Widening Disparities In Infant Mortality And Life Expectancy Between Appalachia And The Rest Of The United States, 1990-2013

The paradox of high greenness and poor health in rural Central Appalachia

While many studies have found positive correlations between greenness and human health, rural Central Appalachia is an exception. The region has high greenness levels but poor health. The purpose of this commentary is to provide a possible explanation for this paradox: three sets of factors overwhelming or attenuating the health benefits of greenness. These include environmental (e.g., steep typography and limited access to green space used for outdoor recreation), social (e.g., chronic poverty, declining coal industry, and limited access to healthcare), and psychological and behavioral factors (e.g., perceptions about health behaviors, healthcare, and greenness). The influence of these factors on the expected health benefits of greenness should be considered as working hypotheses for future research. Policymakers and public health officials need to ensure that greenness-based interventions account for contextual factors and other determinants of health to ensure these interventions have the expected health benefits.

Cause-Specific Mortality and Racial Differentials in Life Expectancy, Chicago 2018-2019

BACKGROUND

In Chicago in 2018, the average life expectancy (ALE) for NH Blacks was 71.5 years, 9.1 fewer years than for NH Whites (80.6 years). Inasmuch as some causes of death are increasingly recognized products of structural racism, in urban areas, such causes may have potential for reducing racial inequities through public health intervention. Our purpose is to allocate racial inequities in ALE in Chicago to differentials in cause-specific mortality.

METHODS

Using multiple decrement processes and decomposition analysis, we examine cause-specific mortality in Chicago to determine the causes of death that contribute to the gap in life expectancy between NH Blacks and NH Whites.

RESULTS

Among females, the racial difference in ALE was 8.21 years; for males, it was 10.53 years. We find that cancer and heart disease mortality account for 3.03 years or 36% of the racial gap in average life expectancy among females. Differences in homicide and heart disease mortality rates comprised over 45% of the disparity among males.

CONCLUSIONS

Strategies for improving inequities in life expectancy should account for differences between males and females in cause-specific mortality rates. In urban areas with high levels of segregation, reducing inequities in ALE may be possible by dramatically reducing mortality rates from some causes.

CONTRIBUTION

This paper illustrates the state of inequities in ALE between NH Blacks and NH Whites in Chicago for the period just prior to the onset of the COVID-19 pandemic, using a well-established method of decomposing mortality differentials for sub-populations.

American clusters: using machine learning to understand health and health care disparities in the United States

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

Rural-urban disparities in health care delivery for children with medical complexity and moderating effects of payer, disability, and community poverty

PURPOSE

Children with medical complexity (CMC) may be at increased risk of rural-urban disparities in health care delivery given their multifaceted health care needs, but these disparities are poorly understood. This study evaluated rural-urban disparities in health care delivery to CMC and determined whether Medicaid coverage, co-occurring disability, and community poverty modified the effects of rurality on care delivery.

METHODS

This retrospective cohort study of 2012-2017 all-payer claims data from Colorado, Massachusetts, and New Hampshire included CMC <18 years. Health care delivery measures (ambulatory clinic visits, emergency department visits, acute care hospitalizations, total hospital days, and receipt of post-acute care) were compared for rural- versus urban-residing CMC in multivariable regression models, following established methods to evaluate effect modification.

FINDINGS

Of 112,475 CMC, 7307 (6.5%) were rural residing and 105,168 (93.5%) were urban residing. A total of 68.9% had Medicaid coverage, 33.9% had a disability, and 39.7% lived in communities with >20% child poverty. In adjusted analyses, rural-residing CMC received significantly fewer ambulatory visits (risk ratio [RR] = 0.95, 95% confidence interval [CI]: 0.94-0.96), more emergency visits (RR = 1.12, 95% CI: 1.08-1.16), and fewer hospitalization days (RR = 0.90, 95% CI = 0.85-0.96). The estimated modification effects of rural residence by Medicaid coverage, disability, and community poverty were each statistically significant. Differences in the odds of having a hospitalization and receiving post-acute care did not persist after incorporating sociodemographic and clinical characteristics and interaction effects.

CONCLUSIONS

Rural- and urban-residing CMC differed in their receipt of health care, and Medicaid coverage, co-occurring disabilities, and community poverty modified several of these effects. These modifying effects should be considered in clinical and policy initiatives to ensure that such initiatives do not widen rural-urban disparities.

Does club convergence matter in health outcomes? Evidence from Indian states

BACKGROUND

Population health is vital to a nation's overall well-being and development. To achieve sustainable human development, a reduction in health inequalities and an increase in interstate convergence in health indicators is necessary. Evaluation of the convergence patterns can aid the government in monitoring the health progress across the Indian states. This study investigates the progressive changes in the convergence and divergence patterns in health status across major states of India from 1990 to 2018.

METHODS

Sigma plots (σ), kernel density plots, and log t-test methods are used to test the convergence, divergence, and club convergence patterns in the health indicators at the state level.

RESULTS

The result of the sigma convergence suggests that life expectancy at birth has converged across all states. After 2006, however, the infant mortality rate, neonatal mortality rate, and total fertility rate experienced a divergence pattern. The study's findings indicate that life expectancy at birth converges in the same direction across all states, falling into the same club (Club One). However, considerable cross-state variations and evidence of clubs' convergence and divergence are observed in the domains of infant mortality rate, neonatal death rate, and total fertility rate. As suggested by the kernel density estimates, life expectancy at birth stratifies, polarizes, and becomes unimodal over time, although with a single stable state. A bimodal distribution was found for infant, neonatal, and total fertility rates.

CONCLUSIONS

Therefore, healthcare strategies must consider each club's transition path while focusing on divergence states to reduce health variations and improve health outcomes for each group of individuals.

Validity and Accuracy of the Tilburg Frailty Indicator Part B for Identification of Frailty in Older Adults Consulting a Rural Geriatric Medicine Clinic

The Tilburg Frailty Indicator (TFI) is a validated tool for determining frailty in older adults. This study examined the validity and accuracy of the TFI Part B (TFI-B) in a North American context. Seventy-two individuals ≥ 65 years of age recruited from a rural geriatric medicine clinic completed a set of self-reported and performance-based measures, including TFI-B. Frailty level was determined using modified Fried's Frailty Phenotype (FFP). Pearson correlation coefficients (r) assessed the concurrent relationships between the TFI-B and other measures. Accuracy of the TFI-B in classifying frailty level was assessed using assessing area under the curve (AUC). The TFI-B scores showed low correlations (r < 0.4) with gait speed and grip, suggesting that the TFI-B did not consider frailty as merely a physical problem. The AUC of 0.82 indicated that the TFI-B scores accurately classified frail versus non-frail individuals. The score of ≥ 5 on the TFI-B scores showed satisfactory sensitivity/specificity (73%/77%) and excellent negative predictive value (91.95%). This indicates that a TFI-B score of < 5 can be used to rule out frailty.

Spatiotemporal evolution and characteristics of worldwide life expectancy

Exploring global differences in life expectancy can facilitate the development of strategies to narrow regional disparities. However, few researchers have systematically examined patterns in the evolution of worldwide life expectancy over a long time period. Spatial differences among 181 countries in 4 types of worldwide life expectancy patterns from 1990 to 2019 were investigated via geographic information system (GIS) analysis. The aggregation characteristics of the spatiotemporal evolution of life expectancy were revealed by local indicators of spatial association. The analysis employed spatiotemporal sequence-based kernel density estimation and explored the differences in life expectancy among regions with the Theil index. We found that the global life expectancy progress rate shows upward then downward patterns over the last 30 years. Female have higher rates of spatiotemporal progression in life expectancy than male, with less internal variation and a wider spatial aggregation. The global spatial and temporal autocorrelation of life expectancy shows a weakening trend. The difference in life expectancy between male and female is reflected in both intrinsic causes of biological differences and extrinsic causes such as environment and lifestyle habits. Investment in education pulls apart differences in life expectancy over long time series. These results provide scientific guidelines for obtaining the highest possible level of health in countries around the world.

Evaluation of Social Determinants of Health and Prostate Cancer Outcomes Among Black and White Patients: A Systematic Review and Meta-analysis

IMPORTANCE

As the field of medicine strives for equity in care, research showing the association of social determinants of health (SDOH) with poorer health care outcomes is needed to better inform quality improvement strategies.

OBJECTIVE

To evaluate the association of SDOH with prostate cancer-specific mortality (PCSM) and overall survival (OS) among Black and White patients with prostate cancer.

