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

The Health Economic Assessment Tool (HEAT) for walking and cycling - experiences from 10 years of application of a health impact assessment tool in policy and practice

Introduction

In recent years, walking and cycling have moved into the focus as promising approaches to achieve public health, sustainable transport, climate goals and better urban resilience. However, they are only realistic transport and activity options for a large proportion of the population when they are safe, inclusive and convenient. One way to increase their recognition in transport policy is the inclusion of health impacts of walking and cycling into transport economic appraisals.

Methods

The Health Economic Assessment Tool (HEAT) for walking and cycling calculates: if x people walk or cycle a distance of y on most days, what is the economic value of impacts on premature mortality, taking into account effects of physical activity, air pollution and road fatalities, as well as effects on carbon emissions. Different data sources were collated to examine how the HEAT in more than 10 years of existence, and to identify lessons learned and challenges.

Results

Since its launch in 2009, the HEAT has gained wide recognition as a user friendly, yet robust, evidence-based tool usable by academics, policymakers, and practitioners. Originally designed for use in Europe, it has since been expanded for global use.

Discussion

Challenges for a wider uptake of health-impact assessment (HIA) tools including active transport such as HEAT are the promotion and dissemination to local practitioners and policy makers also outside European and English-speaking regions and in low- and middle-income contexts, further increasing usability, and more generally the advancement of systematic data collection and impact quantification related to walking and cycling.

Impact on mortality of pathways to net zero greenhouse gas emissions in England and Wales: a multisectoral modelling study

BACKGROUND

The UK is legally committed to reduce its greenhouse gas emissions to net zero by 2050. We aimed to understand the potential impact on population health of two pathways for achieving this target through the integrated effects of six actions in four sectors.

METHODS

In this multisectoral modelling study we assessed the impact on population health in England and Wales of six policy actions relating to electricity generation, transport, home energy, active travel, and diets relative to a baseline scenario in which climate actions, exposures, and behaviours were held constant at 2020 levels under two scenarios: the UK Climate Change Committee's Balanced Pathway of technological and behavioural measures; and its Widespread Engagement Pathway, which assumes more substantial changes to consumer behaviours. We quantified the impacts of each policy action on mortality using a life table comprising all exposures, behaviours, and health outcomes in a single model.

FINDINGS

Both scenarios are predicted to result in substantial reductions in mortality by 2050. The Widespread Engagement Pathway achieves a slightly greater reduction in outdoor fine particulate matter air pollution of 3·2 μg/m³ (33%) and, under assumptions of appropriate ventilation, a greater improvement in indoor air pollution (a decrease in indoor-generated fine particulate matter from 9·4 μg/m³ to 4·6 μg/m³) and winter temperatures (increasing from 17·8°C to 18·1°C), as well as appreciably greater changes in levels of active travel (27% increase in metabolic equivalent hours per week of walking and cycling) by 2050. Additionally, the greater reduction in red meat consumption (50% compared with 35% under the Balanced Pathway) by 2050 results in greater consumption of fruits (17-18 g/day), vegetables (22-23 g/day), and legumes (5-7 g/day). Combined actions under the Balanced Pathway result in more than 2 million cumulative life-years gained over 2021-50; the estimated gain under the Widespread Engagement Pathway is greater, corresponding to nearly 2·5 million life-years gained by 2050 and 13·7 million life-years gained by 2100.

INTERPRETATION

Reaching net zero greenhouse gas emissions is likely to lead to substantial benefits for public health in England and Wales, with the cumulative net benefits being correspondingly greater with a pathway that entails faster and more ambitious changes, especially in physical activity and diets.

FUNDING

National Institute for Health Research and the Wellcome Trust.

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.

