Equity in temporary street closures: The case of London's Covid-19 'School Streets' schemes.

School Streets are a street space reallocation scheme that has proliferated since the beginning of the Covid-19 pandemic in the UK, reducing motor traffic on streets outside many schools. Utilising a minimum-standards approach to equity, this paper examines the distribution of School Streets closures across social and environmental indicators of equity, and spatially across London's administrative geography. Using a multi-level regression analysis, we show that although School Streets have been equally distributed across several socio-demographic indicators, they are less likely to benefit schools in car-dominated areas of poor air quality, and their spatial distribution is highly unequal. This study presents an example of using environmental and spatial variables alongside more typical sociodemographic indicators in measuring the equity of school travel provision. For policymakers, the findings signal the need to implement complementary policies that can benefit schools with worse air quality, and to accelerate School Street implementation in slower districts.

Health, environmental and distributional impacts of cycling uptake: The model underlying the Propensity to Cycle tool for England and Wales.

INTRODUCTION: The Propensity to Cycle Tool (PCT) is a widely used free, open source and publicly available tool for modelling cycling uptake and corresponding health and carbon impacts in England and Wales. In this paper we present the methods for our new individual-level modelling representing all commuters in England and Wales. METHODS: Scenario commuter cycling potential in the PCT is modelled as a function of route distance and hilliness between home and work. Our new individual-level approach has allowed us to create an additional "Near Market" scenario where age, gender, ethnicity, car ownership and area level deprivation also affect an individual's likelihood of switching to cycling. For this and other scenarios, we calculate the carbon benefits of cycling uptake based on the trip distance and previous mode, while health benefits are additionally affected by hilliness and baseline average mortality risk. This allows the estimation of how health and carbon benefits differ by demographic group as well as by scenario. RESULTS: While cycle commuting in England and Wales is demographically skewed towards men and white people, women and people from ethnic minorities have greater cycling potential based on route distance and hilliness. Benefits from cycling uptake are distributed differently again. For example, while increasing female cycling mode share is good for equity, each additional female cyclist generates a smaller average health and carbon benefit than a male cyclist. This is based on women's lower baseline mortality risk, shorter commute travel distances, and lower propensity to commute by car than men. CONCLUSION: We have demonstrated a new approach to modelling that allows for more sophisticated and nuanced assessment of cycling uptake and subsequent benefits, under different scenarios. Health and carbon are increasingly incorporated into appraisal of active travel schemes, valuing important outcomes. However, especially with better representation of demographic factors, this can act as a barrier to equity goals.

Association of Infrastructure and Route Environment Factors with Cycling Injury Risk at Intersection and Non-Intersection Locations: A Case-Crossover Study of Britain.

OBJECTIVE: This paper examines infrastructural and route environment correlates of cycling injury risk in Britain for commuters riding in the morning peak. METHODS: The study uses a case-crossover design which controls for exposure. Control sites from modelled cyclist routes (matched on intersection status) were compared with sites where cyclists were injured. Conditional logistic regression for matched case-control groups was used to compare characteristics of control and injury sites. RESULTS: High streets (defined by clustering of retail premises) raised injury odds by 32%. Main (Class A or primary) roads were riskier than other road types, with injury odds twice that for residential roads. Wider roads, and those with lower gradients increased injury odds. Guard railing raised injury odds by 18%, and petrol stations or car parks by 43%. Bus lanes raised injury odds by 84%. As in other studies, there was a 'safety in numbers' effect from more cyclists. Contrary to other analysis, including two recent studies in London, we did not find a protective effect from cycle infrastructure and the presence of painted cycle lanes raised injury odds by 54%. At intersections, both standard and mini roundabouts were associated with injury odds several times higher than other intersections. Presence of traffic signals, with or without an Advanced Stop Line ('bike box'), had no impact on injury odds. For a cyclist on a main road, intersections with minor roads were riskier than intersections with other main roads. CONCLUSIONS: Typical cycling environments in Britain put cyclists at risk, and infrastructure must be improved, particularly on busy main roads, high streets, and bus routes.

Cycling injury risk in Britain: A case-crossover study of infrastructural and route environment correlates.

