Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2024 May:258:114333.
doi: 10.1016/j.ijheh.2024.114333. Epub 2024 Mar 8.

Associations of prenatal ambient air pollution exposures with asthma in middle childhood

Affiliations

Associations of prenatal ambient air pollution exposures with asthma in middle childhood

Marnie F Hazlehurst et al. Int J Hyg Environ Health. 2024 May.

Abstract

We examined associations between prenatal fine particulate matter (PM2.5), nitrogen dioxide (NO2), and ozone (O3) exposures and child respiratory outcomes through age 8-9 years in 1279 ECHO-PATHWAYS Consortium mother-child dyads. We averaged spatiotemporally modeled air pollutant exposures during four fetal lung development phases: pseudoglandular (5-16 weeks), canalicular (16-24 weeks), saccular (24-36 weeks), and alveolar (36+ weeks). We estimated adjusted relative risks (RR) for current asthma at age 8-9 and asthma with recent exacerbation or atopic disease, and odds ratios (OR) for wheezing trajectories using modified Poisson and multinomial logistic regression, respectively. Effect modification by child sex, maternal asthma, and prenatal environmental tobacco smoke was explored. Across all outcomes, 95% confidence intervals (CI) included the null for all estimates of associations between prenatal air pollution exposures and respiratory outcomes. Pseudoglandular PM2.5 exposure modestly increased risk of current asthma (RRadj = 1.15, 95% CI: 0.88-1.51); canalicular PM2.5 exposure modestly increased risk of asthma with recent exacerbation (RRadj = 1.26, 95% CI: 0.86-1.86) and persistent wheezing (ORadj = 1.28, 95% CI: 0.86-1.89). Similar findings were observed for O3, but not NO2, and associations were strengthened among mothers without asthma. While not statistically distinguishable from the null, trends in effect estimates suggest some adverse associations of early pregnancy air pollution exposures with child respiratory conditions, warranting confirmation in larger samples.

Keywords: Developmental origins of health and disease; Particulate matter; air pollution; asthma.

PubMed Disclaimer

Conflict of interest statement

Disclosure of interest

The authors report there are no competing interests to declare.

Figures

Fig. 1.
Fig. 1.
Effect modification of associations between prenatal air pollution and current asthma at age 8–9 by child sex, prenatal environmental tobacco smoke exposure, and maternal history of asthma. Risk ratios for current asthma and corresponding 95% confidence intervals are shown for associations with NO2 in the first column (panels A, D, and G), O3 in the second column (panels B, E, and H), and PM2.5 in the third column (panels C, F, and I). Estimates are reported per 5 ppb NO2, 5 ppb O3, and 2 μg/m3 PM2.5. All models are adjusted for child age, sex, study site, birth year, maternal education, household income*household count, maternal race, maternal smoking during pregnancy, maternal history of asthma, and Neighborhood Deprivation Index, as well as a product term between the air pollutant exposure and effect modifier of interest. P-values for the product interaction term are included at the top of each panel. In the first row (panels A–C), sex-specific effect estimates are shown for models including the full analytic sample (N = 1279). No evidence of effect modification by child sex was observed (all pinteraction >0.05). In the second row (panels D–F), effect estimates are shown among those with maternal history of asthma and those without maternal history of asthma for models including the full analytic sample (N = 1279). For NO2 and PM2.5, those without maternal history of asthma tended to have higher risk ratios than among those with a maternal history of asthma (e.g. p-value for interaction of NO2 in the 24–36 week window and maternal asthma = 0.03), though confidence intervals for strata-specific risk ratios all include the null. In the third row (panels G–I), effect estimates are shown for associations in a post-hoc analysis among those with high versus low environmental tobacco smoke (ETS) exposure, when the sample was restricted to non-smokers (N = 1155). High ETS was defined as participants with a urinary cotinine value in the highest quartile of the sample (>1.43 ng/mL) and low ETS was defined as participants with a urinary cotinine value in the lowest three quartiles (≤1.43 ng/mL). No effect modification by ETS was observed (all pinteraction >0.05).

Similar articles

Cited by

References

    1. Aguilera I, Pedersen M, Garcia-Esteban R, Ballester F, Basterrechea M, Esplugues A, Fernández-Somoano A, Lertxundi A, Tardón A, Sunyer J, 2013. Early-life exposure to Outdoor air pollution and respiratory health, ear infections, and eczema in infants from the INMA study. Environmental Health Perspectives 121 (3), 387–392. 10.1289/ehp.1205281. - DOI - PMC - PubMed
    1. Asher M, Keil U, Anderson H, Beasley R, Crane J, Martinez F, Mitchell E, Pearce N, Sibbald B, Stewart A, et al., 1995. International study of asthma and Allergies in childhood (ISAAC): rationale and methods. Eur. Respir. J 8 (3), 483–491. 10.1183/09031936.95.08030483. - DOI - PubMed
    1. Benmarhnia T, Hajat A, Kaufman JS, 2021. Inferential challenges when assessing racial/ethnic health disparities in environmental research. Environ. Health 20 (1), 7. 10.1186/s12940-020-00689-5. - DOI - PMC - PubMed
    1. Bettiol A, Gelain E, Milanesio E, Asta F, Rusconi F, 2021. The first 1000 days of life: traffic-related air pollution and development of wheezing and asthma in childhood. A systematic review of birth cohort studies. Environ. Health 20 (1), 46. 10.1186/s12940-021-00728-9. - DOI - PMC - PubMed
    1. Bobb JF, Henn B, Valeri L, Coull BA, 2018. Statistical software for analyzing the health effects of multiple concurrent exposures via Bayesian kernel machine regression. Environmental Health 17 (67). 10.1186/s12940-018-0413-y. - DOI - PMC - PubMed