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

The value for Mortality rate, under-5, female (per 1,000 live births) in Papua New Guinea was 40.40 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 190.50 in 1960 and a minimum value of 40.40 in 2020.

Definition: Under-five mortality rate, female is the probability per 1,000 that a newborn female baby will die before reaching age five, if subject to female 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 190.50
1961 184.60
1962 178.70
1963 173.10
1964 167.50
1965 162.10
1966 156.70
1967 151.50
1968 146.40
1969 141.50
1970 136.70
1971 132.20
1972 127.90
1973 123.70
1974 119.80
1975 116.00
1976 112.50
1977 109.20
1978 106.10
1979 103.20
1980 100.50
1981 97.80
1982 95.40
1983 93.10
1984 91.00
1985 89.00
1986 87.10
1987 85.30
1988 83.60
1989 81.90
1990 80.20
1991 78.60
1992 77.10
1993 75.60
1994 74.20
1995 72.90
1996 71.60
1997 70.40
1998 69.20
1999 68.00
2000 66.80
2001 65.70
2002 64.50
2003 63.30
2004 62.00
2005 60.70
2006 59.40
2007 58.00
2008 56.70
2009 55.20
2010 53.90
2011 52.50
2012 51.20
2013 49.80
2014 48.50
2015 47.10
2016 45.80
2017 44.40
2018 43.10
2019 41.60
2020 40.40

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