Poverty vs Food Access: County Correlation

It is natural to assume the places with the worst food access are the poorest. According to the USDA Economic Research Service Food Access Research Atlas (2019) and the U.S. Census Bureau American Community Survey (2024), measured across all 3,128 U.S. counties that report both figures, the data says otherwise: see the methodology for how each value is computed.

Compiled by Plainfoodaccess, Food Access Editorial Process

-0.08

Pearson r: poverty vs low food access

effectively no linear relationship

0.772

Pearson r: poverty vs SNAP participation

a very strong relationship

What the numbers mean

A Pearson correlation runs from -1 (perfect inverse) through 0 (no linear relationship) to +1 (perfect direct). At r = -0.08, county poverty and low food access are effectively no linear relationship: knowing a county's poverty rate tells you almost nothing about whether its residents live far from a supermarket. The same poverty rate, by contrast, tracks SNAP participation closely (r = 0.772) because SNAP enrollment is driven directly by income.

Why food access is a distance story

Low access is a function of geography: how far the nearest supermarket is. Sparsely populated rural counties can have high low-access shares at modest poverty levels simply because stores are far apart, while dense urban counties can have high poverty yet short trips to a grocer. That is why anti-hunger policy and food-access policy are not the same lever: SNAP follows income, but closing a food desert means changing the distance to food.

How this was computed

Both coefficients are Pearson product-moment correlations computed at request time over the 3,128 counties that have all three measures, joining the USDA Food Access Research Atlas low-access share to the Census ACS poverty rate and SNAP participation rate. No figure on this page is hand-entered; each recomputes from the underlying rows. See the methodology and the per-state breakdown on the food access statistics page.