Obesity
Adults with a body mass index (a measure of weight for height) of 30 or more, worked out from the height and weight they reported themselves.
Reported for49states — none in KY, PA, PR
Link to density0.30not mostly about how urban a place is
Nearby places alike—not worked out for states: the map data here has no location points to measure distances between states
Typerate% of adults
How it has moved
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Every state, every year
One row per state and one column per year, sorted by the latest value. It shows states, not counties: nobody can scan 3,222 rows, and the pattern only shows when it all fits on one screen.
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Where it comes from
· BRFSS _BMI5CAT, age-standardised
Adults with a body mass index of 30 or more, from reported height and weight. People report this themselves in the Behavioral Risk Factor Surveillance System, a national health survey. This is the survey result for each state, not an estimate from a statistical model. CDC PLACES builds its county estimates from this same survey. Here it is used at the state level, where the survey is designed to give a fair picture. Rates are adjusted to the age mix of the 2000 US population, so the figures do not just reflect which states have older people.
Combining areas: it cannot be combined, so it is shown only where its publisher works it out.
What it goes with
The strongest links that have a page of their own. Unadjusted is the link before adjusting for anything, from −1 (opposite) to +1 (in step). Adjusted compares places with the same population density, income and education levels, so those differences can’t explain the link. This list leaves out the 1 pairs built from the same numbers or the same model as this measure, since they are bound to match. These compare 49 states, not counties. With only about fifty places behind each figure, none of them is strong evidence on its own.
| Measure | Unadjusted | Adjusted |
|---|---|---|
| Median household incomeLinked across states, but mostly as both follow how urban, rich and educated a place is. Comparing only places with similar density, income and education, what is left could easily be chance. | -0.78 | -0.38 |
| ArthritisLinked across states, but mostly as both follow how urban, rich and educated a place is. Comparing only places with similar density, income and education, what is left could easily be chance. | +0.76 | +0.37 |
| Median household income (model-based)Linked across states, but mostly as both follow how urban, rich and educated a place is. Comparing only places with similar density, income and education, what is left could easily be chance. | -0.80 | -0.36 |
| Years of potential life lostLinked across states, but mostly as both follow how urban, rich and educated a place is. Comparing only places with similar density, income and education, what is left could easily be chance. | +0.70 | +0.32 |
| Evangelical Protestant adherentsLinked across states, but mostly as both follow how urban, rich and educated a place is. Comparing only places with similar density, income and education, what is left could easily be chance. | +0.62 | +0.31 |
| Child mortalityLinked across states, but mostly as both follow how urban, rich and educated a place is. Comparing only places with similar density, income and education, what is left could easily be chance. | +0.63 | +0.30 |
| Meets aerobic guidelinesLinked across states, but mostly as both follow how urban, rich and educated a place is. Comparing only places with similar density, income and education, what is left could easily be chance. | -0.61 | -0.26 |
| Returns reporting unemployment compensationLinked across states, but mostly as both follow how urban, rich and educated a place is. Comparing only places with similar density, income and education, what is left could easily be chance. | -0.52 | -0.25 |
| Safety scoreLinked across states, but mostly as both follow how urban, rich and educated a place is. Comparing only places with similar density, income and education, what is left could easily be chance. | -0.55 | -0.23 |
| Homeownership rateLinked across states, but mostly as both follow how urban, rich and educated a place is. Comparing only places with similar density, income and education, what is left could easily be chance. | +0.51 | +0.21 |
Population makeup
How this measure varies with the racial and ethnic makeup of states. Every group is shown, whatever its rank. These are links across states: they describe places, not people. They say nothing about any person’s risk or behaviour based on their race. States with a larger share of one group also differ in much else, such as income, segregation, region and history. The adjusted figure only accounts for density, income and education.
| Share of residents | Unadjusted | Adjusted |
|---|---|---|
| Share White, not HispanicCould easily be chance once only places with similar density, income and education are compared. | +0.31 | +0.24 |
| Share Black, not HispanicCould easily be chance once only places with similar density, income and education are compared. | +0.16 | +0.30 |
| Share Hispanic or Latino, any raceCould easily be chance once only places with similar density, income and education are compared. | -0.34 | -0.38 |
| Share Asian, not HispanicCould easily be chance once only places with similar density, income and education are compared. | -0.45 | -0.37 |
| Share American Indian or Alaska Native, not HispanicCould easily be chance once only places with similar density, income and education are compared. | +0.15 | +0.16 |
Highest and lowest
Of 49 states reporting it. These are the two ends of a national ranking. For most measures, that ranking mostly sorts places by income and how urban they are. That is why the place pages compare each place with similar places instead.
Highest
- West Virginia — 42.3
- Mississippi — 40.9
- Arkansas — 40.7
- Louisiana — 40.2
- Alabama — 39.8
Lowest
- District of Columbia — 24.2
- Colorado — 24.7
- Hawaii — 27
- Massachusetts — 27.3
- California — 28
The middle state reports 34.4. The middle half of states falls between 30.9 and 36.6 (the 25th to 75th percentile).
All measures · Explore its pairs · How the US county data works