A Closer Look at Rural-Urban Health Disparities: Associations Between Obesity and Rurality Vary by Geospatial and Sociodemographic Factors

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.

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.

How does urbanization affect the cognitive function among older adults: A geospatial analysis in China

There has been a plethora of studies on urbanization and older adults, and more recent ones on how older adults adapt to this process with their cognitive competence. Yet it has been unclear about the relationship between them, like how the level and rate of urbanization affect the cognitive function among older adults. This study sourced, formed, and analyzed a set of geospatial big datasets from different sources, such as the Chinese Longitudinal Healthy Longevity Survey (CLHLS) data, and the NPP/VIIRS nighttime light (NTL) data. Results showed a generally negative linear association between the rate of urbanization and cognitive performance among older adults in China. The "U" shaped non-linear relationship between urbanization level and cognitive function, as well as the tipping point, were identified. At the same time, it should be noted that mediators such as education, physical activity, social activity, and community elderly service might be able to mitigate these negative associations. Furthermore, older adults living in eastern regions or urban areas appeared to have better cognitive function than those living in mid-western regions or rural areas in China. The findings also pointed to the importance of focusing on older adults with poor cognitive health status in rapidly urbanizing areas.

EpiVECS: exploring spatiotemporal epidemiological data using cluster embedding and interactive visualization

The analysis of data over space and time is a core part of descriptive epidemiology, but the complexity of spatiotemporal data makes this challenging. There is a need for methods that simplify the exploration of such data for tasks such as surveillance and hypothesis generation. In this paper, we use combined clustering and dimensionality reduction methods (hereafter referred to as 'cluster embedding' methods) to spatially visualize patterns in epidemiological time-series data. We compare several cluster embedding techniques to see which performs best along a variety of internal cluster validation metrics. We find that methods based on k-means clustering generally perform better than self-organizing maps on real world epidemiological data, with some minor exceptions. We also introduce EpiVECS, a tool which allows the user to perform cluster embedding and explore the results using interactive visualization. EpiVECS is available as a privacy preserving, in-browser open source web application at https://episphere.github.io/epivecs .

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.

Geographic differences in the magnitude of black-white disparities in having obesity

Background

Obesity disparities in the United States are well documented, but the limited body of research suggests that geographic factors may alter the magnitude of these disparities. A growing body of evidence has identified a "rural mortality penalty" where morbidity and mortality rates are higher in rural than urban areas, even after controlling for other factors. Black-White differences in health and mortality are more pronounced in rural areas than in urban areas.

Objective

Therefore, the purpose of this study was to explore how rural-urban status and region moderate Black-White health disparities in obesity.

Methods

Data were abstracted from the 2012 Behavioral Risk Factor Surveillance System, with the sample being restricted to Black and White respondents (n = 403,231). Respondents' county of residence was linked to US Census information to obtain the county-level Index of Relative Rurality (IRR) and Census division. Crude and adjusted logistic regression models were utilized to assess the magnitude of Black-White disparities in having obesity (yes/no) by IRR quartile and by Census division.

Results

Overall, Black-White differences in obesity were wider in rural than in urban counties, with a significant linear trend (p < 0.001). Furthermore, when stratified by US Census division, results revealed that disparities were significantly wider in rural than urban areas for respondents living in the Middle Atlantic and South Atlantic divisions. In contrast, the association was reversed for the remaining divisions (New England, East North Central, West North Central, Mountain, and Pacific), where the magnitude of the Black-White difference was the largest in urban areas.

Conclusion

Findings highlight the need to understand and account for critical place-based factors that exacerbate racial obesity disparities to develop and maximize the effectiveness of policies and programs designed to reduce racial inequalities and improve population health.

Characterization and efficacy of lifestyle behavior change interventions among adult rural cancer survivors: a systematic review

PURPOSE

Little is known about the intersection between age and rurality as characteristics that impact lifestyle behavior change for cancer survivors. This review aims to summarize the current literature on lifestyle behavior change interventions conducted among rural survivors of cancer, with an emphasis on older survivors.

METHODS

A systematic search of five databases identified randomized controlled trials and controlled clinical trials that targeted diet, physical activity, alcohol consumption, or tobacco use change in adult cancer survivors living in rural areas of the world.

RESULTS

Eight studies met the inclusion criteria. Most studies were conducted in either Australia or the USA, included survivors at least 6 weeks post-treatment, and half included only breast cancer survivors, while the other four included a mix of cancer types. All but one had a physical activity component. No articles addressed changes in alcohol or tobacco behavior. Seven (87.5%) had a fully remote or hybrid delivery model. Most of the physical activity interventions showed significant changes in physical activity outcomes, while the dietary interventions showed changes of clinical but not statistical significance.

CONCLUSIONS

Few studies have been conducted to implement and evaluate the effectiveness of lifestyle behavior change interventions among older rural survivors of cancer. Future research should evaluate the acceptability and relevancy of adapted, evidence-based intervention with this population.

IMPLICATIONS FOR CANCER SURVIVORS

Effective diet and physical activity interventions exist, albeit limited in terms of effective lifestyle behavior change intervention tailored to older, rural survivors of cancer, particularly in relation to alcohol and tobacco behaviors.

Dietary Pattern Indicators among Healthy and Unhealthy Weight Adolescents Residing in Different Contexts across the Otago Region, New Zealand

Reported obesity rates for adolescents in different urban and rural areas are inconsistent. We examined indicators of healthy and unhealthy dietary patterns among 1863 adolescents aged 13-18 years with a healthy or excess body weight attending 23 secondary schools in four different settlement types across the Otago region, New Zealand. An online survey included demographics and dietary behaviours. Height and weight were measured, and body mass index was calculated. New Zealand defined urban and rural settlement types were used. Home addresses determined a small area-level index of deprivation. Data were analysed using Chi-square tests and ANOVA. A logistic model was fitted to estimate adjusted odds ratios of excess weight. The proportion of adolescents with a healthy weight differed (p < 0.001) between the most (64.9%) and least (76.4%) deprived neighbourhood areas. There was only indicative evidence of differences between settlement types (p = 0.087). Sugar-sweetened beverage and fast-food consumption was more frequent in the most deprived areas (p < 0.001), and in urban versus rural settlements (p < 0.001). The most important associations with excess weight were area-level deprivation and ethnicity, but not settlement type. Prioritising socioeconomic factors irrespective of settlement type is necessary when developing interventions to improve dietary patterns and body weight status among adolescents.

Sociodemographic and behavioural risk factors for obesity among community-dwelling older adults in Ghana and Nigeria: A secondary analysis of data from the SIREN study

OBJECTIVES

To explore the prevalence and risk factors of obesity among older adults from low- and middle-income countries (LMICs).

METHODS

This is a secondary analysis of data obtained from the SIREN study through in-person interviews and measurements from healthy stroke-free older adults (≥60 years). Overweight/obesity was defined as body mass index ≥25 kg/m². Abdominal obesity was defined as waist-to-hip ratio (WHR) of >0.90 for males and >0.85/females or waist circumference (WC) of >102 cm for males/>88 cm for females. Adjusted odds ratio (aORs) with 95% confidence interval (CIs) of the relationship between obesity and sociodemographic factors were assessed at P < 0.05.

RESULTS

Overall, 47.5% of participants were overweight/obese, 76.6% had a larger than recommended WHR, and 54.4% had a larger than recommended WC. Abdominal obesity (WC; aOR: 9.43, CI: 6.99-12.50), being a Nigerian (aOR: 0.55; CI: 0.42-0.72), living in an urban setting (aOR: 1.92; CI: 1.49-2.46), earning >$100/month (aOR: 1.53; CI: 1.19-1.96), and having formal education (aOR: 1.42; CI: 1.08-1.87) were associated with overweight/obesity.

