Systematic review and meta-analysis on the impact of COVID-19 related restrictions on air quality in low- and middle-income countries

BACKGROUND

Low- and middle-income countries (LMIC) are disproportionately affected by air pollution and its health burden, representing a global inequity. The COVID-19 pandemic provided a unique opportunity to investigate the impact of unprecedented lockdown measures on air pollutant concentrations globally. We aim to quantify air pollutant concentration changes across LMIC settings as a result of COVID-19 restrictions.

METHODS

Searches for this systematic review and meta-analysis were carried out across five databases on 30th March 2022; MEDLINE, Embase, Web of Science, Scopus and Transport Research Information Documentation. Modelling and observational studies were included, as long as the estimates reflected city or town level data and were taken exclusively in pre-lockdown and lockdown periods. Mean percentage changes per pollutant were calculated and meta-analyses were carried out to calculate mean difference in measured ground-level observed concentrations for each pollutant (PROSPERO CRD42022326924).

FINDINGS

Of the 2982 manuscripts from initial searches, 256 manuscripts were included providing 3818 percentage changes of all pollutants. No studies included any countries from Sub-Saharan Africa and 34 % and 39.4 % of studies were from China and India, respectively. There was a mean percentage change of -37.4 %, -21.7 %, -54.6 %, -39.1 %, -48.9 %, 16.9 %, -34.9 %, -30.6 % and - 14.7 % for black carbon (BC), carbon monoxide (CO), nitric oxide (NO), nitrogen dioxide (NO2), oxides of nitrogen (NOx), ozone (O3), particulate matter 10 (PM10) and 2.5 (PM2.5) and sulphur dioxide (SO2), respectively. Meta-analysis included 100 manuscripts, providing 908 mean concentration differences, which showed significant reduction in mean concentration in all study settings for BC (-0.46 μg/m3, PI -0.85; -0.08), CO (-0.25 mg/m3, PI -0.44; -0.03), NO2 (-19.41 μg/m3, PI -31.14; -7.68) and NOx (-22.32 μg/m3, PI -40.94; -3.70).

INTERPRETATION

The findings of this systematic review and meta-analysis quantify and confirm the trends reported across the globe in air pollutant concentration, including increases in O3. Despite the majority of global urban growth occurring in LMIC, there are distinct geographical gaps in air pollution data and, where it is available, differing approaches to analysis and reporting.

Non-occupational physical activity and risk of cardiovascular disease, cancer and mortality outcomes: a dose-response meta-analysis of large prospective studies

OBJECTIVE

To estimate the dose-response associations between non-occupational physical activity and several chronic disease and mortality outcomes in the general adult population.

DESIGN

Systematic review and cohort-level dose-response meta-analysis.

DATA SOURCES

PubMed, Scopus, Web of Science and reference lists of published studies.

ELIGIBILITY CRITERIA

Prospective cohort studies with (1) general population samples >10 000 adults, (2) ≥3 physical activity categories, and (3) risk measures and CIs for all-cause mortality or incident total cardiovascular disease, coronary heart disease, stroke, heart failure, total cancer and site-specific cancers (head and neck, myeloid leukaemia, myeloma, gastric cardia, lung, liver, endometrium, colon, breast, bladder, rectum, oesophagus, prostate, kidney).

RESULTS

196 articles were included, covering 94 cohorts with >30 million participants. The evidence base was largest for all-cause mortality (50 separate results; 163 415 543 person-years, 811 616 events), and incidence of cardiovascular disease (37 results; 28 884 209 person-years, 74 757 events) and cancer (31 results; 35 500 867 person-years, 185 870 events). In general, higher activity levels were associated with lower risk of all outcomes. Differences in risk were greater between 0 and 8.75 marginal metabolic equivalent of task-hours per week (mMET-hours/week) (equivalent to the recommended 150 min/week of moderate-to-vigorous aerobic physical activity), with smaller marginal differences in risk above this level to 17.5 mMET-hours/week, beyond which additional differences were small and uncertain. Associations were stronger for all-cause (relative risk (RR) at 8.75 mMET-hours/week: 0.69, 95% CI 0.65 to 0.73) and cardiovascular disease (RR at 8.75 mMET-hours/week: 0.71, 95% CI 0.66 to 0.77) mortality than for cancer mortality (RR at 8.75 mMET-hours/week: 0.85, 95% CI 0.81 to 0.89). If all insufficiently active individuals had achieved 8.75 mMET-hours/week, 15.7% (95% CI 13.1 to 18.2) of all premature deaths would have been averted.

CONCLUSIONS

Inverse non-linear dose-response associations suggest substantial protection against a range of chronic disease outcomes from small increases in non-occupational physical activity in inactive adults. PROSPERO registration number CRD42018095481.

Comparing travel behaviour characteristics and correlates between large and small Kenyan cities (Nairobi versus Kisumu)

Understanding urban travel behaviour is crucial for planning healthy and sustainable cities. Africa is urbanising at one of the fastest rates in the world and urgently needs this knowledge. However, the data and literature on urban travel behaviour, their correlates, and their variation across African cities are limited. We aimed to describe and compare travel behaviour characteristics and correlates of two Kenyan cities (Nairobi and Kisumu). We analysed data from 16,793 participants (10,000 households) in a 2013 Japan International Cooperation Agency (JICA) household travel survey in Nairobi and 5790 participants (2760 households) in a 2016 Institute for Transportation and Development Policy (ITDP) household travel survey in Kisumu. We used the Heckman selection model to explore correlations of travel duration by trip mode. The proportion of individuals reporting no trips was far higher in Kisumu (47% vs 5%). For participants with trips, the mean number [lower - upper quartiles] of daily trips was similar (Kisumu (2.2 [2-2] versus 2.4 [2-2] trips), but total daily travel durations were lower in Kisumu (65 [30-80] versus 116 [60-150] minutes). Walking was the most common trip mode in both cities (61% in Kisumu and 42% in Nairobi), followed by motorcycles (17%), matatus (minibuses) (11%), and cars (5%) in Kisumu; and matatus (28%), cars (12%) and buses (12%) in Nairobi. In both cities, females were less likely to make trips, and when they did, they travelled for shorter durations; people living in households with higher incomes were more likely to travel and did so for longer durations. Gender, income, occupation, and household vehicle ownership were associated differently with trip making, use of transport modes and daily travel times in cities. These findings illustrate marked differences in reported travel behaviour characteristics and correlates within the same country, indicating setting-dependent influences on travel behaviour. More sub-national data collection and harmonisation are needed to build a more nuanced understanding of patterns and drivers of travel behaviour in African cities.

Gender differences in active travel in major cities across the world

There is lack of literature on international comparison of gender differences in the use of active travel modes. We used population-representative travel surveys for 19 major cities across 13 countries and 6 continents, representing a mix of cites from low-and-middle income (n = 8) and high-income countries (n = 11). In all the cities, females are more likely than males to walk and, in most cities, more likely to use public transport. This relationship reverses in cycling, with females often less likely users than males. In high cycling cities, both genders are equally likely to cycle. Active travel to access public transport contributes 30-50% of total active travel time. The gender differences in active travel metrics are age dependent. Among children (< 16 years), these metrics are often equal for girls and boys, while gender disparity increases with age. On average, active travel enables one in every four people in the population to achieve at least 30 min of physical activity in a day, though there is large variation across the cities. In general, females are more likely to achieve this level than males. The results highlight the importance of a gendered approach towards active transport policies. Such an approach necessitates reducing road traffic danger and male violence, as well as overcoming social norms that restrict women from cycling.

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.

