Informing environmental health policy in urban areas: the HEADLAMP approach

Rev Environ Health. 2000 Jan-Jun;15(1-2):169-86. doi: 10.1515/reveh.2000.15.1-2.169.

Abstract

Urban areas represent complex environments in which to protect health. Accurate and highly resolved information is thus a prerequisite for effective environmental health policy. The HEADLAMP approach is designed to improve decision-making by providing indicators, based on sound science, to all relevant stakeholders, in an appropriate and usable form. The approach comprises three linked stages: categorization of the issues to be addressed, construction of relevant indicators, and policy formulation and implementation. Nevertheless, the application of this approach faces many challenges. The environment-health chain is both lengthy and complex, so that a wide range of indicators is needed from different points in this chain. The DPSEEA framework provides a useful, though limited, structure to help define and organize these indicators. This complexity also means that the indicators have to be linked, so that problems can be tracked from cause to effect and the effectiveness of actions at different points in the DPSEEA chain can be evaluated. Indicators also have to be designed in ways reflecting the spatial and temporal complexity of urban areas--namely, the rapid rates of change in urban environments and the marked spatial variations in environmental and sociodemographic conditions. Effective methods of participation are equally essential if the indicators are to represent the concerns of the stakeholders involved, and if decisions are to be made on a collective basis. Good indicators thus must be designed to fit many different and varying purposes. The challenge is to devise indicators that serve these purposes by representing the intricacies that are inherent in urban areas, rather than by hiding that complexity.

MeSH terms

  • Data Collection / methods
  • Decision Making
  • Decision Support Techniques*
  • Environmental Health*
  • Health Policy*
  • Health Status Indicators*
  • Humans
  • Models, Theoretical
  • Time Factors
  • United Kingdom
  • Urban Health*