What Causes Hearing Loss: Advancing the Methods

导致听力损失的原因：改进方法

• 批准号: 10242853
• 负责人: Molin Wang
• 金额: $ 38.38万
• 依托单位: HARVARD SCHOOL OF PUBLIC HEALTH
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-13 至 2024-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10242853
• 关键词: Accounting; Acquired Deafness; Address; Affect; Applications Grants; Area; Audiology; Auditory Threshold; Clinic; Clinical; Complex; Computer software; Data; Data Analyses; Data Collection; Disease; Ear; Elderly; Environmental Risk Factor; Epidemiologist; Epidemiology; Equipment; Etiology; European; Frequencies; Genetic; Hearing; Hearing Tests; Hospitalization; Individual; Lead; Left; Longitudinal Studies; Measurement; Mental Depression; Methods; Multicenter Studies; National Institute on Deafness and Other Communication Disorders; Nature; Nurses' Health Study; Outcome; Outcome Assessment; Outcome Measure; Outcome Measurement Error; Population; Procedures; Publishing; Quality Control; Quality of life; Research Personnel; Risk Factors; Shapes; Site; Social isolation; Specific qualifier value; Statistical Data Interpretation; Statistical Methods; Structure; Study Section; Testing; Time; Validation; Woman; analytical method; base; burden of illness; cognitive function; cohort; cost; epidemiologic data; epidemiology study; hearing impairment; hearing measurement; modifiable risk; novel; population based; prevent; prospective; research study; software development; user friendly software; user-friendly; wasting

Project Summary / Abstract Existing statistical methods are insufficient for quality control or analysis of audiometrically-assessed hearing measurements. Statistical analysis of audiometrically-assessed hearing measurements is challenging due to the complex correlation structure of the data, and because the definition of hearing loss is typically based on the pure tone average which is typically the average of measurements at three or four specified frequencies, leading to a potential loss of useful information available in the individual frequency data. In addition, it is now possible to perform audiometric testing outside of the clinic with inexpensive electronic equipment in large- scale epidemiologic hearing studies. In doing so, statistical analysis must account for measurement error in the hearing tests to prevent bias in the estimates of associations and causal effects. We will develop entirely novel methods for quality control of hearing data, and for validly and efficiently assessing the exposure-hearing loss associations and their causal relationships, while accounting for the multiple layers of correlation and multivariate outcomes from multiple frequencies in audiometrically-assessed hearing data. We will develop methods to correct for measurement error-induced bias in the estimated associations and causal effects for studies where hearing outcomes are measured in non-clinical settings. We will apply the hearing data analysis methods to the Conservation of Hearing Study based in the Nurses’ Health Study II. User-friendly publicly available software development will be a central feature accompanying all new methods to be developed. We have formed an interdisciplinary team of expert theoretical and applied statisticians, epidemiologists and audiologists, and we expect to be well equipped to solve the challenging problems that have been identified.

项目摘要/摘要