Instituto de Estudos em Saúde Coletiva, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brasil.
Escola Nacional de Saúde Pública Sergio Arouca, Fundação Oswaldo Cruz, Rio de Janeiro, Brasil.
Cad Saude Publica. 2020 Feb 10;36Suppl 1(Suppl 1):e00190718. doi: 10.1590/0102-311X00190718. eCollection 2020.
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.
在具有限制堕胎法的司法管辖区中，关于接受人工流产的妇女数量的估计在科学文献中仍然很少，而且目前使用的方法得出的差异估计值需要应用创新的估计技术，如新的间接方法。在人口密度较高的地区，如巴西的首府，这种需求尤其迫切，因为不安全堕胎的数量巨大，以及由此产生的风险和危害。本文旨在根据贝叶斯层次模型，估计 2011 年里约热内卢市接受人工流产的妇女数量。该模型应用于一项家庭调查的数据，该调查支持在里约热内卢市使用网络扩展方法，该模型使用贝叶斯层次模型，基于从一般人群中随机选择的参与者的接触网络间接信息。在里约热内卢市 15-49 岁的 1,758,145 名妇女中，有 13,025 名妇女（95%CrI：10,635；15,748）在 2011 年接受了人工流产，导致每 1,000 名 15-49 岁的妇女中有 7.41（95%CrI：6.05；8.96）发生人工流产。该模型的自我验证过程确定了在社会可见度低的受污名化亚群体中低估的模式，例如接受人工流产的妇女。人工流产是里约热内卢市妇女的常见做法。新的间接估计方法可以更准确地衡量这种情况，考虑到非法的情况，并有助于制定适当的卫生政策。
