Aggregate measures of family planning are used to monitor demand for and usage of contraceptive methods in populations globally, for example as part of the FP2030 initiative. Family planning measures for low- and middle-income countries are typically based on data collected through cross-sectional household surveys. Recently proposed measures account for sexual activity through assessment of the distribution of time-between-sex (TBS) in the population of interest. In this paper, we propose a statistical approach to estimate the distribution of TBS using data typically available in low- and middle-income countries, while addressing two major challenges. The first challenge is that timing of sex information is typically limited to women's time-since-last-sex (TSLS) data collected in the cross-sectional survey. In our proposed approach, we adopt the current duration method to estimate the distribution of TBS using the available TSLS data, from which the frequency of sex at the population level can be derived. Furthermore, the observed TSLS data are subject to reporting issues because they can be reported in different units and may be rounded off. To apply the current duration approach and account for these data reporting issues, we develop a flexible Bayesian model, and provide a detailed technical description of the proposed modeling approach.
翻译:计划生育的综合措施用于监测全球人口对避孕方法的需求和使用情况,例如,作为FP2030倡议的一部分。中低收入国家的计划生育措施通常以通过跨部门住户调查收集的数据为基础。最近提出的措施通过评估感兴趣的人口中两性间时间分配情况来说明性活动。在本文件中,我们建议采用统计方法,利用中低收入国家通常可获得的数据来估计TBS的分布情况,同时应对两大挑战。第一个挑战是,性别信息的时间通常限于在跨部门调查中收集的妇女自上而下的性(TSLS)数据。在我们提议的办法中,我们采用目前的方法,利用现有的TBS数据来估计TS的分布情况,从中可以得出人口层面的性别频率。此外,观察到的TSLS数据是报告问题的统计方法,因为可以在不同单位报告这些数据,并且可以四舍五入。为了采用目前的持续时间方法和说明这些数据报告问题,我们制定了一个灵活的Bayesian模型,并提出了一个详细的技术说明。