Spinning the wheels and rolling the dice: life-cycle risks and benefits of bicycle commuting in the U.S

[The severely injured older cyclist-Evaluation of the TraumaRegister DGU® : Retrospective, multicenter cross-sectional study based on the TraumaRegister DGU®]

BACKGROUND

Contrary to the trend of decreasing traffic fatalities, the number of cyclists killed in Germany has been steadily increasing in recent years. With the increasing popularity of cycling in all age groups, the number of accidents with sometimes serious injuries is rising. In the course of this, the question arises what influence age has on the type and severity of injuries, the probability of survival and the length of hospital stay in seriously injured cyclists.

METHODS

A retrospective analysis of data from the TraumaRegister DGU® (TR-DGU) from 2010 to 2019 was performed. All severely injured cyclists with a maximum abbreviated injury scale (MAIS) of 3+ (n = 14,651) in the TR-DGU were included in this study and the available parameters were evaluated. A subdivision into three age groups (60-69, 70-79, and ≥ 80 years) and a control group (20-59 years) was carried out.

RESULTS

Injuries to the head were by far the most common, accounting for 64.2%. There was a marked increase in severe head injuries in the 60-plus years age group. Furthermore, with increasing age, the probability of prehospital intubation, catecholamine requirement, intensive care and hospital length of stay, and mortality increased.

CONCLUSION

Head injuries represent the most common serious injury, especially among older cyclists. As helmet wearing was not recorded in the TraumaRegister DGU® during the evaluation period, no conclusion can be drawn about its effect. Furthermore, a higher age correlates with a longer hospital stay and a higher mortality, but does not represent an independent risk factor for death in severely injured patients.

How do cyclists interact with motorized vehicles at unsignalized intersections? Modeling cyclists' yielding behavior using naturalistic data

When a cyclist's path intersects with that of a motorized vehicle at an unsignalized intersection, serious conflicts may happen. In recent years, the number of cyclist fatalities in this conflict scenario has held steady, while the number in many other traffic scenarios has been decreasing. There is, therefore, a need to further study this conflict scenario in order to make it safer. With the advent of automated vehicles, threat assessment algorithms able to predict cyclists' (other road users') behavior will be increasingly important to ensure safety. To date, the handful of studies that have modeled the vehicle-cyclist interaction at unsignalized intersections have used kinematics (speed and location) alone without using cyclists' behavioral cues, such as pedaling or gesturing. As a result, we do not know whether non-verbal communication (e.g., from behavioral cues) could improve model predictions. In this paper, we propose a quantitative model based on naturalistic data, which uses additional non-verbal information to predict cyclists' crossing intentions at unsignalized intersections. Interaction events were extracted from a trajectory dataset and enriched by adding cyclists' behavioral cues obtained from sensors. Both kinematics and cyclists' behavioral cues (e.g., pedaling and head movement), were found to be statistically significant for predicting the cyclist's yielding behavior. This research shows that adding information about the cyclists' behavioral cues to the threat assessment algorithms of active safety systems and automated vehicles will improve safety.

Assessment of Factors Influencing Personal Exposure to Air Pollution on Main Roads in Bogota: A Mixed-Method Study

Background and Objectives: Particulate Matter (PM), particles of variable but small diameter can penetrate the respiratory system via inhalation, causing respiratory and/or cardiovascular diseases. This study aims to evaluate the association of environmental particulate matter (PM_2.5) and black carbon (BC) with respiratory health in users of different transport modes in four roads in Bogotá. Materials and Methods: this was a mixed-method study (including a cross sectional study and a qualitative description of the air quality perception), in 300 healthy participants, based on an exploratory sequential design. The respiratory effect was measured comparing the changes between pre- and post-spirometry. The PM_2.5 and black carbon (BC) concentrations were measured using portable devices. Inhaled doses were also calculated for each participant according to the mode and route. Perception was approached through semi-structured interviews. The analysis included multivariate models and concurrent triangulation. Results: The concentration of matter and black carbon were greater in bus users (median 50.67 µg m^-3; interquartile range (-IR): 306.7). We found greater inhaled dosages of air pollutants among bike users (16.41 µg m^-3). We did not find changes in the spirometry parameter associated with air pollutants or transport modes. The participants reported a major sensory influence at the visual and olfactory level as perception of bad air quality. Conclusions: We observed greater inhaled doses among active transport users. Nevertheless, no pathological changes were identified in the spirometry parameters. People's perceptions are a preponderant element in the assessment of air quality.

