Papua New Guinea - Mortality rate, under-5, male (per 1,000 live births)

The value for Mortality rate, under-5, male (per 1,000 live births) in Papua New Guinea was 47.30 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 204.70 in 1960 and a minimum value of 47.30 in 2020.

Definition: Under-five mortality rate, male is the probability per 1,000 that a newborn male baby will die before reaching age five, if subject to male 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 204.70
1961 198.50
1962 192.30
1963 186.40
1964 180.70
1965 174.90
1966 169.40
1967 164.10
1968 158.90
1969 153.70
1970 148.80
1971 144.10
1972 139.50
1973 135.10
1974 131.10
1975 127.20
1976 123.50
1977 119.90
1978 116.60
1979 113.50
1980 110.50
1981 107.90
1982 105.30
1983 102.90
1984 100.60
1985 98.50
1986 96.60
1987 94.60
1988 92.80
1989 90.90
1990 89.20
1991 87.50
1992 85.90
1993 84.40
1994 82.90
1995 81.50
1996 80.20
1997 78.90
1998 77.60
1999 76.40
2000 75.20
2001 73.90
2002 72.80
2003 71.50
2004 70.20
2005 68.90
2006 67.50
2007 66.10
2008 64.60
2009 63.20
2010 61.70
2011 60.40
2012 58.90
2013 57.60
2014 56.20
2015 54.70
2016 53.30
2017 51.90
2018 50.30
2019 48.80
2020 47.30

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