DATA SOURCES

A MEDLINE search was performed of prostate cancer comparative effectiveness research from January 1, 1960, to June 5, 2020.

STUDY SELECTION

Two authors independently selected studies conducted among patients within the United States and performed comparative outcome analysis between Black and White patients. Studies were required to report time-to-event outcomes. A total of 251 studies were identified for review.

DATA EXTRACTION AND SYNTHESIS

Three authors independently screened and extracted data. End point meta-analyses were performed using both fixed-effects and random-effects models. The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline was followed, and 2 authors independently reviewed all steps. All conflicts were resolved by consensus.

MAIN OUTCOMES AND MEASURES

The primary outcome was PCSM, and the secondary outcome was OS. With the US Department of Health and Human Services Healthy People 2030 initiative, an SDOH scoring system was incorporated to evaluate the association of SDOH with the predefined end points. The covariables included in the scoring system were age, comorbidities, insurance status, income status, extent of disease, geography, standardized treatment, and equitable and harmonized insurance benefits. The scoring system was discretized into 3 categories: high (≥10 points), intermediate (5-9 points), and low (<5 points).

RESULTS

The 47 studies identified comprised 1 019 908 patients (176 028 Black men and 843 880 White men; median age, 66.4 years [IQR, 64.8-69.0 years]). The median follow-up was 66.0 months (IQR, 41.5-91.4 months). Pooled estimates found no statistically significant difference in PCSM for Black patients compared with White patients (hazard ratio [HR], 1.08 [95% CI, 0.99-1.19]; P = .08); results were similar for OS (HR, 1.01 [95% CI, 0.95-1.07]; P = .68). There was a significant race-SDOH interaction for both PCSM (regression coefficient, -0.041 [95% CI, -0.059 to 0.023]; P < .001) and OS (meta-regression coefficient, -0.017 [95% CI, -0.033 to -0.002]; P = .03). In studies with minimal accounting for SDOH (<5-point score), Black patients had significantly higher PCSM compared with White patients (HR, 1.29; 95% CI, 1.17-1.41; P < .001). In studies with greater accounting for SDOH variables (≥10-point score), PCSM was significantly lower among Black patients compared with White patients (HR, 0.86; 95% CI, 0.77-0.96; P = .02).

CONCLUSIONS AND RELEVANCE

The findings of this meta-analysis suggest that there is a significant interaction between race and SDOH with respect to PCSM and OS among men with prostate cancer. Incorporating SDOH variables into data collection and analyses are vital to developing strategies for achieving equity.

Comparison of Gross Motor Outcomes Between Children With Cerebral Palsy From Appalachian and Non-Appalachian Counties

PURPOSE

This study evaluated gross motor outcomes between children with cerebral palsy from non-Appalachian and Appalachian counties in the United States.

METHODS

For this retrospective, matched-case controlled study, data were sourced from electronic medical record and compared between groups. Groups were matched by age and Gross Motor Function Classification System (GMFCS) level.

RESULTS

Children from Appalachian counties had significantly higher Gross Motor Function Measure, 66 (GMFM-66) scores and had a cerebral palsy diagnosis reported in the electronic medical record significantly later compared with children from non-Appalachian counties, controlling for age and GMFCS level.

CONCLUSION

Although it has been documented that families and children from Appalachian counties have poorer overall health outcomes, motor development may not be affected. Our study found that children with cerebral palsy from Appalachian counties scored significantly higher on the GMFM-66 across GMFCS levels.

Geographic Location Impacts Patient Portal Use via Desktop and Mobile Devices

Disparities in patient portal use are impacted by individuals' access to technology and the internet as well as their skills and health behaviors. An individual's geographic location may impact these factors as well as contribute to their decision to use a portal, their choice of device to access the portal, and their use of portal functions. This study evaluated patient portal use by geographic location according to three comparators: proximity to the medical center offering the portal, urban/rural classification, and degree of digital distress. Patients residing farther from the medical center, in rural areas, or in areas of higher digital distress were less likely to be active portal users. Patients in areas of higher digital distress were more likely to use the mobile portal application instead of the desktop portal website alone. Users of the mobile portal application used portal functions more frequently, and being a mobile user had a greater impact on the use of some portal functions by patients residing in areas of higher digital distress. Mobile patient portal applications have the potential to increase portal use, but work is needed to ensure equitable internet access, to promote mobile patient portal applications, and to cultivate individuals' skills to use portals.

Adaptation and study protocol of the evidence-based Make Better Choices (MBC2) multiple diet and activity change intervention for a rural Appalachian population

Background

Rural Appalachian residents experience among the highest prevalence of chronic disease, premature mortality, and decreased life expectancy in the nation. Addressing these growing inequities while avoiding duplicating existing programming necessitates the development of appropriate adaptations of evidence-based lifestyle interventions. Yet few published articles explicate how to accomplish such contextual and cultural adaptation.

Methods

In this paper, we describe the process of adapting the Make Better Choices 2 (MBC2) mHealth diet and activity randomized trial and the revised protocol for intervention implementation in rural Appalachia. Deploying the NIH’s Cultural Framework on Health and Aaron’s Adaptation framework, the iterative adaptation process included convening focus groups (N = 4, 38 participants), conducting key informant interviews (N = 16), verifying findings with our Community Advisory Board (N = 9), and deploying usability surveys (N = 8), wireframing (N = 8), and pilot testing (N = 9. This intense process resulted in a comprehensive revision of recruitment, retention, assessment, and intervention components. For the main trial, 350 participants will be randomized to receive either the multicomponent MBC2 diet and activity intervention or an active control condition (stress and sleep management). The main outcome is a composite score of four behavioral outcomes: two outcomes related to diet (increased fruits and vegetables and decreased saturated fat intake) and two related to activity (increased moderate vigorous physical activity [MVPA] and decreased time spent on sedentary activities). Secondary outcomes include change in biomarkers, including blood pressure, lipids, A1C, waist circumference, and BMI.

Discussion

Adaptation and implementation of evidence-based interventions is necessary to ensure efficacious contextually and culturally appropriate health services and programs, particularly for underserved and vulnerable populations. This article describes the development process of an adapted, community-embedded health intervention and the final protocol created to improve health behavior and, ultimately, advance health equity.

Trial registration

ClinicalTrials.gov Identifier NCT04309461. The trial was registered on 6/3/2020.

Prevalence and Predictors of Integrated Care Among Teen Mothers and Their Infants

PURPOSE

Integrated models of primary care for parenting teens, in which teens and infants are cared for by the same clinical team on the same day, are associated with reduced repeated pregnancies and increased uptake of contraception and immunization. Our purpose was to determine how frequently teen-infant dyads receive integrated care.

METHODS

This study used Medicaid Analytic eXtract data to create a retrospective cohort of mothers aged 12-17 linked with infants born from 2007-2012 in 12 states. Teen-infant dyads were enrolled in Medicaid throughout the year after birth. The primary outcome was integrated care in the year after birth, defined as ≥ 1 instance when teen and infant had visits on the same day, billed to the same clinician identifier. Logistic regression assessed the relationship between integrated care and maternal demographics, dyad health, clinician specialty, and community factors.

RESULTS

Of 20,203 dyads, 3,371 (16.7%) had integrated care in the year after birth. Dyads with integrated care had a mean of 1.2 (SD 1.3) integrated visits. Dyads with integrated care had more visits (14.9, SD 10.6 vs. 11.7, SD 8.3), including more preventive visits for teens and more acute visits for both teens and infants. In regression, integrated care was associated with maternal factors (younger age, non-Latinx white race, and maternal health risks), residence in rural or high-poverty areas, and ever visiting Family Medicine clinicians.

DISCUSSION

Though uncommon, integrated care was associated with greater engagement in health care. Implementation of integrated care may support increased preventive care for parenting teens.

Incremental cost analysis of pediatric hospice care in rural and urban Appalachia

PURPOSE

Considering growing disparities in health outcomes between rural and urban areas of Appalachia, this study compared the incremental Medicaid costs of pediatric concurrent care (implemented by the Patient Protection and Affordable Care Act) versus standard hospice care.

METHODS

Data on 1,788 pediatric hospice patients, from the Appalachian region, collected between 2011 and 2013, were obtained from the Centers for Medicare and Medicaid Services. Incremental per-patient-per-month (PPM) costs of enrollment in concurrent versus standard hospice care were analyzed using multilevel generalized linear models. Increments for analysis were hospice length of stay (LOS).

