Jamie Perin, Yue Chu, Francisco Villavicencio, Austin Schumacher, Tyler McCormick, Michel Guillot, Li Liu
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引用次数: 0
Abstract
Background: The mortality pattern from birth to age five is known to vary by underlying cause of mortality, which has been documented in multiple instances. Many countries without high functioning vital registration systems could benefit from estimates of age- and cause-specific mortality to inform health programming, however, to date the causes of under-five death have only been described for broad age categories such as for neonates (0-27 days), infants (0-11 months), and children age 12-59 months.
Methods: We adapt the log quadratic model to mortality patterns for children under five to all-cause child mortality and then to age- and cause-specific mortality (U5ACSM). We apply these methods to empirical sample registration system mortality data in China from 1996 to 2015. Based on these empirical data, we simulate probabilities of mortality in the case when the true relationships between age and mortality by cause are known.
Results: We estimate U5ACSM within 0.1-0.7 deaths per 1000 livebirths in hold out strata for life tables constructed from the China sample registration system, representing considerable improvement compared to an error of 1.2 per 1000 livebirths using a standard approach. This improved prediction error for U5ACSM is consistently demonstrated for all-cause as well as pneumonia- and injury-specific mortality. We also consistently identified cause-specific mortality patterns in simulated mortality scenarios.
Conclusion: The log quadratic model is a significant improvement over the standard approach for deriving U5ACSM based on both simulation and empirical results.
期刊介绍:
Population Health Metrics aims to advance the science of population health assessment, and welcomes papers relating to concepts, methods, ethics, applications, and summary measures of population health. The journal provides a unique platform for population health researchers to share their findings with the global community. We seek research that addresses the communication of population health measures and policy implications to stakeholders; this includes papers related to burden estimation and risk assessment, and research addressing population health across the full range of development. Population Health Metrics covers a broad range of topics encompassing health state measurement and valuation, summary measures of population health, descriptive epidemiology at the population level, burden of disease and injury analysis, disease and risk factor modeling for populations, and comparative assessment of risks to health at the population level. The journal is also interested in how to use and communicate indicators of population health to reduce disease burden, and the approaches for translating from indicators of population health to health-advancing actions. As a cross-cutting topic of importance, we are particularly interested in inequalities in population health and their measurement.