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

The value for Mortality rate, infant, male (per 1,000 live births) in Zambia was 45.30 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 128.60 in 1960 and a minimum value of 45.30 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 128.60
1961 126.60
1962 124.60
1963 122.90
1964 121.50
1965 120.60
1966 120.00
1967 119.50
1968 118.90
1969 117.50
1970 115.50
1971 112.80
1972 109.60
1973 106.60
1974 103.90
1975 101.90
1976 101.00
1977 100.90
1978 101.20
1979 101.50
1980 102.10
1981 102.50
1982 103.10
1983 104.30
1984 106.10
1985 108.40
1986 110.70
1987 112.70
1988 114.10
1989 114.80
1990 114.90
1991 114.60
1992 113.90
1993 112.40
1994 110.20
1995 107.80
1996 105.60
1997 103.70
1998 101.90
1999 99.60
2000 96.30
2001 91.20
2002 84.90
2003 78.70
2004 72.30
2005 66.70
2006 63.00
2007 61.30
2008 59.00
2009 57.30
2010 55.50
2011 54.30
2012 53.20
2013 50.60
2014 50.00
2015 50.90
2016 49.50
2017 48.10
2018 47.70
2019 46.60
2020 45.30

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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