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South African urban imaginaries: cases from Johannesburg 南非城市想象:来自约翰内斯堡的案例
Pub Date : 2022-06-01 DOI: 10.36634/kdew3665
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引用次数: 0
Social Susceptibility to Multiple Air Pollutants in Cardiovascular Disease. 心血管疾病患者对多种空气污染物的社会易感性
Pub Date : 2018-09-24 DOI: 10.1289/isesisee.2018.p02.1390
Jamie L. Humphrey, E. Kinnee, L. Kubzansky, C. Reid, L. McClure, Lucy F. Robinson, J. Clougherty
INTRODUCTIONCardiovascular disease (CVD) is the leading cause of death in the United States, and substantial research has linked ambient air pollution to elevated rates of CVD etiology and events. Much of this research identified increased effects of air pollution in lower socioeconomic position (SEP) communities, where pollution exposures are also often higher. The complex spatial confounding between air pollution and SEP makes it very challenging, however, to disentangle the impacts of these very different exposure types and to accurately assess their interactions.The specific causal components (i.e., specific social stressors) underlying this SEP-related susceptibility remain unknown, because there are myriad pathways through which poverty and/or lower-SEP conditions may influence pollution susceptibility - including diet, smoking, coexposures in the home and occupational environments, health behaviors, and healthcare access. Growing evidence suggests that a substantial portion of SEP-related susceptibility may be due to chronic psychosocial stress - given the known wide-ranging impacts of chronic stress on immune, endocrine, and metabolic function - and to a higher prevalence of unpredictable chronic stressors in many lower-SEP communities, including violence, job insecurity, and housing instability. As such, elucidating susceptibility to pollution in the etiology of CVD, and in the risk of CVD events, has been identified as a research priority.This interplay among social and environmental conditions may be particularly relevant for CVD, because pollution and chronic stress both impact inflammation, metabolic function, oxidative stress, hypertension, atherosclerosis, and other processes relevant to CVD etiology. Because pollution exposures are often spatially patterned by SEP, disentangling their effects - and quantifying any interplay - is especially challenging. Doing so, however, would help to improve our ability to identify and characterize susceptible populations and to improve our understanding of how community stressors may alter responses to multiple air pollutants. More clearly characterizing susceptible populations will improve our ability to design and target interventions more effectively (and cost-effectively) and may reveal greater benefits of pollution reduction in susceptible communities, strengthening cost-benefit and accountability analyses, ultimately reducing the