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

The value for Mortality rate, under-5, female (per 1,000 live births) in Cabo Verde was 12.80 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 172.50 in 1960 and a minimum value of 12.80 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 172.50
1961 170.90
1962 168.50
1963 166.00
1964 163.30
1965 160.30
1966 156.80
1967 152.60
1968 148.10
1969 143.00
1970 137.20
1971 130.90
1972 124.40
1973 117.90
1974 111.60
1975 105.50
1976 99.70
1977 94.60
1978 90.20
1979 86.60
1980 83.90
1981 82.10
1982 80.70
1983 79.20
1984 77.30
1985 74.40
1986 70.60
1987 66.50
1988 62.30
1989 58.60
1990 56.00
1991 54.40
1992 53.70
1993 53.50
1994 53.30
1995 52.50
1996 50.50
1997 47.40
1998 43.50
1999 39.10
2000 34.90
2001 31.40
2002 28.80
2003 27.10
2004 26.00
2005 25.50
2006 25.30
2007 25.20
2008 25.00
2009 24.50
2010 23.80
2011 22.80
2012 21.60
2013 20.30
2014 18.90
2015 17.60
2016 16.30
2017 15.20
2018 14.20
2019 13.50
2020 12.80

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