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

The value for Mortality rate, infant, female (per 1,000 live births) in Mauritania was 43.60 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 120.40 in 1960 and a minimum value of 43.60 in 2020.

Definition: Infant mortality rate, female is the number of female infants dying before reaching one year of age, per 1,000 female 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 120.40
1961 117.70
1962 114.80
1963 112.20
1964 109.30
1965 106.70
1966 104.10
1967 101.30
1968 98.80
1969 96.80
1970 95.40
1971 94.60
1972 94.10
1973 93.80
1974 93.30
1975 92.50
1976 91.20
1977 89.40
1978 87.40
1979 85.30
1980 83.40
1981 81.50
1982 79.50
1983 77.50
1984 75.30
1985 72.90
1986 70.60
1987 68.40
1988 66.50
1989 65.00
1990 63.90
1991 63.20
1992 62.60
1993 62.30
1994 62.20
1995 62.10
1996 62.00
1997 61.90
1998 61.90
1999 61.80
2000 61.50
2001 61.30
2002 61.10
2003 60.80
2004 60.50
2005 59.80
2006 59.00
2007 58.00
2008 57.00
2009 55.80
2010 54.70
2011 53.60
2012 52.50
2013 51.30
2014 50.10
2015 49.00
2016 47.90
2017 46.80
2018 45.80
2019 44.60
2020 43.60

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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