disproportionate burden of CVD and reducing health disparities.METHODSIn the current study, we aimed to quantify combined effects of multiple pollutants and stressor exposures on CVD events, using a number of unique datasets we have compiled and verified, including the following.1. Poverty metrics, violent crime rates, a composite socioeconomic deprivation index (SDI), an index of racial and economic segregation, noise disturbance metrics, and three composite spatial factors produced from a factor analysis of 27 community stressors. All indicators have cit
在美国,心血管疾病(CVD)是导致死亡的主要原因,大量研究已将环境空气污染与CVD病因和事件发生率升高联系起来。大部分研究发现,在社会经济地位较低(SEP)的社区,空气污染的影响更大,那里的污染暴露也往往更高。然而,空气污染和SEP之间复杂的空间混淆使得理清这些不同暴露类型的影响并准确评估它们之间的相互作用非常具有挑战性。这种与sep相关的易感性背后的具体因果成分(即特定的社会压力源)仍然未知,因为贫困和/或低sep条件可能通过无数途径影响污染易感性,包括饮食、吸烟、家庭和职业环境中的共同暴露、健康行为和医疗保健获取。越来越多的证据表明,sep相关易感性的很大一部分可能是由于慢性社会心理压力-鉴于慢性压力对免疫,内分泌和代谢功能的已知广泛影响-以及在许多低sep社区中不可预测的慢性压力源的更高患病率,包括暴力,工作不安全感和住房不稳定。因此,在CVD的病因学和CVD事件的风险中阐明对污染的易感性已被确定为研究重点。这种社会和环境条件之间的相互作用可能与CVD特别相关,因为污染和慢性应激都会影响炎症、代谢功能、氧化应激、高血压、动脉粥样硬化和其他与CVD病因相关的过程。由于污染暴露通常是由SEP构成的空间模式,因此理清它们的影响——并量化任何相互作用——尤其具有挑战性。然而,这样做将有助于提高我们识别和描述易感人群的能力,并提高我们对社区压力因素如何改变对多种空气污染物的反应的理解。更明确地描述易感人群的特征将提高我们更有效地(和具有成本效益地)设计和确定干预措施目标的能力,并可能揭示易感社区减少污染的更大好处,加强成本效益和问责制分析,最终减少心血管疾病的不成比例负担并缩小健康差距。在当前的研究中,我们的目标是量化多种污染物和应激源暴露对心血管疾病事件的综合影响,使用我们汇编和验证的一些独特数据集,包括以下数据。贫困指标、暴力犯罪率、综合社会经济剥夺指数(SDI)、种族和经济隔离指数、噪音干扰指标,以及27个社区压力源因子分析得出的三个综合空间因子。所有指标均覆盖全市,并在全市焦点小组和调查中与压力和压力源暴露的个人报告进行了验证。来自纽约市社区空气调查(NYCCAS)的多种污染物的空间表面,该调查在150个站点全年监测多种污染物,并使用土地利用回归(LUR)模型估算细颗粒(PM2.5)、二氧化氮(NO2)、二氧化硫(SO2)和臭氧(O3)的细尺度(100米)城市内空间变异。从2005-2011年美国环境保护署(EPA)空气质量系统(AQS)在纽约市的所有监测仪中获得的每日数据和时间趋势,我们将其与NYCCAS表面相结合,以创建住宅和特定日的时空暴露估计。来自纽约州(NYS)卫生部全州规划和研究合作系统(SPARCS)的2005-2011年纽约市医院门诊和门诊非计划心血管疾病事件的完整数据(n = 1,113,185)。在这项研究中,我们量化了纽约市多种污染物暴露与社区CVD事件发生率和个体CVD事件风险之间的关系,并测试了污染与CVD的关联是否因社区SEP和社会压力源暴露而变化。我们假设(1)较高的慢性社区水平SEP、应激源和污染暴露与较高的社区CVD发生率相关;(2)多种污染物的时空变化与CVD事件的过度风险相关;(3)在低SEP或高应激源暴露的社区中,污染与心血管疾病的关联更强。结果为了首先了解压力源和污染物在相同时空分辨率尺度下与心血管疾病的单独和联合关联,我们使用生态横截面模型研究了多种慢性污染物和压力源暴露与年龄调整后的社区心血管疾病发病率之间的空间关系。
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引用次数: 6
Ambient and Controlled Particle Exposures as Triggers for Acute ECG Changes. 环境和受控颗粒暴露作为急性心电图改变的触发因素。
Pub Date : 2014-10-20 DOI: 10.1289/isee.2014.o-030
D. Rich, A. Peters, A. Schneider, W. Zareba, S. Breitner, D. Oakes, Jelani Wiltshire, Cathleen Kane, M. Frampton, Regina Hampel, P. Hopke, J. Cyrys, M. Utell
INTRODUCTIONPrevious studies have examined changes in heart rate variability (HRV*) and repolarization associated with increased particulate matter (PM) concentrations on the same and previous few days. However, few studies have examined whether these health responses to PM occur within a few hours or even less. Moreover, it is not clear whether exposure of subjects to ambient or-controlled PM concentrations both lead to similar health effects or whether any of the subjects' individual characteristics modify any of their responses