Active travel and paratransit use in African cities: Mixed-method systematic review and meta-ethnography

Active travel, as a key form of physical activity, can help offset noncommunicable diseases as rapidly urbanising countries undergo epidemiological transition. In Africa a human mobility transition is underway as cities sprawl and motorization rises and preserving active travel modes (walking, cycling and public transport) is important for public health. Across the continent, public transport is dominated by paratransit, privately owned informal modes serving the general public. We reviewed the literature on active travel and paratransit in African cities, published from January 2008 to January 2019. We included 19 quantitative, 14 mixed-method and 8 qualitative studies (n = 41), narratively synthesizing the quantitative data and meta-ethnographically analysing the qualitative data. Integrated findings showed that walking was high, cycling was low and paratransit was a critical mobility option for poor peripheral residents facing long livelihood-generation journeys. As an indigenous solution to dysfunctional mobility systems shaped by colonial and apartheid legacies it was an effective connector, penetrating areas unserved by formal public transport and helping break cycles of poverty. From a public health perspective, it preserved active travel by reducing mode-shifting to private vehicles. Yet many city authorities viewed it as rogue, out of keeping with the 'ideal modern city', adopting official anti-paratransit stances without necessarily considering the contribution of active travel to public health. The studies varied in quality and showed uneven geographic representation, with data from Central and Northern Africa especially sparse; notably, there was a high prevalence of non-local authors and out-of-country funding. Nevertheless, drawing together a rich cross-disciplinary set of studies spanning over a decade, the review expands the literature at the intersection of transport and health with its novel focus on paratransit as a key active travel mode in African cities. Further innovative research could improve paratransit's legibility for policymakers and practitioners, fostering its inclusion in integrated transport plans.

Impact of long-term air pollution exposure on incidence of neurodegenerative diseases: A protocol for a systematic review and exposure-response meta-analysis

BACKGROUND

Ambient air pollution is a pervasive and ubiquitous hazard, which has been linked to premature morbidity and a growing number of morbidity endpoints. Air pollution may be linked to neurodegeneration, and via this or other pathways, to neurodegenerative diseases. Emerging evidence suggests that air pollution may contribute to neurodegenerative diseases such as dementia, Parkinson's Disease (PD), Multiple Sclerosis (MS) and Motor Neuron Diseases (MND), although this evidence remains inconsistent and very limited for MS and MND. In addition, this evidence base is rapidly emerging and would benefit from a wide and critical synthesis, including a better understanding of heterogeneity.

OBJECTIVES

In this paper, we present a protocol for a systematic review and meta-analysis and specify our methods a priori. The main aim of the planned systematic review is to answer the question of whether long-term exposure (>1 year) to ambient (outdoor) air pollution (exposure, compared to lower exposure) increases the risk of adult (population) incidence of neurodegenerative diseases (outcomes) in epidemiological observational studies (study design). Another aim is to meta-analyze the associations between long-term exposure to ambient air pollutants and the risk of the selected outcomes and assess the shape of exposure-response functions. To set the stage for the proposed work, we also overview the existing epidemiological evidence in this protocol, but do not critically evaluate it, as these results will be fully presented in the planned systematic review.

SEARCH AND STUDY ELIGIBILITY

We will search the electronic databases Medline (via Ovid), Embase (via Ovid), Cochrane Library, Cinahl (via Ebscohost), Global Health (via Ebscohost), PsycINFO (via Ebscohost), Scopus, Web of Science (Core Collection), from inception to October 2022. Eligible studies must contain primary research investigating the link between 1-year + exposure to any outdoor air pollutant, from any source, and dementia, PD, MS, and MND, or dementia subtypes: Alzheimer's Disease, vascular dementia, and mixed dementia. The search strategy and eligibility criteria are pre-determined and described in full in this protocol.

STUDY APPRAISAL AND SYNTHESIS METHODS

Articles will be stored and screened using Rayyan QCRI. Title and abstract screening, full text review, data extraction, risk of bias assessment and data preparation for statistical analysis will be conducted independently by two reviewers using pre-defined forms and criteria, described in this protocol. All these steps will also be piloted and the forms and/or methods adapted if issues arise. Meta-analysis and assessment of the shape of the exposure-response functions will be conducted if four independent exposure-outcomes pairs are available, and the remainder of results will be synthesized in the forms of tables and via a narrative summary. Certainty in the body of evidence will be assessed using the OHAT approach. This protocol describes the planned analysis and synthesis a priori and serves to increase transparency and impact of this systematic review and meta-analysis.

Developing and implementing 20-mph speed limits in Edinburgh and Belfast: mixed-methods study

Background

Transport initiatives such as 20-mph (≈30-km/h) speed limits are anticipated to result in fewer road casualties and improve perceptions of safety, leading to increases in active travel. Lower speeds may also lead to more pleasant environments in which to live, work and play.

Objectives

The main objective was to evaluate and understand the processes and effects of developing and implementing 20-mph speed limits in Edinburgh and Belfast. The focus was on health-related outcomes (casualties and active travel) that may lead to public health improvements. An additional objective was to investigate the political and policy factors (conditions) that led to the decision to introduce the new speed limits.

Design

This was a mixed-methods study that comprised an outcome, process, policy and economic evaluation of two natural experiments.

Setting

The study was set in Edinburgh, Scotland, and Belfast, Northern Ireland, from 2000 to 2018.

Participants

The whole population of each city were participants, as well as stakeholders involved in implementation and decision-making processes.

Intervention

The intervention was the implementation of 20-mph legislation, signage, enforcement, and education and awareness-raising in Edinburgh (citywide) and Belfast (city centre).

Main outcome measures

The main outcomes measured were speed; number, type and severity of road collisions; perceptions; and liveability.

Data sources

The following data sources were used – routinely and locally collected quantitative data for speed, volume of traffic, casualties and collisions, and costs; documents and print media; surveys; interviews and focus groups; and Google Street View (Google Inc., Mountain View, CA, USA).

Results

Collisions and casualties – the overall percentage reduction in casualty rates was 39% (the overall percentage reduction in collision rates was 40%) in Edinburgh. The percentage reduction for each level of severity was 23% for fatal casualties, 33% for serious casualties and 37% for minor casualties. In Belfast there was a 2% reduction in casualties, reflecting differences in the size, reach and implementation of the two schemes. Perceptions – in Edinburgh there was an increase in two factors (support for 20 mph and rule-following after implementation) supported by the qualitative data. Liveability – for both cities, there was a small statistical increase in liveability. Speed – mean and median speeds reduced by 1.34 mph and 0.47 mph, respectively, at 12 months in Edinburgh, with no statistically significant changes in Belfast. History, political context, local policy goals, local priorities and leadership influenced decision-making and implementation in the two cities.

Limitations

There was no analysis of active travel outcomes because the available data were not suitable.

Conclusions

The pre-implementation period is important. It helps frame public and political attitudes. The scale of implementation and additional activities in the two cities had a bearing on the impacts. The citywide approach adopted by Edinburgh was effective in reducing speeds and positively affected a range of public health outcomes. The city-centre approach in Belfast (where speeds were already low) was less effective. However, the main outcome of these schemes was a reduction in road casualties at all levels of severity.

Future work

Future work should develop a statistical approach to public health interventions that incorporates variables from multiple outcomes. In this study, each outcome was analysed independently of each other. Furthermore, population measures of active travel that can be administered simply, inexpensively and at scale should be developed.

Study registration

This study is registered as ISRCTN10200526.

Funding

This project was funded by the National Institute for Health and Care Research (NIHR) Public Health Research programme and will be published in full in Public Health Research; Vol. 10, No. 9. See the NIHR Journals Library website for further project information.

