Health effects of the London bicycle sharing system: health impact modelling study

Features that influence bike sharing demand

During the last few years, Bike Sharing Systems (BSS) have become a popular means of transportation in several cities across the world, owing to their low costs and associated advantages. Citizens have adopted these systems as they help improve their health and contribute to creating more sustainable cities. However, customer satisfaction and the willingness to use the systems are directly affected by the ease of access to the docking stations and finding available bikes or slots. Therefore, system operators and managers' major responsibilities focus on urban and transport planning by improving the rebalancing operations of their BSS. Many approaches can be considered to overcome the unbalanced station problem, but predicting the number of arrivals and departures at the docking stations has been proven to be one of the most efficient. In this paper, we study the features that influence the prediction of bikes' arrivals and departures in Barcelona BSS, using a Random Forest model and a one-year data period. We considered features related to the weather, the stations' characteristics, and the facilities available within a 200-meter diameter of each station, called spatial features. The results indicate that features related to specific months, as well as temperature, pressure, altitude, and holidays, have a strong influence on the model, while spatial features have a small impact on the prediction results.

Does bike-sharing reduce traffic congestion? Evidence from three mega-cities in China

This study employs a regression discontinuity design to systematically examine the governance effect of bike-sharing on urban traffic congestion, utilizing city-level data from Beijing, Shanghai, and Wuhan in China between 2016 and 2018. We discover that the introduction of bike-sharing services significantly mitigates traffic congestion in the short term. Our heterogeneity analysis reveals that the initial deployment of shared bicycles primarily alleviates urban congestion, while additional deployments have a limited impact. Further, mechanism test analysis demonstrates that bike-sharing leads to increased metro ridership in these cities, effectively explaining the reduction in road congestion. This study underscores the pivotal role of bike-sharing services in easing urban traffic congestion and provides vital policy insights for enhancing traffic management strategies in Chinese cities.

Impacts of active mobility on individual health mediated by physical activities

Active mobility, encompassing walking and cycling for transportation, is a potential solution to health issues arising from inadequate physical activity in modern society. However, the extent of active mobility's impact on individual physical activity levels, and its association with health as mediated by physical activities, is not fully quantified. This study aims to clarify the direct relationship between active mobility usage and individual health, as well as the indirect relationship mediated by physical activity, with a focus on varying levels of physical activity intensity. Utilizing data from the 2017 U.S. National Household Travel Survey (NHTS), we employed Poisson regression to predict active mobility usage based on socio-demographic and household socio-economic characteristics. A Structural Equation Model (SEM) was then used to investigate the direct and indirect effects of active mobility on individual health, mediated by physical activity. We further segmented individuals according to their intensity of physical activity to examine how such effect differs between different levels of physical activity. The study demonstrates that active mobility usage positively correlates with both the amount and intensity of physical activity. The effect of active mobility on individual health includes a direct positive effect (29% for intensity, 67.7% for amount) and an indirect effect mediated by physical activity (71% for intensity, 32.3% for amount). Notably, the mediation effect of active mobility on health is more substantial in the context of vigorous physical activities compared to light or moderate activities. Our findings reveal a significant positive influence of active mobility on individual health, encompassing both direct and indirect effects mediated by physical activities. These results quantitatively underscore the health benefits of active mobility and suggest the importance of promoting active mobility as a strategy to improve public health.

Scalability evaluation of forecasting methods applied to bicycle sharing systems

Public Bicycle Sharing Systems (BSS) have spread in many cities for the last decade. The need of analysis tools to predict the behavior or estimate balancing needs has fostered a wide set of approaches that consider many variables. Often, these approaches use a single scenario to evaluate their algorithms, and little is known about the applicability of such algorithms in BSS of different sizes. In this paper, we evaluate the performance of widely known prediction algorithms for three sized scenarios: a small system, with around 20 docking stations, a medium-sized one, with 400+ docking stations, and a large one, with more than 1500 stations. The results show that Prophet and Random Forest are the prediction algorithms with more consistent results, and that small systems often have not enough data for the algorithms to perform a solid work.

Equity impacts of cycling investment in England: A natural experimental study using longitudinally linked individual-level Census data

Background

Cycling is beneficial for health and the environment but the evidence on the overall and differential impacts of interventions to promote cycling is limited. Here we assess the equity impacts of funding awarded to support cycling in 18 urban areas between 2005 and 2011.

Methods

We used longitudinally linked 2001 and 2011 census data from 25,747 individuals in the Office for National Statistics Longitudinal Study of England and Wales. Logistic regression was used to assess the impacts of funding on commute mode as the interaction between time and area (intervention/comparison) in individual-level difference-in-difference analyses, adjusting for a range of potential confounding factors. Differential impacts were examined by age, gender, education and area-level deprivation, and uptake and maintenance of cycling were examined separately.

Results

Difference-in-difference analyses showed no intervention impact on cycle commuting prevalence in the whole sample (AOR = 1.08; 95% CI 0.92, 1.26) or among men (AOR = 0.91; 95% CI 0.76, 1.10) but found an intervention effect among women (AOR = 1.56; 95% CI 1.16, 2.10). The intervention promoted uptake of cycling commuting in women (AOR = 2.13; 95% CI 1.56, 2.91) but not men (AOR = 1.19; 95% CI 0.93, 1.51). Differences in intervention effects by age, education and area-level deprivation were less consistent and more modest in magnitude.

Conclusions

Living in an intervention area was associated with greater uptake of cycle commuting among women but not men. Potential gender differences in the determinants of transport mode choice should be considered in the design and evaluation of future interventions to promote cycling.

Model Choice for Quantitative Health Impact Assessment and Modelling: An Expert Consultation and Narrative Literature Review

BACKGROUND

Health impact assessment (HIA) is a widely used process that aims to identify the health impacts, positive or negative, of a policy or intervention that is not necessarily placed in the health sector. Most HIAs are done prospectively and aim to forecast expected health impacts under assumed policy implementation. HIAs may quantitatively and/ or qualitatively assess health impacts, with this study focusing on the former. A variety of quantitative modelling methods exist that are used for forecasting health impacts, however, they differ in application area, data requirements, assumptions, risk modelling, complexities, limitations, strengths, and comprehensibility. We reviewed relevant models, so as to provide public health researchers with considerations for HIA model choice.

METHODS

Based on an HIA expert consultation, combined with a narrative literature review, we identified the most relevant models that can be used for health impact forecasting. We narratively and comparatively reviewed the models, according to their fields of application, their configuration and purposes, counterfactual scenarios, underlying assumptions, health risk modelling, limitations and strengths.

RESULTS

Seven relevant models for health impacts forecasting were identified, consisting of (i) comparative risk assessment (CRA), (ii) time series analysis (TSA), (iii) compartmental models (CMs), (iv) structural models (SMs), (v) agent-based models (ABMs), (vi) microsimulations (MS), and (vii) artificial intelligence (AI)/machine learning (ML). These models represent a variety in approaches and vary in the fields of HIA application, complexity and comprehensibility. We provide a set of criteria for HIA model choice. Researchers must consider that model input assumptions match the available data and parameter structures, the available resources, and that model outputs match the research question, meet expectations and are comprehensible to end-users.

CONCLUSION

The reviewed models have specific characteristics, related to available data and parameter structures, computational implementation, interpretation and comprehensibility, which the researcher should critically consider before HIA model choice.

Bayesian multistate modelling of incomplete chronic disease burden data

A widely-used model for determining the long-term health impacts of public health interventions, often called a "multistate lifetable", requires estimates of incidence, case fatality, and sometimes also remission rates, for multiple diseases by age and gender. Generally, direct data on both incidence and case fatality are not available in every disease and setting. For example, we may know population mortality and prevalence rather than case fatality and incidence. This paper presents Bayesian continuous-time multistate models for estimating transition rates between disease states based on incomplete data. This builds on previous methods by using a formal statistical model with transparent data-generating assumptions, while providing accessible software as an R package. Rates for people of different ages and areas can be related flexibly through splines or hierarchical models. Previous methods are also extended to allow age-specific trends through calendar time. The model is used to estimate case fatality for multiple diseases in the city regions of England, based on incidence, prevalence and mortality data from the Global Burden of Disease study. The estimates can be used to inform health impact models relating to those diseases and areas. Different assumptions about rates are compared, and we check the influence of different data sources.

