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

The value for Mortality rate, infant, male (per 1,000 live births) in Pakistan was 59.00 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 194.00 in 1960 and a minimum value of 59.00 in 2020.

Definition: Infant mortality rate, male is the number of male infants dying before reaching one year of age, per 1,000 male 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 194.00
1961 187.20
1962 180.80
1963 174.70
1964 169.40
1965 164.60
1966 160.40
1967 156.80
1968 153.50
1969 150.50
1970 147.80
1971 145.30
1972 143.00
1973 140.80
1974 139.00
1975 137.40
1976 135.80
1977 134.30
1978 132.90
1979 131.60
1980 130.10
1981 128.80
1982 127.30
1983 125.80
1984 124.20
1985 122.50
1986 120.80
1987 119.00
1988 117.00
1989 115.10
1990 113.00
1991 110.90
1992 108.80
1993 106.60
1994 104.20
1995 101.80
1996 99.50
1997 97.10
1998 94.70
1999 92.50
2000 90.30
2001 88.40
2002 86.70
2003 85.20
2004 83.90
2005 82.60
2006 81.40
2007 80.10
2008 78.80
2009 77.50
2010 76.00
2011 74.40
2012 72.70
2013 71.00
2014 69.30
2015 67.50
2016 65.80
2017 64.10
2018 62.40
2019 60.70
2020 59.00

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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