placestats

Population for whom poverty status is determined

The people whose poverty status can be worked out, used as the base for the poverty rate. It leaves out people in institutions, military barracks and college dorms, so it is a little smaller than the population.

Reported for3,220areas, in 52 states
Link to density0.85mostly 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 ACS 5-year · ACS table B17001_001

Combining areas: added up across areas.

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 50 pairs built from the same numbers or the same model as this measure, since they are bound to match.

MeasureUnadjustedAdjusted
Population for whom poverty status is determined and Share foreign-bornWhere Population for whom poverty status is determined is higher, Share foreign-born 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. Share foreign-born by US county+0.49+0.39
Population for whom poverty status is determined and Share Asian, not HispanicWhere Population for whom poverty status is determined is higher, Share Asian, not Hispanic 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. Share Asian, not Hispanic by US county+0.46+0.30

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 residentsUnadjustedAdjusted
Population for whom poverty status is determined and Share White, not HispanicWhere Population for whom poverty status is determined is higher, Share White, not Hispanic tends to be lower: a weak link that holds when only places with similar density, income and education are compared, and inside states as well. Share White, not Hispanic by US county-0.25-0.22
Population for whom poverty status is determined and Share Black, not HispanicCould easily be chance once only places with similar density, income and education are compared. Share Black, not Hispanic by US county+0.03+0.04
Population for whom poverty status is determined and Share Hispanic or Latino, any raceWhere Population for whom poverty status is determined is higher, Share Hispanic or Latino, any race 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. Share Hispanic or Latino, any race by US county+0.12+0.11
Population for whom poverty status is determined and Share Asian, not HispanicWhere Population for whom poverty status is determined is higher, Share Asian, not Hispanic 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. Share Asian, not Hispanic by US county+0.46+0.30
Population for whom poverty status is determined and Share American Indian or Alaska Native, not HispanicCould easily be chance once only places with similar density, income and education are compared. Share American Indian or Alaska Native, not Hispanic by US county-0.10+0.08

Highest and lowest, per 1,000 residents

Of 3,220 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 0.85, so the raw order would match almost every other count here. The published totals are in the table on each place page.

Highest

  1. San Juan County, CO — 1000.00 (690 total)
  2. Mineral County, CO — 1000.00 (799 total)
  3. Hinsdale County, CO — 1000.00 (939 total)
  4. Dolores County, CO — 1000.00 (2,385 total)
  5. Alpine County, CA — 1000.00 (1,695 total)

Lowest

  1. Chattahoochee County, GA — 520.10 (4,775 total)
  2. Lexington city, VA — 562.53 (4,174 total)
  3. Forest County, PA — 647.90 (4,396 total)
  4. Lincoln County, AR — 659.42 (8,550 total)
  5. Lake County, TN — 671.65 (4,494 total)

The middle area reports 980.26. The middle half of counties falls between 964.23 and 987.65 (the 25th to 75th percentile).

All measures · Explore its pairs · How the US county data works