Development of a behavioural support intervention for e-bike use in Australia

BACKGROUND

Insufficient physical activity (PA) is a risk factor for the development of many non-communicable diseases. Electric bicycles (e-bikes) offer considerable potential to support people to be physically active, however, no previous e-bike intervention studies have supported e-bike use with behavioural support. The aim of this study was to co-develop theory-based intervention components which can be used to increase physical activity through e-cycling among people who are overweight or obese and physically inactive.

METHODS

We conducted a mixed-methods study using an online survey and virtual co-design workshops. We utilised the Behaviour Change Wheel (BCW) to inform the development of the behavioural support intervention to facilitate day-to-day e-cycling.

RESULTS

One hundred participants completed an online survey and seven participated in the online co-design workshops. The development of the intervention identified five intervention functions (enablement, training, environmental restructuring, education, and persuasion) and 16 behaviour change techniques (BCTs) from 11 BCT groups (goals and planning, feedback and monitoring, social support, shaping knowledge, natural consequences, comparison of behaviour, associations, repetition and substitution, comparison of outcomes, antecedents, and self-belief).

CONCLUSION

To our knowledge, this is the first study to combine co-design and the BCW to develop a comprehensive behavioural support intervention for e-bike use. Theory based intervention options should be considered when providing e-bikes to individuals to help them increase their habitual PA levels.

Development of a method for walking step observation based on large-scale GPS data

Background

Widespread use of smartphones has enabled the continuous monitoring of people’s movements and physical activity. Linking global positioning systems (GPS) data obtained via smartphone applications to physical activity data may allow for large-scale and retrospective evaluation of where and how much physical activity has increased or decreased due to environmental, social, or individual changes caused by policy interventions, disasters, and infectious disease outbreaks. However, little attention has been paid to the use of large-scale commercial GPS data for physical activity research due to limitations in data specifications, including limited personal attribute and physical activity information. Using GPS logs with step counts measured by a smartphone application, we developed a simple method for daily walking step estimation based on large-scale GPS data.

Methods

The samples of this study were users whose GPS logs were obtained in Sendai City, Miyagi Prefecture, Japan, during October 2019 (37,460 users, 36,059,000 logs), and some logs included information on daily step counts (731 users, 450,307 logs). The relationship between land use exposure and daily step counts in the activity space was modeled using the small-scale GPS logs with daily step counts. Furthermore, we visualized the geographic distribution of estimated step counts using a large set of GPS logs with no step count information.

Results

The estimated model showed positive relationships between visiting high-rise buildings, parks and public spaces, and railway areas and step counts, and negative relationships between low-rise buildings and factory areas and daily step counts. The estimated daily step counts tended to be higher in urban areas than in suburban areas. Decreased step counts were mitigated in areas close to train stations. In addition, a clear temporal drop in step counts was observed in the suburbs during heavy rainfall.

Conclusions

The relationship between land use exposure and step counts observed in this study was consistent with previous findings, suggesting that the assessment of walking steps based on large-scale GPS logs is feasible. The methodology of this study can contribute to future policy interventions and public health measures by enabling the retrospective and large-scale observation of physical activity by walking.

Is environment perception associated with change in leisure-time physical activity in Brazilian older adults? Results of EpiFloripa Idoso cohort study

This study aims to analyze the association between perceived characteristics of the neighborhood environment and changes in leisure-time physical activity in Brazilian older adults. Longitudinal analysis was performed considering a population-based study carried out in 2009/2010 with follow-up in 2013/2014. Changes in leisure-time physical activity, obtained with the International Physical Activity Questionnaire during both waves, were associated with data of environment perception with the Neighborhood Environment Walkability Scale - Abbreviated (baseline only) performing multinomial logistic regression. In total, 1,162 older adults (65.2% women, mean age = 73.7 years) participated. Older adults who perceived flat streets, bicycle paths, and high flow of vehicles in the neighborhood were more likely to remain active in leisure time walking. Those who noticed the presence of flat streets also had a greater chance of becoming active than those who did not notice it. Older adults who perceived bicycle paths and sports events were more likely to maintain moderate and vigorous physical activity during leisure time. Furthermore, older adults who noticed parks and squares close to their residence were 0.49 times less likely to become insufficiently active. Brazilian older adults are more active in neighborhoods with more favorable attributes regarding leisure-time physical activity.

Scenarios of demographic distributional aspects of health co-benefits from decarbonising urban transport

BACKGROUND

There is limited knowledge on the distribution of the health co-benefits of reduced air pollutants and carbon emissions in the transport sector across populations.

METHODS

This Article describes a health impact assessment used to estimate the health co-benefits of alternative land passenger transport scenarios for the city of Beijing, China, testing the effect of five transport-based scenarios from 2020 to 2050 on health outcomes. New potential scenarios range from implementing a green transport infrastructure, to scenarios primarily based on the electrification of vehicle fleets and a deep decarbonisation scenario with near zero carbon emissions by 2050. The health co-benefits are disaggregated by age and sex and estimated in monetary terms.

FINDINGS

The results show that all the alternative mitigation scenarios result in reduced PM_2·5 and CO₂ emissions compared to a business-as-usual scenario during 2020-50. The near zero scenario achieves the largest health co-benefits and economic benefits annually relative to the sole mitigation strategy, preventing 300 (95% CI 229-450) deaths, with health co-benefits and CO₂ cost-saving an equivalent of 0·01% (0·00-0·03%) of Beijing's Gross domestic product in 2015 by 2050. Given Beijing's ageing population and higher mortality rate, individuals aged 50 years and older experience the greatest benefit from the mitigation scenarios. Regarding sex, the greatest health benefits occur in men.

INTERPRETATION

This assessment provides estimates of the demographic distribution of benefits from the effects of combinations of green transport and decarbonising vehicles in transport futures. The results show that there are substantial positive health outcomes from decarbonising transport in Beijing. Policies aimed at encouraging active travel and use of public transport, increasing the safety of active travel, improving public transport infrastructure, and decarbonising vehicles lead to differential benefits. In addition, disaggregation by age and sex shows that the health impacts related to transport pollution disproportionately influence different age cohorts and genders.

FUNDING

National Natural Science Foundation of China and FRIEND Project (through the National Research Foundation of Korea, funded by the Ministry of Science and ICT).

The role of bike sharing during the coronavirus pandemic: An analysis of the mobility patterns and perceptions of Lisbon's GIRA users

COVID-19 has dramatically impacted urban mobility, of which public transport (PT) has been particularly affected. With PT ridership plummeting due to infection fears and many people returning to work, there is a danger of a steep rise in car use that would exacerbate environmental and health problems. Therefore, other modes such as bike sharing should be considered as potential alternatives during the coronavirus pandemic. This study focuses on assessing how coronavirus has impacted bike sharing by implementing a travel behaviour survey to the users of GIRA, the bike sharing system (BSS) of Lisbon. While the coronavirus has led some to decrease the frequency of use or quit the system, other users have increased the usage or joined GIRA during the pandemic. Furthermore, most users who have quit or decreased the usage of GIRA justify their decision not so much on avoiding the risk of infection (although for some it is an important reason) but on having stopped commuting due to COVID-19. The survey has also revealed substantial changes not only on the usage patterns of GIRA users but also on their relationship with other modes of transport. While before the pandemic, most respondents were shifting from PT to GIRA, that percentage has declined, with an increase on the share of users replacing walking, private car, and personal cycling. Moreover, the motivations for using bike sharing related with avoiding PT and maintaining a social distance during the trip have gained more relevance. Concurrently, the perceived safety of using PT has drastically declined, and while the perceived safety of using GIRA has also decreased it was in a much smaller scale. Policy insights can be derived from this research on how bike sharing can contribute to a more sustainable and resilient urban transport system. During infectious public health crises such as COVID-19, BSS can be a viable transport alternative, not only providing the population with an affordable mode of transport where social distancing can be maintained in most of the trip but also mitigating a modal shift from PT to the private car.

