Problem, research strategy, and findings: News reports and academic articles contend that Millennials (those born in the last two decades of the 20th century) are different from earlier generations ...in their consumption and travel patterns. This article investigates the travel behavior of young American adults and compares the behavior of Millennials with those of previous generations using data from the 1995, 2001, and 2009 National Household Travel Surveys. The analysis uses descriptive statistics to profile trends and regression models to identify the factors associated with decreased travel by Millennials. In fact, automobility declines for all Americans between 1995 and 2009, but the drops are largest for Millennials and younger members of Generation X starting in the late 1990s. Decreases in driving are not compensated by increases in the use of other modes for travel, nor do decreased trip distances explain the downturn in automobility. Among young adults, lifestyle-related demographic shifts, including decreased employment, explain 10% to 25% of the decrease in driving; Millennial-specific factors such as changing attitudes and use of virtual mobility (online shopping, social media) explain 35% to 50% of the drop in driving; and the general dampening of travel demand that occurred across all age groups accounts for the remaining 40%.
Takeaway for practice: These changes highlight two challenges to planners and policymakers: managing increases in automobility as Millennials age and their economic fortunes improve, and developing improved planning processes that deal robustly with the uncertain future presented by Millennials who may continue to make very different travel choices than comparable people did in the past.
Rising rates of overweight children have focused attention on walking and biking to school as a means to increase children's physical activity levels. Despite this attention, there has been little ...documentation of trends in school travel over the past 30 years or analysis of what has caused the changes in mode choice for school trips.
This article analyzes data from the 1969, 1977, 1983, 1990, 1995, and 2001 National Personal Transportation Survey conducted by the U.S. Department of Transportation to document the proportion of students actively commuting to school in aggregate and by subgroups and analyze the relative influence of trip, child, and household characteristics across survey years. All analyses were done in 2006.
The National Personal Transportation Survey data show that in 1969, 40.7% (95% confidence interval CI=37.9-43.5) of students walked or biked to school; by 2001, the proportion was 12.9% (95% CI=11.8-13.9). Distance to school has increased over time and may account for half of the decline in active transportation to school. It also has the strongest influence on the decision to walk or bike across survey years.
Declining rates of active transportation among school travelers represents a worrisome loss of physical activity. Policymakers should continue to support programs designed to encourage children to walk to school such as Safe Routes to School and the Centers for Disease Control and Prevention's KidsWalk. In addition, officials need to design policies that encourage schools to be placed within neighborhoods to ensure that the distance to school is not beyond an acceptable walking distance.
Context Some evidence suggests that treating vascular risk factors and performing mentally stimulating activities may delay cognitive impairment onset in older adults. Exposure to a complex ...neighborhood environment may be one mechanism to help delay cognitive decline. Evidence acquisition PubMed, Web of Science, and ProQuest Dissertation and Theses Global database were systematically reviewed, identifying 25 studies published from February 1, 1989 to March 5, 2016 (data synthesized, May 3, 2015 to October 7, 2016). The review was restricted to quantitative studies focused on: (1) neighborhood social and built environment and cognition; and (2) community-dwelling adults aged ≥45 years. Evidence synthesis The majority of studies were cross-sectional, U.S.-based, and found at least one significant association. The diversity of measures and neighborhood definitions limited the synthesis of findings in many instances. Evidence was moderately strong for an association between neighborhood SES and cognition, and modest for associations between neighborhood demographics, design, and destination accessibility and cognition. Most studies examining effect modification found significant associations, with some evidence for effect modification of the neighborhood SES−cognition association by individual-level SES. No studies had low risk of bias and many tested multiple associations that increased the chance of a statistically significant finding. Considering the studies to date, the evidence for an association between neighborhood characteristics and cognition is modest. Conclusions Future studies should include longitudinal measures of neighborhood characteristics and cognition; examine potential effect modifiers, such as sex and disability; and study mediators that may help elucidate the biological mechanisms linking neighborhood environment and cognition.