CONCLUSION

Living in urban settings, earning a higher income, and having a formal education were associated with a higher odds of obesity among older adults from LMICs.

Rural and socioeconomic differences in the effectiveness of the HEART Pathway accelerated diagnostic protocol

BACKGROUND

The HEART Pathway is a validated accelerated diagnostic protocol (ADP) for patients with possible acute coronary syndrome (ACS). This study aimed to compare the safety and effectiveness of the HEART Pathway based on patient rurality (rural vs. urban) or socioeconomic status (SES).

METHODS

We performed a preplanned subgroup analysis of the HEART Pathway Implementation Study. The primary outcomes were death or myocardial infarction (MI) and hospitalization at 30 days. Proportions were compared by SES and rurality with Fisher's exact tests. Logistic regression evaluated for interactions of ADP implementation with SES or rurality and changes in outcomes within subgroups.

RESULTS

Among 7245 patients with rurality and SES data, 39.9% (2887/7245) were rural and 22.2% were low SES (1607/7245). The HEART Pathway identified patients as low risk in 32.2% (818/2540) of urban versus 28.1% (425/1512) of rural patients (p = 0.007) and 34.0% (311/915) of low SES versus 29.7% (932/3137) high SES patients (p = 0.02). Among low-risk patients, 30-day death or MI occurred in 0.6% (5/818) of urban versus 0.2% (1/425) rural (p = 0.67) and 0.6% (2/311) with low SES versus 0.4% (4/932) high SES (p = 0.64). Following implementation, 30-day hospitalization was reduced by 7.7% in urban patients (adjusted odds ratio [aOR] 0.76, 95% confidence interval [CI] 0.66-0.87), 10.6% in low SES patients (aOR 0.68, 95% CI 0.54-0.86), and 4.5% in high SES patients (aOR 0.83, 95% CI 0.73-0.94). However, rural patients had a nonsignificant 3.3% reduction in hospitalizations.

CONCLUSIONS

HEART Pathway implementation decreased 30-day hospitalizations regardless of SES and for urban patients but not rural patients. The 30-day death or MI rate was similar among low-risk patients.

Social Determinants of Cardiovascular Health: A Longitudinal Analysis of Cardiovascular Disease Mortality in US Counties From 2009 to 2018

Background Disparities in cardiovascular disease (CVD) outcomes persist across the United States. Social determinants of health play an important role in driving these disparities. The current study aims to identify the most important social determinants associated with CVD mortality over time in US counties. Methods and Results The authors used the Agency for Healthcare Research and Quality's database on social determinants of health and linked it with CVD mortality data at the county level from 2009 to 2018. The age-standardized CVD mortality rate was measured as the number of deaths per 100 000 people. Penalized generalized estimating equations were used to select social determinants associated with county-level CVD mortality. The analytic sample included 3142 counties. The penalized generalized estimating equation identified 17 key social determinants of health including rural-urban status, county's racial composition, income, food, and housing status. Over the 10-year period, CVD mortality declined at an annual rate of 1.08 (95% CI, 0.74-1.42) deaths per 100 000 people. Rural counties and counties with a higher percentage of Black residents had a consistently higher CVD mortality rate than urban counties and counties with a lower percentage of Black residents. The rural-urban CVD mortality gap did not change significantly over the past decade, whereas the association between the percentage of Black residents and CVD mortality showed a significant diminishing trend over time. Conclusions County-level CVD mortality declined from 2009 through 2018. However, rural counties and counties with a higher percentage of Black residents continued to experience higher CVD mortality. Median income, food, and housing status consistently predicted higher CVD mortality.

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.

Rural depopulation and the rural-urban gap in cognitive functioning among older adults

PURPOSE

As the population ages, the number of people with cognitive impairment will rapidly increase. Although previous research has explored the rural-urban gap in physical health, few studies have analyzed cognitive health. The purpose of this study was to examine rural-urban differences in cognitive health, with a focus on the moderating effect of population decline.

METHODS

The study used individual-level nationally representative data from the 2000-2016 waves of the Health and Retirement Study (N = 152,444) merged to county-level contextual characteristics. Hierarchical linear models were used to predict the cognitive functioning of US adults aged 50 and over by rural-urban residence, county depopulation, and their interactions while controlling for individual-level and county-level demographic and contextual factors.

FINDINGS

Older adults living in rural counties had lower cognitive functioning than urban adults. The interaction between living in a rural and depopulated county was statistically significant (P < .001). The rural penalty in cognitive functioning was 40% larger for those who lived in counties that lost population between 1980 and 2010 compared to those who lived in stable or growing rural counties. These results were independent of race-ethnicity, gender, age, education, income, region, employment status, marital status, physical health, and depression as well as the county's racial-ethnic composition, age structure, economic and educational disadvantage, and health care shortages.

CONCLUSIONS

The results have important implications for those seeking to reduce health disparities both between rural and urban older adults and among different groups of rural people. Interventions targeting those living in rural depopulating areas are particularly warranted.

Association Between Neighborhood Factors and Adult Obesity in Shelby County, Tennessee: Geospatial Machine Learning Approach

Background

Obesity is a global epidemic causing at least 2.8 million deaths per year. This complex disease is associated with significant socioeconomic burden, reduced work productivity, unemployment, and other social determinants of health (SDOH) disparities.

Objective

The objective of this study was to investigate the effects of SDOH on obesity prevalence among adults in Shelby County, Tennessee, the United States, using a geospatial machine learning approach.

Methods

Obesity prevalence was obtained from the publicly available 500 Cities database of Centers for Disease Control and Prevention, and SDOH indicators were extracted from the US census and the US Department of Agriculture. We examined the geographic distributions of obesity prevalence patterns, using Getis-Ord Gi* statistics and calibrated multiple models to study the association between SDOH and adult obesity. Unsupervised machine learning was used to conduct grouping analysis to investigate the distribution of obesity prevalence and associated SDOH indicators.

Results

Results depicted a high percentage of neighborhoods experiencing high adult obesity prevalence within Shelby County. In the census tract, the median household income, as well as the percentage of individuals who were Black, home renters, living below the poverty level, 55 years or older, unmarried, and uninsured, had a significant association with adult obesity prevalence. The grouping analysis revealed disparities in obesity prevalence among disadvantaged neighborhoods.

Conclusions

More research is needed to examine links between geographical location, SDOH, and chronic diseases. The findings of this study, which depict a significantly higher prevalence of obesity within disadvantaged neighborhoods, and other geospatial information can be leveraged to offer valuable insights, informing health decision-making and interventions that mitigate risk factors of increasing obesity prevalence.

Reducing New Ileostomy Readmissions in a Rural Health Care Setting: A Quality Improvement Initiative

BACKGROUND

Readmission after ileostomy creation continues to be a major cause of morbidity with rates ranging from 15% to 30% due to dehydration and obstruction. Rural environments pose an added risk of readmission due to larger travel distances and lack of consistent home health services.

OBJECTIVE

This study aimed to reduce ileostomy-related readmission rates in a rural academic medical center.

DESIGN

This is a rapid cycle quality improvement study.

SETTING

This single-center study was conducted in a rural academic medical center.

PATIENTS

Colorectal surgery patients receiving a new ileostomy were included in this study.

INTERVENTIONS

Improvement initiatives were identified through Plan-Do-Study-Act cycles (enhanced team continuity, standardized rehydration, nursing/staff education).

MAIN OUTCOME MEASURES

Thirty-day readmission, average length of stay, and average time to readmission served as main outcome measures.

