Premature mortality and Hospital stays per 1,000 Medicare enrollees

Holds after adjusting

Every place, plotted

One dot for each place reporting both measures. Hover over or tap a dot to see its name and values. The thin line is the straight line that best fits the dots. The bold line, shown for counties, is the link after adjusting for density, income and education. A dot far from the lines is a place that does not follow the pattern.

Loading every place…

What each measure is

Highest and lowest

Where each measure is highest and lowest among the places reporting both (2023), with the other measure beside it. This is shown for every size of place where both are published. Metro-area values are added up from their counties. A measure that cannot be added up across counties, such as a middle value (median), has no metro figure. Counts are shown per 1,000 residents, since raw totals would only list the largest places. Cities and towns and ZIP codes are shown where the Census survey or the CDC publishes them; most other sources stop at the county. They are shown for places of 5,000 residents or more, and only where the survey’s margin of error is small enough for the figure to be usable. The CDC publishes its health estimates for cities in a version adjusted for age, so places with older or younger people can be compared fairly, but not for ZIP codes.

Counties furthest from the pattern

Compared with the straight line that best fits all 3,080 counties: the five with far more hospital stays per 1,000 Medicare enrollees than their premature mortality would suggest, and the five with far less.

Two series, one county

Both measures over time for a county you pick. The two charts are stacked, so they share only the years along the bottom. You can pick from the thirty largest counties reporting both. This panel covers 2010–2024, and a measure published only once shows as a single dot.

Loading…

Every version of the link

Each row measures the same link, from −1 to +1, in a different way. If the rows mostly agree, the link does not depend on one choice of method.

How much to believe it

Did they change together?

The figures above compare counties at one moment. This asks a different question: where premature mortality rose most, did hospital stays per 1,000 Medicare enrolleesmove too? Each county’s change is compared with the average change in its own state. That takes out ups and downs that hit a whole region at once. Each change is the gap between two estimates that both contain some error. That error pulls these links towards zero, so a weak one is weak partly for that reason. The q column shows whether a link could be a fluke, allowing for the many pairs tested: 0.05 or less means it is unlikely to be chance.

Measured over the nearest years published: Premature mortality: 2013–2019 for the 2014–2019 row; Premature mortality: 2019–2022 for the 2019–2023 row.

Over the main period, any link between the changes could easily be chance. How change is measured.

Related pairs

• Premature mortality and Safety score — -0.67
• Premature mortality and Homicide rate, annual — +0.67
• Share American Indian or Alaska Native, not Hispanic and Premature mortality — +0.63
• Independent-living disability and Premature mortality — +0.60
• Threat of utility shut-off and Premature mortality — +0.58
• Premature mortality and Returns claiming the earned income credit — +0.58
• Premature mortality and Disability-free score — -0.57
• Stroke and Premature mortality — +0.57

Association only. Nothing here shows that either measure changes the other. This describes counties, not the people in them. Two measures going together across places does not mean the same people have both. How the US county data works · Explore Premature mortality and Hospital stays per 1,000 Medicare enrollees