Prediction for Origin-Destination Distribution of Dockless Shared Bicycles: A Case Study in Nanjing City

Shared bicycles are currently widely welcomed by the public due to their flexibility and convenience; they also help reduce chemical emissions and improve public health by encouraging people to engage in physical activities. However, during their development process, the imbalance between the supply and demand of shared bicycles has restricted the public's willingness to use them. Thus, it is necessary to forecast the demand for shared bicycles in different urban regions. This article presents a prediction model called QPSO-LSTM for the origin and destination (OD) distribution of shared bicycles by combining long short-term memory (LSTM) and quantum particle swarm optimization (QPSO). LSTM is a special type of recurrent neural network (RNN) that solves the long-term dependence problem existing in the general RNN, and is suitable for processing and predicting important events with very long intervals and delays in time series. QPSO is an important swarm intelligence algorithm that solves the optimization problem by simulating the process of birds searching for food. In the QPSO-LSTM model, LSTM is applied to predict the OD numbers. QPSO is used to optimize the LSTM for a problem involving a large number of hyperparameters, and the optimal combination of hyperparameters is quickly determined. Taking Nanjing as an example, the prediction model is applied to two typical areas, and the number of bicycles needed per hour in a future day is predicted. QPSO-LSTM can effectively learn the cycle regularity of the change in bicycle OD quantity. Finally, the QPSO-LSTM model is compared with the autoregressive integrated moving average model (ARIMA), back propagation (BP), and recurrent neural networks (RNNs). This shows that the QPSO-LSTM prediction result is more accurate.

Bike-Sharing Adoption in Cross-National Contexts: An Empirical Research on the Factors Affecting Users’ Intentions

Due to the need to promote a larger scale of low-carbon commuting, it is important to identify the influencing factors of the users’ intentions in the adoption of sharing bikes. For studying bike-sharing adoption in cross-national contexts, this research establishes a new model. By conducting multi-group structural equation modeling (SEM), the influencing factors of the adoption in China and Estonia are identified, respectively. Meanwhile, the moderation effects of the national context on several influencing factors are confirmed, and this result indicates that the contexts for bike-sharing adoption are different in the two countries. Two factors have also been found, namely the availability of infrastructure and the beneficial cost, for which policy interventions could have a significant impact in China but not in Estonia. Thus, more active policy interventions might lead to a higher level of adoption intention for the Chinese. This finding provides the implication that implementing policy interventions could be critical for accelerating the adoption of bike sharing and promoting low-carbon commuting.

Cycling-Related Injuries During COVID-19 Lockdown: A North London Experience

Objectives

There has been a notable surge in cycling injuries during the COVID-19(SARS-CoV-2 virus) pandemic. Cycling in general increased during lockdown as a leisure & fitness activity along with reduction in the use of public transport for commuting. We investigated the bicycle-related maxillofacial injuries & associations presenting through our emergency department(ED) which covers more than 1.6 million of London population.

Study Design/Methods

A retrospective observational study was undertaken in the Barnet General Hospital ("hub") which receives all maxillofacial referrals from 6 "spoke" hospitals & other urgent primary/community care practices in North London area between 16 March 2020 & 16 July 2020. All data corresponding to cycling injuries during the lockdown period was analyzed with the aid of trauma database/trust-wide electronic patient records.

Results

Twenty-two patients (6.7%) with cycling-related injuries out of a total of 322 patients who attended during the 4 months study period with maxillofacial emergencies were identified. Average age of patient cohort was 35.4 years, mainly consisting of adult males (77%). Seven patients had minor head injury and 1 patient suffered traumatic brain injury. About 59% patients did not wear a protective helmet & 3 patients had heavy alcohol/recreational drug intoxication during the accidents. Four patients needed inpatient admission and treatment under general anesthesia.

Conclusions

Based on our humble study, we advocate the need for robust road & personal safety measures with mandatory government legislations, policing of drug intoxication & encouragement of physical & mental health improvement measures during these unprecedented times & beyond.

Study protocol of the European Urban Burden of Disease Project: a health impact assessment study

INTRODUCTION

Cities have long been known to be society's predominant engine of innovation and wealth creation, yet they are also hotspots of pollution and disease partly due to current urban and transport practices. The aim of the European Urban Burden of Disease project is to evaluate the health burden and its determinants related to current and future potential urban and transport planning practices and related exposures in European cities and make this evidence available for policy and decision making for healthy and sustainable futures.

METHODS AND ANALYSIS

Drawing on an established comparative risk assessment methodology (ie, Urban and Transport Planning Health Impact Assessment) tool), in nearly 1000 European cities we will (1) quantify the health impacts of current urban and transport planning related exposures (eg, air pollution, noise, excess heat, lack of green space) (2) and evaluate the relationship between current levels of exposure, health impacts and city characteristics (eg, size, density, design, mobility) (3) rank and compare the cities based on exposure levels and the health impacts, (4) in a number of selected cities assess in-depth the linkages between urban and transport planning, environment, physical activity and health, and model the health impacts of alternative and realistic urban and transport planning scenarios, and, finally, (5) construct a healthy city index and set up an effective knowledge translation hub to generate impact in society and policy.

ETHICS AND DISSEMINATION

All data to be used in the project are publicly available data and do not need ethics approval. We will request consent for personal data on opinions and views and create data agreements for those providing information on current and future urban and transport planning scenarios.For dissemination and to generate impact, we will create a knowledge translation hub with information tailored to various stakeholders.

Premature Mortality of 2050 High Bike Use Scenarios in 17 Countries

BACKGROUND

Biking plays a significant role in urban mobility and has been suggested as a tool to promote public health. A recent study has proposed 2050 global biking scenarios based on large shifts from motorized vehicles to bikes. No previous studies have estimated the health impacts of global cycling scenarios, either future car-bike shift substitutions.

OBJECTIVES

We aimed to quantify changes in premature mortality of 2050 global biking scenarios in urban populations from 17 countries.

METHODS

Through a quantitative Health Impact Assessment, the mortality risks and benefits of replacing car trips by bike (mechanica bike and electric bike) in urban populations from 17 countries were estimated. Multiple bike scenarios were created based on current transport trends or large shifts from car trips to bike trips. We quantified the estimated change in the number of premature deaths (reduced or increased) concerning road traffic fatalities, air pollution, and physical activity. This study focuses on urban populations between 20 and 64 y old.

RESULTS

We found that, among the urban populations (20-64 y old) of 17 countries, 205,424 annual premature deaths could be prevented if high bike-use scenarios are achieved by 2050 (assuming that 100% of bike trips replace car trips). If only 8% of bike trips replace car trips in a more conservative scenario, 18,589 annual premature deaths could be prevented by 2050 in the same population. In all the countries and scenarios, the mortality benefits related to bike use (rather than car use) outweighed the mortality risks.

DISCUSSION

We found that global biking policies may provide important mortality benefits in 2050. Current and future bike- vs. car-trip policies should be considered key public health interventions for a healthy urban design. https://doi.org/10.1289/EHP9073.

A guide to value of information methods for prioritising research in health impact modelling

Health impact simulation models are used to predict how a proposed policy or scenario will affect population health outcomes. These models represent the typically-complex systems that describe how the scenarios affect exposures to risk factors for disease or injury (e.g. air pollution or physical inactivity), and how these risk factors are related to measures of population health (e.g. expected survival). These models are informed by multiple sources of data, and are subject to multiple sources of uncertainty. We want to describe which sources of uncertainty contribute most to uncertainty about the estimate or decision arising from the model. Furthermore, we want to decide where further research should be focused to obtain further data to reduce this uncertainty, and what form that research might take. This article presents a tutorial in the use of Value of Information methods for uncertainty analysis and research prioritisation in health impact simulation models. These methods are based on Bayesian decision-theoretic principles, and quantify the expected benefits from further information of different kinds. The expected value of partial perfect information about a parameter measures sensitivity of a decision or estimate to uncertainty about that parameter. The expected value of sample information represents the expected benefit from a specific proposed study to get better information about the parameter. The methods are applicable both to situationswhere the model is used to make a decision between alternative policies, and situations where the model is simply used to estimate a quantity (such as expected gains in survival under a scenario). This paper explains how to calculate and interpret the expected value of information in the context of a simple model describing the health impacts of air pollution from motorised transport. We provide a general-purpose R package and full code to reproduce the example analyses.

