Global Effect Factors for Exposure to Fine Particulate Matter.

We evaluate fine particulate matter (PM2.5) exposure-response models to propose a consistent set of global effect factors for product and policy assessments across spatial scales and across urban and rural environments. Relationships among exposure concentrations and PM2.5-attributable health effects largely depend on location, population density, and mortality rates. Existing effect factors build mostly on an essentially linear exposure-response function with coefficients from the American Cancer Society study. In contrast, the Global Burden of Disease analysis offers a nonlinear integrated exposure-response (IER) model with coefficients derived from numerous epidemiological studies covering a wide range of exposure concentrations. We explore the IER, additionally provide a simplified regression as a function of PM2.5 level, mortality rates, and severity, and compare results with effect factors derived from the recently published global exposure mortality model (GEMM). Uncertainty in effect factors is dominated by the exposure-response shape, background mortality, and geographic variability. Our central IER-based effect factor estimates for different regions do not differ substantially from previous estimates. However, IER estimates exhibit significant variability between locations as well as between urban and rural environments, driven primarily by variability in PM2.5 concentrations and mortality rates. Using the IER as the basis for effect factors presents a consistent picture of global PM2.5-related effects for use in product and policy assessment frameworks.

Impact of ambient air pollution on physical activity and sedentary behavior in China: A systematic review.

This study systematically reviewed scientific evidence linking ambient air pollution to physical activity and sedentary behavior in China. A keyword and reference search was conducted in PubMed, Web of Science, and the Cochrane Library. Predetermined selection criteria included-study designs: interventions or experiments, retrospective or prospective cohort studies, cross-sectional studies, and case-control studies; subjects: people of all ages; exposures: specific air pollutants and/or overall air quality; outcomes: physical activity and/or sedentary behavior; and country/area: mainland China. Ten studies met the selection criteria and were included in the review. Six adopted a cross-sectional design and the remaining four adopted a prospective cohort design. Four studies assessed a specific air pollutant namely particulate matter with diameter <2.5 µg/m3 (PM2.5), whereas the remaining six focused on overall air quality, defined using air quality indexes. Decline in overall air quality and increase in PM2.5 concentration were found to be associated with reduced daily/weekly duration of outdoor leisure-time and/or transportation-related physical activity such as walking but increased duration of daytime/nighttime sleeping among Chinese residents. In contrast, evidence linking overall air quality and PM2.5 concentration to sedentary behavior remains mixed and inconclusive. In conclusion, preliminary evidence indicates that ambient air pollution impacts Chinese residents' daily physical activity-related behaviors. Future studies adopting objective measures of physical activity and a longitudinal or experimental study design are warranted to examine the impact of air pollution on sensitive sub-populations such as children, older adults and people with pre-existing conditions, and in locations outside China.

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.

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.

Cycling in Warsaw, Poland - Perceived enablers and barriers according to cyclists and non-cyclists.

Cycling in urban environments provides many benefits to people. However, planning of cycling infrastructures in large cities faces numerous challenges and requires better understanding of both the factors enabling cycling as well as barriers to it, determined by particular local context. While there is a growing body of research that tackle the bike transport related questions in Western Europe and the USA, there is relatively little research on that in Central Eastern Europe (CEE), in post-communist countries. In this study we used qualitative and quantitative methods to explore urban cyclists and non-cyclists opinions about the cycling, the perceived problems and obstacles, and perception of the on-going changes in bicycle transportation system in Warsaw, Poland. Although many people see potential advantages of cycling, it is mostly perceived as a leisure time activity. Those who do utilitarian cycling are more acutely aware of the benefits, such as rapidity and flexibility of this mean of transport. The main perceived barriers are linked to lack of good cycling infrastructure in the city, the feeling of insecurity linked to the behaviour of drivers, and to maintenance during winter. In conclusion, our research highlights both the opportunities and challenges linked to the development of improved cycle transportation system, suggesting the need for a range of policies, from the infrastructure improvements and comprehensive planning of the whole transportation system, to improving the driving culture that would support feeling of security of the cyclists.

The modelled impact of increases in physical activity: the effect of both increased survival and reduced incidence of disease.

