Supporting Local Public Health and Planning Professionals to Implement Built Environment Changes: A Technical Assistance Program to Promote Physical Activity in Texas.

Built environment approaches that improve active transportation infrastructure and environmental design can increase physical activity. Funded by the Centers for Disease Control and Prevention, the Texas Department of State Health Services rejuvenated the Texas Plan4Health program from 2018 to 2023 to expand such approaches in Texas by providing technical assistance to teams of local public health professionals and planners to identify and implement projects connecting people to everyday destinations via active transport in their communities. However, the COVID-19 pandemic prompted Texas Plan4Health to modify the delivery of technical assistance to accommodate restrictions on travel and in-person gatherings. We used qualitative methods to conduct a postintervention process evaluation to describe the modified technical assistance process, understand the experiences of the 4 participating communities, and identify short-term outcomes and lessons learned. Texas Plan4Health helped communities overcome common barriers to built environment change, facilitated collaboration across community public health and planning professionals, and educated professionals about active transportation infrastructure and the relationship between their disciplines, thereby increasing community capacity to implement built environment improvements. This outcome, however, was mediated by the pre-existing resources and previous experiences with active transportation planning among the participating communities. Public health practitioners seeking to improve active transportation infrastructure and environmental design for physical activity should consider community-engaged approaches that advance partnership-building and collaborative experiential education among public health, planning, and other local government representatives, directing particular attention and additional training toward communities with fewer resources.

Uncovering physical activity trade-offs in transportation policy: A spatial agent-based model of Bogotá, Colombia.

BACKGROUND: Transportation policies can impact health outcomes while simultaneously promoting social equity and environmental sustainability. We developed an agent-based model (ABM) to simulate the impacts of fare subsidies and congestion taxes on commuter decision-making and travel patterns. We report effects on mode share, travel time and transport-related physical activity (PA), including the variability of effects by socioeconomic strata (SES), and the trade-offs that may need to be considered in the implementation of these policies in a context with high levels of necessity-based physical activity. METHODS: The ABM design was informed by local stakeholder engagement. The demographic and spatial characteristics of the in-silico city, and its residents, were informed by local surveys and empirical studies. We used ridership and travel time data from the 2019 Bogotá Household Travel Survey to calibrate and validate the model by SES. We then explored the impacts of fare subsidy and congestion tax policy scenarios. RESULTS: Our model reproduced commuting patterns observed in Bogotá, including substantial necessity-based walking for transportation. At the city-level, congestion taxes fractionally reduced car use, including among mid-to-high SES groups but not among low SES commuters. Neither travel times nor physical activity levels were impacted at the city level or by SES. Comparatively, fare subsidies promoted city-level public transportation (PT) ridership, particularly under a 'free-fare' scenario, largely through reductions in walking trips. 'Free fare' policies also led to a large reduction in very long walking times and an overall reduction in the commuting-based attainment of physical activity guidelines. Differential effects were observed by SES, with free fares promoting PT ridership primarily among low-and-middle SES groups. These shifts to PT reduced median walking times among all SES groups, particularly low-SES groups. Moreover, the proportion of low-to-mid SES commuters meeting weekly physical activity recommendations decreased under the 'freefare' policy, with no change observed among high-SES groups. CONCLUSIONS: Transport policies can differentially impact SES-level disparities in necessity-based walking and travel times. Understanding these impacts is critical in shaping transportation policies that balance the dual aims of reducing SES-level disparities in travel time (and time poverty) and the promotion of choice-based physical activity.

Addressing transportation barriers in oncology: existing programs and new solutions.

Transportation is an underrecognized, but modifiable barrier to accessing cancer care, especially for clinical trials. Clinicians, insurers, and health systems can screen patients for transportation needs and link them to transportation. Direct transportation services (i.e., ride-sharing, insurance-provided transportation) have high rates of patient satisfaction and visit completion. Patient financial reimbursements provide necessary funds to counteract the effects of transportation barriers, which can lead to higher trial enrollment, especially for low socioeconomic status and racially and ethnically diverse patients. Expanding transportation interventions to more cancer patients, and addressing knowledge, service, and system gaps, can help more patients access needed cancer care.