To quantify the number of people in the US who delay medical care annually because of lack of available transportation and to examine the differential prevalence of this barrier for adults across ...sociodemographic characteristics and patient populations.
We used data from the National Health Interview Survey (1997-2017) to examine this barrier over time and across groups. We used joinpoint regression analysis to identify significant changes in trends and multivariate analysis to examine correlates of this barrier for the year 2017.
In 2017, 5.8 million persons in the United States (1.8%) delayed medical care because they did not have transportation. The proportion reporting transportation barriers increased between 2003 and 2009 with no significant trends before or after this window within our study period. We found that Hispanic people, those living below the poverty threshold, Medicaid recipients, and people with a functional limitation had greater odds of reporting a transportation barrier after we controlled for other sociodemographic and health characteristics.
Transportation barriers to health care have a disproportionate impact on individuals who are poor and who have chronic conditions. Our study documents a significant problem in access to health care during a time of rapidly changing transportation technology.
U.S. pedestrian fatalities have risen recently, even as vehicles are equipped with increasingly sophisticated safety and crash avoidance technology. Many experts expect that advances in automated ...vehicle technology will reduce pedestrian fatalities substantially through eliminating crashes caused by human error. This paper investigates automated vehicles’ potential for reducing pedestrian fatalities by analyzing nearly 5,000 pedestrian fatalities recorded in 2015 in the Fatality Analysis Reporting System, virtually reconstructing them under a hypothetical scenario that replaces involved vehicles with automated versions equipped with state-of-the-art (as of December 2017) sensor technology.
This research involved the following activities: (1) establish functional ranges of state-of-the-art pedestrian sensor technologies, (2) use data from the Fatality Analysis Reporting System to identify pedestrian fatalities recorded in each state in the U.S. and District of Columbia in 2015, and (3) assess the maximum numbers of pedestrian fatalities that could have been avoided had involved vehicles been replaced with autonomous versions equipped with the described sensors. The research was conducted from July to December 2017.
Sensors’ abilities to detect pedestrians in advance of fatal collisions vary from <30% to >90% of fatalities. Combining sensor technologies offers the greatest potential for eliminating fatalities, but may be unrealistically expensive. Furthermore, whereas initial deployment of automated vehicles will likely be restricted to freeways and select urban areas, non-freeway streets and rural settings account for a substantial share of pedestrian fatalities.
Although technologies are being developed for automated vehicles to successfully detect pedestrians in advance of most fatal collisions, the current costs and operating conditions of those technologies substantially decrease the potential for automated vehicles to radically reduce pedestrian fatalities in the short term.
Rising levels of childhood obesity in the United States and a 75% decline in the proportion of children walking to school in the past 30 years have focused attention on school travel. This paper uses ...data from the US Department of Transportation’s 2001 National Household Travel Survey to analyze the factors affecting mode choice for elementary and middle school children. The analysis shows that walk travel time is the most policy-relevant factor affecting the decision to walk to school with an estimated direct elasticity of −0.75. If policymakers want to increase walking rates, these findings suggest that current policies, such as Safe Routes to School, which do not affect the spatial distribution of schools and residences will not be enough to change travel behavior. The final part of the paper uses the mode choice model to test how a land use strategy—community schools—might affect walking to school. The results show that community schools have the potential to increase walking rates but would require large changes from current land use, school, and transportation planning practices.
Walking to school may be an important source of daily physical activity in children's lives, and government agencies are supporting programs to encourage walking to school (e.g., Safe Routes to ...School and the CDC's KidsWalk programs). However, little research has looked at differences in behavior across racial/ethnic and income groups.
This cross-sectional study used data from the 2001 National Household Travel Survey to document rates of walking and biking to school among low-income and minority youth in the U.S. (N=14,553). Binary models of the decision to use active transport to school were developed to simultaneously adjust for trip, individual, household, and neighborhood correlates. All analyses were conducted in 2007.
