DEATH & DISPARITY

Color palette

CDC data · 1999-2024 · County level

Death & Disparity: An American Portrait

Explore 25 years of CDC data to understand who dies, where, and why...and what it means for policy.

Race and ethnicity classification Race and ethnicity on death certificates is recorded by the funeral director based on observation or next of kin report, not self identification. This can introduce misclassification, particularly for American Indian and Alaska Native, Asian, and Hispanic populations, meaning disparities for these groups may be understated or inconsistently captured across counties and years.   Suppressed county counts Counties with fewer than 10 deaths in a category are suppressed by the CDC to protect individual privacy. These values are excluded from this dashboard, meaning rural counties and smaller racial and ethnic groups are underrepresented. Disparities in the most vulnerable and lowest population communities are likely understated as a result.   Age-adjusted rates Age-adjusted rates are used throughout to allow fair comparisons across counties and demographic groups with different age structures. Raw death counts alone would conflate older populations with higher mortality areas and make geographic comparisons misleading.   About this dashboard The front end is built in R Shiny using bslib, plotly, leaflet, sf, and tigris for visualization and mapping. All app data lives in a PostgreSQL database hosted on Railway, connected at runtime via DBI and RPostgres. Mortality data comes from CDC WONDER, pre-processed and stored in PostgreSQL so the app never calls the CDC directly. Congressional trades, lobbying spend, and campaign finance data are fetched from Quiver Quant by a companion Python service and cached in the same database. US county and state boundaries come from Census TIGER shapefiles via the tigris package.

Chris Bell & Julian Pacheco · v1.0

Source: CDC WONDER · tigris · U.S. Census

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US Mortality Explorer

CDC WONDER | 1999–2024

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Total deaths

Leading cause

Rate per 100k

Age Adjusted Rate reflects deaths per 100,000 people after statistically accounting for age distribution differences between populations making it a fairer way to compare mortality across states, counties, and time periods.

Rates shown are not age-adjusted at this level and should be interpreted as population level counts rather than risk comparisons across groups.

Mortality Rate by Race and Ethnicity

How each race group compares to the national mortality average

Race is recorded on death certificates by funeral directors based on observation or next of kin report, not self-identification, which can introduce misclassification particularly for American Indian, Alaska Native, and multiracial populations. County-level filtering may trigger CDC suppression for smaller race groups. When fewer than 4 groups have data a suppression notice appears in place of this chart.

DISPARITY ANALYSIS

The disparity index is a composite score ranging from 0 to 1 built from two components. Relative burden is a county’s age adjusted mortality rate divided by the national average (1.0 = national average; 2.0 = twice as deadly). Sex disparity ratio is the male mortality rate divided by the female rate within the same county, capturing how unequally death is distributed between men and women locally. Each component is scaled using a percent rank, converting every county’s value into a 0 to 1 position relative to all other counties in the same year and cause group, then averaged into a single index. A county scoring 0.9 is not just a deadly place. It is a place where mortality is both elevated and internally unequal compared to nearly every other county in the country. The relative burden component draws on Murray et al. (2006), which found that where you live can matter as much as who you are. The sex disparity component draws on Williams and Collins (2001), which examined how structural inequalities produce measurable gaps in health outcomes between groups in the same place.

Burden & Disparity Divergence

Top 20 counties sorted by relative burden, hover for details

The left panel shows each county's male to female death rate ratio, where 1.0 means equal rates between men and women. The right panel shows how far each county's overall death rate exceeds the national average. Counties are sorted by relative burden. Gasconade County, Missouri shows an unusually high sex disparity ratio reflecting a large gap between male and female death rates in that county across the selected filters.

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