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Data analysis techniques: a tool for cumulative exposure assessment

Journal of Exposure Science & Environmental Epidemiology volume 25, pages 222–230 (2015)Cite this article

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Abstract

Everyone is subject to environmental exposures from various sources, with negative health impacts (air, water and soil contamination, noise, etc.or with positive effects (e.g. green space). Studies considering such complex environmental settings in a global manner are rare. We propose to use statistical factor and cluster analyses to create a composite exposure index with a data-driven approach, in view to assess the environmental burden experienced by populations. We illustrate this approach in a large French metropolitan area. The study was carried out in the Great Lyon area (France, 1.2 M inhabitants) at the census Block Group (BG) scale. We used as environmental indicators ambient air NO2 annual concentrations, noise levels and proximity to green spaces, to industrial plants, to polluted sites and to road traffic. They were synthesized using Multiple Factor Analysis (MFA), a data-driven technique without a priori modeling, followed by a Hierarchical Clustering to create BG classes. The first components of the MFA explained, respectively, 30, 14, 11 and 9% of the total variance. Clustering in five classes group: (1) a particular type of large BGs without population; (2) BGs of green residential areas, with less negative exposures than average; (3) BGs of residential areas near midtown; (4) BGs close to industries; and (5) midtown urban BGs, with higher negative exposures than average and less green spaces. Other numbers of classes were tested in order to assess a variety of clustering. We present an approach using statistical factor and cluster analyses techniques, which seem overlooked to assess cumulative exposure in complex environmental settings. Although it cannot be applied directly for risk or health effect assessment, the resulting index can help to identify hot spots of cumulative exposure, to prioritize urban policies or to compare the environmental burden across study areas in an epidemiological framework.

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Acknowledgements

This work and the Equit’Area project are supported by the French National Research Agency (ANR, contract-2010-PRSP-002-01) and the EHESP School of Public Health. This research was also jointly supported by the Direction Générale de la Santé (DGS), the Caisse Nationale d’Assurance Maladie des Travailleurs Salariés (CNAMTS), the Régime Social des Indépendants (RSI), the Caisse Nationale de Solidarité pour l’Autonomie (CNSA), the Mission Recherche de la Direction de la Recherche, des Etudes, de l’Evaluation et des Statistiques (MiRe-DREES) and l’Institut national de prévention et de promotion de la santé (Inpes), under the research call launched by the French Institute of Public Health Research (IReSP) in 2010.

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Authors and Affiliations

  1. EHESP Rennes, Sorbonne Paris Cité, Rennes, France

    Benoît Lalloué, Cindy Padilla, Wahida Kihal, Denis Zmirou-Navier & Séverine Deguen

  2. Inserm, UMR1085-IRSET (Institut de Recherche sur la Santé L’environnement et le Travail), Rennes, France

    Benoît Lalloué, Cindy Padilla, Wahida Kihal, Denis Zmirou-Navier & Séverine Deguen

  3. Lorraine University, Institut Elie Cartan de Lorraine, CNRS UMR, Nancy, 7502, France

    Benoît Lalloué & Jean-Marie Monnez

  4. Lorraine University, INRIA, CNRS UMR7502, BIGS (INRIA Nancy — Grand Est/IECL), Nancy, France

    Benoît Lalloué & Jean-Marie Monnez

  5. Lorraine University Medical School, Nancy, France

    Denis Zmirou-Navier

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  1. Benoît Lalloué
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  2. Jean-Marie Monnez
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Correspondence to Séverine Deguen.

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Lalloué, B., Monnez, JM., Padilla, C. et al. Data analysis techniques: a tool for cumulative exposure assessment. J Expo Sci Environ Epidemiol 25, 222–230 (2015). https://doi.org/10.1038/jes.2014.66

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