Marteleto Letícia J, Kumar Sneha, Dondero Molly, Sereno Luiz Gustavo Fernandes
Department of Sociology, University of Texas at Austin, Austin, TX, 78712, USA.
Population Research Center, University of Texas at Austin, Austin, TX, 78712, USA.
Popul Dev Rev. 2024 Jul;50(Suppl 1):213-242. doi: 10.1111/padr.12561. Epub 2023 May 17.
Recognizing the prolonged, uneven, and evolving nature of the Covid-19 pandemic, this study provides one of the first dynamic, multilevel perspectives of women's fertility intentions in response to the pandemic and its multifaceted impacts. We examine how evolving individual- and community-level Covid-19 risk mechanisms and socioeconomic and life-course conditions are associated with continuity and change in women's fertility intentions. We combine individual-level panel data from a population-based sample of women aged 18-34 in Pernambuco, Brazil in 2020 and 2021 with corresponding administrative data from 94 municipalities. We use multinomial logit regressions to model continuity and change in fertility intentions across waves. We then estimate fixed effect models to highlight the time-varying determinants of changing fertility intentions while accounting for unobserved, time-invariant individual factors. We find that high and/or increasing individual and community-level Covid-19 exposure is associated with a greater likelihood of abandoning initial childbearing plans and a greater likelihood to maintain intentions to forego versus to intend having additional children. We advance the literature by highlighting how individual-level Covid-19 infection risk perceptions matter for fertility intentions, net of community-level exposure, and the necessity of dynamic perspectives for understanding how fertility intentions have changed (or not) in response to the pandemic.
认识到新冠疫情具有长期性、不均衡性和不断演变的特点,本研究提供了首批动态、多层次视角之一,以探讨女性生育意愿如何应对疫情及其多方面影响。我们研究了不断演变的个人和社区层面的新冠疫情风险机制以及社会经济和生命历程状况如何与女性生育意愿的连续性和变化相关联。我们将2020年和2021年巴西伯南布哥州18至34岁女性的基于人群样本的个人层面面板数据与94个城市的相应行政数据相结合。我们使用多项逻辑回归来模拟各波次生育意愿的连续性和变化。然后,我们估计固定效应模型,以突出生育意愿变化的时变决定因素,同时考虑未观察到的、随时间不变的个体因素。我们发现,个人和社区层面新冠疫情暴露程度高和/或不断增加,与放弃初始生育计划的可能性更大以及维持不打算生育而非打算生育更多子女的意愿的可能性更大相关。我们通过强调个人层面的新冠疫情感染风险认知在排除社区层面暴露因素后对生育意愿的重要性,以及动态视角对于理解生育意愿如何因疫情而发生变化(或未发生变化)的必要性,推进了该领域的文献研究。