Estimating the infant mortality rate from DHS birth histories in the presence of age heaping.
Estimating the infant mortality rate from DHS birth histories in the presence of age heaping.
复制标题
在年龄堆积的情况下，估计DHS出生历史的婴儿死亡率。
DOI：
10.1371/journal.pone.0259304
复制
发表时间：
2021
期刊：
影响因子：
3.7
通讯作者：
Guillot M
中科院分区：
文献类型：
--
作者：
Romero Prieto J;Verhulst A;Guillot M
婴儿死亡率是衡量人口健康的关键指标，但在没有完整生命登记制度的国家，婴儿死亡率的衡量存在反应偏差，这些国家依赖通过抽样调查收集的出生史。最突出的偏见之一是，在这些出生历史中，儿童死亡往往是在12个月大时大量堆积的。由于这个问题，分析师和国际机构不直接使用基于人口与健康调查(DHS)等调查的IMR估计；他们转而依赖死亡率模型，如模型生命表。然而，在这种情况下使用模型生命表是武断的，这种方法在多大程度上适当地解决了基于国土安全部的IMR估计的偏差仍不清楚。这妨碍了我们监测低收入和中等收入国家的IMR水平和趋势的能力。这项研究的目的是评估基于DHS的IMR估计中的年龄堆积偏差，并提出一种调整这种偏差的改进方法。我们的方法依赖于最近开发的对数二次模型，该模型可以根据0到5岁之间的详细年龄预测特定年龄的死亡率。该模型的系数来自新建立的数据库-5岁以下死亡率数据库(U5MD)，该数据库代表了拥有高质量生命登记数据的国家的死亡率经验。我们将该模型应用于204项国土安全部调查，并将未经调整的IMR值与用对数二次模型以及经典模型生命表方法调整后的IMR值进行了比较。结果表明，与现有的知识相反，在12个月龄时堆积年龄很少会在IMR估计中产生大量的偏差。在大多数情况下，未调整的IMR值与调整后的值的偏差不超过+/-5%。相比之下，模型寿命表法在调整后的IMR值中引入了不必要的向下偏差。我们还发现，撒哈拉以南非洲和南亚这两个地区目前5岁以下儿童死亡率的年龄模式与U5MD所代表的经验大相径庭。对于这些国家，无论是现有的模型寿命表，还是对数二次模型，都不能产生经验支持的IMR调整。在基于国土安全部的IMR估计中，12个月的年龄堆积产生的偏倚比之前认为的要小。如果调查中存在大量的年龄堆积，对数二次模型允许用户评估，并在必要时调整IMR估计，其方式比现有方法更能从当地死亡率模式中获得信息。今后的研究应致力于了解为什么撒哈拉以南非洲和南亚国家的五岁以下儿童死亡率有如此不同的年龄模式。
The infant mortality rate (IMR) is a critical indicator of population health, but its measurement is subject to response bias in countries without complete vital registration systems who rely instead on birth histories collected via sample surveys. One of the most salient bias is the fact that child deaths in these birth histories tend to be reported with a large amount of heaping at age 12 months. Because of this issue, analysts and international agencies do not directly use IMR estimates based on surveys such as Demographic and Health Surveys (DHS); they rely instead on mortality models such as model life tables. The use of model life tables in this context, however, is arbitrary, and the extent to which this approach appropriately addresses bias in DHS-based IMR estimates remains unclear. This hinders our ability to monitor IMR levels and trends in low-and middle-income countries. The objective of this study is to evaluate age heaping bias in DHS-based IMR estimates and propose an improved method for adjusting this bias. Our method relies on a recently-developed log-quadratic model that can predict age-specific mortality by detailed age between 0 and 5. The model’s coefficients were derived from a newly constituted database, the Under-5 Mortality Database (U5MD), that represents the mortality experience of countries with high-quality vital registration data. We applied this model to 204 DHS surveys, and compared unadjusted IMR values to IMR values adjusted with the log-quadratic model as well as with the classic model life table approach. Results show that contrary to existing knowledge, age heaping at age 12 months rarely generates a large amount of bias in IMR estimates. In most cases, the unadjusted IMR values were not deviating by more than +/- 5% from the adjusted values. The model life table approach, by contrast, introduced an unwarranted, downward bias in adjusted IMR values. We also found that two regions, Sub-Saharan Africa and South Asia, present age patterns of under-5 mortality that strongly depart from the experience represented in the U5MD. For these countries, neither the existing model life tables nor the log-quadratic model can produce empirically-supported IMR adjustments. Age heaping at age 12 months produces a smaller amount of bias in DHS-based IMR estimates than previously thought. If a large amount of age heaping is present in a survey, the log-quadratic model allows users to evaluate, and whenever necessary, adjust IMR estimates in a way that is more informed by the local mortality pattern than existing approaches. Future research should be devoted to understanding why Sub-Saharan African and South Asian countries have such distinct age patterns of under-five mortality.
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