Health impacts of bike-sharing systems in the U.S

BACKGROUND

Bike-sharing systems (BSS) are short-term bike rentals that can be borrowed from one location and retired to another at the conclusion of the trip. In 2019, 109,589 BSS trips were made each day in the U.S, and half of those in New York City (NYC).

AIM

This study aims to quantify the health risks and benefits of BSS in the U.S. and NYC.

METHODS

This study followed a quantitative health impact assessment approach to estimate the risks and benefits of BSS. Specifically, we quantified the health impacts of physical activity, air pollution, and traffic incidents. We analyzed all the trips made by BSS in the U.S. and NYC. Input data on transport, traffic safety, air quality, and physical activity were collated from public records and scientific publications. We modeled the health impacts on adult users related to mortality, disease incidence, disability-adjusted life years (DALYs), and health economic impacts (related to morbidity and mortality).

RESULTS

We estimated that in the U.S. BSS trips resulted in an annual reduction of 4.7 premature deaths, 737 DALYs, and 36 million $USD in health economic impacts, mainly derived from the increment in physical activity. In NYC, we estimated an annual reduction of 2 premature deaths, 355 DALYs, and 15 million $USD in health economic impacts.

CONCLUSION

BSS in the U.S. and NYC provide a health benefit for bicyclists. Improvements in air quality and traffic safety across U.S. cities will maximize the health benefits of BSS.

Health impacts of changes in travel patterns in Greater Accra Metropolitan Area, Ghana

BACKGROUND

Health impact assessments of alternative travel patterns are urgently needed to inform transport and urban planning in African cities, but none exists so far.

OBJECTIVE

To quantify the health impacts of changes in travel patterns in the Greater Accra Metropolitan Area, Ghana.

METHODS

We estimated changes to population exposures to physical activity, air pollution, and road traffic fatality risk and consequent health burden (deaths and years of life lost prematurely - YLL) in response to changes in transportation patterns. Five scenarios were defined in collaboration with international and local partners and stakeholders to reflect potential local policy actions.

RESULTS

Swapping bus and walking trips for car trips can lead to more than 400 extra deaths and 20,500 YLL per year than travel patterns observed in 2009. If part of the rise in motorisation is from motorcycles, we estimated an additional nearly 370 deaths and over 18,500 YLL per year. Mitigating the rise in motorisation by swapping long trips by car or taxi to bus trips is the most beneficial for health, averting more than 600 premature deaths and over 31,500 YLL per year. Without significant improvements in road safety, reduction of short motorised trips in favour of cycling and walking had no significant net health benefits as non-communicable diseases deaths and YLL benefits were offset by increases in road traffic deaths. In all scenarios, road traffic fatalities were the largest contributor to changes in deaths and YLL.

CONCLUSIONS

Rising motorisation, particularly from motorcycles, can cause significant increase in health burden in the Greater Accra Metropolitan Area. Mitigating rising motorisation by improving public transport would benefit population health. Tackling road injury risk to ensure safe walking and cycling is a top priority. In the short term, this will save lives from injury. Longer term it will help halt the likely fall in physical activity.

HIA and EIA Are Different, but Maybe Not in the Way We Thought They Were: A Bibliometric Analysis

Background: The fields of Health Impact Assessment (HIA) and Environmental Impact Assessment (EIA) have grown with increasing numbers of disciplines and sectors contributing to their advancements, but with it, perceived conflict over methodological and disciplinary approaches to integrate health in impact assessments. This study maps the current field of HIA and health in EIA to examine the scientific landscape of the field. Methods: We carried out a bibliometric analysis of HIA papers and EIA papers that included a health focus in peer-reviewed journals in the Web of Science Core Collection (n = 229). We carried out co-authorship and co-citation network analyses of authors and documents in VOSviewer. Results: We identified two main co-authorship and co-citation groupings. Our document co-citation analysis also identified four clusters with two major groups, the Defining HIA cluster and the Describing the fields cluster versus the Active transport quantitative HIA cluster, and the Quantitative modelling tools cluster. Conclusion: Our findings strongly suggest that there exist two groups of thought in the scholarly fields of HIA and health in EIA. Barriers to developing more methodologically integrated approaches to considering health within EIA are related more to disciplinary differences than field (HIA versus EIA)-based differences and we advocate for the development of transdisciplinary approaches to both HIA and EIA.

Socioeconomic inequalities in physical activity in Brazil: a pooled cross-sectional analysis from 2013 to 2019

BACKGROUND

Information on socioeconomic inequalities in physical activity over time is sparse in low- to middle-income countries. In this study, we examined trends in physical activity educational inequalities in adults from Brazil between 2013 and 2019.

METHODS

We analyzed data from seven cross-sectional studies including 359,038 adults (≥ 18 years) from the VIGITEL study conducted annually from 2013 to 2019. Participants responded to a questionnaire about physical activity (total, leisure, and commuting). Educational inequalities by sex and skin color were assessed through absolute (slope index of inequality - SII) and relative measures of inequality (concentration index - CIX).

RESULTS

We found large absolute and relative inequalities for leisure-time physical activity, favoring those with higher educational attainment (SII₂₀₁₉ = 35.4; CIX₂₀₁₉ = 11.82). Active commuting was more prevalent in intermediate education groups, with a slight inequality toward the less educated group (SII₂₀₁₉ = -2.8; CIX₂₀₁₉ = -0.4). From 2013 to 2019, the absolute educational inequality in physical activity (total, leisure, and commuting) remained unchanged; however, the relative inequality gap narrowed for total physical activity (CIX: 8.4 in 2013 to 5.5 in 2019) and leisure-time physical activity (CIX: 18.3 in 2013 to 11.8 in 2019). Educational inequality increased in leisure-time physical activity among women and non-white individuals, while it reduced among men and white individuals; for active commuting, inequality decreased among women, and increased among men and white individuals.

CONCLUSIONS

Inequality in total physical activity and leisure-time physical activity favors the most educated groups in Brazil. Over time, relative educational inequality decreased for total and leisure-time physical activity, while no progress was found for absolute inequality.

A Novel Acceleration Signal Processing Procedure for Cycling Safety Assessment

With the growing rate of urban population and transport congestion, it is important for a city to have bike riding as an attractive travel choice but one of its biggest barriers for people is the perceived lack of safety. To improve the safety of urban cycling, identification of high-risk location and routes are major obstacles for safety countermeasures. Risk assessment is performed by crash data analysis, but the lack of data makes that approach less effective when applied to cyclist safety. Furthermore, the availability of data collected with the modern technologies opens the way to different approaches. This research aim is to analyse data needs and capability to identify critical cycling safety events for urban context where bicyclist behaviour can be recorded with different equipment and bicycle used as a probe vehicle to collect data. More specifically, three different sampling frequencies have been investigated to define the minimum one able to detect and recognize hard breaking. In details, a novel signal processing procedure has been proposed to correctly deal with speed and acceleration signals. Besides common signal filtering approaches, wavelet transformation and Dynamic Time Warping (DTW) techniques have been applied to remove more efficiently the instrument noise and align the signals with respect to the reference. The Euclidean distance of the DTW has been introduced as index to get the best filter parameters configuration. Obtained results, both during the calibration and the investigated real scenario, confirm that at least a GPS signal with a sampling frequency of 1Hz is needed to track the rider’s behaviour to detect events. In conclusion, with a very cheap hardware setup is possible to monitor riders’ speed and acceleration.

Overall health impacts of a potential increase in cycle commuting in Stockholm, Sweden

AIMS

To estimate the overall health impact of transferring commuting trips from car to bicycle.

