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

The value for Mortality rate, infant, male (per 1,000 live births) in Cabo Verde was 13.40 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 130.60 in 1960 and a minimum value of 13.40 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 130.60
1961 129.10
1962 127.80
1963 126.30
1964 124.70
1965 122.70
1966 120.50
1967 117.60
1968 114.70
1969 111.40
1970 107.40
1971 103.20
1972 98.90
1973 94.50
1974 90.20
1975 86.00
1976 82.20
1977 78.70
1978 75.80
1979 73.40
1980 71.60
1981 70.20
1982 68.90
1983 67.70
1984 66.00
1985 63.90
1986 61.20
1987 58.20
1988 55.20
1989 52.50
1990 50.40
1991 49.20
1992 48.60
1993 48.50
1994 48.40
1995 47.70
1996 46.20
1997 43.80
1998 40.50
1999 37.00
2000 33.70
2001 30.80
2002 28.50
2003 27.00
2004 26.10
2005 25.60
2006 25.40
2007 25.30
2008 25.20
2009 24.80
2010 24.20
2011 23.30
2012 22.20
2013 21.00
2014 19.70
2015 18.30
2016 17.00
2017 15.80
2018 14.90
2019 14.10
2020 13.40

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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