This paper examines infrastructural and route environment correlates of cycling injury risk in Britain. We used a case-crossover design, randomly selecting control sites from modelled cyclist routes, comparing these with sites where cyclists were injured. We then used conditional logistic regression for matched case-control groups modelling to compare characteristics of control and injury sites. Intersections were strongly associated with injury risk. High streets were associated with an elevated injury risk in final adjusted models, as was road type being primary, and a more downhill gradient. Lower speed limits and lower motor traffic connectivity were initially associated with lower injury risk, but these effects were no longer statistically significant in adjusted models. Increased road width was associated with increased injury risk in all models. Increased injury risk was associated in all models with presence of bus lane (somewhat mitigated at stops), guardrail, and fuel station or parking lot. Presence of parked cars in street view data raised injury risk in fully adjusted models, as did congestion (measured by low morning peak speeds), while higher volumes of people cycling along the street reduced it. In fully adjusted models, a statistically significant increase in risk was associated with presence of an on-road painted cycle lane. Most cycle lanes or tracks at control and injury sites were very poor, with narrow lanes, shared footways, and lack of protection at junctions. Given findings from other studies showing protective effects of cycle infrastructure, Britain must create higher quality cycle provision, avoiding narrow on-road painted lanes.

How does mode of travel affect risks posed to other road users? An analysis of English road fatality data, incorporating gender and road type.

BACKGROUND: Most analysis of road injuries examines the risk experienced by people using different modes of transport, for instance, pedestrian fatalities per-head or per-km. A small but growing field analyses the impact that the use of different transport modes has on other road users, for instance, injuries to others per-km driven. METHODS: This paper moves the analysis of risk posed to others forward by comparing six different vehicular modes, separating road types (major vs minor roads in urban vs rural settings). The comparison of risk posed by men and women for all these modes is also novel. RESULTS: Per-vehicle kilometre, buses and lorries pose much the highest risk to others, while cycles pose the lowest. Motorcycles pose a substantially higher per-km risk to others than cars. The fatality risk posed by cars or vans to ORUs per km is higher in rural areas. Risk posed is generally higher on major roads, although not in the case of lorries, suggesting a link to higher speeds. Men pose higher per-km risk to others than women for all modes except buses, as well as being over-represented among users of the most dangerous vehicles. CONCLUSIONS: Future research should examine more settings, adjust for spatial and temporal confounders, or examine how infrastructure or route characteristics affect risk posed to others. Although for most victims the other vehicle involved is a car, results suggest policy-makers should also seek to reduce disproportionate risks posed by the more dangerous vehicles, for instance, by discouraging motorcycling. Finally, given higher risk posed to others by men across five of six modes analysed, policy-makers should consider how to reduce persistent large gender imbalances in jobs involving driving.

Cyclist Injury Severity in Spain: A Bayesian Analysis of Police Road Injury Data Focusing on Involved Vehicles and Route Environment.

This study analyses factors associated with cyclist injury severity, focusing on vehicle type, route environment, and interactions between them. Data analysed was collected by Spanish police during 2016 and includes records relating to 12,318 drivers and cyclist involving in collisions with at least one injured cyclist, of whom 7230 were injured cyclists. Bayesian methods were used to model relationships between cyclist injury severity and circumstances related to the crash, with the outcome variable being whether a cyclist was killed or seriously injured (KSI) rather than slightly injured. Factors in the model included those relating to the injured cyclist, the route environment, and involved motorists. Injury severity among cyclists was likely to be higher where an Heavy Goods Vehicle (HGV) was involved, and certain route conditions (bicycle infrastructure, 30 kph zones, and urban zones) were associated with lower injury severity. Interactions exist between the two: collisions involving large vehicles in lower-risk environments are less likely to lead to KSIs than collisions involving large vehicles in higher-risk environments. Finally, motorists involved in a collision were more likely than the injured cyclists to have committed an error or infraction. The study supports the creation of infrastructure that separates cyclists from motor traffic. Also, action needs to be taken to address motorist behaviour, given the imbalance between responsibility and risk.

Built Environment Interventions to Increase Active Travel: a Critical Review and Discussion.

