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城市规模与一氧化碳(CO)浓度的关系及其对心率变异性(HRV)的影响。

The Relationship between City Size and Carbon Monoxide (CO) Concentration and Their Effect on Heart Rate Variability (HRV).

机构信息

Porter School of the Environmental and Earth Sciences, The Faculty of Exact Sciences, Tel Aviv University, Tel-Aviv-Jaffa 66978, Israel.

Bnei Zion Medical Center, (Emeritus) the Rappaport Family Faculty of Medicine, The Technion, Israel Institute of Technology, Haifa 23774, Israel.

出版信息

Int J Environ Res Public Health. 2021 Jan 18;18(2):788. doi: 10.3390/ijerph18020788.

DOI:10.3390/ijerph18020788
PMID:33477714
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7831902/
Abstract

Generally, larger cities are characterized by traffic congestion, which is associated with higher concentrations of pollution, including Carbon Monoxide (CO) pollution. However, this convention requires empirical support on the basis of accurate and reliable measurements. In addition, the assessment of the effect of CO on the autonomic nervous system (ANS), as measured by heart rate variability (HRV), has yielded conflicting results. A majority of the (few) studies on the topic have shown that increases in CO concentration of up to about 10 parts per million (ppm) are associated with a decrease in stress and risk to health in subjects. Beyond the hypothesis postulating city size as a determinant of increased CO concentration, the hypothesis proposing a causal link between CO concentration and HRV balance also requires empirical support. This article compares CO concentrations in a large metropolis with those in a small town, analyzing the relationship between CO and the HRV responses of young women in terms of city size. Four different types of environments were compared, taking into account mediating variables. The study participants spent 35 min in selected environments (a city center, a residential environment, a park, and a home) wearing Polar devices to measure HRV, and portable devices to measure noise thermal load and CO. The average concentrations of CO in each environment were calculated, along with the time distribution of the CO concentration, and the regression slopes between the concentrations of CO and the ANS balance, as measured by the low frequency power/high frequency power ratio (LF/HF) expressed as an HRV index. The results show that, regardless of size, the cities measured were all characterized by low levels of CO, far below the maximal accepted threshold standards, and that urban residents were exposed to these concentrations for less than half of the daytime hours. Furthermore, in contrast to the common view, larger cities do not necessarily accumulate higher concentrations of CO compared to small cities, regardless of the level of transport congestion. This study confirms the findings of the majority of the other studies on the subject, which showed a decrease in stress (as measured by HRV) as a result of an increase in CO concentrations below 7 ppm. Finally, following the assessment of the differential contribution attributed to the different environmental factors, it appears that noise, thermal load, and congestion all contribute more to a higher level of HRV balance than CO. This finding highlights the importance of a multivariable approach to the study, and a remediation of the effect of environmental factors on stress in urban environments.

摘要

一般来说,大城市的特点是交通拥堵,这与包括一氧化碳(CO)污染在内的更高浓度的污染有关。然而,这一惯例需要基于准确可靠的测量结果来提供经验支持。此外,CO 对自主神经系统(ANS)的影响评估,如心率变异性(HRV)所示,结果相互矛盾。关于这一主题的大多数(少数)研究表明,CO 浓度增加到约 10 百万分率(ppm)以内与受试者的压力降低和健康风险降低有关。除了假设城市规模是 CO 浓度增加的决定因素之外,假设 CO 浓度与 HRV 平衡之间存在因果关系的假设也需要经验支持。本文比较了一个大城市和一个小镇的 CO 浓度,分析了城市规模对年轻女性 CO 和 HRV 反应之间关系的影响。考虑到中介变量,比较了四种不同类型的环境。研究参与者在选定的环境中(市中心、居住环境、公园和家庭)佩戴 Polar 设备测量 HRV 并使用便携式设备测量噪声热负荷和 CO 35 分钟。计算了每个环境中的 CO 平均浓度以及 CO 浓度的时间分布,以及 CO 浓度与自主神经系统平衡之间的回归斜率,由低频功率/高频功率比(LF/HF)表示作为 HRV 指数。结果表明,无论城市规模大小,所测量的城市的 CO 浓度都很低,远低于最大可接受的阈值标准,城市居民在白天的大部分时间内暴露在这些浓度下的时间都不到一半。此外,与普遍观点相反,无论交通拥堵程度如何,与小城市相比,大城市不一定会积累更高浓度的 CO。这项研究证实了大多数其他关于该主题的研究结果,即 HRV 测量的压力降低(由于 CO 浓度增加至 7 ppm 以下)。最后,在评估归因于不同环境因素的差异贡献后,似乎噪声、热负荷和拥堵比 CO 对更高水平的 HRV 平衡贡献更大。这一发现强调了对研究进行多变量方法的重要性,以及对城市环境中环境因素对压力的影响进行补救的重要性。

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