Exposure to Fine Particulate Matter Leads to Rapid Heart Rate Variability Changes

被引:12
作者
Riediker, Michael [1 ,2 ,3 ]
Franc, Yannick [4 ]
Bochud, Murielle [4 ]
Meier, Reto [2 ,5 ]
Rousson, Valentin [4 ]
机构
[1] Inst Occupat Med Singapore, Singapore, Singapore
[2] Univ Lausanne, Inst Univ Romand Sante Travail, Lausanne, Switzerland
[3] Nanyang Technol Univ, Sch Mat Sci & Engn, Singapore, Singapore
[4] Univ Lausanne, Inst Univ Med Sociale & Prevent, Lausanne, Switzerland
[5] Fed Off Environm, Bern, Switzerland
基金
瑞士国家科学基金会;
关键词
heart rate variability; fine particulate matter; acute exposure; homeostatic interference; ARIMA methodology; AMBIENT AIR-POLLUTION; PERSONAL EXPOSURE; ASSOCIATION; STATEMENT; PRESSURE; MARKERS; PANEL; RISK;
D O I
10.3389/fenvs.2018.00002
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Introduction: Heart Rate Variability (HRV) reflects the adaptability of the heart to internal and external stimuli. Reduced HRV is a predictor of post-infarction mortality. We previously found in road maintenance workers HRV-increases several hours after exposure to fine particulate matter (PM2.5). This seemed to conflict with studies where PM-exposure acutely reduced HRV. We therefore assessed whether time from exposure to HRV-assessment could explain the differences observed. Methods: On five non-consecutive days, workers carried nephelometers providing 1-min-interval PM2.5-exposure. Five-min HRV-intervals of SDNN (Standard Deviation of Normal to Normal beat intervals) and pNN50 (Percentage of the interval differences exceeding 50 ms) were extracted from 24-h electrocardiograms (ECGs). Following 60 min PM2.5-exposure, changes in HRV-parameters were assessed during 120-min visually and by regression analysis with control for time at work, at home, and during the night using autoregressive integrating moving average (ARIMA) models to account for autocorrelation of the time-series. Additional controls included changing the time windows and including body mass index (BMI) and age in the models. Result: Pattern analysis of 12,669 data points showed high modulation of mean, standard deviation (SD), and time trend of HRV (SDNN and pNN50) at low, and much reduced modulation at high PM2.5-exposures. The time trend following exposure was highly symmetrical, resembling a funnel plot. Regression analysis showed significant associations of decreasing SDNN and pNN50 (average, SD, and absolute value of time trend) with increasing PM2.5-exposure, which remained significant when controlling for activity phases. Changing time windows did not change the pattern of response. Including BMI and age did not change the results. Conclusions: The reduced modulation of HRV following PM2.5-exposure is striking. It suggests strong interference with homeostatic controls. Such an interference would represent a serious bodily burden, and could help explain acute cardiac events. In this model, the increase of HRV several hours later would reflect a recovery response.
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页数:9
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