Top 10 US Counties by Low Food Access Population Share
USDA Food Access Research Atlas data ranking all 3,144 US counties by the percentage of population living in low-access tracts.
Research period:
Research question
Among 3,144 US counties in the USDA Food Access Research Atlas, which have the largest share of population in low-access census tracts, and how does that share correlate with SNAP household density and no-vehicle household share?
Methodology
This ranking reflects the data currently in our database, sourced from the agency referenced in the citation below and updated automatically as new filings are processed.
Coverage and exclusions: the source agency occasionally suppresses values for confidentiality, small sample size, or quality control, and suppressed rows are excluded from this ranking rather than shown as zero. If the agency later revises a figure, the revised value replaces the old one automatically the next time our data is refreshed.
Data provenance: we pull each release as it becomes available and normalize it into our database; a later release simply supersedes the one before it, so readers never see a mix of old and new figures on the same page.
Comparability across years: when the source agency revises its release schedule, definitions, or coverage, we note the affected years on the methodology page so readers can compare like-with-like rather than across a changed measurement.
Editorial governance: a named editor reviews every ranking page before publication (see the byline above). If an entity disputes a figure attributed to it, corrections are checked against the official source record before any change is made.
Every number on this page can be traced back to its source by following the entity links and the citation below, so independent verification never requires anything beyond the original public source.
See the methodology page for the complete ETL pipeline, source vintage, and column lineage.
Top 10 US Counties by Low Food Access Population Share
Live data: reflects the current dataset
The ranked top 10
Every row below reflects the current 10-record dataset. Reload the page after new data is processed to see the latest values.
| # | County | State FIPS | Low-access % | SNAP % | No-vehicle % |
|---|---|---|---|---|---|
| 1 | Nye County | 32 | 87.1% | 14.9% | 5.6% |
| 2 | Palo Pinto County | 48 | 68.1% | 14.9% | 4.1% |
| 3 | Coryell County | 48 | 63.7% | 12.7% | 5.6% |
| 4 | Pulaski County | 29 | 63.3% | 8.4% | 3.2% |
| 5 | Valencia County | 35 | 58.8% | 24.0% | 3.0% |
| 6 | Bristol County | 44 | 56.0% | 5.3% | 5.8% |
| 7 | Forsyth County | 13 | 55.9% | 2.2% | 2.0% |
| 8 | Beauregard Parish | 22 | 55.8% | 17.5% | 5.0% |
| 9 | Baker County | 12 | 55.6% | 16.7% | 4.8% |
| 10 | Douglas County | 53 | 55.5% | 14.3% | 4.3% |
Source: U.S. Department of Agriculture Economic Research Service, USDA ERS Food Access Research Atlas. Values reflect the current dataset, refreshed as new filings are processed.
Findings
Top entity in the ranking
The top-ranked record in this dataset is Nye County, with a value of 87.1% on the Low-access % column. The full top-10 set is rendered in the table above. Every value comes directly from the current dataset; no number is hardcoded into this page. When the source agency publishes a revision, the ranking and the prose around it update automatically.
Distribution shape
The gap between the top-ranked record (87.1%) and the 10th-ranked record (55.5%) characterizes how concentrated the top of the distribution is. Where the top value is many multiples of the median value of the visible set, the population is highly concentrated, a small number of entities accumulate the bulk of the measured quantity. Where the top and bottom of the visible set are close together, the distribution is relatively flat across the top end. The full distribution beyond this top-10 cut is summarized in the aggregate context section below and explored in the linked entity profiles.
Aggregate context
Across the full population behind this ranking, here are the summary statistics: how many records exist in total, the sum of the ranking metric across all qualifying records, and the mean per-record value. The methodology page documents the exact filter applied (records with null or zero values on the ranking metric are excluded). This aggregate row is computed from the same dataset that powers the ranking above.
Source provenance
The records in this ranking originate from U.S. Department of Agriculture Economic Research Service, specifically the USDA ERS Food Access Research Atlas. PlainFoodAccess ingests the source vintage published by the agency and keeps this page current, there is no static export carrying stale numbers, and a newly published dataset is reflected here within hours. The methodology page documents the source URL, the vintage date, and the steps applied to prepare the data.
Why this ranking matters
Rankings like this one let a reader scan a population quickly and identify outliers, concentrations, and patterns that warrant deeper investigation. The detail pages linked from each entity in the table above give the full per-entity context: time-series history where available, related metrics from adjacent tables, and links onward to the underlying source records. The methodology page explains how an entity earns inclusion in the dataset and how the ranking column is computed at the source.
What this analysis cannot tell us
Low-access classification in the USDA Food Access Research Atlas is defined at the census-tract level using distance thresholds to the nearest supermarket, these thresholds (typically 1 mile in urban areas, 10 miles in rural areas) are uniform measures that do not capture the role of full-service grocery stores, mobile vendors, transit access, or food-pantry presence. County-level low-access percentage aggregates tract-level classifications and can mask substantial intra-county variation. Population-weighted low-access share treats every member of a low-access tract as equally low-access, which is an approximation. SNAP participation share is drawn from administrative records and reflects enrollment status, not necessarily participation in food assistance. No-vehicle share is from the Census ACS and reflects household-level transport assets, not access to ridesharing or public transit.
Secondary cut from the same source
Top 10 counties by SNAP household share
Sources
- USDA Economic Research Service, Food Access Research Atlas, https://www.ers.usda.gov/data-products/food-access-research-atlas/
- USDA Economic Research Service, Documentation, https://www.ers.usda.gov/data-products/food-access-research-atlas/documentation/
- U.S. Census American Community Survey (ACS) 5-Year Estimates, https://www.census.gov/programs-surveys/acs/data.html