2030 Agenda: discussion on Brazilian priorities facing air pollution and climate change challenges

The advance of human activities in a disorderly way has accelerated in recent decades, intensifying the environmental impacts directly linked to these practices. The atmosphere, essential for the maintenance of life, is increasingly saturated with pollutants, offering risks to practically all the inhabitants of the planet, a process that, in addition to causing illness and early mortality, is related to serious financial losses (including in the production of goods), dangerous temperature increase and severe natural disasters. Although this perception is not recent, the global initiative to control the different mechanisms that trigger the commitment of biodiversity and irreversible climate changes arising from pollution is still very incipient, given that global initiatives on the subject emerged just over 50 years ago. Brazil is a territory that centralizes many of these discussions, as it still faces both political and economic obstacles in achieving a sustainable growth model as it was agreed through the United Nations 2030 Agenda. Even though there is little time left for the completion of these goals, much remains to be done, and despite the fulfillment of this deadline, the works will certainly need to be extended for much longer until an effective reorientation of consciousness occurs. Scientific researches and discussions are fundamental tools to the understanding of issues still little explored in this field.

The impact of urban environmental exposures on health: An assessment of the attributable mortality burden in Sao Paulo city, Brazil

BACKGROUND

Currently, more than half of the global population lives in cities. Contemporary urban planning practices result in environmental risk factors (e.g. air pollution, noise, lack of green space, excess heat) that put health and well-being of city dwellers at risk and contribute to chronic diseases and premature death. Despite a growing body of evidence on adverse health impacts related to current urban and transport planning practices, especially for cities in the Global North, not much is known about associated health impacts in South American cities. Therefore, we estimated the mortality burden attributable to breaching internationally-recommended or locally-preferable exposure levels of urban planning related environmental exposures in Sao Paulo, Brazil.

METHODS

We carried out a health impact assessment study, following the comparative risk assessment framework, to assess preventable mortality impacts of breaching exposure recommendations for air pollution, green spaces and temperature at the census tract (CT) level (n = 18,363). We also assessed the distribution thereof by socioeconomic vulnerability.

RESULTS

We estimated that annually 11,372 (95% CI: 7921; 15,910) attributable deaths could be prevented by complying with recommended exposure levels. The largest proportion of preventable mortality was due to breaching air pollution limits (i.e. 8409 attributable deaths), followed by insufficient green space (i.e. 2593), and excess heat (i.e. 370). Adverse health impacts were larger in CTs of lower socioeconomic vulnerability, due to demographic profile, traffic density and residential area configurations.

DISCUSSION

Not complying with the health limits for air pollution, green space and temperature exposures resulted in a considerable preventable mortality burden (i.e. 17% of total expected deaths) in Sao Paulo. This burden can be reduced by improving current urban and transport planning practices.

GeoAI for Large-Scale Image Analysis and Machine Vision: Recent Progress of Artificial Intelligence in Geography

GeoAI, or geospatial artificial intelligence, has become a trending topic and the frontier for spatial analytics in Geography. Although much progress has been made in exploring the integration of AI and Geography, there is yet no clear definition of GeoAI, its scope of research, or a broad discussion of how it enables new ways of problem solving across social and environmental sciences. This paper provides a comprehensive overview of GeoAI research used in large-scale image analysis, and its methodological foundation, most recent progress in geospatial applications, and comparative advantages over traditional methods. We organize this review of GeoAI research according to different kinds of image or structured data, including satellite and drone images, street views, and geo-scientific data, as well as their applications in a variety of image analysis and machine vision tasks. While different applications tend to use diverse types of data and models, we summarized six major strengths of GeoAI research, including (1) enablement of large-scale analytics; (2) automation; (3) high accuracy; (4) sensitivity in detecting subtle changes; (5) tolerance of noise in data; and (6) rapid technological advancement. As GeoAI remains a rapidly evolving field, we also describe current knowledge gaps and discuss future research directions.

Value of Information Analysis in Models to Inform Health Policy

Value of information (VoI) is a decision-theoretic approach to estimating the expected benefits from collecting further information of different kinds, in scientific problems based on combining one or more sources of data. VoI methods can assess the sensitivity of models to different sources of uncertainty and help to set priorities for further data collection. They have been widely applied in healthcare policy making, but the ideas are general to a range of evidence synthesis and decision problems. This article gives a broad overview of VoI methods, explaining the principles behind them, the range of problems that can be tackled with them, and how they can be implemented, and discusses the ongoing challenges in the area.