METHODS

In this study registry information on the location of home and work for residents in Stockholm County was used to obtain the shortest travel route on a network of bicycle paths and roads. Current modes of travel to work were based on travel survey data. The relation between duration of cycling and distance cycled was established as a basis for selecting the number of individuals that normally would drive a car to work, but have a distance to work that they could bicycle within 30 minutes. The change in traffic flows was estimated by a transport model (LuTrans) and effects on road traffic injuries and fatalities were estimated by using national hospital injury data. Effects on air pollution concentrations were modelled using dispersion models.

RESULTS

Within the scenario, 111,000 commuters would shift from car to bicycle. On average the increased physical activity reduced the one-year mortality risk by 12% among the additional bicyclists. Including the number of years lost due to morbidity, the total number of disability adjusted life-years gained was 696. The amount of disability adjusted life-years gained in the general population due to reduced air pollution exposure was 471. The number of disability adjusted life-years lost by traffic injuries was 176. Also including air pollution effects among bicyclists, the net benefit was 939 disability adjusted life-years per year.

CONCLUSIONS

Large health benefits were estimated by transferring commuting by car to bicycle.

Cycling in one of the most polluted cities in the world: Exposure to noise and air pollution and potential adverse health impacts in Delhi

Background

In India, many cities struggle with extreme levels of air pollution and noise. Delhi, in particular, has the notorious reputation of being one of the most polluted cities in the world. Cyclists constitute a particularly exposed population, since they cycle among motor vehicles without any protection. This paper modeled the cyclists’ exposure to nitrogen dioxide (NO₂) and noise in Delhi, India.

Methods

Using primary data collected on 1,229 kms of roads in Delhi, Generalized Additive Mixed Models with Auto-Regressive terms (GAMMAR) are constructed for noise exposure, NO₂ exposure and NO₂ inhalation doses.

Results

Results show that cyclists are exposed to 47 µg/m³ of NO₂ and 3.3 dB(A) more when cycling on a primary road than on a residential street. Using WHO guideline values for noise and air pollution, we assessed how many minutes of inhaling doses and noise doses become potentially harmful to cyclists’ health in Delhi. Such thresholds are quickly exceeded: after cycling one hour in an area with moderate predicted values of noise and air pollution, the noise dose and inhaled dose of NO₂ will reach 212% and 403 µg on residential streets, and 459% and 482 µg on primary roads, respectively.

Conclusion

Policy makers should take these results into account to minimize cyclists’ exposure, especially for the most deprived people.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12942-021-00272-2.

Impacts of the Sharing Economy on Urban Sustainability: The Perceptions of Municipal Governments and Sharing Organisations

By changing the institutionalised practices associated with resource distribution, the sharing economy could support sustainable urban transformations. However, its impacts on urban sustainability are unknown and contested, and key actors hold different perceptions about them. Understanding how they frame these impacts could help solve conflicts and outline what can be done to influence the development of the sharing economy in a way that fosters urban sustainability. This study explores the diversity of these frames across actors (sharing economy organisations and municipalities), segments (accommodation, bicycle, and car sharing), and cities (Amsterdam and Toronto). A framework of the impacts on urban sustainability was developed following a systematic literature review. This then guided the analysis of secondary data and 51 interviews with key actors. Results show that accommodation sharing is framed most negatively due to its impact on urban liveability. Bicycle sharing is surrounded by less conflict. Still, in Amsterdam, which has a well-functioning bicycle infrastructure, it is viewed less positively than in Toronto. Car sharing is the most positively framed segment in Amsterdam as its potentials to lower emissions align with municipal sustainability agendas. Practical insights for negotiations between sharing economy organisations and municipalities to advance urban sustainability are proposed.

Smart-Mobility Services for Climate Mitigation in Urban Areas: Case Studies of Baltic Countries and Germany

The transport sector is one of the largest contributors of CO2 emissions and other greenhouse gases. In order to achieve the Paris goal of decreasing the global average temperature by 2 °C, urgent and transformative actions in urban mobility are required. As a sub-domain of the smart-city concept, smart-mobility-solutions integration at the municipal level is thought to have environmental, economic and social benefits, e.g., reducing air pollution in cities, providing new markets for alternative mobility and ensuring universal access to public transportation. Therefore, this article aims to analyze the relevance of smart mobility in creating a cleaner environment and provide strategic and practical examples of smart-mobility services in four European cities: Berlin (Germany), Kaunas (Lithuania), Riga (Latvia) and Tartu (Estonia). The paper presents a systematized literature review about the potential of smart-mobility services in reducing the negative environmental impact to urban environments in various cities. The authors highlight broad opportunities from the European Union and municipal documents for smart-mobility initiatives. The theoretical part is supplemented by socioeconomic and environmental descriptions, as well as experience, related to smart-mobility services in the four cities selected.

The Health Cost of Transport in Cities

Purpose of Review

The study aims to provide an understanding of health cost assessments of different transport modes in urban contexts, and their relevance for transport planning and political decision-making.

Recent Findings

There is strong evidence that motorized transportation imposes a high health cost on society, and specifically children. In contrast, active transport is a very significant health benefit.

Summary

Economic analyses support urban change in favor of compact neighborhoods and public transit, as well as infrastructure exclusively devoted to active transport. Private cars need to be restricted because of the high cost they impose on society.

Bikeability and Emerging Phenomena in Cycling: Exploratory Analysis and Review

Recent strategies to improve the performance of the cycling mode of transport are based on infrastructural, behavioral, and multimodal measures, which are related to the concept of bikeability. A literature review on “bikeability indexes” was conducted focusing on indicators, using a four-step systematic process. Fourteen studies were included for the final analysis and provided 138 indicators, 17 criteria, and four domains. The exploratory analysis evidenced limited application of indicators related to pollution, scarce use of indicators related to bicycle sharing systems (BSS), absence of indicators related to electric bicycles, lack of indicators related to digital solutions, and the need of a calibration and validation process for bikeability indexes. Considering the changes and opportunities created by emerging innovations (namely BSS and electric bicycles) and the health trade-off related to pollution reduction, this research reveals that the current bikeability indexes do not fully address the real potential of a cycle network, limiting its use as a comprehensive tool for the promotion of sustainable mobility.

Potential for reduced premature mortality by current and increased bicycle commuting: a health impact assessment using registry data on home and work addresses in Stockholm, Sweden

Objectives

The study aims to make use of individual data to estimate the impact on premature mortality due to both existing commuter bicycling and the potential impact due to increased physical activity through shifting transport mode from car commuting to bicycling.

Methods

Using registry data on home and work addresses for the population of Stockholm County the shortest bicycling route on a network of bicycle paths and roads was retrieved. Travel survey data were used to establish current modes of commuting. The relation between duration of bicycling and distance bicycled within the general population in 2015 was established as a basis for identifying individuals that currently drive a car to work but were estimated to have the physical capacity to bicycle to work within 30 min. Within this mode-shift scenario from car-to-bike the duration of bicycling per week was estimated, both among current and potential bicycle commuters. The health impact assessment (HIA) on mortality due to bicycle commuting physical activity was estimated using the same relative risk as within the WHO Health Economic Assessment Tool.

Results

The current number of bicycle commuters were 53 000, and the scenario estimated an additional 111 000. Their mean bicycle distances were 4.5 and 3.4 km, respectively. On average these respective amounts of physical activity reduced the yearly mortality by 16% and 12%, resulting in 11.3 and 16.2 fewer preterm deaths per year.

Conclusion

The HIA of transferring commuting by car to bicycle estimated large health benefits due to increased physical activity.

Personal-Level Protective Actions Against Particulate Matter Air Pollution Exposure: A Scientific Statement From the American Heart Association

Since the publication of the last American Heart Association scientific statement on air pollution and cardiovascular disease in 2010, unequivocal evidence of the causal role of fine particulate matter air pollution (PM2.5, or particulate matter ≤2.5 μm in diameter) in cardiovascular disease has emerged. There is a compelling case to provide the public with practical personalized approaches to reduce the health effects of PM2.5. Such interventions would be applicable not only to individuals in heavily polluted countries, high-risk or susceptible individuals living in cleaner environments, and microenvironments with higher pollution exposures, but also to those traveling to locations with high levels of PM2.5. The overarching motivation for this document is to summarize the current evidence supporting personal-level strategies to prevent the adverse cardiovascular effects of PM2.5, guide the use of the most proven/viable approaches, obviate the use of ineffective measures, and avoid unwarranted interventions. The significance of this statement relates not only to the global importance of PM2.5, but also to its focus on the most tested interventions and viable approaches directed at particulate matter air pollution. The writing group sought to provide expert consensus opinions on personal-level measures recognizing the current uncertainty and limited evidence base for many interventions. In doing so, the writing group acknowledges that its intent is to assist other agencies charged with protecting public health, without minimizing the personal choice considerations of an individual who may decide to use these interventions in the face of ongoing air pollution exposure.

