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.

Data for a city-level health impact assessment of urban transport in Mauritius.

Participatory quantitative Health Impact Assessments (HIAs) in developing countries are rare partly due to data scarcity. This paper reports on primary data collected in the city of Port Louis to complete a HIA of urban transport planning in Mauritius. We conducted a full-chain participatory HIA to assess health impacts on the basis of a transport mode shift in Port Louis, Mauritius [1]. By applying mixed-methods, we estimated averted deaths per year and economic outcomes by assessing the health determinants of air pollution, traffic deaths and physical activity. The participatory quantitative HIA included [1] baseline data collection [2] co-validation of transport policy scenarios with stakeholders and [3] quantitative modelling of health impacts. We used the risk assessment method for HIA appraisal. The data can be reused for epidemiological analysis and different types of impact assessments.

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.