Biometrical Modeling of Fertility Using the NLSY

描述（由申请人提供）：要求支持一个为期四年的五部分项目。我们团队最近的工作记录了遗传对生育结果及其前兆（包括月经初潮、性行为开始、生育预期和怀孕）的影响。此外，基因型与环境的相互作用也已被确定，例如与生育过渡有关的生育遗传力的历史变化。提出的工作在经验和理论上扩展了以前的结果。本研究将从三个理论角度出发：在生物学领域由费雪的自然选择基本定理推动；在人口领域与生育率过渡有关；在行为遗传领域，与最初由Udry提出的一个新兴理论结构有关，该理论结构表明基因和环境的影响应该如何在社会中对生育的意志控制水平方面进行权衡。未来的工作可以扩展我们在每个理论背景下的理解。本研究在方法上有几个不同的创新：我们将过去的单变量亲属关系设计扩展到多变量亲属关系设计；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和NLSY-Children数据集的数据结合起来。NLSY亲属关系是通过该团队在过去的工作中开发的亲属关系联系算法来确定的。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数据中所有女性生育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数据集的亲属关系结构，这是开展研究项目#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，将母女对与姨妈侄女对进行比较。最后，研究项目#4调查了研究项目#1-#2中发现的各种调节和中介影响。潜在的调节/调节因素包括教育、家庭结构和家庭环境质量。

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.