RESULTS

For rural children enrolled in concurrent hospice care, the mean Medicaid cost of hospice care was $3,954 PPPM (95% CI: $3,223-$4,684) versus $1,933 PPPM (95% CI: $1,357-$2,509) for urban. For rural children enrolled in standard hospice care, the mean Medicaid cost was $2,889 PPPM (95% CI: $2,639-$3,139) versus $1,122 PPPM (95% CI: $980-$1,264) for urban. There were no statistically significant differences in Medicaid costs for LOS of 1 day. However, for LOS between 2 and 14 days, concurrent enrollment decreased total costs for urban children (IC = $-236.9 PPPM, 95% CI: $-421-$-53). For LOS of 15 days or more, concurrent care had higher costs compared to standard care, for both rural (IC = $1,399 PPPM, 95% CI: $92-$2,706) and urban children (IC = $1,867 PPPM, 95% CI: $1,172-$2,363).

CONCLUSIONS

The findings revealed that Medicaid costs for concurrent hospice care were highest among children in rural Appalachia. Future research on factors of high costs of rural care is needed.

Risk and Resilience Pathways, Community Adversity, Decision-making, and Alcohol Use Among Appalachian Adolescents: Protocol for the Longitudinal Young Mountaineer Health Study Cohort

BACKGROUND

Alcohol use impairs psychosocial and neurocognitive development and increases the vulnerability of youth to academic failure, substance use disorders, and other mental health problems. The early onset of alcohol use in adolescents is of particular concern, forecasting substance abuse in later adolescence and adulthood. To date, evidence suggests that youth in rural areas are especially vulnerable to contextual and community factors that contribute to the early onset of alcohol use.

OBJECTIVE

The objective of the Young Mountaineer Health Study is to investigate the influence of contextual and health behavior variables on the early onset of alcohol use among middle school-aged youth in resource-poor Appalachian rural communities.

METHODS

This is a program of prospective cohort studies of approximately 2200 middle school youth from a range of 20 rural, small town, and small city (population <30,000) public schools in West Virginia. Students are participating in 6 waves of data collection (2 per year) over the course of middle school (sixth to eighth grades; fall and spring) from 2020 to 2023. On the basis of an organizational arrangement, which includes a team of local data collection leaders, supervising contact agents in schools, and an honest broker system to deidentify data linked via school IDs, we are able to collect novel forms of data (self-reported data, teacher-reported data, census-linked area data, and archival school records) while ensuring high rates of participation by a large majority of youth in each participating school.

RESULTS

In the spring of 2021, 3 waves of student survey data, 2 waves of data from teachers, and a selection of archival school records were collected. Student survey wave 1 comprised 1349 (response rate 80.7%) participants, wave 2 comprised 1649 (response rate 87%) participants, and wave 3 comprised 1909 (response rate 83.1%) participants. The COVID-19 pandemic has had a negative impact on the sampling frame size, resulting in a reduced number of eligible students, particularly during the fall of 2020. Nevertheless, our team structure and incentive system have proven vitally important in mitigating the potentially far greater negative impact of the pandemic on our data collection processes.

CONCLUSIONS

The Young Mountaineer Health Study will use a large data set to test pathways linking rural community disadvantage to alcohol misuse among early adolescents. Furthermore, the program will test hypotheses regarding contextual factors (eg, parenting practices and neighborhood collective efficacy) that protect youth from community disadvantage and explore alcohol antecedents in the onset of nicotine, marijuana, and other drug use. Data collection efforts have been successful despite interruptions caused by the COVID-19 pandemic in 2020 and 2021.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/40451.

The rising burden of Alzheimer's disease mortality in rural America

Since the 1990s, there has been a striking urban-rural divergence in life expectancy within the United States, with metropolitan areas achieving strong life expectancy increases and nonmetropolitan areas experiencing stagnation or actual declines in life expectancy. While Alzheimer's disease and related dementias (ADRD) are likely to pose a particular challenge in nonmetropolitan areas, we know relatively little about the level of ADRD mortality in nonmetropolitan areas, how it has changed over time, and whether it is contributing to metropolitan/nonmetropolitan life expectancy gaps. This study finds that ADRD mortality has risen more rapidly in nonmetropolitan areas than in all other metro areas (large central metros, suburbs, and medium/small cities) between 1999 and 2019. While death rates from ADRD were nearly identical in large central metros and nonmetros in 1999, a clear metro/nonmetro gradient has emerged and widened substantially over the past two decades. Today, nonmetros now experience the highest levels of ADRD mortality, while large central metros have the lowest levels. These metro/nonmetro gaps in ADRD differ substantially by region, with the largest gaps observed in the Middle Atlantic and South Atlantic. The contribution of ADRD to metro/nonmetro differences life expectancy at age 65 is now considerable in many regions, reaching up to 30% for women and 13% for men. In several regions, ADRD's contribution to female life expectancy gaps is on par with or exceeds the contributions of other leading causes of death such as heart disease, cancer, and chronic lower respiratory diseases. The rising burden of Alzheimer's disease mortality is likely to pose a substantial challenge in rural areas of the United States which are aging rapidly, experiencing adverse mortality trends, and increasingly disadvantaged in terms of socioeconomic resources and health care infrastructure.

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ADRD mortality increased the most in nonmetropolitan areas between 1999 and 2019.

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Today, nonmetropolitan areas have the highest levels of ADRD mortality.

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Gaps in ADRD mortality between large central metros and nonmetros have widened.

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Metro/nonmetro gaps in ADRD mortality differ substantially by region.

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In some areas, ADRD is the leading contributor to urban/rural life expectancy gaps.

Trans*Forming Access and Care in Rural Areas: A Community-Engaged Approach

Research indicates that rural transgender and gender diverse (TGD) populations have a greater need for health services when compared with their urban counterparts, face unique barriers to accessing services, and have health disparities that are less researched than urban TGD populations. Therefore, the primary aim of this mixed-methods study (n = 24) was to increase research on the health care needs of TGD people in a rural Appalachian American context. This study was guided by a community-engaged model utilizing a community advisory board of TGD people and supportive parents of TGD children. Quantitative results indicate that travel burden is high, affirming provider availability is low, and the impacts on the health and mental health of TGD people in this sample are notable. Qualitative results provide recommendations for providers and health care systems to better serve this population. Integrated mixed-methods results further illustrate ways that rural TGD people and families adapt to the services available to them, sometimes at significant economic and emotional costs. This study contributes to the small but growing body of literature on the unique needs of rural TGD populations, including both adults and minors with supportive parents, by offering insights into strategies to address known disparities.

From convergence to divergence: Lifespan variation in US states, 1959-2017

BACKGROUND

Large disparities in life expectancy exist across US states and the gaps have been widening in recent decades. Less is known about the lifespan variability - a measure that can provide important insights into mortality inequalities both between and within states.

METHOD

Using yearly lifetables from the United States Mortality Database, we explore geographic and temporal patterns in lifespan variation (unconditional and conditional on survival to age 10, 35 and 65) across US states between 1959 and 2017. We also examine the contribution of state differences in life expectancy to overall lifespan variation using standard decomposition techniques.

RESULTS

Despite overall convergence in lifespan variation across states over the last six decades, in more recent years there has been notable divergence. Gender-specific analyses show that lifespan variation was generally greater among males than among females; but this pattern reverses for mortality past age 65. Much of the state disparities in lifespan variation, unconditional and conditional on survival to age 10 and 35, were due to mortality differences under the age 65. Decomposition analysis shows that while within-state variability remains the primary driver of overall lifespan variation, the contribution of cross-state differences in life expectancy is growing.

CONCLUSIONS

Variation in longevity is greater within US States than between them, yet cross-states disparities in mortality are increasing. This likely reflects the long-term consequences of rising social, economic, and political stratification for health inequalities both within and across states.

