Social and Environmental Characteristics Associated With Older Drivers' Use of Non-driving Transportation Modes.

Objective: We examined associations between older drivers' social and environmental characteristics and odds of using non-driving transportation modes. Methods: Using 2015 National Health and Aging Trends Study data for community-dwelling drivers (n = 5102), we estimated logistic regression models of associations between social characteristics, environmental characteristics, and odds of using non-driving transportation modes three years later. Results: Drivers had 20% increase in odds of getting rides three years later for each additional confidante (adjusted odds ratio [aOR] = 1.20, 95% confidence interval [CI]: 1.11-1.30). Drivers living in more walkable neighborhoods were more likely to walk to get places (National Walkability Index [NWI] score of 18 vs. 2 aOR = 1.71, 95% CI: 1.02-2.90) and take public transit three years later (NWI 18 vs. 2 aOR = 7.47, 95% CI: 1.69-33.0). Discussion: Identifying modifiable social and environmental characteristics can inform future interventions supporting older adults' health during the transition to non-driving.

Getting Rides From Others As a Coping Mechanism in the Transition to Non-Driving.

OBJECTIVES: To characterize the effect of the actual and potential ability to get rides from others on older adults' driving reduction at 3-year follow-up in the United States. METHODS: We analyzed National Health and Aging Trends Study data from community-dwelling drivers in 2015 (unweighted n = 5,102). We used weighted logistic regression models to estimate whether getting rides from others in 2015 was associated with older adults increasing the number of driving behaviors they avoided, decreasing the frequency with which they drove, or not driving at 3-year follow-up after adjusting for biopsychosocial variables. We also measured presence of social network members living nearby including household and non-household members and estimated associated odds of driving reduction at 3-year follow-up. RESULTS: Older adults who got rides from others in 2015 had greater odds of reporting no longer driving at 3-year follow-up compared to those who did not get rides (adjusted odds ratio [aOR] = 1.53, 95% confidence interval [CI]: 1.11-2.11). We found no statistically significant association between older adults living with others or having more nearby confidantes outside their household and their odds of reducing driving at 3-year follow-up. DISCUSSION: These findings suggest that getting rides from others plays an important role in the transition to non-driving for older adults. Future research should examine whether other aspects of social networks (e.g., type, quality, and closer proximity) might also be key modifiable coping factors for older adults transitioning to non-driving.

Measuring Age-Friendliness of Transportation and Mobility Characteristics in Communities: A Scoping Review.

BACKGROUND AND OBJECTIVES: Age-friendly communities are those with characteristics that can support and promote healthy aging. Among the common domains of these characteristics, transportation and neighborhood spaces are particularly relevant for older adults maintaining mobility in their communities. The objective of this scoping review is to provide a synthesis of age-friendly community indicators, developed for research and planning, that evaluate characteristics most associated with community-level mobility, specifically transportation and neighborhood spaces. RESEARCH DESIGN AND METHODS: We conducted a systematic search of PubMed, Scopus, Medline, APA PsychInfo, CINAHL Plus, SocIndex, Academic Search Premier, and Web of Science. We reviewed 8 articles and reports that described the development or evaluation of a set of generalizable indicators to measure the age-friendliness of a community's transportation and neighborhood spaces resources. RESULTS: Indicators of transportation and neighborhood spaces ranged from self-reported measures of accessibility and convenience to objective measures of the availability and cost of services. Explicit discussion of mobility at the community level was variable in these records, and few authors specifically discussed common life transitions impacted by these age-friendly community indicators, such as driving cessation. DISCUSSION AND IMPLICATIONS: Although age-friendly communities are a well-established goal for promoting healthy aging, our review found few validated approaches for measuring age-friendliness that researchers and communities can use to investigate mobility at the community level. This is an important gap in studying life transitions such as driving cessation. Further research can provide a better understanding of which community characteristics support ongoing mobility.

Transportation Justice and Health.

Policy Points The health care sector is increasingly investing in social conditions, including availability of safe, reliable, and adequate transportation, that contribute to improving health. In this paper, we suggest ways to advance the impact of transportation interventions and highlight the limitations of how health services researchers and practitioners currently conceptualize and use transportation. Incorporating a transportation justice framework offers an opportunity to address transportation and mobility needs more comprehensively and equitably within health care research, delivery, and policy.

Evaluating How Safety-Net Hospitals Are Identified: Systematic Review and Recommendations.