to PM. The aims of the cur- rent study were to investigate whether exposure to PM was associated with rapid changes (< 60 minutes or con- current hour up to a delay of 6 hours) in markers of car- diac rhythni or changes in total antioxidant capacity (a marker of protection against oxidative stress) and whether any PM effects on cardiac rhythm markers were modified by total antioxidant capacity, age, obesity, smoking, hypertension, exertion, prior myocardial infarction (MI), or medication.METHODSWe obtained data from a completed study in Augsburg, Germany (a panel study in N= 109 subjects, including a group with type 2 diabetes or impaired glucose tolerance [IGT; also known as prediabetes]) and a group of other- wise healthy subjects with a potential genetic susceptibil- ity to detoxifying and inflammatory pathways (Hampel et al. 2012b), as well as three completed studies in Rochester, New York (the REHAB panel study of N= 76 postinfarction patients in a cardiac rehabilitation pro- gram [Rich et al. 2012b]; the UPDIABETES study of con- trolled exposure to ultrafine particles [UFPs, particles with an aerodynamic diameter < 100 nm] of N = 19 patients with type 2 diabetes [Stewart et al. 2010; Vora et al. 2014j; and the UPCON controlled-exposure study of concentrated UFP exposure in N = 20 young, healthy, life- time nonsmokers). Data included 5-minute and 1-hour values for HRV and repolarization parameters from elec- trocardiogram (ECG) recordings and total antioxidant capacity measured in stored blood samples. Ambient con- centrations of UFPs, accumulation-mode particles (AMP, particles with an aerodynamic diameter of 100-500 nm), fine PM (PM2.5, particles with an aerodynamic diameter 2.5 pm), and black carbon (BC) were also available. We first conducted factor analyses in each study to find subgroups of correlated ECG outcomes and to reduce the number of outcomes examined in our statistical models. We then restricted the statistical analyses to the factors and representative.outcomes that were common to all four studies, including total HRV (measured as the standard deviation of normal-to-normal [NN] beat intervals [SDNNj), parasympathetic modulation (measured as the root mean square of the successive differences [RMSSD between adjacent NN beat intervals), and T-wave morphol- ogy (measured as T-wave complexity). Next, we used addi- tive mixed models to estimate the change in each outcome associated with increased pol
以前的研究已经检查了心率变异性(HRV*)和复极化在同一天和前几天与颗粒物(PM)浓度增加相关的变化。然而,很少有研究检查这些对PM的健康反应是否在几小时甚至更短的时间内发生。此外,尚不清楚受试者暴露于环境或受控的PM浓度是否会导致类似的健康影响,也不清楚受试者的任何个体特征是否会改变他们对PM的任何反应。本研究的目的是调查暴露于PM是否与心律标记物的快速变化(< 60分钟或同步一小时至延迟6小时)或总抗氧化能力(抗氧化应激的标志)的变化有关,以及PM对心律标记物的影响是否因总抗氧化能力、年龄、肥胖、吸烟、高血压、劳累、既往心肌梗死(MI)或药物治疗而改变。方法:我们从德国奥格斯堡的一项已完成的研究中获得数据(N= 109名受试者的小组研究,包括2型糖尿病或糖耐量受损组[IGT;也被称为前驱糖尿病])和一组对解毒和炎症途径具有潜在遗传易感性的健康受试者(Hampel et al. 2012b),以及在纽约州罗切斯特市完成的三项研究(心脏康复计划中N= 76例梗死后患者的康复小组研究[Rich et al. 2012b];UPDIABETES对N = 19例2型糖尿病患者的控制暴露于超细颗粒[ufp,空气动力学直径< 100 nm的颗粒]的研究[Stewart et al. 2010;Vora et al. 2014j;以及UPCON控制暴露研究(集中UFP暴露于N = 20名年轻、健康、终生不吸烟的人)。