Biometrical Modeling of Fertility Using the NLSY

使用 NLSY 进行生育力生物统计建模

• 批准号: 6923560
• 负责人: Joseph L. Rodgers
• 金额: $ 26.36万
• 依托单位: UNIVERSITY OF OKLAHOMA
• 依托单位国家: 美国
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-07-07 至 2007-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6923560
• 关键词: academic achievement; adolescence (12-20); adult human (21+); behavioral /social science research tag; behavioral genetics; clinical research; data management; education; expectancy; family genetics; family structure /dynamics; fertility; gene environment interaction; generation difference; human data; human puberty; longitudinal human study; mathematical model; menstrual cycle; model design /development; natural selections; pregnancy; sex behavior; statistics /biometry

DESCRIPTION (provided by applicant): Support is requested for a five-component project lasting four years. Recent work by our team has documented the empirical existence of genetic influences on both fertility outcomes and their precursors (including menarche, sexual initiation, fertility expectations, and pregnancy). In addition, genotype x environment interactions have been identified, such as historical changes in the heritability of fertility in relation to fertility transition. The proposed work extends previous results both empirically and theoretically. This research will be motivated by three theoretical perspectives: in the biological domain by Fisher's Fundamental Theorem of Natural Selection; in the demographic domain in relation to fertility transition; and in the behavior genetic domain in relation to an emerging theoretical structure originally developed by Udry suggesting how genetic and environmental influences should trade off in relation to the level of volitional control over fertility within the society. Future work can expand our understanding within each theoretical context. The proposed research is methodologically innovative in several different ways: We expand past univariate kinship designs into multivariate kinship designs; we combine applications of univariate DF Analyses and multivariate Mx Analyses; and we combine data from the NLSY-Youth with the NLSY-Children dataset. The NLSY kinship links are identified through the kinship linking algorithms that have been developed in past work by this team. These efforts are organized into four research projects and one data management project. Research Project #1 investigates the overlapping genetic basis for a whole range of fertility variables among females in the NLSY-Youth data. Next, the data management project is devoted to redefinition of the kinship structure of the NLSY-Children dataset, a prerequisite for conducting Research Projects #2 through #4. Research Project #2 investigates the overlapping genetic and environmental structure for the early fertility behaviors in the NLSY-Children data. Research Project #3 is baseed on a new inter-generational kinship design in which mother-daughter pairs are compared to aunt-niece pairs. Finally, Research Project #4 investigates the various moderating and mediating influences on the patterns found in Research Projects #1-#2. Potential moderators/mediators include education, family structure, and quality of the family environment.

描述（由申请人提供）：请求为一个持续四年的由五部分组成的项目提供支持。我们团队最近的工作记录了遗传对生育结果及其前兆（包括初潮、性开始、生育期望和怀孕）的影响的实证存在。此外，基因型与环境的相互作用也已被确定，例如与生育转变相关的生育遗传力的历史变化。所提出的工作在经验和理论上扩展了先前的结果。这项研究将受到三个理论视角的推动：在生物学领域，费希尔自然选择基本定理；在与生育率转变相关的人口领域；在行为遗传领域，与乌德里最初开发的新兴理论结构相关，该理论结构表明遗传和环境影响应如何与社会内对生育的意志控制水平进行权衡。未来的工作可以扩大我们在每个理论背景下的理解。所提出的研究在几个不同方面在方法上具有创新性：我们将过去的单变量亲属关系设计扩展到多元亲属关系设计；我们结合了单变量 DF 分析和多变量 Mx 分析的应用；我们将 NLSY-Youth 数据集与 NLSY-Children 数据集相结合。 NLSY 亲属关系链接是通过该团队在过去的工作中开发的亲属关系链接算法来识别的。这些工作分为四个研究项目和一个数据管理项目。研究项目#1 调查了 NLSY-Youth 数据中女性一系列生育力变量的重叠遗传基础。接下来，数据管理项目致力于重新定义 NLSY-Children 数据集的亲属结构，这是进行研究项目 #2 至 #4 的先决条件。研究项目#2 调查了 NLSY-Children 数据中早期生育行为的重叠遗传和环境结构。研究项目#3基于一种新的代际亲属关系设计，其中母女对与姑姑侄女对进行比较。最后，研究项目#4 调查了对研究项目#1-#2 中发现的模式的各种调节和中介影响。潜在的调节因素/中介因素包括教育、家庭结构和家庭环境质量。