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

The value for Mortality rate, under-5, male (per 1,000 live births) in Pakistan was 69.60 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 254.30 in 1960 and a minimum value of 69.60 in 2020.

Definition: Under-five mortality rate, male is the probability per 1,000 that a newborn male baby will die before reaching age five, if subject to male 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 254.30
1961 244.90
1962 236.30
1963 228.10
1964 220.70
1965 214.20
1966 208.40
1967 203.40
1968 199.00
1969 195.00
1970 191.30
1971 187.90
1972 184.80
1973 181.80
1974 179.30
1975 177.00
1976 174.80
1977 172.70
1978 170.80
1979 168.70
1980 166.80
1981 164.80
1982 162.80
1983 160.60
1984 158.40
1985 156.10
1986 153.50
1987 151.00
1988 148.40
1989 145.70
1990 142.90
1991 140.20
1992 137.20
1993 134.20
1994 131.00
1995 127.70
1996 124.30
1997 121.10
1998 117.80
1999 114.60
2000 111.70
2001 109.00
2002 106.60
2003 104.50
2004 102.60
2005 100.90
2006 99.20
2007 97.40
2008 95.70
2009 93.80
2010 91.90
2011 89.70
2012 87.50
2013 85.30
2014 83.00
2015 80.70
2016 78.40
2017 76.20
2018 74.00
2019 71.70
2020 69.60

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