RESULTS

Roughly equal rates of ileostomy were created in each time point, consistent with a tertiary care colorectal practice. The preimplementation readmission rate was 29%. Over the course of the entire quality improvement initiative, re-admission rates decreased by more than 50% (29% to 14%). PDSA cycle 1, which involved integrating a service-specific physician assistant to the team, allowed for greater continuity of care and had the most dramatic effect, decreasing rates by 27.5% (29% to 21%). Standardization of oral rehydration therapy and the implementation of a patient-directed intake/output sheet during PDSA cycle 2 resulted in further improvement in readmission rates (21% to 15%). Finally, implementation of nurse and physician assistant (PA)-driven patient education on fiber supplementation resulted in an additional yet nominal decrease in readmissions (15% to 14%). Latency to readmission also significantly increased throughout the study period.

LIMITATIONS

This study was limited by its small sample size in a single-center study.

CONCLUSION

Implementation of initiatives targeting enhanced team continuity, the standardization of rehydration therapies, and improved patient education decreased readmission rates in patients with new ileostomies. Rural centers, where outpatient resources are not as readily available or accessible, stand to benefit the most from these types of targeted interventions to decrease readmission rates. See Video Abstract at http://links.lww.com/DCR/B771.

REDUCCIN EN LAS READMISIONES POR ILEOSTOMAS NE MEDIOS DE ATENCIN MDICA RURAL INICIATIVA DE MEJORA EN LA CALIDAD

ANTECEDENTES:La readmisión después de la creación de una ileostomía sigue siendo una de las principales causas de morbilidad con tasas que oscilan entre el 15% y el 30% debido a la deshidratación y la oclusión. Un entorno rurale presenta un riesgo adicional de readmisión debido a las mayores distancias de viaje y la falta de servicios de salud domiciliarios adecuados.OBJETIVO:Reducir las tasas de reingreso por ileostomía en un centro médico académico rural.DISEÑO:Estudio de mejoría de la calidad de ciclo rápido.AJUSTE:Estudio unicéntrico en una unidad de servicio médico académico rural.PACIENTES:Pacientes de cirugía colorrectal a quienes se les confeccionó una ileostomía.INTERVENCIONES:Iniciativas de mejoría identificadas a través de los ciclos Planificar-Hacer-Estudiar-Actuar (Continuidad del equipo mejorada, rehidratación estandarizada, educación de enfermería / personal).PRINCIPALES MEDIDAS DE RESULTADO:30 días de readmisión, duración media de la estadía hospitalaria, tiempo medio de reingreso.RESULTADOS:Se crearon tasas aproximadamente iguales de ileostomías un momento dado de tiempo, subsecuentes en la práctica colorrectal de atención terciaria. La tasa de readmisión previa a la implementación del estudio fue del 29%. En el transcurso de toda la iniciativa de mejoría en la calidad, las tasas de readmisión disminuyeron en más del 50% (29% a 14%). El ciclo 1 de PDSA, que implicó la integración en el equipo de un asistente médico específico, lo que permitió una mayor continuidad en la atención y tuvo el mayor efecto disminuyendo las tasas en un 27,5% (29% a 21%). La estandarización de una terapia de rehidratación oral y la implementación de una hoja de ingresos / perdidas dirigida al paciente durante el ciclo 2 de PDSA resultó en una mejoría adicional en las tasas de readmisión (21% a 15%). Finalmente, la implementación de la educación del paciente impulsada por enfermeras y AF sobre el consumo suplementario de dietas con fibra dio como resultado una disminución adicional, aunque nominal, de las readmisiones (15% a 14%). La latencia hasta la readmisión también aumentó significativamente durante el período de estudio.LIMITACIONES:Estudio de un solo centro con un muestreo de pequeño tamaño.CONCLUSIONES:La implementación de iniciativas dirigidas a mejorar la continuidad en el equipo, la estandarización de las terapias de rehidratación y la mejoría en la información de los pacientes disminuyeron las tasas de readmisión en todos aquellas personas con nuevas ileostomías. Los centros rurales, donde los recursos para pacientes ambulatorios no están tan fácilmente disponibles o accesibles, son los que más beneficiaron de este tipo de intervenciones específicas para reducir las tasas de readmisión. Consulte Video Resumen en http://links.lww.com/DCR/B771. (Traducción-Dr. Xavier Delgadillo).

System- and Individual-Level Barriers to Accessing Medical Care Services Across the Rural-Urban Spectrum, Washington State

Background:

Residents of rural areas face barriers beyond geography and distance when accessing medical care services. The purpose of this study was to characterize medical care access barriers across several commonly used classifications of rurality.

Methods:

Washington State household residents completed a mixed-mode (paper/online) health care access survey between June 2018 and December 2019 administered to a stratified random sample of ZIP codes classified as urban, suburban, large rural, and small rural (4-tier scheme). For analyses, rurality was also classified into 2-tier schemes (rural/urban) based on ZIP code and county. Respondents reported availability of medical care services and system- and individual-level barriers to accessing services. Logistic regression models estimated the odds of reporting system- or individual-level barriers in accessing medical care services across rurality (4- and 2-tier schemes), adjusting for respondent characteristics, and weighted to account for survey design.

Results:

About 617 households completed the survey (25.7% response rate). Compared to urban residents (across all 3 schemes), more rural residents reported traveling to a distant city or town for medical care (P < .001). Rurality was significantly associated with increased odds of facing system-level barriers. Respondents from small rural areas had greater odds access barriers for primary care (OR 7.31, 95% CI 1.84-29.09) and having no primary care provider (OR 11.37, 95% CI 3.03-42.75) compared to urban respondents. Individual-level barriers were not associated with rurality.

Conclusions:

To improve healthcare access across the rural-urban spectrum, policymakers must consider system-level barriers facing rural populations.

Cancer Screening among Rural People Who Use Drugs: Colliding Risks and Barriers

Rural cancer disparities are associated with lesser healthcare access and screening adherence. The opioid epidemic may increase disparities as people who use drugs (PWUD) frequently experience healthcare-associated stigmatizing experiences which discourage seeking routine care. Rural PWUD were recruited to complete surveys and interviews exploring cancer (cervical, breast, colorectal, lung) risk, screening history, and healthcare experiences. From July 2020–July 2021 we collected 37 surveys and 8 interviews. Participants were 24.3% male, 86.5% White race, and had a mean age of 44.8 years. Females were less likely to report seeing a primary care provider on a regular basis, and more likely to report stigmatizing healthcare experiences. A majority of females reporting receiving recommendations and screens for cervical and breast cancer, but only a minority were adherent. Similarly, only a minority of males and females reported receiving screening tests for colorectal and lung cancer. Screening rates for all cancers were substantially below those for the US generally and rural areas specifically. Interviews confirmed stigmatizing healthcare experiences and suggested screening barriers and possible solutions. The opioid epidemic involves millions of individuals and is disproportionately experienced in rural communities. To avoid exacerbating existing rural cancer disparities, methods to engage PWUD in cancer screening need to be developed.

Rural Latino health and the built environment: a systematic review

Objective: This study systematically reviewed literature examining the influence of the rural built environment on Latinos' health outcomes and behaviour in the United States. A secondary aim of the study was to identify strategies developed to address challenges in the rural built environment affecting Latinos' health.Design: This study followed the reporting guidelines set forth by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. Articles included in the final analysis clearly linked Latino health outcomes to characteristics of the rural built environment.Results: Of the nearly 2,500 articles identified in the initial search, the final review included approximately 146 full-text sources. The majority of the articles focused on aspects of Latinos' physical (n = 68), behavioural (n = 43), and mental health (n = 23).Conclusions: Rural Latino neighbourhoods in the United States possess limited access to health care, internet, transportation, and recreation infrastructure, which negatively impacts health outcomes and behaviours. Strategies developed to mitigate these issues include but are not limited to: the use of telecommunications to distribute health information; the use of community health workers and mobile clinics to increase awareness and availability of select health services; the use of worksite trainings and adaptations to the workplace; and the promotion of safety net programmes, such as the Supplemental Nutrition Programme for Women, Infants and Children (WIC). This review supports the need for a more robust research agenda documenting the health experiences of rural Latinos of various nationalities, age groups, and genders.

