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

The value for Mortality rate, infant, male (per 1,000 live births) in Mauritania was 54.10 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 140.10 in 1960 and a minimum value of 54.10 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 140.10
1961 137.20
1962 134.30
1963 131.60
1964 128.80
1965 126.00
1966 123.10
1967 120.20
1968 117.60
1969 115.40
1970 114.00
1971 113.20
1972 112.80
1973 112.50
1974 112.10
1975 111.20
1976 109.90
1977 108.00
1978 105.80
1979 103.50
1980 101.30
1981 99.10
1982 96.90
1983 94.40
1984 91.90
1985 89.10
1986 86.30
1987 83.80
1988 81.50
1989 79.80
1990 78.50
1991 77.50
1992 76.90
1993 76.60
1994 76.40
1995 76.50
1996 76.50
1997 76.60
1998 76.50
1999 76.40
2000 76.20
2001 75.90
2002 75.70
2003 75.30
2004 74.70
2005 73.90
2006 72.80
2007 71.70
2008 70.30
2009 68.90
2010 67.40
2011 66.00
2012 64.90
2013 63.40
2014 62.00
2015 60.70
2016 59.40
2017 58.00
2018 56.70
2019 55.40
2020 54.10

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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