Association between prenatal and childhood PM2.5 exposure and preadolescent anxiety and depressive symptoms

Abstract

Background: Fine particulate matter (PM2.5) exposure has been linked to anxiety and depression in adults; however, there is limited research in the younger populations, in which symptoms often first arise. Methods: We examined the association between early-life PM2.5 exposure and symptoms of anxiety and depression in a cohort of 8–11-year-olds in Mexico City. Anxiety and depressive symptoms were assessed using the Spanish versions of the Revised Children’s Manifest Anxiety Scale and Children’s Depression Inventory. Daily PM2.5 was estimated using a satellite-based exposure model and averaged over several early and recent exposure windows. Linear and logistic regression models were used to estimate the change in symptoms with each 5-µg/m3 increase in PM2.5. Models were adjusted for child’s age, child’s sex, maternal age, maternal socioeconomic status, season of conception, and temperature. Results: Average anxiety and depressive symptom T-scores were 51.0 (range 33–73) and 53.4 (range 44–90), respectively. We observed consistent findings for exposures around the fourth year of life, as this was present for both continuous and dichotomized anxiety symptoms, in both independent exposure models and distributed lag modeling approaches. This window was also observed for elevated depressive symptoms. An additional consistent finding was for PM2.5 exposure during early pregnancy in relation to both clinically elevated anxiety and depressive symptoms, this was seen in both traditional and distributed lag modeling approaches. Conclusion: Both early life and recent PM2.5 exposure were associated with higher mental health symptoms in the child highlighting the role of PM2.5 in the etiology of these conditions.

Particulate Matter Exposure during Pregnancy and Childhood Leukemia Incidence

“…For example, in the previously cited South Korean study [40], PM 10 exposure was calculated by collecting data from air quality monitoring stations throughout the country. But more recent studies have used satellite data to estimate PM exposure, such as the study conducted in Mexico published in 2024, which used a model combining satellite data and meteorological variables and land use variable [45], similar to the models used in our research [36]. These kinds of models exhibited a good performance and allow for the simulation and prediction of air quality in different regions and periods, using this data to estimate PM 2.5 exposure levels at residential addresses [46].…”