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Dimensions of Health and Illness01:21

Dimensions of Health and Illness

The factors influencing the health-illness continuum can be internal or external and may or may not be under conscious control. They are related to the following eight human dimensions, and each dimension is interrelated to one other.

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Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data
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Assessing external exposome by implementing an Environmental Data Management System using Open Data.

Sofia Tagliaferro1,2, Sara Maio1, Federico Pirona1

  • 1Pulmonary Environmental Epidemiology Unit, National Research Council (CNR), Institute of Clinical Physiology (IFC), Pisa, Italy.

Scientific Reports
|July 26, 2024
PubMed
Summary
This summary is machine-generated.

An Environmental Data Management System (EDMS) using open data was evaluated for its feasibility and usefulness in environmental epidemiology. Findings highlight significant variations in health and environmental factors across 10 European cities.

Keywords:
Air qualityLifestyleNoisePesticidesPollenWater quality

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Area of Science:

  • Environmental Epidemiology
  • Public Health
  • Environmental Science

Background:

  • The exposome concept is increasingly vital in environmental epidemiology.
  • An Environmental Data Management System (EDMS) was developed to manage exposome data.
  • Open data principles were employed to enhance data accessibility and utility.

Purpose of the Study:

  • To evaluate the feasibility and usefulness of an EDMS for environmental epidemiology.
  • To analyze external exposome factors across 10 European cities.
  • To identify potential public health interventions based on environmental data.

Main Methods:

  • An EDMS was created using open data from 10 European cities (2017-2020).
  • Data included external non-specific and specific exposome factors at city/country levels.
  • Key health indicators (life expectancy, obesity, drug consumption, smoking, alcohol) and environmental exposures (air pollution, pollen, noise, water contaminants, pesticides) were analyzed.

Main Results:

  • Significant variations in life expectancy, obesity, drug consumption, smoking, and alcohol intake were observed across cities.
  • Highest pollution levels: Thessaloniki (PM10), Łódź (PM2.5), Porto (NO2), Rijeka (O3).
  • Highest grey space in Thessaloniki (98%), pollen in Łódź (39,041 p/m3), noise in Reus (81% traffic). Arsenic in Thessaloniki, boron in Celje, lead in Paris drinking water.
  • Highest pesticide residues in Portugal and Greece (7%).

Conclusions:

  • Utilizing open-access databases and EDMS facilitates the translation of research findings into actionable public health strategies.
  • The study demonstrates the value of integrated environmental data for understanding population health.
  • Identified environmental and health disparities underscore the need for targeted public health interventions.