) visits and hospitalizations. This analysis using baseline data from an epilepsy self-management clinical trial targeting people from rural regions and other underserved populations assessed the relationship between demographic and clinical variables vs. NHEs.

METHODS

Data to evaluate disparities and clinical correlates was collected using patient surveys from a baseline sample of 94 participants in a larger prospective study of 160 individuals with epilepsy who experienced an NHE within the last six months. Demographic characteristics, mental and physical functional status assessed using 36-Item Short Form Health Survey questionnaire version 2 (SF-36v2), depression assessed with the 9-item Patient Health Questionnaire (PHQ-9), quality of life assessed with the 10-item Quality of Life in Epilepsy Inventory (QOLIE-10), self-efficacy assessed the Epilepsy Self-Efficacy Scale (ESES), social support assessed with the Multidimensional Scale of Perceived Social Support (MSPSS), self-management assessed with the Epilepsy Self-Management Scale (ESMS), and stigma assessed with the Epilepsy Stigma Scale (ESS) were all examined in association with past 6-month total NHE frequency as well as NHE sub-categories of past 30-day and 6-month seizure counts, self-harm attempts, ED visits and hospitalizations. An exploratory evaluation of NHE correlates in relation to the Rural Urban Continuum Code (RUCC) residence classification compared 3 subgroups of increasing rurality. Descriptive statistics were generated for demographic and clinical variables and NHEs, and exploratory analyses compared the distribution of demographic, clinical, and NHE variables by RUCC categorization.

RESULTS

The mean age was 38.5 years (SD 11.9), predominantly female (N= 62, 66.0%) and white (N=81, 86.2%). Just a little under half (N=43, 45.7%) of participants had annual incomes of less than $25,000, and 40% (N=38) were rural residents (RUCC >3). The past 6-month NHEs count was 20.4 (SD 32.0). Seizures were the most common NHE with a mean 30-day seizure frequency = 5.4 (SD 11.8) and 6-month seizure frequency of 18.7 (SD 31.6). Other NHE types were less common with a past 6-month self-harm frequency of 0.16 (SD 1.55), ED visit frequency of 0.72 (SD 1.10), and hospitalization frequency of 0.28 (SD 1.02). There were few significant demographic and clinical correlates for total and sub-categories of NHEs. Worse physical health status, as measured by the physical component summary (PCS) of the SF-36v2, was significantly associated with 6-month seizure counts (p=.04). There were no significant differences between the 3 RUCC subgroups on demographic variables. However, past 30-day seizure count, past 6-month seizure count and total past 6-month NHE counts were all higher among individuals from more rural settings (p-values <.01 for each).

CONCLUSIONS

Rural adults with epilepsy were more likely to have a greater number of seizures and more epilepsy complications in general. Worse physical health function was also associated with more epilepsy complications. However, this analysis found few other demographic and clinical correlates of cumulative NHEs among adults with epilepsy. Additional efforts are needed to investigate health disparities among people with epilepsy who live in rural regions or who have poor physical health function.

Weight management in rural health clinics: Results from the randomized midwest diet and exercise trial

Introduction

Rural living adults have higher rates of obesity compared with their urban counterparts and less access to weight management programs. Previous research studies have demonstrated clinically relevant weight loss in rural living adults who complete weight management programs delivered by university affiliated interventionists. However, this approach limits the potential reach, adoption, implementation, and maintenance of weight management programs for rural residents. Weight management delivered through rural health clinics by non-physician clinic associated staff, for example, nurses, registered dieticians, allied health professionals, etc. has the potential to improve access to weight management for rural living adults. This trial compared the effectiveness of a 6-month multicomponent weight management intervention for rural living adults delivered using group phone calls (GP), individual phone calls (IP) or an enhanced usual care control (EUC) by rural clinic associated staff trained by our research team.

Methods

Rural living adults with overweight/obesity (n = 187, age ∼ 50 years 82% female, body mass index ∼35 kg/m2) were randomized (2:2:1) to 1 of 3 intervention arms: GP, which included weekly ∼ 45 min sessions with 7-14 participants (n = 71), IP, which included weekly ∼ 15 min individual sessions (n = 80), or EUC, which included one-45 min in-person session at baseline.

Results

Weight loss at 6 months was clinically relevant, that is, ≥5% in the GP (-11.4 kg, 11.7%) and the IP arms (-9.1 kg, 9.2%) but not in the EUC arm (-2.6%, -2.5% kg). Specifically, 6 month weight loss was significantly greater in the IP versus EUC arms (-6.5 kg. p ≤ 0.025) but did not differ between the GP and IP arms (-2.4 kg, p > 0.025). The per participant cost per kg. weight loss for implementing the intervention was $93 and $60 for the IP and GP arms, respectively.

Conclusions

Weight management delivered by interventionists associated with rural health clinics using both group and IP calls results in clinically relevant 6 months weight loss in rural dwelling adults with overweight/obesity with the group format offering the most cost-effective strategy. Clinical trial registration: ClinicalTrials.gov (NCT02932748).

Where we live matters: a comparison of chronic pain treatment between remote and non-remote regions of Quebec, Canada

Objective

Where a person lives is a recognized socioeconomic determinant of health and influences healthcare access. This study aimed to compare the pain treatment profile of persons with chronic pain (CP) living in remote regions to those living in non-remote regions (near or in major urban centers).

Methods

A cross-sectional study was performed among persons living with CP across Quebec. In a web-based questionnaire, participants were asked to report in which of the 17 administrative regions they were living (six considered "remote"). Pain treatment profile was drawn up using seven variables: use of prescribed pain medications, over-the-counter pain medications, non-pharmacological pain treatments, multimodal approach, access to a trusted healthcare professional for pain management, excessive polypharmacy (≥10 medications), and use of cannabis for pain.

