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Impact of Plastic Waste on the human Health in Low-Income Countries: A Systematic Review

Journal of Environmental Protection 2024年第5期15卷 572-595页

作者： Ramde Wendkoaghenda Sophie Gbandama Koffi Kouame Pacome Gansore Aminata Camara Kelety Tolno Barthélemy Assogba Ange Wenceslas Vinciale Niare Boubacar Patrice Ngangue Institute for Interdisciplinary Training and Research in Health Sciences and Education Ouagadougou Burkina Faso Regional Directorate of Health and Public Hygiene of South-Central Burkina Faso Ministry of Health Ouagadougou Burkina Faso Department of Health Promotion and Education Ministry of Health and Public Hygi&#232ne Ouagadougou Burkina Faso Department of Dermatology-Venorology Treichville University Hospital F&#233lix Houphou&#235t-Boigny University Abidjan C&#244te d&#8217Ivoire Department of Infectious and Tropical Diseases Donka National Hospital Faculty of Health Sciences and Techniques Bamako Mali National AIDS Control Program PNLS Ministry of Health and Public Hygiene Abidjan C&#244te d&#8217Ivoire Marketing and Consumer Welfare Research Laboratory Abomey-Calavi University Cotonou Benin Regional Health Directorate of the District of Bamako Ministry of Health and Social Development Bamako Mali Department of Family Medicine Faculty of Medicine and Odonto Stomatology University of Sciences Techniques and Technologies of Bamako Bamako Mali Faculty of Nursing Sciences Laval University Quebec Canada

Background: Plastic pollution is the accumulation of waste composed of plastic and its derivatives all over the environment. Whether in the form of visible garbage or microparticles, as it slowly degrades, plastic pollution poses significant threats to terrestrial and aquatic habitats and the wildlife that call them home, whether through ingestion, entanglement or exposure to the chemicals contained in the material. Unfortunately, there is a lack of documentation on the impact of plastic waste on human health in low- and middle-income countries (LMICs). Methods: We searched five electronic databases (PubMed, Embase, Global Health, CINAHL and Web of Science) and gray literature, following the preferred reporting elements for systematic reviews and meta-analyses (PRISMA), for the impact of plastic waste on human health in developing countries. We included quantitative and qualitative studies written in English and French. We assessed the quality of the included articles using the Mixed Methods Appraisal tool (MMAT). Results: A total of 3779 articles were initially identified by searching electronic databases. After eliminating duplicates, 3167 articles were reviewed based on title and abstract, and 26 were selected for full-text review. Only three articles were retained. The three articles dealt with practices likely to lead to oral exposure to plastic chemicals in human health, as well as the level of awareness of participants concerning the possible impact of plastic on human health, namely, the use of plastic baby bottles, the use of microwaves to cook food and reheat precooked food, the use of plastic bottles to store water in the refrigerator, water purifier containers with plastic bodies and plastic lunch boxes, the reuse of plastic bags and the inadequacy of treatment facilities. Conclusion: Plastic waste poses different risks to human health at every stage of its life cycle. Hence, strategies must be adopted to raise public awareness of the dangers of plastic waste to their health. Trial registration: The r

关键词： Human population Plastic Waste Health Impact Low-Income-Countries (humans Iatrogenic Disease Plastics Policy Recycling Waste Management)

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Modelling changing population distributions:an example of the Kenyan Coast,1979–2009

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International Journal of Digital Earth 2017年第10期10卷 1017-1029页

作者： Catherine Linard Caroline W.Kabaria Marius Gilbert Andrew J.Tatem Andrea E.Gaughan Forrest R.Stevens Alessandro Sorichetta Abdisalan M.Noor Robert W.Snow Spatial Epidemiology Lab(SpELL) UniversitéLibre de BruxellesBrusselsBelgium Department of Geography Universitéde NamurNamurBelgium Spatial Health Metrics Group KEMRI Wellcome Trust Research ProgrammeNairobiKenya Fonds National de la Recherche Scientifique(F.R.S.-FNRS) BrusselsBelgium WorldPop Department of Geography and EnvironmentUniversity of SouthamptonSouthamptonUK Fogarty International Center National Institutes of HealthBethesdaMDUSA Flowminder Foundation StockholmSweden Department of Geography and Geosciences University of LouisvilleLouisvilleKYUSA Nuffield Department of Clinical Medicine Centre for Tropical Medicine and Global HealthUniversity of OxfordOxfordUK

Large-scale gridded population datasets are usually produced for the year of input census data using a top-down approach and projected backward and forward in time using national growth rates.Such temporal projections do not include any subnational variation in population distribution trends and ignore changes in geographical covariates such as urban land cover changes.Improved predictions of population distribution changes over time require the use of a limited number of covariates that are time-invariant or temporally explicit.Here we make use of recently released multi-temporal high-resolution global settlement layers,historical census data and latest developments in population distribution modelling methods to reconstruct population distribution changes over 30 years across the Kenyan Coast.We explore the methodological challenges associated with the production of gridded population distribution time-series in data-scarce countries and show that trade-offs have to be found between spatial and temporal resolutions when selecting the best modelling approach.Strategies used to fill data gaps may vary according to the local context and the objective of the study.This work will hopefully serve as a benchmark for future developments of population distribution time-series that are increasingly required for population-at-risk estimations and spatial modelling in various fields.

关键词： Human population distribution modelling gridded population datasets temporal change Kenya

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Global spatio-temporally harmonised datasets for producing high-resolution gridded population distribution datasets

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Big Earth Data 2019年第2期3卷 108-139页

作者： Christopher T.Lloyd Heather Chamberlain David Kerr Greg Yetman Linda Pistolesi Forrest R.Stevens Andrea E.Gaughan Jeremiah J.Nieves Graeme Hornby Kytt MacManus Parmanand Sinha Maksym Bondarenko Alessandro Sorichetta Andrew J.Tatem WorldPop School of Geography and Environmental ScienceUniversity of SouthamptonSouthamptonUK Flowminder Foundation StockholmSweden Center for International Earth Science Information Network(CIESIN) Columbia UniversityPalisadesNYUSA Department of Geography and Geosciences University of LouisvilleLouisvilleKYUSA GeoData University of SouthamptonSouthamptonUK

Multi-temporal,globally consistent,high-resolution Human population datasets provide consistent and comparable population distributions in support of mapping sub-national heterogeneities in health,wealth,and resource access,and monitoring change in these over time.The production of more reliable and spatially detailed population datasets is increasingly necessary due to the importance of improving metrics at sub-national and multitemporal scales.This is in support of measurement and monitoring of UN Sustainable Development Goals and related agendas.In response to these agendas,a method has been developed to assemble and harmonise a unique,open access,archive of geospatial datasets.Datasets are provided as global,annual time series,where pertinent at the timescale of population analyses and where data is available,for use in the construction of population distribution layers.The archive includes sub-national census-based population estimates,matched to a geospatial layer denoting administrative unit boundaries,and a number of co-registered gridded geospatial factors that correlate strongly with population presence and density.Here,we describe these harmonised datasets and their limitations,along with the production workflow.Further,we demonstrate applications of the archive by producing multi-temporal gridded population outputs for Africa and using these to derive health and development metrics.The geospatial archive is available at https://***/10.5258/SOTON/WP00650.

关键词： Human population subnational global spatial dataset multi-temporal

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