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Is atmospheric pollution exposure during pregnancy associated with individual and contextual characteristics? A nationwide study in France
  1. Marion Ouidir1,
  2. Johanna Lepeule1,2,
  3. Valérie Siroux1,
  4. Laure Malherbe3,
  5. Frederik Meleux3,
  6. Emmanuel Rivière4,
  7. Ludivine Launay5,
  8. Cécile Zaros6,
  9. Marie Cheminat6,
  10. Marie-Aline Charles6,7,
  11. Rémy Slama1
  1. 1 IAB, Team of Environmental Epidemiology applied to Reproduction and Respiratory Health, Inserm, CNRS, Université Grenoble Alpes joint research center, Grenoble, France
  2. 2 Exposure, Epidemiology, and Risk Program, Department of Environmental Health, Harvard School of Public Health, Boston, Massachusetts, USA
  3. 3 National Institute for Industrial Environment and Risks (INERIS), Verneuil en Halatte, France
  4. 4 ASPA, ATMO Grand Est, Schiltigheim, France
  5. 5 U1086 INSERM-UCN ‘Anticipe’, Caen, France
  6. 6 Ined-Inserm-EFS joint unit Elfe, Paris, France
  7. 7 Inserm Univ Paris Descartes, U1153 CRESS, Paris, France
  1. Correspondence to Dr Rémy Slama, Team of Environmental Epidemiology applied to Reproduction and Respiratory Health, Inserm U1209/CNRS UMR 5309/Université Grenoble Alpes joint research center, Institute for Advanced Biosciences, Site Santé, Allée des Alpes, La Tronche F-38700, France; remy.slama{at}univ-grenoble-alpes.fr

Abstract

Background Exposure to atmospheric pollutants is a danger for the health of pregnant mother and children. Our objective was to identify individual (socioeconomic and behavioural) and contextual factors associated with atmospheric pollution pregnancy exposure at the nationwide level.

Method Among 14 921 women from the French nationwide ELFE (French Longitudinal Study of Children) mother-child cohort recruited in 2011, outdoor exposure levels of PM2.5, PM10 (particulate matter <2.5 µm and <10 µm in diameter) and NO2 (nitrogen dioxide) were estimated at the pregnancy home address from a dispersion model with 1 km resolution. We used classification and regression trees (CART) and linear regression to characterise the association of atmospheric pollutants with individual (maternal age, body mass index, parity, education level, relationship status, smoking status) and contextual (European Deprivation Index, urbanisation level) factors.

Results Patterns of associations were globally similar across pollutants. For the CART approach, the highest tertile of exposure included mainly women not in a relationship living in urban and socially deprived areas, with lower education level. Linear regression models identified different determinants of atmospheric pollutants exposure according to the residential urbanisation level. In urban areas, atmospheric pollutants exposure increased with social deprivation, while in rural areas a U-shaped relationship was observed.

Conclusion We highlighted social inequalities in atmospheric pollutants exposure according to contextual characteristics such as urbanisation level and social deprivation and also according to individual characteristics such as education, being in a relationship and smoking status. In French urban areas, pregnant women from the most deprived neighbourhoods were those most exposed to health-threatening atmospheric pollutants.

  • air pollution
  • inequalities
  • nitrogen dioxide
  • particulate matter
  • socioeconomic status
  • social deprivation
  • urbanisation

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Footnotes

  • Contributors MO drafted and revised the manuscript, conducted data analysis, and contributed to the conception and interpretation. JL and RS contributed to the conception and interpretation, and revised the manuscript. RS had the original idea for the manuscript. MAC coordinates the ELFE cohort and revised the manuscript. MC contributed to the analysis and revised the manuscript. VS contributed to the interpretation and revised the manuscript. LM, FM, ER, LL and CZ contributed to the data collection and revised the manuscript. All authors accepted the final version of the manuscript.

  • Funding This work was partly supported by ANSES (the French Agency for Food, Environmental and Occupational Health & Safety; Grant No EST-10-130) in the context of the PATer (Pollution Atmosphérique sur le territoire français) project and by EU-funded project in the context of the SysCLAD study (HEALTH-F5-2012; Grant No 305457 under the Seventh Framework Program (FP7)). The ELFE cohort is supported by the French National Research Agency under the ‘Investments for the Future’ program, Grant No ANR-11-EQPX-0038. MO benefits of a doctoral grant from Université Grenoble Alpes and RS is supported by a consolidator grant from the European Research Council (ERC consolidator Grant No 311765-E-DOHaD).

  • Competing interests None declared.

  • Patient consent Obtained.

  • Ethics approval CNIL, Commission nationale de l’informatique et des libertés; CCTIRS, Comité consultatif sur le traitement de l’information en matière de recherche dans le domaine de la santé; CNIS, Conseil national de l'information statistique.

  • Provenance and peer review Not commissioned; externally peer reviewed.

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