Results

1,399 participants completed the questionnaire (women: 83.4%, mean age: 50 years, living in remote regions: 23.8%). As compared to persons living in remote regions, those living in non-remote regions were more likely to report using prescribed pain medications (83.8% vs. 67.4%), a multimodal approach (81.5% vs. 75.5%), experience excessive polypharmacy (28.1% vs. 19.1%), and report using cannabis for pain (33.1% vs. 20.7%) (bivariable p < 0.05). Only the use of prescribed medications as well as cannabis remained significantly associated with the region of residence in the multivariable models.

Discussion

There are differences in treatment profiles of persons with CP depending on the region they live. Our results highlight the importance of considering remoteness, and not only rurality, when it comes to better understanding the determinants of pain management.

Associations between metals and metabolomic profiles related to diabetes among adults in a rural region

INTRODUCTION

Exposure to metals is associated with increased risk of type 2 diabetes (T2D). Potential mechanisms for metals-T2D associations involve biological processes including oxidative stress and disruption of insulin-regulated glucose uptake. In this study, we assessed whether associations between metal exposure and metabolite profiles relate to biological pathways linked to T2D.

MATERIALS AND METHODS

We used data from 29 adults rural Colorado residents enrolled in the San Luis Valley Diabetes Study. Urinary concentrations of arsenic, cadmium, cobalt, lead, manganese, and tungsten were measured. Metabolic effects were evaluated using untargeted metabolic profiling, which included 61,851 metabolite signals detected in serum. We evaluated cross-sectional associations between metals and metabolites present in at least 50% of samples. Primary analyses adjusted urinary heavy metal concentrations for creatinine. Metabolite outcomes associated with each metal exposure were evaluated using pathway enrichment to investigate potential mechanisms underlying the relationship between metals and T2D.

RESULTS

Participants had a mean age of 58.5 years (standard deviation = 9.2), 48.3% were female, 48.3% identified as Hispanic/Latino, 13.8% were current smokers, and 65.5% had T2D. Of the detected metabolites, 455 were associated with at least one metal, including 42 associated with arsenic, 22 with cadmium, 10 with cobalt, 313 with lead, 66 with manganese, and two with tungsten. The metabolic features were linked to 24 pathways including linoleate metabolism, butanoate metabolism, and arginine and proline metabolism. Several of these pathways have been previously associated with T2D, and our results were similar when including only participants with T2D.

CONCLUSIONS

Our results support the hypothesis that metals exposure may be associated with biological processes related to T2D, including amino acid, co-enzyme, and sugar and fatty acid metabolism. Insight into biological pathways could influence interventions to prevent adverse health outcomes due to metal exposure.

Gender differences in all-cause and cardiovascular mortality among US adults: from NHANES 2005-2018

Background

Gender disparities in mortality have drawn great interest, with previous studies identifying various biological, social, and behavioral factors contributing to the observed gender differences. This study aims to identify the sources of gender disparities in mortality rates and quantify the extent to which these factors mediate the gender differences in all-cause mortality.

Methods

Data from the National Health and Nutrition Examination Survey (NHANES) conducted between 2005 and 2018 were analyzed. A total of 38,924 participants were included in the study. Gender information, socioeconomic status, lifestyle factors, and baseline disease status were obtained through questionnaires. Blood samples were collected to assess serological indicators. All-cause and cardiovascular mortality were considered as primary and secondary outcomes, respectively.

Results

The study with an average age of 50.1 ± 17.9 years. Among the participants, 50.7% were women, and 41.8% were non-Hispanic White. The median follow-up length was 87 months [Inter-Quartile Range (IQR): 47-128]. Men showed higher rates of all-cause and cardiovascular mortality compared to women in both the general population and the population with cardiovascular disease. After adjustment for potential confounders (age, race, marital status, socioeconomic status, lifestyle level, smoking status, cardiovascular disease, hypertension, diabetes and cancer), the men: women hazard ratios (HRs) for all-cause and cardiovascular mortality were 1.58 [95% Confidence Interval (CI): 1.48-1.68] and 1.60 (95%CI:1.43-1.80) in the general population. Among individuals with cardiovascular disease, the fully adjusted HR for all-cause mortality was 1.34 (95% CI: 1.20 to 1.51), and for cardiovascular mortality, the fully adjusted HRs was 1.52 (95% CI: 1.26 to 1.83). Mediation analysis revealed that uric acid levels significantly mediated the association between gender and all-cause mortality, accounting for 17.53% (95% CI: 11.0% to 23.7%) in the general population and 27.47% (95% CI: 9.0% to 13.6%) in the population with cardiovascular disease.

Conclusions

The study highlights the complex interplay of biological and social factors contributing to gender disparities in mortality. Uric acid was identified as key mediators of the gender-mortality association. These findings can inform targeted interventions aimed at reducing gender disparities in mortality and promoting better public health outcomes.

Rural-urban health differences among aging adults in India

Background

The aim of this study was to determine the rural-urban health differences among aging adults in India.

Methods

The national cross-sectional data of 67,489 individuals (≥45 years) in 2017-2018 from 35 states and union territories of India (excluding Sikkim) in 2017-2018 were analysed. Various sociodemographic data, well-being indicators, lifestyle factors and physical conditions were assessed by face-to-face interviews and physical measurement. Univariable and multivariable logistic regression was utilized to assess the predictors between residence status (rural dweller, urban migrant, and urban dweller) and various health indicator outcomes.