Changes in active commuting and changes in health: Within- and between-individual analyses among 16 881 Finnish public sector employees.

BACKGROUND: Active commuting, such as walking or cycling to work, can be beneficial for health. However, because within-individual studies on the association between change in active commuting and change in health are scarce, the previous results may have been biased due to unmeasured confounding. Additionally, prior studies have often lacked information about commuting distance. METHODS: We used two waves (2020, T1 and 2022, T2) of self-report data from the Finnish Public Sector study (N = 16,881; 80% female) to examine the within- and between associations (in a hybrid model) between active commuting and health. Exposure was measured by actively commuted kilometers per week, that is, by multiplying the number of walking or cycling days per week with the daily commuting distance. The primary outcome, self-rated health, was measured at T1 and T2. The secondary outcomes, psychological distress, and sleep problems were measured only at T2 and were therefore analyzed only in a between-individual design. RESULTS: After adjustment for potential time-varying confounders such as socioeconomic factors, body mass index, and health behaviors, an increase equivalent to 10 additional active commuting kilometers per week was associated with a small improvement in self-rated health (within-individual unstandardized beta = 0.01, 95% CI 0.01-0.02; between-individual unstandardized beta = 0.03, 95% CI 0.02-0.04). No associations were observed between changes in active commuting and psychological distress or sleep problems. CONCLUSIONS: An increase in active commuting may promote self-rated health. However, increase of tens of additional kilometers in commuting every day may be required to produce even a small effect on health.

The finest diamond must be green: a closer look at the roles of institution in shipping firms' sustainable practices.

Shipping companies' implementation of sustainable shipping management is an important means of protecting major water bodies in the marine environment. This research establishes a theoretical model based on institutional theory and incorporates a micro-consciousness level to explore the factors influencing companies' implementation of sustainable shipping practices. After surveying the management of Chinese shipping companies, a total of 282 datasets were obtained for analysis. This study demonstrated that rules and regulations, societal norms, environmental awareness, and legal awareness can improve shipping companies' sustainable shipping practices. Meanwhile, these practices have a positive impact on the environmental, financial, and competitive performance of shipping companies. Moreover, these findings are highly significant for maritime environmental protection and sustainability.

Co-Benefit Assessment of Active Transportation in Delhi, Estimating the Willingness to Use Nonmotorized Mode and Near-Roadway-Avoided PM2.5 Exposure.

This study aims to estimate the avoided mortalities and morbidities and related economic impacts due to adopting the nonmotorized transportation (NMT) policy in Delhi, India. To this aim, an integrated quantitative assessment framework is developed to estimate the expected environmental, health, and economic co-benefits from replacing personal motorized transport with NMT in Delhi, taking into account the inhabitants' willingness to use NMT (walking and cycling) mode. The willingness to accept NMT is estimated by conducting a cross-sectional survey in Delhi, which is further used to estimate the expected health benefits from both increased physical activity and near-roadway-avoided PM2.5 exposure in selected traffic areas in 11 major districts in Delhi. The value of a statistical life (VSL) and cost of illness methods are used to calculate the economic benefits of the avoided mortalities and morbidities from NMT in Delhi. The willingness assessment indicates that the average per capita time spent walking and cycling in Delhi is 11.054 and 2.255 min, respectively. The results from the application of the NMT in Delhi show the annual reduction in CO2 and PM2.5 to be 121.5 kilotons and 138.9 tons, respectively. The model estimates the expected co-benefits from increased physical activities and reduced PM2.5 exposure at 17,529 avoided cases of mortality with an associated savings of about USD 4870 million in Delhi.

Impact of Emerging Transport Technologies on Freight Economic and Environmental Performance: A System Dynamics View.

