Associations between Personal Exposure to Metals in Fine Particulate Matter and Autonomic Nervous System Dysfunction among Healthy Adults

• Published in: Aerosol and air quality research Vol. 20; no. 8; pp. 1842 - 1849
• Main Authors: Liao, Yi-Hsueh, Chen, Wei-Liang, Wang, Chung-Ching, Lai, Ching-Huang
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01.08.2020; Taiwan Association of Aerosol Research; Springer
• Subjects: Adults; Air pollution; Airborne particulates; Autonomic nervous system; Blood-brain barrier; Brain research; Emissions; Exposure; Gallium; Heart rate; Heavy metals; Humidity; Hypotheses; Metal concentrations; Metals; Nervous system; Noise; Particulate emissions; Particulate matter; Questionnaires; Reference materials; Special Session on Pulmonary and Neurological Health Impacts from Airborne Particulate Matter (II); Standard deviation; Urban areas; Young adults; United States > US; Taiwan; Autonomic nervous system; Particulate matter; Metals
• ISSN: 1680-8584; 2071-1409; 2071-1409
• DOI: 10.4209/aaqr.2020.04.0156

The impact of airborne particulate matter and its metal components on autonomic nervous system (ANS) dysfunction in healthy subjects remains unclear. The aim of this study was to examine the effects of personal exposure to airborne particulate matter on the ANS in young, healthy adults. This longitudinal study recruited 82 adults aged 20 to 35 years from districts A and B. District A had lower ambient PM 2.5 levels than district B. Personal exposure to fine particulate matter and metals in PM 2.5 was collected every two months. The heart rate variability (HRV) indices of each participant were measured three times. The relationship among the PM 2.5 concentration, metals in PM 2.5 and HRV level was investigated by a generalized estimating equation with an autoregression of order 1. The average age of the participants was 26.4 ± 3.6 years in district A and 21.9 ± 1.5 years in district B ( p < 0.001). After adjusting for covariables, significant changes in Log 10 standard deviation of normal to normal (SDNN) intervals and Log 10 square root of the mean of the sum of the squares of differences (r-MSSDs) were related to unit changes in Log 10 iron in PM 2.5 (β = −0.033, 95% CI = −0.060 to -0.0056, p < 0.05 and β = −0.041, 95% CI = −0.075 to −0.0076, p < 0.05, respectively). The Log 10 SDNN levels were significantly positively related to Log 10 gallium in PM 2.5 (β = 0.054, 95% CI = 0.0064 to 0.10, p < 0.05). Exposure to heavy metals in airborne particulate matter was associated with ANS dysfunction.