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

The value for Mortality rate, infant, female (per 1,000 live births) in Peru was 9.00 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 126.20 in 1960 and a minimum value of 9.00 in 2020.

Definition: Infant mortality rate, female is the number of female infants dying before reaching one year of age, per 1,000 female 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 126.20
1961 123.00
1962 119.60
1963 116.20
1964 112.80
1965 109.30
1966 106.10
1967 103.00
1968 100.30
1969 97.80
1970 105.40
1971 93.20
1972 90.80
1973 88.70
1974 86.60
1975 84.50
1976 82.60
1977 80.90
1978 79.40
1979 78.00
1980 76.50
1981 74.80
1982 72.90
1983 70.60
1984 68.10
1985 65.30
1986 62.50
1987 59.60
1988 56.90
1989 54.40
1990 52.00
1991 49.70
1992 47.30
1993 44.70
1994 42.00
1995 39.20
1996 36.50
1997 33.80
1998 31.20
1999 28.70
2000 26.50
2001 24.50
2002 22.80
2003 21.20
2004 19.70
2005 18.50
2006 17.30
2007 16.30
2008 15.30
2009 14.50
2010 13.70
2011 13.00
2012 12.50
2013 11.90
2014 11.40
2015 10.90
2016 10.50
2017 10.10
2018 9.70
2019 9.30
2020 9.00

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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