Maternal exposure to ambient PM2.5 and term birth weight: A systematic review and meta-analysis of effect estimates

Effect estimates of prenatal exposure to ambient PM2.5 on change in grams (3) of birth weight among term births (>= 37 weeks of gestation; term birth weight, TBW) vary widely across studies. We present the first systematic review and meta-analysis of evidence regarding these associations. Sixty-two studies met the eligibility criteria for this review, and 31 studies were included in the meta-analysis. Random-effects meta-analysis was used to assess the quantitative relationships. Subgroup analyses were performed to gain insight into heterogeneity derived from exposure assessment methods (grouped by land use regression [LUR]-models, aerosol optical depth [AOD]-based models, interpolation/dispersion/Bayesian models, and data from monitoring stations), study regions, and concentrations of PM2.5 exposure. The overall pooled estimate involving 23,925,941 newborns showed that TBW was negatively associated with PM2.5 exposure (per 10 mu g/m(3) increment) during the entire pregnancy (beta = -16.54 g), but with high heterogeneity (I2 = 95.6%). The effect estimate in the LUR-models subgroup (3 = -16.77 g) was the closest to the overall estimate and with less heterogeneity (I-2 = 18.3%) than in the other subgroups of AOD-based models (beta = -41.58 g; I-2 = 95.6%), interpolation/dispersion models (beta = -10.78 g; I-2 = 86.6%), and data from monitoring stations (beta = -11.53 g; I-2 = 97.3%). Even PM2.5 exposure levels of lower than 10 mu g/m(3) (the WHO air quality guideline value) had adverse effects on TBW. The LUR-models subgroup was the only subgroup that obtained similar significant of negative associations during the three trimesters as the overall trimester-specific analyses. In conclusion, TBW was negatively associated with maternal PM2.5 exposures during the entire pregnancy and each trimester. More studies based on relatively standardized exposure assessment methods need to be conducted to further understand the precise susceptible exposure time windows and potential mechanisms. (C) 2021 Elsevier B.V. All rights reserved.