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

The value for Mortality rate, under-5, female (per 1,000 live births) in Peru was 11.60 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 219.80 in 1960 and a minimum value of 11.60 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 219.80
1961 213.30
1962 206.50
1963 199.60
1964 192.60
1965 185.70
1966 179.10
1967 173.00
1968 167.40
1969 162.40
1970 187.10
1971 153.20
1972 148.60
1973 144.30
1974 140.00
1975 136.10
1976 132.40
1977 129.20
1978 126.50
1979 123.80
1980 121.00
1981 117.90
1982 114.30
1983 110.20
1984 105.40
1985 100.20
1986 94.90
1987 89.70
1988 84.80
1989 80.20
1990 76.00
1991 71.90
1992 67.60
1993 63.20
1994 58.80
1995 54.30
1996 49.90
1997 45.70
1998 41.80
1999 38.30
2000 35.10
2001 32.20
2002 29.80
2003 27.60
2004 25.60
2005 24.00
2006 22.50
2007 21.00
2008 19.80
2009 18.70
2010 17.70
2011 16.90
2012 16.10
2013 15.40
2014 14.70
2015 14.10
2016 13.50
2017 13.00
2018 12.50
2019 12.00
2020 11.60

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