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To aid policy-makers and programme managers, we have now estimated neonatal causes of death separately for the early and late neonatal periods, and added injuries as a distinct cause for low-mortality countries. The input data have also been updated and the modelling strategy has been modified, particularly for the split of neonatal infections between pneumonia and sepsis. We present global, regional, and national estimates of proportions, risks, and numbers of deaths for programmatically relevant neonatal causes of death by the early and late neonatal periods.
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In the early period, preterm birth (40.8%) and intrapartum complications (27.0%) accounted for the majority of deaths while in the late neonatal period nearly half of all deaths occurred from infectious causes (47.6%; Table 2). The proportion of deaths from congenital disorders was relatively stable across the periods. Higher neonatal mortality rates and lower national income levels were associated with a higher proportion of deaths attributable to intrapartum complications and infectious causes (Appendix M, available from: ). The variation between the 10 MDG regions appears to reflect the differences in neonatal mortality rate between these regions. In low-mortality settings, injuries accounted for less than 1% of neonatal deaths, and this fraction increased slightly from the early to late period (Appendix M). See Appendix N (available from: ) for model-specific results, Appendix O (available from: ) for country-specific results and Appendix P (available from: ) for a comparison of results for China.
We developed comparable estimates of programmatically relevant causes of death in the early and late neonatal periods for 194 countries. The proportional neonatal cause distribution varied with several factors, including the age of death, the national neonatal mortality rate and over time. To reduce neonatal deaths, these variations must be understood and incorporated into decisions regarding the selection of appropriate interventions. With the launch of the Every newborn: an action plan to end preventable deaths, this is the time to tailor interventions to the individual circumstances of countries.
We used our model to predict trends in causes of death. Our model predicts that deaths due to intrapartum complications had the largest absolute risk reduction. The relative decrease in tetanus may be due to increases in clean deliveries, facility birth, cord care and tetanus toxoid vaccination, as well as contextual changes in maternal education and social norms.2121 Thwaites CL, Beeching NJ, Newton CR. Maternal and neonatal tetanus. Lancet. 2014. doi: -6736(14)60236-1 PMID: 25149223 -6736(14)60... Additionally, a few countries in the low-mortality model eliminated neonatal tetanus after 2000. Since tetanus was not estimated in the low-mortality model, we may have underestimated the relative decline in risk.
Given the considerable variations in health systems and contextual factors within individual countries, subnational neonatal cause-of-death estimates are needed and should be a target for future estimation exercises and data collection. National-level estimates aim to ascertain the average causal distribution for a country, which can help guide national priorities, but may mask subnational variation. Some countries are beginning to collect information for subnational estimates. For example, our national estimates for India were produced by aggregating state-level estimates. We also wish to further differentiate causes within the current broad categories such as congenital disorders. However, such differentiation may only be possible for vital registration-based models, since verbal autopsy-based data generally lack the needed information for such differentiation. Finally, we believe that the production of estimates should be transparent. Therefore, the datasets and Stata code we used for this analysis are available on the WHO Global Health Observatory website.1818 Global Health Observatory. The data repository [Internet]. Geneva: World Health Organization; 2014. Available from: [cited 2014 Oct 20]. 041b061a72