COVID-19 and the impact on rural and black church Congregants: Results of the C-M-C project

The COVID-19 pandemic has had devastating effects on Black and rural populations with a mortality rate among Blacks three times that of Whites and both rural and Black populations experiencing limited access to COVID-19 resources. The primary purpose of this study was to explore the health, financial, and psychological impact of COVID-19 among rural White Appalachian and Black nonrural central Kentucky church congregants. Secondarily we sought to examine the association between sociodemographics and behaviors, attitudes, and beliefs regarding COVID-19 and intent to vaccinate. We used a cross sectional survey design developed with the constructs of the Health Belief and Theory of Planned Behavior models. The majority of the 942 respondents were ≥36 years. A total of 54% were from central Kentucky, while 47.5% were from Appalachia. Among all participants, the pandemic worsened anxiety and depression and delayed access to medical care. There were no associations between sociodemographics and practicing COVID-19 prevention behaviors. Appalachian region was associated with financial burden and delay in medical care (p = 0.03). Appalachian respondents had lower perceived benefit and attitude for COVID-19 prevention behaviors (p = 0.004 and <0.001, respectively). Among all respondents, the perceived risk of contracting COVID was high (54%), yet 33.2% indicated unlikeliness to receive the COVID-19 vaccine if offered. The COVID-19 pandemic had a differential impact on White rural and Black nonrural populations. Nurses and public health officials should assess knowledge and explore patient's attitudes regarding COVID-19 prevention behaviors, as well as advocate for public health resources to reduce the differential impact of COVID-19 on these at-risk populations.

Addressing infant mortality through positive youth development opportunities for adolescent girls

Adolescent girls experience risks prior to pregnancy and giving birth that influence their overall health, and development, as well as community rates of infant mortality. Supporting adolescent girls through positive youth development (PYD) opportunities offers a potential long-term strategy to preventing infant mortality and improving maternal health outcomes. The current study sought to assess state-wide needs, resources and opportunities related to PYD supports for adolescent girls, especially among those most at risk for early pregnancy. A strengths, weaknesses, opportunities and threats (SWOT) analysis guided nine community forums in counties with the highest rates of infant mortality in one large Midwestern state. In total, 368 stakeholders attended the forums and provided insights related to the context of PYD for adolescent girls. Researchers also conducted three focus group with 19 parents/guardians and three focus groups with 25 adolescent girls aged 11-14 to validate the findings from the SWOT analysis. Content analysis was utilised to synthesise the qualitative results. Strengths and opportunities related to PYD for adolescent girls included access to afterschool programming and access to health and mental health services. Weaknesses brought awareness to more systemic problems as all nine counties reported a lack of communication and coordination among youth programs and a need for greater collaboration among youth agencies. Threats included challenges associated with technology and social media, unsafe neighbourhood conditions, and issues of racism, sexism, poverty and discrimination. Findings support the need for a continued focus and priority on improving access, services and supports for adolescent girls to prevent infant mortality and improve their health and well-being. Local, state and national leaders can use the results of this study to promote additional strategies for addressing infant mortality through PYD for adolescent girls.

Place, Power, and Premature Mortality: A Rapid Scoping Review on the Health of Women in Appalachia

OBJECTIVE

Appalachian women continue to die younger than in other US regions. We performed a rapid scoping review to summarize women's health research in Appalachia from 2000 to 2019, including health topics, study populations, theoretical frameworks, methods, and findings.

DATA SOURCE

We searched bibliographic databases (eg, PubMed, PsycINFO, Google Scholar) for literature focusing on women's health in Appalachia.

STUDY INCLUSION AND EXCLUSION CRITERIA

Included articles were: (1) on women's health in Appalachia; (2) published January 2000 to June 2019; (3) peer-reviewed; and (4) written in English. We excluded studies without reported data findings.

DATA EXTRACTION

Two coders reviewed articles for descriptive information to create summary tables comparing variables of interest.

DATA SYNTHESIS

Two coders co-reviewed a sub-sample to ensure consensus and refine data charting categories. We categorized major findings across the social-ecological framework.

RESULTS

A search of nearly 2 decades of literature revealed 81 articles, which primarily focused on cancer disparities (49.4%) and prenatal/pregnancy outcomes (23.5%). Many of these research studies took place in Central Appalachia (eg, 42.0% in Kentucky) with reproductive or middle-aged women (82.7%). Half of the studies employed quantitative methods, and half used qualitative methods, with few mixed method or community-engaged approaches (3.7%). Nearly half (40.7%) did not specify a theoretical framework. Findings included complex multi-level factors with few articles exploring the co-occurrence of factors across multiple levels.

CONCLUSIONS

Future studies should: 1) systematically include Appalachian women at various life stages from under-represented sub-regions; 2) expand the use of rigorous methods and specified theoretical frameworks to account for complex interactions of social-ecological factors; and 3) build upon existing community assets to improve health in this vulnerable population.

Prevalence and Social and Built Environmental Determinants of Maternal Prepregnancy Obesity in 68 Major Metropolitan Cities of the United States, 2013-2016

Objective

Maternal prepregnancy obesity is related to increased maternal morbidity and mortality and poor birth outcomes. However, prevalence and risk factors for prepregnancy obesity in US cities are not known. This study examines the prevalence and social and environmental determinants of maternal prepregnancy obesity (BMI ≥30), overweight/obesity (BMI ≥25), and severe obesity (BMI ≥40) in the 68 largest metropolitan cities of the United States.

Methods

We fitted logistic and Poisson regression models to the 2013–2016 national vital statistics birth cohort data (N = 3,083,600) to derive unadjusted and adjusted city differentials in maternal obesity and to determine social and environmental determinants.

Results

Considerable disparities existed across cities, with the prevalence of prepregnancy obesity ranging from 10.4% in San Francisco to 36.6% in Detroit. Approximately 63.0% of mothers in Detroit were overweight or obese before pregnancy, compared with 29.2% of mothers in San Francisco. Severe obesity ranged from 1.4% in San Francisco to 8.5% in Cleveland. Women in Anchorage, Buffalo, Cleveland, Fresno, Indianapolis, Louisville, Milwaukee, Oklahoma City, Sacramento, St Paul, Toledo, Tulsa, and Wichita had >2 times higher adjusted odds of prepregnancy obesity compared to those in San Francisco. Race/ethnicity, maternal age, parity, marital status, nativity/immigrant status, and maternal education were important individual-level risk factors and accounted for 63%, 39%, and 72% of the city disparities in prepregnancy obesity, overweight/obesity, and severe obesity, respectively. Area deprivation, violent crime rates, physical inactivity rates, public transport use, and access to parkland and green spaces remained significant predictors of prepregnancy obesity even after controlling for individual-level covariates.

Conclusions

Substantial disparities in maternal prepregnancy obesity among the major US cities remain despite risk-factor adjustment, with women in several Southern and Midwestern cities experiencing high risks of obesity. Sound urban policies are needed to promote healthier lifestyles and favorable social and built environments for obesity reduction and improved maternal health.

County Poverty, Urban-Rural Classification, and the Causes of Term Infant Death : United States, 2012-2015

OBJECTIVE

Higher mortality among full-term infants (term infant deaths) contributes to disparities in infant mortality between the United States and other developed countries. We examined differences in the causes of term infant deaths across county poverty levels and urban-rural classification to understand underlying mechanisms through which these factors may act.

METHODS

We linked period birth/infant death files for 2012-2015 with US Census poverty estimates and county urban-rural classifications. We grouped the causes of term infant deaths as sudden unexpected death in infancy (SUDI), congenital malformations, perinatal conditions, and all other causes. We computed the distribution and relative risk of overall and cause-specific term infant mortality rates (term IMRs) per 1000 live births and 95% CIs for county-level factors.

RESULTS

The increase in term IMR across county poverty and urban-rural classification was mostly driven by an increase in the rate of SUDI. The relative risk of term infant deaths as a result of SUDI was 1.6 (95% CI, 1.5-1.8) times higher in medium-poverty counties and 2.3 (95% CI, 1.2-2.5) times higher in high-poverty counties than in low-poverty counties. Cause-specific IMRs of congenital malformations, perinatal conditions, and death from other causes did not differ by county poverty level. We found similar trends across county urban-rural classification. Sudden infant death syndrome was the main cause of SUDI across both county poverty levels and urban-rural classifications, followed by unknown causes and accidental suffocation and strangulation in bed.

CONCLUSIONS

Interventions aimed at reducing SUDI, particularly in high-poverty and rural areas, could have a major effect on reducing term IMR disparities between the United States and other developed countries.