Results

Majority (70.4 %) of the participants lived in rural areas, 10.3 % were urban migrants and 19.3 % urban dwellers. In the multivariable logistic regression analysis, urban migrants and urban dwellers had a higher self-rated health status, cognitive functioning, physical inactivity, overweight or obesity and abdominal obesity than rural dwellers, while urban migrants and/or urban dwellers had lower functional disability, insomnia symptoms, current smokeless tobacco use, current smoking, heavy episodic drinking and underweight than rural dwellers. Furthermore, urban migrants and/or urban dwellers had higher odds of diabetes, hypertension, heart disease, cancer, high cholesterol than rural dwellers, while urban migrants and/or urban dwellers had lower odds of persistent headaches, major injury, recurrent fall, physical pain, periodontal disease, vision impairment, and gastrointestinal problems than rural dwellers.

Conclusion

Among 30 health indicators assessed, 16 had an urban migrant and/or urban dweller advantage, 8 had urban migrant and/or urban dweller penalty, and 6 did not differ between rural-urban groups. Public health promotion and health care should address differing health care needs of rural and urban middle-aged and older adults.

Rurality and race in heart failure risk: Insights from the Southern Community Cohort Study

INTRODUCTION

Rural-urban health disparities are apparent in the burden of disease and health outcomes, including cardiovascular disease (CVD), specifically heart failure (HF). However, the factors influencing these disparities are not fully understood. Study and results: Among 27,115 participants in the Southern Community Cohort Study (SCCS) (mean age: 54 years (47-65)), 18,647 (68.8%) were black, 8,468 (32.3%) were white, and 20% resided in rural areas. Over a median 13-year follow-up period, 7,542 HF events occurred (rural = 1,865 vs. urban = 5,677). The age-adjusted HF incidence was 29.6 (95% CI, 28.9-30.5) and 36.5 (95% CI, 34.9-38.3) per 1,000 person-years for urban and rural participants, respectively (P < .001). The risk of HF associated with rurality varied by race and sex. Rural black men had the highest risk across all groups (HR, 1.34; 95% CI, 1.19-1.51) (age-adjusted incidence rate: 40.4/1000 person-years (95% CI, 36.8-44.3)) followed by black women (HR, 1.18; 95% CI, 1.08-1.28) and white women (HR, 1.22; 95% CI, 1.07-1.39). Rurality was not associated with HF risk among white men (HR, 0.97; 95% CI, 0.81-1.16).

LESSONS LEARNED

This large study shows that rural populations have an increased incidence of HF, which is particularly striking among women and black men, independent of individual-level biological, behavioral, and sociocultural risk factors. It also shows the need for further investigation into the rurality-associated risk of HF, the impact of preventive care utilization on the risk of HF and interpersonal, community, or societal factors that could contribute to rural-urban disparities. This will help to guide public health efforts aimed at HF prevention among rural populations.

Associations between PM2.5 and O3 exposures and new onset type 2 diabetes in regional and national samples in the United States

BACKGROUND

Exposure to particulate matter ≤2.5 μm in diameter (PM2.5) and ozone (O3) has been linked to numerous harmful health outcomes. While epidemiologic evidence has suggested a positive association with type 2 diabetes (T2D), there is heterogeneity in findings. We evaluated exposures to PM2.5 and O3 across three large samples in the US using a harmonized approach for exposure assignment and covariate adjustment.

METHODS

Data were obtained from the Veterans Administration Diabetes Risk (VADR) cohort (electronic health records [EHRs]), the Reasons for Geographic and Racial Disparities in Stroke (REGARDS) cohort (primary data collection), and the Geisinger health system (EHRs), and reflect the years 2003-2016 (REGARDS) and 2008-2016 (VADR and Geisinger). New onset T2D was ascertained using EHR information on medication orders, laboratory results, and T2D diagnoses (VADR and Geisinger) or report of T2D medication or diagnosis and/or elevated blood glucose levels (REGARDS). Exposure was assigned using pollutant annual averages from the Downscaler model. Models stratified by community type (higher density urban, lower density urban, suburban/small town, or rural census tracts) evaluated likelihood of new onset T2D in each study sample in single- and two-pollutant models of PM2.5 and O3.

RESULTS

In two pollutant models, associations of PM2.5, and new onset T2D were null in the REGARDS cohort except for in suburban/small town community types in models that also adjusted for NSEE, with an odds ratio (95% CI) of 1.51 (1.01, 2.25) per 5 μg/m3 of PM2.5. Results in the Geisinger sample were null. VADR sample results evidenced nonlinear associations for both pollutants; the shape of the association was dependent on community type.

CONCLUSIONS

Associations between PM2.5, O3 and new onset T2D differed across three large study samples in the US. None of the results from any of the three study populations found strong and clear positive associations.

Rural-urban otolaryngologic observational workforce analysis: The state of Nebraska

Objective

To analyze the rural-urban access to otolaryngology (OHNS) care within the state of Nebraska.

Design

Cross-sectional study.

Methods

Counties in Nebraska were categorized into rural versus urban status based upon the 2013 National Center for Health Statistics urban-rural classification scheme with I indicating most urban and VI indicating most rural. The information on otolaryngologists was gathered utilizing the Health Professions Tracking System. Otolaryngologists were categorized based on the county of their primary and outreach clinic location(s). Travel burden was estimated using census tract centroid distance to the nearest clinic location, aggregated to county using weighted population means to determine the average county distance to the nearest otolaryngologist.

Results

Nebraska is a state with a population of 1.8 million people unequally distributed across 76,824 square miles, with rural counties covering 2/3 of the land area. Nebraska has 78 primary OHNS clinics and 70 outreach OHNS clinics distributed across 93 counties. More than half (54.8%) of the counties in Nebraska lacked any OHNS clinic. Overall, a statistically significant difference was found when comparing mean primary OHNS per 100,000 population and mean miles to a primary OHNS clinic with Level III counties being 5.17 linear miles from primary OHNS compared to Level V counties being 29.94 linear miles.

