Biometrical Modeling of Fertility Using the NLSY

使用 NLSY 进行生育力生物统计建模

• 批准号: 6685779
• 负责人: Joseph L. Rodgers
• 金额: $ 27.6万
• 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/6685779
• 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）：请求支持一个持续四年的五部分项目。我们的团队最近的工作记录了遗传影响对生育能力及其前体的经验存在（包括初潮，性启动，生育期望和怀孕）。此外，已经确定了基因型X环境相互作用，例如生育能力过渡的遗传力的历史变化。提出的工作从经验和理论上扩展了先前的结果。这项研究将由三种理论观点激励：在Fisher的自然选择基本定理中，在生物领域中；在人口统计领域与生育率转变有关；在与最初由乌德里（Udry）开发的新出现的理论结构有关的行为遗传领域中，这表明遗传和环境影响如何应与社会内生育能力的意志控制水平有关。未来的工作可以在每个理论背景下扩大我们的理解。拟议的研究在方法论上以几种不同的方式具有创新性：我们将过去的独立亲属设计扩展到多元亲属关系设计；我们结合了单变量DF分析和多元MX分析的应用；我们将来自NLSY-Youth的数据与NLSY-Children数据集相结合。 NLSY亲属链接是通过该团队在过去的工作中开发的亲属链接算法来识别的。这些努力组织成四个研究项目和一个数据管理项目。研究项目＃1研究了NLSY-Youth数据中女性之间整个生育能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数据集的亲属关系，这是进行研究项目＃2至4的前提。研究项目＃2研究了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设计设计，其中将母女对与纽阿姨对比较。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调解影响。潜在的主持人/调解员包括教育，家庭结构和家庭环境的质量。