School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
Int J Health Geogr. 2011 Nov 18;10:61. doi: 10.1186/1476-072X-10-61.
Many sub-Saharan countries are confronted with persistently high levels of infant mortality because of the impact of a range of biological and social determinants. In particular, infant mortality has increased in sub-Saharan Africa in recent decades due to the HIV/AIDS epidemic. The geographic distribution of health problems and their relationship to potential risk factors can be invaluable for cost effective intervention planning. The objective of this paper is to determine and map the spatial nature of infant mortality in South Africa at a sub district level in order to inform policy intervention. In particular, the paper identifies and maps high risk clusters of infant mortality, as well as examines the impact of a range of determinants on infant mortality. A Bayesian approach is used to quantify the spatial risk of infant mortality, as well as significant associations (given spatial correlation between neighbouring areas) between infant mortality and a range of determinants. The most attributable determinants in each sub-district are calculated based on a combination of prevalence and model risk factor coefficient estimates. This integrated small area approach can be adapted and applied in other high burden settings to assist intervention planning and targeting.
Infant mortality remains high in South Africa with seemingly little reduction since previous estimates in the early 2000's. Results showed marked geographical differences in infant mortality risk between provinces as well as within provinces as well as significantly higher risk in specific sub-districts and provinces. A number of determinants were found to have a significant adverse influence on infant mortality at the sub-district level. Following multivariable adjustment increasing maternal mortality, antenatal HIV prevalence, previous sibling mortality and male infant gender remained significantly associated with increased infant mortality risk. Of these antenatal HIV sero-prevalence, previous sibling mortality and maternal mortality were found to be the most attributable respectively.
This study demonstrates the usefulness of advanced spatial analysis to both quantify excess infant mortality risk at the lowest administrative unit, as well as the use of Bayesian modelling to quantify determinant significance given spatial correlation. The "novel" integration of determinant prevalence at the sub-district and coefficient estimates to estimate attributable fractions further elucidates the "high impact" factors in particular areas and has considerable potential to be applied in other locations. The usefulness of the paper, therefore, not only suggests where to intervene geographically, but also what specific interventions policy makers should prioritize in order to reduce the infant mortality burden in specific administration areas.
由于一系列生物和社会决定因素的影响，许多撒哈拉以南非洲国家的婴儿死亡率持续居高不下。特别是，由于艾滋病毒/艾滋病的流行，撒哈拉以南非洲地区的婴儿死亡率在最近几十年有所上升。了解卫生问题的地理分布及其与潜在风险因素的关系，对于进行具有成本效益的干预规划非常有价值。本文的目的是确定并绘制南非在分区一级的婴儿死亡率的空间性质，以便为政策干预提供信息。特别是，本文确定并绘制了婴儿死亡率高风险集群，并研究了一系列决定因素对婴儿死亡率的影响。使用贝叶斯方法来量化婴儿死亡率的空间风险，以及婴儿死亡率与一系列决定因素之间的显著关联（考虑到相邻地区之间的空间相关性）。根据流行率和模型风险因素系数估计值的组合，计算每个分区的最归因决定因素。这种综合的小区域方法可以适应并应用于其他高负担环境，以协助干预规划和目标定位。
南非的婴儿死亡率仍然很高，自 21 世纪初的先前估计以来，似乎没有明显减少。结果表明，各省之间以及省内之间的婴儿死亡率风险存在明显的地域差异，特定分区和省份的风险明显更高。一些决定因素被发现对分区一级的婴儿死亡率有显著的不利影响。经过多变量调整，孕产妇死亡率增加、产前 HIV 流行率、先前的兄弟姐妹死亡率和男婴性别仍然与婴儿死亡率风险增加显著相关。在这些因素中，产前 HIV 血清流行率、先前的兄弟姐妹死亡率和孕产妇死亡率分别被认为是最归因的因素。
本研究表明，先进的空间分析不仅可以在最低行政单位量化过高的婴儿死亡率风险，还可以在考虑空间相关性的情况下，使用贝叶斯模型量化决定因素的重要性。在分区一级将决定因素的流行率和系数估计值“新颖”地结合起来，以估计归因分数，进一步阐明了特定地区的“高影响”因素，并且在其他地区具有相当大的应用潜力。因此，本文的有用性不仅表明了地理干预的地点，还表明了政策制定者应该优先考虑哪些具体干预措施，以减少特定行政区域的婴儿死亡率负担。