Conclusion

Overall, a clear discrepancy between rural and urban primary OHNS clinics in Nebraska can be seen visually and statistically with rural Nebraskans having to travel at least 5.5 times farther to primary OHNS clinics when compared to urban Nebraskans.

Prevalence of age-related macular degeneration in Iran and its projections through 2050: a systematic review and meta-analysis

BACKGROUND

Age-related Macular Degeneration (AMD) is one of the most common causes of vision loss. A substantial increase in the burden of AMD is expected in the aging populations, including the Iranians. We investigated the age and gender-specific prevalence of AMD and its determinants in Iran.

METHODS

We systematically searched international (PubMed, Scopus, Embase, etc.) and local (IranDoc, Magiran, etc.) online databases. We included cross-sectional or cohort studies, either clinic- or population-based, published on the prevalence of AMD among Iranians, with no limitation on age. Joanna Briggs Institute (JBI) tools for critical appraisal were used. Prevalence estimates are pooled by applying random-effects modeling. Subgroup analysis and meta-regression were performed.

RESULTS

Seventeen studies with 16,120 participants were included. Based on studies in general population, the pooled prevalence of AMD was 10.8% (95% CI: 6.5-16.2%) in males, and 9.8% (95% CI: 4.7-16.4%) in females. 8.5% of moderate vision impaired, 13.6% of severe vision impaired, and 15.7% of blind participants were affected by AMD. The prevalence of AMD was 2% in 40-49, and 32.3% in the ≥ 80 population. The prevalence of AMD was 11.9% among the visually impaired vs. 8.7% in the general population. The study's sampling method, location, and mean age were correlated with the heterogeneities of the prevalence. We observed an increasing trend in the number of AMD cases (average annual percent change = 3.66%; 95% CI: 3.65-3.67%) from 1990 to 2050. The expected number of AMD cases in Iran will be near 5.5 million by 2050.

CONCLUSION

The prevalence of AMD in Iran was somewhere between the prevalence of Asians and Europeans. Given the aging trend of the Iranian community and an average annual percent change of 3.66%, it is indispensable to adopt preventive and screening policies to diminish the burden of the disease in the future decades.

The urban-rural disparities and factors associated with the utilization of public health services among diabetes patients in China

BACKGROUND

Basic public health services for diabetes play an essential role in controlling glycemia in patients with diabetes. This study was conducted to understand the urban-rural disparities in the utilization of basic public health services for people with diabetes and the factors influencing them.

METHODS

The data were obtained from the 2018 China Health and Retirement Longitudinal Study (CHARLS) with 2976 diabetes patients. Chi-square tests were used to examine the disparities in the utilization of diabetes physical examination and health education between urban and rural areas. Logistic regression was performed to explore the factors associated with the utilization of diabetes public health services.

RESULTS

Among all participants, 8.4% used diabetes physical examination in the past year, and 28.4% used diabetes health education services. A significant association with age (OR = 0.64, 95% CI:0.49-0.85; P < 0.05) was found between patients' use of health education services. Compared with diabetes patients living in an urban area, diabetes patients living in a rural area used less diabetes health education. (χ2= 92.39, P < 0.05). Patients' self-reported health status (OR = 2.04, CI:1.24-3.35; P < 0.05) and the use of glucose control (OR = 9.33, CI:6.61-13.16; P < 0.05) were significantly positively associated with the utilization of diabetes physical examination. Patients with higher education levels were more likely to use various kinds of health education services than their peers with lower education levels (OR = 1.64, CI:1.21-2.22; P < 0.05).

CONCLUSION

Overall, urban-rural disparities in the utilization of public health services existed. Vulnerable with diabetes, such as those in rural areas, are less available to use diabetes public health services. Providing convenient health service infrastructure facilitates the utilization of basic public health services for diabetes in older patients with diabetes, especially in rural areas.

Rural Hospital Disparities in Goals of Care Documentation

CONTEXT

Goals of care conversations for seriously ill hospitalized patients are associated with high-quality patient-centered care.

OBJECTIVES

We aimed to assess the prevalence of documented goals of care conversations for rural hospitalized patients compared to nonrural hospitalized patients.

METHODS

We retrospectively assessed goals of care documentation using a template note for adult patients with predicted 90-day mortality greater than 30% admitted to eight rural and nine nonrural community hospitals between July 2021 and April 2023. We compared predictors and prevalence of goals of care documentation among rural and nonrural hospitals.

RESULTS

Of the 31,098 patients admitted during the study period, 21% were admitted to a rural hospital. Rural patients were more likely than nonrural patients to be >65 years old (89% vs. 86%, P = <.0001), more likely to live in a neighborhood classified in the highest quintile of socioeconomic disadvantage (40% vs. 16%, P = <.0001), and less likely to receive a palliative care consult (8% vs. 18%, P = <.0001). Goals of care documentation occurred less often for patients admitted to rural vs. nonrural community hospitals (2% vs. 7%, P < .0001). In the base multivariable logistic regression model adjusting for patient characteristics, the odds of goals care documentation were lower in rural vs. nonrural community hospitals (aOR 0.4, P = .0232). In a second multivariable logistic regression model including both patient characteristics and severity of illness, the odds of goals of care documentation in rural community hospitals were no longer statistically different than nonrural community hospitals (aOR 0.5, P = .1080). Patients who received a palliative care consult had a lower prevalence of goals of care documentation in rural vs. nonrural hospitals (16% vs. 37%, P = <.0001).

