Dataset Information

Evaluation of the public health impacts of traffic congestion: a health risk assessment.

ABSTRACT:

Background

Traffic congestion is a significant issue in urban areas in the United States and around the world. Previous analyses have estimated the economic costs of congestion, related to fuel and time wasted, but few have quantified the public health impacts or determined how these impacts compare in magnitude to the economic costs. Moreover, the relative magnitudes of economic and public health impacts of congestion would be expected to vary significantly across urban areas, as a function of road infrastructure, population density, and atmospheric conditions influencing pollutant formation, but this variability has not been explored.

Methods

In this study, we evaluate the public health impacts of ambient exposures to fine particulate matter (PM2.5) concentrations associated with a business-as-usual scenario of predicted traffic congestion. We evaluate 83 individual urban areas using traffic demand models to estimate the degree of congestion in each area from 2000 to 2030. We link traffic volume and speed data with the MOBILE6 model to characterize emissions of PM2.5 and particle precursors attributable to congestion, and we use a source-receptor matrix to evaluate the impact of these emissions on ambient PM2.5 concentrations. Marginal concentration changes are related to a concentration-response function for mortality, with a value of statistical life approach used to monetize the impacts.

Results

We estimate that the monetized value of PM2.5-related mortality attributable to congestion in these 83 cities in 2000 was approximately $31 billion (2007 dollars), as compared with a value of time and fuel wasted of $60 billion. In future years, the economic impacts grow (to over $100 billion in 2030) while the public health impacts decrease to $13 billion in 2020 before increasing to $17 billion in 2030, given increasing population and congestion but lower emissions per vehicle. Across cities and years, the public health impacts range from more than an order of magnitude less to in excess of the economic impacts.

Conclusions

Our analyses indicate that the public health impacts of congestion may be significant enough in magnitude, at least in some urban areas, to be considered in future evaluations of the benefits of policies to mitigate congestion.

SUBMITTER: Levy JI

PROVIDER: S-EPMC2987789 | biostudies-literature | 2010 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Evaluation of the public health impacts of traffic congestion: a health risk assessment.

Levy Jonathan I JI Buonocore Jonathan J JJ von Stackelberg Katherine K

Environmental health : a global access science source 20101027

<h4>Background</h4>Traffic congestion is a significant issue in urban areas in the United States and around the world. Previous analyses have estimated the economic costs of congestion, related to fuel and time wasted, but few have quantified the public health impacts or determined how these impacts compare in magnitude to the economic costs. Moreover, the relative magnitudes of economic and public health impacts of congestion would be expected to vary significantly across urban areas, as a func ...[more]

PMID: 20979626

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Project description:BackgroundPublic mental health interventions are non-clinical services that aim to promote wellbeing and prevent mental ill health at the population level. In England, the health, social and community system is characterised by complex and fragmented inter-sectoral relationships. To overcome this, there has been an expansion in co-locating public mental health services within clinical settings, the focus of prior research. This study evaluates how co-location in community-based settings can support adult mental health and reduce health inequalities.MethodsA qualitative multi-site case study design using a realist evaluation approach was employed. Data collection took place in three phases: theory gleaning, parallel testing and refining of theories, and theory consolidation. We collected data from service users (n = 32), service providers (n = 32), funders, commissioners, and policy makers (n = 11), and members of the public (n = 10). We conducted in-depth interviews (n = 65) and four focus group discussions (n = 20) at six case study sites across England, UK, and two online multi-stakeholder workshops (n = 20). Interview guides followed realist-informed open-ended questions, adapted for each phase. The realist analysis used an iterative, inductive, and deductive data analysis approach to identify the underlying mechanisms for how community co-location affects public mental health outcomes, who this works best for, and understand the contexts in which co-location operates.ResultsFive overarching co-location theories were elicited and supported. Co-located services: (1) improved provision of holistic and person-centred support; (2) reduced stigma by creating non-judgemental environments that were not associated with clinical or mental health services; (3) delivered services in psychologically safe environments by creating a culture of empathy, friendliness and trust where people felt they were being treated with dignity and respect; (4) helped to overcome barriers to accessibility by making service access less costly and more time efficient, and (5) enhance the sustainability of services through better pooling of resources.ConclusionCo-locating public mental health services within communities impacts multiple social determinants of poor mental health. It has a role in reducing mental health inequalities by helping those least likely to access services. Operating practices that engender inter-service trust and resource-sharing are likely to support sustainability.

Dataset Information

Evaluation of the public health impacts of traffic congestion: a health risk assessment.

Background

Methods

Results

Conclusions

Publications

Evaluation of the public health impacts of traffic congestion: a health risk assessment.

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