Abstract

BackgroundTraffic-related air pollution has been associated to a range of adverse health impacts, including decreased heart rate variability (HRV). The association between traffic-related pollution and HRV, however, has varied by traffic-related or HRV marker as well as by study, suggesting the need for a more comprehensive and integrative approach to examining air pollution-mediated biological impacts on these outcomes. In a Bayesian framework, we examined the effect of traffic pollution on HRV using structural equation models (SEMs) and looked at effect modification by participant characteristics.MethodsWe studied measurements of 5 HRV markers [high frequency (HF), low frequency (LF), 5-min standard deviation of normal-to-normal intervals (SDNN), square root of the mean squared differences of successive normal-to-normal intervals (rMSSD), and LF/HF ratio (LF/HF)] for 700 elderly men from the Normative Aging Study. Using SEMs, we fit a latent variable for traffic pollution that is reflected by levels of carbon monoxide, nitrogen monoxide, nitrogen dioxide, and black carbon (BC) to estimate its effect on latent variable for parasympathetic tone that included HF, SDNN and rMSSD, and the sympathetic tone marker, LF/HF. Exposure periods were assessed using 4-, 24-, 48-, 72-hour moving average pre-visit. We compared our main effect findings using SEMs with those obtained using linear mixed models.ResultsTraffic pollution was not associated with mean parasympathetic tone and LF/HF for all examined moving averages. In Bayesian linear mixed models, however, BC was related to increased LF/HF, an inter quartile range (IQR) increase in BC was associated with a 6.5% (95% posterior interval (PI): -0.7%, 14.2%) increase in mean LF/HF 24-hours later. The strongest association observed was for the 4-hour moving average (10.1%; 95% PI: 3.0%, 17.6%). The effect of traffic on parasympathetic tone was stronger among diabetic as compared to non-diabetic participants. Specifically, an IQR increase in traffic pollution in the 48-hr prior to the clinic visit was associated with a 44.3% (95% PI: -67.7%, -4.2%) lower mean parasympathetic tone among diabetics, and a 7.7% (95% PI: -18.0%, 41.4%) higher mean parasympathetic tone among non-diabetics.ConclusionsBC was associated with adverse changes LF/HF in the elderly. Traffic pollution may decrease parasympathetic tone among diabetic elderly.

Highlights

  • Traffic-related air pollution has been associated to a range of adverse health impacts, including decreased heart rate variability (HRV)

  • We develop in a Bayesian framework Structural equation model (SEM) to examine separately the impact of short-term changes in traffic pollution on parasympathetic tone, and a sympathetic tone marker, the low frequency HRV (LF) to high frequency HRV (HF) ratio (LF/HF), among participants in the Normative Aging Study (NAS)

  • Statistical analysis We examined the association between latent traffic pollution and latent parasympathetic tone and between latent traffic pollution and sympathetic tone marker, LF/ HF, using SEMs in a Bayesian framework that account for repeated measures

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Summary

Introduction

Traffic-related air pollution has been associated to a range of adverse health impacts, including decreased heart rate variability (HRV). Schwartz et al in 2005 found associations between traffic-related pollution exposures and disturbances of autonomic control of the heart as measured through heart rate variability (HRV), a measure of naturally occurring beat-to-beat interval in heart rate [4]. This association between traffic-related pollution and HRV, has varied by traffic-related pollutants or HRV markers as well as by study, suggesting the need for a more comprehensive and integrative approach to examining air pollution-mediated biological impacts on these outcomes and in addition to consider multiple traffic-related pollutants and multiple health markers simultaneously. The hope is that the total mean squared error (bias squared + variance) is lower than uncorrected estimate

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