CONCLUSION

In this study of 17 rural and nonrural community hospitals, we found low overall prevalence of goals of care documentation with particularly infrequent documentation occurring within rural hospitals. Future study is needed to assess barriers to goals of care documentation contributing to low prevalence of goals of care conversations in rural hospital settings.

Rural-Urban Differences in Cognition: Findings From the Advanced Cognitive Training for Independent and Vital Elderly Trial

ObjectivesWe examined associations between three geographic areas (urban, suburban, rural) and cognition (memory, reasoning, processing speed) over a 10-year period. Methods: Data were obtained from 2539 participants in the Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) trial. Multilevel, mixed-effects linear regression was used to estimate cognitive trajectories by geographical areas over 10 years, after adjusting for social determinants of health. Results: Compared to urban and suburban participants, rural participants fared worse on all cognitive measures-memory (B = -1.17 (0.17)), reasoning (B = -1.55 (0.19)), and processing speed (B = 0.76 (0.19)) across the 10-year trajectory. Across geographic areas, greater economic stability, health care access and quality, and neighborhood resources were associated with better cognition over time. Discussion: Findings highlight the importance of geographical location when examining cognition later in life. More research examining place-based life experiences is needed to make the greatest impact on geographically diverse communities.

Cancer survivorship challenges of rural older adults: a qualitative study

BACKGROUND

Although research has advanced the field of oncologic geriatrics with survivors to assess their cancer-related needs and devise patient-centered interventions, most of that research has excluded rural populations. This study aimed to understand the survivorship challenges and recommendations in the perspective of rural older adults.

METHODS

This was a qualitative study that explored the survivorship challenges and recommendations of rural older adults who have completed curative intent chemotherapy for a solid tumor malignancy in the 12 months prior to enrollment in the present study.

RESULTS

Twenty-seven older adult survivors from rural areas completed open-ended semi-structured interviews. The mean age was 73.4 (SD = 5.0). Most participants were non-Hispanic White (96.3%), female (59.3%), married (63.0%), and had up to a high school education (51.9%). Rural older survivors reported a general lack of awareness of survivorship care plans, communication challenges with healthcare team, transportation challenges, financial toxicity, psychological challenges, and diet and physical challenges. Rural older survivors recommend the provision of nutritional advice referral to exercise programs, and social support groups and for their healthcare providers to discuss their survivorship plan with them.

CONCLUSIONS

Although study participants reported similar survivorship challenges as urban older adult survivors, additional challenges reported regarding transportation and consideration of farm animals have not been previously reported. Heightened awareness of the survivorship needs of rural older adults may result in better survivorship care for this population.

Factors associated with higher hemoglobin A1c and type 2 diabetes-related costs: Secondary data analysis of adults 18 to 64 in Texas with commercial insurance

OBJECTIVE

This study will identify factors associated with higher hemoglobin A1c (A1c) values and diabetes-related costs among commercially insured adults in Texas diagnosed with type 2 diabetes.

RESEARCH DESIGN AND METHODS

This secondary data analysis was based on claims data from commercially insured individuals 18-64 years of age residing in Texas with diagnosed type 2 diabetes during the 2018-2019 study period. The final analysis sample after all the exclusions consisted of 34,992 individuals. Measures included hemoglobin A1c, diabetes-related costs, Charlson Comorbidity Index, diabetes-related complications, rurality and other socioeconomic characteristics. Longitudinal A1c measurements were modeled using age, sex, rurality, comorbidity, and diabetes-related complications in generalized linear longitudinal regression models adjusting the observation time, which was one of the 8 quarters in 2018 and 2019. The diabetes-related costs were similarly modeled in both univariable and multivariable generalized linear longitudinal regression models adjusting the observation time by calendar quarters and covariates.

RESULTS

The median A1c value was 7, and the median quarterly diabetes-related cost was $120. A positive statistically significant relationship (p = < .0001) was found between A1c levels and diabetes-related costs, although this trend slowed down as A1c levels exceeded 8.0%. Higher A1c values were associated with being male, having diabetes-related complications, and living in rural areas. Higher costs were associated with higher A1c values, older age, and higher Charlson Comorbidity Index scores.

CONCLUSION

The study adds updated analyses of the interrelationships among demographic and geographic factors, clinical indicators, and health-related costs, reinforcing the role of higher A1c values and complications as diabetes-related cost drivers.

Development and external validation of a diagnostic model for cardiometabolic-based chronic disease : results from the China health and retirement longitudinal study (CHARLS)

BACKGROUND

Cardiovascular disease(CVD) is the leading cause of death in the world. Cardiometabolic-based chronic disease (CMBCD) model is presented that provides a basis for sustainable and early, evidence-based therapeutic targeting to mitigate the ravagest and development of CVD. CMBCD include dysglycemia, hypertension, and/or dyslipidemia progressing to downstream CVD events.

OBJECTIVES

The objective of our research was to develop and externally validate a diagnostic model of CMBCD.

METHODS

Design: Multivariable logistic regression of a cohort for 9,463 participants aged at least 45 years were drawn from the 2018 wave of the China Health and Retirement Longitudinal Study (CHARLS).

SETTING

The 2018 wave of the CHARLS.

PARTICIPANTS

Diagnostic model development: Totally 6,218 participants whose individual ID < 250,000,000,000. External validation: Totally 3,245 participants whose individual ID > 250,000,000,000.

OUTCOMES

CMBCD .

