Prenatal Exposure to Metal Mixture and Birth Weight; a Bayesian Kernel Machine Regression Analysis of Two Cohort Studies in Japan and Iran

Abstract Purpose Potentially toxic metals can directly induce various adverse effects on reproductive organs or interrupt essential metals' physiological activities. Despite intensive efforts to reduce these metals in the environment, chronic and low-level exposure remains a public health problem. The present study aimed to investigate prenatal metal exposure, including arsenic (As), copper (Cu), lead (Pb), manganese (Mn), rubidium (Rb), selenium (Se), and zinc (Zn), effects on birth weight. Methods We collected 579 blood samples before the 16th week of gestation from apparently healthy women with singleton pregnancy in Iran and Japan. Blood metal concentrations were measured using inductively coupled plasma-mass spectrometry. Results Prenatal blood levels of As, Mn, Pb, and Zn were significantly higher, while Cu, Rb, and Se were significantly (p < 0.01) lower in Iranian participants than in Japanese. Adjusted linear regression analyses and Bayesian Kernel Machine Regression (BKMR) overall exposure-response functions showed inverse relationships between metals and birth weight. Conclusion The study findings, using data from geographically diverse countries, suggest prenatal blood metal exposure as a potential risk factor for lower birth weight. Therefore, women of reproductive age should minimize encountering to potentially toxic metals as much as possible.