The data showed that low-income and minority groups, particularly blacks and Hispanics, use active travel modes to get to school at much higher rates than whites or higher-income students. However, racial variation in travel patterns is removed by controlling for household income, vehicle access, distance between home and school, and residential density.
Active transportation to school may be an important strategy to increase and maintain physical activity levels for low-income and minority youth. Current policy interventions such as Safe Routes to School have the opportunity to provide benefits for low-income and minority students who are the most likely to walk to school.
This study evaluates how household interactions affect walking and biking to school. The cross-sectional research design uses a representative sample of trips to school by US youth (
n
=
8231) to ...test how parental employment status and commute patterns affect non-motorized travel. Results from a binary logit model show that young children (5–14) with mothers who commute to work in the morning are less likely to walk or bike to school after controlling for individual, household, and neighborhood factors. Policymakers may therefore want to create programs that allow parents to share chaperoning responsibilities for the school trip to address parental time constraints.
Improving road safety and setting targets for reducing traffic-related crashes and deaths are highlighted as part of the United Nations sustainable development goals and worldwide vision zero ...efforts. The advent of transportation network companies and ridesourcing expands mobility options in cities and may impact road safety outcomes. We analyze the effects of ridesourcing use on road crashes, injuries, fatalities, and driving while intoxicated (DWI) offenses in Travis County, Texas. Our approach leverages real-time ridesourcing volume to explain variation in road safety outcomes. Spatial panel data models with fixed-effects are deployed to examine whether the use of ridesourcing is significantly associated with road crashes and other safety metrics. Our results suggest that for a 10% increase in ridesourcing trips, we expect a 0.12% decrease in road crashes, a 0.25% decrease in road injuries, and a 0.36% decrease in DWI offenses in Travis County. On the other hand, ridesourcing use is not significantly associated with road fatalities. This study augments existing work because it moves beyond binary indicators of ridesourcing availability and analyzes crash and ridesourcing trips patterns within an urbanized area rather than their metropolitan-level variation. Contributions include developing a data-rich approach for assessing the impacts of ridesourcing use on the transportation system's safety, which may serve as a template for future analyses for other cities. Our findings provide feedback to policymakers by clarifying associations between ridesourcing use and traffic safety and uncover the potential to achieve safer mobility systems with transportation network companies.
Abstract
Background
Transportation barriers prevent millions of people from accessing health care each year. Health policy innovations such as shared savings payment models (commonly used in ...accountable care organizations) present financial incentives for providers to offer patient transportation to medical care. Meanwhile, ridesourcing companies like Uber and Lyft have entered the market to capture a significant share of spending on non-emergency health care transportation. Our research examines the current landscape of innovative health care mobility services in the US.
Methods
We conducted an environmental scan to identify case examples of utilization of ridesourcing technology to facilitate non-emergency health care transportation and developed a typology of innovative health care mobility services. The scan used a keyword-based search of news publications with inductive analysis. For each instance identified, we abstracted key information including: stakeholders, launch date, transportation provider, location/service area, payment/booking method, target population, level of service, and any documented outcomes.
Results
We discovered 53 cases of innovation and among them we identified three core types of innovation or collaboration. The first and most common type of innovation is when a health care provider leverages ridesourcing technology to book patient trips. This involves both established and nascent transportation companies tailoring the ridesourcing experience to the health care industry by adding HIPAA-compliance to the booking process. The second type of innovation involves an insurer or health plan formally partnering with a ridesourcing company to expand transportation offerings to beneficiaries or offer these services for the first time. The third type of innovation is when a paratransit provider partners with a ridesourcing company; these cases cite increased flexibility and reliability of ridesourcing services compared to traditional paratransit.
Conclusions
Ridesourcing options are becoming a part of the mode choice set for patients through formal partnerships between ridesourcing companies, health care providers, insurers, and transit agencies. The on-demand nature of rides, booking flexibility, and integration of ride requests and payment options via electronic medical records appear to be the strongest drivers of this innovation.
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