Trinidad and Tobago - Mortality rate, infant, female (per 1,000 live births)

The value for Mortality rate, infant, female (per 1,000 live births) in Trinidad and Tobago was 13.30 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 51.40 in 1960 and a minimum value of 13.30 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 51.40
1961 49.80
1962 48.30
1963 46.90
1964 45.70
1965 44.50
1966 43.50
1967 42.60
1968 41.70
1969 41.00
1970 40.20
1971 39.50
1972 38.70
1973 37.80
1974 36.90
1975 36.00
1976 35.10
1977 34.10
1978 33.10
1979 32.10
1980 31.10
1981 30.20
1982 29.30
1983 28.50
1984 27.70
1985 26.90
1986 26.20
1987 25.60
1988 25.10
1989 24.60
1990 24.10
1991 23.70
1992 23.40
1993 23.10
1994 22.90
1995 22.70
1996 22.60
1997 22.50
1998 22.40
1999 22.30
2000 22.20
2001 22.10
2002 21.80
2003 21.50
2004 21.10
2005 20.60
2006 20.10
2007 19.60
2008 19.00
2009 18.50
2010 17.90
2011 17.50
2012 17.00
2013 16.50
2014 16.00
2015 15.50
2016 15.00
2017 14.60
2018 14.20
2019 13.70
2020 13.30

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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