PURPOSE OF REVIEW: To review the literature on built environment interventions to increase active travel, focusing on work since 2000 and on methodological choices and challenges affecting studies. RECENT FINDINGS: Increasingly, there is evidence that built environment interventions can lead to more walking or cycling. Evidence is stronger for cycling than for walking interventions, and there is a relative lack of evidence around differential impacts of interventions. Some of the evidence remains methodologically weak, with much work in the 'grey' literature. While evidence in the area continues to grow, data gaps remain. Greater use of quasi-experimental techniques, improvements in routine monitoring of smaller schemes, and the use of new big data sources are promising. More qualitative research could help develop a more sophisticated understanding of behaviour change.

Barriers to investing in cycling: Stakeholder views from England.

BACKGROUND: Planners and politicians in many countries seek to increase the proportion of trips made by cycling. However, this is often challenging. In England, a national target to double cycling by 2025 is likely to be missed: between 2001 and 2011 the proportion of commutes made by cycling barely grew. One important contributory factor is continued low investment in cycling infrastructure, by comparison to European leaders. METHODS: This paper examines barriers to cycling investment, considering that these need to be better understood to understand failures to increase cycling level. It is based on qualitative data from an online survey of over 400 stakeholders, alongside seven in-depth interviews. RESULTS: Many respondents reported that change continues to be blocked by chronic barriers including a lack of funding and leadership. Participants provided insights into how challenges develop along the life of a scheme. In authorities with little consideration given to cycling provision, media and public opposition were not reported as a major issue. However, where planning and implementation have begun, this can change quickly; although examples were given of schemes successfully proceeding, despite this. The research points to a growing gap between authorities that have overcome key challenges, and those that have not.

Contextualising Safety in Numbers: a longitudinal investigation into change in cycling safety in Britain, 1991-2001 and 2001-2011.

INTRODUCTION: The 'Safety in Numbers' (SiN) phenomenon refers to a decline of injury risk per time or distance exposed as use of a mode increases. It has been demonstrated for cycling using cross-sectional data, but little evidence exists as to whether the effect applies longitudinally -that is, whether changes in cycling levels correlate with changes in per-cyclist injury risks. METHODS: This paper examines cross-sectional and longitudinal SiN effects in 202 local authorities in Britain, using commuting data from 1991, 2001 and 2011 censuses plus police -recorded data on 'killed and seriously injured' (KSI) road traffic injuries. We modelled a log-linear relationship between number of injuries and number of cycle commuters. Second, we conducted longitudinal analysis to examine whether local authorities where commuter cycling increased became safer (and vice versa). RESULTS: The paper finds a cross-sectional SiN effect exists in the 1991, 2001 and 2011 censuses. The longitudinal analysis also found a SiN effect, that is, places where cycling increased were more likely to become safer than places where it had declined. Finally, these longitudinal results are placed in the context of changes in pedestrian, cyclist and motorist safety. While between 1991 and 2001 all modes saw declines in KSI risk (37% for pedestrians, 36% for cyclists and 27% for motor vehicle users), between 2001 and 2011 pedestrians and motorists saw even more substantial declines (41% and 49%), while risk for cyclists increased by 4%. CONCLUSION: The SiN mechanism does seem to operate longitudinally as well as cross-sectionally. However, at a national level between 2001-11 it co-existed with an increase in cyclist injury risk both in absolute terms and in relation to other modes.

Estimating city-level travel patterns using street imagery: A case study of using Google Street View in Britain.