Differences in Loneliness Across the Rural-Urban Continuum Among Adults Living in Washington State

PURPOSE

Rural residents may be at higher risk for loneliness than urban residents due to factors such as social isolation, poorer health, and socioeconomic disadvantage. To date, there have been few studies examining rural-urban differences in loneliness among adults in the United States. We examined differences in loneliness across the rural-urban continuum among adult residents living in Washington State.

METHODS

Stratified random sampling was used to select 2,575 adults from small rural, large rural, suburban, and urban areas who were invited to complete a survey on factors affecting health. Data were obtained from 616 adults (278 from small rural, 100 from large rural, 98 from suburban, and 140 from urban areas) from June 2018 through October 2019. Loneliness was measured using the UCLA Loneliness Scale (3rd version). Multivariable linear and logistic regressions were used to examine geographic differences in loneliness (measured continuously and dichotomously).

FINDINGS

Mean unadjusted loneliness scores were lower in suburban compared to urban areas (35.06 vs 38.57, P = .03). The prevalence of loneliness was 50.7%, 59.0%, 40.8%, and 54.3% in small rural, large rural, suburban, and urban areas, respectively. Suburban living was associated with lower odds for being lonely compared to urban living (unadjusted OR = 0.58; 95% CI = 0.34-0.98), but this association was not statistically significant in the adjusted model (OR = 0.63; 95% CI = 0.33-1.19).

CONCLUSION

Loneliness is a prevalent health issue across the rural-urban continuum among Washington State adults.

A cross-sectional, exploratory survey on health-relevant free-time activities and body mass index in preschool children in urban and rural settings of Austria

BACKGROUND

The increasing prevalence of obesity is among the most relevant healthcare issues in Europe. The number of overweight people rises due to lifestyle changes, increased sitting activities, and less physical activity. Prevention in early childhood is paramount to stop this alarming trend.

AIM

This study primarily aimed to evaluate the average time children (3-5 years) from rural and urban Austrian regions spent engaging in physical activity and sedentary behaviors in their free-time. Additionally, we investigated the potential correlation between duration and habits of free-time activity or place of residence and age- and sex-specific body mass index (BMI). The potential impact of socio-economic factors on BMI was examined.

METHODS

Urban (Vienna) and rural (Carinthia) regions of Austria were chosen for this observational cross-sectional study. Preschool children (n=130) attending nurseries in these regions were included. Weight and height were measured and BMI calculated. Free-time activity and socio-economic data were asked using a self-administered questionnaire. Data on sedentary behavior time (sedentary activity and media consumption) and physical activity time (defined as organized or spontaneous exercise) were analyzed using non-parametric tests.

RESULTS

Preschool children spent approximately as many hours of their free-time engaged in physical activity as in sedentary behaviors. Time trend in media consumption amounts to one-third of the cumulative time spent engaging in sedentary behaviors. Preschoolers from the urban area spent fewer hours practicing organized exercise and more in sedentary behaviors than peers in the rural area. In the selected areas, 7 % of preschoolers were overweight, 3.9 % were obese. BMI was not associated with free-time activities but showed a trendwise negative correlation with organized exercise. A positive correlation of age and organized exercise was observed but not with physical activity per se.

CONCLUSIONS

Our results confirm the necessity of preventive interventions among Austrian preschoolers and lead to a better understanding of their free-time activities. Further investigations with larger study populations are needed to promote effective childhood obesity prevention and examine the differences regarding obesity prevalence and leisure-time activity between rural and urban areas.

The Compounding Effect of Rurality on Health Disparities Among Black Patients with COVID-19

BACKGROUND

West Virginia had garnered national attention for its vaccination rollout against coronavirus 2019 (COVID-19). Outcomes of this mostly rural population, however, have been underreported. As the pandemic continues, identifying high risk populations remains important to further epidemiologic information and target vaccines.

PURPOSE

The objective of this study is to examine the effects of COVID-19 and the influence of race and rurality on hospitalization and outcomes in Appalachians.

METHODS

In this retrospective study, data from patients who tested positive and were admitted for COVID-19 and seen within the state's largest health system (West Virginia University Health System) between March 18 and September 16, 2020 were analyzed. Cases were stratified into rural or urban based on rural urban continuum codes (RUCCs) and by race into 'white,' 'black,' or 'other.' Associations between rurality, rurality and race, and outcomes were assessed.

RESULTS

A total of 2011 adult West Virginians tested positive, of which 8.2% were hospitalized. Of the hospitalized patients, 33.5% were rural and 11.6% were black. Rural black patients were three times more likely (OR: 3.33; 95%CI:1.46-7.60) to be admitted. Rural blacks were also more likely to have a history of obstructive pulmonary disease (OR: 2.73; 1.24-6.01), hypertension (OR: 2.78; 1.38-5.57), and multiple chronic conditions (3.04; 1.48-6.22).

IMPLICATIONS

Rural blacks were more likely to have risk factors for severe COVID-19 influencing their increased risk of hospitalization. These findings support that race as a risk factor for severe COVID-19 is compounded by rurality and identifies an important target group for vaccination.

Social Determinants of Health and Adverse Outcomes in Adolescent Pregnancies

The association between adolescent childbearing and adverse maternal and birth outcomes has been well documented. Adverse adolescent pregnancy outcomes are associated with substantial risk of long-term morbidities for the young mother and their newborns. Multiple levels of social disadvantage have been related to adverse pregnancy outcomes among adolescent mothers. Patterns of cumulative social adversity define the most marginalized group of adolescents at the highest risk of experiencing adverse maternal and birth outcomes. Using a social determinants of health (SDOH) framework, we present an overview of the current scientific evidence on the influence of these conditions on adolescent pregnancy outcomes. Multiple SDOH such as residence in remote areas, low educational attainment, low socioeconomic status, and lack of family and community support have been linked with increased risk of adverse pregnancy outcomes among adolescents. Based on the PROGRESS-Plus equity framework, this review highlights some SDOH aspects that perinatal health researchers, clinicians, and policy makers should consider in the context of adolescent pregnancies. There is a need to acknowledge the intersectional nature of multiple SDOH when formulating clinical and societal interventions to address the needs of the most marginalized adolescent in this critical period of life.

Development of a School-Based Physical Activity Intervention Using an Integrated Approach: Project SMART

Physical activity (PA) is a health-protective factor with multiple benefits for school-age children, yet only 22% of children and adolescents living in the United States (United States) accrue the recommended amount of moderate to vigorous PA. Given the prevalence of insufficient PA among children, promoting and providing PA opportunities during the school day, especially when integrated into the curriculum and linked to the learning standards, is essential for children. The purpose of this paper is to describe the procedure for the development of a school-based PA program using an integrated approach through the modified intervention mapping protocol (IMP). A total of 22 physical education teachers and 167 children from five different elementary schools were involved in the process. The procedure includes the Self-Determination Theory (SDT) that provides a theoretical framework that plays a vital role in motivating students to have a physically active lifestyle. This study applied SDT and IMP to develop and pilot a PA intervention called Project SMART using an integrative community participatory approach. As a pilot PA intervention, Project SMART is an online educational game where the students navigate a virtual journey across the United States A class’s aggregate PA propels the students on their journey, where standards-based modules are unlocked to achieve STEM (science, technology, engineering, and math) and social-emotional learning outcomes while gaining an understanding of the importance of health behaviors and opportunities to habitually engage in healthy decision-making with the support of their peers. Although initially labor intensive for the researchers, the process of tailoring the intervention to the children’s contextual and cultural needs has implications for all theoretically grounded and evidence-based PA interventions.

