East Asia & Pacific (IDA & IBRD countries) | Probability of dying among adolescents ages 10-14 years (per 1,000)
Probability of dying between age 10-14 years of age expressed per 1,000 adolescents age 10, if subject to age-specific mortality rates of the specified year. Development relevance: Mortality rates for different age groups (infants, children, adolescents, youth 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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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.
Publisher
The World Bank
Origin
East Asia & Pacific (IDA & IBRD countries)
Records
63
Source
East Asia & Pacific (IDA & IBRD countries) | Probability of dying among adolescents ages 10-14 years (per 1,000)
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
3.13372633 1990
3.07456014 1991
2.95807436 1992
2.84349747 1993
2.75148263 1994
2.71543765 1995
2.6199854 1996
2.51896143 1997
2.41314749 1998
2.30155907 1999
2.26462682 2000
2.17308288 2001
2.08874813 2002
2.10008701 2003
2.3881596 2004
2.01795018 2005
1.9534816 2006
1.92529653 2007
2.40935022 2008
1.84273131 2009
1.75650435 2010
1.74596519 2011
1.71114667 2012
1.64823613 2013
1.61145718 2014
1.58721676 2015
1.51512406 2016
1.49035383 2017
1.47949539 2018
1.46150974 2019
1.44841106 2020
1.36351589 2021
2022
East Asia & Pacific (IDA & IBRD countries) | Probability of dying among adolescents ages 10-14 years (per 1,000)
Probability of dying between age 10-14 years of age expressed per 1,000 adolescents age 10, if subject to age-specific mortality rates of the specified year. Development relevance: Mortality rates for different age groups (infants, children, adolescents, youth 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.
Publisher
The World Bank
Origin
East Asia & Pacific (IDA & IBRD countries)
Records
63
Source