**6. Conclusions**

In a public health perspective, regarding maternal and child practice, individual-level interventions predominate. However, adverse birth outcomes result from a complex combination of individual determinants and behavior of the parents (more particularly the mother during pregnancy) and the characteristics of the place where people live requiring appropriate ecological approaches.

Today, spatial approach constitutes a powerful tool to use in the context of the life course perspective of health, and more specifically in reproductive health [117]. A healthy pregnan<sup>t</sup> woman is more likely to have a healthy newborn. In addition, neonates born in healthier place of residence in term of environmental exposure and, living and social conditions will tend to have better health trajectories throughout their life. The theoretical model suggests that adverse exposures (including characteristics of the place where people live) accumulate over time since the birth and will increase adverse outcomes during the adulthood period. In this context, this study is an attempt to fill the gap regarding a need for spatial approaches to support priority setting and guide policy makers in their choice of health interventions in general and on birth outcomes in particular. Our findings underscore the area with increased risk for preterm birth where local authorities should focus their resources and efforts to reduce health inequalities regarding birth outcomes. They highlight significant spatial implication of neighborhood characteristics including socioeconomic deprivation level and maternal

exposure to ambient air NO2, and their combination, which could guide policymakers in choosing and developing the most appropriate and specific community-oriented interventions. We hope that in the future this kind of approach will be more often used in public health studies especially in life courses perspectives.

**Supplementary Materials:** The following are available online at http://www.mdpi.com/1660-4601/15/9/1895/s1, Figure S1: Scatterplot matrix of NO2, PM10 and PM2.5, Table S1: Correlation Matrix between NO2, PM10 and PM2.5.

**Author Contributions:** Conceptualization, S.D. and W.K.; Methodology, S.D., W.K., N.A. and M.G.; Validation, S.D., W.K., M.C., A.D. and D.Z.N.; Formal Analysis, S.D., W.K., N.A.; Investigation, S.D. and W.K.; Writing-Original Draft Preparation, S.D., W.K., N.A., M.C., A.D. and D.Z.N.; Writing-Review & Editing, S.D. and W.K.; Supervision, S.D. and W.K.

**Funding:** This study was supported by Foundation de France: 201300040943.

**Acknowledgments:** The authors thank all scientific researchers of the Equit' Area project and the personnel of the local association in air quality of Paris Metropolitan Area.

**Conflicts of Interest:** The authors declare they have no actual or potential competing financial interests.
