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Reframing the environment in data-intensive health sciences.

Stefano Canali1, Sabina Leonelli2

  • 1Department of Electronics, Information and Bioengineering and META - Social Sciences and Humanities for Science and Technology, Politecnico di Milano, Milan, Italy.

Studies in History and Philosophy of Science
|May 16, 2022
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Summary
This summary is machine-generated.

Contemporary health sciences increasingly use environmental data, leading to conceptual shifts in understanding the environment and health. This analysis explores how diverse data sources and novel tools reshape environmental exposure and causality in epidemiology.

Keywords:
Big dataEnvironmentEpidemiologyExposure

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Area of Science:

  • Environmental Health Sciences
  • Epidemiology
  • Data Science

Background:

  • Contemporary health sciences increasingly utilize diverse environmental data.
  • The integration of environmental data necessitates re-evaluating the concept of 'environment' in health research.
  • Data-intensive epidemiology faces challenges in conceptualizing and operationalizing environmental factors.

Purpose of the Study:

  • To analyze the relationship between environmental data use in health sciences and conceptualizations of the environment.
  • To examine three case studies demonstrating different data selections and integration methods in epidemiology.
  • To identify conceptual shifts in environmental health research driven by novel data and analytical tools.

Main Methods:

  • Analysis of three case studies in data-intensive epidemiology.
  • Examination of the EXPOsOMICS project integrating genomic and environmental data.
  • Exploration of the MEDMI platform combining health, environmental, and climate data.
  • Illustration of epidemiological insights from social data via the CIDACS institute.

Main Results:

  • The EXPOsOMICS project reframes boundaries between external and internal environments.
  • The MEDMI platform expands the concept of environmental exposure by integrating climate data.
  • Analysis of social data reveals innovative attributions of causal power to environmental factors.
  • Diversification of data sources and analytical tools drive conceptual shifts in environmental health.

Conclusions:

  • New environmental data offer significant benefits and opportunities for understanding and improving health.
  • Challenges exist in conceptualizing health impacts due to data selection and accessibility constraints.
  • Novel data integration in epidemiology reshapes understanding of environmental influences on health outcomes.