RESULTS

CMBCD occurred in 25.5%(1,584/6,218)of individuals in the development data set and 26.2%(850 /3,245)of individuals in the validation data set. The strongest predictors of CMBCD were age, general health status, location of residential address, smoking, housework ability, pain, and exercise tolerance. We developed a diagnostic model of CMBCD. Discrimination was the ability of the diagnostic model to differentiate between people who with and without CMBCD. This measure was quantified by calculating the area under the receiver operating characteristic(ROC) curve(AUC).The AUC was 0.6199 ± 0.0083, 95% confidence interval(CI) = 0.60372 ~ 0.63612. We constructed a nomograms using the development database based on age, general health status, location of residential address, smoking, housework ability, pain, and exercise tolerance. The AUC was 0.6033 ± 0.0116, 95% CI = 0.58066 ~ 0.62603 in the validation data set.

CONCLUSIONS

We developed and externally validated a diagnostic model of CMBCD. Discrimination, calibration, and decision curve analysis were satisfactory.

'A Different Ball Game': Adaptation of a men's health program for implementation in rural Australia

BACKGROUND

Men residing in rural areas are less likely to participate in weight management interventions than women, and few men-specific programs target rural areas. Aussie-Fans in Training (Aussie-FIT) is an evidence-based weight management intervention that uses professional Australian Football club affiliations and settings as a 'hook' to engage urban-residing men. The aim of this study is to report on how findings from rural stakeholder focus groups were used to inform the adaptation of Aussie-FIT for implementation in rural areas.

METHODS

Seven focus groups with stakeholders (n = 24) in three rural towns explored existing weight management and physical activity provisions, barriers and facilitators to engaging men, and considerations for adapting Aussie-FIT for implementation in rural contexts. Qualitative data were analysed using the framework approach. Adaptations made to the Aussie-FIT program and strategies to implement the program in rural contexts were reported using a structured framework.

RESULTS

Themes generated from our analysis include limited appealing services for men, Australian Football as a 'common language', the influence of the 'smaller fishpond'(population), considerations for program inclusivity, and the importance of local partner organisations for sustainability. We adapted the recruitment and marketing strategies, delivery settings, football program theme and partnerships for rural implementation. Stakeholders advised that an Australian Football program theme without specific local club affiliations would be important to avoid alienating men with differing club allegiances or non-sporting backgrounds. A multi-component recruitment strategy utilising local trusted sources, and program marketing that aligns with masculine ideals were considered important by stakeholders in small communities where 'people talk'.

CONCLUSIONS

Rural areas were described as 'a different ball game' due to limited local services and resources in comparison to metropolitan areas. Study findings have synergies with previous studies undertaken in rural contexts including in relation to the power of word of mouth, the importance of trust, and local partner organisations. Findings have implications for engaging rural men in health interventions in rural contexts where professional sporting contexts are not available. Assessing the extent to which the adapted Aussie-FIT program can reach and engage men in rural Australia, and exploring the barriers and facilitators to delivering the program in rural contexts is required.

Integrating Civic Engagement Into a Lifestyle Intervention for Rural Women - A Mixed Methods Process Evaluation

PURPOSE

The present study aimed to evaluate the implementation of a civic engagement curriculum (HEART Club) designed to catalyze positive environmental change in rural communities.

DESIGN

The HEART Club curriculum was integrated into a six-month community-based health behavior intervention to reduce cardiovascular disease risk.

SETTING

Participants were recruited from eight rural towns in Montana and New York.

SUBJECTS

101 midlife and older women.

INTERVENTION

Participants worked to address an issue related to their local food or physical activity environment and establish progress monitoring benchmarks.

METHOD

Evaluation components included after-class surveys, program leader interviews (n = 15), participant focus groups (n = 8), and post-intervention surveys.

RESULTS

Intervention sites reported high fidelity (78%) to the curriculum. Average attendance was 69% and program classes were rated as highly effective (4.1 out of 5). Despite positive participant feedback, low readiness for civic engagement and insufficient time were implementation challenges. The majority of HEART Club groups had accomplished two or more benchmarks post-intervention. Facilitators of progress included community support, effective leadership, and collective effort. Participants also indicated that trying to affect community change while simultaneously making personal health improvements likely stalled initial progress.

CONCLUSION

These findings highlight the potential and challenges associated with civic engagement within the context of rural lifestyle interventions. Future implementation efforts should focus on reframing civic engagement as an approach to support and maintain behavior change.

Assessing the Feasibility of Rural Residency Training for Licensed Naturopathic Physicians in the Northwest: A Qualitative Study

Objectives

Naturopathic physicians (ND) are uniquely situated to address areas of unmet health care need as primary care providers (PCPs). In several states, NDs have a broad scope of practice and are licensed as independent practitioners regardless of residency training. However, with a larger role in the health care system, the need for post-graduate medical training becomes more important for clinical success and patient safety. Our study aimed at assessing the feasibility of developing residencies for licensed NDs in rural federally qualified health centers (FQHCs) of Oregon and Washington.

Methods

We conducted interviews with leadership from a convenience sample of eight FQHCs. Six centers were rural, two of which already employed NDs. Two urban centers that employed NDs as PCPs were included for their valuable insights related to study design. Two investigators independently reviewed and coded site visit notes for prominent themes through inductive reasoning analysis.

Results

Consensus was met identifying the following themes: onboarding and mentorship; diversity of clinical training; financial structure; length of residency; and addressing health care needs in the community. We identified several opportunities for the development of primary care residencies for NDs, including the need for PCPs in rural communities, the ability of NDs to manage chronic pain with prescription drugs, and the prevention of morbidity from complex conditions such as diabetes and cardiovascular disease. Potential barriers to residency development include lack of Medicare reimbursement, mixed awareness of the ND scope of practice, and scarcity of dedicated mentors.

Conclusion

These results may serve as guideposts for the future development of naturopathic residencies in rural community health centers.

