Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia.
PLoS One. 2018 May 30;13(5):e0197047. doi: 10.1371/journal.pone.0197047. eCollection 2018.
Many national and subnational governments need to routinely measure the completeness of death registration for monitoring and statistical purposes. Existing methods, such as death distribution and capture-recapture methods, have a number of limitations such as inaccuracy and complexity that prevent widespread application. This paper presents a novel empirical method to estimate completeness of death registration at the national and subnational level.
Random-effects models to predict the logit of death registration completeness were developed from 2,451 country-years in 110 countries from 1970-2015 using the Global Burden of Disease 2015 database. Predictors include the registered crude death rate, under-five mortality rate, population age structure and under-five death registration completeness. Models were developed separately for males, females and both sexes.
All variables are highly significant and reliably predict completeness of registration across a wide range of registered crude death rates (R-squared 0.85). Mean error is highest at medium levels of observed completeness. The models show quite close agreement between predicted and observed completeness for populations outside the dataset. There is high concordance with the Hybrid death distribution method in Brazilian states. Uncertainty in the under-five mortality rate, assessed using the dataset and in Colombian departmentos, has minimal impact on national level predicted completeness, but a larger effect at the subnational level.
The method demonstrates sufficient flexibility to predict a wide range of completeness levels at a given registered crude death rate. The method can be applied utilising data readily available at the subnational level, and can be used to assess completeness of deaths reported from health facilities, censuses and surveys. Its utility is diminished where the adult mortality rate is unusually high for a given under-five mortality rate. The method overcomes the considerable limitations of existing methods and has considerable potential for widespread application by national and subnational governments.
许多国家和次国家级政府需要定期衡量死亡登记的完整性，以进行监测和统计。现有的方法，如死亡分布和捕获-再捕获方法，存在准确性和复杂性等诸多限制，从而阻碍了其广泛应用。本文提出了一种新颖的经验方法，可用于估算国家和次国家级的死亡登记完整性。
使用 2015 年全球疾病负担数据库，我们从 1970 年至 2015 年的 110 个国家中的 2451 个国家年中，开发了一种随机效应模型，以预测死亡登记完整性的对数几率。预测因素包括注册的粗死亡率、五岁以下儿童死亡率、人口年龄结构和五岁以下儿童死亡登记完整性。该模型分别针对男性、女性和两性进行了开发。
所有变量都具有高度显著性，可在广泛的注册粗死亡率范围内可靠地预测登记的完整性（R-squared 为 0.85）。在观察到的完整性处于中等水平时，误差最高。该模型在数据集之外的人群中，预测的完整性与观察到的完整性非常吻合。与巴西各州的混合死亡分布方法的一致性很高。在使用数据集评估和哥伦比亚部门的五岁以下儿童死亡率不确定性时，对国家层面预测的完整性影响很小，但对次国家级的影响较大。
该方法具有足够的灵活性，可在给定的注册粗死亡率下预测广泛的完整性水平。该方法可以利用次国家级现成的数据进行应用，并且可以用于评估从卫生机构、人口普查和调查报告的死亡情况的完整性。在给定的五岁以下儿童死亡率下，成人死亡率异常高的情况下，该方法的效用会降低。该方法克服了现有方法的重大局限性，具有在国家和次国家级政府中广泛应用的巨大潜力。
