Residential Context and Childbearing: Application of Multilevel Analysis to Study Individual and Contextual Determinants of Fertility

居住环境和生育：应用多层次分析研究生育率的个体和环境决定因素

• 批准号: 2095177
• 金额: --
• 依托单位: University of St Andrews
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2018
• 资助国家: 英国
• 起止时间: 2018 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2095177
• 关键词: Residential; Context; Childbearing; Application; Multilevel

Fertility levels are below replacement level in most industrialised countries and have further declined in recent years. However, they vary significantly within countries by residential context. Fertility is high in rural areas and small towns and low in large cities. The reasons for spatial variation in fertility remain unclear. Some studies argue that fertility levels vary between places because different people live in different settlements. Others emphasise the importance of factors related to immediate living environment. The role of selective migrations has also been discussed.This PhD project will investigate childbearing patterns by residential context in Britain, a country with a significant spatial fertility variation. The objectives are: First, to determine the extent to which spatial variation in childbearing patterns is attributed to compositional characteristics and selective migrations, and what role contextual factors play. Second, to investigate how contextual factors influence individuals' childbearing behaviour. Third, to develop a spatial multilevel multiprocess hazard model to properly measure the effect of living environment on individuals' childbearing behaviour. An understanding of how residential context influences fertility is essential to improve our understanding of the causes of low fertility in industrialised countries.The project will develop and apply a spatial multilevel multiprocess hazard model to data from the ONS Longitudinal Study, the Scottish Longitudinal Study and the British Household Panel Survey to determine how contextual factors shape individuals' childbearing behaviour. The performance of the proposed approach will be compared to that of conventional methods using maximum likelihood and Bayesian methods. The project will provide rich and reliable information on spatial fertility variation in Britain and will improve our understanding of the causes of high fertility in some areas and low fertility in others. The developed method could be applied to study contextual determinants of other domains of individuals' behaviour (e.g. health, employment, residential relocations).

大多数工业化国家的生育率低于更替水平，近年来进一步下降。然而，各国的居住环境不同，这些指标也有很大差异。农村地区和小城镇的生育率高，大城市的生育率低。生育率空间差异的原因尚不清楚。一些研究认为，不同地区的生育率水平不同，因为不同的人生活在不同的定居点。其他人则强调与直接生活环境有关的因素的重要性。选择性移民的作用也进行了讨论。这个博士项目将调查在英国，一个具有显着的空间生育率变化的国家的居住环境的生育模式。其目标是：首先，要确定在何种程度上的生育模式的空间变化是由于组成特征和选择性迁移，以及什么样的作用的背景因素发挥。第二，探讨情境因素如何影响个体的生育行为。第三，建立一个空间多层次多过程风险模型，以恰当地衡量生活环境对个体生育行为的影响。了解居住环境如何影响生育率对于提高我们对工业化国家低生育率原因的理解至关重要。该项目将开发一个空间多层次多过程风险模型，并将其应用于ONS纵向研究，苏格兰纵向研究和英国家庭面板调查的数据，以确定环境因素如何塑造个人的生育行为。所提出的方法的性能进行比较，使用最大似然和贝叶斯方法的传统方法。该项目将提供关于英国生育率空间变化的丰富和可靠的信息，并将增进我们对某些地区生育率高而另一些地区生育率低的原因的了解。所开发的方法可应用于研究个人行为其他领域（如健康、就业、住宅搬迁）的背景决定因素。