Asthma Simulation Tool for Housing, Medication and Social Adversity (ASTHMA)

针对住房、药物和社会逆境的哮喘模拟工具 (ASTHMA)

• 批准号: 10203966
• 负责人: Maria Patricia Fabian
• 金额: $ 32万
• 依托单位: BOSTON UNIVERSITY MEDICAL CAMPUS
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-01 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10203966
• 关键词: Address; Affect; Air; Asthma; Behavior; Behavioral; Boston; Characteristics; Chemical Exposure; Child; Child health care; Childhood; Childhood Asthma; Chronic Disease; Clinical; Code; Communities; Complex; Crime; Data; Databases; Department of Energy; Dimensions; Disease; Drug Prescriptions; Electronic Health Record; Ensure; Environment; Environmental Exposure; Environmental Pollution; Evaluation; Event; Exposure to; Feedback; Health; Healthcare; Home; Hospitalization; Housing; Humidity; Income; Individual; Indoor Air Quality; Intervention; Link; Location; Low income; Measures; Medical; Medical center; Methodology; Methods; Modeling; Neighborhood Health Center; Neighborhoods; Nitrogen Dioxide; Outcome; Pathway interactions; Patients; Pattern; Pharmaceutical Preparations; Physical environment; Policies; Population; Populations at Risk; Psychosocial Stress; Public Health; Public Housing; Published Database; Publishing; Risk Factors; Science; Services; Social support; Statistical Models; Stress; Structure; System; Techniques; Temperature; Time; asthma exacerbation; asthmatic; base; behavioral response; community intervention; contextual factors; data resource; demographics; design; electronic data; environmental health disparity; ethnic minority population; fine particles; health care availability; health care disparity; health care service utilization; high risk; indoor pollutant; insight; intervention effect; medication compliance; minority children; model building; models and simulation; pollutant; programs; prototype; pulmonary function; racial and ethnic; repository; simulation; simulation software; social; social stressor; sociodemographics; socioeconomics; stressor; therapy design; tool; urban area; urban setting; ventilation; violence exposure

PROJECT SUMMARY / ABSTRACT Pediatric asthma has a substantial public health burden with numerous contributing risk factors in the physical, social, and health care environments. This burden is elevated among low-income minority children living in urban areas, related in part to multi-factorial residential exposures. There are numerous complex feedback loops among risk factors, with interventions potentially inducing behavioral responses that modify levels of other risk factors. Given these characteristics, pediatric asthma is an ideal candidate for systems science tools to prioritize among risk factors and design intervention strategies. However, there have been few applications of systems science techniques to asthma, and no applications to date that take account of multiple risk factors with housing, social and behavioral components. Discrete event simulation (DES), a systems science approach that involves modeling a complex system in which individuals can be tracked over time, multiple attributes can be incorporated simultaneously, and interactions and non-linear effects can be incorporated, is ideally suited for this application. This project (the Asthma Simulation Tool for Housing, Medication, and Social Adversity - ASTHMA) builds upon the only DES model of pediatric asthma or the physical environment, leveraging data from a longstanding electronic health record (EHR) database, and extensive neighborhood contextual data available from a BU center of environmental health disparities. Building on prior expertise and the strength of an established interdisciplinary team we propose the following specific aims: Aim 1: To build the Boston Children’s Healthcare Disparities Repository (BCHDR), a large database of predominantly low-income and racial/ethnic minority asthmatic children extracted from the BMC EHR, and use it to develop associations among key predictors of lung function, medication prescription and adherence, social adversity, asthma outcomes, and healthcare utilization. Aim 2: To predict exposure to indoor pollutants and environmental conditions across a range of housing types, resident behaviors, and sociodemographic characteristics, in a manner useful for DES modeling. Aim 3: To expand the existing DES model to capture the variability in housing, sociodemographic, and neighborhood environments for asthmatic children in the BCHDR, and evaluate the influence of implemented or proposed policies addressing housing conditions, medication adherence, and aspects of social adversity on asthma outcomes. These data and methods collectively allow us to develop unique insights about the individual and cumulative impacts of multiple stressors on asthma outcomes, as well as about how candidate interventions would influence asthma outcomes given the multiple pathways and complex behavioral responses. While we focus on data specific to Boston to ensure internal consistency, our methods and insights will generalize to other urban settings, our housing modeling approach can be expanded to any are in the US, and our discrete event simulation code and methodology for extracting and analyzing clinical and social risk factor data from an EHR could be adapted to other circumstances.

