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

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. 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 (PM2.5 and PM10), PM-related elemental carbon (EC), organic carbon (OC), sulfate (SO42-), nitrate (NO3-), ammonium (NH4+), secondary organic aerosols (SOA), and sea salt as well as nitrogen dioxide (NO2), nitrogen oxides (NOx), 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. The prenatal mean and interquartile range (IQR) concentrations of PM2.5 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 PM2.5 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 PM2.5, PM10, NO2, NOx, EC, SO42-, 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 PM2.5 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. 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.