CONTRACEPTIVE CHOICE IN A CHANGING ENVIRONMENT

这项研究考察了选择避孕措施的决定因素 泰国南荣区。避孕选择(包括 决定根本不使用某个方法)发生在 相对复杂的社会世界，具有以下特点 个人、夫妇、家庭和社区都是相关的。 由于数据和方法的限制，过去的工作没有 能够尽可能地对整个模型进行建模 影响避孕选择的决定因素的复杂性。 使用丰富的纵向数据集并适应最近开发的 多变量技术，拟议的研究将包括 从人口学、社会学和经济学的见解到更好 了解避孕选择决策的决定因素。 泰国南荣区是一个有趣的背景 来研究避孕行为。它是最少的之一 泰国的发达地区和一直是紧张的焦点 最近的开发活动。人们的期望是，随着 环境改变，避孕行为也会改变。 多变量分析将使用大约5800个样本 1984年和1988年访问的15岁至49岁的已婚女性(至 将于1988年6月前完成)。这些妇女居住在50个村庄， 1984年，每个村庄都有丰富的社区级数据 和1988年。 除了对现有纵向数据进行多变量分析之外 数据集，计划在第二个月收集定性数据 项目的年份。几个焦点小组会议将在#年举行 南荣区，这将有助于改善 多变量模型的规范和更广泛和更深入的 对结果的理解。

This research examines the determinants of contraceptive choice in Nang Rong district, Thailand. Contraceptive choice (including the decision not to use a method at all) takes place within a relatively complex social world, with characteristics of individuals, couples, households, and communities all relevant. Because of data and methodological constraints, past work has not been able to proceed as far as desirable in modeling the full complexity of determinants which affect contraceptive choices. Using a rich longitudinal data set and adapting recently developed multivariate techniques, the proposed research will incorporate insights from demography, sociology, and economics to better understand the determinants of the contraceptive choice decision. Nang Rong district, Thailand serves as an interesting context in which to study contraceptive behavior. It is one of the least developed regions of Thailand and has been the focus of intense development activity recently. The expectation is that as the context changes, contraceptive behavior will change too. The multivariate analysis will use a sample of approximately 5,800 ever-married women aged 15 to 49 interviewed in 1984 and 1988 (to be completed by June 1988). These women reside in 50 villages, and rich community level data is available for each village for 1984 and 1988. In addition to multivariate analysis of this existing longitudinal data set, qualitative data collection is planned for the second year of the project. Several focus group sessions will be held in Nang Rong district, which will contribute to an improved specification of the multivariate model and a broader and deeper understanding of the results.