Physical activity can affect 'need' for healthcare both by reducing the incidence rate of some diseases and by increasing longevity (increasing the time lived at older ages when disease incidence is higher). However, it is common to consider only the first effect, which may overestimate any reduction in need for healthcare. We developed a hybrid micro-simulation lifetable model, which made allowance for both changes in longevity and risk of disease incidence, to estimate the effects of increases in physical activity (all adults meeting guidelines) on measures of healthcare need for diseases for which physical activity is protective. These were compared with estimates made using comparative risk assessment (CRA) methods, which assumed that longevity was fixed. Using the lifetable model, life expectancy increased by 95 days (95% uncertainty intervals: 68-126 days). Estimates of the healthcare need tended to decrease, but the magnitude of the decreases were noticeably smaller than those estimated using CRA methods (e.g. dementia: change in person-years, -0.6%, 95% uncertainty interval -3.7% to +1.6%; change in incident cases, -0.4%, -3.6% to +1.9%; change in person-years (CRA methods), -4.0%, -7.4% to -1.6%). The pattern of results persisted under different scenarios and sensitivity analyses. For most diseases for which physical activity is protective, increases in physical activity are associated with decreases in indices of healthcare need. However, disease onset may be delayed or time lived with disease may increase, such that the decreases in need may be relatively small and less than is sometimes expected.

Can air pollution negate the health benefits of cycling and walking?

Active travel (cycling, walking) is beneficial for the health due to increased physical activity (PA). However, active travel may increase the intake of air pollution, leading to negative health consequences. We examined the risk-benefit balance between active travel related PA and exposure to air pollution across a range of air pollution and PA scenarios. The health effects of active travel and air pollution were estimated through changes in all-cause mortality for different levels of active travel and air pollution. Air pollution exposure was estimated through changes in background concentrations of fine particulate matter (PM2.5), ranging from 5 to 200µg/m3. For active travel exposure, we estimated cycling and walking from 0 up to 16h per day, respectively. These refer to long-term average levels of active travel and PM2.5 exposure. For the global average urban background PM2.5 concentration (22µg/m3) benefits of PA by far outweigh risks from air pollution even under the most extreme levels of active travel. In areas with PM2.5 concentrations of 100µg/m3, harms would exceed benefits after 1h 30min of cycling per day or more than 10h of walking per day. If the counterfactual was driving, rather than staying at home, the benefits of PA would exceed harms from air pollution up to 3h 30min of cycling per day. The results were sensitive to dose-response function (DRF) assumptions for PM2.5 and PA. PA benefits of active travel outweighed the harm caused by air pollution in all but the most extreme air pollution concentrations.

Contrasts in active transport behaviour across four countries: how do they translate into public health benefits?

OBJECTIVE: Countries and regions vary substantially in transport related physical activity that people gain from walking and cycling and in how this varies by age and gender. This study aims to quantify the population health impacts of differences between four settings. METHOD: The Integrated Transport and Health Model (ITHIM) was used to estimate health impacts from changes to physical activity that would arise if adults in urban areas in England and Wales adopted travel patterns of Switzerland, the Netherlands, and California. The model was parameterised with data from travel surveys from each setting and estimated using Monte Carlo simulation. Two types of scenarios were created, one in which the total travel time budget was assumed to be fixed and one where total travel times varied. RESULTS: Substantial population health benefits would accrue if people in England and Wales gained as much transport related physical activity as people in Switzerland or the Netherlands, whilst smaller but still considerable harms would occur if active travel fell to the level seen in California. The benefits from achieving the travel patterns of the high cycling Netherlands or high walking Switzerland were similar. CONCLUSION: Differences between high income countries in how people travel have important implications for population health.

Severity of injuries in different modes of transport, expressed with disability-adjusted life years (DALYs).