Impacts of changes in environmental exposures and health behaviours due to the COVID-19 pandemic on cardiovascular and mental health: A comparison of Barcelona, Vienna, and Stockholm

Responses to COVID-19 altered environmental exposures and health behaviours associated with non-communicable diseases. We aimed to (1) quantify changes in nitrogen dioxide (NO₂), noise, physical activity, and greenspace visits associated with COVID-19 policies in the spring of 2020 in Barcelona (Spain), Vienna (Austria), and Stockholm (Sweden), and (2) estimated the number of additional and prevented diagnoses of myocardial infarction (MI), stroke, depression, and anxiety based on these changes. We calculated differences in NO₂, noise, physical activity, and greenspace visits between pre-pandemic (baseline) and pandemic (counterfactual) levels. With two counterfactual scenarios, we distinguished between Acute Period (March 15th - April 26th, 2020) and Deconfinement Period (May 2nd - June 30th^, 2020) assuming counterfactual scenarios were extended for 12 months. Relative risks for each exposure difference were estimated with exposure-risk functions. In the Acute Period, reductions in NO₂ (range of change from -16.9 μg/m³ to -1.1 μg/m³), noise (from -5 dB(A) to -2 dB(A)), physical activity (from -659 MET*min/wk to -183 MET*min/wk) and greenspace visits (from -20.2 h/m to 1.1 h/m) were largest in Barcelona and smallest in Stockholm. In the Deconfinement Period, NO₂ (from -13.9 μg/m³ to -3.1 μg/m³), noise (from -3 dB(A) to -1 dB(A)), and physical activity levels (from -524 MET*min/wk to -83 MET*min/wk) remained below pre-pandemic levels in all cities. Greatest impacts were caused by physical activity reductions. If physical activity levels in Barcelona remained at Acute Period levels, increases in annual diagnoses for MI (mean: 572 (95% CI: 224, 943)), stroke (585 (6, 1156)), depression (7903 (5202, 10,936)), and anxiety (16,677 (926, 27,002)) would be anticipated. To decrease cardiovascular and mental health impacts, reductions in NO₂ and noise from the first COVID-19 surge should be sustained, but without reducing physical activity. Focusing on cities' connectivity that promotes active transportation and reduces motor vehicle use assists in achieving this goal.

Physical Activity Behaviour and Comparison of GPAQ and Travel Diary Transport-Related Physical Activity in Accra, Ghana

There is a lack of data on physical activity (PA), active travel, and the comparison of measurement instruments in low-resource settings. The objective of this paper is to describe PA behaviour and the agreement of walking estimates from the Global Physical Activity Questionnaire (GPAQ) and the travel diary in a low-resource setting. We used a cross-sectional survey design to capture data from the residents of Accra (Ghana) between May 2020 and March 2021. Of the 863 participants aged 15+ years, 65% were females, and 86% reported PA. The median weekly PA was 18 (interquartile range: 5-75) metabolic equivalent of task hours, with 50% of females and 37% of males achieving low PA levels. In the GPAQ, 80% of participants reported weekly walking; the mean number of days walked was 3.8 (standard deviation (SD): 2.5); hence, 54% of participants reported walking on any day, and the mean daily walking duration was 51 (SD: 82) minutes. In the diary, 56% of participants reported walking for over 24 h, with a mean walking duration of 31 (SD: 65) minutes. The correlation of walking duration between instruments was weak (rho: 0.31; 95% Confidence Interval: 0.25-0.37); the mean bias was 20 min, with GPAQ estimates being 0.1 to 9 times higher than diary estimates. We concluded that low PA is prevalent in Accra, and while the travel diary and GPAQ estimate similar walking prevalence, their walking duration agreement is poor. We recommend accompanying PA questionnaires with objective measures for calibration.

1079 USE OF AN ADVANCE CARE PLAN CHECKLIST TO IMPROVE COMMUNICATION AND ASSESSMENT OF THE IMPACT ON HOSPITAL READMISSIONS

Introduction

Advance care planning (ACP) is a vital part of holistic and person-centred care. It allows formalising of an individual’s wishes and best interests, and avoids unnecessary or unwanted interventions including, potentially, hospital admissions. It is crucial that any decisions or recommendations are communicated to all relevant healthcare professionals to ensure peoples’ wishes are upheld. We developed this project to review and improve documentation and communication on discharge when a decision had been made to limit care to the community and avoid admission.

Method

A checklist was developed comprising 11 criteria to be documented in the discharge letter and actions to disseminate information including; updating the ReSPECT form and alerting the hospital frailty and community out of hours teams. We carried out a closed loop audit of patients where admission should be avoided and reviewed discharge letters against the criteria. Where patients were readmitted we reviewed the notes to determine whether the admission was appropriate.

Results

We compared patients discharged between February 2020–February 2021 and then from March–September 2021. 161 and 27 patients were identified respectively. Average age was 84.6 and 87.3 years respectively. In cohort 2 48.1% of patients were readmitted, up from 8.7% during the previous cycle. 33% of admissions in cohort 2 and 38.9% of readmissions in cohort 1 were deemed appropriate. Documentation improved in 10 of the 11 criteria. Average length of stay for readmissions was reduced from 16.7 to 5.7 days.

Conclusion

As evidenced by our study utilising a checklist has improved documentation and dissemination of ACPs to the Community. This did not lead to a reduction in hospital admissions but this may have been skewed by factors relating to the Covid-19 pandemic. We did find a significant reduction in length of stay for those subsequently readmitted.

Association Between Physical Activity and Risk of Depression: A Systematic Review and Meta-analysis

Importance

Depression is the leading cause of mental health-related disease burden and may be reduced by physical activity, but the dose-response relationship between activity and depression is uncertain.

Objective

To systematically review and meta-analyze the dose-response association between physical activity and incident depression from published prospective studies of adults.

Data Sources

PubMed, SCOPUS, Web of Science, PsycINFO, and the reference lists of systematic reviews retrieved by a systematic search up to December 11, 2020, with no language limits. The date of the search was November 12, 2020.

Study Selection

We included prospective cohort studies reporting physical activity at 3 or more exposure levels and risk estimates for depression with 3000 or more adults and 3 years or longer of follow-up.

Data Extraction and Synthesis

Data extraction was completed independently by 2 extractors and cross-checked for errors. A 2-stage random-effects dose-response meta-analysis was used to synthesize data. Study-specific associations were estimated using generalized least-squares regression and the pooled association was estimated by combining the study-specific coefficients using restricted maximum likelihood.

Main Outcomes and Measures

The outcome of interest was depression, including (1) presence of major depressive disorder indicated by self-report of physician diagnosis, registry data, or diagnostic interviews and (2) elevated depressive symptoms established using validated cutoffs for a depressive screening instrument.

Results

Fifteen studies comprising 191 130 participants and 2 110 588 person-years were included. An inverse curvilinear dose-response association between physical activity and depression was observed, with steeper association gradients at lower activity volumes; heterogeneity was large and significant (I2 = 74%; P < .001). Relative to adults not reporting any activity, those accumulating half the recommended volume of physical activity (4.4 marginal metabolic equivalent task hours per week [mMET-h/wk]) had 18% (95% CI, 13%-23%) lower risk of depression. Adults accumulating the recommended volume of 8.8 mMET hours per week had 25% (95% CI, 18%-32%) lower risk with diminishing potential benefits and higher uncertainty observed beyond that exposure level. There were diminishing additional potential benefits and greater uncertainty at higher volumes of physical activity. Based on an estimate of exposure prevalences among included cohorts, if less active adults had achieved the current physical activity recommendations, 11.5% (95% CI, 7.7%-15.4%) of depression cases could have been prevented.

Conclusions and Relevance

This systematic review and meta-analysis of associations between physical activity and depression suggests significant mental health benefits from being physically active, even at levels below the public health recommendations. Health practitioners should therefore encourage any increase in physical activity to improve mental health.

Exploring ways to respond to rising obesity and diabetes in the Caribbean using a system dynamics model

Diabetes and obesity present a high and increasing burden of disease in the Caribbean that have failed to respond to prevention policies and interventions. These conditions are the result of a complex system of drivers and determinants that can make it difficult to predict the impact of interventions. In partnership with stakeholders, we developed a system dynamics simulation model to map the system driving diabetes and obesity prevalence in the Caribbean using Jamaica as a test case. The study aims to use the model to assess the magnitude changes necessary in physical activity and dietary intake to achieve global targets set by the WHO Global Action plan and to test scenarios for interventions to reduce the burden of diabetes and obesity. Continuing current trends in diet, physical activity, and demographics, the model predicts diabetes in Jamaican adults (20+ years) to rise from 12% in 2018 to 15.4% in 2030 and 20.9% by 2050. For obesity, it predicts prevalence to rise from 28.6% in 2018 to 32.1% by 2030 and 39.2% by 2050. The magnitude change necessary to achieve the global targets set by the World Health Organization is so great as to be unachievable. However, a combination of measures both upstream (including reducing the consumption of sugar sweetened beverages and ultra processed foods, increasing fruit and vegetable intake, and increasing moderate-to-vigorous activity) at the population level, and downstream (targeting people at high risk and with diabetes) can significantly reduce the future burden of diabetes and obesity in the region. No single intervention reduces the prevalence of these conditions as much as a combination of interventions. Thus, the findings of this model strongly support adopting a sustained and coordinated approach across various sectors to synergistically maximise the benefits of interventions.