The Impact of Transport on Population Health and Health Equity for Māori in Aotearoa New Zealand: A Prospective Burden of Disease Study

Background: The land transport system influences health via a range of pathways. This study aimed to quantify the amount and distribution of health loss caused by the current land transport system in Aotearoa New Zealand (NZ) through the pathways of road injury, air pollution and physical inactivity. Methods: We used an existing multi-state life table model to estimate the long-term health impacts (in health-adjusted life years (HALYs)) and changes in health system costs of removing road injury and transport related air pollution and increasing physical activity to recommended levels through active transport. Health equity implications were estimated using relative changes in HALYs and life expectancy for Māori and non-Māori. Results: If the NZ resident population alive in 2011 was exposed to no further air pollution from transport, had no road traffic injuries and achieved at least the recommended weekly amount of physical activity through walking and cycling from 2011 onwards, 1.28 (95% UI: 1.11–1.5) million HALYs would be gained and $7.7 (95% UI: 10.2 to 5.6) billion (2011 NZ Dollars) would be saved from the health system over the lifetime of this cohort. Māori would likely gain more healthy years per capita than non-Māori, which would translate to small but important reductions (2–3%) in the present gaps in life expectancy. Conclusion: The current transport system in NZ, like many other car-dominated transport systems, has substantial negative impacts on health, at a similar level to the effects of tobacco and obesity. Transport contributes to health inequity, as Māori bear greater shares of the negative health impacts. Creating a healthier transport system would bring substantial benefits for health, society and the economy.

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.

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.

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.

Climate Change, Physical Activity and Sport: A Systematic Review

BACKGROUND

Climate change impacts are associated with dramatic consequences for human health and threaten physical activity (PA) behaviors.

OBJECTIVE

The aims of this systematic review were to present the potential bidirectional associations between climate change impacts and PA behaviors in humans and to propose a synthesis of the literature through a conceptual model of climate change and PA.

METHODS

Studies published before October 2020 were identified through database searches in PubMed, PsycARTICLES, CINAHL, SPORTDiscus, GreenFILE, GeoRef, Scopus, JSTOR and Transportation Research Information Services. Studies examining the associations between PA domains and climate change (e.g., natural disasters, air pollution, and carbon footprint) were included.

RESULTS

A narrative synthesis was performed and the 74 identified articles were classified into 6 topics: air pollution and PA, extreme weather conditions and PA, greenhouse gas emissions and PA, carbon footprint among sport participants, natural disasters and PA and the future of PA and sport practices in a changing world. Then, a conceptual model was proposed to identify the multidimensional associations between climate change and PA as well as sport practices. Results indicated a consistent negative effect of air pollution, extreme temperatures and natural disasters on PA levels. This PA reduction is more severe in adults with chronic diseases, higher body mass index and the elderly. Sport and PA communities can play an important mitigating role in post-natural disaster contexts. However, transport related to sport practices is also a source of greenhouse gas emissions.

CONCLUSION

Climate change impacts affect PA at a worldwide scale. PA is observed to play both a mitigation and an amplification role in climate changes.

TRIAL REGISTRATION NUMBER

PROSPERO CRD42019128314.

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.

Appraisal of cycling and pedestrian projects

Cycling and walking have gained a prominent role in the mobility policy agenda as awareness has risen over the growing unsustainability of the current transport system and the multiple co-benefits of active mobility. As interest and investments for cycling and walking increase, how active mobility can be appraised becomes a crucial question, which has been tackled over the years through different methods and tools. The aim of this chapter is to provide a structured review of the methods and the practices of appraisal of walking and cycling policies and projects, focusing on both traditional and emerging assessment techniques. At present, much attention has been paid to the application of four main traditional methods: Balance Sheet Calculations, Cost-Benefit Analysis, Cost-Effectiveness Analysis and Multi-Criteria Analysis. We compare and discuss these methods to identify strengths and weaknesses for each of them, as well as their main limitations and knowledge gaps in their application. We conclude that over the last decades much effort has been undertaken to further expand and develop these tools thanks to an increased attention to walking and cycling. However, much research is still needed, particularly in the quantification and valuation of specific effects within Cost-Benefit Analysis and in better integrating different appraisal techniques. Finally, the impact of appraisals on decision-making outcomes is still underexplored.