Road freight transport promotes economic development while impeding the future of green development due to excessive fossil fuel use. Road freight enterprises need to adapt to stricter environmental regulations while maintaining a reasonable level of profit. However, this is not easy in a growing economy such as China's, whose domestic freight demand is increasing rapidly with economic growth. The development of emerging transport technologies (ETTs) creates great potential for reducing the negative environmental impact of road freight transport. This study considers five candidate ETTs: eco-driving, fleet platooning, vehicle utilization, optimized vehicle design, and renewable energy trucks. A system dynamics analytical framework is established to explore the long-term impact of ETTs on road profit and greenhouse gas (GHG) emissions under the uncertainty of macroeconomic development. Road freight enterprises affiliated with the Qingdao port in China are taken as a case study. The economic and environmental impact of their adoption of ETTs is projected from 2020 to 2035. The results show that the economic growth in the port hinterland leads to an increase in road freight volume and profit, but it also yields a greater amount of GHG emissions from road transport. All of the candidate ETTs exhibit a positive effect on reducing GHG emissions from road transport, but they also cause profit losses due to a high application cost, even though they reduce transport operating costs by fuel savings. The results of the Sobol sensitivity analysis show that GHG reductions are sensitive to the adoption of ETTs. Thus, a carbon-based compensation mechanism is introduced. With this mechanism, road freight enterprises should prioritize vehicle utilization, optimized vehicle design, and eco-driving in their adoption of ETTs for more sustainable development. The results provide systems-based insights into ETT deployment decisions for road freight companies.

The Impact of Rail Transit on Accessibility and Spatial Equity of Public Transit: A Case Study of Guangzhou, China.

The urban rail transit network provides the possibility for people to shift from car to public transit for travel. This paper clarified the relationships among public transit, accessibility, and equity and studied the impact of rail transit on public transit accessibility that incorporates the measure of travel time and transit fare and the impacts' spatial equity. The results show that rail transit contributes to the similar distribution between high rate of changes of time-based accessibility communities and fare-based accessibility communities, which are located nearby the rail transit lines. The degree of inequity in travel time is higher than the degree in transit fare in two scenarios. Due to the well-connected bus transit in the city center, absolute changes in travel time are slight, while relative changes are high. The rail transit has promoted the improvement of public transit equity in some areas. The difference between the time-based accessibility of Conghua District, northern and southern Baiyun District, Huadu District, Nansha District and southern Panyu District, and other communities is getting smaller, which is conducive to the improvement of spatial equity. The results provide theoretical support for the development of an integrated multimodal public transit system.

Comparison and Economic Envelope Structure Schemes for Deep Foundation Pit of Subway Stations Based on Fuzzy Logic.

Since the 1990s, with the continuous advancement of urbanization, the proportion of urban population has gradually increased. There is a serious shortage of land resources, and people's demand for underground space is increasing day by day. The construction of subway stations has developed into an inevitable trend in the future construction engineering industry, and it is also necessary to select the best solution from various solutions. The purpose of this paper is to study how to evaluate and analyze the economy of the deep foundation pit envelope structure of subway stations based on fuzzy logic, so as to choose the optimal and most economical plan. This paper proposes a fuzzy comprehensive evaluation method based on fuzzy logic, which is a reasonable method for the classic evaluation index. The experimental results of this paper show that in 2015 about 8% of people chose to travel by subway. By 2020, 54.5% of people chose to travel by subway, an increase of 46.5% during this period. It can be seen that more and more people are willing to take the subway, and subway transportation is a public transportation mode with large transportation volume. It has obvious public welfare, and it can relieve the urban traffic pressure very well, so the investment in subway construction in various cities is also increasing.

The TROLLEY Study: assessing travel, health, and equity impacts of a new light rail transit investment during the COVID-19 pandemic.