Impact of road traffic noise on annoyance and preventable mortality in European cities: A health impact assessment

BACKGROUND

Road traffic is the main source of environmental noise in European cities and one of the main environmental risks to health and wellbeing. In this study we aimed to provide an in-depth assessment of available road traffic noise data and to estimate population exposure and health impacts for cities in Europe.

METHODS

We conducted the analysis for 724 cities and 25 greater cities in 25 European countries. We retrieved road traffic strategic noise maps delivered under the Environmental Noise Directive (END) or available from local sources. We assessed noise exposure using the 24 h day-evening-night noise level indicator (L_den) starting at exposure levels of 55 dB L_den - based on data availability - for the adult population aged 20 and over (n = 123,966,346). For the adults exposed to noise levels above 55 dB L_den we estimated the health impacts of compliance with the World Health Organization (WHO) recommendation of 53 dB L_den. Two primary health outcomes were assessed: high noise annoyance and Ischemic Heart Disease (IHD), using mortality from IHD causes as indicator. Exposure Response Functions (ERFs) relating road traffic noise exposure to annoyance and IHD mortality were retrieved from the literature. Uncertainties in input parameters were propagated using Monte Carlo simulations to obtain point estimates and empirical 95% Confidence Intervals (CIs). Lastly, the noise maps were categorized as high, moderate and low quality following a qualitative approach.

RESULTS

Strategic noise map data was delivered in three distinct formats (i.e. raster, polygon or polyline) and had distinct noise ranges and levels of categorization. The majority of noise maps (i.e. 83.2%) were considered of moderate or low quality. Based on the data provided, almost 60 million adults were exposed to road traffic noise levels above 55 dB L_den, equating to a median of 42% (Interquartile Range (IQR): 31.8-64.8) of the adult population across the analysed cities. We estimated that approximately 11 million adults were highly annoyed by road traffic noise and that 3608 deaths from IHD (95% CI: 843-6266) could be prevented annually with compliance of the WHO recommendation. The proportion of highly annoyed adults by city had a median value of 7.6% (IQR: 5.6-11.8) across the analysed cities, while the number preventable deaths had a median of 2.2 deaths per 100,000 population (IQR: 1.4-3.1).

CONCLUSIONS

Based on the provided strategic noise maps a considerable number of adults in European cities are exposed to road traffic noise levels harmful for health. Efforts to standardize the strategic noise maps and to increase noise and disease data availability at the city level are needed. These would allow for a more accurate and comprehensive assessment of the health impacts and further help local governments to address the adverse health effects of road traffic noise.

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.

Socioeconomic and gendered inequities in travel behaviour in Africa: Mixed-method systematic review and meta-ethnography

Travel has individual, societal and planetary health implications. We explored socioeconomic and gendered differences in travel behaviour in Africa, to develop an understanding of travel-related inequity. We conducted a mixed-methods systematic review (PROSPERO CRD42019124802). In 2019, we searched MEDLINE, TRID, SCOPUS, Web of Science, LILACS, SciELO, Global Health, Africa Index Medicus, CINAHL and MediCarib for studies examining travel behaviour by socioeconomic status and gender in Africa. We appraised study quality using Critical Appraisal Skills Programme checklists. We synthesised qualitative data using meta-ethnography, followed by a narrative synthesis of quantitative data, and integrated qualitative and quantitative strands using pattern matching principles. We retrieved 103 studies (20 qualitative, 24 mixed-methods, 59 quantitative). From the meta-ethnography, we observed that travel is: intertwined with social mobility; necessary to access resources; associated with cost and safety barriers; typified by long distances and slow modes; and dictated by gendered social expectations. We also observed that: motorised transport is needed in cities; walking is an unsafe, 'captive' mode; and urban and transport planning are uncoordinated. From these observations, we derived hypothesised patterns that were tested using the quantitative data, and found support for these overall. In lower socioeconomic individuals, travel inequity entailed reliance on walking and paratransit (informal public transport), being unable to afford travel, travelling less overall, and travelling long distances in hazardous conditions. In women and girls, travel inequity entailed reliance on walking and lack of access to private vehicles, risk of personal violence, societally-imposed travel constraints, and household duties shaping travel. Limitations included lack of analytical rigour in qualitative studies and a preponderance of cross-sectional quantitative studies (offering a static view of an evolving process). Overall, we found that travel inequity in Africa perpetuates socioeconomic and gendered disadvantage. Proposed solutions focus on improving the safety, efficiency and affordability of public transport and walking.

Evaluating the citywide Edinburgh 20mph speed limit intervention effects on traffic speed and volume: A pre-post observational evaluation

OBJECTIVES

Traffic speed is important to public health as it is a major contributory factor to collision risk and casualty severity. 20mph (32km/h) speed limit interventions are an increasingly common approach to address this transport and health challenge, but a more developed evidence base is needed to understand their effects. This study describes the changes in traffic speed and traffic volume in the City of Edinburgh, pre- and 12 months post-implementation of phased city-wide 20mph speed limits from 2016-2018.

METHODS

The City of Edinburgh Council collected speed and volume data across one full week (24 hours a day) pre- and post-20mph speed limits for 66 streets. The pre- and post-speed limit intervention data were compared using measures of central tendency, dispersion, and basic t-tests. The changes were assessed at different aggregations and evaluated for statistical significance (alpha = 0.05). A mixed effects model was used to model speed reduction, in the presence of key variables such as baseline traffic speed and time of day.

RESULTS

City-wide, a statistically significant reduction in mean speed of 1.34mph (95% CI 0.95 to 1.72) was observed at 12 months post-implementation, representing a 5.7% reduction. Reductions in speed were observed throughout the day and across the week, and larger reductions in speed were observed on roads with higher initial speeds. Mean 7-day volume of traffic was found to be lower by 86 vehicles (95% CI: -112 to 286) representing a reduction of 2.4% across the city of Edinburgh (p = 0.39) but with the direction of effect uncertain.

CONCLUSIONS

The implementation of the city-wide 20mph speed limit intervention was associated with meaningful reductions in traffic speeds but not volume. The reduction observed in road traffic speed may act as a mechanism to lessen the frequency and severity of collisions and casualties, increase road safety, and improve liveability.

Analysis of Cameroon's Sectoral Policies on Physical Activity for Noncommunicable Disease Prevention

Physical inactivity is increasing in low- and middle-income countries (LMICs), where noncommunicable diseases (NCDs), urbanisation and sedentary living are rapidly growing in tandem. Increasing active living requires the participation of multiple sectors, yet it is unclear whether physical activity (PA)-relevant sectors in LMICs are prioritising PA. We investigated to what extent sectors that influence PA explicitly integrate it in their policies in an LMIC such as Cameroon. We systematically identified policy documents relevant to PA and NCD prevention in Cameroon; and using the Walt and Gilson policy triangle we described, analysed, and interpreted the policy contexts, contents, processes, and actors. We found 17 PA and NCD policy documents spanning from 1974 to 2019 across seven ministries. Thirteen (13/17) policies targeted infrastructure improvement, and four (4/17) targeted communication for behaviour change, all aiming to enhance leisure domain PA. Only the health sector explicitly acknowledged the role of PA in NCD prevention. Notably, no policy from the transport sector mentioned PA. Our findings highlight the need for intersectoral action to integrate PA into policies in all relevant sectors. These actions will need to encompass the breadth of PA domains, including transport, while emphasising the multiple health benefits of PA for the population.