Social factors and public policies associated with state infant mortality rates

Despite mounting evidence that social factors and public policies affect state infant mortality rates (IMRs), few researchers have examined variation in IMRs associated with those factors and policies. We quantified disparities in infant mortality by state social factors and public policy characteristics. We hypothesized that some social factors and public policies would be more strongly associated with infant mortality than others, and that states with similar factors and policies would form clusters with varying levels of infant mortality. We examined associations of women's economic empowerment, health and well-being, political participation, reproductive rights, and work and family-related policies with state IMRs in 2012 and 2015, using indicators created by the Institute for Women's Policy Research. Methods included generalized linear models, principal component analysis, and cluster analysis. Health and well-being predicted IMRs (2012, 2015, both p < .05), as did poverty and opportunity, and reproductive rights (2012, p < .10). Consistent with our hypothesis, states formed clusters, with the states in each cluster having similar social factors and public policies, and similar IMRs. Women's health status and insurance coverage were more predictive of state IMRs than other social factors. Improving health and insurance coverage may be an effective way to reduce state IMRs.

Rural Residents' Perspectives on an mHealth or Personalized Health Coaching Intervention: Qualitative Study With Focus Groups and Key Informant Interviews

Background

Compared with national averages, rural Appalachians experience extremely elevated rates of premature morbidity and mortality. New opportunities, including approaches incorporating personal technology, may help improve lifestyles and overcome health inequities.

Objective

This study aims to gather perspectives on whether a healthy lifestyle intervention, specifically an app originally designed for urban users, may be feasible and acceptable to rural residents. In addition to a smartphone app, this program—Make Better Choices 2—consists of personalized health coaching, accelerometer use, and financial incentives.

Methods

We convened 4 focus groups and 16 key informant interviews with diverse community stakeholders to assess perspectives on this novel, evidence-based diet and physical activity intervention. Participants were shown a slide presentation and asked open-ended follow-up questions. The focus group and key informant interview sessions were audiotaped, transcribed, and subjected to thematic analysis.

Results

We identified 3 main themes regarding Appalachian residents’ perspectives on this mobile health (mHealth) intervention: personal technology is feasible and desirable; challenges persist in implementing mHealth lifestyle interventions in Appalachian communities; and successful mHealth interventions should include personal connections, local coaches, and educational opportunities. Although viewed as feasible and acceptable overall, lack of healthy lifestyle awareness, habitual behavior, and financial constraints may challenge the success of mHealth lifestyle interventions in Appalachia. Finally, participants described several minor elements that require modification, including expanding the upper age inclusion, providing extra coaching on technology use, emphasizing personal and supportive connections, employing local coaches, and ensuring adequate educational content for the program.

Conclusions

Blending new technologies, health coaching, and other features is not only acceptable but may be essential to reach vulnerable rural residents.

Substance consumption and intoxication patterns in a medically supervised overdose prevention program for people experiencing homelessness

Background: Opioid overdose is a leading cause of death among homeless individuals. Combining psychoactive substances with opioids increases overdose risk. This study aimed to describe intoxication patterns at a drop-in space offering medical monitoring and harm reduction services to individuals who arrive intoxicated and at risk of overdose. Methods: We examined data from visits to the Supportive Place for Observation and Treatment at Boston Health Care for the Homeless Program between January 1, 2017 and December 31, 2017. We used k-means cluster analysis to characterize intoxication patterns based on clinically assessed sedation levels and vital sign parameters. Multinomial logistic regression analysis assessed demographic and substance consumption predictors of cluster membership. Linear and logistic regression models examined associations between cluster membership and care outcomes. Results: Across 305 care episodes involving 156 unique patients, cluster analysis revealed 3 distinct intoxication patterns. Cluster A (26.6%) had mild sedation and normal vital signs. Cluster B (44.5%) featured greater sedation with bradycardia and/or hypotension. Cluster C (28.9%) was comparable to cluster B but with the addition of hypoxia. Self-reported consumption of non-opioid sedatives prior to arrival was common (63.3% of episodes) and predicted membership in cluster B (aOR 2.75, 95% CI 1.40, 5.40) and cluster C (aOR 3.38, 95% CI 1.48, 7.70). In comparison to cluster A episodes, cluster C episodes were longer (mean 4.8 vs. 2.3 hours, p < 0.001) and more likely to require supplemental oxygen (27.3% vs. 2.5%, p < 0.001). Few episodes required hospital transfer (4.7%) or naloxone (1.0%). No deaths occurred. Conclusions: In a medically supervised overdose monitoring program, reported use of non-opioid sedatives strongly predicted more complex clinical courses and should be factored into overdose prevention efforts. Low-threshold medical monitoring in an ambulatory setting was sufficient for most episodes, suggesting a role for such programs in reducing harm and averting costly emergency services.

Improving Research, Policy, and Practice to Address Women's Sexual and Reproductive Health Care Needs During Emerging Adulthood

Women in the period of emerging adulthood (18-25 years of age) have the greatest rates of unintended pregnancy and sexually transmitted infections. Despite this disproportionate risk, women's sexual and reproductive health needs during emerging adulthood are poorly understood. As a result, few age-specific policies or person-centered practice guidelines are available to reduce sexual risk. In this commentary we explore the unique characteristics of emerging adulthood that contribute to greater sexual and reproductive health risks for women. Current evidence on sexual and reproductive health outcomes of women during emerging adulthood and limited practice guidelines are discussed. Recommendations for health care providers, especially nurses, for guiding personalized care for women in emerging adulthood are discussed.

Marked Disparities in Life Expectancy by Education, Poverty Level, Occupation, and Housing Tenure in the United States, 1997-2014

OBJECTIVES

Socioeconomic disparities in life expectancy in the United States (US) are marked and have widened over time. However, there is limited research using individual-level socioeconomic variables as such information is generally lacking or unreliable in vital records used for life table construction. Using longitudinal cohort data, we computed life expectancy for US adults by social determinants such as education, income/poverty level, occupation, and housing tenure.

METHODS

We analyzed the 1997-2014 National Health Interview Survey prospectively linked to mortality records in the National Death Index (N=1,146,271). Standard life table methodologies were used to compute life expectancy and other life table functions at various ages according to socioeconomic variables stratified by sex and race/ethnicity.

RESULTS

Adults with at least a Master's degree had 14.7 years higher life expectancy at age 18 than those with less than a high school education and 8.3 years higher life expectancy than those with a high school education. Poverty was inversely related to life expectancy. Individuals living in poverty had 10.5 years lower life expectancy at age 18 than those with incomes ≥400% of the poverty threshold. Laborers and those employed in craft and repair occupations had, respectively, 10.9 years and 8.6 years lower life expectancy at age 18 than those with professional and managerial occupations. Male and female renters had, respectively, 4.0 years and 4.6 years lower life expectancy at age 18 than homeowners. Women in the most advantaged socioeconomic group outlived men in the most disadvantaged group by 23.5 years at age 18.

CONCLUSIONS AND GLOBAL HEALTH IMPLICATIONS

Marked socioeconomic gradients in US life expectancy were found across all sex and racial/ethnic groups. Adults with lower education, higher poverty levels, in manual occupations, and with rental housing had substantially lower life expectancy compared to their counterparts with higher socioeconomic position.

County-Level Contextual Characteristics and Disparities in Life Expectancy

OBJECTIVE

To estimate the contribution of county-level contextual factors to differences in life expectancy in the United States.

METHODS

We used a counterfactual approach to estimate the years of life expectancy lost associated with 45 potentially modifiable county-level contextual characteristics in the United States in the year 2016. Contextual data and life expectancy data were obtained from the County Health Ranking Project and the U.S. Small-Area Life Expectancy Estimates Project, respectively.

RESULTS

Median census-tract-level life expectancy was 78.90 (interquartile range, 76.30-81.00) years, and the range across census tracts spanned 41.20 years. Large variations in life expectancy existed within and between states and within and between counties; the gap between counties was 20.30 years and gaps within counties ranged from 0 to 34.60 years. An array of 45 county-level factors was associated with 4.30 years of life expectancy loss. County-level adult smoking, food insecurity, adult obesity, physical inactivity, college education, and median household income were associated with 1.24-, 0.89-, 0.58-, 0.35-, 0.33-, and 0.14-year losses in life expectancy, respectively; and altogether were associated with a 3.53-year loss in life expectancy. The contribution of contextual factors to years of life expectancy lost varied among states and was more pronounced in states with lower life expectancy and in areas of increased socioeconomic deprivation and increased percentage of Black race.

CONCLUSION

Substantial geographic variation in life expectancy was observed. Six county-level contextual factors were associated with a 3.53-year loss in life expectancy. The findings may inform and help prioritize approaches to reduce inequalities in life expectancy in the United States.

