Particulate Matter (PM) Metals and Racial Disparity in Cardiovascular (CVD) Risk Factors

颗粒物 (PM) 金属和心血管 (CVD) 危险因素的种族差异

• 批准号: 9892567
• 负责人: Boubakari Ibrahimou
• 金额: $ 17.66万
• 依托单位: FLORIDA INTERNATIONAL UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-02-17 至 2025-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/9892567
• 关键词: Address; Air; Air Pollutants; Air Pollution; Aluminum; Bayesian Analysis; Biological; Biological Markers; Biometry; Cadmium; Cardiovascular Diseases; Cardiovascular system; Caucasians; Characteristics; Chemicals; Child; Child Development; Child Mortality; Clinical; Complex; Data; Development Plans; Disease; Embryology; Environment; Equation; Ethnic Origin; Etiology; Exposure to; Factor Analysis; Fetal Development; Fetal Growth; Fetus; Florida; Funding; Future; Geographic Information Systems; Gestational Diabetes; Goals; Growth and Development function; Health; Heavy Metals; Hispanics; Hospitals; Human; Infant Mortality; Inhalation; Intervention; Latino; Lead; Linear Models; Literature; Logistic Regressions; Mediating; Mediator of activation protein; Mentors; Mercury; Metal exposure; Metals; Methods; Minority; Minority Groups; Modeling; Morbidity - disease rate; Mothers; Particulate Matter; Pathway interactions; Physician' s Role; Pollution; Power Plants; Pre-Eclampsia; Pregnancy; Pregnancy Trimesters; Pregnant Women; Prevalence; Public Health; Race; Regression Analysis; Regulation; Research; Research Project Grants; Risk; Risk Assessment; Risk Factors; Silicon; Source; Statistical Methods; Structure; Testing; Time; Toxic effect; Training; United States Environmental Protection Agency; Vanadium; Vulnerable Populations; Weight; Woman; Zinc; Zoran; base; cardiovascular disorder epidemiology; cardiovascular disorder risk; cardiovascular risk factor; career; career development; child bearing; environmental toxicology; flexibility; health disparity; infant morbidity/mortality; mortality; novel; pollutant; pregnancy hypertension; pregnant; prenatal; programs; racial disparity; spatiotemporal; tool; waste treatment

Summary/Abstract Given the complex composition of pollutants such as particulate matter PM in the environment, it is believed that our exposure is not limited to one chemical at a time but to several possible mixtures with varying composition and mix ratios. These mixtures could be formed because they are emitted at the same time from the same source origin as latent factors. As a result, humans are more susceptible to exposure to these mixtures as characterized by these latent factors. Factor analysis is one tool used in the literature to define mixtures. Unfortunately statistical methods of identifying mixtures are limited. Additionally, exposure to PM chemicals during pregnancy is known to be harmful to both mother and child. To address the problem a new method of identifying mixtures exposure based on extension of the traditional factor analysis combined with source apportionment methods will be used. This proposal will test the following hypothesis: Hypothesis 1: Exposure to PM mixture metals during pregnancy increased the risk of cardiovascular disease (CVD) risk factors among black and Hispanic minorities and vary by trimester. Hypothesis 2: CVD risk factors are mediators between PM metals exposure and child development, through the following Aims. 1) Quantify mixtures and estimate mother's exposure during various trimesters of pregnancy. We will use the newly developed Bayesian extended factor analysis (FA), based on the flexibility of Bayesian statistics and the decomposition of the error covariance matrix combined with SAM models to estimate metal mixtures. We will perform a spatio-temporal analysis of the mixtures using Generalized Additive Mixed Models(GAMM). We will use the inverse distance weighting method to estimate mother's inhaled quantities during each trimester of pregnancy. 2) Investigate CVD risk factors difference among black and white and interaction between air pollution and race/ethnicity by trimester. We will use logistic regression analysis and generalized spatial linear model for this aim. 3) Investigate CVD risk factors moderating between mixture metals exposure and infant mortality. We will use structural equation modeling (SEM) to investigate wich risk factors is in the pathway between exposure and child mortality. Results from the proposed studies could have implications in identifying mixtures exposures, their chemical toxicity and relative implication in CVD during pregnancy.

摘要/摘要 鉴于环境中颗粒物PM等污染物成分复杂， 相信我们一次接触的不只是一种化学物质，而是几种可能的混合物 不同的成分和混合比例。这些混合物之所以能形成，是因为它们是在 与潜在因素同一时间、同一来源。因此，人类更容易受到 暴露于这些混合物的特征是这些潜在因素。因子分析是一种常用的工具 定义混合物的文献。不幸的是，识别混合物的统计方法是有限的。 此外，众所周知，怀孕期间接触 PM 化学物质对母亲和婴儿都有害。 孩子。为了解决这个问题，一种基于扩展的混合物暴露识别新方法 将使用传统的因素分析与源解析方法相结合。该提案将 检验以下假设： 假设 1：怀孕期间 PM 混合金属的暴露增加 黑人和西班牙裔少数族裔患心血管疾病 (CVD) 的危险因素因人而异 三个月。假设 2：CVD 危险因素是 PM 金属暴露与儿童之间的中介因素 发展，通过以下目标。 1) 量化混合物并估计母亲在怀孕期间的暴露情况 怀孕的各个三个月。我们将使用新开发的贝叶斯扩展因子分析 (FA)，基于贝叶斯统计的灵活性和误差协方差矩阵的分解 结合 SAM 模型来估计金属混合物。我们将进行时空分析 使用广义加法混合模型（GAMM）的混合物。我们将使用反距离 加权法估计母亲在怀孕每个三个月期间的吸入量。 2） 调查黑人和白人之间的 CVD 危险因素差异以及空气污染与白人之间的相互作用 按三个月划分的种族/民族。我们将使用逻辑回归分析和广义空间线性模型 为了这个目标。 3) 研究混合金属暴露与婴儿之间的 CVD 危险因素 死亡。我们将使用结构方程模型（SEM）来研究风险因素 暴露与儿童死亡率之间的途径。拟议研究的结果可能会 识别混合物暴露的影响、其化学毒性以及对 CVD 的相关影响 怀孕期间。