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 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.

Systems science for developing policy to improve physical activity, the Caribbean

The World Health Organization (WHO) Global Action Plan on Physical Activity recommends adopting a systems approach to implementing and tailoring actions according to local contexts. We held group model-building workshops with key stakeholders in the Caribbean region to develop a causal loop diagram to describe the system driving the increasing physical inactivity in the region and envision the most effective ways of intervening in that system to encourage and promote physical activity. We used the causal loop diagram to inform how the WHO Global Action Plan on Physical Activity might be adapted to a local context. Although the WHO recommendations aligned well with our causal loop diagram, the diagram also illustrates the importance of local context in determining how interventions should be coordinated and implemented. Some interventions included creating safe physical activity spaces for both sexes, tackling negative attitudes to physical activity in certain contexts, including in schools and workplaces, and improving infrastructure for active transport. The causal loop diagram may also help understand how policies may be undermined or supported by key actors or where policies should be coordinated. We demonstrate how, in a region with a high level of physical inactivity and low resources, applying systems thinking with relevant stakeholders can help the targeted adaptation of global recommendations to local contexts.

The Built Environment and Health in Low- and Middle-Income Countries: a Review on Quantitative Health Impact Assessments

PURPOSE OF REVIEW

Features and attributes of the built environment (BE) impact positively and negatively on health, especially in cities facing unprecedented urban population growth and mass motorization. A common approach to assess the health impacts of built environment is health impact assessment (HIA), but it is rarely used in low- and middle-income countries (LMICs) where urbanization rates are fastest. This article reviews selected HIA case studies from LMICs and reports the methods and tools used to support further implementation of quantitative HIAs in cities of LMICs.

RECENT FINDINGS

In total, 24 studies were reviewed across Algeria, Brazil, China, India, Iran, Kenya, Thailand, Turkey, and Mauritius. HIAs examine specific pathways through which the built environment acts: air pollution, noise, physical activity, and traffic injury. Few HIAs of BE addressed more than one exposure pathway at a time, and most studies focused on air pollution across the sectors of transport and energy. A wide number of tools were used to conduct exposure assessment, and different models were applied to assess health impacts of different exposures. Those HIAs rely on availability of local concentration data and often use models that have set exposure-response functions (ERFs). ERFs were not adapted to local populations except for HIAs conducted in China. HIAs of BE are being successfully conducted in LMICs with a variety of tools and datasets. Scaling and expanding quantitative health impact modeling in LMICs will require further study on data availability, adapted models/tools, low technical capacity, and low policy demand for evidence from modeling studies. As case studies with successful use of evidence from modeling emerge, the uptake of health impact modeling of BE is likely to increase in favor of people and planet.

Use of natural experimental studies to evaluate 20mph speed limits in two major UK cities

INTRODUCTION

Reductions in traffic speed can potentially offer multiple health and public health benefits. In 2016, implementation of 20mph (30kph) speed limit interventions began in Edinburgh (city-wide) and Belfast (city centre). The aims of this paper are to describe 1) the broad theoretical approach and design of two natural experimental studies to evaluate the 20mph speed limits in Edinburgh and Belfast and 2) how these studies allowed us to test and explore theoretical mechanisms of 20mph speed limit interventions.

METHODS

The evaluation consisted of several work packages, each with different research foci, including the political decision-making processes that led to the schemes, their implementation processes, outcomes (including traffic speed, perceptions of safety, and casualties) and cost effectiveness. We used a combination of routinely and locally collected quantitative data and primary quantitative and qualitative data.

RESULTS

The evaluation identified many contextual factors influencing the likelihood of 20mph speed limits reaching the political agenda. There were substantial differences between the two sites in several aspects related to implementation. Reductions in speed resulted in significant reductions in collisions and casualties, particularly in Edinburgh, which had higher average speed at baseline. The monetary value of collisions and casualties prevented are likely to exceed the costs of the intervention and thus the overall balance of costs and benefits is likely to be favourable.

CONCLUSIONS

Innovative study designs, including natural experiments, are important for assessing the impact of 'real world' public health interventions. Using multiple methods, this project enabled a deeper understanding of not only the effects of the intervention but the factors that explain how and why the intervention and the effects did or did not occur. Importantly it has shown that 20mph speed limits can lead to reductions in speed, collisions and casualties, and are therefore an effective public health intervention.

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.

Effect of COVID-19 response policies on walking behavior in US cities

The COVID-19 pandemic is causing mass disruption to our daily lives. We integrate mobility data from mobile devices and area-level data to study the walking patterns of 1.62 million anonymous users in 10 metropolitan areas in the United States. The data covers the period from mid-February 2020 (pre-lockdown) to late June 2020 (easing of lockdown restrictions). We detect when users were walking, distance walked and time of the walk, and classify each walk as recreational or utilitarian. Our results reveal dramatic declines in walking, particularly utilitarian walking, while recreational walking has recovered and even surpassed pre-pandemic levels. Our findings also demonstrate important social patterns, widening existing inequalities in walking behavior. COVID-19 response measures have a larger impact on walking behavior for those from low-income areas and high use of public transportation. Provision of equal opportunities to support walking is key to opening up our society and economy.

The public health implications of the Paris Agreement: a modelling study

BACKGROUND

nationally determined contributions (NDCs) serve to meet the goals of the Paris Agreement of staying "well below 2°C", which could also yield substantial health co-benefits in the process. However, existing NDC commitments are inadequate to achieve this goal. Placing health as a key focus of the NDCs could present an opportunity to increase ambition and realise health co-benefits. We modelled scenarios to analyse the health co-benefits of NDCs for the year 2040 for nine representative countries (ie, Brazil, China, Germany, India, Indonesia, Nigeria, South Africa, the UK, and the USA) that were selected for their contribution to global greenhouse gas emissions and their global or regional influence.

METHODS

Modelling the energy, food and agriculture, and transport sectors, and mortality related to risk factors of air pollution, diet, and physical activity, we analysed the health co-benefits of existing NDCs and related policies (ie, the current pathways scenario) for 2040 in nine countries around the world. We compared these health co-benefits with two alternative scenarios, one consistent with the goal of the Paris Agreement and the Sustainable Development Goals (ie, the sustainable pathways scenario), and one in line with the sustainable pathways scenario, but also placing health as a central focus of the policies (ie, the health in all climate policies scenario).

FINDINGS

Compared with the current pathways scenario, the sustainable pathways scenario resulted in an annual reduction of 1·18 million air pollution-related deaths, 5·86 million diet-related deaths, and 1·15 million deaths due to physical inactivity, across the nine countries, by 2040. Adopting the more ambitious health in all climate policies scenario would result in a further reduction of 462 000 annual deaths attributable to air pollution, 572 000 annual deaths attributable to diet, and 943 000 annual deaths attributable to physical inactivity. These benefits were attributable to the mitigation of direct greenhouse gas emissions and the commensurate actions that reduce exposure to harmful pollutants, as well as improved diets and safe physical activity.

INTERPRETATION

A greater consideration of health in the NDCs and climate change mitigation policies has the potential to yield considerable health benefits as well as achieve the "well below 2°C" commitment across a range of regional and economic contexts.

FUNDING

This work was in part funded through an unrestricted grant from the Wellcome Trust (award number 209734/Z/17/Z) and supported by an Engineering and Physical Sciences Research Council grant (grant number EP/R035288/1).