数据包括5分钟和1小时HRV值和心电图(ECG)记录的复极化参数,以及储存血液样本中测量的总抗氧化能力。ufp、累积模式粒子(AMP,空气动力学直径为100-500 nm的粒子)、细颗粒物(PM2.5,空气动力学直径为2.5 PM的粒子)和黑碳(BC)的环境浓度也可用。我们首先对每项研究进行因素分析,以找到相关心电图结果的亚组,并减少统计模型中检查的结果数量。然后,我们将统计分析限制在因素和代表性上。所有四项研究共有的结果,包括总HRV(以正常到正常[NN]心跳间隔[ssdnj]的标准偏差测量),副交感神经调节(以相邻NN心跳间隔之间连续差异的均方根测量[RMSSD])和t波形态(以t波复杂性测量)。接下来,我们使用加性混合模型来估计与大气中污染物浓度增加相关的每个结果的变化。同时和之前的6小时,间隔5分钟直到之前的60分钟,考虑到每个受试者重复结果测量的相关性,并根据时间趋势、每天的小时、温度、相对湿度、星期几、月份和就诊次数进行调整。因为多重比较是个问题。在分析中,我们使用了发现和复制的方法来得出每个研究问题的结论。结果在Augsburg研究中,UFP浓度滞后2 - 5小时的四分位数范围(IQR)增加与SDNN下降1%-3%相关(例如,遗传易感性组滞后3小时:-2.26%;95%置信区间[CI], -3.98%至-0.53%)。在康复研究中,同样,前5小时内UFP浓度的IQR增加与SDNN下降< 3%相关(例如,滞后1小时:-2.69%;95% CI, -5.13%至-0.26%)。我们还发现,在UPDIABETES研究中,sdn的减少与总颗粒计数(UFP的替代指标)的IQR增加相关(滞后1小时:-13.22%;95% CI, -24.11%至-2.33%),但在UPCON研究中没有。在Augsburg的研究中,PM2.5浓度在同期1小时和滞后1-5小时,AMP浓度滞后1和3小时,以及BC浓度滞后1-5小时的IQR增加与SDNN下降-1%-5%相关(例如,PM2.5在糖尿病或IGT组滞后2小时:-4.59%;95% CI, -7.44%至-1.75%)。在康复研究中,PM2.5浓度的IQR增加滞后5和6小时,AMP浓度在同期和滞后5小时内的增加与SDNN下降1%-2%相关(例如,PM2.5滞后4小时:-2.13%;95% CI, -3.91%至-0.35%)。在Augsburg的研究中,PM2.5浓度的IQR增加与RMSSD降低3%-7%相关(例如,糖尿病或IGT组的PM2.5同时小时:-7)。 20%;95% CI, -12.11%至-2.02%)。同样,在康复研究中,PM2.5浓度的增加-滞后4至6小时-尽管AMP或BC浓度不在任何滞后时间-与RMSSD下降2.5%-3.5%相关(例如PM2.5滞后5小时:-3.49%;95% CI, -6.13%至-0.84%)。在1小时的记录中,我们没有发现任何污染物对t波复杂性影响的一致证据。对于5分钟的记录,没有一致的证据表明UFP在60分钟内任何5分钟间隔对SDNN、RMSSD或t波复杂性有影响。我们进一步得出结论,UFP和PM2.5对SDNN和RMSSD短期测量的重复小时效应在研究组(即2型糖尿病、糖尿病前期/IGT、梗死后和健康受试者)之间通常没有差异。最后,我们没有发现任何污染物对总抗氧化能力的影响的一致证据,也没有发现任何潜在影响调节剂改变我们的pm2.5结局关联的一致证据。结论UFP浓度的升高与SDNN的降低相关,在两项小组研究和两项对照暴露研究中的一项中都是如此。我们还发现,在小组研究中,SDNN的降低与前6小时PM2.5和AMP浓度的增加有关,RMSSD的降低与前6小时PM2.5浓度的增加有关。因此,我们得出结论,研究问题是重复的。我们的研究结果表明,ufp和PM2.5在暴露数小时内都与自主神经功能障碍有关,这可能是部分原因。解释先前报道的与前几小时PM升高相关的急性心血管事件风险。尽管研究人群和研究方案存在异质性,但我们的研究结果为ufp和PM2.5诱导快速病理生理反应提供了一致的证据——在检测较短时间间隔时,ufp、PM2.5和这些结果之间缺乏一致的关联,这表明5至60分钟的反应可能不如数小时内发生的反应明显。然而,5分钟间隔的结果可能受到不同研究的方案和条件的影响,也可能受到潜在疾病的潜在影响(例如,健康个体与糖尿病患者或新近患冠心病的个体)。事件)、身体活动、昼夜节律、压力和/或药物。
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引用次数: 11
Retention modeling of diesel exhaust particles in rats and humans. 柴油机废气颗粒在大鼠和人体内的滞留模型。
Pub Date : 1991-05-01 DOI: 10.1089/JAM.1991.4.79
C. P. Yu, K. J. Yoon, Yu-Kang Chen
The objective of this study was to predict the lung burden in rats and humans of diesel exhaust particles from automobile emissions by means of a mathematical model. We previously developed a model to predict the deposition of diesel exhaust particles in the lungs of these species. In this study, the clearance and retention of diesel exhaust particles deposited in the lung are examined. A diesel particle is composed of a carbonaceous core (soot) and adsorbed organics. These materials can be removed from the lung after deposition by two mechanisms: (1) mechanical clearance, provided by mucociliary transport in the ciliated airways as well as macrophage phagocytosis