Associations of arsenic exposure with blood pressure and platelet indices in pregnant women: A cross-sectional study in Wuhan, China.

ABSTRACT

BACKGROUND: Environmental inorganic arsenic (iAs) exposure is potentially related to abnormal blood pressure (BP) changes and abnormal platelet activation. However, limited epidemiological studies have explored the impacts of iAs exposure on platelet change mediated by BP, especially for pregnant women. OBJECTIVES: Our purpose was to investigate the associations of arsenic exposure with blood pressure and platelet indices among pregnant women. METHODS: The present study population included 765 pregnant women drawn from a prospective birth cohort study in Wuhan, China, recruited between October 2013 and April 2016. Urine sampled in the second trimester were used to assess arsenic species concentrations. The relative distribution of urinary arsenic species was used to measure human methylation capacity. BP parameters and platelet indices originated from the medical record. We applied multivariable linear regression models to explore the cross-sectional relationships between urinary arsenic metabolites, BP parameters, and platelet indices. We utilized mediation analysis to investigate the impacts of arsenic exposure on platelet indices through BP as mediator variables. RESULTS: We observed significant positive correlations between iAs and systolic BP (SBP), diastolic BP (DBP), and mean arterial pressure (MAP). Pregnant women with higher methylation capacity to metabolize iAs characterized by higher secondary methylation index (SMI) and total methylation index (TMI) had a more significant reduction in SBP, DBP, and MAP. Pregnant women with higher DBP and MAP had higher platelet counts (PLC). A decreased PLC was found in subjects wither higher SMI. Additionally, SMI was negatively linked to PLC mediated through MAP. CONCLUSIONS: Obtained results suggested that higher methylation capacity to metabolize iAs might contribute to decreased PLC among pregnant women, and MAP might mediate the influence of SMI on PLC.