Could smart research ensure healthy people in disrupted cities?

BACKGROUND

Since the late 19th century, city planners have struggled to cope with new types of urban transport and mobility that threatened the existing system, or even rendered it obsolete.

PURPOSE

As city planners confront the range of disruptive urban mobilities currently on the horizon, this paper explores how we can draw on a vast body of evidence to anticipate and avoid unintended consequences to people's health and wellbeing.

METHODS

This commentary involved a rapid review of the literature on transport disruption.

RESULTS

We found that to avoid the unintended consequences of disruption, research, policy and practice must think beyond single issues (such as the risk of chronic disease, injury, or traffic management) and consider the broader consequences of interventions. For example, although autonomous vehicles will probably reduce road trauma, what will be the negative consequences for physical inactivity, sedentary behavior, chronic disease, land use, traffic congestion and commuting patterns? Research is needed that considers and informs how to mitigate the range of potential harms caused by disruptive mobilities.

CONCLUSION

In the face of new disruptive mobilities, we must: (a) draw on existing evidence to shape new regulations that address the 'who, when and where' rules of introducing new mobilities (such as electric assisted bicycles (e-bikes) and scooters (e-scooters)) of which the health repercussions can be easily anticipated; (b) monitor and evaluate the implementation of any interventions through natural experiment studies; and (c) use innovative research methods (such as agent-based simulation and health-impact-assessment modelling) to assess the likely effects of emerging disruptive mobilities (e.g., autonomous vehicles) on health and wellbeing and on the environment.

The Association between the Regular Use of ICT Based Mobility Services and the Bicycle Mode Choice in Tehran and Cairo

Regarding the sharp growth rate of ICT (information and communication technology)—based mobility services like ridesourcing, it is essential to investigate the impact of these new mobility services on the transport mode choices, particularly on active mobility modes like cycling. This impact is more important in the MENA context (the Middle East and North Africa), where cycling does not constitute the main mobility mode in the modal split of most MENA cities. This paper studies the relationship between the regular use of ICT-based mobility services like ridesourcing and the tendency to cycle to near destinations. This paper contains the analysis of 4431 interviews in two large cities of the MENA region (Cairo and Tehran). This research uses logistic regression to analyze and compare the odds of cycling among regular and non-regular users of ridesourcing by considering the socio-economic, land use, and perception variables. The findings indicate that the odds of cycling among the regular users of ridesourcing are 2.30 and 1.94 times greater than these odds among non-regular ridesourcing users in Tehran and Cairo, respectively. Therefore, the regular users of ridesourcing are more likely to cycle to their near destinations than non-regular ridesourcing users in these cities.

Sports & exercise related traumatic brain injury in the Republic of Ireland - The neurosurgical perspective

BACKGROUND

While the concerns regarding the long-term cognitive effects of repeated sports related head injury have become a major source of debate, it is not uncommon for these patients to require neurosurgical interventions in the acute setting. The aim of this study was to provide a unique insight into the acute nature and neurosurgical management of sports and exercise related traumatic brain injury.

METHODS

We retrospectively analysed electronic records of all referrals made between July 2016 and December 2018 to the National Neurosurgical Centre at Beaumont Hospital to identify instances of sport and exercise related traumatic brain injuries (TBI). A sub-group analysis was carried out on patients transferred to the tertiary centre requiring neurosurgical/neuro-critical care.

RESULTS

Over the 30-month period, 194 patients (mean age: 36) were referred withsports and exercise related TBI, of which 56 were transferred to our unit (26 adults, 30 paediatrics). The most frequently encountered sporting activities were cycling, gaelic football, horse riding and rugby. Injuries included cerebral contusions, subdural haematomas, extradural haematomas and skull fractures. Neurosurgical intervention via intracranial pressure monitoring (ICP), decompressive craniectomy and elevation of depressed skull fracture was required in 28 out of 194 patients (14.4%). 85.7% (n = 48) of patients had a discharge Glasgow Coma Scale (GCS) of 15. 4 patients had a tracheostomy in place at discharge and there were 4 mortalities.

CONCLUSIONS

Sports and exercise activities, ranging from contact team sports to individual activities, are a common cause of traumatic brain injury and maybe associated with a significant morbidity and mortality.

Socio-Ecological Predictors of Frequent Bike Share Trips: Do Purposes Matter?

Using bike share could increase physical activity and improve health. This study used the social-ecological model to identify predictors of frequent bike share trips for different purposes. Participants residing in the U.S. were recruited via Amazon Mechanical Turk (MTurk). Self-report trip purposes were used to group participants into using bike share for commuting only (n = 260), social/entertainment only (n = 313), exercise only (n = 358), dual or triple-purpose (n = 501), and purposes other than commuting, social/entertainment, and exercise (n = 279). Results showed that at the intrapersonal level, perceived use of bike share to be helpful for increasing physical activity was a significant predictor for all groups, except for the other purpose group. Adjusting outdoor activity based on air quality was a significant predictor for the dual or triple-purpose group. At the interpersonal level, having four or more friends/family using bike share was a significant predictor for the other purpose group. At the community level, distance to the nearest bike share within acceptable range was a significant predictor for social/entertainment and dual or triple-purpose groups. The findings suggest that it is important to consider factors at multiple levels for predicting bike share usage. Moreover, health educators and policy makers should adopt different strategies for promoting bike share usage based on trip purposes.

Potential Effects on Travelers' Air Pollution Exposure and Associated Mortality Estimated for a Mode Shift from Car to Bicycle Commuting

This study aims to use dispersion-modeled concentrations of nitrogen oxides (NOx) and black carbon (BC) to estimate bicyclist exposures along a network of roads and bicycle paths. Such modeling was also performed in a scenario with increased bicycling. Accumulated concentrations between home and work were thereafter calculated for both bicyclists and drivers of cars. A transport model was used to estimate traffic volumes and current commuting preferences in Stockholm County. The study used individuals’ home and work addresses, their age, sex, and an empirical model estimate of their expected physical capacity in order to establish realistic bicycle travel distances. If car commuters with estimated physical capacity to bicycle to their workplace within 30 min changed their mode of transport to bicycle, >110,000 additional bicyclists would be achieved. Time-weighted mean concentrations along paths were, among current bicyclists, reduced from 25.8 to 24.2 μg/m³ for NOx and 1.14 to 1.08 μg/m³ for BC. Among the additional bicyclists, the yearly mean NOx dose from commuting increased from 0.08 to 1.03 μg/m³. This would be expected to yearly cause 0.10 fewer deaths for current bicycling levels and 1.7 more deaths for additional bicycling. This increased air pollution impact is much smaller than the decrease in the total population.

Integrated Impact Assessment of Active Travel: Expanding the Scope of the Health Economic Assessment Tool (HEAT) for Walking and Cycling

The World Health Organization’s Health Economic Assessment Tool (HEAT) for walking and cycling is a user-friendly web-based tool to assess the health impacts of active travel. HEAT, developed over 10 years ago, has been used by researchers, planners and policymakers alike in appraisals of walking and cycling policies at both national and more local scales. HEAT has undergone regular upgrades adopting the latest scientific evidence. This article presents the most recent upgrades of the tool. The health impacts of walking and/or cycling in a specified population are quantified in terms of premature deaths avoided (or caused). In addition to the calculation of benefits derived from physical activity, HEAT was recently expanded to include assessments of the burden associated with air pollution exposure and crash risks while walking or cycling. Further, the impacts on carbon emissions from mode shifts to active travel modes can now be assessed. The monetization of impacts using Value of Statistical Life and Social Costs of Carbon now uses country-specific values. As active travel inherently results in often substantial health benefits as well as not always negligible risks, assessments of active travel behavior or policies are incomplete without considering health implications. The recent developments of HEAT make it easier than ever to obtain ballpark estimates of health impacts and carbon emissions related to walking and cycling.

