Mortality rate, neonatal (per 1,000 live births) - Country Ranking - Asia

Definition: Neonatal mortality rate is the number of neonates dying before reaching 28 days of age, per 1,000 live births in a given year.

Source: Estimates Developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.

See also: Thematic map, Time series comparison

Find indicator:
Rank Country Value Year
1 Pakistan 40.40 2020
2 Afghanistan 35.20 2020
3 Yemen 28.10 2020
4 Turkmenistan 23.50 2020
5 Myanmar 22.30 2020
6 Lao PDR 21.70 2020
7 India 20.30 2020
8 Timor-Leste 19.40 2020
9 Bangladesh 17.50 2020
10 Nepal 16.90 2020
11 Bhutan 15.30 2020
12 Iraq 14.40 2020
13 Tajikistan 14.00 2020
14 Cambodia 13.20 2020
15 Philippines 12.60 2020
16 Indonesia 11.70 2020
16 Kyrgyz Republic 11.70 2020
18 Syrian Arab Republic 10.70 2020
19 Vietnam 10.00 2020
20 Azerbaijan 9.80 2020
21 Dem. People's Rep. Korea 8.90 2020
22 Jordan 8.80 2020
23 Iran 8.30 2020
24 Mongolia 7.90 2020
25 Uzbekistan 7.60 2020
26 Brunei 6.10 2020
27 Armenia 5.70 2020
28 Georgia 5.00 2020
28 Kuwait 5.00 2020
28 Turkey 5.00 2020
31 Thailand 4.90 2020
31 Oman 4.90 2020
33 Kazakhstan 4.80 2020
34 Malaysia 4.60 2020
35 Lebanon 4.00 2020
35 Sri Lanka 4.00 2020
37 United Arab Emirates 3.60 2020
38 China 3.50 2020
38 Qatar 3.50 2020
38 Saudi Arabia 3.50 2020
41 Bahrain 2.90 2020
42 Russia 2.30 2020
43 Israel 1.90 2020
44 Korea 1.50 2020
45 Japan 0.80 2020
45 Singapore 0.80 2020

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Development Relevance: Mortality rates for different age groups (infants, children, and adults) and overall mortality indicators (life expectancy at birth or survival to a given age) are important indicators of health status in a country. Because data on the incidence and prevalence of diseases are frequently unavailable, mortality rates are often used to identify vulnerable populations. And they are among the indicators most frequently used to compare socioeconomic development across countries.

Limitations and Exceptions: Complete vital registration systems are fairly uncommon in developing countries. Thus estimates must be obtained from sample surveys or derived by applying indirect estimation techniques to registration, census, or survey data. Survey data are subject to recall error, and surveys estimating infant/child deaths require large samples because households in which a birth has occurred during a given year cannot ordinarily be preselected for sampling. Indirect estimates rely on model life tables that may be inappropriate for the population concerned. Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.

Statistical Concept and Methodology: The main sources of mortality data are vital registration systems and direct or indirect estimates based on sample surveys or censuses. A "complete" vital registration system - covering at least 90 percent of vital events in the population - is the best source of age-specific mortality data. Estimates of neonatal, infant, and child mortality tend to vary by source and method for a given time and place. Years for available estimates also vary by country, making comparisons across countries and over time difficult. To make neonatal, infant, and child mortality estimates comparable and to ensure consistency across estimates by different agencies, the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME), which comprises the United Nations Children's Fund (UNICEF), the World Health Organization (WHO), the World Bank, the United Nations Population Division, and other universities and research institutes, developed and adopted a statistical method that uses all available information to reconcile differences. The method uses statistical models to obtain a best estimate trend line by fitting a country-specific regression model of mortality rates against their reference dates.

Aggregation method: Weighted average

Periodicity: Annual

General Comments: Given that data on the incidence and prevalence of diseases are frequently unavailable, mortality rates are often used to identify vulnerable populations. Moreover, they are among the indicators most frequently used to compare socioeconomic development ac