Contents lists available at ScienceDirect Environmental Research journal homepage: www.elsevier.com/locate/envres Synergistic eﬀects of prenatal exposure to ﬁne particulate matter (PM 2.5 ) and ozone (O 3 ) on the risk of preterm birth: A population-based cohort study Nazeeba Siddika a,b , Aino K. Rantala a,b , Harri Antikainen c , Hamudat Balogun a,b , A. Koﬁ Amegah d , Niilo R.I. Ryti a,b , Jaakko Kukkonen e , Mikhail Soﬁev e , Maritta S. Jaakkola a,b , Jouni J.K. Jaakkola a,b,∗ a Center for Environmental and Respiratory Health Research, Faculty of Medicine, P.O. Box 5000, FI-90014, University of Oulu, Oulu, Finland b Medical Research Center Oulu, Oulu University Hospital, P.O. Box 8000, FI-90014, University of Oulu, Oulu, Finland c Geography Research Unit, P.O. Box 3000, 90014, University of Oulu, Oulu, Finland d Public Health Research Group, Department of Biomedical Sciences, University Post Oﬃce, University of Cape Coast, Cape Coast, Ghana e Finnish Meteorological Institute, P.O. Box 503, FI-00101, Helsinki, Finland ARTICLE INFO Keywords: Air pollution Fine particulates Ozone Prenatal exposure Preterm birth Interaction ABSTRACT Background: There is some evidence that prenatal exposure to low-level air pollution increases the risk of pre- term birth (PTB), but little is known about synergistic eﬀects of diﬀerent pollutants. Objectives: We assessed the independent and joint eﬀects of prenatal exposure to air pollution during the entire duration of pregnancy. Methods: The study population consisted of the 2568 members of the Espoo Cohort Study, born between 1984 and 1990, and living in the City of Espoo, Finland. We assessed individual-level prenatal exposure to ambient air pollutants of interest at all the residential addresses from conception to birth. The pollutant concentrations were estimated both by using regional-to-city-scale dispersion modelling and land-use regression–based method. We applied Poisson regression analysis to estimate the adjusted risk ratios (RRs) with their 95% conﬁdence intervals (CI) by comparing the risk of PTB among babies with the highest quartile (Q 4 ) of exposure during the entire duration of pregnancy with those with the lower exposure quartiles (Q 1 -Q 3 ). We adjusted for season of birth, maternal age, sex of the baby, family's socioeconomic status, maternal smoking during pregnancy, maternal exposure to environmental tobacco smoke during pregnancy, single parenthood, and exposure to other air pollutants (only in multi-pollutant models) in the analysis. Results: In a multi-pollutant model estimating the eﬀects of exposure during entire pregnancy, the adjusted RR was 1.37 (95% CI: 0.85, 2.23) for PM 2.5 and 1.64 (95% CI: 1.15, 2.35) for O 3 . The joint eﬀect of PM 2.5 and O 3 was substantially higher, an adjusted RR of 3.63 (95% CI: 2.16, 6.10), than what would have been expected from their independent eﬀects (0.99 for PM 2.5 and 1.34 for O 3 ). The relative risk due to interaction (RERI) was 2.30 (95% CI: 0.95, 4.57). Discussion: Our results strengthen the evidence that exposure to fairly low-level air pollution during pregnancy increases the risk of PTB. We provide novel observations indicating that individual air pollutants such as PM 2.5 and O 3 may act synergistically potentiating each other's adverse eﬀects. 1. Introduction Preterm birth (PTB), deﬁned as birth before 37 weeks of gestation is the leading cause of perinatal mortality and morbidity worldwide (Blencowe et al., 2013; Liu et al., 2012). A total of 14.9 million babies are born preterm each year worldwide (Blencowe et al., 2012; Goldenberg et al., 2008). In Finland, the occurrence of premature in- fants has been reported to be low, 5.7% of all births in 2013 (Vuori and Gissler, 2014). The causes of preterm birth are not yet well understood, but there is evidence that environmental exposures play a role in the https://doi.org/10.1016/j.envres.2019.108549 Received 6 March 2019; Received in revised form 14 June 2019; Accepted 18 June 2019 Abbreviations: FMI, Finnish Meteorological Institute; SILAM, The system for integrated modelling of atmospheric composition; UDM-FMI, Urban Dispersion Model- Finnish Meteorological Institute; CAR-FMI, Contaminants in the Air from a Road-Finnish Meteorological Institute ∗ Corresponding author. Center for Environmental and Respiratory Health Research, Faculty of Medicine, Aapistie 5B, P.O. Box 5000, FI-90014, University of Oulu, Oulu, Finland. E-mail address: jouni.jaakkola@oulu.ﬁ (J.J.K. Jaakkola). Environmental Research 176 (2019) 108549 Available online 19 June 2019 0013-9351/ © 2019 Elsevier Inc. All rights reserved. T