Using satellite imagery to estimate heavy vehicle volume for ecological injury analysis in India

A major limitation of road injury research in low- and-middle income countries is the lack of consistent data across the settings, such as traffic counts, to measure traffic risk. This study presents a novel method in which traffic volume of heavy vehicles - trucks and buses - is estimated by identifying these vehicles from satellite imagery of Google Earth. For Rajasthan state in India, a total of ∼44,000 such vehicles were manually identified and geo-located on national highways (NHs), with no distinction made between trucks and buses. To estimate population living in proximity to NHs, defined as those living within 1 km buffer of NH, we geocoded ∼45,000 villages and ∼300 cities using Google Maps Geocoding Application Programming Interface (API). We fitted a spatio-temporal Bayesian regression model with the number of road deaths at the district level as the outcome variable. We found a strong Pearson correlation of 0.84 (p < 0.001) between Google Earth estimates of heavy vehicles and freight vehicle counts reported by a national-level study for different road sections. The regression results show that the volume of heavy vehicles and rural population in proximity to highways are positively associated with fatality risk in the districts. These effects have been estimated after controlling for other modes of travel.

Guidelines for Modeling and Reporting Health Effects of Climate Change Mitigation Actions

BACKGROUND

Modeling suggests that climate change mitigation actions can have substantial human health benefits that accrue quickly and locally. Documenting the benefits can help drive more ambitious and health-protective climate change mitigation actions; however, documenting the adverse health effects can help to avoid them. Estimating the health effects of mitigation (HEM) actions can help policy makers prioritize investments based not only on mitigation potential but also on expected health benefits. To date, however, the wide range of incompatible approaches taken to developing and reporting HEM estimates has limited their comparability and usefulness to policymakers.

OBJECTIVE

The objective of this effort was to generate guidance for modeling studies on scoping, estimating, and reporting population health effects from climate change mitigation actions.

METHODS

An expert panel of HEM researchers was recruited to participate in developing guidance for conducting HEM studies. The primary literature and a synthesis of HEM studies were provided to the panel. Panel members then participated in a modified Delphi exercise to identify areas of consensus regarding HEM estimation. Finally, the panel met to review and discuss consensus findings, resolve remaining differences, and generate guidance regarding conducting HEM studies.

RESULTS

The panel generated a checklist of recommendations regarding stakeholder engagement: HEM modeling, including model structure, scope and scale, demographics, time horizons, counterfactuals, health response functions, and metrics; parameterization and reporting; approaches to uncertainty and sensitivity analysis; accounting for policy uptake; and discounting.

DISCUSSION

This checklist provides guidance for conducting and reporting HEM estimates to make them more comparable and useful for policymakers. Harmonization of HEM estimates has the potential to lead to advances in and improved synthesis of policy-relevant research that can inform evidence-based decision making and practice. https://doi.org/10.1289/EHP6745.

The global diet and activity research (GDAR) network: a global public health partnership to address upstream NCD risk factors in urban low and middle-income contexts

BACKGROUND

Non-communicable diseases (NCDs) are the leading cause of death globally. While upstream approaches to tackle NCD risk factors of poor quality diets and physical inactivity have been trialled in high income countries (HICs), there is little evidence from low and middle-income countries (LMICs) that bear a disproportionate NCD burden. Sub-Saharan Africa and the Caribbean are therefore the focus regions for a novel global health partnership to address upstream determinants of NCDs.

PARTNERSHIP

The Global Diet and Activity research Network (GDAR Network) was formed in July 2017 with funding from the UK National Institute for Health Research (NIHR) Global Health Research Units and Groups Programme. We describe the GDAR Network as a case example and a potential model for research generation and capacity strengthening for others committed to addressing the upstream determinants of NCDs in LMICs. We highlight the dual equity targets of research generation and capacity strengthening in the description of the four work packages. The work packages focus on learning from the past through identifying evidence and policy gaps and priorities, understanding the present through adolescent lived experiences of healthy eating and physical activity, and co-designing future interventions with non-academic stakeholders.

CONCLUSION

We present five lessons learned to date from the GDAR Network activities that can benefit other global health research partnerships. We close with a summary of the GDAR Network contribution to cultivating sustainable capacity strengthening and cutting-edge policy-relevant research as a beacon to exemplify the need for such collaborative groups.

Implications of COVID-19 control measures for diet and physical activity, and lessons for addressing other pandemics facing rapidly urbanising countries

At the time of writing, it is unclear how the COVID-19 pandemic will play out in rapidly urbanising regions of the world. In these regions, the realities of large overcrowded informal settlements, a high burden of infectious and non-communicable diseases, as well as malnutrition and precarity of livelihoods, have raised added concerns about the potential impact of the COVID-19 pandemic in these contexts. COVID-19 infection control measures have been shown to have some effects in slowing down the progress of the pandemic, effectively buying time to prepare the healthcare system. However, there has been less of a focus on the indirect impacts of these measures on health behaviours and the consequent health risks, particularly in the most vulnerable. In this current debate piece, focusing on two of the four risk factors that contribute to >80% of the NCD burden, we consider the possible ways that the restrictions put in place to control the pandemic, have the potential to impact on dietary and physical activity behaviours and their determinants. By considering mitigation responses implemented by governments in several LMIC cities, we identify key lessons that highlight the potential of economic, political, food and built environment sectors, mobilised during the pandemic, to retain health as a priority beyond the context of pandemic response. Such whole-of society approaches are feasible and necessary to support equitable healthy eating and active living required to address other epidemics and to lower the baseline need for healthcare in the long term.

Estimating traffic contribution to particulate matter concentration in urban areas using a multilevel Bayesian meta-regression approach

Quantifying traffic contribution to air pollution in urban settings is required to inform traffic management strategies and environmental policies that aim at improving air quality. Assessments and comparative analyses across multiple urban areas are challenged by the lack of datasets and methods available for global applications. In this study, we quantify the traffic contribution to particulate matter concentration in multiple cities worldwide by synthesising 155 previous studies reported in the World Health Organization (WHO)'s air pollution source apportionment data for PM10 and PM2.5. We employed a Bayesian multilevel meta-regression that accounts for uncertainties and captures both within- and between-study variations (in estimation methods, study protocols, etc.) through study-specific and location-specific explanatory variables. The final sample analysed in this paper covers 169 cities worldwide. Based on our analysis, traffic contribution to air pollution (particulate matter) varies from 5% to 61% in cities worldwide, with an average of 27%. We found that variability in the traffic contribution estimates reported worldwide can be explained by the region of study, publication year, PM size fraction, and population. Specifically, traffic contribution to air pollution in cities located in Europe, North America, or Oceania is on average 36% lower relative to the rest of the world. Traffic contribution is 28% lower among studies published after 2005 than those published on or before 2005. Traffic contribution is on average 24% lower among cities with less than 500,000 inhabitants and 19% higher when estimated based on PM10 relative to PM2.5. This quantitative summary overcomes challenges in the data and provides useful information for health impact modellers and decision-makers to assess impacts of traffic reduction policies.

The long-term impact of restricting cycling and walking during high air pollution days on all-cause mortality: Health impact Assessment study

Regular active commuting, such as cycling and walking to and from the workplace, is associated with lower all-cause mortality through increased physical activity (PA). However, active commuting may increase intake of fine particles (PM_2.5), causing negative health effects. The purpose of this study is to estimate the combined risk of PA and air pollution for all-cause mortality among active commuters who, on days with high PM_2.5 levels, switch to commuting by public transportation or work from home. Towards this purpose, we developed a Health Impact Assessment model for six cities (Helsinki, London, Sao Paulo, Warsaw, Beijing, New Delhi) using daily, city-specific PM_2.5 concentrations. For each city we estimated combined Relative Risk (RR) due to all-cause mortality for the PA benefits and PM_2.5 risks with different thresholds concentrations. Everyday cycling to work resulted in annual all-cause mortality risk reductions ranging from 28 averted deaths per 1000 cyclists (95% confidence interval (CI): 20-38) in Sao Paolo to 12 averted deaths per 1000 cyclists (95% CI: 5-19) in Beijing. Similarly, for everyday walking, the reductions in annual all-cause mortality ranged from 23 averted deaths per 1000 pedestrians (95 CI: 16-31) in Sao Paolo to 10 averted deaths per 1000 pedestrians (95%CI: 5-16) in Beijing. Restricting active commuting during days with PM_2.5 levels above specific air quality thresholds would not decrease all-cause mortality risk in any examined city. On the contrary, all-cause mortality risk would increase if walking and cycling are restricted in days with PM_2.5 concentrations below 150 μg/m³ in highly polluted cities (Beijing, New Delhi). In all six cities, everyday active commuting reduced all-cause mortality when benefits of PA and risk or air pollution were combined. Switching to working from home or using public transport on days with high air pollution is not expected to lead to improved all-cause mortality risks.

