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Revamping Urban Transport for Better Health

Reforming city transport can significantly boost public health and environmental conditions.

Haneen Khreis, Ali Abbas, Daniel Gil-Sanchez, Lambed Tatah, Anna Schroeder, Rahul Goel, Christian Brand, Rob Johnson, James Woodcock

― 5 min read


Transforming Urban Transforming Urban Transport transport choices in cities. Enhancing public health through better
Table of Contents

Cities are complex places where people travel in various ways. How we get around can affect our health in different ways. While cities can expose us to harmful things, they also offer chances to improve our health through better transport choices. By 2050, most people on Earth will live in urban areas, emphasizing the need for smart transport policies that promote health.

The Need for Health Impact Assessments

To make good transport decisions, it’s vital to measure how different travel methods impact health and the environment. Studies have shown that pollution from vehicles and a lack of Physical Activity can lead to serious health problems. Health Impact Assessments (HIA) can help us predict the health effects of different transport options. Unfortunately, many existing models oversimplify the situation, often assuming that reducing pollution would magically fix everything without looking into the details of how transport changes affect health.

The Challenge in Low and Middle-Income Countries

Much of the work on health impact assessments has happened in richer countries, leaving a gap in research for low and middle-income countries (LMICs). Collecting the right data and finding models that work in these regions can be hard. Without clear instructions and usable models, it’s tough for decision-makers to get a handle on the situation.

Introducing the Integrated Transport and Health Impact Modelling Tool

To address these issues, a new tool called ITHIM-Global has been developed. This model focuses on assessing health impacts from transport changes specifically in cities of low and middle-income countries. It looks at three main health pathways: physical activity, Air Pollution, and Road Traffic Accidents. The model also assesses Carbon Dioxide Emissions related to transport.

How the Model Works

Gathering Travel Data

The first step in using the model involves collecting data about how people travel in a city. This data can come from household surveys that ask residents about their travel habits, including information on age, gender, and the types of transport they use. Essentially, we need to know who is going where and how they’re getting there.

Creating a Baseline Population

Once we have the travel data, we can create a baseline population that mirrors the real demographics of the city. This population will serve as the foundation for evaluating different transport scenarios.

Defining Transport Scenarios

In ITHIM-Global, we can create scenarios to see what might happen if people changed their travel habits. For example, what if 5% more people decided to take the bus instead of driving? The model allows us to play around with these scenarios to explore the potential health effects.

Evaluating Health Impacts

Physical Activity Pathway

One of the pathways ITHIM-Global evaluates is physical activity. When people walk or cycle instead of driving, they naturally increase their physical activity levels, which can lead to better health. The model examines changes in physical activity based on the travel scenarios created, comparing how this affects overall health outcomes.

Air Pollution Pathway

Next, the model looks at air pollution. Different modes of transport can produce varying levels of pollution. When more people cycle or take public transport, we can expect changes in air pollution levels. The model measures these impacts to determine how they affect health.

Road Traffic Injuries Pathway

The road traffic injuries pathway focuses on the risks associated with different transport methods. For instance, while cycling and walking can boost physical activity, they may also come with higher risks of accidents. The model evaluates how these risks change with different travel scenarios.

Health Impact Assessment Results

Once all the data is plugged into the model, users can begin to see the potential health impacts of transport shifts. Results will show whether a scenario will lead to more healthy years or, unfortunately, more fatalities.

The Case Study: Bogotá

To illustrate how the model works in practice, a case study was conducted in Bogotá, Colombia. The study simulated a 5% shift in transport modes towards bus and cycling. Results revealed significant health benefits linked to increased physical activity and reduced emissions. The analysis emphasized the importance of considering the trade-offs when promoting transport changes—like how more cyclists might face higher pollution exposure.

Conclusions and Future Improvements

ITHIM-Global is designed to help city planners in LMICs make better decisions about transport and health. While it captures rich details about how different transport options affect health, there is still room for improvement. Future adaptations of the model could consider additional factors like age and seasonal changes in travel behavior.

The Importance of a Multifaceted Approach

Transport is not just about getting from point A to point B; it’s a complex dance involving health, safety, and environmental concerns. By considering all these pathways, cities can create transport systems that not only get people where they need to go but also promote better health outcomes and reduce environmental impact.