Community-engaged research in translational science: Innovations to improve health in Appalachia

Health disparities between Appalachia and the rest of the country are widening. To address this, the Appalachian Translational Research Network (ATRN) organizes an annual ATRN Health Summit. The most recent Summit was held online September 22–23, 2020, and hosted by Wake Forest Clinical and Translational Science Institute in partnership with the Northwest Area Health Education Center. The Summit, titled “Community-Engaged Research in Translational Science: Innovations to Improve Health in Appalachia,” brought together a diverse group of 141 stakeholders from communities, academic institutions, and the National Center for Advancing Translational Science (NCATS) to highlight current research, identify innovative approaches to translational science and community-engaged research, develop cross-regional research partnerships, and establish and disseminate priorities for future Appalachian-focused research. The Summit included three plenary presentations and 39 presentations within 12 concurrent breakout sessions. Here, we describe the Summit planning process and implementation, highlight some of the research presented, and outline nine emergent themes to guide future Appalachian-focused research.

Adverse Childhood Experiences among Adults in North Carolina, USA: Influences on Risk Factors for Poor Health across the Lifespan and Intergenerational Implications

Adverse childhood experiences (ACEs) are a critical determinant and predictor of health across the lifespan. The Appalachian region of the United States, particularly the central and southern portions, experiences worse health outcomes when compared to the rest of the nation. The current research sought to understand the cross-sectional relationships between ACEs, social determinants of health and other health risk factors in one southcentral Appalachian state. Researchers used the 2012 and 2014 North Carolina Behavioral Risk Factor Surveillance System (BRFSS) for analyses. An indicator variable of Appalachian county (n = 29) was used to make comparisons against non-Appalachian counties (n = 71). Analyses further examined the prevalence of ACEs in households with and without children across Appalachian and non-Appalachian regions, and the effects of experiencing four or more ACEs on health risk factors. There were no statistically significant differences between Appalachian and non-Appalachian counties in the prevalence of ACEs. However, compared with adults in households without children, those with children reported a higher percentage of ACEs. Reporting four or more ACEs was associated with higher prevalence of smoking (prevalence ratio [PR] = 1.56), heavy alcohol consumption (PR = 1.69), overweight/obesity (PR = 1.07), frequent mental distress (PR = 2.45), and food insecurity (PR = 1.58) in adjusted models and with fair or poor health only outside Appalachia (PR = 1.65). Residence in an Appalachian county was independently associated with higher prevalence of food insecurity (PR = 1.13). Developing programs and implementing policies aimed at reducing the impact of ACEs could improve social determinants of health, thereby helping to reduce health disparities.

Fueling Clinical and Translational Research in Appalachia: Informatics Platform Approach

BACKGROUND

The Appalachian population is distinct, not just culturally and geographically but also in its health care needs, facing the most health care disparities in the United States. To meet these unique demands, Appalachian medical centers need an arsenal of analytics and data science tools with the foundation of a centralized data warehouse to transform health care data into actionable clinical interventions. However, this is an especially challenging task given the fragmented state of medical data within Appalachia and the need for integration of other types of data such as environmental, social, and economic with medical data.

OBJECTIVE

This paper aims to present the structure and process of the development of an integrated platform at a midlevel Appalachian academic medical center along with its initial uses.

METHODS

The Appalachian Informatics Platform was developed by the Appalachian Clinical and Translational Science Institute's Division of Clinical Informatics and consists of 4 major components: a centralized clinical data warehouse, modeling (statistical and machine learning), visualization, and model evaluation. Data from different clinical systems, billing systems, and state- or national-level data sets were integrated into a centralized data warehouse. The platform supports research efforts by enabling curation and analysis of data using the different components, as appropriate.

RESULTS

The Appalachian Informatics Platform is functional and has supported several research efforts since its implementation for a variety of purposes, such as increasing knowledge of the pathophysiology of diseases, risk identification, risk prediction, and health care resource utilization research and estimation of the economic impact of diseases.

CONCLUSIONS

The platform provides an inexpensive yet seamless way to translate clinical and translational research ideas into clinical applications for regions similar to Appalachia that have limited resources and a largely rural population.

Qualitative Analysis of Maternal Barriers and Perceptions o Participation in a Federal Supplemental Nutrition Program in Rural Appalachian North Carolina

Background

Little is known about barriers to and perceptions of participation in the in Women, Infants, and Children (WIC) program in rural Appalachia.

Purpose

To gain a deeper understanding of maternal barriers and perceptions related to WIC participation in rural Appalachia

Methods

Pregnant women and mothers were recruited in-person and via flyers from WIC offices in three counties in Appalachian North Carolina. Four semi-structured focus groups were conducted between May to July 2018. Each focus group was approximately 60 minutes long and included open-ended questions about the overall WIC experience in rural Appalachia. Focus groups were audio-recorded, transcribed verbatim, and content analysis of transcripts was performed by two trained researchers. Identified themes were discussed and consensus was reached by the researchers to generate final themes for four areas of interest: (1) most valued aspects of WIC program, (2) barriers to program participation and benefit redemption, (3) experiences during appointments, and (4) suggestions for improving experiences in program.

Results

The most valued aspects of participation were financial benefits and support/resources provided by WIC staff. In contrast, lack of variety of WIC-approved foods and social stigma were perceived as major barriers to participation and redeeming benefits.

Implications

This study contributes to a better understanding of the barriers and perceptions related to WIC participation in this geographically and culturally unique area of rural Appalachia. Findings are valuable for informing WIC state-agencies and policymakers whose efforts focus on the identification and development of effective recruitment and retention strategies for WIC-eligible families in rural Appalachia.

Geographic Variation in the Structure of Kentucky's Population Health Systems: An Urban, Rural, and Appalachian Comparison

INTRODUCTION

Research examining geographic variation in the structure of population health systems is continuing to emerge, and most of the evidence that currently exists divides systems by urban and rural designation. Very little is understood about how being rural and Appalachian impacts population health system structure and strength.

PURPOSE

This study examines geographic differences in key characteristics of population health systems in urban, rural non-Appalachian, and rural Appalachian regions of Kentucky.

METHODS

Data from a 2018 statewide survey of community networks was used to examine population health system characteristics. Descriptive statistics were generated to examine variation across geographic regions in the availability of 20 population health activities, the range of organizations that contribute to those activities, and system strength. Data were collected in 2018 and analyzed in 2020.

RESULTS

Variation in the provision of population health protections and the structure of public health systems across KY exists. Urban communities are more likely than rural to have a comprehensive set of population health protections delivered in collaboration with a diverse set of multisector partners. Rural Appalachian communities face additional limited capacity in the delivery of population health activities, compared to other rural communities in the state.

IMPLICATIONS

Understanding the delivery of population health provides further insight into additional system-level factors that may drive persistent health inequities in rural and Appalachian communities. The capacity to improve health happens beyond the clinic, and the strengthening of population health systems will be a critical step in efforts to improve population health.

The geographic alignment of primary care Health Professional Shortage Areas with markers for social determinants of health

Background

The Health Resources and Services Administration (HRSA), an agency within the U.S. Department of Health and Human Services (HHS), works to ensure accessible, quality, health care for the nation’s underserved populations, especially those who are medically, economically, or geographically vulnerable. HRSA-designated primary care Health Professional Shortage Areas (pcHPSAs) provide a vital measure by which to identify underserved populations and prioritize locations and populations lacking access to adequate primary and preventive health care–the foundation for advancing health equity and maintaining health and wellness for individuals and populations. However, access to care is a complex, multifactorial issue that involves more than just the number of health care providers available, and pcHPSAs alone cannot fully characterize the distribution of medically, economically, and geographically vulnerable populations.

Methods and findings

In this county-level analysis, we used descriptive statistics and multiple correspondence analysis to assess how HRSA’s pcHPSA designations align geographically with other established markers of medical, economic, and geographic vulnerability. Reflecting recognized social determinants of health (SDOH), markers included demographic characteristics, race and ethnicity, rates of low birth weight births, median household income, poverty, educational attainment, and rurality. Nationally, 96 percent of U.S. counties were either classified as whole county or partial county pcHPSAs or had one or more established markers of medical, economic, or geographic vulnerability in 2017, suggesting that at-risk populations were nearly ubiquitous throughout the nation. Primary care HPSA counties in HHS Regions 4 and 6 (largely lying within the southeastern and south central United States) had the most pervasive and complex patterns in population risk.

Conclusion

HHS Regions displayed unique signatures with respect to SDOH markers. Descriptive and analytic findings from our work may help inform health workforce and health care planning at all levels, and, by illustrating both the complexity of and differences in county-level population characteristics in pcHPSA counties, our findings may have relevance for strengthening the delivery of primary care and addressing social determinants of health in areas beset by provider shortages.

