Programs and Communities

Diabetes, a common chronic condition, effects many individuals causing poor quality of life, expensive medical bills, and devastating medical complications. While health care providers try to manage diabetes during short office visits, many patients still struggle to control their diabetes at home. Lack of diabetes self-management (DSM) is a potential barrier for people with diabetes having to maintain healthy hemoglobin A1cs (HgA1c).

In hopes of addressing this concern, an evidenced-based intervention; diabetic education and phone calls, using the chronic care model as its framework was implemented. The intervention targeted people with type II diabetes at a transitional care setting. Measured variables included HgA1c and DSM. Statistically significant improvements were seen in reported physical activity. Average improvements were seen in HgA1c and DSM after three months of diabetes self-management education (DSME). Attrition, cultural sensitivity, and increasing DSME hours should be further evaluated for future projects.

Background and Purpose: Over 30 million people in the United States (U.S.) have diabetes mellitus, which comprises about 9% of the population, and about 90% of individuals with diabetes have type 2 diabetes (Centers for Disease Control and Prevention [CDC], 2017). Adults with type 2 diabetes at a local internal medicine clinic were consistently having high glycated hemoglobin (HbA1C) levels, demonstrated by data collected from the electronic health record (EHR), and there was no ordering process for referring patients to diabetes management education and support (DSMES) services. The purpose of this project was to improve glycemic control, demonstrated by lower HbA1C levels, and reach a diabetes education attendance rate of 62.5% at an internal medicine clinic in Chandler, Arizona.

Methods: An electronic health record (EHR) template was created and brief staff training was completed to connect patients with diabetes in the community to a local formal diabetes education program. HbA1C levels were measured before and three months after adults with education program. HbA1C levels were measured before and three months after adults with type 2 diabetes mellitus (T2DM) received physicians’ orders for a DSMES program, and rates of attendance to the program were calculated. Data was collected through the EHR and through feedback from the DSMES program. Descriptive statistics were used in data analysis.

Outcomes: The participants’ results did not demonstrate significant differences in pre-referral and post-referral HbA1C results after they were ordered DSMES services (p = .506). The proportion of education attendance (30%) was lower than the project goal of 62.5%, but increased from the clinic baseline.

Conclusions: EHR template implementation for referral to DSMES may increase rates of formal diabetes education and improve glycemic control. Larger sample sizes, longer project periods, alternative methods of communication, and increased follow-up of participants may be required to produce significant results.

Background: The global prevalence of all types of diabetes increased from 108 million in 1980 to 422 million in 2014 (Nazir et al., 2018). The Centers for Disease Control and Prevention (2017) ranks diabetes as the 7th leading cause of death in the United States with an estimated annual expense of $327 billion. Within the rural setting, patients typically have less resources available for the treatment and self-management of their diseases. It is important to explore self-management techniques that can be utilized by patients with type 2 diabetes living in rural areas. Research demonstrating the importance of education, exercise, diet, glucose monitoring, medications, and supportive measures is prominent throughout the literature.

Objective: The purpose of this Doctor of Nursing Practice (DNP) applied project is to investigate the effects of delivering biweekly text messages containing diabetes self-management education (DSME) materials to patients in an effort to support successful self-care.

Methods: During an 8 week period, DSME was provided via text messaging, bi-weekly (Sunday and Wednesday), to 23 rural participants with type 2 diabetes, in a family clinic in Payson, Arizona. Participants were asked to complete the Skills, Confidence, and Preparedness Index both pre- and post-intervention to evaluate their knowledge of diabetes self-management.

Results: Twenty-three adults aged 52 to 78 years (M = 64.91) participated in the project. Of the participants, 57% (13/23) were female. The majority of participants had T2DM diagnosis less than 10 years (M=13.8 years). There was a statistical difference between the pre- and post-Skills, Confidence and Preparedness Index questionnaire (p < .001) indicating an improvement in self-efficacy scores post- intervention.

Conclusion: DSME delivered via text message is a cost-effective way to increase patients' self-efficacy and potentially improve their ability to successfully self-manage their disease.

