Dominican Republic - Mortality rate, under-5, female (per 1,000 live births)

The value for Mortality rate, under-5, female (per 1,000 live births) in Dominican Republic was 30.60 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 143.50 in 1960 and a minimum value of 30.60 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 143.50
1961 142.30
1962 140.80
1963 138.80
1964 136.50
1965 133.90
1966 131.20
1967 128.40
1968 125.50
1969 122.60
1970 119.40
1971 116.10
1972 112.50
1973 108.40
1974 104.20
1975 100.00
1976 96.00
1977 92.20
1978 88.50
1979 84.90
1980 81.60
1981 78.50
1982 75.30
1983 72.40
1984 69.60
1985 67.00
1986 64.60
1987 62.10
1988 59.80
1989 57.50
1990 55.10
1991 52.80
1992 50.50
1993 48.30
1994 46.20
1995 44.20
1996 42.30
1997 40.60
1998 39.00
1999 37.70
2000 36.60
2001 35.60
2002 34.80
2003 34.20
2004 33.70
2005 33.20
2006 32.90
2007 32.50
2008 32.30
2009 32.00
2010 31.90
2011 31.80
2012 31.80
2013 31.80
2014 31.80
2015 31.80
2016 31.90
2017 31.80
2018 31.60
2019 31.20
2020 30.60

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