Investigating Rurality as a Risk Factor for State and Trait Hopelessness in Hospitalized Patients With Ischemic Heart Disease

Background

Rurality and hopelessness are each associated with increased mortality in adults with ischemic heart disease (IHD), yet there is no known research examining rurality as a risk factor for hopelessness in patients with IHD. This study evaluated rurality as a risk factor for state and trait hopelessness in adults hospitalized with IHD in samples drawn from the Great Lakes and Great Plains regions of the United States.

Methods and Results

A descriptive cross‐sectional design was used. Data were collected from 628 patients hospitalized for IHD in the Great Lakes (n=516) and Great Plains (n=112). Rural–Urban Commuting Area codes were used to stratify study participants by level of rurality. Levels of state hopelessness (measured by the State‐Trait Hopelessness Scale) were higher in rural patients (58.8% versus 48.8%; odds ratio [OR], 1.50; 95% CI, 1.03–2.18), a difference that remained statistically significant after adjusting for demographics, depression severity (measured by the Patient Health Questionnaire–8), and physical functioning (measured by the Duke Activity Status Index; OR, 1.59; 95% CI, 1.06–2.40; P=0.026). There was evidence of an interaction between marital status and rurality on state hopelessness after accounting for covariates (P=0.02). Nonmarried individuals had an increased prevalence of state hopelessness (nonmarried 72.0% versus married 52.0%) in rural areas (P=0.03).

Conclusions

Rural patients with IHD, particularly those who are nonmarried, may be at higher risk for state hopelessness compared with patients with IHD living in urban settings. Understanding rurality differences is important in identifying subgroups most at risk for hopelessness.

Registration

URL: http://www.clinicaltrials.gov. Unique identifier: NCT04498975.

Income Inequality and Obesity among US Adults 1999-2016: Does Sex Matter?

Obesity is a major public health problem that varies by income and sex, yet there is little evidence to determine the association between income inequality and obesity. We examined the association between income and obesity in adults ages 20 years and older and tested whether this relationship differs by sex in the United States. We used the 1999-2016 National Health and Nutrition Examination Survey (NHANES). We defined obesity if the body mass index was ≥30 kg/m2, and calculated the Gini coefficient (GC) to measure income inequality by using the Poverty Income Ratio. We examined the association between income and obesity using a Modified Poisson regression in a sample of 36,665 adults. We adjusted the models according to age, racial/ethnic groups, marital status, education, health behaviors, health insurance, self-reported health, and household structure. The association between income and obesity was consistently more significant among middle-income quintile and higher-income quintile men than among lower-income quintile men. The same association was not found for women; women in the highest income quintile were less likely to suffer from obesity than among lower-income quintile women. Our results suggest that policymakers should consider strategies to reduce structural inequality and encourage access to healthy foods and community-supported agricultural programs as nutritional interventions in low-income population settings.

Urban-Rural Disparities in Vaccination Service Use Among Low-Income Adolescents

OBJECTIVE

To access urban-rural disparities in vaccination service use among Medicaid-enrolled adolescents and examine its association with residence county characteristics.

STUDY DESIGN

We used the 2016 Medicaid T-MSIS Analytic File to estimate adolescents' use of vaccination services, defined as the proportion of adolescents aged 11-18 years with ≥ 1 vaccination visit in a county. We used linear regression and the Oaxaca-Blinder decomposition method to examine the association between county characteristics and urban-rural disparities in vaccination service use.

RESULTS

The analysis included 2,473 counties located in 38 states. The mean proportion of adolescents making ≥ 1 vaccination visit at the county level was low (36.09%) and was lower in rural than in urban counties (31.99% vs. 36.85%, p < .01). The number of primary care physicians (PCPs) was positively associated with vaccination service use in rural counties; in urban counties, % of households without a vehicle was negatively associated with vaccination service use. The decomposition results showed that 66.78% (3.24 percentage points) of the urban-rural disparities in vaccination service use could be attributed to urban-rural differences in the county characteristics included in the study. Characteristics measuring access to care (number of PCPs), social and economic factors (% adults with at least a bachelor's degree and % children in poverty), quality of care (influenza vaccination rates and preventable hospital stays), and demographics (% non-Hispanic black, % Hispanic, and % females) played a role in urban-rural disparities.

CONCLUSIONS

Differences in county characteristics could partly explain the observed urban-rural disparities in vaccination service use among low-income adolescents.

The Burden of Obesity in the Rural Adult Population of America

There is an epidemic of obesity in adults in rural America. It is estimated that about 19% of the population resides in rural areas, which encompasses 97% of America's total landmass. Although rural America makes up a fraction of America's total population, it has been estimated that the prevalence of obesity is approximately 6.2 times higher than in urban America. This illustrates an apparent disparity that exists between the rural population and urban populations that needs to be examined. The prevalence of obesity, especially in rural America, is a growing concern in the medical community in recent years. Obesity has been identified as a significant risk factor for cardiovascular disease, cancer, and type 2 diabetes mellitus, which are leading causes of morbidity and mortality in the US. To better understand the disparity in the prevalence of adult obesity between rural and urban America, researchers have identified risk factors that are associated with the high incidence and prevalence of obesity in the rural American adult population. Low income and lack of physical activity have been identified as factors that predispose rural Americans to increased risk of obesity, arguing that low-income Americans may not have access to the resources available to assist them in weight reduction. With rural Americans being at an income disadvantage, it creates a risk for obesity, which further predisposes them to chronic diseases such as hypertension, obstructive sleep apnea (OSA), diabetes, and coronary artery disease. As obesity continues to rise among the American population, the burden on the rural population is incredibly evident. Despite ongoing efforts by the US government and strategies implemented by the Common Community Measures for Obesity Prevention, there is still much to be done to tackle the epidemic. With an existing strategy in place, such as the 12 Common Community Measures for Obesity Prevention (COCOMO) strategies to fight obesity with physical activity, Americans are a step closer to conquering this epidemic. However, until other disparities such as income are addressed, rural Americans may continue to be severely impacted by the rising incidence of obesity and subsequent higher mortality rates from associated diseases.

Monitoring Prediabetes Screening in Two Primary Care Offices in Rural Appalachia: A Quality Improvement Process

BACKGROUND

One-third of the U.S. population has prediabetes, but 90% remain undiagnosed because healthcare providers are not screening for this condition.

OBJECTIVE

The purpose of this quality improvement project was to monitor prediabetes screening and identification, and implement evidence-based recommendations including registered dietician referral.

METHODS

This project involved using an evidence-based screening tool to measure individual risk of prediabetes. Aggregate data was collected to evaluate screening implementation, evidence-based recommendations offered by providers, and assess patient risk factors.

RESULTS

The percentage of patients at risk for prediabetes was 41.3% (n = 111). The most frequent risks were identified as overweight, history of hypertension, family history of type 2 diabetes mellitus (T2DM), and older age. Providers offered education on weight loss 68.5% (n = 76) and exercise 76.6% (n = 85) but referred 33.3% (n = 37) patients for nutrition education. The screening rates were 52.3% (n = 176) and 72.5% (n = 244) in clinics A and B respectively.

