Population for whom poverty status is determined
The people whose poverty status is worked out, used as the base for the poverty rate. It is calculated back from the poverty count and the poverty rate.
Reported for3,143areas, in 51 states — none in PR
Link to density0.87mostly reflects how urban a place is
Nearby places alike0.32Moran’s I: strongly, neighbouring places tend to be similar
Typecountcounts rise and fall together from size alone
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
Census SAIPE · Census SAIPE, derived from the count and rate
Worked out as the number of people in poverty divided by the poverty rate.
Combining areas: added up across areas.
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 |
|---|---|---|
| Population for whom poverty status is determined 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 | -0.26 | -0.24 |
| Population for whom poverty status is determined 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 | +0.02 | +0.02 |
| Population for whom poverty status is determined 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 | +0.20 | +0.24 |
| Population for whom poverty status is determined 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 | +0.45 | +0.30 |
| Population for whom poverty status is determined 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 | -0.10 | +0.08 |
Highest and lowest, per 1,000 residents
Of 3,141 counties reporting it. This is a count, so it is ranked per 1,000 residents, not as published. Ranked by raw totals, it would just list the largest counties in the country. Its link to population is 0.87, so the raw order would match almost every other count here. The published totals are in the table on each place page.
Highest
- Petroleum County, MT — 1381.17 (554 total)
- Yakutat City and Borough, AK — 1356.26 (686 total)
- Daggett County, UT — 1321.07 (987 total)
- Lake and Peninsula Borough, AK — 1319.17 (1,328 total)
- Garfield County, MT — 1274.31 (1,195 total)
Lowest
- Crowley County, CO — 525.06 (3,011 total)
- Forest County, PA — 590.13 (4,004 total)
- West Feliciana Parish, LA — 647.82 (9,964 total)
- Lexington city, VA — 649.30 (4,818 total)
- Wheeler County, GA — 668.51 (4,970 total)
The middle area reports 979.37. The middle half of counties falls between 957.67 and 998.29 (the 25th to 75th percentile).
All measures · Explore its pairs · How the US county data works