Public Bike Sharing Programs Under the Prism of Urban Planning Officials: The Case of Santiago de Chile

Background: Public bike-sharing schemes have gained enormous popularity worldwide. However, so far most of the research has focused on issues regarding the functioning of these schemes in cities, with little attention on how these systems are perceived and managed by urban planning authorities, which is the aim of this paper. Methods: The analysis is set in Santiago, a highly segregated city composed of 37 independent districts. Two focus groups with urban planning authorities belonging to districts with and without functioning bike-sharing schemes were conducted. Information was processed using a thematic analysis framework, which permitted to reduce, reorganize, and analyze these testimonial data. Results: The main results show that bike-sharing schemes are perceived as being part of a larger phenomenon related to the city’s socio-economic differences. A series of issues emerged that are related to urban planning authorities limitations in terms of governance and availability of planning instruments and strategies to cope with contrasting realities of the city. It was noted that bike-sharing schemes are helping to improve a neighborhood image, while, at the same time, promoting contemporary and cosmopolitan lifestyles. However, the functioning of bike-sharing schemes also is a reminder of the fragmented and dysfunctional governance of Santiago.

Seasonal Impacts of Particulate Matter Levels on Bike Sharing in Seoul, South Korea

Bike sharing is increasingly attracting more riders in cities around the world for its benefits regarding the urban environment and public health. The public bike sharing program of Seoul, South Korea, first launched in October 2015, is now widely spread around the city and serves more than 27,000 riders daily. However, concerns are being raised as rising air pollution levels in Seoul, represented by particulate matter (PM) levels, in recent years may negatively discourage citizens from using bike sharing. This study investigates the impact of PM10 and PM2.5 levels on bike sharing use in Seoul and seeks to identify any seasonal differences. A series of negative binomial regression models, which take into account control variables like weather conditions and calendar events, are adopted to empirically measure the impacts. Results show that the PM levels yield statistically significant negative impacts (p < 0.01) on bike sharing use throughout the year. The impacts are particularly stronger in winter and spring, when the PM levels are higher. Findings suggest that PM levels may operate as driving factors for bike sharing use in addition to meteorological conditions like temperature, humidity, and precipitation.

Personal strategies to minimise effects of air pollution on respiratory health: advice for providers, patients and the public

As global awareness of air pollution rises, so does the imperative to provide evidence-based recommendations for strategies to mitigate its impact. While public policy has a central role in reducing air pollution, exposure can also be reduced by personal choices. Qualified evidence supports limiting physical exertion outdoors on high air pollution days and near air pollution sources, reducing near-roadway exposure while commuting, utilising air quality alert systems to plan activities, and wearing facemasks in prescribed circumstances. Other strategies include avoiding cooking with solid fuels, ventilating and isolating cooking areas, and using portable air cleaners fitted with high-efficiency particulate air filters. We detail recommendations to assist providers and public health officials when advising patients and the public regarding personal-level strategies to mitigate risk imposed by air pollution, while recognising that well-designed prospective studies are urgently needed to better establish and validate interventions that benefit respiratory health in this context.

Association of prevalence of active transport to work and incidence of myocardial infarction: A nationwide ecological study

BACKGROUND

There is a paucity of population-based geospatial data about the association between active transport and myocardial infarction. We investigated the association between active transport to work and incidence of myocardial infarction.

DESIGN

This ecological study of 325 local authorities in England included 43,077,039 employed individuals aged 25-74 years (UK Census, 2011), and 117,521 individuals with myocardial infarction (Myocardial Ischaemia National Audit Project, 2011-2013).

METHODS

Bayesian negative binomial regression models were used to investigate the association of active transport to work and incidence of myocardial infarction adjusting for local levels of deprivation, obesity, smoking, diabetes and physical activity.

RESULTS

In 2011, the prevalence of active transportation to work for people in employment in England aged 25-74 years was 11.4% (4,531,182 active transporters; 8.6% walking and 2.8% cycling). Active transport in 2011 was associated with a reduced incidence of myocardial infarction in 2012 amongst men cycling to work (incidence rate ratio (95% credible interval) 0.983 (0.967-0.999); and women walking to work (0.983 (0.967-0.999)) after full adjustments. However, the prevalence of active transport for men and women was not significantly associated with the combined incidence of myocardial infarction between 2011-2013 after adjusting for physical activity, smoking and diabetes.

CONCLUSIONS

In England, the prevalence of active transportation was associated with a reduced incidence of myocardial infarction for women walking and men cycling to work in corresponding local geographic areas. The overall association of active transport with myocardial infarction was, however, explained by local area levels of smoking, diabetes and physical activity.

Research on the Psychological Model of Free-floating Bike-Sharing Using Behavior: A Case Study of Beijing

As a clean, sustainable transport tool, bicycles have significant advantages in short-distance travel. Despite many efforts assumed in Beijing to improve the cycling environment, the popularity of cycling remains relatively low. However, the advent of the free-floating bike-sharing (FFBS) system has engendered an unexpected cycling enthusiasm in Beijing. Therefore, it is of great importance to delve into why travelers prefer FFBS as a transportation form from a psychological perspective. In this paper, 352 valid questionnaires were collected from an online survey, and an extended theory of planned behavior (TPB) was adopted to examine the psychological determinants of intention and actual behavior to use FFBS. The results showed that men and car-owners prefer vehicles and show a lower willingness to use FFBS. In contrast, residents under the age of 60, residents with FFBS riding experience, and residents skilled in cycling are inclined to use FFBS; the economic convenience of FFBS is the most important attractant for FFBS, while bad weather is the biggest hindrance factor for residents to use FFBS; however, imperfection in infrastructure has no significant impact on reducing residents’ willingness to use FFBS. These results have important implications for planners to better understand the FFBS use behavior, and several suggestions are proposed to support the policymaking about FFBS.

Association of injury related hospital admissions with commuting by bicycle in the UK: prospective population based study

OBJECTIVE

To determine whether bicycle commuting is associated with risk of injury.

DESIGN

Prospective population based study.

SETTING

UK Biobank.

PARTICIPANTS

230 390 commuters (52.1% women; mean age 52.4 years) recruited from 22 sites across the UK compared by mode of transport used (walking, cycling, mixed mode versus non-active (car or public transport)) to commute to and from work on a typical day.

MAIN OUTCOME MEASURE

First incident admission to hospital for injury.

RESULTS

5704 (2.5%) participants reported cycling as their main form of commuter transport. Median follow-up was 8.9 years (interquartile range 8.2-9.5 years), and overall 10 241 (4.4%) participants experienced an injury. Injuries occurred in 397 (7.0%) of the commuters who cycled and 7698 (4.3%) of the commuters who used a non-active mode of transport. After adjustment for major confounding sociodemographic, health, and lifestyle factors, cycling to work was associated with a higher risk of injury compared with commuting by a non-active mode (hazard ratio 1.45, 95% confidence interval 1.30 to 1.61). Similar trends were observed for commuters who used mixed mode cycling. Walking to work was not associated with a higher risk of injury. Longer cycling distances during commuting were associated with a higher risk of injury, but commute distance was not associated with injury in non-active commuters. Cycle commuting was also associated with a higher number of injuries when the external cause was a transport related incident (incident rate ratio 3.42, 95% confidence interval 3.00 to 3.90). Commuters who cycled to work had a lower risk of cardiovascular disease, cancer, and death than those who did not. If the associations are causal, an estimated 1000 participants changing their mode of commuting to include cycling for 10 years would result in 26 additional admissions to hospital for a first injury (of which three would require a hospital stay of a week or longer), 15 fewer first cancer diagnoses, four fewer cardiovascular disease events, and three fewer deaths.

CONCLUSION

Compared with non-active commuting to work, commuting by cycling was associated with a higher risk of hospital admission for a first injury and higher risk of transport related incidents specifically. These risks should be viewed in context of the health benefits of active commuting and underscore the need for a safer infrastructure for cycling in the UK.