and migration in the nonciliated airways, and (2) clearance by dissolution. To study the clearance of diesel exhaust particles from the lung, we used a compartmental model consisting of four anatomical compartments: nasopharyngeal, tracheobronchial, alveolar, and the lung-associated lymph node compartments. We also assumed a particle model made up of material components according to the characteristics of clearance: (1) a carbonaceous core of about 80 percent of particle mass, (2) slowly cleared organics of about 10 percent of particle mass, and (3) fast-cleared organics accounting for the remaining 10 percent of particle mass. The kinetic equations of the retention model were first developed for Fischer-344 rats. The transport rates of each material component of diesel exhaust particles (soot, slowly cleared organics, and fast-cleared organics) were derived using available experimental data and several mathematical approximations. The lung burden results calculated from the model showed that although the organics were cleared at nearly constant rates, the alveolar clearance rate of diesel soot decreased with increasing lung burden. This is consistent with existing experimental observations. At low lung burdens, the alveolar clearance rate of diesel soot was a constant, equal to the normal clearance rate controlled by macrophage migration to the mucociliary escalator, whereas at high lung burdens, the clearance rate was determined principally by transport to the lymphatic system. The retention model of diesel exhaust particles for rats was extrapolated to humans of different age groups, from birth to adulthood. To derive the transport rates for the human model, the mechanical clearance from the alveolar region of the lung was assumed to be dependent on the specific particulate burden on the alveolar surface. The reduction in the mechanical clearance in adult humans caused by exposure to high concentrations of diesel exhaust was found to be much less than that observed in rats. The reduction in children was greater than that in adults.(ABSTRACT TRUNCATED AT 400 WORDS)
本研究的目的是通过数学模型来预测汽车排放的柴油废气颗粒对大鼠和人的肺负荷。我们之前开发了一个模型来预测柴油废气颗粒在这些物种肺部的沉积。在这项研究中,清除和保留柴油废气颗粒沉积在肺检查。柴油颗粒由碳质核心(烟灰)和吸附的有机物组成。这些物质沉积后可通过两种机制从肺中清除:(1)机械清除,由纤毛气道中的纤毛黏液运输以及非纤毛气道中的巨噬细胞吞噬和迁移提供;(2)溶解清除。为了研究柴油废气颗粒从肺部的清除,我们使用了一个由四个解剖室组成的室室模型:鼻咽室、气管支气管室、肺泡室和肺相关淋巴结室。我们还假设了一个由材料成分组成的颗粒模型,根据其清除特性:(1)碳质核心约占颗粒质量的80%,(2)缓慢清除的有机物约占颗粒质量的10%,(3)快速清除的有机物占颗粒质量的10%。首先建立了fisher -344大鼠滞留模型的动力学方程。利用现有的实验数据和几个数学近似,得出了柴油尾气颗粒(烟灰、缓慢清除有机物和快速清除有机物)的每种物质成分的传输速率。由模型计算的肺负荷结果表明,尽管有机物的清除率几乎恒定,但随着肺负荷的增加,柴油烟灰的肺泡清除率降低。这与现有的实验观察结果一致。在低肺负荷时,柴油烟灰的肺泡清除率是一个常数,等于由巨噬细胞向黏毛自动扶梯迁移控制的正常清除率,而在高肺负荷时,清除率主要由向淋巴系统的运输决定。将大鼠对柴油机尾气颗粒的滞留模型外推到不同年龄段的人,从出生到成年。为了得出人体模型的运输速率,假设肺肺泡区的机械清除依赖于肺泡表面的特定颗粒负荷。研究发现,暴露于高浓度柴油废气所造成的成人机械间隙的减少,远远小于在大鼠身上观察到的情况。儿童的下降幅度大于成人。(摘要删节为400字)
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引用次数: 42
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