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

The value for Mortality rate, under-5, male (per 1,000 live births) in Mauritania was 76.40 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 263.60 in 1960 and a minimum value of 76.40 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 263.60
1961 256.80
1962 250.30
1963 243.80
1964 237.40
1965 230.90
1966 224.40
1967 218.00
1968 211.80
1969 206.90
1970 203.50
1971 201.70
1972 200.90
1973 200.10
1974 199.10
1975 197.10
1976 193.90
1977 189.70
1978 184.80
1979 179.70
1980 174.70
1981 169.80
1982 164.90
1983 159.70
1984 153.90
1985 147.80
1986 141.90
1987 136.40
1988 131.80
1989 127.90
1990 125.10
1991 123.20
1992 121.90
1993 121.20
1994 120.80
1995 120.80
1996 121.00
1997 121.10
1998 120.90
1999 120.60
2000 120.30
2001 119.70
2002 119.20
2003 118.50
2004 117.20
2005 115.60
2006 113.40
2007 111.00
2008 108.30
2009 105.40
2010 102.20
2011 99.60
2012 97.10
2013 94.10
2014 91.30
2015 88.90
2016 86.20
2017 83.70
2018 81.30
2019 78.70
2020 76.40

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