CONCLUSIONS

A gap remains in using evidence-based recommendations to decrease risk of prediabetes. Prediabetes screening identified a greater percentage of persons in this population.

IMPLICATIONS FOR NURSING

There is a need for consistent practice of evidence-based recommendations. This project set the benchmark for future efforts to educate, encourage, and measure providers successes.

Association of community types and features in a case-control analysis of new onset type 2 diabetes across a diverse geography in Pennsylvania

OBJECTIVES

To evaluate associations of community types and features with new onset type 2 diabetes in diverse communities. Understanding the location and scale of geographic disparities can lead to community-level interventions.

DESIGN

Nested case-control study within the open dynamic cohort of health system patients.

SETTING

Large, integrated health system in 37 counties in central and northeastern Pennsylvania, USA.

PARTICIPANTS AND ANALYSIS

We used electronic health records to identify persons with new-onset type 2 diabetes from 2008 to 2016 (n=15 888). Persons with diabetes were age, sex and year matched (1:5) to persons without diabetes (n=79 435). We used generalised estimating equations to control for individual-level confounding variables, accounting for clustering of persons within communities. Communities were defined as (1) townships, boroughs and city census tracts; (2) urbanised area (large metro), urban cluster (small cities and towns) and rural; (3) combination of the first two; and (4) county. Community socioeconomic deprivation and greenness were evaluated alone and in models stratified by community types.

RESULTS

Borough and city census tract residence (vs townships) were associated (OR (95% CI)) with higher odds of type 2 diabetes (1.10 (1.04 to 1.16) and 1.34 (1.25 to 1.44), respectively). Urbanised areas (vs rural) also had increased odds of type 2 diabetes (1.14 (1.08 to 1.21)). In the combined definition, the strongest associations (vs townships in rural areas) were city census tracts in urban clusters (1.41 (1.22 to 1.62)) and city census tracts in urbanised areas (1.33 (1.22 to 1.45)). Higher community socioeconomic deprivation and lower greenness were each associated with increased odds.

CONCLUSIONS

Urban residence was associated with higher odds of type 2 diabetes than for other areas. Higher community socioeconomic deprivation in city census tracts and lower greenness in all community types were also associated with type 2 diabetes.

Rural Community Engagement for Health Disparities Research: The Unique Role of Historically Black Colleges and Universities (HBCUs)

Reducing health disparities in rural communities of color remains a national concern. Efforts to reduce health disparities often center on community engagement, which is historically the strategy used to provide rural minority populations with support to access and utilize health information and services. Historically Black Colleges and Universities (HBCUs), with their origins derived from social injustices and discrimination, are uniquely positioned to conduct this type of engagement. We present the "Research with Care" project, a long-standing positive working relationship between North Carolina Central University (NCCU) and rural Halifax County, North Carolina, demonstrating an effective campus-community partnership. The importance of readiness to implement Community-based Participatory Research (CBPR) principles is underscored. As demonstrated by the NCCU-Halifax partnership, we recommend leveraging the positive associations of the HBCU brand identity as a method of building and sustaining meaningful relationships with rural Black communities. This underscores the role and value of HBCUs in the health disparities research arena and should be communicated and embraced.

Rural-urban differences in meeting physical activity recommendations and health status in cancer survivors in central Pennsylvania

PURPOSE

This study explored rural-urban differences in meeting physical activity (PA) recommendations and health status in cancer survivors in central Pennsylvania and associations between PA and health status.

METHODS

Cancer survivors (N = 2463) were identified through a state cancer registry and mailed questionnaires assessing PA and health status. Rural-urban residence was based on county of residence at diagnosis. Participants self-reported frequency and duration of leisure-time PA and were classified as meeting: (1) aerobic recommendations (≥ 150 min/week), (2) muscle-strengthening recommendations (≥ 2 times/week), (3) both aerobic and muscle-strengthening recommendations, or (4) neither recommendation. Logistic regression models examined associations between rural-urban residence and meeting PA recommendations and associations between PA and health status, adjusting for age, cancer type, gender, and income.

RESULTS

Nearly 600 (N = 591, 24.0%) cancer survivors returned completed questionnaires (rural 9.5%, urban 90.5%). Half (50.0%) of rural cancer survivors reported no leisure-time PA compared to 35.2% of urban cancer survivors (p = 0.020), and urban cancer survivors were 2.6 times more likely to meet aerobic PA recommendations (95% CI 1.1-6.4). Odds of reporting good physical and mental health were 2.3 times higher among survivors who reported meeting aerobic recommendations compared to those who did not meet PA recommendations (95% CI 1.1-4.5), adjusting for rurality and covariates.

CONCLUSIONS

Results demonstrate persistent rural-urban differences in meeting PA recommendations in cancer survivors and its association with self-reported health.

IMPLICATIONS FOR CANCER SURVIVORS

Findings underscore the need for interventions to increase PA in rural cancer survivors in an effort to improve health status and reduce cancer health disparities.

Cancer screening utilization by residence and sexual orientation

PURPOSE

Although few studies have examined screening uptake among sexual minorities (lesbian, gay, bisexual, queer), almost none have examined it in the specific context of rural populations. Therefore, our objective was to assess how cancer screening utilization varies by residence and sexual orientation.

METHODS

Publicly available population-level data from the 2014 and 2016 Behavioral Risk Factor Surveillance System were utilized. Study outcomes included recommended recent receipt of breast, cervical, and colorectal cancer screening. Independent variables of interest were residence (rural/urban) and sexual orientation (heterosexual/gay or lesbian/bisexual). Weighted proportions and multivariable logistic regressions were used to assess the association between the independent variables and the outcomes, adjusting for demographic, socioeconomic, and healthcare utilization factors.

RESULTS

Rates for all three cancer screenings were lowest in rural areas and among sexual minority populations (cervical: rural lesbians at 64.8% vs. urban heterosexual at 84.6%; breast: rural lesbians at 66.8% vs. urban heterosexual at 80.0%; colorectal for males: rural bisexuals at 52.4% vs. urban bisexuals at 81.3%; and colorectal for females: rural heterosexuals at 67.2% vs. rural lesbians at 74.4%). In the multivariate analyses for colorectal screening, compared to urban heterosexual males, both rural gay and rural heterosexual males were less likely to receive screening (aOR = 0.45; 95% = 0.24-0.73 and aOR = 0.79; 95% = 0.72-0.87, respectively) as were rural heterosexual females (aOR = 0.87; 95% = 0.80-0.94) compared to urban heterosexual females. For cervical screening, lesbians were less likely to receive screening (aOR = 0.62; 95% = 0.41-0.94) than heterosexuals, and there were no differences for breast screening.

CONCLUSION

We found that rural sexual minorities may experience disparities in cancer screening utilization associated with the compounding barriers of rural residence and sexual minority status, after adjusting for demographic, socioeconomic, and healthcare utilization factors. Further work is needed to identify factors influencing these disparities and how they might be addressed.

Regional and Social Disparities for Obesity among Austrian Adults: Representative Long-term Trends from 1973-2014

STUDY AIM

To present regional long-term trends for the prevalence of obesity (BMI ≥ 30 kg/m²) among Austrian adults in Western, Central and Eastern Austria. Furthermore, the educational inequality regarding obesity was analysed in these regions in Austria for the investigation period.

METHODS

Self-reported data from six nationally representative, cross-sectional surveys (n=194,030) conducted between 1973 and 2014 were analysed. Absolute changes (AC) and Etiologic fractions (EF) were calculated to measure trends. The extent of social inequality was presented by the relative index of inequality (RII) based on the educational level.

