Fertility After a Large-Scale Disaster

大规模灾难后的生育率

• 批准号: 8433215
• 负责人: JENNA E. NOBLES
• 金额: $ 7.14万
• 依托单位: UNIVERSITY OF WISCONSIN-MADISON
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-02-28 至 2016-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8433215
• 关键词: Address; Affect; Area; Baseline Surveys; Birth; Characteristics; China; Communities; Community Surveys; Complement; Complex; Contraceptive Agents; Contraceptive Availability; Country; Data; Data Analyses; Data Collection; Data Set; Disasters; Earthquakes; Economics; Empirical Research; Environment; Event; Evolution; Family; Fertility; Fertility Determinant; Fertility Rates; Funding; Goals; Haiti; Hazard Models; Indian Ocean; Individual; Indonesia; Interview; Literature; Low income; Measurement; Measures; Natural Disasters; Pakistan; Pattern; Persons; Physiological; Policies; Population; Population Dynamics; Process; Provider; Province; Proxy; Recovery; Research; Resources; Respondent; Series; Services; Shock; Spontaneous abortion; Sumatra; Surveys; Time; Trauma; Tsunami; United States; Water; Woman; Work; base; design; hazard; improved; informant; insight; interest; killings; men; mortality; physical conditioning; public health relevance; response; trend

DESCRIPTION (provided by applicant): This application seeks funding to examine demographic change after a recent large-scale disaster, the 2004 Indian Ocean tsunami. We aim to elucidate the timing, pace, and determinants of fertility in Indonesian communities that were exposed to a continuum of destruction. To do so, we draw from a highly unusual data set - the Study of the Tsunami Aftermath and Recovery (STAR) - collected during 2004-2010 in over 500 communities from two provinces of Indonesia. The study includes regions of Indonesia that were completely destroyed as well as communities that were not exposed to the tsunami. The data thus support a treatment-control design to study the disaster's effects. Because the baseline survey was conducted in 2004, the survey is representative of population before the disaster, and much is known about the survey respondents before the event (N~40,000). Data on these respondents, their families, their communities, and their service providers were collected beginning five months after the tsunami. Re- interview occurred approximately annually for five years after the event. We aim to capture the timing and the evolution of a fertility response to the disaster by comparing temporal trends in aggregate fertility in the heavily damaged and undamaged regions. We then develop a series of multilevel hazard models that examine how the timing of post-disaster fertility responded to pre-disaster attributes, disaster exposure, and temporal shifts in fertility antecedents - such as contraceptive availability and economic stability - in the wake of the event. Measurement of respondents prior to the disaster provides a means of causally attributing observed fertility changes to mechanisms shifted by the disaster. The proposed research both informs our understanding of the post-disaster environment in Indonesia and provides theoretical insights for larger questions regarding demographic response to population trauma. Of particular importance is our ability to assess why fertility changes in the context of disaster - an underdeveloped line of inquiry with clear implications for improving recovery policy and interpreting modern fertility trends.

描述(申请人提供)：这项申请寻求资金，以审查最近的一次大规模灾难，2004年印度洋海啸后的人口变化。我们的目标是阐明印度尼西亚社区中遭受连续破坏的生育率的时间、速度和决定因素。为此，我们采用了一个极不寻常的数据集--海啸灾后和灾后恢复研究(STAR)--在2004-2010年间收集了印度尼西亚两个省的500多个社区的数据。这项研究包括印度尼西亚被完全摧毁的地区以及没有暴露在海啸中的社区。因此，这些数据支持研究灾难影响的处理-控制设计。由于基线调查是在2004年进行的，调查具有灾前人口的代表性，对灾前调查对象(N~4万人)有较多了解。关于这些受访者、他们的家庭、他们的社区和他们的服务提供者的数据是从海啸发生五个月后开始收集的。在事件发生后的五年里，大约每年都会进行重新面谈。我们的目标是通过比较严重受灾地区和未受灾地区的总生育率的时间趋势，来捕捉应对灾害的生育率的时间和演变。然后，我们开发了一系列多水平的风险模型，考察了灾后生育率的时间对灾前属性、灾难暴露以及事件发生后生育率先行因素的时间变化--如避孕措施的可获得性和经济稳定性--的反应。灾害发生前对受访者的测量提供了一种手段，可以将观察到的生育率变化归因于灾害所改变的机制。拟议的研究既为我们提供了对印度尼西亚灾后环境的理解，也为有关人口对人口创伤的反应的更大问题提供了理论见解。尤其重要的是，我们有能力评估为什么在发生灾害时生育率会发生变化--这是一种不发达的调查方法，对改进复苏政策和解释现代生育率趋势具有明显的影响。