This study assessed the spatial distribution of vulnerability to extreme heat in 1990 and 2000 within metropolitan Phoenix based on an index of seven equally weighted measures of physical exposure and adaptive capacity. These measures were derived from spatially interpolated climate, normalized differential vegetation index, and U.S. Census data. From resulting vulnerability maps, we also analyzed population groups living in areas of high heat vulnerability. Results revealed that landscapes of heat vulnerability changed substantially in response to variations in physical and socioeconomic factors, with significant alterations to spatial distribution of vulnerability especially between eastern and western sectors of Phoenix. These changes worked to the detriment of Phoenix's Hispanic population and the elderly concentrated in urban-fringe retirement communities.

Context:
With rapidly expanding urban regions, the effects of land cover changes on urban surface temperatures and the consequences of these changes for human health are becoming progressively larger problems.

Objectives:
We investigated residential parcel and neighborhood scale variations in urban land surface temperature, land cover, and residents’ perceptions of landscapes and heat illnesses in the subtropical desert city of Phoenix, AZ USA.

Methods:
We conducted an airborne imaging campaign that acquired high resolution urban land surface temperature data (7 m/pixel) during the day and night. We performed a geographic overlay of these data with high resolution land cover maps, parcel boundaries, neighborhood boundaries, and a household survey.

Results:
Land cover composition, including percentages of vegetated, building, and road areas, and values for NDVI, and albedo, was correlated with residential parcel surface temperatures and the effects differed between day and night. Vegetation was more effective at cooling hotter neighborhoods. We found consistencies between heat risk factors in neighborhood environments and residents’ perceptions of these factors. Symptoms of heat-related illness were correlated with parcel scale surface temperature patterns during the daytime but no corresponding relationship was observed with nighttime surface temperatures.

Conclusions:
Residents’ experiences of heat vulnerability were related to the daytime land surface thermal environment, which is influenced by micro-scale variation in land cover composition. These results provide a first look at parcel-scale causes and consequences of urban surface temperature variation and provide a critically needed perspective on heat vulnerability assessment studies conducted at much coarser scales.

Background: Vulnerability mapping based on vulnerability indices is a pragmatic approach for highlighting the areas in a city where people are at the greatest risk of harm from heat, but the manner in which vulnerability is conceptualized influences the results.

Objectives: We tested a generic national heat-vulnerability index, based on a 10-variable indicator framework, using data on heat-related hospitalizations in Phoenix, Arizona. We also identified potential local risk factors not included in the generic indicators.

Methods: To evaluate the accuracy of the generic index in a city-specific context, we used factor scores, derived from a factor analysis using census tract–level characteristics, as independent variables, and heat hospitalizations (with census tracts categorized as zero-, moderate-, or highincidence) as dependent variables in a multinomial logistic regression model. We also compared the geographical differences between a vulnerability map derived from the generic index and one derived from actual heat-related hospitalizations at the census-tract scale.

Results: We found that the national-indicator framework correctly classified just over half (54%) of census tracts in Phoenix. Compared with all census tracts, high-vulnerability tracts that were misclassified by the index as zero-vulnerability tracts had higher average income and higher proportions of residents with a duration of residency < 5 years.

Conclusion: The generic indicators of vulnerability are useful, but they are sensitive to scale, measurement, and context. Decision makers need to consider the characteristics of their cities to determine how closely vulnerability maps based on generic indicators reflect actual risk of harm.

Climate change is predicted to increase the intensity and negative impacts of urban heat events, prompting the need to develop preparedness and adaptation strategies that reduce societal vulnerability to extreme heat. Analysis of societal vulnerability to extreme heat events requires an interdisciplinary approach that includes information about weather and climate, the natural and built environment, social processes and characteristics, interactions with stakeholders, and an assessment of community vulnerability at a local level. In this letter, we explore the relationships between people and places, in the context of urban heat stress, and present a new research framework for a multi-faceted, top-down and bottom-up analysis of local-level vulnerability to extreme heat. This framework aims to better represent societal vulnerability through the integration of quantitative and qualitative data that go beyond aggregate demographic information. We discuss how different elements of the framework help to focus attention and resources on more targeted health interventions, heat hazard mitigation and climate adaptation strategies.

