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

The value for Mortality rate, infant, female (per 1,000 live births) in Dominican Republic was 25.30 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 97.80 in 1960 and a minimum value of 25.30 in 2020.

Definition: Infant mortality rate, female is the number of female infants dying before reaching one year of age, per 1,000 female 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 97.80
1961 97.20
1962 96.20
1963 95.00
1964 93.50
1965 91.90
1966 90.20
1967 88.50
1968 86.60
1969 84.70
1970 82.80
1971 80.60
1972 78.30
1973 75.70
1974 73.00
1975 70.30
1976 67.70
1977 65.30
1978 63.00
1979 60.70
1980 58.60
1981 56.60
1982 54.70
1983 52.80
1984 51.20
1985 49.60
1986 48.10
1987 46.60
1988 45.10
1989 43.70
1990 42.20
1991 40.70
1992 39.10
1993 37.70
1994 36.20
1995 34.90
1996 33.60
1997 32.40
1998 31.30
1999 30.30
2000 29.50
2001 28.90
2002 28.30
2003 27.90
2004 27.50
2005 27.20
2006 26.90
2007 26.70
2008 26.50
2009 26.30
2010 26.20
2011 26.10
2012 26.10
2013 26.10
2014 26.20
2015 26.20
2016 26.20
2017 26.10
2018 26.00
2019 25.70
2020 25.30

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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