RESULTS

Since 1973, a clear east to west gradient for obesity among adults in Austria has been observed. In 2014, the age-standardized prevalence was highest among Eastern Austrian adults (women: 16.9%; men: 18.2%). A constant increase in obesity among men has been visible since 1983. Since 2007, the values for women have stabilized, while the prevalence of obesity among female Austrians in Western and Central Austria decreased. Considering the AC for the prevalence of obesity from 1983 on, the highest increase was found among women (+2.60%) and men (+1.56%) in Eastern Austria. The outcomes regarding social inequality are instable on a regional level, with the highest RII observed in 2014 for Central Austria.

CONCLUSION

These study findings reveal significant regional differences in the prevalence of obesity in Austria and confirm the existence of an current east-west gradient in Austria for obesity. Considering the latest trends, especially men represent a risk group for obesity in the 3 regions.

Rural-Urban Variation in Weight Loss Recommendations Among US Older Adults with Arthritis and Obesity

Purpose: Weight loss is advantageous for individuals with obesity and arthritis. Therefore, this study was conducted to determine if there are differences by rural-urban status among older adults with these conditions who reported being advised by a health care provider to lose weight for arthritis or to ameliorate arthritis symptoms. Methods: A cross-sectional analysis of 2011 Behavioral Risk Factor Surveillance System (BRFSS) data. Respondents reported if they had been diagnosed with arthritis and if they received a provider weight loss recommendation (WLR). The analytic sample was limited to older adults aged 60⁻79 living in the five states that administered the examined BRFSS arthritis module who had body mass index ≥ 30 kg/m² and reported having arthritis (n = 2920). The respondent's county of residence was linked to the corresponding county-level population density from the US Decennial Census to determine rural-urban status. A generalized linear model examined the association between receipt of a WLR and population density, controlling for demographics. Results: The sample was 83.6% white, 57.8% female, and 63.2% received a WLR. Respondents from more urban counties were more likely to receive a WLR (p value for trend <0.001). Additionally, older respondents, men, individuals with less than a high school education, and whites had a decreased likelihood of receiving a WLR. Conclusions: The analysis identified notable rural-urban differences with respondents in more urban counties being more likely to receive a WLR. Furthermore, there were differences in those who received a WLR by age, sex, and education. Reasons for these differences should be explored.

Assessment of dietary patterns, physical activity and obesity from a national survey: Rural-urban health disparities in older adults

BACKGROUND

Obesity is a critical public health issue, affecting over one-third of all Americans, and is an underlying cause of numerous health issues across the lifespan. For older adults, obesity is linked to premature declines in physical and mental health and cognitive functioning. The occurrence of obesity and related health behaviors and chronic diseases are higher in rural areas than in urban areas. Furthermore, rural areas of the United States have a higher proportion of older adults than urban areas. Few studies, to date, have explored rural-urban differences in the relationships between dietary patterns and obesity among older adults. Therefore, the purpose of this study is to assess rural-urban differences in obesity rates in older adults, and the potential for the associations between obesity and physical activity and dietary patterns to vary by rural-urban status.

METHODS

Data were abstracted from respondents aged 65 and above from the 2012 Behavioral Risk Factor Surveillance System (BRFSS) database linked to Census-based county-level information on rural-urban status and socioeconomic status. Generalized linear models were utilized to assess rural-urban disparities in obesity, and the potential for associations between obesity and known risk factors (fruit consumption, green vegetable consumption and physical activity) to vary by rural-urban status, accounting for complex sampling and confounders.

RESULTS

Obesity rates were highest and fruit consumption was lowest in the most rural areas. However, for older adults in the most urban areas, there was a significant negative association between obesity and fruit and green vegetable consumption. This association was not observed in more rural older adults.

CONCLUSION

These findings underscore the need to take into account place-based factors such as rural-urban status, when designing and implementing policies and interventions designed to reduce obesity through risk factor mitigation in older adults. To reduce rural-urban disparities in older adults, all policies, programs, and interventions should address the unique barriers and needs specific to rural and urban older adults.

Geographic Disparities in Previously Diagnosed Health Conditions in Colorectal Cancer Patients Are Largely Explained by Age and Area Level Disadvantage

Background: Geographical disparity in colorectal cancer (CRC) survival rates may be partly due to aging populations and disadvantage in more remote locations; factors that also impact the incidence and outcomes of other chronic health conditions. The current study investigates whether geographic disparity exists amongst previously diagnosed health conditions in CRC patients above and beyond age and area-level disadvantage and whether this disparity is linked to geographic disparity in CRC survival.

Methods: Data regarding previously diagnosed health conditions were collected via computer-assisted telephone interviews with a cross-sectional sample of n = 1,966 Australian CRC patients between 2003 and 2004. Ten-year survival outcomes were acquired in December 2014 from cancer registry data. Multivariate logistic regressions were applied to test associations between previously diagnosed health conditions and survival rates in rural, regional, and metropolitan areas.

Results: Results suggest that only few geographical disparities exist in previously diagnosed health conditions for CRC patients and these were largely explained by socio-economic status and age. Living in an inner regional area was associated with cardio-vascular conditions, one or more respiratory diseases, and multiple respiratory diagnoses. Higher occurrences of these conditions did not explain lower CRC-specific 10 years survival rates in inner regional Australia.

Conclusion: It is unlikely that health disparities in terms of previously diagnosed conditions account for poorer CRC survival in regional and remote areas. Interventions to improve the health of regional CRC patients may need to target issues unique to socio-economic disadvantage and older age.

Differences in Obesity Prevalence by Demographic Characteristics and Urbanization Level Among Adults in the United States, 2013-2016

IMPORTANCE

Differences in obesity by sex, age group, race and Hispanic origin among US adults have been reported, but differences by urbanization level have been less studied.

OBJECTIVES

To provide estimates of obesity by demographic characteristics and urbanization level and to examine trends in obesity prevalence by urbanization level.

DESIGN, SETTING, AND PARTICIPANTS

Serial cross-sectional analysis of measured height and weight among adults aged 20 years or older in the 2001-2016 National Health and Nutrition Examination Survey, a nationally representative survey of the civilian, noninstitutionalized US population.

EXPOSURES

Sex, age group, race and Hispanic origin, education level, smoking status, and urbanization level as assessed by metropolitan statistical areas (MSAs; large: ≥1 million population).

MAIN OUTCOMES AND MEASURES

Prevalence of obesity (body mass index [BMI] ≥30) and severe obesity (BMI ≥40) by subgroups in 2013-2016 and trends by urbanization level between 2001-2004 and 2013-2016.

RESULTS

Complete data on weight, height, and urbanization level were available for 10 792 adults (mean age, 48 years; 51% female [weighted]). During 2013-2016, 38.9% (95% CI, 37.0% to 40.7%) of US adults had obesity and 7.6% (95% CI, 6.8% to 8.6%) had severe obesity. Men living in medium or small MSAs had a higher age-adjusted prevalence of obesity compared with men living in large MSAs (42.4% vs 31.8%, respectively; adjusted difference, 9.8 percentage points [95% CI, 5.1 to 14.5 percentage points]); however, the age-adjusted prevalence among men living in non-MSAs was not significantly different compared with men living in large MSAs (38.9% vs 31.8%, respectively; adjusted difference, 4.8 percentage points [95% CI, -2.9 to 12.6 percentage points]). The age-adjusted prevalence of obesity was higher among women living in medium or small MSAs compared with women living in large MSAs (42.5% vs 38.1%, respectively; adjusted difference, 4.3 percentage points [95% CI, 0.2 to 8.5 percentage points]) and among women living in non-MSAs compared with women living in large MSAs (47.2% vs 38.1%, respectively; adjusted difference, 4.7 percentage points [95% CI, 0.2 to 9.3 percentage points]). Similar patterns were seen for severe obesity except that the difference between men living in large MSAs compared with non-MSAs was significant. The age-adjusted prevalence of obesity and severe obesity also varied significantly by age group, race and Hispanic origin, and education level, and these patterns of variation were often different by sex. Between 2001-2004 and 2013-2016, the age-adjusted prevalence of obesity and severe obesity significantly increased among all adults at all urbanization levels.

