Browse Food Access Data

What is on PlainFoodAccess

PlainFoodAccess publishes county-level food access indicators for every U.S. state. Each state has a state-summary page and a list of every county the USDA Economic Research Service Food Access Research Atlas tracks inside that state. Each county has its own detail page with the underlying tract counts, low-access shares, SNAP participation, no-vehicle households, poverty rate, and the Census ACS population denominator that anchors every other figure. The state and county pages are computed from the same SQLite table, so a number cited on a county page will match the number rolled up to that county's state page.

Food desert classification is a USDA framework. A census tract counts as low-access when residents must travel more than one mile to the nearest supermarket in urban areas, or more than ten miles in rural areas. A tract becomes a food desert only when low-access overlaps with low-income status, as defined by the Census Bureau American Community Survey 5-Year Estimates. Distance and income together are what convert "inconvenient to grocery shop" into a measurable public-health and policy concern. PlainFoodAccess surfaces both components separately and as a combined indicator, so a reader can see whether a county's headline figure is driven by sparse rural geography, urban-tract poverty, transit gaps, or all three at once.

Rankings on PlainFoodAccess are computed live from the same SQLite table. The worst-food-deserts ranking sorts every county by the low-access share, top to bottom, and shows the first 100. The most-SNAP ranking sorts by SNAP participation. Because the rankings query the live database rather than a cached list, a county's rank reproduces row-for-row when the underlying file is read directly from USDA or the Census Bureau. The methodology page documents the joins and the population-weighted aggregation used to roll tract values up to county and state.

For researchers and journalists who need to cite a specific figure, every page on PlainFoodAccess links to the upstream URL for the data it shows: the USDA Food Access Research Atlas tract file for low-access indicators, the Census ACS B22001 table for SNAP, the Census ACS B25044 table for no-vehicle households, and the standard ACS poverty rate. The data citation block at the bottom of each detail page lists those URLs explicitly. PlainFoodAccess does not republish raw tract data; it aggregates and contextualizes the public files so the resulting county and state figures are easier to compare across geographies than the raw USDA delivery format allows.

The state list below is the canonical entry point. Each row links to a state page that aggregates every county the USDA Atlas tracks in that state and shows the population-weighted average low-access share, SNAP participation, and county count. From any state page, a reader can drill into individual counties to see the underlying tract counts, the income and poverty context, and the no-vehicle household share that converts measured distance into a real food access barrier. Rankings provide an orthogonal entry point: the worst-food-deserts ranking sorts every county nationally by the low-access share, and the most-SNAP ranking does the same for SNAP participation. Both are useful for cross-state comparisons that the state-by-state browse cannot easily surface.

The guides section translates the underlying federal definitions into plain language. The USDA classification framework is precise but technical, and the Census ACS table structure is unfamiliar to readers who have not worked with American Community Survey data before. The guides describe what a food desert is in the USDA sense, why distance and income are combined to produce the official designation, how SNAP and WIC overlap with the food access conversation, and how to read a county-level no-vehicle figure as a transit and walkability proxy rather than an absolute car-ownership statistic. Reading one or two guides before browsing the state and county pages tends to make the indicators easier to interpret, because the same vocabulary that appears in the federal source files is used consistently across every page on PlainFoodAccess.