Smoking-Cessation Interventions in Appalachia: A Systematic Review and Meta-Analysis

CONTEXT

Appalachia, a socioeconomically disadvantaged rural region in the eastern U.S., has one of the nation's highest prevalence rates of smoking and some of the poorest health outcomes. Effective interventions that lower smoking rates in Appalachia have great potential to reduce health disparities and preventable illness; however, a better understanding of effective interventions is needed.

EVIDENCE ACQUISITION

This review included trials that evaluated the impact of smoking-cessation programs among populations living in Appalachia. The search was carried out on October 9, 2018 and comprised the Cochrane Central Register of Controlled Trials, Medline, Embase, and Scopus for academic journal articles published in English, with no date restrictions. After preliminary screening, potentially relevant full-text articles were independently reviewed by the authors with a Cohen's κ of 0.72, leading to the final inclusion of 9 articles.

EVIDENCE SYNTHESIS

Eligible studies were assessed qualitatively for heterogeneity and risk of bias. Six of the 9 included studies had extractable data related to dichotomous smoking status and reported a measure of association suitable for inclusion in a meta-analysis. For those 6 studies, the pooled RR and pooled OR were estimated using random effects models, with an I² index demonstrating substantial heterogeneity. A funnel plot of the 6 trials appeared relatively symmetric.

CONCLUSIONS

Participation in smoking-cessation interventions increased the probability of smoking abstinence among Appalachian smokers by an estimated 2.33 times (pooled RR=2.33, 95% CI=1.03, 5.25, p=0.04). Given the low number of studies, their substantial heterogeneity, and high risk of bias, the evidence of the effectiveness of smoking-cessation interventions in Appalachia must be interpreted with caution.

Prevalence and domains of disability within and outside Appalachian North Carolina: 2013-2016 Behavioral Risk Factor Surveillance System

BACKGROUND

The health and social conditions of the Appalachian region generally are poorer than in the US overall, and this gap is widening, suggesting disability may be higher in Appalachia.

OBJECTIVE

To describe the prevalence of disability overall and by domain in Appalachian and non-Appalachian regions in North Carolina (NC) and describe the characteristics of people with and without disability in each region.

METHODS

We conducted a cross-sectional study using data from the NC Behavioral Risk Factor Surveillance System from 2013 to 2016 which assessed disability in five domains: vision, cognitive, mobility, self-care, and independent living. We calculated weighted proportions and age- and sex-adjusted prevalence using direct standardization to the 2010 Census.

RESULTS

The prevalence of disability in Appalachian NC was significantly higher than in non-Appalachian NC after standardizing by age and sex (26.6% in Appalachia, 24.1% outside Appalachia, p < 0.001). In both regions, mobility disability was most common and self-care disability was least common. People within Appalachia more frequently reported disability in all domains compared to people outside Appalachia.

CONCLUSIONS

More than one in four adults in Appalachian North Carolina experience disability in at least one domain and one in eight experiences disability in multiple domains. The high prevalence of disability should be considered when planning programs and services across the spectrum of public health. Understanding common disability domains present in populations can inform public health agencies and service providers and help them develop programs and messaging that meet the needs of residents in Appalachia and are accessible to people with disabilities.

The persistent southern disadvantage in US early life mortality, 1965-2014

BACKGROUND

Recent studies of US adult mortality demonstrate a growing disadvantage among southern states. Few studies have examined long-term trends and geographic patterns in US early life (ages 1 to 24) mortality, ages at which key risk factors and causes of death are quite different than among adults.

OBJECTIVE

This article examines trends and variations in early life mortality rates across US states and census divisions. We assess whether those variations have changed over a 50-year time period and which causes of death contribute to contemporary geographic disparities.

METHODS

We calculate all-cause and cause-specific death rates using death certificate data from the Multiple Cause of Death files, combining public-use files from 1965-2004 and restricted data with state geographic identifiers from 2005-2014. State population (denominator) data come from US decennial censuses or intercensal estimates.

RESULTS

Results demonstrate a persistent mortality disadvantage for young people (ages 1 to 24) living in southern states over the last 50 years, particularly those located in the East South Central and West South Central divisions. Motor vehicle accidents and homicide by firearm account for most of the contemporary southern disadvantage in US early life mortality.

CONTRIBUTION

Our results illustrate that US children and youth living in the southern United States have long suffered from higher levels of mortality than children and youth living in other parts of the country. Our findings also suggest the contemporary southern disadvantage in US early life mortality could potentially be reduced with state-level policies designed to prevent deaths involving motor vehicles and firearms.

Explaining the spatial variation in American life expectancy

Since 1980, average life expectancy in the United States has increased by roughly five years; however, in recent years it has been declining. At the same time, spatial variation in life expectancy has been growing. To explore reasons for this trend, some researchers have focused on morbidity factors, while others have focused on how mortality trends differ by personal characteristics. However, the effect community characteristics may play in expanding the spatial heterogeneity has not yet been fully explored. Using a spatial Durbin error model, we explore how community and demographic factors influence county-level life expectancy in 2014, controlling for life expectancy in 1980 and migration over time, and analyzing men and women separately. We find that community characteristics are important in determining life expectancy and that there may be a role for policy makers in addressing factors that are associated with lower life expectancy in some regions.

A "Swiss paradox" in the United States? Level of spatial aggregation changes the association between income inequality and morbidity for older Americans

Although a preponderance of research indicates that increased income inequality negatively impacts population health, several international studies found that a greater income inequality was associated with better population health when measured on a fine geographic level of aggregation. This finding is known as a “Swiss paradox”. To date, no studies have examined variability in the associations between income inequality and health outcomes by spatial aggregation level in the US. Therefore, this study examined associations between income inequality (Gini index, GI) and population health by geographic level using a large, nationally representative dataset of older adults. We geographically linked respondents’ county data from the 2012 Behavioral Risk Factor Surveillance System to 2012 American Community Survey data. Using generalized linear models, we estimated the association between GI decile on the state and county levels and five population health outcomes (diabetes, obesity, smoking, sedentary lifestyle and self-rated health), accounting for confounders and complex sampling. Although state-level GI was not significantly associated with obesity rates (b = − 0.245, 95% CI − 0.497, 0.008), there was a significant, negative association between county-level GI and obesity rates (b = − 0.416, 95% CI − 0.629, − 0.202). State-level GI also associated with an increased diabetes rate (b = 0.304, 95% CI 0.063, 0.546), but the association was not significant for county-level GI and diabetes rate (b = − 0.101, 95% CI − 0.305, 0.104). Associations between both county-level GI and state-level GI and current smoking status were also not significant. These findings show the associations between income inequality and health vary by spatial aggregation level and challenge the preponderance of evidence suggesting that income inequality is consistently associated with worse health. Further research is needed to understand the nuances behind these observed associations to design informed policies and programs designed to reduce socioeconomic health inequities among older adults.

Decomposition of the US black/white inequality in premature mortality, 2010-2015: an observational study

OBJECTIVE

Decompose the US black/white inequality in premature mortality into shared and group-specific risks to better inform health policy.

SETTING

All 50 US states and the District of Columbia, 2010 to 2015.

PARTICIPANTS

A total of 2.85 million non-Hispanic white and 762 639 non-Hispanic black US-resident decedents.

PRIMARY AND SECONDARY OUTCOME MEASURES

The race-specific county-level relative risks for US blacks and whites, separately, and the risk ratio between groups.

RESULTS

There is substantial geographic variation in premature mortality for both groups and the risk ratio between groups. After adjusting for median household income, county-level relative risks ranged from 0.46 to 2.04 (median: 1.03) for whites and from 0.31 to 3.28 (median: 1.15) for blacks. County-level risk ratios (black/white) ranged from 0.33 to 4.56 (median: 1.09). Half of the geographic variation in white premature mortality was shared with blacks, while only 15% of the geographic variation in black premature mortality was shared with whites. Non-Hispanic blacks experience substantial geographic variation in premature mortality that is not shared with whites. Moreover, black-specific geographic variation was not accounted for by median household income.

CONCLUSION

Understanding geographic variation in mortality is crucial to informing health policy; however, estimating mortality is difficult at small spatial scales or for small subpopulations. Bayesian joint spatial models ameliorate many of these issues and can provide a nuanced decomposition of risk. Using premature mortality as an example application, we show that Bayesian joint spatial models are a powerful tool as researchers grapple with disentangling neighbourhood contextual effects and sociodemographic compositional effects of an area when evaluating health outcomes. Further research is necessary in fully understanding when and how these models can be applied in an epidemiological setting.

