Methods for Time-Varying Disease Attribution in Chronic Disease Prevention

慢性病预防中随时间变化的疾病归因方法

• 批准号: 8577058
• 负责人: Ying Qing Chen
• 金额: $ 35.53万
• 依托单位: FRED HUTCHINSON CANCER RESEARCH CENTER
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-30 至 2017-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8577058
• 关键词: Accounting; Adherence; Adult; Alcohol consumption; American; Asia; Asians; Body Weight; Burn injury; Cessation of life; Chronic; Chronic Disease; Clinical; Cohort Studies; Collection; Communities; Computer software; Counseling; Country; Data; Diet; Diet Habits; Disease; Disease Outcome; Epidemiologic Studies; Epidemiology; Equilibrium; Ethics; Event; Exercise; Health; Individual; Lead; Life; Life Expectancy; Measures; Medical; Methods; Nature; Non-Insulin-Dependent Diabetes Mellitus; Obesity; Outcome; Pharmaceutical Preparations; Population; Population Attributable Risks; Pregnancy; Prevalence; Prevention; Prevention Research; Prevention strategy; Process; Public Health; Residual state; Resources; Risk; Risk Factors; Risk Reduction; Rosa; Statistical Methods; Time; Tobacco smoking; Translational Research; Vascular Diseases; World Health Organization; base; cancer type; clinical care; cohort; disorder prevention; disorder risk; flexibility; improved; moderate obesity; modifiable risk; obesity prevention; public health relevance; tool; trend

DESCRIPTION (provided by applicant): The objective of this methods proposal is to develop and apply new statistical methods to improve scientific inferences on the disease attribution associated with risk factors, such as obesity and tobacco smoking, for data collected from longitudinal cohort studies in chronic disease prevention research, specifically aiming to: (1) develop general statistical methods for time-varying attributable risk functions (ARF) to assess and compare prevention strategies; (2) develop statistical methods for a set of pairwise ARF's to assess and identify practically optimal prevention strategies; (3) develop statistical methods to evaluate the disease attribution in residual time; (4) develop statistical software and apply the developed methods to a large collection of cohort data from the Asia Cohort Consortium.

描述（由申请方提供）：本方法提案的目的是开发和应用新的统计方法，以改善对慢性病预防研究中纵向队列研究收集的数据与风险因素（如肥胖和吸烟）相关的疾病归因的科学推断，具体目的是：（1）为时变归因风险函数（ARF）发展一般统计方法，以评估和比较预防策略;（2）为一组成对ARF发展统计方法，以评估和确定实际最佳预防策略;（3）发展统计学方法，以评估疾病在剩余时间中的归因;（4）开发统计学软件，并将所开发的方法应用于亚洲队列联盟的大量队列数据。