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Characterizing the link between multiple environmental exposures and Parkinsons disease exacerbation

描述多种环境暴露与帕金森病恶化之间的联系

基本信息

批准号：
10707226
负责人：
Danielle Braun
金额：
$ 61.02万
依托单位：
HARVARD SCHOOL OF PUBLIC HEALTH
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-09-20 至 2027-07-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10707226
关键词：
Acceleration Acute Admission activity Adverse effects Age Air Pollution American Carbon Black Caring Censuses Central Nervous System Cessation of life Chronic Climate Communities Complex Computer software Data Data Science Disease Disease Outcome Economic Burden Ensure Environmental Exposure Environmental Health Environmental Risk Factor Etiology Exposure to Foundations Genetic Goals Green space Hospitalization Incidence Individual Inpatients Intervention Knowledge Link Medical Medicare Medicare Part A Medicare claim Methods Modeling Nitrates Nitrogen Dioxide Outcome Outpatients Oxidative Stress Ozone Parkinson Disease Pathogenesis Peer Review Persons Pharmaceutical Preparations Policies Population Poverty Predisposition Prevention strategy Quality of life Race Reproducibility Reproducibility of Results Research Research Personnel Risk Risk Factors Role Severities Severity of illness Socioeconomic Status Statistical Data Interpretation Statistical Methods Subgroup Sulfate Symptoms Temperature Visit Weather burden of illness climate change comorbidity fine particles high risk hospital readmission hospitalization rates improved indexing machine learning algorithm machine learning method modifiable risk nervous system disorder neuroinflammation novel open source protective factors response sex spatiotemporal study population urban planning

项目摘要

Project Summary/Abstract Parkinson's disease (PD) is one of the fastest growing neurological disorders in the US. The number of people with PD is projected to increase to over 12 million by 2030, with an economic burden surpassing $79 billion by 2037. The progression of pathogenesis is paralleled by an exacerbation in symptom severity, which underlies the need for hospitalization. If environmental exposures exacerbate PD symptoms, then days (acute effects) or years (chronic effects) of higher exposure should result in higher rates of hospitalizations. There is evidence that: 1) air pollution might negatively impact the central nervous system via oxidative stress and neuroinflammation; 2) temperature might increase the risk of PD due to thermoregulatory disorders or medication use; and 3) access to green spaces might protect against PD exacerbation. While few studies have examined the association between air pollution, temperature, and greenness and PD, the specific PM2.5 components contributing to PD are unknown, the effects of weather parameters on PD are poorly understood, and there is a lack of evidence on how to identify individuals who are at highest risk for adverse PD outcomes. To date, no study has estimated the link between simultaneous exposure to air pollution, weather, and greenness and PD exacerbation in a nationally representative population using rigorous statistical methods for confounding adjustment. Our goal is to conduct national studies to identify the multiple modifiable environmental factors that contribute to PD exacerbation and increased PD vulnerability. Specifically, in Aim 1 we will conduct national studies to estimate the chronic effects of 1a) PM2.5, NO2, ozone, PM2.5 components, 1b) greenness, 1c) simultaneous multiple exposures and their interactions on: a) incidence of first PD hospitalization and b) re-hospitalizations, as surrogate for accelerated disease severity. In Aim 2 we will estimate the acute effects of 2a) PM2.5, NO2, ozone, 2b) greenness, 2c) mean daily temperature and heat index, 3c) simultaneous multiple exposures on PD hospitalizations. In both Aims 1 and 2 in main analysis we will use Medicare Part A (inpatient hospitalizations) for the full study period (2000-2020), and we will then conduct sensitivity analyses using Part A linked to B (outpatient) and D (medication use) claims to increase rigor in identifying PD cases. In Aim 3 we will develop and apply machine learning methods and existing methods to identify subpopulations at increased risk. In Aim 4, to ensure transparency and reproducibility, we will develop peer-reviewed, open-source, and computationally efficient software so other investigators may implement our methods. In summary, findings of this study will provide evidence on the link between simultaneous environmental exposures and PD exacerbation with the highest possible scientific rigor, and will identify multiple modifiable risk and protective factors that lead to increased vulnerability in PD. Completion of this project will provide the foundation to inform actionable policy (e.g., ensure stringent air pollution standards for PM2.5, implement heat prevention strategies, inform urban planning) to help slow the PD disease burden and improve the quality of life for millions of Americans.

项目总结/文摘