项目摘要/摘要 儿童哮喘是一个重大的公共卫生负担，在身体上有许多促成风险因素， 社交和医疗保健环境。这一负担在生活在城市的低收入少数民族儿童中更为严重。 区域，部分与多因素住宅暴露有关。有许多复杂的反馈回路 在风险因素中，干预措施可能会引发行为反应，从而改变其他风险的水平 各种因素。鉴于这些特点，儿童哮喘是系统科学工具优先考虑的理想对象。 在危险因素中，设计干预策略。然而，系统的应用还很少 哮喘的科学技术，到目前为止还没有考虑到住房的多种风险因素的应用， 社交和行为成分。离散事件仿真(DES)是一种系统科学方法，涉及 对可以随时间跟踪个人的复杂系统进行建模，可以 同时结合，并且可以结合相互作用和非线性效果，非常适合于此 申请。本项目(用于住房、药物和社会逆境的哮喘模拟工具-哮喘) 建立在儿科哮喘或物理环境的唯一DES模型基础上，利用来自 长期电子健康记录(EHR)数据库和广泛的社区背景数据可用 来自不列颠哥伦比亚大学环境健康差距研究中心。以先前的专业知识和 建立跨学科团队我们提出以下具体目标：目标1：建设波士顿儿童基金会 医疗保健差异资料库(BCHDR)，主要是低收入和种族/民族的大型数据库 从BMC EHR中提取的少数族裔哮喘儿童，并用它来建立关键关键因素之间的关联 肺功能、用药处方和依从性、社会逆境、哮喘结局的预测因素 医疗保健利用率。目标2：预测暴露在室内污染物和环境条件下 一系列住房类型、居民行为和社会人口特征，以对DES有用的方式 模特儿。目标3：扩展现有的DES模型，以捕捉住房、社会人口和 BCHDR中哮喘儿童的邻里环境，并评估实施或 针对住房条件、服药依从性和社会逆境方面的拟议政策 哮喘结果。这些数据和方法共同允许我们发展对个人的独特见解 以及多种应激源对哮喘结局的累积影响，以及候选干预措施如何 会影响哮喘的结局，因为有多种途径和复杂的行为反应。当我们 专注于特定于波士顿的数据以确保内部一致性，我们的方法和见解将推广到其他 城市环境，我们的住房建模方法可以扩展到美国的任何地方，我们的离散事件 从电子病历中提取和分析临床和社会风险因素数据的模拟代码和方法 可以适应其他情况。

项目成果

Spatial resolution of Normalized Difference Vegetation Index and greenness exposure misclassification in an urban cohort

• DOI: 10.1038/s41370-022-00409-w
• 发表时间: 2022-01-29
• 期刊: JOURNAL OF EXPOSURE SCIENCE AND ENVIRONMENTAL EPIDEMIOLOGY
• 影响因子: 4.5
• 作者: Jimenez, Raquel B.;Lane, Kevin J.;Fabian, M. Patricia
• 通讯作者: Fabian, M. Patricia

The impact of energy retrofits on pediatric asthma exacerbation in a Boston multi-family housing complex: a systems science approach.

• DOI: 10.1186/s12940-021-00699-x
• 发表时间: 2021-02-14
• 期刊: Environmental health : a global access science source
• 作者: Tieskens KF;Milando CW;Underhill LJ;Vermeer K;Levy JI;Fabian MP
• 通讯作者: Fabian MP

Sensitivity of modeled residential fine particulate matter exposure to select building and source characteristics: A case study using public data in Boston, MA.

• DOI: 10.1016/j.scitotenv.2022.156625
• 发表时间: 2022-09-20
• 期刊: SCIENCE OF THE TOTAL ENVIRONMENT
• 影响因子: 9.8
• 作者: Milando, Chad W.;Carnes, Fei;Vermeer, Kimberly;Levy, Jonathan I.;Fabian, M. Patricia
• 通讯作者: Fabian, M. Patricia