Probability of dying among adolescents ages 15-19 years (per 1,000)

Probability of dying between age 15-19 years of age expressed per 1,000 adolescents age 15, 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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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
Global
Records
24206
Source
Probability of dying among adolescents ages 15-19 years (per 1,000)
country_code year value
ABW 1960
AFE 1960
AFG 1960
AFW 1960
AGO 1960
ALB 1960
AND 1960
ARB 1960
ARE 1960
ARG 1960
ARM 1960
ASM 1960
ATG 1960
AUS 1960
AUT 1960
AZE 1960
BDI 1960
BEL 1960
BEN 1960
BFA 1960
BGD 1960
BGR 1960
BHR 1960
BHS 1960
BIH 1960
BLR 1960
BLZ 1960
BMU 1960
BOL 1960
BRA 1960
BRB 1960
BRN 1960
BTN 1960
BWA 1960
CAF 1960
CAN 1960
CEB 1960
CHE 1960
CHI 1960
CHL 1960
CHN 1960
CIV 1960
CMR 1960
COD 1960
COG 1960
COL 1960
COM 1960
CPV 1960
CRI 1960
CSS 1960
CUB 1960
CUW 1960
CYM 1960
CYP 1960
CZE 1960
DEU 1960
DJI 1960
DMA 1960
DNK 1960
DOM 1960
DZA 1960
EAP 1960
EAR 1960
EAS 1960
ECA 1960
ECS 1960
ECU 1960
EGY 1960
EMU 1960
ERI 1960
ESP 1960
EST 1960
ETH 1960
EUU 1960
FCS 1960
FIN 1960
FJI 1960
FRA 1960
FRO 1960
FSM 1960
GAB 1960
GBR 1960
GEO 1960
GHA 1960
GIB 1960
GIN 1960
GMB 1960
GNB 1960
GNQ 1960
GRC 1960
GRD 1960
GRL 1960
GTM 1960
GUM 1960
GUY 1960
HIC 1960
HKG 1960
HND 1960
HPC 1960
HRV 1960

Probability of dying among adolescents ages 15-19 years (per 1,000)

Probability of dying between age 15-19 years of age expressed per 1,000 adolescents age 15, 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
Global
Records
24206
Source