Women who have undergone abortion in the city of Rio de Janeiro, Brazil: application of a Bayesian hierarchical model

Abstract: Estimates of number of women who have undergone induced abortion in jurisdictions with restrictive abortion laws are still scarce in the scientific literature, and the disparate estimates from currently used methods call for the application of innovative estimation techniques such as new indirect methods. This need is especially acute in more densely populated areas, such as Brazil’s state capitals, given the magnitude of unsafe abortions and the resulting risks and harms. The article aims to estimate the number of women who had induced abortions in the city of Rio de Janeiro in 2011, based on a Bayesian hierarchical model. The model was applied to data from a household survey that supported the use of the network scale-up method in the city of Rio de Janeiro, a Bayesian hierarchical model using indirect information based on the contact networks of randomly selected participants from the general population. Among the 1,758,145 women 15-49 years of age living in the city of Rio de Janeiro, 13,025 women (95%CrI: 10,635; 15,748) had induced abortions in 2011, resulting in a mean cumulative incidence of 7.41 (95%CrI: 6.05; 8.96) for every 1,000 women 15-49 years of age. The model’s self-validation process identified patterns of underestimation in stigmatized subpopulations with low social visibility, such as women who have undergone induced abortion. Induced abortion is a common practice among women in the city of Rio de Janeiro. New indirect estimation methods can contribute to more precise measurement of this event, considering the context of illegality, and thereby contribute to appropriate health policies.

摘要：目前科学文献中，针对实施限制性堕胎法的管辖区域内接受人工流产（induced abortion）的女性人数估算仍较为匮乏，且当前所用方法得到的估算结果参差不齐，亟需应用创新的估算技术，例如新型间接估算方法。鉴于不安全流产（unsafe abortion）的发生规模及其引发的各类风险与危害，此类需求在巴西各州府等人口稠密地区尤为突出。本研究基于贝叶斯分层模型（Bayesian hierarchical model），旨在估算2011年里约热内卢市接受人工流产的女性人数。研究将该模型应用于里约热内卢市一项家庭调查的数据，该调查支持使用网络规模估算方法（network scale-up method）；此模型为基于普通人群随机选取受访者的社交网络间接信息构建的贝叶斯分层模型。在里约热内卢市居住的1758145名15~49岁育龄女性中，2011年共有13025名女性接受了人工流产（95%可信区间（CrI）：10635~15748），对应每1000名15~49岁育龄女性的平均累积发生率为7.41（95%可信区间（CrI）：6.05~8.96）。该模型的自验证过程显示，在社会可见度较低的污名化亚群（如曾接受人工流产的女性）中，存在估算值偏低的模式。人工流产在里约热内卢市女性群体中较为普遍。结合堕胎行为的非法性背景，新型间接估算方法可助力更精准地测算该事件的发生情况，进而为制定合理的卫生政策提供支撑。