Pakistan - Mortality rate, infant, female (per 1,000 live births)

The value for Mortality rate, infant, female (per 1,000 live births) in Pakistan was 49.00 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 175.50 in 1960 and a minimum value of 49.00 in 2020.

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:

Year Value
1960 175.50
1961 169.80
1962 164.50
1963 159.60
1964 154.80
1965 150.60
1966 146.90
1967 143.70
1968 140.90
1969 138.60
1970 136.40
1971 134.30
1972 132.40
1973 130.50
1974 128.50
1975 126.70
1976 125.00
1977 123.60
1978 121.90
1979 120.20
1980 118.70
1981 116.90
1982 115.30
1983 113.50
1984 111.60
1985 109.60
1986 107.60
1987 105.60
1988 103.80
1989 102.10
1990 100.40
1991 98.60
1992 96.60
1993 94.60
1994 92.60
1995 90.40
1996 88.00
1997 85.50
1998 83.00
1999 80.60
2000 78.50
2001 76.50
2002 74.70
2003 73.10
2004 71.60
2005 70.30
2006 68.90
2007 67.70
2008 66.50
2009 65.20
2010 63.90
2011 62.60
2012 61.00
2013 59.50
2014 57.90
2015 56.40
2016 54.90
2017 53.40
2018 51.90
2019 50.40
2020 49.00

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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

Classification

Topic: Health Indicators

Sub-Topic: Mortality