BACKGROUND: The COVID-19 pandemic disrupted life in extraordinary ways impacting health and daily mobility. Public transit provides a strategy to improve individual and population health through increased active travel and reduced vehicle dependency, while ensuring equitable access to jobs, healthcare, education, and mitigating climate change. However, health safety concerns during the COVID-19 pandemic eroded ridership, which could have longstanding negative consequences. Research is needed to understand how mobility and health change as the pandemic recedes and how transit investments impact health and equity outcomes. METHODS: The TROLLEY (TRansit Opportunities for HeaLth, Livability, Exercise and EquitY) study will prospectively investigate a diverse cohort of university employees after the opening of a new light rail transit (LRT) line and the easing of campus COVID-19 restrictions. Participants are current staff who live either < 1 mile, 1-2 miles, or > 2 miles from LRT, with equal distribution across economic and racial/ethnic strata. The primary aim is to assess change in physical activity, travel mode, and vehicle miles travelled using accelerometer and GPS devices. Equity outcomes include household transportation and health-related expenditures. Change in health outcomes, including depressive symptoms, stress, quality of life, body mass index and behavior change constructs related to transit use will be assessed via self-report. Pre-pandemic variables will be retrospectively collected. Participants will be measured at 3 times over 2 years of follow up. Longitudinal changes in outcomes will be assessed using multilevel mixed effects models. Analyses will evaluate whether proximity to LRT, sociodemographic, and environmental factors modify change in outcomes over time. DISCUSSION: The TROLLEY study will utilize rigorous methods to advance our understanding of health, well-being, and equity-oriented outcomes of new LRT infrastructure through the COVID-19 recovery period, in a sample of demographically diverse adult workers whose employment location is accessed by new transit. Results will inform land use, transportation and health investments, and workplace interventions. Findings have the potential to elevate LRT as a public health priority and provide insight on how to ensure public transit meets the needs of vulnerable users and is more resilient in the face of future health pandemics. TRIAL REGISTRATION: The TROLLEY study was registered at ClinicalTrials.gov ( NCT04940481 ) June 17, 2021, and OSF Registries ( https://doi.org/10.17605/OSF.IO/PGEHU ) June 24, 2021, prior to participant enrollment.

Impact Estimation of Unplanned Urban Rail Disruptions on Public Transport Passengers: A Multi-Agent Based Simulation Approach.

Once unplanned urban rail disruptions occur, it is essential to evaluate the impacts on public transport passengers since impact estimation results enable transit agencies to verify whether alternative transit services have adequate capacity to evacuate the affected rail passengers and to adopt effective emergency measures in response to the disruptions. This paper focuses on estimating the impacts of unplanned rail line segment disruptions on rail passengers as well as original bus passengers, as the latter are overlooked in existing studies. A method of identifying affected rail passengers based on passenger tap-in time is proposed, which is helpful for evaluating the scale and origin-destination distribution of the affected passengers. Passengers' response behaviors are analyzed and modeled in a multi-agent simulation system. The system realizes the simulation of the multimodal evacuation process, in which a rule-based logit model is employed to describe passengers' travel selection behavior and the Monte Carlo method is utilized to address the issue of uncertainty in passengers' travel selection. In particular, the original bus passengers are integrated into the simulation and interact with rail passengers. Finally, some indicators assessing the impacts on rail passengers and bus passengers are presented, and a case study based on the Ningbo urban rail transit network is conducted.

A Demand-Centric Repositioning Strategy for Bike-Sharing Systems.

Transport-sharing systems are eco-friendly and the most promising services in smart urban environments, where the booming Internet of things (IoT) technologies play an important role in the smart infrastructure. Due to the imbalanced bike distribution, bikes and stalls in the docking stations could be unavailable when needed, leading to bad customer experiences. We develop a dynamic repositioning strategy for the management of bikes in this paper, which supports dispatchers to keep stations in service. Two open datasets are examined, and the exploratory data analysis presents that there is a significant difference of travel patterns between working and non-working days, where the former has an excess demand at rush hours and the latter is usually at a low demand. To evaluate the effect when the demand outstrips a station's capacity, we propose a non-linear scaling technique to transform demand patterns and perform the clustering analysis for each of five categories obtained from the sophisticated analysis of the dataset. Our repositioning strategy is developed according to the transformed demands. Compared with the previous work, numerical simulations reveal that our strategy has a better performance for high-demand stations, and thus can substantially reduce the repositioning cost, which brings benefit to bike-sharing operators for managing the city bike system.

