Research Networks in Biodemography and Demography of Aging

生物人口学和老龄人口学研究网络

• 批准号: 8721298
• 负责人: SHRIPAD D. TULJAPURKAR
• 金额: $ 23.41万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-30 至 2016-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8721298
• 关键词: Address; Aging; Area; Behavioral; Behavioral Genetics; Biological; Catalysis; Collaborations; Data; Demography; Discipline; Economics; Educational process of instructing; Educational workshop; Epidemiologic Methods; Fertilization; Genetic; Genetic Models; Genetic Variation; Genomics; Group Meetings; Health; Health Policy; Heritability; Individual; Instruction; Knowledge; Link; Longitudinal Surveys; Measures; Methods; Modeling; Nonlinear Dynamics; Online Systems; Pathway Analysis; Population; Population Genetics; Quantitative Genetics; Research; Research Infrastructure; Research Personnel; Scientist; Social Network; Surveys; Techniques; Time; Training; Work; base; biodemography; cost; genetic epidemiology; genetic pedigree; innovation; interest; meetings; network models; novel; social; theories; tool; trait; working group

Research on aging and health requires knowledge, methods, ideas and data from multiple disciplines and presents great opportunities for cross-fertilization between disciplines. But there are many challenges to cross-fertilization - communicating questions across disciplines, cross-teaching researchers in aging about Other fields, and stimulating innovative collaborations between established scientists from different fields to work on aging. This project will address these challenges by developing research networks via the following specific aims: Specific Aim 1: Conduct training workshops in the formal demography and biodemography of aging to train young and new investigators in diverse analytical and quantitative approaches to aging. Specific Aim 2: Organize catalysis meetings to stimulate cross-disciplinary collaborative research on aging that deals with several broad questions - the interplay between genetics and behavioral and social factors, theories and data on social networks, and the integration into aging research of work on quantitative and population genetics and genomics, evolutionary and ecological genetics, epidemiology and health policy. Specific Aim 3: Organize advanced workshops/seminars to bring together small groups of researchers to focus intensively on particular questions and data in aging research, using a variety of tools including short working group meetings, web-based seminars and workshops, and other web-based collaborative tools. Training workshops teach young and new researchers about recent scientific work on aging and provide links to established investigators. Catalysis meetings, successful in other fields, provide a stimulating setting in which a small group explores and formulates new cross-disciplinary ideas. Advanced workshops are expected to emerge from catalysis meetings and go beyond them by allowing researchers with substantive interests in a problem to work through in detail ideas and plans for collaborative work. These activities will strengthen research on aging and launch collaborative research in several emerging areas as requested in the FOA on Network Infrastructure Support for Emercino Behavioral and Social Research Areas in Aoinc.

老龄化与健康的研究需要多学科的知识、方法、思想和数据， 为学科间的交叉提供了巨大的机会。但是， 交叉施肥-跨学科交流问题，交叉教学研究人员在老龄化有关 其他领域，并鼓励来自不同领域的知名科学家之间的创新合作， 研究衰老 该项目将通过以下具体目标建立研究网络来应对这些挑战： 具体目标1：举办关于老龄化的正式人口学和生物人口学的培训讲习班， 年轻和新的研究人员在不同的分析和定量方法老化。 具体目标2：组织催化会议以刺激老龄化跨学科合作研究 它涉及几个广泛的问题-遗传学和行为及社会因素之间的相互作用， 关于社交网络的理论和数据，以及将定量和 人口遗传学和基因组学、进化和生态遗传学、流行病学和卫生政策。 具体目标3：组织高级讲习班/研讨会，将研究人员小组聚集在一起， 专注于特定的问题和数据在老龄化研究，使用各种工具，包括短 工作组会议、网上研讨会和讲习班以及其他网上协作工具。 培训讲习班向年轻和新的研究人员介绍有关衰老的最新科学工作， 与现有调查人员的联系。催化会议，在其他领域取得成功，提供了一个刺激的设置 一个小组在其中探索和制定新的跨学科的想法。高级研讨会是 预计将出现从催化会议，并超越他们，让研究人员与实质性的 对一个问题的兴趣，通过详细的想法和计划进行合作。这些活动将 加强对老龄问题的研究，并根据《 在Aoinc的Emercino行为和社会研究领域的网络基础设施支持的FOA。

项目成果

Mutations and the age pattern of death.

突变和死亡年龄模式。

• DOI: 10.1073/pnas.1307921110
• 发表时间: 2013
• 期刊: Proceedings of the National Academy of Sciences of the United States of America
• 影响因子: 11.1
• 作者: Tuljapurkar,Shripad

Machine learning approaches to the social determinants of health in the health and retirement study.

• DOI: 10.1016/j.ssmph.2017.11.008
• 发表时间: 2018-04
• 期刊: SSM - population health
• 作者: Seligman B;Tuljapurkar S;Rehkopf D
• 通讯作者: Rehkopf D

Influence of life-history tactics on transient dynamics: a comparative analysis across mammalian populations.

• DOI: 10.1086/677929
• 发表时间: 2014-11
• 期刊: The American naturalist
• 作者: Gamelon M;Gimenez O;Baubet E;Coulson T;Tuljapurkar S;Gaillard JM
• 通讯作者: Gaillard JM

The Geographic Distribution of Genetic Risk as Compared to Social Risk for Chronic Diseases in the United States.

美国慢性病遗传风险与社会风险的地理分布比较。

• DOI: 10.1080/19485565.2016.1141353
• 发表时间: 2016
• 期刊: Biodemography and social biology
• 影响因子: 1.3
• 作者: Rehkopf,DavidH;Domingue,BenjaminW;Cullen,MarkR
• 通讯作者: Cullen,MarkR

Structured population models: introduction.

结构化人口模型：简介。

• DOI: 10.1016/j.tpb.2012.10.007
• 发表时间: 2012
• 期刊: Theoretical population biology
• 影响因子: 1.4
• 作者: Tuljapurkar,Shripad;Coulson,Tim;Steiner,UlrichKarl
• 通讯作者: Steiner,UlrichKarl