Exposure to air pollution and noise from road traffic and risk of congenital anomalies in the Danish National Birth Cohort

Research output: Contribution to journalJournal articleResearchpeer-review

Background: Ambient air pollution has been associated with certain congenital anomalies, but few studies rely on assessment of fine-scale variation in air quality and associations with noise from road traffic are unexplored.

Methods: Among 84,218 liveborn singletons (1997–2002) from the Danish National Birth Cohort with complete covariate data and residential address history from conception until birth, we identified major congenital anomalies in 4018 children. Nitrogen dioxide (NO2) and noise from road traffic (Lden) burden during fetal life was modeled. Outcome and covariate data were derived from registries, hospital records and questionnaires. Odds ratios (ORs) for eleven major anomaly groups associated with road traffic pollution during first trimester were estimated using logistic regression with generalized estimating equation (GEE) approach.

Results: Most of the associations tested did not suggest increased risks. A 10-µg/m3 increase in NO2 exposure during first trimester was associated with an adjusted ORs of 1.22 (95% confidence interval: 0.98–1.52) for ear, face and neck anomalies; 1.14 0.98–1.33) for urinary anomalies. A 10-dB increase in road traffic noise was also associated with these subgroups of anomalies as well as with an increased OR for orofacial cleft anomalies (1.17, 0.94–1.47). Inverse associations for several both air pollution and noise were observed for atrial septal defects (0.85, 0.68–1.04 and 0.81, 0.65–0.99, respectively).

Conclusions: Residential road traffic exposure to noise or air pollution during pregnancy did not seem to pose a risk for development of congenital anomalies.
Original languageEnglish
JournalEnvironmental Research
Pages (from-to)39-45
Number of pages7
Publication statusPublished - Nov 2017

    Research areas

  • Air pollution, Cohort, Congenital anomalies, Noise, Traffic

ID: 185846801