Assessment of Staling Aldehydes in Lager Beer under Maritime Transport and Storage Conditions.

Beer flavor stability is greatly influenced by external temperature, vibrations, and longer delivery times. The present study assessed the impact of transport and storage conditions on staling aldehyde evolution in lager beers across five sample groups (fresh, transport, and storage simulation, and their controls), which differed in their bottle opening system (either crown cap or ring pull cap). Maritime transport conditions (45 days of travel, vibrations of 1.7 Hz, and warm temperatures (21-30 °C)) were simulated, together with storage time in a distributor's warehouse (up to 75 days). The results revealed that the concentration of Strecker aldehydes increased more quickly after transport and storage simulation in beer bottles with the ring pull cap opening system, and the contents of 2-methylpropanal and 3-methylbutanal, in particular, were up to three times higher. Benzaldehyde content also increased significantly, by 33% on average, in these samples. Hexanal was only found in beers with a ring pull cap that underwent transport simulation. Further storage after transport simulation significantly reduced the content of 2-methylpropanal, 3-methylbutanal, and hexanal, by 73%, 57%, and 43%, respectively, suggesting the formation of a bound state. 5-hydroxymethylfurfural was continuously increased by 78.5% and 40.5% after the Transport and Transport & Storage simulations, respectively. Transport conditions lead to a slight increase, of 0.6 EBC units, in beer color.

Health Benefits of Strategies for Carbon Mitigation in US Transportation, 2017‒2050.

Objectives. To quantify health benefits and carbon emissions of 2 transportation scenarios that contrast optimum levels of physical activity from active travel and minimal air pollution from electric cars. Methods. We used data on burden of disease, travel, and vehicle emissions in the US population and a health impact model to assess health benefits and harms of physical activity from transportation-related walking and cycling, fine particulate pollution from car emissions, and road traffic injuries. We compared baseline travel with walking and cycling a median of 150 weekly minutes for physical activity, and with electric cars that minimized carbon pollution and fine particulates. Results. In 2050, the target year for carbon neutrality, the active travel scenario avoided 167 000 deaths and gained 2.5 million disability-adjusted life years, monetized at $1.6 trillion using the value of a statistical life. Carbon emissions were reduced by 24% from baseline. Electric cars avoided 1400 deaths and gained 16 400 disability-adjusted life years, monetized at $13 billion. Conclusions. To achieve carbon neutrality in transportation and maximize health benefits, active travel should have a prominent role along with electric vehicles in national blueprints. (Am J Public Health. 2022; 112(3):426-433. https://doi.org/10.2105/AJPH.2021.306600).

Travel time prediction of urban public transportation based on detection of single routes.

Improving travel time prediction for public transit effectively enhances service reliability, optimizes travel structure, and alleviates traffic problems. Its greater time-variance and uncertainty make predictions for short travel times (≤35min) more subject to be influenced by random factors. It requires higher precision and is more complicated than long-term predictions. Effectively extracting and mining real-time, accurate, reliable, and low-cost multi-source data such as GPS, AFC, and IC can provide data support for travel time prediction. Kalman filter model has high accuracy in one-step prediction and can be used to calculate a large amount of data. This paper adopts the Kalman filter as a travel time prediction model for a single bus based on single-line detection: including the travel time prediction model of route (RTM) and the stop dwell time prediction model (DTM); the evaluation criteria and indexes of the models are given. The error analysis of the prediction results is carried out based on AVL data by case study. Results show that under the precondition of multi-source data, the public transportation prediction model can meet the accuracy requirement for travel time prediction and the prediction effect of the whole route is superior to that of the route segment between stops.

Beyond the dichotomy: How ride-hailing competes with and complements public transport.

