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

The value for Mortality rate, under-5, male (per 1,000 live births) in Cabo Verde was 15.50 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 188.10 in 1960 and a minimum value of 15.50 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 188.10
1961 186.10
1962 183.80
1963 181.40
1964 178.80
1965 175.70
1966 172.00
1967 167.50
1968 162.70
1969 157.40
1970 151.20
1971 144.80
1972 138.00
1973 131.20
1974 124.50
1975 118.10
1976 112.10
1977 106.90
1978 102.30
1979 98.70
1980 95.90
1981 93.80
1982 91.90
1983 90.10
1984 87.80
1985 84.50
1986 80.50
1987 75.90
1988 71.40
1989 67.50
1990 64.60
1991 62.80
1992 62.00
1993 61.70
1994 61.60
1995 60.60
1996 58.50
1997 55.00
1998 50.50
1999 45.70
2000 41.20
2001 37.30
2002 34.30
2003 32.30
2004 31.10
2005 30.50
2006 30.30
2007 30.20
2008 29.90
2009 29.40
2010 28.70
2011 27.60
2012 26.20
2013 24.60
2014 23.00
2015 21.40
2016 19.80
2017 18.40
2018 17.30
2019 16.30
2020 15.50

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