CONCLUSIONS AND RELEVANCE

In this nationally representative survey of adults in the United States, the age-adjusted prevalence of obesity and severe obesity in 2013-2016 varied by level of urbanization, with significantly greater prevalence of obesity and severe obesity among adults living in nonmetropolitan statistical areas compared with adults living in large metropolitan statistical areas.

The Urban Gradient in Malaria-Endemic Municipalities in Acre: Revisiting the Role of Locality

Urbanization has altered the distribution of diseases of public health importance along gradients of human occupation. Adopting dichotomous urban/rural categories to explain differences in the risk of exposure, as well as the prevention of diseases is insufficient. In this paper, we present the potential of representations based on the gradient perspective to characterize the living spaces of municipalities where malaria is endemic in northwest Acre. Inventoried data in 40 localities in the Mâncio Lima and Rodrigues Alves municipalities and information on land use and land cover obtained from the TerraClass Database were used to characterize the urban spatial forms and their social content. Results showed a gradient of intensities: from municipal seats to the most connected localities through the road network to riverine communities. Based on the results, we hope to advance the discussion about the use of normative definitions of “urban” and “rural” for public policies and actions to control and eliminate malaria, considering the position of each locality in its own locally referenced urban gradient.

Rural-Urban Differences in Cancer Incidence and Trends in the United States

Background: Cancer incidence and mortality rates in the United States are declining, but this decrease may not be observed in rural areas where residents are more likely to live in poverty, smoke, and forego cancer screening. However, there is limited research exploring national rural-urban differences in cancer incidence and trends.Methods: We analyzed data from the North American Association of Central Cancer Registries' public use dataset, which includes population-based cancer incidence data from 46 states. We calculated age-adjusted incidence rates, rate ratios, and annual percentage change (APC) for: all cancers combined, selected individual cancers, and cancers associated with tobacco use and human papillomavirus (HPV). Rural-urban comparisons were made by demographic, geographic, and socioeconomic characteristics for 2009 to 2013. Trends were analyzed for 1995 to 2013.Results: Combined cancers incidence rates were generally higher in urban populations, except for the South, although the urban decline in incidence rate was greater than in rural populations (10.2% vs. 4.8%, respectively). Rural cancer disparities included higher rates of tobacco-associated, HPV-associated, lung and bronchus, cervical, and colorectal cancers across most population groups. Furthermore, HPV-associated cancer incidence rates increased in rural areas (APC = 0.724, P < 0.05), while temporal trends remained stable in urban areas.Conclusions: Cancer rates associated with modifiable risks-tobacco, HPV, and some preventive screening modalities (e.g., colorectal and cervical cancers)-were higher in rural compared with urban populations.Impact: Population-based, clinical, and/or policy strategies and interventions that address these modifiable risk factors could help reduce cancer disparities experienced in rural populations. Cancer Epidemiol Biomarkers Prev; 27(11); 1265-74. ©2017 AACR.

Rural and Urban Differences in Air Quality, 2008-2012, and Community Drinking Water Quality, 2010-2015 - United States

Problem/Condition

The places in which persons live, work, and play can contribute to the development of adverse health outcomes. Understanding the differences in risk factors in various environments can help to explain differences in the occurrence of these outcomes and can be used to develop public health programs, interventions, and policies. Efforts to characterize urban and rural differences have largely focused on social and demographic characteristics. A paucity of national standardized environmental data has hindered efforts to characterize differences in the physical aspects of urban and rural areas, such as air and water quality.

Reporting Period

2008–2012 for air quality and 2010–2015 for water quality.

Description of System

Since 2002, CDC’s National Environmental Public Health Tracking Program has collaborated with federal, state, and local partners to gather standardized environmental data by creating national data standards, collecting available data, and disseminating data to be used in developing public health actions. The National Environmental Public Health Tracking Network (i.e., the tracking network) collects data provided by national, state, and local partners and includes 21 health outcomes, exposures, and environmental hazards. To assess environmental factors that affect health, CDC analyzed three air-quality measures from the tracking network for all counties in the contiguous United States during 2008–2012 and one water-quality measure for 26 states during 2010–2015. The three air-quality measures include 1) total number of days with fine particulate matter (PM_2.5) levels greater than the U.S. Environmental Protection Agency’s (EPA’s) National Ambient Air Quality Standards (NAAQS) for 24-hour average PM_2.5 (PM_2.5 days); 2) mean annual average ambient concentrations of PM_2.5 in micrograms per cubic meter (mean PM_2.5); and 3) total number of days with maximum 8-hour average ozone concentrations greater than the NAAQS (ozone days). The water-quality measure compared the annual mean concentration for a community water system (CWS) to the maximum contaminant level (MCL) defined by EPA for 10 contaminants: arsenic, atrazine, di(2-ethylhexyl) phthalate (DEHP), haloacetic acids (HAA5), nitrate, perchloroethene (PCE), radium, trichloroethene (TCE), total trihalomethanes (TTHM), and uranium. Findings are presented by urban-rural classification scheme: four metropolitan (large central metropolitan, large fringe metropolitan, medium metropolitan, and small metropolitan) and two nonmetropolitan (micropolitan and noncore) categories. Regression modeling was used to determine whether differences in the measures by urban-rural categories were statistically significant.

Results

Patterns for all three air-quality measures suggest that air quality improves as areas become more rural (or less urban). The mean total number of ozone days decreased from 47.54 days in large central metropolitan counties to 3.81 days in noncore counties, whereas the mean total number of PM_2.5 days decreased from 11.21 in large central metropolitan counties to 0.95 in noncore counties. The mean average annual PM_2.5 concentration decreased from 11.15 μg/m³ in large central metropolitan counties to 8.87 μg/m³ in noncore counties. Patterns for the water-quality measure suggest that water quality improves as areas become more urban (or less rural). Overall, 7% of CWSs reported at least one annual mean concentration greater than the MCL for all 10 contaminants combined. The percentage increased from 5.4% in large central metropolitan counties to 10% in noncore counties, a difference that was significant, adjusting for U.S. region, CWS size, water source, and potential spatial correlation. Similar results were found for two disinfection by-products, HAA5 and TTHM. Arsenic was the only other contaminant with a significant result. Medium metropolitan counties had 3.1% of CWSs reporting at least one annual mean greater than the MCL, compared with 2.4% in large central counties.

Interpretation

Noncore (rural) counties experienced fewer unhealthy air-quality days than large central metropolitan counties, likely because of fewer air pollution sources in the noncore counties. All categories of counties had a mean annual average PM_2.5 concentration lower than the EPA standard. Among all CWSs analyzed, the number reporting one or more annual mean contaminant concentrations greater the MCL was small. The water-quality measure suggests that water quality worsens as counties become more rural, in regards to all contaminants combined and for the two disinfection by-products individually. Although significant differences were found for the water-quality measure, the odds ratios were very small, making it difficult to determine whether these differences have a meaningful effect on public health. These differences might be a result of variations in water treatment practices in rural versus urban counties.

Public Health Action

Understanding the differences between rural and urban areas in air and water quality can help public health departments to identify, monitor, and prioritize potential environmental public health concerns and opportunities for action. These findings suggest a continued need to develop more geographically targeted, evidence-based interventions to prevent morbidity and mortality associated with poor air and water quality.