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

The value for Mortality rate, under-5, female (per 1,000 live births) in Mauritania was 64.80 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 242.00 in 1960 and a minimum value of 64.80 in 2020.

Definition: Under-five mortality rate, female is the probability per 1,000 that a newborn female baby will die before reaching age five, if subject to female 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 242.00
1961 235.40
1962 229.00
1963 222.60
1964 216.40
1965 210.20
1966 203.90
1967 197.60
1968 191.70
1969 187.00
1970 183.90
1971 181.80
1972 180.80
1973 180.10
1974 179.00
1975 176.90
1976 173.90
1977 169.90
1978 165.20
1979 160.30
1980 155.60
1981 151.00
1982 146.40
1983 141.50
1984 136.20
1985 130.60
1986 125.00
1987 120.00
1988 115.70
1989 112.20
1990 109.60
1991 107.90
1992 106.70
1993 106.00
1994 105.60
1995 105.40
1996 105.30
1997 105.20
1998 105.10
1999 104.80
2000 104.40
2001 103.90
2002 103.40
2003 102.70
2004 101.60
2005 100.20
2006 98.20
2007 96.20
2008 93.70
2009 91.10
2010 88.50
2011 85.90
2012 83.60
2013 81.00
2014 78.70
2015 76.10
2016 73.80
2017 71.40
2018 69.30
2019 67.00
2020 64.80

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