Discipline of Public Health Medicine, College of Health Sciences, University of KwaZulu-Natal, 2nd Floor George Campbell Building, Howard College Campus, Durban, 4001, South Africa.
Department of Management Science and Technology, The Technical University of Kenya, Nairobi, Kenya.
BMC Public Health. 2021 Dec 30;21(1):2331. doi: 10.1186/s12889-021-12210-9.
Adverse pregnancy outcomes jointly account for a high proportion of mortality and morbidity among pregnant women and their infants. Furthermore, the burden attributed to adverse pregnancy outcomes remains high and inadequately characterised due to the intricate interplay of its etiology and shared set of important risk factors. This study sought to quantify and map the underlying risk of multiple adverse pregnancy outcomes in Kenya at sub-county level using a shared component space-time modelling framework.
Reported sub-county level adverse pregnancy outcomes count from January 2016 - December 2019 were obtained from the Kenyan District Health Information System. A Bayesian hierarchical spatio-temporal model was used to estimate the joint burden of adverse pregnancy outcomes in space (sub-county) and time (year). To improve the precision of our estimates over time and space, information across the outcomes were combined via the shared and the outcome-specific components using a shared component model with spatio-temporal interactions.
Overall, the total number of adverse outcomes in pregnancy increased by 14.2% (95% UI: 14.0-14.5) from 88,816 cases in 2016 to 101,455 cases in 2019. Between 2016 and 2019, the estimated low birth weight rate and the pre-term birth rate were 4.5 (95% UI: 4.4-4.7) and 2.3 (95% UI: 2.2-2.5) per 100 live births. The stillbirth and neonatal death rates were estimated to be 18.7 (95% UI: 18.0-19.4) and 6.9 (95% UI: 6.4-7.4) per 1000 live births. The magnitude of the spatio-temporal variation attributed to shared risk was high for pre-term births, low birth weight, neonatal deaths, stillbirths and neonatal deaths, respectively. The shared risk patterns were dominant in sub-counties located along the Indian ocean coastline, central and western Kenya.
This study demonstrates the usefulness of a Bayesian joint spatio-temporal shared component model in exploiting specific and shared risk of adverse pregnancy outcomes sub-nationally. By identifying sub-counties with elevated risks and data gaps, our estimates not only assert the need for bolstering maternal health programs in the identified high-risk sub-counties but also provides a baseline against which to assess the progress towards the attainment of Sustainable Development Goals.
不良妊娠结局共同导致孕妇及其婴儿的死亡率和发病率居高不下。此外，由于其病因和共同的重要危险因素之间的复杂相互作用，不良妊娠结局的负担仍然很高且描述不足。本研究旨在使用共享分量时空建模框架，在县级以下层面量化和绘制肯尼亚多种不良妊娠结局的潜在风险。
从肯尼亚地区卫生信息系统中获取 2016 年 1 月至 2019 年 12 月报告的县级以下不良妊娠结局计数。使用贝叶斯分层时空模型估计空间（县级以下）和时间（年份）不良妊娠结局的联合负担。为了提高我们在时间和空间上的估计精度，通过共享分量模型和时空相互作用，跨结局合并信息，使用共享和特定于结局的分量。
总体而言，2016 年至 2019 年，妊娠不良结局总数增加了 14.2%（95%UI：14.0-14.5），从 2016 年的 88816 例增加到 2019 年的 101455 例。2016 年至 2019 年间，估计的低出生体重率和早产率分别为每 100 例活产 4.5（95%UI：4.4-4.7）和 2.3（95%UI：2.2-2.5）。死产和新生儿死亡率估计分别为每 1000 例活产 18.7（95%UI：18.0-19.4）和 6.9（95%UI：6.4-7.4）。早产、低出生体重、新生儿死亡、死产和新生儿死亡的共享风险归因的时空变异性程度很高。共享风险模式在印度洋沿岸、肯尼亚中部和西部的县级以下地区占主导地位。
本研究证明了贝叶斯联合时空共享分量模型在国家以下利用不良妊娠结局的特定和共享风险方面的有用性。通过确定高风险县级以下地区的县级以下地区，我们的估计不仅强调了加强这些高风险县级以下地区的孕产妇健康计划的必要性，而且还提供了一个基线，用于评估实现可持续发展目标的进展情况。