BACKGROUND: Health impact assessment (HIA) studies are increasingly predicting the health effects of mode shifts in traffic. The challenge for such studies is to combine the health effects, caused by injuries, with the disease driven health effects, and to express the change in the health with a common health indicator. Disability-adjusted life year (DALY) combines years lived disabled or injured (YLD) and years of life lost (YLL) providing practical indicator to combine injuries with diseases. In this study, we estimate the average YLDs for one person injured in a transport crash to allow easy to use methods to predict health effects of transport injuries. METHODS: We calculated YLDs and YLLs for transport fatalities and injuries based on the data from the Swedish Traffic Accident Data Acquisition (STRADA). In STRADA, all the fatalities and most of the injuries in Sweden for 2007-2011 were recorded. The type of injury was recorded with the Abbreviated Injury Scale (AIS) codes. In this study these AIS codes were aggregated to injury types, and YLDs were calculated for each victim by multiplying the type of injury with the disability weight and the average duration of that injury. YLLs were calculated by multiplying the age of the victim with life expectancy of that age and gender. YLDs and YLLs were estimated separately for different gender, mode of transport and location of the crash. RESULTS: The average YLDs for injured person was 14.7 for lifelong injuries and 0.012 for temporal injuries. The average YLDs per injured person for lifelong injuries for pedestrians, cyclists and car occupants were 9.4, 12.8 and 18.4, YLDs, respectively. Lifelong injuries sustained in rural areas were on average 31% more serious than injuries in urban areas. CONCLUSIONS: The results show that shifting modes of transport will not only change the likelihood of injuries but also the severity of injuries sustained, if injured. The results of this study can be used to predict DALY changes in HIA studies that take into account mode shifts between different transport modes, and in other studies predicting the health effects of traffic injuries.

Intake fraction variability between air pollution emission sources inside an urban area.

The cost-effective mitigation of adverse health effects caused by air pollution requires information on the contribution of different emission sources to exposure. In urban areas the exposure potential of different sources may vary significantly depending on emission height, population density, and other factors. In this study, we quantified this intraurban variability by predicting intake fraction (iF) for 3,066 emission sources in Warsaw, Poland. iF describes the fraction of the pollutant that is inhaled by people in the study area. We considered the following seven pollutants: particulate matter (PM), nitrogen oxides (NOx), sulfur dioxide (SO2), benzo[a] pyrene (BaP), nickel (Ni), cadmium (Cd), and lead (Pb). Emissions for these pollutants were grouped into four emission source categories (Mobile, Area, High Point, and Other Point sources). The dispersion of the pollutants was predicted with the CALPUFF dispersion model using the year 2005 emission rate data and meteorological records. The resulting annual average concentrations were combined with population data to predict the contribution of each individual source to population exposure. The iFs for different pollutant-source category combinations varied between 51 per million (PM from Mobile sources) and 0.013 per million (sulfate PM from High Point sources). The intraurban iF variability for Mobile sources primary PM emission was from 4 per million to 100 per million with the emission-weighted iF of 44 per million. These results propose that exposure due to intraurban air pollution emissions could be decreased more effectively by specifically targeting sources with high exposure potency rather than all sources.

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.

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.

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.

Air pollution, physical activity and health: A mapping review of the evidence.

BACKGROUND: Exposure to air pollution and physical inactivity are both significant risk factors for non-communicable diseases (NCDs). These risk factors are also linked so that the change in exposure in one will impact risks and benefits of the other. These links are well captured in the active transport (walking, cycling) health impact models, in which the increases in active transport leading to increased inhaled dose of air pollution. However, these links are more complex and go beyond the active transport research field. Hence, in this study, we aimed to summarize the empirical evidence on the links between air pollution and physical activity, and their combined effect on individual and population health. OBJECTIVES AND METHODS: We conducted a non-systematic mapping review of empirical and modelling evidence of the possible links between exposure to air pollution and physical activity published until Autumn 2019. We reviewed empirical evidence for the (i) impact of exposure to air pollution on physical activity behaviour, (ii) exposure to air pollution while engaged in physical activity and (iii) the short-term and (iv) long-term health effects of air pollution exposure on people engaged in physical activity. In addition, we reviewed (v) public health modelling studies that have quantified the combined effect of air pollution and physical activity. These broad research areas were identified through expert discussions, including two public events performed in health-related conferences. RESULTS AND DISCUSSION: The current literature suggests that air pollution may decrease physical activity levels during high air pollution episodes or may prevent people from engaging in physical activity overall in highly polluted environments. Several studies have estimated fine particulate matter (PM2.5) exposure in active transport environment in Europe and North-America, but the concentration in other regions, places for physical activity and for other air pollutants are poorly understood. Observational epidemiological studies provide some evidence for a possible interaction between air pollution and physical activity for acute health outcomes, while results for long-term effects are mixed with several studies suggesting small diminishing health gains from physical activity due to exposure to air pollution for long-term outcomes. Public health modelling studies have estimated that in most situations benefits of physical activity outweigh the risks of air pollution, at least in the active transport environment. However, overall evidence on all examined links is weak for low- and middle-income countries, for sensitive subpopulations (children, elderly, pregnant women, people with pre-existing conditions), and for indoor air pollution. CONCLUSIONS: Physical activity and air pollution are linked through multiple mechanisms, and these relations could have important implications for public health, especially in locations with high air pollution concentrations. Overall, this review calls for international collaboration between air pollution and physical activity research fields to strengthen the evidence base on the links between both and on how policy options could potentially reduce risks and maximise health benefits.

