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

The value for Mortality rate, infant, male (per 1,000 live births) in Dominican Republic was 30.30 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 106.00 in 1960 and a minimum value of 30.30 in 2020.

Definition: Infant mortality rate, male is the number of male infants dying before reaching one year of age, per 1,000 male live births in a given 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 106.00
1961 105.20
1962 104.20
1963 103.00
1964 101.60
1965 100.00
1966 98.20
1967 96.40
1968 94.70
1969 92.90
1970 91.10
1971 89.00
1972 86.70
1973 84.50
1974 82.00
1975 79.60
1976 77.10
1977 74.80
1978 72.50
1979 70.40
1980 68.40
1981 66.30
1982 64.40
1983 62.50
1984 60.60
1985 58.70
1986 56.90
1987 55.10
1988 53.30
1989 51.40
1990 49.70
1991 47.90
1992 46.20
1993 44.40
1994 42.80
1995 41.20
1996 39.70
1997 38.30
1998 37.10
1999 36.10
2000 35.20
2001 34.40
2002 33.70
2003 33.10
2004 32.70
2005 32.30
2006 32.00
2007 31.80
2008 31.60
2009 31.50
2010 31.40
2011 31.40
2012 31.30
2013 31.30
2014 31.30
2015 31.30
2016 31.20
2017 31.20
2018 31.00
2019 30.80
2020 30.30

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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