Estimating the Health Effects of Adding Bicycle & Pedestrian Paths: Modeling At The Census Tract-Level (Preprint)

Background

Adding additional bicycle and pedestrian paths to an area can lead to improved health outcomes for residents over time. However, quantitatively determining which areas benefit more from bicycle and pedestrian paths, how many miles of bicycle and pedestrian paths are needed, and the health outcomes that may be most improved remain open questions.

Objective

Our work provides and evaluates a methodology that offers actionable insight for city-level planners, public health officials, and decision makers tasked with the question “To what extent will adding specified bicycle and pedestrian path mileage to a census tract improve residents’ health outcomes over time?”

Methods

We conducted a factor analysis of data from the American Community Survey, Center for Disease Control 500 Cities project, Strava, and bicycle and pedestrian path location and use data from two different cities (Norfolk, Virginia, and San Francisco, California). We constructed 2 city-specific factor models and used an algorithm to predict the expected mean improvement that a specified number of bicycle and pedestrian path miles contributes to the identified health outcomes.

Results

We show that given a factor model constructed from data from 2011 to 2015, the number of additional bicycle and pedestrian path miles in 2016, and a specific census tract, our models forecast health outcome improvements in 2020 more accurately than 2 alternative approaches for both Norfolk, Virginia, and San Francisco, California. Furthermore, for each city, we show that the additional accuracy is a statistically significant improvement (P<.001 in every case) when compared with the alternate approaches. For Norfolk, Virginia (n=31 census tracts), our approach estimated, on average, the percentage of individuals with high blood pressure in the census tract within 1.49% (SD 0.85%), the percentage of individuals with diabetes in the census tract within 1.63% (SD 0.59%), and the percentage of individuals who had >2 weeks of poor physical health days in the census tract within 1.83% (SD 0.57%). For San Francisco (n=49 census tracts), our approach estimates, on average, that the percentage of individuals who had a stroke in the census tract is within 1.81% (SD 0.52%), and the percentage of individuals with diabetes in the census tract is within 1.26% (SD 0.91%).

Conclusions

We propose and evaluate a methodology to enable decision makers to weigh the extent to which 2 bicycle and pedestrian paths of equal cost, which were proposed in different census tracts, improve residents’ health outcomes; identify areas where bicycle and pedestrian paths are unlikely to be effective interventions and other strategies should be used; and quantify the minimum amount of additional bicycle path miles needed to maximize health outcome improvements. Our methodology shows statistically significant improvements, compared with alternative approaches, in historical accuracy for 2 large cities (for 2016) within different geographic areas and with different demographics.

Active transportation and social capital: The association between walking or biking for transportation and community participation

Active transportation provides benefits to communities and individuals, yet little is known about its relationship with social capital. This study examined relationships between active transportation behavior and three indices of social capital (community participation, sense of community, and sociopolitical control). Linear regression was used to assess cross-sectional data (N = 1700) from the Survey of the Health of Wisconsin, a population-based representative sample collected in 2014, 2015, and 2016. Active transportation was associated with greater levels of community participation (p = 0.012). The association between active transportation and community participation was the third largest in terms of standardized coefficient (β = 0.07), following only age and college degree or greater educational attainment. Active transportation was not significantly associated with sense of community or sociopolitical control. All models controlled for confounding background characteristics. These findings are important for policy and planning work, as designing supportive environments and removing barriers to active transportation can foster social capital through bolstering community participation. The benefits of active transportation may be broader than previously understood and underscore the need to promote active transportation.

Barriers and Facilitators to Bikeshare Programs: A Qualitative Study in an Urban Environment

INTRODUCTION

Bikeshare programs have emerged across the US to promote bicycling as an active mode of transportation that could potentially improve health and quality of life. However, bikeshare usage is low in some settings. The purpose of this qualitative study is to explore barriers and facilitators of bikeshare use and to identify potential strategies to increase participation in urban environments.

METHODS

Focus groups were conducted with urban bikeshare users in Birmingham, Alabama. Thematic analysis was guided by the PRECEDE model, which identifies predisposing (intrapersonal), reinforcing (interpersonal), and enabling (structural) factors related to a health program.