Participatory quantitative health impact assessment of urban transport planning: A case study from Eastern Africa

BACKGROUND

High rates of motorization in urban areas of Africa have adverse effects on public health. Transport-related mortality will increase as a result of inadequate transport infrastructure, air pollution and sedentary lifestyles. Health Impact Assessments (HIAs) have proven to be a successful tool to predict and mitigate negative health impact of urban transport planning policies, programmes or projects. Yet, there is a gap of evidence on transport and health in African countries. The aim of this study is assessing the health impacts of transport scenarios in Port Louis (city of 119,018 inhabitants in Mauritius) using a full chain participatory HIA model.

METHODS

We estimated health and economic impacts associated to transport scenarios with qualitative data and quantitative comparative risk assessment methods. The health impact modeling was based on differences between the baseline and three transport scenarios (worse, good, ideal), estimating the averted deaths per year and economic outcomes by assessing health determinants of air pollution (AP), traffic deaths and physical activity (PA). Data on air pollution and traffic fatalities were obtained from public data sources. Data used to construct scenarios, establish baseline travel mode shares and physical activity were collected through (a) open-ended individual interviews (IDIs) with 14 stakeholders (b) closed-ended survey questions to 600 citizens and (c) 2 focus group discussions (FGDs) with the same 14 stakeholders from (a).

RESULTS

In Port Louis, the worse-case transport scenario (doubling in car trips and a reduction in walking, motorcycle, and public transport), resulted in a total increment of 3.28 premature deaths per year. The good-case scenario (reducing car trips by half and increasing walking, motorcycle, and public transport trips) resulted in a total increment of 0.79 premature deaths per year. The ideal-case scenario (reduction in car and motorcycle trips and an increase in walking and public transport trips) resulted in a total reduction of 13.72 premature deaths per year. We estimated USD 23 millions of economic benefits related to mortality if the ideal-case was achieved.

CONCLUSION

Participatory HIA shows that implementing transport policies aiming for less than an ideal situation may not be adequate or sufficient to avoid negative transport-related mortality in Mauritius. Urban transport planning is an opportunity to encourage physical activity in rapidly urbanizing settings of Africa. Transport policies should aim to restrict all forms of private motorized vehicles and promote active and public transport to support public health. We highly recommend the use of participatory approaches in quantitative HIA to ensure context specificity and policy relevance.

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.

Self-initiated changes in physical activity and incidence of Metabolic Syndrome: A longitudinal follow-up study

AIM

The aim of this study was to analyze the association between longitudinal physical activity patterns (persistently inactive, became active, became inactive, and persistently active) and the incidence of Metabolic Syndrome (MS) among adults.

METHODS

Our cohort included 5766 adults (18-59y) undergoing repeated routine health screening examinations, with a mean follow-up period of three years. Only subjects without MS at baseline were included in the study. MS was defined according to the ATP III definition, including assessments of fasting blood samples for the collection of HDL-C, triglycerides and glucose, blood pressure, and waist circumference. Physical activity was estimated using the international physical activity questionnaire and four patterns were created (persistently active, became active, became inactive, and persistently inactive). Information on tobacco smoking and alcohol consumption (through structured validated questionnaires), age, interval between baseline and follow-up, anti-hypertensive drugs, statin, anti-diabetic drugs were used as covariates. Logistic regression was conducted.