Since ride-hailing has become an important travel alternative in many cities worldwide, a fervent debate is underway on whether it competes with or complements public transport services. We use Uber trip data in six cities in the United States and Europe to identify the most attractive public transport alternative for each ride. We then address the following questions: (i) How does ride-hailing travel time and cost compare to the fastest public transport alternative? (ii) What proportion of ride-hailing trips do not have a viable public transport alternative? (iii) How does ride-hailing change overall service accessibility? (iv) What is the relation between demand share and relative competition between the two alternatives? Our findings suggest that the dichotomy-competing with or complementing-is false. Though the vast majority of ride-hailing trips have a viable public transport alternative, between 20% and 40% of them have no viable public transport alternative. The increased service accessibility attributed to the inclusion of ride-hailing is greater in our US cities than in their European counterparts. Demand split is directly related to the relative competitiveness of travel times i.e. when public transport travel times are competitive ride-hailing demand share is low and vice-versa.

When more is less: Urban disparities in access to surgical care by transportation means.

BACKGROUND: Structural factors limiting access to surgical care require elucidation. We hypothesize transportation time to hospitals with surgical capacity disproportionately burdens minority populations. METHODS: We identified hospitals with surgical capacity within a 20-mile radius of our city center. Using geocoding, we estimated travel times from each census tract to the nearest facility by car or public bus. RESULTS: For 143 tracts within the county, drive time was 13 ± 4 min and bus time was 33 ± 15 min. Only 41.2% of the population had a facility within 30 min by bus; access was further diminished for those with minority race/ethnicity and/or no insurance. Bus time was associated with percent minority population in a census tract: for each 10% increase in minority population there was a 4.3-min increase in bus time (p < 0.001) when controlling for socioeconomic status and other characteristics. CONCLUSIONS: Geographic information systems analysis has potential to identify communities with disproportionate burden to access surgical services.

What travel scenarios are the opportunities of car sharing?

In face of high-investment and low-revenue crisis, it is critical for new-born car-sharing companies to focus on niche market. Existing literatures have already discussed the niche market of car sharing based on people's irregular travel demands and scenarios; however, current research findings are still lack of adequate travel data support. Aiming to solve this problem, we develop a travel scenarios mining method that first define land usage types of travel Origin-Destination (OD) locations using spatial clustering analysis of city's Points of interests (POI) data, and then discover the most representative travel scenarios using association rules mining method with car-sharing records data. Applying this approach to the car-sharing service case in Beijing, China, we find that: day-time business trips and evening entertainment trips around the city centre, commuting trips in off-peak time, and short-distance city travel for tourism are three travel scenarios suitable for car sharing's niche in the initial stage of market entering. Furthermore, spatio-temporal consumption profiles and competitive advantages of car sharing in the three travel scenarios are analyzed. Finally, theoretical and managerial implications are discussed. In this study, we address the question of finding niche market and suggest that it is critical for car sharing industry treading through the crisis in the early stage of development.

Transport to School and Mental Well-Being of Schoolchildren in Ireland.

Objectives: We explored whether modes of transport (cycling, walking, public transport or private vehicle) between home and school are associated with mental well-being in children aged 10-17 years, participating in the Irish Health Behaviour in School-aged Children (HBSC) study. Methods: Scores on the World Health Organization Well-being Index and the Mental Health Inventory five-item versions, self-reported life satisfaction, happiness with self, body satisfaction, excellent self-rated health, and multiple health complaints of 9,077 schoolchildren (mean age: 13.99 ± 1.91 years, percentage girls: 52.2%) were compared across modes of transport, unadjusted and adjusted for gender, age, family affluence and area of residence. Results: Those who reported using public transport reported poorer mental well-being than those using other means of transport, but adjusting for sociodemographic variables obscured these differences. The only exception was excellent health, where children who cycled outperformed the other three groups, even after adjustment for sociodemographic variables. Conclusions: Cycling can improve well-being in children. However, in promotion of cycling, social and environmental determinants and inequalities which influence adolescents' and their parents' decisions on modes of transport, need to be considered.