Source-specific multi-pollutant exposures and the neighborhood context in disparities in stillbirth

特定来源的多污染物暴露和死产差异中的邻里环境

• 批准号: 10657700
• 负责人: Eun Sug Park
• 金额: $ 53.1万
• 依托单位: BAYLOR COLLEGE OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-24 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10657700
• 关键词: Accounting; Address; Adverse effects; Air Pollutants; Air Pollution; Awareness; Bayesian Modeling; Categories; Cities; Complex Mixtures; County; Data; Disparity; Dust; Environmental Exposure; Ethnic Origin; Exposure to; Fetal Death; Fetal Growth Retardation; Future; Genetic; Health; Health Priorities; Individual; Intervention; Investigation; Location; Low Birth Weight Infant; Low Income Population; Maps; Maternal and Child Health; Measurement; Metals; Meteorology; Methods; Minority; Mission; Modeling; Modification; National Institute of Environmental Health Sciences; Nature; Neighborhoods; Outcome; Ozone; Particulate Matter; Physical environment; Play; Pollution; Population; Predisposition; Pregnancy; Pregnant Women; Premature Birth; Public Health; Race; Reporting; Risk; Role; Social Environment; Source; Surface; Texas; Time; Uncertainty; United States National Institutes of Health; Woman; ambient air pollution; built environment; deprivation; disorder risk; disparity reduction; ethnic disparity; fine particles; health disparity; innovation; land use; neighborhood disadvantage; obstetric outcomes; particle; pollutant; racial disparity; receptor; stillbirth; stressor

ABSTRACT The origin of racial and ethnic disparities in obstetric outcomes does not appear to be genetic nor fully explained by individual-level factors. Hence, we must look toward the broader context in the physical, social and built environments to understand and mitigate disparities in maternal and child health. In the physical, social and built environments, air pollution, neighborhood disadvantage, and residential greenness may play important roles. As compared to low birth weight, fetal growth restriction and preterm birth, considerably less is known about air pollution exposure's impact on stillbirth, defined as an intrauterine fetal death that occurs at or after 20 weeks of gestation. Urban air pollution is a complex mixture of particle and gaseous pollutants, often correlated because they are influenced by common nearby sources and meteorology and thus, simultaneously studying exposure to multiple air pollutants is challenging. Previous studies on the risk of stillbirth associated with air pollution exposure have largely focused on pollutant-specific effects, including our studies examining ozone and metal constituents of PM in the fourth largest city in the U.S., Houston, Texas. Using source apportionment to assess air pollutant exposures takes advantage of the highly correlated nature of the air pollutant mixture, quantifies the contributions of different source categories and provides information that allows more targeted control strategies to be developed. To date, we are aware of only one study that applied source apportionment for fine particulate matter, and it used the Positive Matrix Factorization (PMF) receptor modeling. Yet, that investigation used estimated source contributions as if they were true exposures without accounting for spatial misalignment error and inherent uncertainty in the method itself. Addressing these shortcomings, we will apply an innovative approach that integrates Bayesian spatial multivariate receptor models (BSMRM) with land-use and traffic data as well as accounting for exposure measurement errors in health effects estimation. Like air pollution, the social and built environments cluster neighborhood-level exposures that adversely impact health. These stressors are often greater among minority and low-income populations who suffer what has been termed “double jeopardy”. The objective of the proposed study is three-fold. First, we wish to evaluate the impact of source-specific multipollutant exposures on stillbirth using an innovative approach that integrates BSMRM with land-use and traffic data and accounting for exposure measurement errors in health effects estimation. We hypothesize that increased air pollutant source-apportioned concentrations will be associated with increased risk of stillbirth and that effect sizes will be different for different source categories. Second, we wish to examine the impact of the neighborhood context on risk of stillbirth. Third, given the priority of health disparities for the NIH and the nation, another objective is to evaluate the hypothesis that minorities will suffer disproportionate stillbirth risks associated with air pollutant source-apportioned concentrations and with living in deprived neighborhoods, as assessed by neighborhood disadvantage and residential greenness.

抽象的 种族和种族差异在产科结果中的起源似乎并不是遗传或完全解释的 通过个人级别的因素。因此，我们必须探讨物理，社会和建筑的更广泛的背景 了解和减轻孕产妇和儿童健康分布的环境。在身体，社会和建造 环境，空气污染，邻里灾难和居民绿色可能起着重要作用。作为 与低出生体重，胎儿生长限制和早产相比，关于空气的了解要少得多 污染暴露对死产的影响，定义为在20周或20周后发生的胎儿内死亡 妊娠。城市空气污染是粒子和气态污染物的复杂混合物，通常是因为 它们受到附近常见的来源和气象的影响，因此，仅研究暴露 对于多种空气污染物来说，具有挑战性。先前关于与空气污染相关的死产风险的研究 暴露在很大程度上集中于污染物特异性效应，包括我们检查臭氧和金属的研究 德克萨斯州休斯敦的美国第四大城市PM的组成部分。使用来源分配评估 空气污染物的暴露利用空气污染物混合物的高度相关性，量化 不同来源类别的贡献并提供了允许更具针对性的控制策略的信息 要开发。迄今为止，我们只知道一项将源代码分配应用的研究 物质，它使用了阳性基质分解（PMF）受体建模。但是，调查使用了 估计的源贡献，好像它们是真正的暴露，而无需考虑空间错位错误 以及该方法本身固有的不确定性。解决这些缺点，我们将采用创新性 将贝叶斯空间多元受体模型（BSMRM）与土地利用和交通数据集成的方法 以及对健康效应估计中的暴露测量错误考虑。像空气污染一样 并建立环境集群邻里级别的暴露会对健康产生不利影响。这些压力源是 在少数族裔和低收入人群中，通常会遭受称为“双重危险”的人群。 拟议的研究的目的是三倍。首先，我们希望评估特定来源的影响 使用创新方法将BSMRM与土地使用和土地使用和 交通数据和对健康效应估计中暴露测量错误的核算。我们假设这一点 空气污染物源侵入浓度的增加将与死产的风险增加有关 对于不同的源类别，该效果大小将有所不同。第二，我们希望研究 死产风险的邻里环境。第三，鉴于NIH和国家的健康差异优先 另一个目的是评估少数群体将遭受不成比例的死产风险的假设 由空气污染物源侵占的浓度和生活在被剥夺的社区中的生活 邻里灾难和居民绿色。