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

The value for Mortality rate, under-5, male (per 1,000 live births) in Zambia was 66.10 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 212.70 in 1960 and a minimum value of 66.10 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 212.70
1961 208.80
1962 205.30
1963 202.20
1964 199.70
1965 198.00
1966 196.90
1967 196.10
1968 194.80
1969 192.50
1970 188.70
1971 183.60
1972 177.60
1973 171.80
1974 166.70
1975 162.90
1976 161.20
1977 161.00
1978 161.40
1979 162.00
1980 163.10
1981 163.80
1982 164.90
1983 166.90
1984 170.20
1985 174.50
1986 178.90
1987 182.90
1988 186.20
1989 188.40
1990 189.80
1991 190.50
1992 190.40
1993 188.90
1994 186.00
1995 182.50
1996 179.50
1997 176.80
1998 174.00
1999 170.30
2000 164.60
2001 155.50
2002 144.40
2003 133.40
2004 122.80
2005 113.30
2006 105.30
2007 99.70
2008 94.90
2009 89.60
2010 84.80
2011 82.50
2012 80.20
2013 76.30
2014 73.50
2015 72.90
2016 70.40
2017 69.60
2018 70.30
2019 69.00
2020 66.10

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