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

The value for Mortality rate, under-5, male (per 1,000 live births) in Dominican Republic was 36.70 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 151.30 in 1960 and a minimum value of 36.70 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 151.30
1961 150.10
1962 148.60
1963 146.70
1964 144.50
1965 141.90
1966 139.20
1967 136.50
1968 133.70
1969 130.80
1970 127.80
1971 124.50
1972 120.80
1973 117.20
1974 113.30
1975 109.40
1976 105.60
1977 101.90
1978 98.40
1979 95.10
1980 91.80
1981 88.70
1982 85.70
1983 82.80
1984 79.90
1985 77.10
1986 74.30
1987 71.60
1988 68.90
1989 66.30
1990 63.80
1991 61.20
1992 58.70
1993 56.20
1994 53.80
1995 51.60
1996 49.50
1997 47.60
1998 45.90
1999 44.50
2000 43.20
2001 42.10
2002 41.30
2003 40.50
2004 39.90
2005 39.40
2006 39.00
2007 38.70
2008 38.40
2009 38.30
2010 38.20
2011 38.10
2012 38.00
2013 38.00
2014 38.00
2015 38.00
2016 37.90
2017 37.90
2018 37.70
2019 37.30
2020 36.70

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