Assessing ambient air pollution's effects on birth outcomes: a Scottish IVF cohort study (2010 -2018)

Abstract

Background: Ambient air pollution exposure during and before the pregnancy could result in adverse birth outcomes. This study uses data from women undergoing in vitro fertilization (IVF) data to investigate the associations between ambient air pollution exposure and adverse birth outcomes.

Methods: This study analyses the associations between adverse birth outcomes, namely low birth weight (LBW), small for gestational age (SGA), and preterm birth and daily mean air pollution exposure during each of four IVF windows. The air pollutants considered were particulate matter with an aerodynamic diameter of less than 10 µm (PM₁₀) and 2.5 µm (PM_2.5), as well as nitrogen dioxide (NO₂), which were estimated using the Atmospheric Dispersion Modelling System (ADMS-Urban). This data was linked to the IVF patients' postcode providing estimates of exposure to air pollutants. Logistic regression models were used to quantify the associations between air pollution exposure and adverse birth outcomes, and conditioning confounding factors. A subgroup analysis was conducted to investigate the differences in the effects of ambient air pollution exposure on the ICSI and IVF groups.

Results: From January 2010 to May 2018, there are 2069 babies were able to be included in this study. We found no significant associations between air pollution exposure and the risk of adverse birth outcomes during window 1(85 days before oocyte retrieval) and 2 (14 days after gonadotrophin medication). With 1 µg⋅m^-3 increase in PM₁₀ concentration during window 3 (14 days after embryo transfer) and 4 (embryo transfer to delivery) led to a 5% (95% CI: 1.05-1.06) and 10% (95% CI: 1.01-1.21) increase in the odds of preterm birth, but not other outcomes. In window 3, every 1 µg⋅m^-3 increase in NO₂ concentrations resulted in a 2% (95% CI: 1.00 - 1.04) increase in the odds of LBW and a 3% (95% CI: 1.00 -1.05) increase in the odds of SGA but showed no effect for preterm birth. The results of the subgroup analysis suggest that the air pollution exposure may have a greater impact on the IVF group compared to the ICSI group.

Conclusion: The results suggest that exposure to air pollution during the very early stage of pregnancy (14 days after conception) may represent the most critical window of susceptibility to an increased risk of adverse birth outcomes.

Keywords: ADMS-Urban; Air pollution; ICSI; IVF; Low birth weight; Preterm birth; SGA.

Fig. 1

Studied regions in Scotland. For the postcode polygons, areas surrounding Glasgow, Edinburgh, Dundee, and Aberdeen are highlighted in blue, yellow, red, and green. Source: National Records of Scotland [37]. NRS Postcode polygon map. Background map © OpenStreetMap contributors [42]

Fig. 2

The exposure windows and process of IVF treatment. The studied windows are classified as follows: Window 1: 85 days before Oocyte retrieval. Window 2: 14 days from Gonadotrophin start to oocyte retrieval. Window 3: embryo transfer to biochemical pregnancy. Window 4: Embryo transfer to delivery

Fig. 3

Flowchart of patients included in this study. SMR02: Scottish Morbidity Records. HFEA: UK Human Fertilisation and Embryology Authority

Fig. 4

Directed acyclic graph for the relationship between air pollution exposure and adverse birth outcomes. This figure illustrating key confounding factors that identified by researchers in the association between air pollution and adverse birth outcomes. The identified confounding variables are the nodes connected to the causal paths (highlighted in pink colour). The confounding factors include the patient’s address (urban or rural), the occupation social class of both parents, the smoking history of both mother and father, and exposure to indoor air pollution. The confounding factors were selected based on the DAG and the availability of the variables. The adjusted variables are mother’s occupation social class and Mother smoking during pregnancy

Fig. 5

Forest plot showing the crude (top) and adjusted (bottom) odds ratios (ORs) with 95% confidence intervals (CIs) and p-values for the association between each 1 µg·m.⁻³ increase in air pollution concentrations and the odds of low birth weight across different exposure windows."‘*’ and ‘**’ indicate p-values less than 0.05 and 0.01, respectively. N refers to the number of cases included in the analysis. The adjusted variables include the mother's occupational social class (0—9) and smoking status during pregnancy (1 or 0)

Fig. 6

Forest plot showing the crude and adjusted odds ratios (ORs) with 95% confidence intervals (CIs) and p-values for the association between each 1 µg·m.⁻³ increase in air pollution concentrations and the odds of small in gestational age (SGA) across different exposure windows."‘*’ and ‘**’ indicate p-values less than 0.05 and 0.01, respectively. N refers to the number of cases included in the analysis. The adjusted variables include the mother's occupational social class (0—9) and smoking status during pregnancy (1 or 0)

Fig. 7

Forest plot showing the crude and adjusted odds ratios (ORs) with 95% confidence intervals (CIs) and p-values for the association between each 1 µg⋅m.⁻³ increase in air pollution concentrations and the odds of preterm birth across different exposure windows."‘*’ and ‘**’ indicate p-values less than 0.05 and 0.01, respectively. N refers to the number of cases included in the analysis. The adjusted variables include the mother's occupational social class (0—9) and smoking status during pregnancy (1 or 0)

Appendix Fig. 1

The process of linking the IVF data, Scotland health records (from SMR02 and national records), postcode and air pollution data

Appendix Fig. 2

Subgroup analysis forest plot showing the crude and adjusted odds ratios (ORs) with 95% confidence intervals (CIs) and p-values for the association between each 1µg×m^-3increase in air pollution concentrations and the odds of low birth weight across different exposure windows."‘*’ and ‘**’ indicate p-values less than 0.05 and 0.01, respectively. N refers to the number of cases included in the analysis. The adjusted variables include the mother's occupational social class (0 - 9) and smoking status during pregnancy (1 or 0)

Appendix Fig. 3

Subgroup analysis forest plot showing the crude and adjusted odds ratios (ORs) with 95% confidence intervals (CIs) and p-values for the association between each 1µg×m^-3increase in air pollution concentrations and the odds of preterm birth across different exposure windows."‘*’ and ‘**’ indicate p-values less than 0.05 and 0.01, respectively. N refers to the number of cases included in the analysis. The adjusted variables include the mother's occupational social class (0 - 9) and smoking status during pregnancy (1 or 0)

Appendix Fig. 4

Subgroup analysis forest plot showing the crude and adjusted odds ratios (ORs) with 95% confidence intervals (CIs) and p-values for the association between each 1µg×m^-3increase in air pollution concentrations and the odds of preterm birth across different exposure windows."‘*’ and ‘**’ indicate p-values less than 0.05 and 0.01, respectively. N refers to the number of cases included in the analysis. The adjusted variables include the mother's occupational social class (0 - 9) and smoking status during pregnancy (1 or 0)