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

Definition: Infant mortality rate, female is the number of female infants dying before reaching one year of age, per 1,000 female 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 49.00 2020
2 Afghanistan 41.50 2020
2 Yemen 41.50 2020
4 Timor-Leste 33.00 2020
5 Myanmar 31.20 2020
5 Lao PDR 31.20 2020
7 Turkmenistan 30.80 2020
8 India 26.80 2020
9 Tajikistan 24.60 2020
10 Bangladesh 22.70 2020
11 Nepal 21.40 2020
12 Bhutan 20.90 2020
13 Cambodia 19.30 2020
14 Iraq 19.10 2020
15 Philippines 18.50 2020
16 Indonesia 17.30 2020
17 Syrian Arab Republic 16.50 2020
18 Azerbaijan 15.50 2020
19 Vietnam 14.40 2020
20 Kyrgyz Republic 13.80 2020
21 Mongolia 11.60 2020
21 Jordan 11.60 2020
23 Uzbekistan 10.70 2020
24 Iran 10.50 2020
25 Dem. People's Rep. Korea 10.30 2020
26 Brunei 8.70 2020
26 Armenia 8.70 2020
28 Oman 8.50 2020
29 Kazakhstan 7.70 2020
30 Turkey 7.60 2020
31 Georgia 7.30 2020
32 Kuwait 6.90 2020
33 Malaysia 6.80 2020
34 Thailand 6.60 2020
35 Saudi Arabia 5.80 2020
36 Lebanon 5.70 2020
37 Bahrain 5.50 2020
38 Sri Lanka 5.30 2020
39 China 5.10 2020
40 United Arab Emirates 5.00 2020
41 Qatar 4.60 2020
42 Russia 3.90 2020
43 Israel 2.70 2020
44 Korea 2.30 2020
45 Japan 1.70 2020
45 Singapore 1.70 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