RESULTS

The mean age of participants at baseline was 41.6 ± 7.9 years. We identified 1701 subjects who were active at both moments, 1246 who became active, 709 who became inactive, and 2210 who were inactive at both moments. Persistently inactive subjects presented a higher incidence of MS [10.4% (95%CI = 9.2-11.8%)]. In the adjusted logistic regression analyses, subjects that became active [OR = 0.55(95%CI = 0.40-0.74)] and persistently active [OR = 0.35(95%CI = 0.26-0.46)] were less likely to develop MS when compared with persistently inactive subjects.

CONCLUSION

Persistently active subjects demonstrated the lowest likelihood of developing MS, while subjects who became active presented an attenuated risk.

Health economic assessment of a shift to active transport

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

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

BACKGROUND

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

METHOD

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

RESULTS

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

CONCLUSION

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

Burden of Disease Assessment of Ambient Air Pollution and Premature Mortality in Urban Areas: The Role of Socioeconomic Status and Transportation

With recent rapid urbanization, sustainable development is required to prevent health risks associated with adverse environmental exposures from the unsustainable development of cities. Ambient air pollution is the greatest environmental risk factor for human health and is responsible for considerable levels of mortality worldwide. Burden of disease assessment (BoD) of air pollution in and across cities, and how these estimates vary according to socioeconomic status and exposure to road traffic, can help city planners and health practitioners to mitigate adverse exposures and promote public health. In this study, we quantified the health impacts of air pollution exposure (PM2.5 and NO2) at the census tract level in Houston, Texas, employing a standard BoD assessment framework to estimate the premature deaths (adults 30 to 78 years old) attributable to PM2.5 and NO2. We found that 631 (95% CI: 366-809) premature deaths were attributable to PM2.5 in Houston, and 159 (95% CI: 0-609) were attributable to NO2, in 2010. Complying with the World Health Organization air quality guidelines (annual mean: 10 μg/m3 for PM2.5) and the US National Ambient Air Quality standard (annual mean: 12 μg/m3 for PM2.5) could save 82 (95% CI: 42-95) and 8 (95% CI: 6-10) lives in Houston, respectively. PM2.5 was responsible for 7.3% of all-cause premature deaths in Houston, in 2010, which is higher than the death rate associated with diabetes mellites, Alzheimer's disease, or motor vehicle crashes in the US. Households with lower income had a higher risk of adverse exposure and attributable premature deaths. We also showed a positive relationship between health impacts attributable to air pollution and road traffic passing through census tracts, which was more prominent for NO2.

Understanding the rise of cardiometabolic diseases in low- and middle-income countries

Increases in the prevalence of noncommunicable diseases (NCDs), particularly cardiometabolic diseases such as cardiovascular disease, stroke and diabetes, and their major risk factors have not been uniform across settings: for example, cardiovascular disease mortality has declined over recent decades in high-income countries but increased in low- and middle-income countries (LMICs). The factors contributing to this rise are varied and are influenced by environmental, social, political and commercial determinants of health, among other factors. This Review focuses on understanding the rise of cardiometabolic diseases in LMICs, with particular emphasis on obesity and its drivers, together with broader environmental and macro determinants of health, as well as LMIC-based responses to counteract cardiometabolic diseases.

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.

Systematic Literature Review of Health Impact Assessments in Low and Middle-Income Countries

