Infant Mortality Rate by Maternal Race/Ethnicity for New York City, 2007-2016 Counts of infant deaths (age <1 year) are based on NYC death certificates. The rate is calculated using the counts of infant deaths as the numerator and the count of live births from NYC birth certificates as the denominator.

All birth data by race before 1980 are based on race of the child; starting in 1980, birth data by race are based on race of the mother. Birth data are used to calculate infant mortality rate. https://www.cdc.gov/nchs/data-visualization/mortality-trends/

Survey variables needed to calculate fertility and childhood mortality rates.

In 2023, the infant mortality rate in deaths per 1,000 live births in Brazil amounted to 12.5. Between 1960 and 2023, the figure dropped by 113.9, though the decline followed an uneven course rather than a steady trajectory.

In 2023, the infant mortality rate in deaths per 1,000 live births in the United States amounted to 5.5. Between 1960 and 2023, the figure dropped by 20.4, though the decline followed an uneven course rather than a steady trajectory.

The infant mortality rate in Finland has fluctuated over the last 10 years. In 2015, the infant mortality rate was 1.7 deaths per 1,000 live births, which was the lowest figure ever recorded in the country. The infant mortality rate fluctuated in the years that followed, amounting to 2.1 per thousand live births in 2024.

Fetal mortality occurs after 20 weeks of gestation and before labor. Infant mortality occurs before the first year of age and is a sum of Neonatal (the first 28 days after birth) and Postneonatal (from 28 days up to 1 year) mortality. Rates are calculated per every 1000 births; rates are not available for disaggregated race/ethnicities. Fetal and infant mortality values are available for given race/ethnicities. Connecticut Department of Public Health collects and reports data annually. CTData.org carries 1-, 3- and 5-Year aggregations.

The Global Subnational Infant Mortality Rates, Version 2.01 consist of Infant Mortality Rate (IMR) estimates for 234 countries and territories, 143 of which include subnational Units. The data are benchmarked to the year 2015 (Version 1 was benchmarked to the year 2000), and are drawn from national offices, Demographic and Health Surveys (DHS), Multiple Indicator Cluster Surveys (MICS), and other sources from 2006 to 2014. In addition to Infant Mortality Rates, Version 2.01 includes crude estimates of births and infant deaths, which could be aggregated or disaggregated to different geographies to calculate infant mortality rates at different scales or resolutions, where births are the rate denominator and infant deaths are the rate numerator. Boundary inputs are derived primarily from the Gridded Population of the World, Version 4 (GPWv4) data collection. National and subnational data are mapped to grid cells at a spatial resolution of 30 arc-seconds (~1 km) (Version 1 has a spatial resolution of 1/4 degree, ~28 km at the equator), allowing for easy integration with demographic, environmental, and other spatial data.

This SAS macro generates childhood mortality estimates (neonatal, post-neonatal, infant (1q0), child (4q1) and under-five (5q0) mortality) and standard errors based on birth histories reported by women during a household survey. We have made the SAS macro flexible enough to accommodate a range of calculation specifications including multi-stage sampling frames, and simple random samples or censuses. Childhood mortality rates are the component death probabilities of dying before a specific age. This SAS macro is based on a macro built by Keith Purvis at MeasureDHS. His method is described in Estimating Sampling Errors of Means, Total Fertility, and Childhood Mortality Rates Using SAS (www.measuredhs.com/pubs/pdf/OD17/OD17.pdf, section 4). More information about Childhood Mortality Estimation can also be found in the Guide to DHS Statistics (www.measuredhs.com/pubs/pdf/DHSG1/Guide_DHS_Statistics.pdf, page 93). We allow the user to specify whether childhood mortality calculations should be based on 5 or 10 years of birth histories, when the birth history window ends, and how to handle age of death with it is reported in whole months (rather than days). The user can also calculate mortality rates within sub-populations, and take account of a complex survey design (unequal probability and cluster samples). Finally, this SAS program is designed to read data in a number of different formats.

The probability of dying between birth and the exact age of 1, expressed per 1,000 live births. The data is sorted by both sex and total and includes a range of values from 1900 to 2019. The calculation for infant mortality rates is derived from a standard period abridged life table using the age-specific deaths and mid-year population counts from civil registration data. This data is sourced from the UN Inter-Agency Group for Child Mortality Estimation. The UN IGME uses the same estimation method across all countries to arrive at a smooth trend curve of age-specific mortality rates. The estimates are based on high quality nationally representative data including statistics from civil registration systems, results from household surveys, and censuses. The child mortality estimates are produced in conjunction with national level agencies such as a country’s Ministry of Health, National Statistics Office, or other relevant agencies.

The Global Subnational Infant Mortality Rates, Version 2.01 consist of Infant Mortality Rate (IMR) estimates for 234 countries and territories, 143 of which include subnational Units. The data are benchmarked to the year 2015 (Version 1 was benchmarked to the year 2000), and are drawn from national offices, Demographic and Health Surveys (DHS), Multiple Indicator Cluster Surveys (MICS), and other sources from 2006 to 2014. In addition to Infant Mortality Rates, Version 2.01 includes crude estimates of births and infant deaths, which could be aggregated or disaggregated to different geographies to calculate infant mortality rates at different scales or resolutions, where births are the rate denominator and infant deaths are the rate numerator. Boundary inputs are derived primarily from the Gridded Population of the World, Version 4 (GPWv4) data collection. National and subnational data are mapped to grid cells at a spatial resolution of 30 arc-seconds (~1 km) (Version 1 has a spatial resolution of 1/4 degree, ~28 km at the equator), allowing for easy integration with demographic, environmental, and other spatial data.