Driving status, travel modes and accelerometer-assessed physical activity in younger, middle-aged and older adults: a prospective study of 90 810 UK Biobank participants

Background

Associations between driving and physical-activity (PA) intensities are unclear, particularly among older adults. We estimated prospective associations of travel modes with total PA, sedentary time (ST), light-intensity PA (LPA), and moderate-to-vigorous intensity PA (MVPA) among adults aged 39–70 years.

Methods

We studied 90 810 UK Biobank participants (56.1 ± 7.8 years). Driving status, specific travel modes (non-work travel; commuting to/from work) and covariates were assessed by questionnaire (2006–10). PA was assessed over 7 days by wrist-worn accelerometers (2013–15). We estimated associations using overall and age-stratified multivariable linear-regression models.

Results

Drivers accumulated 1.4% more total PA (95% confidence interval: 0.9, 1.9), 11.2 min/day less ST (–12.9, –9.5), 12.2 min/day more LPA (11.0, 13.3) and 0.9 min/day less MVPA (–1.6, –0.2) than non-drivers. Compared with car/motor-vehicle users, cyclists and walkers had the most optimal activity profiles followed by mixed-mode users (e.g. for non-work travel, cyclists: 10.7% more total PA, 9.0, 12.4; 20.5 min/day less ST, –26.0, –15.0; 14.5 min/day more MVPA, 12.0, 17.2; walkers: 4.2% more total PA, 3.5, 5.0; 7.5 min/day less ST –10.2, –4.9; 10.1 min/day more MVPA, 8.9, 11.3; mixed-mode users: 2.3% more total PA, 1.9, 2.7; 3.4 min/day less ST –4.8, –2.1; 4.9 min/day more MVPA, 4.3, 5.5). Some associations varied by age (p interaction < 0.05), but these differences appeared small.

Conclusions

Assessing specific travel modes rather than driving status alone may better capture variations in activity. Walking, cycling and, to a lesser degree, mixed-mode use are associated with more optimal activity profiles in adults of all ages.

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.

Health benefits of policies to reduce carbon emissions

James Milner and colleagues argue that carefully considered policies to lower carbon emissions can also improve health, and we should use these benefits to push for strong climate action

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.

Assessing the exposure-response relationship of sleep disturbance and vibration in field and laboratory settings

Exposure to nocturnal freight train vibrations may impact sleep, but exposure-response relationships are lacking. The European project CargoVibes evaluated sleep disturbance both in the field and in the laboratory and provides unique data, as measures of response and exposure metrics are comparable. This paper therefore provides data on exposure-response relationships of vibration and sleep disturbance and compares the relationships evaluated in the laboratory and the field. Two field studies (one in Poland and one in the Netherlands) with 233 valid respondents in total, and three laboratory studies in Sweden with a total of 59 subjects over 350 person-nights were performed. The odds ratios (OR) of sleep disturbance were analyzed in relation to nighttime vibration exposure by ordinal logit regression, adjusting for moderating factors common for the studies. Outcome specific fractions were calculated for eleven sleep outcomes and supported comparability between the field and laboratory settings. Vibration exposure was significantly associated with sleep disturbance, OR = 3.51 (95% confidence interval 2.6-4.73) denoting a three and a half times increase in the odds of sleep disturbance with one unit increased 8 h nighttime log10 Root Mean Square vibration. The results suggest no significant difference between field and laboratory settings OR = 1.37 (0.59-3.19). However, odds of sleep disturbance were higher in the Netherlands as compared to Sweden, indicating unexplained differences between study populations or countries, possibly related to cultural and contextual differences and uncertainties in exposure assessments. Future studies should be carefully designed to record explanatory factors in the field and enhance ecological validity in the laboratory. Nevertheless, the presented combined data set provides a first set of exposure response relationships for vibration-induced sleep disturbance, which are useful when considering public health outcomes among exposed populations.

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.

Development of the Impacts of Cycling Tool (ICT): A modelling study and web tool for evaluating health and environmental impacts of cycling uptake

BACKGROUND

A modal shift to cycling has the potential to reduce greenhouse gas emissions and provide health co-benefits. Methods, models, and tools are needed to estimate the potential for cycling uptake and communicate to policy makers the range of impacts this would have.

METHODS AND FINDINGS

The Impacts of Cycling Tool (ICT) is an open source model with a web interface for visualising travel patterns and comparing the impacts of different scenarios of cycling uptake. It is currently applied to England. The ICT allows users to visualise individual and trip-level data from the English National Travel Survey (NTS), 2004-2014 sample, 132,000 adults. It models scenarios in which there is an increase in the proportion of the population who cycle regularly, using a distance-based propensity approach to model which trips would be cycled. From this, the model estimates likely impact on travel patterns, health, and greenhouse gas emissions. Estimates of nonoccupational physical activity are generated by fusing the NTS with the English Active People Survey (APS, 2013-2014, 559,515 adults) to create a synthetic population. Under 'equity' scenarios, we investigate what would happen if cycling levels increased equally among all age and gender categories, as opposed to in proportion to the profile of current cyclists. Under electric assist bike (pedelecs or 'e-bike') scenarios, the probability of cycling longer trips increases, based on the e-bike data from the Netherlands, 2013-2014 Dutch Travel Survey (50,868 adults).Outcomes are presented across domains including transport (trip duration and trips by mode), health (physical activity levels, years of life lost), and car transport-related CO2 emissions. Results can be visualised for the whole population and various subpopulations (region, age, gender, and ethnicity). The tool is available at www.pct.bike/ict. If the proportion of the English population who cycle regularly increased from 4.8% to 25%, then there would be notable reductions in car miles and passenger related CO2 emissions (2.2%) and health benefits (2.1% reduction in years of life lost due to premature mortality). If the new cyclists had access to e-bikes, then mortality reductions would be similar, while the reduction in car miles and CO2 emissions would be larger (2.7%). If take-up of cycling occurred equally by gender and age (under 80 years), then health benefits would be marginally greater (2.2%) but reduction in CO2 slightly smaller (1.8%). The study is limited by the quality and comparability of the input data (including reliance on self-report behaviours). As with all modelling studies, many assumptions are required and potentially important pathways excluded (e.g. injury, air pollution, and noise pollution).

CONCLUSION

This study demonstrates a generalisable approach for using travel survey data to model scenarios of cycling uptake that can be applied to a wide range of settings. The use of individual-level data allows investigation of a wide range of outcomes, and variation across subgroups. Future work should investigate the sensitivity of results to assumptions and omissions, and if this varies across setting.

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.

Sedentary behaviour and risk of all-cause, cardiovascular and cancer mortality, and incident type 2 diabetes: a systematic review and dose response meta-analysis

PURPOSE

 To estimate the strength and shape of the dose-response relationship between sedentary behaviour and all-cause, cardiovascular disease (CVD) and cancer mortality, and incident type 2 diabetes (T2D), adjusted for physical activity (PA). Data Sources: Pubmed, Web of Knowledge, Medline, Embase, Cochrane Library and Google Scholar (through September-2016); reference lists. Study Selection: Prospective studies reporting associations between total daily sedentary time or TV viewing time, and ≥ one outcome of interest. Data Extraction: Two independent reviewers extracted data, study quality was assessed; corresponding authors were approached where needed. Data Synthesis: Thirty-four studies (1,331,468 unique participants; good study quality) covering 8 exposure-outcome combinations were included. For total sedentary behaviour, the PA-adjusted relationship was non-linear for all-cause mortality (RR per 1 h/day: were 1.01 (1.00-1.01) ≤ 8 h/day; 1.04 (1.03-1.05) > 8 h/day of exposure), and for CVD mortality (1.01 (0.99-1.02) ≤ 6 h/day; 1.04 (1.03-1.04) > 6 h/day). The association was linear (1.01 (1.00-1.01)) with T2D and non-significant with cancer mortality. Stronger PA-adjusted associations were found for TV viewing (h/day); non-linear for all-cause mortality (1.03 (1.01-1.04) ≤ 3.5 h/day; 1.06 (1.05-1.08) > 3.5 h/day) and for CVD mortality (1.02 (0.99-1.04) ≤ 4 h/day; 1.08 (1.05-1.12) > 4 h/day). Associations with cancer mortality (1.03 (1.02-1.04)) and T2D were linear (1.09 (1.07-1.12)).

