Child Mortality*

Data Source

National Center for Health Statistics - Mortality Files; Census Population Estimates Program

The National Center for Health Statistics (NCHS) provides birth and death data drawn from the National Vital Statistics System (NVSS). These data are submitted to the NVSS by the vital registration systems operated in the jurisdictions legally responsible for registering vital events (i.e., births, deaths, marriages, divorces, and fetal deaths). 

The Census Bureau’s Population Estimates Program (PEP) uses data on births, deaths, and migration to estimate population changes occurring since the most recent decennial census and produce a vintage, or annual time series of estimates. Each vintage includes the current data year and revised estimates for any earlier years since the last decennial census. Because each vintage of estimates includes all years since the most recent decennial census, the latest vintage supersedes all other estimates produced since the previous decennial census. See the Population Estimates Program methodology for statements and release notes for each vintage of population estimates.

Website to download data

Child Mortality is a rate

Child Mortality measures the number of deaths occurring before age 18 per 100,000 population. Rates measure the number of events (e.g., deaths, births) in a given time period divided by the average number of people at risk during that period. Rates facilitate data comparisons across counties with different population sizes.

Child Mortality is a rare event (statistically speaking)

Child death is a relatively rare event in most counties. Counties with smaller populations can see a lot of relative change in child death rates from year to year. Such changes are usually due to normal variation and are not necessarily caused by any actual change in the underlying risk of child death in the county. To help determine if the child death change in a county is due to normal variation or real change, we recommend examining the provided error margins. Error margins are statistical tools that aid interpretation of variation in measures. If the error margins overlap year to year, it’s less likely that the variation in Child Mortality reflects real underlying changes in community health.

What deaths count toward Child Mortality?

Deaths are counted in the county of residence, regardless of where the death occurred.

Some data are suppressed

A missing value is reported for counties with fewer than 10 child deaths in the time frame.

The method for calculating Child Mortality has changed

In the 2024 Annual Data Release, data from the Census Bureau's Population Estimates Program were used in the calculation of the denominator for this measure. In previous data releases, the denominator was calculated from the National Center for Health Statistics Bridged-Race Population Estimates; this data series was discontinued in 2023. The denominator change and updates to race categories in the 2024 Annual Data Release mean that comparisons with previous years should be made with caution. 

With the 2024 Annual Data Release, the definition of child was expanded from 0-17 years and now includes people ages 0-19 years old.

Caution should be used when comparing these estimates across years

Caution should be used when comparing across years due to methods changes described in the “The method for calculating Child Mortality has changed” section. 

Numerator

The numerator is the number of deaths occurring before the age of 20.

Denominator

The denominator is the total population under the age of 20.

This measure can be used to track progress with some caveats. Child death is a relatively rare event, especially in small counties. Statistics depend on large numbers of events to detect small changes, meaning that small changes in small communities may be difficult to detect. It is also important to note that the estimate provided in the Health Snapshots is a four-year average.

Disaggregation means breaking data down into smaller, meaningful subgroups. Disaggregated data are often broken down by characteristics of people or where they live. Disaggregated data can reveal inequalities that are otherwise hidden. These data can be disaggregated by:

• Age
• Gender
• Race

We recommend starting with the CDC Wonder database, which contains information on death rates by race, ethnicity, age, gender, geography, cause of death, and more. Rates can be exported as crude or age-adjusted. Small counties might need to combine multiple years of data to see rates, as CDC suppresses any rates when there are fewer than 10 deaths.