RESULTS

In the four focus groups, the most prominent barriers to utilization identified were age, disability, stigma, and lack of awareness of programs (intrapersonal), having small children (interpersonal), lack of safety and bicycling infrastructure, bikeshare characteristics such as location, time constraints, cost, ease of use, and availability of bikes (structural). The most prominent facilitators included enjoyment (intrapersonal), peer support (interpersonal), and convenience, location, cost, and availability of electric bikes (structural). Recommendations to increase usage were primarily structural, such as infrastructure improvement, incentive programs, awareness and safety campaigns, expansion to neighborhoods and trails, increasing time users can ride before docking, and providing more electric bikes.

CONCLUSION

To increase bikeshare use in urban settings, use-restricting policies must be addressed.

Assessment of personal exposure to particulate air pollution in different microenvironments and traveling by several modes of transportation in Bogotá, Colombia: protocol for a mixed-methods study. (Preprint)

Background

Air pollution in most countries exceeds the levels recommended by the World Health Organization, causing up to one-third of deaths due to noncommunicable diseases. Fine particulate matter (PM_2.5) and black carbon (BC) from mobile sources are the main contaminants.

Objective

The aim of this study is to assess the relationship of exposure to air pollutants (PM_2.5 and BC) in microenvironments according to respiratory health and physical activity in users traveling by different types of transportation in Bogotá, Colombia.

Methods

A mixed methods study based on a convergent parallel design will be performed with workers and students. The sample will include 350 healthy transport users traveling by different urban transportation modes in three main routes in Bogotá. The study is broken down into two components: (1) a descriptive qualitative component focused on assessing the individual perception of air pollution using semistructured interviews; and (2) a cross-sectional study measuring the individual exposure to PM_2.5 and BC using portable instruments (DustTrak and microAeth, respectively), pulmonary function by spirometry, and physical activity with accelerometry. The analysis will include concurrent triangulation and logistic regression.

Results

The findings will be useful for the conception, design, and decision-making process in the sectors of health and mobility from public, academy, and private perspectives. This study includes personal measurements of PM_2.5 and BC during typical trips in the city to assess the exposure to these contaminants in the major roadways in real time. The study further compares the performance of two different lung tests to identify possible short-term respiratory effects. As a limitation, the protocol will include participants from different institutions in the city, which are not necessarily representative of all healthy populations in Bogotá. In this sense, it is not possible to draw causation conclusions. Moreover, a convergent parallel design could be especially problematic concerning integration because such a design often lacks a clear plan for making a connection between the two sets of results, which may not be well connected. Nevertheless, this study adopts a procedure for how to integrate qualitative and quantitative data in the interpretation of the results and a multilevel regression. The time that participants must live in the city will be considered; this will be controlled in the stratified analysis. Another limitation is the wide age range and working status of the participants. Regional pollution levels and episodes (PM_2.5) will be handled as confounding variables. The study is currently in the enrollment phase of the participants. Measurements have been made on 300 participants. Pandemic conditions affected the study schedule; however, the results are likely to be obtained by late 2022.

Conclusions

This study investigates the exposure to air pollutants in microenvironments in Bogotá, Colombia. To our knowledge, this is the first mixed methods study focusing on PM_2.5, BC, and respiratory health effects in a city over 2 meters above sea level. This study will provide an integration of air pollution exposure variables and respiratory health effects in different microenvironments.

International Registered Report Identifier (IRRID)

PRR1-10.2196/25690

Individual, social, and physical environmental factors related to changes in walking and cycling for transport among older adults: A longitudinal study

To date, no longitudinal studies examined the change in walking and cycling for transport as distinct outcomes over time and investigated the predictors of those changes. Therefore, this present study examined the change in odds of engagement in walking and cycling for transport as distinct outcomes among Belgian older adults over a three-year follow-up period, and examined factors (i.e. socio-demographics, psychosocial, perceived social and physical environmental characteristics) related to these changes in engaging in walking and cycling for transport. Against our expectations, we found significantly higher odds of engaging in cycling for transport among older adults at follow-up compared to baseline and no significant differences in the odds of engaging in walking for transport. Interventions should assist older adults to increase their self-efficacy towards PA, their perceived benefits of PA, and their perception of land use mix diversity in their neighborhood in order to increase the engagement in walking/cycling for transport over time, or help to decrease their perceived barriers towards PA or their perception to have a lot of physical barriers to walk/cycle in their neighborhood. Future longitudinal studies with larger samples are warranted investigating interaction effects between different predictors at various levels to find out which factors can be further integrated into active transport interventions in older adults.