Extreme heat is a natural hazard that could rapidly increase in magnitude in the 21st century. The combination of increasingurbanization, growing numbers of vulnerable people, and the evidence of global warming indicate an urgent need for improved heat-wavemitigation and response systems. A review of the literature on heat-wave impacts in urban environments and on human health revealsopportunities for improved synthesis, integration, and sharing of information resources that relate to the spatial and temporal nature ofthreats posed by extreme heat. This paper illustrates how geospatial technologies can aid in the mitigation of urban heat waves.

Global environmental change and sustainability science increasingly recognize the need to address the consequences of changes taking place in the structure and function of the biosphere. These changes raise questions such as: Who and what are vulnerable to the multiple environmental changes underway, and where? Research demonstrates that vulnerability is registered not by exposure to hazards (perturbations and stresses) alone but also resides in the sensitivity and resilience of the system experiencing such hazards. This recognition requires revisions and enlargements in the basic design of vulnerability assessments, including the capacity to treat coupled human–environment systems and those linkages within and without the systems that affect their vulnerability. A vulnerability framework for the assessment of coupled human–environment systems is presented.

Research on global environmental change has significantly improved our understanding of the structure and function of the biosphere and the human impress on both (1). The emergence of “sustainability science” (2–4) builds toward an understanding of the human–environment condition with the dual objectives of meeting the needs of society while sustaining the life support systems of the planet. These objectives, in turn, require improved dialogue between science and decision making (5–8). The vulnerability of coupled human–environment systems is one of the central elements of this dialogue and sustainability research (6, 9–11). It directs attention to such questions as: Who and what are vulnerable to the multiple environmental and human changes underway, and where? How are these changes and their consequences attenuated or amplified by different human and environmental conditions? What can be done to reduce vulnerability to change? How may more resilient and adaptive communities and societies be built?

Answers to these and related questions require conceptual frameworks that account for the vulnerability of coupled human–environment systems with diverse and complex linkages. Various expert communities have made considerable progress in pointing the way toward the design of these frameworks (10, 11). These advances are briefly reviewed here and, drawing on them, we present a conceptual framework of vulnerability developed by the Research and Assessment Systems for Sustainability Program (http://sust.harvard.edu) that produced the set of works in this Special Feature of PNAS. The framework aims to make vulnerability analysis consistent with the concerns of sustainability and global environmental change science. The case study by Turner et al. (12) in this issue of PNAS illustrates how the framework informs vulnerability assessments.

Background:
The evidence that heat waves can result in both increased deaths and illness is substantial, and concern over this issue is rising because of climate change. Adverse health impacts from heat waves can be avoided, and epidemiologic studies have identified specific population and community characteristics that mark vulnerability to heat waves.

Objectives:
We situated vulnerability to heat in geographic space and identified potential areas for intervention and further research.

Methods:
We mapped and analyzed 10 vulnerability factors for heat-related morbidity/mortality in the United States: six demographic characteristics and two household air conditioning variables from the U.S. Census Bureau, vegetation cover from satellite images, and diabetes prevalence from a national survey. We performed a factor analysis of these 10 variables and assigned values of increasing vulnerability for the four resulting factors to each of 39,794 census tracts. We added the four factor scores to obtain a cumulative heat vulnerability index value.

Results:
Four factors explained > 75% of the total variance in the original 10 vulnerability variables: a) social/environmental vulnerability (combined education/poverty/race/green space), b) social isolation, c) air conditioning prevalence, and d) proportion elderly/diabetes. We found substantial spatial variability of heat vulnerability nationally, with generally higher vulnerability in the Northeast and Pacific Coast and the lowest in the Southeast. In urban areas, inner cities showed the highest vulnerability to heat.

Conclusions:
These methods provide a template for making local and regional heat vulnerability maps. After validation using health outcome data, interventions can be targeted at the most vulnerable populations.