Incident type 2 diabetes attributable to suboptimal diet in 184 countries

The global burden of diet-attributable type 2 diabetes (T2D) is not well established. This risk assessment model estimated T2D incidence among adults attributable to direct and body weight-mediated effects of 11 dietary factors in 184 countries in 1990 and 2018. In 2018, suboptimal intake of these dietary factors was estimated to be attributable to 14.1 million (95% uncertainty interval (UI), 13.8-14.4 million) incident T2D cases, representing 70.3% (68.8-71.8%) of new cases globally. Largest T2D burdens were attributable to insufficient whole-grain intake (26.1% (25.0-27.1%)), excess refined rice and wheat intake (24.6% (22.3-27.2%)) and excess processed meat intake (20.3% (18.3-23.5%)). Across regions, highest proportional burdens were in central and eastern Europe and central Asia (85.6% (83.4-87.7%)) and Latin America and the Caribbean (81.8% (80.1-83.4%)); and lowest proportional burdens were in South Asia (55.4% (52.1-60.7%)). Proportions of diet-attributable T2D were generally larger in men than in women and were inversely correlated with age. Diet-attributable T2D was generally larger among urban versus rural residents and higher versus lower educated individuals, except in high-income countries, central and eastern Europe and central Asia, where burdens were larger in rural residents and in lower educated individuals. Compared with 1990, global diet-attributable T2D increased by 2.6 absolute percentage points (8.6 million more cases) in 2018, with variation in these trends by world region and dietary factor. These findings inform nutritional priorities and clinical and public health planning to improve dietary quality and reduce T2D globally.

Trust Dynamics of Community Health Workers in Frontier Food Banks and Pantries: a Qualitative Study

BACKGROUND

Medical mistrust has had devastating consequences during the COVID-19 pandemic, particularly in rural communities. Community Health Workers (CHWs) have been shown to build trust, but there is little research on trust-building by CHWs in rural communities.

OBJECTIVE

This study aims to understand the strategies that CHWs use to build trust with participants of health screenings in frontier Idaho.

DESIGN

This is a qualitative study based on in-person, semi-structured interviews.

PARTICIPANTS

We interviewed CHWs (N=6) and coordinators of food distribution sites (FDSs; e.g., food banks and pantries) where CHWs hosted a health screening (N=15).

APPROACH

Interviews were conducted with CHWs and FDS coordinators during FDS-based health screenings. Interview guides were initially designed to assess facilitators and barriers to health screenings. Trust and mistrust emerged as dominant themes that determined nearly every aspect of the FDS-CHW collaboration, and thus became the focus of interviews.

KEY RESULTS

CHWs encountered high levels of interpersonal trust, but low institutional and generalized trust, among the coordinators and clients of rural FDSs. When working to reach FDS clients, CHWs anticipated confronting mistrust due to their association with the healthcare system and government, especially if CHWs were perceived as "outsiders." Hosting health screenings at FDSs, which were trusted community organizations, was important for CHWs to begin building trust with FDS clients. CHWs also volunteered at FDS locations to build interpersonal trust before hosting health screenings. Interviewees agreed that trust building was a time- and resource-intensive process.

CONCLUSIONS

CHWs build interpersonal trust with high-risk rural residents, and should be integral parts of trust building initiatives in rural areas. FDSs are vital partners in reaching low-trust populations, and may provide an especially promising environment to reach some rural community members. It is unclear whether trust in individual CHWs also extends to the broader healthcare system.

Using the National Institute on Minority Health and Health Disparities framework to better understand disparities in major amputations

Recently, the United States experienced its first resurgence of major amputations in more than 20 years. Compounding this rise is a longstanding history of disparities. Patients identifying as non-Hispanic Black are twice as likely to lose a limb as those identifying as non-Hispanic White. Those identifying as Latino face a 30% increase. Rural patients are also more likely to undergo major amputations, and the rural-urban disparity is widening. We used the National Institute on Minority Health and Health Disparities framework to better understand these disparities and identify common factors contributing to them. Common factors were abundant and included increased prevalence of diabetes, possible lower rates of foot self-care, transportation barriers to medical appointments, living in disadvantaged neighborhoods, and lack of insurance. Solutions within and outside the health care realm are needed. Health care-specific interventions that embed preventative and ambulatory care services within communities may be particularly high yield.

Association of Rurality With Risk of Heart Failure

Importance

Rural populations experience an increased burden of heart failure (HF) mortality compared with urban populations. Whether HF incidence is greater among rural individuals is less known. Additionally, the intersection between racial and rural health inequities is understudied.

Objective

To determine whether rurality is associated with increased risk of HF, independent of cardiovascular (CV) disease and socioeconomic status (SES), and whether rurality-associated HF risk varies by race and sex.

Design, Setting, and Participants

This prospective cohort study analyzed data for Black and White participants of the Southern Community Cohort Study (SCCS) without HF at enrollment who receive care via Centers for Medicare & Medicaid Services (CMS). The SCCS is a population-based cohort of low-income, underserved participants from 12 states across the southeastern United States. Participants were enrolled between 2002 and 2009 and followed up until December 31, 2016. Data were analyzed from October 2021 to November 2022.

Exposures

Rurality as defined by Rural-Urban Commuting Area codes at the census-tract level.

Main Outcomes and Measures

Heart failure was defined using diagnosis codes via CMS linkage through 2016. Incidence of HF was calculated by person-years of follow-up and age-standardized. Sequentially adjusted Cox proportional hazards regression models tested the association between rurality and incident HF.