Health Impact Assessments (HIAs) motivate effective measures for safeguarding public health. There is consensus that HIAs in low and middle-income countries (LMICs) are lacking, but no study systematically focuses on those that have been successfully conducted across all regions of the world, nor do they highlight factors that may enable or hinder their implementation. Our objectives are to (1) systematically review, geographically map, and characterize HIA activity in LMICs; and (2) apply a process evaluation method to identify factors which are important to improve HIA implementation in LMICs. A systematic review of peer-reviewed HIAs in 156 LMICs was performed in Scopus, Medline, Web of Science, Sociological abstracts, and LILACs (Latin American and Caribbean Health Sciences) databases. The search used PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and covered HIAs across all type of interventions, topics, and health outcomes. HIAs were included if they reported a clear intervention and health outcome to be assessed. No time restriction was applied, and grey literature was not included. The eligible studies were subjected to six process evaluation criteria. The search yielded 3178 hits and 57 studies were retained. HIAs were conducted in 26 out of 156 countries. There was an unequal distribution of HIAs across regions and within LMICs countries. The leading topics of HIA in LMICs were air pollution, development projects, and urban transport planning. Most of the HIAs reported quantitative approaches (72%), focused on air pollution (46%), appraised policies (60%), and were conducted at the city level (36%). The process evaluation showed important variations in the way HIAs have been conducted and low uniformity in the reporting of six criteria. No study reported the time, money, and staff used to perform HIAs. Only 12% of HIAs were based on participatory approaches; 92% of HIAs considered multiple outcomes; and 61% of HIAs provided recommendations and fostered cross-national collaboration. The limited transparency in process, weak participation, and inconsistent delivery of recommendations were potential limitations to HIA implementation in low and middle-income countries. Scaling and improving HIA implementation in low and middle-income countries in the upcoming years will depend on expanding geographically by increasing HIA governance, adapting models and tools in quantitative methods, and adopting better reporting practices.

Spatial variability of on-bicycle black carbon concentrations in the megacity of São Paulo: A pilot study

In 2015, a controversial bicycle lane was installed on Paulista Avenue -a thoroughfare in the heart of the megacity of São Paulo with a high rate of motorised vehicles. For the first time, on-bicycle air pollution concentrations were assessed along this lane using black carbon (BC) as an indicator of fossil fuel combustion. We measured BC concentrations with a hand-held microaethalometer at a high temporal resolution, enabling the capture of fine spatial gradients along the route. Although this new link expanded the city's cycling network, our pioneering study showed that BC concentrations were large (mean 8.5 μg m^-3) with extreme values reaching 24.0 μg m^-3, comparable to concentrations found in many megacities. In agreement with other studies, we observed that concentrations decreased about 1.6 times on a section of the bicycle lane running through a calmer neighbourhood, which could indicate the potential to safeguard the health of cyclists by installing lanes with greater separation from main roads, such as Paulista Avenue. This pilot work paves the way to more detailed studies aiming to map out the spatial distribution of other traffic-related pollutants across the city's 458-km long bicycle network.

Greenhouse gas emissions reduction in different economic sectors: Mitigation measures, health co-benefits, knowledge gaps, and policy implications

To date, greenhouse gas (GHG) emissions, mitigation strategies and the accompanying health co-benefits in different economic sectors have not been fully investigated. The purpose of this paper is to review comprehensively the evidence on GHG mitigation measures and the related health co-benefits, identify knowledge gaps, and provide recommendations to promote further development and implementation of climate change response policies. Evidence on GHG emissions, abatement measures and related health co-benefits has been observed at regional, national and global levels, involving both low- and high-income societies. GHG mitigation actions have mainly been taken in five sectors: energy generation, transport, food and agriculture, household and industry, consistent with the main sources of GHG emissions. GHGs and air pollutants to a large extent stem from the same sources and are inseparable in terms of their atmospheric evolution and effects on ecosystem; thus, GHG reductions are usually, although not always, estimated to have cost effective co-benefits for public health. Some integrated mitigation strategies involving multiple sectors, which tend to create greater health benefits. The pros and cons of different mitigation measures, issues with existing knowledge, priorities for research, and potential policy implications were also discussed. Findings from this study can play a role not only in motivating large GHG emitters to make decisive changes in GHG emissions, but also in facilitating cooperation at international, national and regional levels, to promote GHG mitigation policies that protect public health from climate change and air pollution simultaneously.

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.

Diesel, children and respiratory disease

Air pollution generated in urban areas is a global public health burden since half of the world's population live in either cities, megacities or periurban areas. Its direct effects include initiating and exacerbating disease, with indirect effects on health mediated via climate change putting the basic needs of water, air and food at risk.

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.

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.