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

The value for Mortality rate, infant, male (per 1,000 live births) in Guinea was 67.80 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 221.50 in 1960 and a minimum value of 67.80 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 221.50
1961 219.80
1962 218.30
1963 216.40
1964 214.70
1965 212.70
1966 210.50
1967 208.60
1968 206.80
1969 204.60
1970 202.60
1971 200.50
1972 198.30
1973 195.80
1974 193.40
1975 190.70
1976 188.00
1977 185.20
1978 182.30
1979 179.30
1980 176.30
1981 173.20
1982 170.10
1983 166.90
1984 163.90
1985 160.80
1986 157.80
1987 154.90
1988 152.00
1989 149.00
1990 145.80
1991 142.40
1992 138.50
1993 134.70
1994 130.70
1995 127.00
1996 123.10
1997 119.20
1998 115.40
1999 111.50
2000 107.70
2001 104.00
2002 100.40
2003 96.90
2004 93.90
2005 91.10
2006 88.60
2007 86.40
2008 84.50
2009 82.70
2010 81.30
2011 79.70
2012 78.40
2013 77.00
2014 75.90
2015 74.60
2016 73.20
2017 72.00
2018 70.70
2019 69.30
2020 67.80

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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