Health economic assessment of a shift to active transport

Active transportation (walking or cycling) as a substitute for car trips still represents a small percentage of all daily travels in many European cities. This study aimed to estimate the health and economic co-benefits for the adult population of modal shift from driving to active travel in urban environments. Three scenarios were modelled for the case study, the city of Porto, Portugal, by comparing travel patterns of 2013 to hypothetical scenarios of modal shifts from driving to active transport, namely: i) SC1 - conservative scenario, with a change of 5% from driving to cycling and 10% from driving to walking; ii) SC2 - moderate scenario, with a shift of 10% and 15%, respectively; and iii) SC3 - optimistic scenario, with a shift of 15% and 20%, respectively. The mortality risk reduction for five health outcomes (colon and breast cancers, diabetes, ischemic heart disease, cerebrovascular disease) was assessed, including an estimation of traffic injury and air pollution exposure risks. Results were presented in Disability-Adjusted Life Years (DALYs) avoided. Economic valuation for each scenario was performed using a Willingness-to-Pay approach for morbimortality and a Cost of Illness approach for 2013 hospitalizations and work absenteeism. Significant health benefits were found in all modelled scenarios, ranging from 1657 (16%) to 2881 (28%) DALYs avoided. Total costs averted ranged from €3894 to €6769 million through the scenarios. Cardio and cerebrovascular diseases mortality presented the largest benefit, accounting for about 3/4 of all avoidable DALYs in all scenarios. Reductions in CO₂ and PM₁₀ emissions were calculated, showing a decrease from 31.6 to 73.7 kt of CO₂ and 7 to 16 t for PM₁₀, respectively. A modal shift towards active transportation could lead to significant health and economic benefits, indicating that the evaluation of health impacts should be included in the analysis of active transport interventions.

Burden of disease from transportation noise and motor vehicle crashes: Analysis of data from Houston, Texas

BACKGROUND

Transportation systems have an essential role in satisfying individuals' needs for mobility and accessibility. Yet, they have been linked to several adverse health impacts, with a large, but modifiable, burden of disease. Among the several transportation-related health risk factors, this study focused on transportation-related noise as an emerging exposure whose burden of disease remains partially recognized. We compared premature deaths potentially attributable to transportation-related noise with deaths from motor vehicle crashes, a well-researched and widely recognized transportation risk factor.

METHOD

We employed a standard burden of disease assessment framework to quantify premature cardiovascular diseases mortality attributable to transportation-related (road and aviation) noise at the census tract level (n = 592) in Houston, Texas. The results were compared to motor vehicle crash fatalities, which are routinely observed and collected in the study area. We also investigated the distribution of premature deaths across the city and explored the relationship between household median income and premature deaths attributable to transportation-related noise.

RESULTS

We estimated 302 (95% CI: 185-427) premature deaths (adults 30-75 years old) attributable to transportation-related noise in Houston, compared to 330 fatalities from motor vehicle crashes (adults younger than 75 years old). Transportation-related noise and motor vehicle crashes were responsible for 1.7% and 1.9% of all-cause premature deaths in Houston, respectively. Households with lower median income had a higher risk of adverse exposure and premature deaths potentially attributable to transportation-related noise. A larger number of premature deaths was associated with living in the central business district and the vicinity of highways and airports.

CONCLUSION

This study highlighted the significant contribution of transportation-related noise and motor vehicle crashes to premature deaths in the city of Houston. The analogy between the estimated premature deaths attributable to transportation-related noise and motor vehicle crashes showed that the health impacts of transportation-related noise were as significant as motor vehicle crashes. The estimated premature death rate attributable to transportation-related noise was also comparable to the death rate caused by suicide, influenza, or pneumonia in the US. There is an urgent need for imposing policies to reduce transportation noise emissions and human exposures and to equip health impact assessment tools with a noise burden of disease analysis function.

Prevalence and dissemination risk of antimicrobial-resistant Enterobacteriaceae from shared bikes in Beijing, China

Bike-sharing as a common public transportation has been booming in China in recent years. Previous studies showed that the surfaces of public transport can act as reservoirs of antimicrobial-resistant (AR) bacteria, but AR bacterial contamination of shared bikes has not been investigated. Otherwise, the AR-Enterobacteriaceae is considered as a global health threat for humans. Herein, we aimed to investigate the prevalence of AR Enterobacteriaceae on shared bikes and examine correlations between AR Enterobacteriaceae from shared bikes and public buildings around Metro stations in Beijing. We collected 2117 samples from shared bikes at 240 Metro stations in Beijing. A total of 444 non-duplicate Enterobacteriaceae were isolated from 418 samples at 166 stations. The isolates exhibited low rates of resistance (0.5%-6.3%) to all antimicrobial agents except sulfamethoxazole-trimethoprim (31.5%). Three ceftazidime-resistant E. coli isolates were positive for bla_CTX-M-199 and two of them were positive for carbapenemase-producing gene bla_NDM-5. Multivariable logistic regression model revealed that variable "secondary/tertiary non-profit hospital nearby" was significantly (p < 0.05) associated with isolation of AR Enterobacteriaceae from the shared bikes around the Metro stations. Low AR rates of Enterobacteriaceae observed in this study suggested the risk of dissemination of AR-Enterobacteriaceae via shared bikes is limited. However, we identified hospitals as a risk factor for the dissemination of AR Enterobacteriaceae among shared bike users. More attention should be paid to both comprehensive hygiene managements in the surrounding environment of hospitals and the increasing of public awareness on the personal hygienic habits.

Analysis of Network Structure of Urban Bike-Sharing System: A Case Study Based on Real-Time Data of a Public Bicycle System

To better understand the characteristics of a bike-sharing system, we applied complex network methods to analyze the relationship between stations within the bike-sharing system. Firstly, using Gephi software, we constructed the public bicycle networks of different urban areas based on the real-time data of the Nanjing public bicycle system. Secondly, we analyzed and compared degree, strength, radiation distance, and community structure of the networks to understand the internal relations of the public bicycle system. The results showed that there were many stations with low usage of public bicycles. Furthermore, there was a geographical division between high-demand and low-demand areas for public bicycles. The usage of public bicycles at a station was not only related to land use but also related to the usage of bicycles at stations nearby. Moreover, the average service coverage of the public bicycle system was consistent with the original intention of “the first and last mile”, and public bicycles could meet different travel needs.

Potential of active transport to improve health, reduce healthcare costs, and reduce greenhouse gas emissions: A modelling study

Background

Physical inactivity contributes substantively to disease burden, especially in highly car dependent countries such as New Zealand (NZ). We aimed to quantify the future health gain, health-sector cost-savings, and change in greenhouse gas emissions that could be achieved by switching short vehicle trips to walking and cycling in New Zealand.

Methods

We used unit-level survey data to estimate changes in physical activity, distance travelled by mode, and air pollution for: (a) switching car trips under 1km to walking and (b) switching car trips under 5km to a mix of walking and cycling. We modelled uptake levels of 25%, 50%, and 100%, and assumed changes in transport behaviour were permanent. We then used multi-state life table modelling to quantify health impacts as quality adjusted life years (QALYs) gained and changes in health system costs over the rest of the life course of the NZ population alive in 2011 (n = 4.4 million), with 3% discounting.

Findings

The modelled scenarios resulted in health gains between 1.61 (95% uncertainty interval (UI) 1.35 to 1.89) and 25.43 (UI 20.20 to 30.58) QALYs/1000 people, with total QALYs up to 112,020 (UI 88,969 to 134,725) over the remaining lifespan. Healthcare cost savings ranged between NZ$127million (UI $101m to 157m) and NZ$2.1billion (UI $1.6b to 2.6b). Greenhouse gas emissions were reduced by up to 194kgCO₂e/year, though changes in emissions were not significant under the walking scenario.

Conclusions

Substantial health gains and healthcare cost savings could be achieved by switching short car trips to walking and cycling. Implementing infrastructural improvements and interventions to encourage walking and cycling is likely to be a cost-effective way to improve population health, and may also reduce greenhouse gas emissions.