Pakistan - Mortality rate, under-5, female (per 1,000 live births)

The value for Mortality rate, under-5, female (per 1,000 live births) in Pakistan was 60.50 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 249.30 in 1960 and a minimum value of 60.50 in 2020.

Definition: Under-five mortality rate, female is the probability per 1,000 that a newborn female baby will die before reaching age five, if subject to female age-specific mortality rates of the specified 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 249.30
1961 240.70
1962 232.40
1963 224.80
1964 217.60
1965 211.20
1966 205.60
1967 200.70
1968 196.40
1969 192.80
1970 189.50
1971 186.30
1972 183.30
1973 180.40
1974 177.60
1975 175.00
1976 172.50
1977 170.30
1978 167.90
1979 165.60
1980 163.20
1981 160.80
1982 158.30
1983 155.70
1984 153.00
1985 150.10
1986 147.20
1987 144.30
1988 141.70
1989 139.00
1990 136.30
1991 133.60
1992 130.70
1993 127.60
1994 124.50
1995 121.10
1996 117.60
1997 114.00
1998 110.40
1999 106.90
2000 103.70
2001 100.70
2002 98.00
2003 95.60
2004 93.40
2005 91.40
2006 89.50
2007 87.70
2008 85.90
2009 84.00
2010 82.10
2011 80.10
2012 77.80
2013 75.60
2014 73.30
2015 71.10
2016 69.00
2017 66.80
2018 64.70
2019 62.60
2020 60.50

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