Causal Effects of Prenatal Exposure to PM 2.5 on Child Development and the Role of Unobserved Confounding

Viola Tozzi, Aitana Lertxundi, Jesus M. Ibarluzea and Michela Baccini
Additional contact information
Viola Tozzi: Department of Statistics, Computer Science, Applications, University of Florence, 59 50134 Florence, Viale Morgagni, Italy, viola.t@hotmail.it
Aitana Lertxundi: BIODONOSTIA Health Research Institute, 20014 San Sebastian, Spain
Jesus M. Ibarluzea: BIODONOSTIA Health Research Institute, 20014 San Sebastian, Spain
Michela Baccini: Department of Statistics, Computer Science, Applications, University of Florence, 59 50134 Florence, Viale Morgagni, Italy, viola.t@hotmail.it

IJERPH, 2019, vol. 16, issue 22, 1-12

Abstract: Prenatal exposure to airborne particles is a potential risk factor for infant neuropsychological development. This issue is usually explored by regression analysis under the implicit assumption that all relevant confounders are accounted for. Our aim is to estimate the causal effect of prenatal exposure to high concentrations of airborne particles with a diameter < 2.5 µm (PM2.5) on children’s psychomotor and mental scores in a birth cohort from Gipuzkoa (Spain), and investigate the robustness of the results to possible unobserved confounding. We adopted the propensity score matching approach and performed sensitivity analyses comparing the actual effect estimates with those obtained after adjusting for unobserved confounders simulated to have different strengths. On average, mental and psychomotor scores decreased of −2.47 (90% CI: −7.22; 2.28) and −3.18 (90% CI: −7.61; 1.25) points when the prenatal exposure was ≥17 μg/m 3 (median). These estimates were robust to the presence of unmeasured confounders having strength similar to that of the observed ones. The plausibility of having omitted a confounder strong enough to drive the estimates to zero was poor. The sensitivity analyses conferred solidity to our findings, despite the large sampling variability. This kind of sensitivity analysis should be routinely implemented in observational studies, especially in exploring new relationships.

Keywords: child development; airborne particles; propensity score matching; sensitivity analysis; bias analysis; Monte Carlo simulations (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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