The Broader Implications

The findings from ITHIM-Global can aid not just individual cities but can inform national policies on urban planning and transportation. Imagine a world where urban transport decisions take health into account—where a simple bus ride could mean fewer injuries and better air quality!

Call to Action

If you live in an urban area, the way you travel affects not just yourself but the entire community. Advocacy for better transport options—like cycling lanes and efficient public transport systems—can lead to improved health for everyone.

In summary, understanding the connections between travel and health is vital. With tools like ITHIM-Global, we’re one step closer to creating cities that support healthy living and a greener planet. Now, if only we could figure out how to create a transport system that eliminates traffic jams... Ah, one can dream!

Original Source

Title: Description, Development and Application of the Integrated Transport and Health Impact Modelling Tool for Global Cities (ITHIM-Global)

Abstract: AbstractThe Integrated Transport and Health Impact Modelling Tool for Global Cities (ITHIM-Global) was developed as an open-source tool to assess the impacts of transport mode shifts on public health and the environment in low- and middle-income countries (LMICs) where the need for such assessment is urgent and rising. The model simulates the impacts on all-cause and cause-specific mortality and years of life lost outcomes through a multi-pathway framework, specifically including physical activity, air pollution exposure, and road traffic fatalities. In addition, the model estimates changes in carbon dioxide emissions resulting from these mode shifts. ITHIM-Global employs a quasi-microsimulation approach that enables individualized exposure estimates by age, sex, and activity levels and utilises up- to-date exposure and dose-response functions that account for the non-linear relationship between physical activity levels and health. To demonstrate its functionality, document its strengths and weaknesses, and aid users, the model was applied to Bogota, Colombia, using three hypothetical scenarios, each shifting 5% of trips to one of bus, car, or cycling. Results indicate that increasing public or active transport modes enhances public health, primarily driven by gains in physical activity and to a lesser extent by reductions in traffic-related emissions. Conversely, a shift to car usage worsens health outcomes due to decreased physical activity and increased pollution exposure. ITHIM-Global serves as a flexible, detailed Health Impact Assessment (HIA) tool adaptable to urban areas across LMICs and this article delves into underlying assumptions and their influence to advance generalisable lessons on risk assessment and model development. The modular structure of ITHIM-Global, its covering of individual and population-level analyses, and extensive documentation provide an accessible, evidence-based approach for city planners and practitioners to optimize transport policies that support public health and mitigate environmental harm. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=138 HEIGHT=200 SRC="FIGDIR/small/24318676v1_ufig1.gif" ALT="Figure 1"> View larger version (29K): [email protected]@f38047org.highwire.dtl.DTLVardef@6ae0e3org.highwire.dtl.DTLVardef@d27718_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIWe describe the Integrated Transport and Health Impact Modelling Tool for Global cities (ITHIM- Global), designed for low- and middle-income country (LMIC) cities. C_LIO_LIWe apply ITHIM-Global to Bogota, simulating impacts from three mode shift scenarios with a 5- percentage point increase in car, cycling, and bus shares. C_LIO_LIWe simulate the impacts on physical activity, air pollution, road traffic fatalities, and attributable mortalities and years of life lost. C_LIO_LIWe describe in detail the models elements to aid future uptake, development, and extension to other cities. We discuss strengths, weaknesses, and underlying assumptions to advance generalisable lessons on risk assessment and model development. C_LI

Authors: Haneen Khreis, Ali Abbas, Daniel Gil-Sanchez, Lambed Tatah, Anna Schroeder, Rahul Goel, Christian Brand, Rob Johnson, James Woodcock

Last Update: 2024-12-12 00:00:00

Language: English

Source URL: https://www.medrxiv.org/content/10.1101/2024.12.11.24318676

Source PDF: https://www.medrxiv.org/content/10.1101/2024.12.11.24318676.full.pdf

Licence: https://creativecommons.org/licenses/by/4.0/

Changes: This summary was created with assistance from AI and may have inaccuracies. For accurate information, please refer to the original source documents linked here.

Thank you to medrxiv for use of its open access interoperability.

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