Exposure to Traffic Density during Pregnancy and Birth Weight in a National Cohort, 2000-2017

Int J Environ Res Public Health. 2022 Jul 15;19(14):8611. doi: 10.3390/ijerph19148611.

Abstract

The variation on birth weight is associated with several outcomes early on in life and low birth weight (LBW) increases the risk of morbidity and mortality. Some environmental exposures during pregnancy, such as particulate matters and other traffic-related pollutants can have a significant effect on pregnant women and fetuses. The aim of this study is to estimate the effect of exposure to traffic density during pregnancy over birth weight in Spain, from 2000-2017. This was a retrospective, cross-sectional study using the information from Spain Birth Registry Statistics database. The traffic density was measured using the Annual average daily traffic. Multivariate linear regression models using birth weight and traffic density were performed, as well as a logistic regression model to estimated Odds ratios for LBW and GAM models to evaluate the non-linear effect. Our findings showed that increases in traffic density were associated with reduction of birth weight and increases of LBW risk. Moreover, exposure to high and very-high traffic-density during pregnancy were associated with reduction of birth weight and increase on LBW risk comparing with exposure to low number of cars trespassing the neighborhoods. The results of this study agree with previous literature and highlights the need of effective policies for reducing traffic density in residential neighborhoods of cities and towns.

Keywords: low birthweight; pregnancy; road congestion; traffic-related air pollution.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Air Pollutants* / analysis
  • Air Pollution* / analysis
  • Birth Weight
  • Cross-Sectional Studies
  • Female
  • Humans
  • Logistic Models
  • Maternal Exposure
  • Particulate Matter / analysis
  • Pregnancy
  • Retrospective Studies

Substances

  • Air Pollutants
  • Particulate Matter

Grants and funding

This work was supported by the Spanish Consortium for Research on Epidemiology and Public Health(CIBERESP) (ESP20PI01/2020) and Spanish Institute of Health Carlos III (PI19CIII-00025. Mònica Guxens is funded by a Miguel Servet II fellowship (CPII18/00018) awarded by the Spanish Institute of Health Carlos III. We also acknowledge support from the Spanish Ministry of Science and Innovation and the State Research Agency through the “Centro de Excelencia Severo Ochoa 2019–2023” Program (CEX2018-000806-S), and support from the Generalitat de Catalunya through the CERCA Program.