Guinea - Mortality rate, under-5 (per 1,000 live births)

The value for Mortality rate, under-5 (per 1,000 live births) in Guinea was 95.60 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 348.00 in 1960 and a minimum value of 95.60 in 2020.

Definition: Under-five mortality rate is the probability per 1,000 that a newborn baby will die before reaching age five, if subject to 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 348.00
1961 345.60
1962 343.30
1963 340.60
1964 338.10
1965 335.30
1966 332.50
1967 329.60
1968 326.80
1969 323.70
1970 320.70
1971 317.40
1972 314.10
1973 310.90
1974 307.10
1975 303.20
1976 299.00
1977 294.40
1978 289.70
1979 284.90
1980 280.00
1981 275.10
1982 270.40
1983 265.80
1984 261.00
1985 256.40
1986 251.70
1987 247.10
1988 242.40
1989 237.30
1990 231.80
1991 225.90
1992 219.50
1993 212.90
1994 206.00
1995 199.00
1996 192.00
1997 185.20
1998 178.20
1999 171.20
2000 164.20
2001 157.40
2002 150.90
2003 144.90
2004 139.50
2005 134.70
2006 130.40
2007 126.60
2008 123.30
2009 120.30
2010 117.70
2011 115.30
2012 113.00
2013 110.70
2014 109.20
2015 107.30
2016 104.60
2017 102.60
2018 100.40
2019 98.00
2020 95.60

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