Investigating health risks of environmental stressors in the UK Biobank cohort
Lead Research Organisation:
London School of Hygiene & Tropical Medicine
Department Name: Public Health and Policy
Abstract
Over the past decades, there has been extensive research on the health risks associated with exposure to environmental stressors. Recent global assessments have found that air pollution and non-optimal outdoor temperature, two of the most important risk factors, are responsible for 7.6% and 9.4% of global deaths, respectively. However, while the evidence of their association with increased health risks is established, major gaps in knowledge still remain.
This project illustrates an ambitious research programme for investigating health risks associated with environmental stressors using the UK Biobank (UKB), a cohort study that follows prospectively more than half a million participants. The research endeavour involves an international team of researchers from the London School of Hygiene & Tropical Medicine, Case Western Reserve University in the USA, and Imperial College London, with multidisciplinary expertise and established experience in the research area.
The research plan is structured in different steps. First, the research team will develop sophisticated spatio-temporal models based on machine learning to produce high-resolution maps of environmental stressors such as air pollution and temperature. The output will be used to reconstruct detailed exposure profiles for each UKB participant. The team will then develop innovative methodologies to analyse such a rich set of data and assess the health impacts of environmental stressors. These data resources and analytical methods will be used in a series of epidemiological studies that will investigate a range of different risks related to air pollution and temperature. These will include short-term effects on respiratory events such as asthma exacerbations, long-term associations with cardiovascular outcomes such as myocardial infarction, and individual susceptibility linked to pre-existing clinical conditions, medications, lifestyle habits, socio-economic characteristics, and neighbourhood features. Finally, the exposure data will be permanently linked to the UKB database, making available to the research community fully documented resources and easy-to-use tools to address further research questions on links between environmental stressors on human health.
This project will contribute to advancing our knowledge of the health risks associated with exposure to environmental stressors, and improve our understanding of individual susceptibilities determined by socio-economic, lifestyle, clinical, and contextual factors. The provision of detailed exposure information to the UKB database will provide researchers with unique resources to improve our understanding of the complex relationships between environment, climate, and health.
This project illustrates an ambitious research programme for investigating health risks associated with environmental stressors using the UK Biobank (UKB), a cohort study that follows prospectively more than half a million participants. The research endeavour involves an international team of researchers from the London School of Hygiene & Tropical Medicine, Case Western Reserve University in the USA, and Imperial College London, with multidisciplinary expertise and established experience in the research area.
The research plan is structured in different steps. First, the research team will develop sophisticated spatio-temporal models based on machine learning to produce high-resolution maps of environmental stressors such as air pollution and temperature. The output will be used to reconstruct detailed exposure profiles for each UKB participant. The team will then develop innovative methodologies to analyse such a rich set of data and assess the health impacts of environmental stressors. These data resources and analytical methods will be used in a series of epidemiological studies that will investigate a range of different risks related to air pollution and temperature. These will include short-term effects on respiratory events such as asthma exacerbations, long-term associations with cardiovascular outcomes such as myocardial infarction, and individual susceptibility linked to pre-existing clinical conditions, medications, lifestyle habits, socio-economic characteristics, and neighbourhood features. Finally, the exposure data will be permanently linked to the UKB database, making available to the research community fully documented resources and easy-to-use tools to address further research questions on links between environmental stressors on human health.
This project will contribute to advancing our knowledge of the health risks associated with exposure to environmental stressors, and improve our understanding of individual susceptibilities determined by socio-economic, lifestyle, clinical, and contextual factors. The provision of detailed exposure information to the UKB database will provide researchers with unique resources to improve our understanding of the complex relationships between environment, climate, and health.
Technical Summary
This project illustrates an ambitious research programme to build an advanced analytical and data platform for investigating environmental health risks using the UK Biobank (UKB), a cohort study that follows prospectively more than half a million participants.
The research plan is structured in four work packages (WPs). In WP1, the research team will develop sophisticated spatio-temporal machine learning models to produce high-resolution maps of environmental stressors. These data will be linked to the residential locations of the UKB participants to create individual-level exposure profiles for several pollutants (PM10, PM2.5, O3, and NO2) and temperature indices. In WP2, the team will develop innovative study designs and analytical methods that can make full use of the highly informative data setting. In WP3, the team will perform various epidemiological investigations to evaluate a range of different risks of air pollution and temperature, from short-term effects on respiratory events to long-term associations with cardiovascular outcomes. Further analyses will explore individual susceptibilities determined by individual or contextual factors. Finally, in WP4, the rich exposure data will be fully documented and permanently linked to the UKB database.
This project will contribute to advancing our knowledge of the health risks associated with exposure to environmental stressors, and improve our understanding of individual susceptibilities determined by socio-economic, lifestyle, clinical, and contextual factors. The enhancement of the rich UKB cohort with detailed individual-level exposure information will provide the research community with unique resources to conduct further studies on the complex relationship between environmental factors, climate, and health.
The research plan is structured in four work packages (WPs). In WP1, the research team will develop sophisticated spatio-temporal machine learning models to produce high-resolution maps of environmental stressors. These data will be linked to the residential locations of the UKB participants to create individual-level exposure profiles for several pollutants (PM10, PM2.5, O3, and NO2) and temperature indices. In WP2, the team will develop innovative study designs and analytical methods that can make full use of the highly informative data setting. In WP3, the team will perform various epidemiological investigations to evaluate a range of different risks of air pollution and temperature, from short-term effects on respiratory events to long-term associations with cardiovascular outcomes. Further analyses will explore individual susceptibilities determined by individual or contextual factors. Finally, in WP4, the rich exposure data will be fully documented and permanently linked to the UKB database.
This project will contribute to advancing our knowledge of the health risks associated with exposure to environmental stressors, and improve our understanding of individual susceptibilities determined by socio-economic, lifestyle, clinical, and contextual factors. The enhancement of the rich UKB cohort with detailed individual-level exposure information will provide the research community with unique resources to conduct further studies on the complex relationship between environmental factors, climate, and health.
