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

The value for Mortality rate, under-5, female (per 1,000 live births) in Guinea was 89.40 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 336.90 in 1960 and a minimum value of 89.40 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 336.90
1961 335.00
1962 332.60
1963 330.30
1964 327.70
1965 325.10
1966 322.60
1967 319.90
1968 317.10
1969 314.20
1970 311.50
1971 308.50
1972 305.50
1973 302.00
1974 298.60
1975 294.90
1976 290.80
1977 286.00
1978 281.20
1979 276.30
1980 271.30
1981 266.50
1982 261.80
1983 257.40
1984 253.00
1985 248.50
1986 244.00
1987 239.40
1988 234.60
1989 229.40
1990 223.90
1991 217.80
1992 211.60
1993 204.80
1994 197.80
1995 190.70
1996 183.70
1997 176.80
1998 169.90
1999 163.00
2000 156.20
2001 149.50
2002 143.10
2003 137.20
2004 131.90
2005 127.10
2006 122.90
2007 119.30
2008 116.00
2009 113.20
2010 110.50
2011 108.10
2012 106.00
2013 103.90
2014 102.60
2015 100.70
2016 98.10
2017 96.20
2018 94.10
2019 91.80
2020 89.40

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