Advancing Research on Greenspace and Climate-Sensitive Adverse Birth Outcomes for Equity and Impact
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2024/12/01
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Description:Environmental epidemiologists are increasingly evaluating whether and how human exposure to vegetation (greenspace) can benefit health. Relatedly, scientists and policymakers have highlighted the need to integrate efforts to address the dual crises of accelerating climate change and rapid loss of biodiversity, including nature-based solutions. Greenspace is one solution that can protect humans from climate-related exposures, including heat, air pollution, and flooding. However, most environmental epidemiology research on greenspace occurs in high-income countries, and adverse birth outcomes, previously associated with greenspace, disproportionately occur in low- and middle-income countries (LMICs). Although epidemiology research using existing survey or administrative data and satellite imagery is important for documenting broad patterns, such research is lacking in LMICs. Further, complementary, community-engaged research to inform interventions and policies is needed so that nature-based solutions with co-benefits for climate mitigation and health are adopted effectively and equitably. We provide suggestions for future research that would increase impact and call for better representation of LMICs and vulnerable communities within high-income countries in research and action on greenspace and climate-sensitive birth outcomes. [Description provided by NIOSH]
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ISSN:2474-7882
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Volume:8
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Issue:6
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NIOSHTIC Number:nn:20070351
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Citation:Environ Epidemiol 2024 Dec; 8(6):e353
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Contact Point Address:Marie S. O'Neill, Departments of Environmental Health Sciences and Epidemiology, University of Michigan School of Public Health, 109 Observatory Road, 6623 SPH 1; Ann Arbor, MI 48109
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Email:marieo@umich.edu
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Federal Fiscal Year:2025
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Performing Organization:University of Michigan, Ann Arbor
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Peer Reviewed:True
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Start Date:20050701
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Source Full Name:Environmental Epidemiology
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End Date:20280630
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Main Document Checksum:urn:sha-512:57b266b0af53fceb6af7c2ae7ff0b82b5c71655d8a9c548b5a00f2895aef744417a08b3799cbdbbbe30865660dfeeeda8445dda2c6764eb30c084f146e28fab1
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