Comparison of US metropolitan region pedestrian and bicyclist fatality rates

Annual US pedestrian and bicyclist fatalities involving motor vehicles have each increased by 30% in just six years, reaching their highest levels in two decades. To provide information to reverse this trend, we quantified pedestrian and bicyclist fatality rates in 46 of the largest US metropolitan statistical areas (MSAs) during two five-year time periods: 1999-2003 and 2007-2011. We divided the annual average number of pedestrian and bicyclist fatalities during 1999-2003 from the Fatality Analysis Reporting System by the annual estimates of pedestrian and bicycle trips, kilometers traveled, and minutes traveled from the 2001 National Household Travel Survey (NHTS) and the annual average number of fatalities from 2007 to 2011 by similar estimates from the 2009 NHTS. The five most dangerous regions for walking during 2007-2011 averaged 262 pedestrian fatalities per billion trips while the five safest averaged 49 pedestrian fatalities per billion trips. The five most dangerous regions for bicycling averaged 458 bicyclist fatalities per billion trips while the five safest averaged 75 bicyclist fatalities per billion trips. Random-effects meta-analysis identified eight metropolitan regions as outliers with low pedestrian fatality rates, six with high pedestrian fatality rates, one with a low bicyclist fatality rate, and five with high bicyclist fatality rates. MSAs with low pedestrian and bicycle fatality rates tended to have central cities recognized as Walk Friendly Communities and Bicycle Friendly Communities for investing in pedestrian and bicycle projects and programs. Random-effects meta-regression showed that certain socioeconomic characteristics and high pedestrian and bicyclist mode shares were associated with lower MSA fatality rates. Results suggest that pedestrian and bicycle infrastructure and safety programs should be complemented with strategies to increase walking and bicycling. In particular, safety initiatives should be honed to reduce pedestrian and bicyclist fatality risk in immigrant communities and to make pedestrian travel safer for the growing senior-age population.

Analysis of vehicle-bicycle interactions at unsignalized crossings: A probabilistic approach and application

In the last decades, bicycle usage has been increasing in many countries due to the potential environmental and health benefits. Therefore, there is a need to better understand cyclists' interactions with vehicles, and to build models and tools for evaluating multimodal transportation infrastructure with respect to cycling safety, accessibility, and other planning aspects. This paper presents a modeling framework to describe driver-cyclist interactions when they are approaching a conflicting zone. In particular, the car driver yielding behavior is modeled as a function of a number of explanatory variables. A two-level hierarchical, probabilistic framework (based on discrete choice theory) is proposed to capture the driver's yielding decision process when interacting with a cyclist. The first level models the probability of the car driver perceiving a situation with a bicycle as a potential conflict whereas the second models the probability of yielding given that a conflict has been perceived by the driver. The framework also incorporates the randomness of the location of the drivers' decision point. The methodology is applied in a case study using observations at a typical Swedish roundabout. The results show that the conflict probability is affected differently depending on the user (cyclist or driver) who arrives at the interaction zone first. The yielding probability depends on the speed of the vehicle and the proximity of the cyclist.

Health impact assessment of active transportation: A systematic review

OBJECTIVE

Walking and cycling for transportation (i.e. active transportation, AT), provide substantial health benefits from increased physical activity (PA). However, risks of injury from exposure to motorized traffic and their emissions (i.e. air pollution) exist. The objective was to systematically review studies conducting health impact assessment (HIA) of a mode shift to AT on grounds of associated health benefits and risks.

METHODS

Systematic database searches of MEDLINE, Web of Science and Transportation Research International Documentation were performed by two independent researchers, augmented by bibliographic review, internet searches and expert consultation to identify peer-reviewed studies from inception to December 2014.

RESULTS

Thirty studies were included, originating predominantly from Europe, but also the United States, Australia and New Zealand. They compromised of mostly HIA approaches of comparative risk assessment and cost-benefit analysis. Estimated health benefit-risk or benefit-cost ratios of a mode shift to AT ranged between -2 and 360 (median=9). Effects of increased PA contributed the most to estimated health benefits, which strongly outweighed detrimental effects of traffic incidents and air pollution exposure on health.

CONCLUSION

Despite different HIA methodologies being applied with distinctive assumptions on key parameters, AT can provide substantial net health benefits, irrespective of geographical context.