BACKGROUND: Street imagery is a promising and growing big data source providing current and historical images in more than 100 countries. Studies have reported using this data to audit road infrastructure and other built environment features. Here we explore a novel application, using Google Street View (GSV) to predict travel patterns at the city level. METHODS: We sampled 34 cities in Great Britain. In each city, we accessed 2000 GSV images from 1000 random locations. We selected archived images from time periods overlapping with the 2011 Census and the 2011-2013 Active People Survey (APS). We manually annotated the images into seven categories of road users. We developed regression models with the counts of images of road users as predictors. The outcomes included Census-reported commute shares of four modes (combined walking plus public transport, cycling, motorcycle, and car), as well as APS-reported past-month participation in walking and cycling. RESULTS: We found high correlations between GSV counts of cyclists ('GSV-cyclists') and cycle commute mode share (r = 0.92)/past-month cycling (r = 0.90). Likewise, GSV-pedestrians was moderately correlated with past-month walking for transport (r = 0.46), GSV-motorcycles was moderately correlated with commute share of motorcycles (r = 0.44), and GSV-buses was highly correlated with commute share of walking plus public transport (r = 0.81). GSV-car was not correlated with car commute mode share (r = -0.12). However, in multivariable regression models, all outcomes were predicted well, except past-month walking. The prediction performance was measured using cross-validation analyses. GSV-buses and GSV-cyclists are the strongest predictors for most outcomes. CONCLUSIONS: GSV images are a promising new big data source to predict urban mobility patterns. Predictive power was the greatest for those modes that varied the most (cycle and bus). With its ability to identify mode of travel and capture street activity often excluded in routinely carried out surveys, GSV has the potential to be complementary to new and traditional data. With half the world's population covered by street imagery, and with up to 10 years historical data available in GSV, further testing across multiple settings is warranted both for cross-sectional and longitudinal assessments.

Cycling injury risk in London: A case-control study exploring the impact of cycle volumes, motor vehicle volumes, and road characteristics including speed limits.

Cycling injury risk is an important topic, but few studies explore cycling risk in relation to exposure. This is largely because of a lack of exposure data, in other words how much cycling is done at different locations. This paper helps to fill this gap. It reports a case-control study of cycling injuries in London in 2013-2014, using modelled cyclist flow data alongside datasets covering some characteristics of the London route network. A multilevel binary logistic regression model is used to investigate factors associated with injury risk, comparing injury sites with control sites selected using the modelled flow data. Findings provide support for 'safety in numbers': for each increase of a natural logarithmic unit (2.71828) in cycling flows, an 18% decrease in injury odds was found. Conversely, increased motor traffic volume is associated with higher odds of cycling injury, with one logarithmic unit increase associated with a 31% increase in injury odds. Twenty-mile per hour compared with 30mph speed limits were associated with 21% lower injury odds. Residential streets were associated with reduced injury odds, and junctions with substantially higher injury odds. Bus lanes do not affect injury odds once other factors are controlled for. These data suggest that speed limits of 20 mph may reduce cycling injury risk, as may motor traffic reduction. Further, building cycle routes that generate new cycle trips should generate 'safety in numbers' benefits.

Predictors of the frequency and subjective experience of cycling near misses: Findings from the first two years of the UK Near Miss Project.

Using 2014 and 2015 data from the UK Near Miss Project, this paper examines the stability of self-report incident rates for cycling near misses across these two years. It further examines the stability of the individual-level predictors of experiencing a near miss, including what influences the scariness of an incident. The paper uses three questions asked for only in 2015, which allow further exploration of factors shaping near miss rates and impacts of incidents. Firstly, a respondent's level of cycling experience; secondly, whether an incident was perceived as deliberate; and finally, whether the respondent themselves described the incident as a 'near miss' (as opposed to only a frightening and/or annoying non-injury incident). Using this data, we find a decline of almost a third in incident rates in 2015 compared to 2014, which we believe is likely to be largely an artefact due to differences in reporting rates. This suggests caution about interpreting small fluctuations in subjectively reported near miss rates. However, in both years near miss rates are many times more frequent than injury collisions. In both years of data collection our findings are very similar in terms of the patterning of incident types, and how frightening different incident categories are, which increases confidence in these findings. We find that new cyclists experience very high incident rates compared to other cyclists, and test a conceptual model explaining how perceived deliberateness, near-miss status, and scariness are connected. For example, incidents that are perceived to be deliberate are more likely to be experienced as very frightening, independent of their 'near miss' status.

Cycling provision separated from motor traffic: a systematic review exploring whether stated preferences vary by gender and age.

In this paper, we represent a systematic review of stated preference studies examining the extent to which cycle infrastructure preferences vary by gender and by age. A search of online, English-language academic and policy literature was followed by a three-stage screening process to identify relevant studies. We found 54 studies that investigated whether preferences for cycle infrastructure varied by gender and/or by age. Forty-four of these studies considered the extent of separation from motor traffic. The remainder of the studies covered diverse topics, including preferred winter maintenance methods and attitudes to cycle track lighting. We found that women reported stronger preferences than men for greater separation from motor traffic. There was weaker evidence of stronger preferences among older people. Differences in preferences were quantitative rather than qualitative; that is, preferences for separated infrastructure were stronger in some groups than in others, but no group preferred integration with motor traffic. Thus, in low-cycling countries seeking to increase cycling, this evidence suggests focusing on the stronger preferences of under-represented groups as a necessary element of universal design for cycling.