Results

Among 27 115 participants, the median (IQR) age was 54 years (47-65), 18 647 (68.8%) were Black, and 8468 (32.3%) were White; 5556 participants (20%) resided in rural areas. Over a median 13-year follow-up, age-adjusted HF incidence was 29.6 (95% CI, 28.9-30.5) per 1000 person-years for urban participants and 36.5 (95% CI, 34.9-38.3) per 1000 person-years for rural participants (P < .001). After adjustment for demographic information, CV risk factors, health behaviors, and SES, rural participants had a 19% greater risk of incident HF (hazard ratio [HR], 1.19; 95% CI, 1.13-1.26) compared with their urban counterparts. The rurality-associated risk of HF varied across race and sex and was greatest among Black men (HR, 1.34; 95% CI, 1.19-1.51), followed by White women (HR, 1.22; 95% CI, 1.07-1.39) and Black women (HR, 1.18; 95% CI, 1.08-1.28). Among White men, rurality was not associated with greater risk of incident HF (HR, 0.97; 95% CI, 0.81-1.16).

Conclusions and Relevance

Among predominantly low-income individuals in the southeastern United States, rurality was associated with an increased risk of HF among women and Black men, which persisted after adjustment for CV risk factors and SES. This inequity points to a need for additional emphasis on primary prevention of HF among rural populations.

Aging in Rural Communities

Purpose of Review

Population aging is occurring worldwide, particularly in developed countries such as the United States (US). However, in the US, the population is aging more rapidly in rural areas than in urban areas. Healthy aging in rural areas presents unique challenges. Understanding and addressing those challenges is essential to ensure healthy aging and promote health equity across the lifespan and all geographies. This review aims to present findings and evaluate recent literature (2019-2022) on rural aging and highlight future directions and opportunities to improve population health in rural communities.

Recent Findings

The review first addresses several methodological considerations in measuring rurality, including the choice of measure used, the composition of each measure, and the limitations and drawbacks of each measure. Next, the review considers important concepts and context when describing what it means to be rural, including social, cultural, economic, and environmental conditions. The review assesses several key epidemiologic studies addressing rural-urban differences in population health among older adults. Health and social services in rural areas are then discussed in the context of healthy aging in rural areas. Racial and ethnic minorities, indigenous peoples, and informal caregivers are considered as special populations in the discussion of rural older adults and healthy aging. Lastly, the review provides evidence to support critical longitudinal, place-based research to promote healthy aging across the rural-urban divide is highlighted.

Summary

Policies, programs, and interventions to reduce rural-urban differences in population health and to promote health equity and healthy aging necessitate a context-specific approach. Considering the cultural context and root causes of rural-urban differences in population health and healthy aging is essential to support the real-world effectiveness of such programs, policies, and interventions.

Effectiveness of diabetes education interventions in rural America: a systematic review

The purpose of this systematic review is to summarize the characteristics of recent studies on diabetes education interventions in rural areas and identify the relative proportion of studies with characteristics of interest that showed a reduction in glycated hemoglobin (A1C). A systematic literature search was performed in Web of Science, PubMed and PsychInfo, using keywords and Medical Subject Heading terms. Articles conducted in rural areas of the United States tested an educational intervention for people with type 2 diabetes, and reported outcomes were identified. A total of 2762 articles were identified, of which 27 were included. Of the 27 articles, most were implemented in the Southeast (n = 13). Of the 21 interventions that measured A1C, 10 reported a statistically significant decrease in A1C. The proportion of studies with a significant A1C reduction was higher for the studies that used telehealth/online, delivered by a collaboration between health-care professionals and lay educators or included family or group components. Only three studies included their criteria in determining rurality. Future diabetes education interventions may consider including family members or group sessions, holding online sessions and partnering with local resources. Additionally, stronger research methods are needed to test practical and effective interventions to improve diabetes education in rural areas.

Associations of four indexes of social determinants of health and two community typologies with new onset type 2 diabetes across a diverse geography in Pennsylvania

Evaluation of geographic disparities in type 2 diabetes (T2D) onset requires multidimensional approaches at a relevant spatial scale to characterize community types and features that could influence this health outcome. Using Geisinger electronic health records (2008–2016), we conducted a nested case-control study of new onset T2D in a 37-county area of Pennsylvania. The study included 15,888 incident T2D cases and 79,435 controls without diabetes, frequency-matched 1:5 on age, sex, and year of diagnosis or encounter. We characterized patients’ residential census tracts by four dimensions of social determinants of health (SDOH) and into a 7-category SDOH census tract typology previously generated for the entire United States by dimension reduction techniques. Finally, because the SDOH census tract typology classified 83% of the study region’s census tracts into two heterogeneous categories, termed rural affordable-like and suburban affluent-like, to further delineate geographies relevant to T2D, we subdivided these two typology categories by administrative community types (U.S. Census Bureau minor civil divisions of township, borough, city). We used generalized estimating equations to examine associations of 1) four SDOH indexes, 2) SDOH census tract typology, and 3) modified typology, with odds of new onset T2D, controlling for individual-level confounding variables. Two SDOH dimensions, higher socioeconomic advantage and higher mobility (tracts with fewer seniors and disabled adults) were independently associated with lower odds of T2D. Compared to rural affordable-like as the reference group, residence in tracts categorized as extreme poverty (odds ratio [95% confidence interval] = 1.11 [1.02, 1.21]) or multilingual working (1.07 [1.03, 1.23]) were associated with higher odds of new onset T2D. Suburban affluent-like was associated with lower odds of T2D (0.92 [0.87, 0.97]). With the modified typology, the strongest association (1.37 [1.15, 1.63]) was observed in cities in the suburban affluent-like category (vs. rural affordable-like–township), followed by cities in the rural affordable-like category (1.20 [1.05, 1.36]). We conclude that in evaluating geographic disparities in T2D onset, it is beneficial to conduct simultaneous evaluation of SDOH in multiple dimensions. Associations with the modified typology showed the importance of incorporating governmentally, behaviorally, and experientially relevant community definitions when evaluating geographic health disparities.