The Role of Academic Health Centers in Addressing Health Equity and Social Determinants of Health

Elsewhere in this issue, Park and colleagues argue that academic health centers (AHCs) must partner with communities to address health disparities and social determinants of health (SDOH). Who is ultimately responsible for addressing them is in question. Countries that have been successful in improving the health of their populations have made these efforts a national priority by, among other things, ensuring universal health care coverage. To date, the United States has failed to adequately address these issues. Health care providers will have an important role to play in doing so, albeit a limited one. Under fee-for-service reimbursement, health care providers are paid for health care services and not for improving the health of populations. Capitated reimbursement might provide more of an incentive to focus on population health. Furthermore, AHCs are a heterogeneous group. Some are research-intensive referral centers, some are community providers, others are safety net providers, and still others are hybrids. Different types of AHCs will address SDOH differently. The scourge of poverty and associated health disparities and their underlying SDOH in the United States must be addressed. Providing affordable, comprehensive, universal health care must be a necessary first step. AHCs must educate about these issues, research and develop new approaches to ameliorate these inequities, and undertake appropriate demonstration projects in dealing with these disparities in well-defined populations. Health care providers, including AHCs, cannot take principal responsibility for issues beyond their scope and financial capabilities.

Applying a Health Equity Lens to Evaluate and Inform Policy

Health disparities have persisted despite decades of efforts to eliminate them at the national, regional, state and local levels. Policies have been a driving force in creating and exacerbating health disparities, but they can also play a major role in eliminating disparities. Research evidence and input from affected community-level stakeholders are critical components of evidence-based health policy that will advance health equity. The Transdisciplinary Collaborative Center (TCC) for Health Disparities Research at Morehouse School of Medicine consists of five subprojects focused on studying and informing health equity policy related to maternal-child health, mental health, health information technology, diabetes, and leadership/workforce development. This article describes a "health equity lens" as defined, operationalized and applied by the TCC to inform health policy development, implementation, and analysis. Prioritizing health equity in laws and organizational policies provides an upstream foundation for ensuring that the laws are implemented at the midstream and downstream levels to advance health equity.

Randomized Controlled Trial of Motivational Interviewing to Support Breastfeeding Among Appalachian Women

OBJECTIVE

To determine the effectiveness of a single session of prenatal motivational interviewing (MI) to enhance breastfeeding outcomes.

DESIGN

A randomized controlled trial with two groups (MI and psychoeducation) with repeated measures: preintervention, postintervention, and at 1 month postpartum.

SETTING

The intervention was conducted at a university-associated clinic, community locations, and participants' homes. Postpartum follow-up was conducted by telephone.

PARTICIPANTS

A total of 81 women with low-risk pregnancies enrolled at 28 to 39 weeks gestation who lived in Appalachia.

METHODS

Participants were randomly assigned to MI or psychoeducation on infant development. Pre- and postintervention outcome measures included intention to breastfeed, confidence in and importance of breastfeeding plan, and breastfeeding attitudes. At 1 month postpartum, participants completed a telephone interview to assess actual breastfeeding initiation, exclusivity, and plans to continue breastfeeding.

RESULTS

At 1 month postpartum, women in the MI group were more likely to report any current breastfeeding than women in the psychoeducation group, regardless of parity, χ²(1, N = 79) = 4.30, p = .040, Φ = .233. At the postintervention time point, the MI intervention had a significant effect on improving attitudes about breastfeeding among primiparous women only (p < .05).

CONCLUSION

One session of MI was effective to promote breastfeeding at 1 month postpartum and to enhance positive attitudes toward breastfeeding among primiparous women in Appalachia.

Solutions to the Challenge of Meeting Rural Transportation Needs: Middle-Aged and Older Adults' Perspectives

This study aimed to explore how the aging population in Appalachia manages its transportation and plans for the transition to non-driving and to seek possible solutions to the challenge of meeting rural transportation needs. Four focus groups (N = 38) were conducted, supplemented by a questionnaire, in Appalachian Kentucky. The results showed that few alternative transportation existed except a local paratransit service and informal transportation support. Compared to older adults, middle-aged adults reported a greater willingness to use mobile phones and the Internet to arrange transportation if they were available. Participants also recommended expanding the use of existing transportation in the community - such as church vans - to better meet the aging population's needs. The findings suggest that partnership between government, non-profit, and private sectors is needed, not solely focusing on a tax-dependent solution. Additionally, information and communication technology-based transportation management system would help maximize the use of scare but existing resources in rural areas.

Poverty, urban-rural classification and term infant mortality: a population-based multilevel analysis

Background

U.S. mortality rate of term infants is higher than most other developed countries. Term infant mortality is associated with exogenous socio-environmental factors. Previous research links low socioeconomic status and rurality with high infant mortality, but does not examine the effect of individual level factors on this association. Separating out the effect of contextual factors from individual level factors has important implications for targeting interventions. Therefore, we aim to estimate the independent effect of poverty and urban-rural classification on term infant mortality.

Methods

We used linked 2013 period cohort birth-infant death files from the National Center for Health Statistics (NCHS). Counties were assigned to low, medium and high poverty groups using US Census Bureau county-level percent of children ≤18 years living in poverty, and were classified based on NCHS urban-rural classification. Bivariate and multilevel logistic regression models were used to estimate odds of term infant death, accounting for individual and county level variables.

Results

There were 2,551,828 term births in 2013, with an overall term mortality of 2.1 per 1000 births. Odds of term infant mortality increased from 1.4 (95% CI: 1.2, 1.6) to 1.8 (95% CI: 1.6, 2.0) comparing births over increasing county poverty to those in the lowest. The associations remained significant in the multivariable model, for highest poverty 1.3 (95% CI: 1.1, 1.5). Similarly, the odds of term infant mortality increased with increasing rurality, from 1.3 (95% CI: 1.2, 1.5) in medium metro counties to 1.7 (95% CI: 1.5, 2.0) in non-core counties compared to large fringe metro counties. However, only rural non-core counties remained statistically associated with increased risk of term infant mortality after adjusting for individual level maternal characteristics.

Conclusions

High poverty and very rural counties remained associated with term infant mortality independent of individual maternal sociodemographic, health and obstetric factors. Interventions should focus on contextual factors such as economic environment and availability of health and social services in addition to individual factors to reduce term infant mortality.

Infant Mortality in the United States, 1915-2017: Large Social Inequalities have Persisted for Over a Century

OBJECTIVES

We examined trends in racial/ethnic, socioeconomic, and geographic disparities in age- and cause-specific infant mortality in the United States during 1915-2017.

METHODS

Log-linear regression and inequality indices were used to analyze temporal infant mortality data from the National Vital Statistics System and the National Linked Birth/Infant Death files according to maternal and infant characteristics.

RESULTS

During 1915-2017, the infant mortality rate (IMR) declined dramatically overall and for black and white infants; however, black/white disparities in mortality generally increased through 2000. Racial disparities were greater in post-neonatal mortality than neonatal mortality. Detailed racial/ethnic comparisons show an approximately five-fold difference in IMR, ranging from a low of 2.3 infant deaths per 1,000 live births for Chinese infants to a high of 8.5 for American Indian/Alaska Natives and 11.2 for black infants. Infant mortality from major causes of death showed a downward trend during the past 5 decades although there was a recent upturn in mortality from prematurity/low birthweight and unintentional injury. In 2016, black infants had 2.5-2.8 times higher risk of mortality from perinatal conditions, sudden infant death syndrome, influenza/pneumonia, and unintentional injuries, and 1.3 times higher risk of mortality from birth defects compared to white infants. Educational disparities in infant mortality widened between 1986 and 2016; mothers with less than a high school education in 2016 experienced 2.4, 1.9, and 3.7 times higher risk of infant, neonatal, and post-neonatal mortality than those with a college degree. Geographic disparities were marked and widened across regions, with states in the Southeast region having higher IMRs.

CONCLUSIONS AND GLOBAL HEALTH IMPLICATIONS

Social inequalities in infant mortality have persisted and remained marked, with the disadvantaged ethnic and socioeconomic groups and geographic areas experiencing substantially increased risks of mortality despite the declining trend in mortality over time. Widening social inequalities in infant mortality are a major factor contributing to the worsening international standing of the United States.