Perspectives On Environmental Health Management Paradigms
Price
Free (open access)
Transaction
Volume
85
Pages
7
Published
2005
Size
222 kb
Paper DOI
10.2495/EEH050461
Copyright
WIT Press
Author(s)
M. M. Aral
Abstract
Environmental health management paradigms have evolved over the past several decades through a \“trial and error” approach, or sometimes through a \“destroying and correcting” evolutionary approach. It is not clear whether, at this time, we have reached a final acceptable environmental health management model which may be satisfactory for all environmental concerns; one that addresses all potential adverse health outcomes or one that includes all stakeholders in the environmental health scientific community. This evolutionary, sometimes revolutionary development is still ongoing and maybe the goal of identifying an environmental health management model that answers all questions and concerns may not be achievable. In this study, we first review the historical development of environmental management models, provide some insight as to what the next step might be in this evolution and establish the necessary background to achieve that next step. We also provide an example of a study to demonstrate the potential outcome if one adopts the premise of the next step that is identified here. It is up to the next generation environmental health scientists and environmental health community to adopt this premise and take it further to the next level to address health concerns for the benefit of public. Keywords: health, environment, management models. 1 Environmental management paradigms Over several decades environmental scientists, economists, physicists, social scientists, health scientists and public health officials have been working on critical issues in environmental health management in order to find a feasible medium between limited resources, long term demands, environmental impacts, health effects and (always in conflict) interest groups. During the last decades,
Keywords
health, environment, management models.