Trends in local newspaper reporting of London cyclist fatalities 1992-2012: the role of the media in shaping the systems dynamics of cycling.

BACKGROUND: Successfully increasing cycling across a broad range of the population would confer important health benefits, but many potential cyclists are deterred by fears about traffic danger. Media coverage of road traffic crashes may reinforce this perception. As part of a wider effort to model the system dynamics of urban cycling, in this paper we examined how media coverage of cyclist fatalities in London changed across a period when the prevalence of cycling doubled. We compared this with changes in the coverage of motorcyclist fatalities as a control group. METHODS: Police records of traffic crashes (STATS19) were used to identify all cyclist and motorcyclist fatalities in London between 1992 and 2012. We searched electronic archives of London's largest local newspaper to identify relevant articles (January 1992-April 2014), and sought to identify which police-reported fatalities received any media coverage. We repeated this in three smaller English cities. RESULTS: Across the period when cycling trips doubled in London, the proportion of fatalities covered in the local media increased from 6% in 1992-1994 to 75% in 2010-2012. By contrast, the coverage of motorcyclist fatalities remained low (4% in 1992-1994 versus 5% in 2010-2012; p=0.007 for interaction between mode and time period). Comparisons with other English cities suggested that the changes observed in London might not occur in smaller cities with lower absolute numbers of crashes, as in these settings fatalities are almost always covered regardless of mode share (79-100% coverage for both cyclist and motorcyclist fatalities). CONCLUSION: In large cities, an increase in the popularity (and therefore 'newsworthiness') of cycling may increase the propensity of the media to cover cyclist fatalities. This has the potential to give the public the impression that cycling has become more dangerous, and thereby initiate a negative feedback loop that dampens down further increases in cycling. Understanding these complex roles of the media in shaping cycling trends may help identify effective policy levers to achieve sustained growth in cycling.

'A potential fifth column': conflicts and struggles for control in the context of local NHS privatization.

This article uses case study data to discuss how a new procurement policy (Local Improvement Finance Trust, or LIFT) in English primary care may affect general practitioners' control over their work. LIFT, a series of 51 public-private partnerships, will enable over the medium term a shift towards the corporate ownership of surgeries and the creation of polyclinics or 'onestop-shops'. In this article, I explore the struggles over work autonomy and control within these new LIFT structures, as expressed by clinicians and managers in meetings and in research interviews. More generally, I consider how the findings inform debates over the changing position of professionals within increasingly financialized 'local health economies'.

Cars, corporations, and commodities: consequences for the social determinants of health.

Social epidemiologists have drawn attention to health inequalities as avoidable and inequitable, encouraging thinking beyond proximal risk factors to the causes of the causes. However, key debates remain unresolved including the contribution of material and psychosocial pathways to health inequalities. Tools to operationalise social factors have not developed in tandem with conceptual frameworks, and research has often remained focused on the disadvantaged rather than on forces shaping population health across the distribution. Using the example of transport, we argue that closer attention to social processes (capital accumulation and motorisation) and social forms (commodity, corporation, and car) offers a way forward. Corporations tied to the car, primarily oil and vehicle manufacturers, are central to the world economy. Key drivers in establishing this hegemony are the threat of violence from motor vehicles and the creation of distance through the restructuring of place. Transport matters for epidemiology because the growth of mass car ownership is environmentally unsustainable and affects population health through a myriad of pathways. Starting from social forms and processes, rather than their embodiment as individual health outcomes and inequalities, makes visible connections between road traffic injuries, obesity, climate change, underdevelopment of oil producing countries, and the huge opportunity cost of the car economy. Methodological implications include a movement-based understanding of how place affects health and a process-orientated integration of material and psychosocial explanations that, while materially based, contests assumptions of automatic benefits from economic growth. Finally, we identify car and oil corporations as anti-health forces and suggest collaboration with them creates conflicts of interest.