Obesity
The estimated percentage of adults who have a body mass index (a measure of weight for height) of 30 or above. It is adjusted so places with older or younger populations can be compared fairly. It is an estimate from a statistical model, not a direct count from a local survey.
Reported for2,956areas, in 49 states — none in KY, PA, PR
Link to density0.14not mostly about how urban a place is
Nearby places alike0.61Moran’s I: strongly, neighbouring places tend to be similar
Typerate%
How it has moved
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Every state, every year
Nothing to draw here: this measure has no state figures. Its publisher reports it for counties. This site does not add county numbers up into state figures, since a home-made figure could clash with one an agency publishes itself. The chart above covers the whole country, year by year.
Where it comes from
CDC PLACES · PLACES OBESITY, age-adjusted
An estimate from a statistical model, not a direct measurement. The model starts from interviews in a national health survey (BRFSS). It fills in local detail using Census population counts and figures from the American Community Survey (ACS). So the estimate partly reflects ACS measures that also appear on this site. When counties are combined, bigger ones get more weight. That gives a close figure, not an exact one. Each county rate is age-adjusted: adjusted to the age mix of the 2000 US population, so places with older or younger people can be compared fairly. That makes the rates nearly combinable. The exact figure would need counts by age group, which the CDC does not release. Where precision matters, read the county values directly.
Combining areas: an average weighted by population aged 18 and over.
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 95 pairs built from the same numbers or the same model as this measure, since they are bound to match.
| Measure | Unadjusted | Adjusted |
|---|---|---|
| Obesity and Homicide rateWhere Obesity is higher, Homicide rate tends to be higher: a weak link that holds when only places with similar density, income and education are compared, and inside states as well. Homicide rate by US county | +0.55 | +0.32 |
| Obesity and Mean income of arriving householdsLinked across counties, but mostly as both follow how urban, rich and educated a place is. Comparing only places with similar density, income and education, a weak link of -0.31 remains. Mean income of arriving households by US county | -0.65 | -0.31 |
| Obesity and Infant mortalityLinked across counties, but mostly as both follow how urban, rich and educated a place is. Comparing only places with similar density, income and education, a weak link of +0.26 remains. Infant mortality by US county | +0.60 | +0.26 |
| Obesity and Homicide rate, annualLinked across counties, but mostly as both follow how urban, rich and educated a place is. Comparing only places with similar density, income and education, a weak link of +0.26 remains. Homicide rate, annual by US county | +0.54 | +0.26 |
| Obesity and Mean income of departing householdsLinked across counties, but mostly as both follow how urban, rich and educated a place is. Comparing only places with similar density, income and education, a weak link of -0.23 remains. Mean income of departing households by US county | -0.65 | -0.23 |
| Obesity and Child mortalityLinked across counties, but mostly as both follow how urban, rich and educated a place is. Comparing only places with similar density, income and education, a weak link of +0.20 remains. Child mortality by US county | +0.54 | +0.20 |
| Obesity and Life expectancyLinked across counties, but mostly as both follow how urban, rich and educated a place is. Comparing only places with similar density, income and education, a weak link of -0.20 remains. Life expectancy by US county | -0.61 | -0.20 |
| Obesity and Returns claiming the earned income creditLinked across counties, but mostly as both follow how urban, rich and educated a place is. Comparing only places with similar density, income and education, a weak link of +0.18 remains. Returns claiming the earned income credit by US county | +0.58 | +0.18 |
| Obesity and Premature mortalityLinked across counties, but mostly as both follow how urban, rich and educated a place is. Comparing only places with similar density, income and education, a weak link of +0.17 remains. Premature mortality by US county | +0.58 | +0.17 |
| Obesity and Years of potential life lostLinked across counties, but mostly as both follow how urban, rich and educated a place is. Comparing only places with similar density, income and education, a weak link of +0.15 remains. Years of potential life lost by US county | +0.54 | +0.15 |
Population makeup
How this measure varies with the racial and ethnic makeup of counties. Every group is shown, whatever its rank. These are links across counties: they describe places, not people. They say nothing about any person’s risk or behaviour based on their race. Counties 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 |
|---|---|---|
| Obesity and Share White, not HispanicNot an independent finding: one is modelled from the other. It is an estimate from a statistical model that uses the other as an input, so part of the match is built in. Share White, not Hispanic by US county | -0.13 | -0.09 |
| Obesity and Share Black, not HispanicNot an independent finding: one is modelled from the other. It is an estimate from a statistical model that uses the other as an input, so part of the match is built in. Share Black, not Hispanic by US county | +0.43 | +0.34 |
| Obesity and Share Hispanic or Latino, any raceNot an independent finding: one is modelled from the other. It is an estimate from a statistical model that uses the other as an input, so part of the match is built in. Share Hispanic or Latino, any race by US county | -0.12 | -0.15 |
| Obesity and Share Asian, not HispanicNot an independent finding: one is modelled from the other. It is an estimate from a statistical model that uses the other as an input, so part of the match is built in. Share Asian, not Hispanic by US county | -0.44 | -0.17 |
| Obesity and Share American Indian or Alaska Native, not HispanicNot an independent finding: one is modelled from the other. It is an estimate from a statistical model that uses the other as an input, so part of the match is built in. Share American Indian or Alaska Native, not Hispanic by US county | +0.21 | +0.15 |
Highest and lowest
Of 2,956 counties 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
- Perry County, AL — 54%
- Greene County, AL — 53.4%
- Humphreys County, MS — 53%
- Wilcox County, AL — 51.9%
- Jefferson County, MS — 51.7%
Lowest
- San Francisco County, CA — 17.1%
- Boulder County, CO — 17.4%
- Summit County, UT — 19.3%
- New York County, NY — 19.5%
- Pitkin County, CO — 20.3%
The middle area reports 38.2%. The middle half of counties falls between 35.1% and 40.6% (the 25th to 75th percentile).
All measures · Explore its pairs · How the US county data works