Indicator 3.2.2 Neonatal mortality rate

Indicator 3.2.2: Neonatal mortality rate

Target 3.2: By 2030, end preventable deaths of newborns and children under 5 years of age, with all countries aiming to reduce neonatal mortality to at least as low as 12 per 1,000 live births and under-5 mortality to at least as low as 25 per 1,000 live births

United Nations Children's Fund (UNICEF)

Definition:

The neonatal mortality rate is the probability that a child born in a specific year or period will die during the first 28 completed days of life, if subject to age-specific mortality rates of that period, expressed per 1000 live births.

Neonatal deaths (deaths among live births during the first 28 completed days of life) may be subdivided into early neonatal deaths, occurring during the first 7 days of life, and late neonatal deaths, occurring after the 7th day but before the 28th completed day of life.

Number (SH_DYN_NMRTN); Deaths per 1,000 live births (SH_DYN_NMRT)

Nationally representative estimates of child mortality can be derived from several different sources, including civil registration and sample surveys. Demographic surveillance sites and hospital data are excluded as they are not nationally representative. The preferred source of data is a civil registration system that records births and deaths on a continuous basis. If registration is complete and the system functions efficiently, the resulting estimates will be accurate and timely. However, many countries do not have well-functioning vital registration systems. In such cases household surveys, such as the UNICEF-supported Multiple Indicator Cluster Surveys (MICS), the USAID-supported Demographic and Health Surveys (DHS) and periodic population censuses have become the primary sources of data on under-five and neonatal mortality. These surveys ask women about the survival of their children, and it is these reports that provide the basis of child mortality estimates for a majority of low- and middle-income countries. These data are subject to sampling and non-sampling errors, which might be substantial.

Civil registration

Civil registration is the preferred data source for under-five, infant and neonatal mortality estimation. Neonatal mortality rates are calculated using the number of neonatal deaths and the number of live births over a period. For civil registration data, initially annual observations were constructed for all observation years in a country.

Population census and household survey data

The majority of survey data comes from the full birth history (FBH), whereby women are asked for the date of birth of each of their children, whether the child is still alive, and if not the age at death.

The National Statistical Office or the Ministry of Health is the typical provider of data for generating neonatal mortality estimates at the national level.

A civil registration system that continuously records all births and deaths in a population is the preferred source of high-quality underlying data on under-five mortality but these systems are not well developed in many low- and middle-income countries. Instead, household surveys and population censuses are the primary sources of underlying data in these countries.

The reliance on multiple data sources, i.e. surveys and census conducted several years apart and producing retrospective time series, can result in disparate mortality rates from different sources, sometimes referring to the same time period. Available data also suffer from sampling and nonsampling errors, including misreporting of age and sex, survivor selection bias, underreporting of child deaths, and recall errors as data are collected retrospectively. Further misclassifications can also impact the accuracy of data, for example, early neonatal deaths may be classified as stillbirths. Thus, simply comparing two country data points from different sources and drawing a line between them is not a technically sound way to assess levels and trends. Given varying levels of data quality across different sources, this sort of trend assessment will provide misleading results. Hence, the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME) fits a statistical model to these data that takes into account these various data sources to produce annualized estimates.

It is important to keep these challenges in mind when looking at available country data and also when discrepancies between country data and the UN IGME estimates are being discussed. The following

points are important to highlight:

• The UN IGME aims to minimize the errors for each estimate, harmonize trends over time and produce up-to-date and properly assessed estimates of child mortality. Thus, UN IGME estimates are derived from country data. Notably, UN IGME assesses the quality of underlying data sources and adjusts data when necessary.
• National estimates may refer to an earlier calendar year than the UN IGME estimates. This is particularly the case where estimates from the most recent national survey are used as the national estimate, since the survey estimates derived from a birth history are retrospective and typically refer to a period before the year of the survey, which may be several years behind the target year for the UN IGME estimates. National estimates may also use a different combination of data sources, or different projection or calculation methods.
• In the absence of error-free data, there will always be uncertainty around data and estimates. To allow for added comparability, the UN IGME generates estimates with uncertainty bounds. When discussing the UN IGME estimates, it’s important to look at the uncertainty ranges, which might be fairly wide in the case of some countries.

The United Nations Inter-agency Group for Child Mortality Estimation (UN IGME) estimates are derived from nationally representative data from censuses, surveys or vital registration systems. The UN IGME does not use any covariates to derive its estimates (except in the case of neonatal mortality estimation, which incorporates the relatively more data-rich under-five mortality rate estimates in the modelling). It only applies a curve fitting method to good-quality empirical data to derive trend estimates after data quality assessment. In most cases, the UN IGME estimates are close to the underlying data. The UN IGME aims to minimize the errors for each estimate, harmonize trends over time and produce up-to-date and properly assessed estimates. The UN IGME produces neonatal mortality rate (NMR) estimates with a Bayesian spline regression model, which models the ratio of neonatal mortality rate / (under-five mortality rate - neonatal mortality rate). Estimates of NMR are obtained by recombining the estimates of the ratio with the UN IGME-estimated under-five mortality rate. See the references for details.

For the underlying data mentioned above, the most frequently used methods are as follows:

Civil registration: The neonatal mortality rate can be calculated from the number of children who died during the first 28 days of life and the number of live births.

Censuses and surveys: Censuses and surveys often include questions on household deaths in the last 12 months, which can be used to calculate mortality estimates.

Surveys: A direct method is used based on a full birth history, a series of detailed questions on each child a woman has given birth to during her lifetime. Neonatal, post-neonatal, infant, child and under-five mortality estimates can be derived from the full birth history.

2024-03-28

United Nations Children's Fund (UNICEF)

3.2.1: Under-five mortality rate