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.

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 (PM2.5), 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 PM2.5 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 PM2.5 concentrations. For each city we estimated combined Relative Risk (RR) due to all-cause mortality for the PA benefits and PM2.5 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 PM2.5 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 PM2.5 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.

Use of the prevented fraction for the population to determine deaths averted by existing prevalence of physical activity: a descriptive study.

BACKGROUND: Disease and mortality burdens of unhealthy lifestyle behaviours are often reported. In contrast, the positive narrative around the burdens that an existing behaviour have averted is rarely acknowledged. We aimed to estimate the prevented fraction for the population (PFP) for premature mortality averted by physical activity on a global scale. METHODS: In this descriptive study, we obtained previously published data on physical activity prevalence (2001-16) and relative risks of all-cause mortality for 168 countries. We combined the data in Monte-Carlo simulations to estimate country-specific, mean PFP values, corresponding to percentage of mortality averted, and their 95% CIs. High prevented fractions indicated an increased proportion of deaths averted due to physical activity. Using mortality data for all people in a country aged 40-74 years, we estimated the number of premature deaths averted for all adults and by gender. We present the median and range of the prevented fractions globally, by WHO region, and by World Bank income classification. FINDINGS: The global median PFP was 15·0% (range 6·6-20·5), conservatively equating to 3·9 million (95% CI 2·5-5·6) premature deaths averted annually. The African region had the highest median prevented fraction (16·6% [range 12·1-20·5]) and the Americas had the lowest (13·1% [10·8-16·6]). Low-income countries tended to have higher prevented fractions (group median 17·9% [12·3-20·5]) than high-income countries (14·1% [6·6-17·8]). Globally, the median prevented fraction was higher for men (16·0% [7·8-20·7] than women (14·1% [5·0-20·4]). INTERPRETATION: Existing physical activity prevalence has contributed to averting premature mortality across all countries. PFP has utility as an advocacy tool to promote healthy lifestyle behaviours. By making the case of what has been achieved, the prevented fraction can show the value of current investment and services, which might be conducive to political support. FUNDING: UK Medical Research Council, British Heart Foundation, Cancer Research UK, Economic and Social Research Council, National Institute for Health Research, Wellcome Trust, Heart Foundation Australia.

Comparative risk analysis of dioxins in fish and fine particles from heavy-duty vehicles.

Dioxins and airborne fine particles are both environmental health problems that have been the subject of active public debate. Knowledge on fine particles has increased substantially during the last 10 years, and even the current, lowered levels in the Europe and in the United States appear to be a major public health problem. On the other hand, dioxins are ubiquitous persistent contaminants, some being carcinogens at high doses, and therefore of great concern. Our aim was to (a) quantitatively analyze the two pollutant health risks and (b) study the changes in risk in view of the current and forthcoming EU legislations on pollutants. We performed a comparative risk assessment for both pollutants in the Helsinki metropolitan area (Finland) and estimated the health effects with several scenarios. For primary fine particles: a comparison between the present emission situation for heavy-duty vehicles and the new fine particle emission standards set by the EU. For dioxins: an EU directive that regulates commercial fishing of Baltic salmon and herring that exceed the dioxin concentration limit set for fish meat, and a derogation (= exemption) from the directive for these two species. Both of these two decisions are very topical issues and this study estimates the expected changes in health effects due to these regulations. It was found that the estimated fine particle risk clearly outweighed the estimated dioxin risk. A substantial improvement to public health could be achieved by initiating reductions in emission standards; about 30 avoided premature deaths annually in the study area. In addition, the benefits of fish consumption due to omega-3 exposure were notably higher than the potential dioxin cancer risk. Both regulations were instigated as ways of promoting public health.