CONCLUSIONS

 Independent of PA, total sitting and TV viewing time are associated with greater risk for several major chronic disease outcomes. For all-cause and CVD mortality, a threshold of 6-8 h/day of total sitting and 3-4 h/day of TV viewing was identified, above which the risk is increased.

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.

Understanding bicycling in cities using system dynamics modelling

BACKGROUND

Increasing urban bicycling has established net benefits for human and environmental health. Questions remain about which policies are needed and in what order, to achieve an increase in cycling while avoiding negative consequences. Novel ways of considering cycling policy are needed, bringing together expertise across policy, community and research to develop a shared understanding of the dynamically complex cycling system. In this paper we use a collaborative learning process to develop a dynamic causal model of urban cycling to develop consensus about the nature and order of policies needed in different cycling contexts to optimise outcomes.

METHODS

We used participatory system dynamics modelling to develop causal loop diagrams (CLDs) of cycling in three contrasting contexts: Auckland, London and Nijmegen. We combined qualitative interviews and workshops to develop the CLDs. We used the three CLDs to compare and contrast influences on cycling at different points on a "cycling trajectory" and drew out policy insights.

RESULTS

The three CLDs consisted of feedback loops dynamically influencing cycling, with significant overlap between the three diagrams. Common reinforcing patterns emerged: growing numbers of people cycling lifts political will to improve the environment; cycling safety in numbers drives further growth; and more cycling can lead to normalisation across the population. By contrast, limits to growth varied as cycling increases. In Auckland and London, real and perceived danger was considered the main limit, with added barriers to normalisation in London. Cycling congestion and "market saturation" were important in the Netherlands.

CONCLUSIONS

A generalisable, dynamic causal theory for urban cycling enables a more ordered set of policy recommendations for different cities on a cycling trajectory. Participation meant the collective knowledge of cycling stakeholders was represented and triangulated with research evidence. Extending this research to further cities, especially in low-middle income countries, would enhance generalizability of the CLDs.

Health impact modelling of different travel patterns on physical activity, air pollution and road injuries for São Paulo, Brazil

BACKGROUND

São Paulo city, Brazil, faces challenges caused by rapid urbanization. We illustrate how future travel patterns could lead to different health consequences in the city.

METHODS

We evaluated the health impacts of different travel pattern scenarios for the São Paulo adult population by comparing the travel patterns of São Paulo in 2012 with counterfactual scenarios in which the city adopted travel patterns of i) those living in the city's expanded centre; ii) London (2012); iii) a highly motorized São Paulo (SP California); and iv) a visionary São Paulo (SP 2040), with high levels of walking and cycling and low levels of car and motorcycle use. For each scenario we estimated changes in exposure to air pollution, road injury risk, and physical activity. Health outcomes were estimated using disability adjusted life years (DALYs) and premature deaths averted. Sensitivity analyses were performed to identify the main sources of uncertainty.

RESULTS

We found considerable health gains in the SP 2040 scenario (total 63.6k DALYs avoided), with 4.7% of premature deaths from ischemic heart disease avoided from increases in physical activity alone. Conversely, we found substantial health losses in the scenario favouring private transport (SP California, total increase of 54.9k DALYs), with an increase in road traffic deaths and injuries among pedestrians and motorized vehicles. Parameters related to air pollution had the largest impact on uncertainty.

CONCLUSIONS

Shifting travel patterns towards more sustainable transport can provide major health benefits in São Paulo. Reducing the uncertainties in the findings should be a priority for empirical and modelling research on the health impacts of such shifts.

A shift from motorised travel to active transport: What are the potential health gains for an Australian city?

INTRODUCTION

An alarmingly high proportion of the Australian adult population does not meet national physical activity guidelines (57%). This is concerning because physical inactivity is a risk factor for several chronic diseases. In recent years, an increasing emphasis has been placed on the potential for transport and urban planning to contribute to increased physical activity via greater uptake of active transport (walking, cycling and public transport). In this study, we aimed to estimate the potential health gains and savings in health care costs of an Australian city achieving its stated travel targets for the use of active transport.

METHODS

Additional active transport time was estimated for the hypothetical scenario of Brisbane (1.1 million population 2013) in Australia achieving specified travel targets. A multi-state life table model was used to estimate the number of health-adjusted life years, life-years, changes in the burden of diseases and injuries, and the health care costs associated with changes in physical activity, fine particle (<2.5 μm; PM2.5) exposure, and road trauma attributable to a shift from motorised travel to active transport. Sensitivity analyses were conducted to test alternative modelling assumptions.

RESULTS

Over the life course of the Brisbane adult population in 2013 (860,000 persons), 33,000 health-adjusted life years could be gained if the travel targets were achieved by 2026. This was mainly due to lower risks of physical inactivity-related diseases, with life course reductions in prevalence and mortality risk in the range of 1.5%-6.0%. Prevalence and mortality of respiratory diseases increased slightly (≥0.27%) due to increased exposure of larger numbers of cyclists and pedestrians to fine particles. The burden of road trauma increased by 30% for mortality and 7% for years lived with disability. We calculated substantial net savings ($AU183 million, 2013 values) in health care costs.

CONCLUSION

In cities, such as Brisbane, where over 80% of trips are made by private cars, shifts towards walking, cycling and public transport would cause substantial net health benefits and savings in health care costs. However, for such shifts to occur, investments are needed to ensure safe and convenient travel.

Health and greenhouse gas mitigation benefits of ambitious expansion of cycling, walking, and transit in California

The purpose of this research was to quantify health co-benefits and carbon reductions of preferred scenarios of California regional transportation plans and alternatives with ambitious levels of active transport. The alternatives were designed to examine the efficacy of independent contributions of walking, bicycling, and transit at levels consistent with the U.S. Surgeon General recommendation for physical activity. Using data from travel and health surveys, vital statistics, collision databases, and outputs from regional and statewide travel models, the Integrated Transport and Health Impacts Model estimated the change in the population disease burden, as measured by deaths and disability adjusted life years (DALYs), due to a shift from a 2010 baseline travel pattern to an alternative. Health pathways modeled were physical activity and road traffic injuries. The preferred scenarios increased statewide active transport from 40.5 to 53.4 min person-1 w-1, which was associated with an annual decrease of 909 deaths and 16,089 DALYs. Sensitivity analyses that accounted for 2040 projected age- and sex-specific population characteristics and cause-specific mortality rates did not appreciably alter the annual change in deaths and DALYs on a population basis. The ambitious, maximal alternatives increased population mean travel duration to 283 min person-1 w-1 for walking, bicycling, or transit and were associated a reduction in deaths and DALYs from 2.5 to 12 times greater than the California preferred scenarios. The alternative with the largest health impact was bicycling 283 min person-1 w-1 which led to 8,543 fewer annual deaths and 194,003 fewer DALYs, despite an increase in bicyclist injuries. With anticipated population growth, no alternative achieved decreases in carbon emissions but bicycling had the greatest potential for slowing their growth. Alternatives that included transit similarly reduced carbon emissions, but with less health benefit. Aggressive expansion of active transport is an efficacious, but underutilized policy option with significant health co-benefits for mitigating greenhouse gases.