Department of Global Health Systems and Development, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana, United States of America.
PLoS Med. 2013;10(5):e1001386. doi: 10.1371/journal.pmed.1001386. Epub 2013 May 7.
Nationally representative household surveys are increasingly relied upon to measure maternal, newborn, and child health (MNCH) intervention coverage at the population level in low- and middle-income countries. Surveys are the best tool we have for this purpose and are central to national and global decision making. However, all survey point estimates have a certain level of error (total survey error) comprising sampling and non-sampling error, both of which must be considered when interpreting survey results for decision making. In this review, we discuss the importance of considering these errors when interpreting MNCH intervention coverage estimates derived from household surveys, using relevant examples from national surveys to provide context. Sampling error is usually thought of as the precision of a point estimate and is represented by 95% confidence intervals, which are measurable. Confidence intervals can inform judgments about whether estimated parameters are likely to be different from the real value of a parameter. We recommend, therefore, that confidence intervals for key coverage indicators should always be provided in survey reports. By contrast, the direction and magnitude of non-sampling error is almost always unmeasurable, and therefore unknown. Information error and bias are the most common sources of non-sampling error in household survey estimates and we recommend that they should always be carefully considered when interpreting MNCH intervention coverage based on survey data. Overall, we recommend that future research on measuring MNCH intervention coverage should focus on refining and improving survey-based coverage estimates to develop a better understanding of how results should be interpreted and used.
越来越多的国家采用具有代表性的家庭调查来衡量中低收入国家人群层面的母婴、新生儿和儿童健康（MNCH）干预措施的覆盖情况。调查是我们为此目的拥有的最佳工具，也是国家和全球决策的核心。然而，所有调查点估计都存在一定程度的误差（总调查误差），包括抽样误差和非抽样误差，在为决策目的解释调查结果时，必须考虑这两种误差。在这篇综述中，我们使用国家调查中的相关示例来提供背景信息，讨论了当解释来自家庭调查的 MNCH 干预措施覆盖估计值时，考虑这些误差的重要性。抽样误差通常被认为是点估计的精度，由 95%置信区间表示，是可测量的。置信区间可以告知关于估计参数是否可能与参数的真实值不同的判断。因此，我们建议在调查报告中始终提供关键覆盖指标的置信区间。相比之下，非抽样误差的方向和大小几乎总是不可测量的，因此是未知的。信息误差和偏差是非抽样误差在家庭调查估计中最常见的来源，我们建议在根据调查数据解释 MNCH 干预措施覆盖情况时，始终应仔细考虑这些误差。总体而言，我们建议未来关于衡量 MNCH 干预措施覆盖情况的研究应侧重于改进和提高基于调查的覆盖估计，以更好地理解如何解释和使用结果。
