Birth Cohort Studies of Long-Term Exposure to Ambient Air Pollution in Early Life and Development of Asthma in Children and Adolescents from Denmark.

Introduction: Exposure to ambient air pollution from combustion-source emissions contributes to the prevalence of asthma, but the role of early-life exposure in asthma development is not well understood. The objective was to examine the effects of early-life exposure to multiple specific ambient air pollutants on incidence and prevalence of asthma and to determine the mechanistic basis for these effects.

Methods: The study included all live-born singletons in Denmark during 1998-2016 (N = 1,060,154), participants in the Danish National Birth Cohort (DNBC³, N = 22,084), and participants in the Copenhagen Prospective Studies on Asthma in Childhood (COPSAC, N = 803). We modeled the concentrations of particulate matter ≤2.5 and ≤10 μm in aerodynamic diameter (PM_2.5 and PM₁₀), PM-related elemental carbon (EC), organic carbon (OC), sulfate (SO₄^2-), nitrate (NO₃^-), ammonium (NH₄⁺), secondary organic aerosols (SOA), and sea salt as well as nitrogen dioxide (NO₂), nitrogen oxides (NO_x), sulfur dioxide (SO₂), and ozone (O₃) - from all sources. Prenatal and postnatal time-weighted mean exposures were calculated for all residential addresses.

We defined asthma incidence as the first registered asthma diagnosis for all and used parental recall at child aged 7 to determine the prevalence of doctor-diagnosed asthma ever and active asthma for the DNBC participants. For the COPSAC participants, we analyzed inflammatory markers in blood collected at 6 months of age; at 6 years of age, we analyzed nasal epithelial deoxyribonucleic acid (DNA) methylation, gene expression, immune mediators, and forced expiratory volume in 1 second (FEV₁).

Cox proportional hazard models were fitted with fixed prenatal means and time-varying running annual means of a year before the event for the postnatal follow-up period for asthma incidence. Logistic regression models with cluster-robust standard errors and generalized estimating equations for dependence between women being included more than once were used for asthma prevalence. Mixed-effect linear regression models with random intercept for cohort were used to examine changes in lung function, and linear regression models were used to examine changes in biomarkers.

Results: The prenatal mean and interquartile range (IQR) concentrations of PM_2.5 and NO₂ were 10.5 (2.4) and 17.5 (8.7) μg/m³. In the nationwide study the risk of asthma incidence increased with increasing prenatal exposure to all pollutants except for O₃ and sea salt. An IQR increase in prenatal exposure was associated with an adjusted hazard ratio (HR) and 95% confidence interval (CI) of 1.06 (95% CI: 1.04-1.08) for PM_2.5 and 1.04 (1.02-1.05) for NO₂. The corresponding estimates for postnatal exposures were 1.08 (1.05-1.10) and 1.02 (1.01-1.04), respectively.

In the DNBC participants, the asthma incidence results from models further adjusted with cohort-specific covariates were similar to models adjusted for register-based covariates only. Prenatal exposure to PM_2.5, PM₁₀, NO₂, NO_x, EC, SO₄^2-, and sea salt were weakly associated with elevated risk for asthma incidence. There was no evidence of associations with asthma prevalence.

For the COPSAC children, an IQR of PM_2.5 and of NH₄⁺ was each associated with a 2%-3% (95% CI: 1%-5%) reduction in mean FEV₁, consistently for prenatal and postnatal exposures. Prenatal exposure to PM and NO₂ was associated with immunological changes in blood and the airways but not with DNA methylation or gene expression changes.

Conclusions: The results of these studies strengthen the evidence that long-term exposure to ambient air pollution contributes to the development of asthma in early life through an altered immune profile, even at these relatively low concentrations.