Objective: To systematically review how safety-net hospitals' status is identified and defined, discuss current definitions' limitations, and provide recommendations for a new classification and evaluation framework. Data Sources: Safety-net hospital-related studies in the MEDLINE database published before May 16, 2019. Study Design: Systematic review of the literature that adheres to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Data Collection/Extraction Methods: We followed standard selection protocol, whereby studies went through an abstract review followed by a full-text screening for eligibility. For each included study, we extracted information about the identification method itself, including the operational definition, the dimension(s) of disadvantage reflected, study objective, and how safety-net status was evaluated. Principal Findings: Our review identified 132 studies investigating safety-net hospitals. Analysis of identification methodologies revealed substantial heterogeneity in the ways disadvantage is defined, measured, and summarized at the hospital level, despite a 4.5-fold increase in studies investigating safety-net hospitals for the past decade. Definitions often exclusively used low-income proxies captured within existing health system data, rarely incorporated external social risk factor measures, and were commonly separated into distinct safety-net status categories when analyzed. Conclusions: Consistency in research and improvement in policy both require a standard definition for identifying safety-net hospitals. Yet no standardized definition of safety-net hospitals is endorsed and existing definitions have key limitations. Moving forward, approaches rooted in health equity theory can provide a more holistic framework for evaluating disadvantage at the hospital level. Furthermore, advancements in precision public health technologies make it easier to incorporate detailed neighborhood-level social determinants of health metrics into multidimensional definitions. Other countries, including the United Kingdom and New Zealand, have used similar methods of identifying social need to determine more accurate assessments of hospital performance and the development of policies and targeted programs for improving outcomes.

Hospital Characteristics by Proportion of Patients from Disadvantaged Neighborhoods.

Neighborhood disadvantage reflects historic and ongoing systemic injustices. Without addressing these upstream social determinants of health, hospitals may face different risk profiles for important quality metrics. Our objective was to assess differences in hospital characteristics where the proportion of patients residing in severely disadvantaged neighborhoods was high vs low. Using Medicare fee-for-service claims between January 1, 2014 and November 30, 2014 (5,807,499 hospital stays), we calculated Area Disadvantage Share (ADS), the proportion of each hospital's discharges to severely disadvantaged neighborhoods, for 4,528 hospitals. We examined hospital characteristics by distribution of ADS and by risk-adjusted 30-day readmission. Hospitals in the highest decile cared for a higher proportion of Black patients, were more often located in rural areas, and had higher patient risk of 30-day readmission compared to all other deciles. Hospitals face unequal burdens of neighborhood disadvantage, a factor distinct from other social determinants such as rurality.

Defining the "New Normal" in Primary Care.

Health care organizations in the United States have transformed at an unprecedented rate since March 2020 due to COVID-19, most notably with a shift to telemedicine. Despite rapidly adapting health care delivery in light of new safety considerations and a shifting insurance landscape, primary care offices across the country are facing drastic decreases in revenue and potential bankruptcy. To survive, primary care's adaptations will need to go beyond virtual versions of traditional office visits. Primary care is faced with a chance to redefine what it means to care for and support patients wherever they are. This opportunity to shape the "new normal" is a critical step for primary care to meet its full potential to lead a paradigm shift to patient-centered health care reform in America during this time when we need it most.

A Scoping Review of the Association of Social Disadvantage and Cerebrovascular Disease Confirmed by Neuroimaging and Neuropathology.

Social disadvantage-a state of low-income, limited education, poor living conditions, or limited social support-mediates chronic health conditions, including cerebrovascular disease. Social disadvantage is a key component in several health impact frameworks, providing explanations for how individual-level factors interact with interpersonal and environmental factors to create health disparities. Understanding the association between social disadvantage and vascular neuropathology, brain lesions identified by neuroimaging and autopsy, could provide insight into how one's social context interacts with biological processes to produce disease. The goal of this scoping review was to evaluate the scientific literature on the relationship between social disadvantage and cerebrovascular disease, confirmed through assessment of vascular neuropathology. We reviewed 4049 titles and abstracts returned from our search and included records for full-text review that evaluated a measure of social disadvantage as an exposure variable and cerebrovascular disease, confirmed through assessment of vascular neuropathology, as an outcome measure. We extracted exposures and outcomes from 20 articles meeting the criteria after full-text review, and described the study findings and populations sampled. An improved understanding of the link between social factors and cerebrovascular disease will be an important step in moving the field closer to addressing the fundamental causes of disease and towards more equitable brain health.