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

The value for Mortality rate, under-5 (per 1,000 live births) in Philippines was 26.40 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 102.70 in 1960 and a minimum value of 26.40 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 102.70
1961 99.60
1962 97.00
1963 94.70
1964 92.70
1965 90.80
1966 89.00
1967 87.30
1968 85.80
1969 84.50
1970 83.60
1971 82.90
1972 82.60
1973 82.40
1974 82.40
1975 82.40
1976 82.20
1977 81.90
1978 81.40
1979 80.60
1980 79.70
1981 78.70
1982 77.60
1983 76.30
1984 74.80
1985 72.80
1986 70.30
1987 67.20
1988 63.80
1989 60.20
1990 56.60
1991 53.30
1992 50.40
1993 47.80
1994 45.60
1995 43.70
1996 42.00
1997 40.60
1998 39.40
1999 38.50
2000 37.70
2001 36.90
2002 36.20
2003 35.50
2004 34.90
2005 34.20
2006 33.60
2007 33.00
2008 32.50
2009 32.10
2010 31.70
2011 31.30
2012 30.90
2013 30.50
2014 30.10
2015 29.60
2016 29.10
2017 28.50
2018 27.90
2019 27.10
2020 26.40

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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