In 2023, the infant mortality rate in deaths per 1,000 live births in Finland stood at 1.8. Between 1960 and 2023, the figure dropped by 20.1, though the decline followed an uneven course rather than a steady trajectory.

Number of infant deaths and infant mortality rates, by age group (neonatal and post-neonatal), 1991 to most recent year.

In 2023, the infant mortality rate in deaths per 1,000 live births in Portugal amounted to 2.6. Between 1960 and 2023, the figure dropped by 81.6, though the decline followed an uneven course rather than a steady trajectory.

Fetal mortality occurs after 20 weeks of gestation and before labor. Infant mortality occurs before the first year of age and is a sum of Neonatal (the first 28 days after birth) and Postneonatal (from 28 days up to 1 year) mortality. Rates are calculated per every 1000 births; rates are not available for disaggregated race/ethnicities. Fetal and infant mortality values are available for given race/ethnicities. Connecticut Department of Public Health collects and reports data annually. CTData.org carries 1-, 3- and 5-Year aggregations.

OBJECTIVE : To propose a simplified method of correcting vital information and estimating the coefficient of infant mortality in Brazil. METHODS : Vital data in the information systems on mortality and live births were corrected using correction factors, estimated based on events not reported to the Brazilian Ministry of Health and obtained by active search. This simplified method for correcting vital information for the period 2000-2009 for Brazil and its federal units establishes the level of adequacy of information on deaths and live births by calculating the overall coefficient of mortality standardized by age and the ratio between reported and expected live births, respectively, in each Brazilian municipality. By applying correction factors to the number of deaths and live births reported in each county, the vital statistics were corrected, making it possible to estimate the coefficient of infant mortality. RESULTS : The highest correction factors were related to infant deaths, reaching values higher than 7 for municipalities with very precarious mortality information. For deaths and live births, the correction factors exhibit a decreasing gradient as indicators of adequacy of the vital information improve. For the year 2008, the vital information corrected by the simplified method per state were similar to those obtained in the research of active search. Both the birth rate and the infant mortality rate decreased in the period in all Brazilian regions. In the Northeast, the annual rate of decline was 6.0%, the highest in Brazil (4.7%). CONCLUSIONS : The active search of deaths and births allowed correction factors to be calculated by level of adequacy of mortality information and live births. The simplified method proposed here allowed vital information to be corrected per state for the period 2000-2009 and the progress of the coefficient of infant mortality in Brazil, its regions and states to be assessed.

For current version see: https://www.sandiegocounty.gov/content/sdc/hhsa/programs/phs/maternal_child_family_health_services/MCFHSstatistics.html

Infant Mortality - Cohort Dataset Note: The Infant Mortality Rate is infant deaths (under one year of age) per 1,000 live births, by geography. Numerator represents infant's race/ethnicity. Denominator represents mother's race/ethnicity.

***API: Asian/Pacific Islander. ***AIAN: American Indian/Alaska Native. Blank Cells: Rates not calculated for fewer than 5 events. Rates not calculated in cases where infant's zip code of residence is unknown.

Sources: State of California, Department of Public Health, Death Statistical Master Files (before 2014), California Comprehensive Death Files (2014 and later), and Birth Statistical Master Files. Prepared by: County of San Diego, Health & Human Services Agency, Public Health Services, Community Health Statistics Unit, 2019.

Interpretation: "There were 5 infant deaths per 1,000 live births in Geography X".

Data Guide, Dictionary, and Codebook: https://www.sandiegocounty.gov/content/dam/sdc/hhsa/programs/phs/CHS/Community%20Profiles/Public%20Health%20Services%20Codebook_Data%20Guide_Metadata_10.2.19.xlsx

14.5 (Deaths per 1,000 live births) in 2015. The infant mortality rate is calculated as the sum of two components, the first of which - the ratio of the number of deaths before the age of one year from the generation born in the year for which the calculated ratio to the total number of births in the same year, and the second - the ratio of the number of deaths at age up to one year from the generation born in the previous year to the total number of births in the previous year

For current version see: https://www.sandiegocounty.gov/content/sdc/hhsa/programs/phs/maternal_child_family_health_services/MCFHSstatistics.html

Infant Mortality - VRBIS Dataset Note: This dataset is created from the mortality database. Cases are registered deaths only. The Infant Mortality Rate is infant deaths (under one year of age) per 1,000 live births, by geography. Rates not calculated in cases where infant's zip code of residence is unknown. Numerator represents infant's race/ethnicity. Denominator represents mother's race/ethnicity.

***API: Asian/Pacific Islander. ***AIAN: American Indian/Alaska Native. Blank Cells: Rates not calculated for fewer than 5 events.

Sources: California Department of Public Health, Center for Health Statistics, Office of Health Information and Research, Vital Records Business Intelligence System, 2016.
Prepared by: County of San Diego, Health & Human Services Agency, Public Health Services, Community Health Statistics Unit, 2019.

Interpretation: "There were 5 infant deaths per 1,000 live births in Geography X".

Data Guide, Dictionary, and Codebook: https://www.sandiegocounty.gov/content/dam/sdc/hhsa/programs/phs/CHS/Community%20Profiles/Public%20Health%20Services%20Codebook_Data%20Guide_Metadata_10.2.19.xlsx

7.0 (Deaths per 1,000 live births) in 2015. The infant mortality rate is calculated as the sum of two components, the first of which - the ratio of the number of deaths before the age of one year from the generation born in the year for which the calculated ratio to the total number of births in the same year, and the second - the ratio of the number of deaths at age up to one year from the generation born in the previous year to the total number of births in the previous year