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PantryPath Research · School Hunger Atlas

School hunger in Kentucky

59% certified free/reduced

Across 1,204 public schools serving 640,741 students, 58.6% of Kentucky students are certified free or reduced-price. 1,090 schools (91% of NSLP participants) operate under the Community Eligibility Provision, and 52.7% of students are directly certified through SNAP, TANF, or Medicaid linkage.

641K

Students enrolled

1,204

Public schools (CCD)

1,090

CEP / Provision 2 schools

120

Counties in atlas

Kentucky by county

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Toggle between the school-food-access composite, free/reduced eligibility, CEP share, direct-certification rate, and SAIPE school-age poverty. Hover a county to see schools, enrollment, and the underlying certification mix.

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Lower
Higher

Kentucky at a glance

Free/reduced

58.6%

Share of enrollment

CEP share

91%

Of NSLP schools

Direct cert

52.7%

SNAP/TANF/Medicaid

NSLP schools

99%

Serve NSLP meals

5–17 in poverty

19.1%

Census SAIPE 2023

Access score

0.77

Composite 0–1

The access score is a 0–1 composite weighted 50% eligibility, 30% CEP share, 20% NSLP share — a visualization and ranking aid, not a direct measurement. See methodology.

County-level hotspots

Top five counties across 120 in Kentucky.

Highest free/reduced share

Certified ≤185% FPL per enrollment

  1. 1 Owsley 84.5%
  2. 2 McCreary 82.5%
  3. 3 Harlan 81.9%
  4. 4 Bell 81.1%
  5. 5 Wayne 79.6%

Highest CEP adoption

Of NSLP schools — min. 3 NSLP schools

  1. 1 Adair 100%
  2. 2 Allen 100%
  3. 3 Anderson 100%
  4. 4 Ballard 100%
  5. 5 Barren 100%

Largest enrollment

Total students in CCD universe

  1. 1 Jefferson 90K
  2. 2 Fayette 40K
  3. 3 Kenton 22K
  4. 4 Warren 22K
  5. 5 Boone 22K

Every county in Kentucky

All 120 counties with school counts, enrollment, certification mix, CEP adoption, and the SAIPE 5–17 poverty backdrop.

County Schools Enrollment Free/reduced CEP Direct cert 5–17 poverty Access
Adair 4 2,583 66.6% 100% 65.0% 27.7% 0.83
Allen 4 3,001 64.8% 100% 57.3% 21.8% 0.82
Anderson 6 3,751 49.6% 100% 44.7% 11.5% 0.75
Ballard 4 1,039 60.9% 100% 52.4% 21.3% 0.80
Barren 15 7,777 59.1% 100% 54.3% 20.9% 0.80
Bath 4 1,912 74.8% 100% 64.6% 26.6% 0.87
Bell 11 4,107 81.1% 100% 73.7% 38.2% 0.91
Boone 29 22,025 40.7% 38% 33.8% 7.5% 0.52
Bourbon 10 3,421 64.7% 100% 58.2% 18.2% 0.82
Boyd 17 6,740 62.5% 100% 57.4% 21.0% 0.81
Boyle 9 4,675 56.1% 67% 50.6% 17.1% 0.68
Bracken 4 1,470 59.3% 100% 52.1% 17.5% 0.80
Breathitt 4 1,648 71.4% 100% 68.6% 38.4% 0.86
Breckinridge 7 2,964 56.2% 100% 51.6% 22.0% 0.78
Bullitt 22 12,902 49.1% 59% 42.4% 10.5% 0.62
Butler 4 2,149 64.6% 100% 58.8% 19.5% 0.82
Caldwell 4 1,905 50.0% 100% 45.4% 22.5% 0.75
Calloway 10 4,894 57.3% 70% 46.8% 18.2% 0.70
Campbell 20 11,305 41.6% 80% 35.0% 12.3% 0.60
Carlisle 3 738 60.0% 100% 55.6% 18.9% 0.80
Carroll 5 1,963 63.3% 100% 63.3% 21.9% 0.82
Carter 10 4,036 65.4% 100% 62.7% 23.3% 0.83
Casey 5 2,183 68.2% 100% 61.8% 26.1% 0.84
Christian 14 7,983 71.0% 100% 62.2% 21.8% 0.85
Clark 8 5,348 62.5% 100% 57.1% 16.0% 0.81
Clay 9 2,872 76.8% 100% 74.0% 56.1% 0.88
Clinton 4 1,515 77.7% 100% 70.6% 33.8% 0.89
Crittenden 3 1,362 56.9% 100% 54.3% 25.6% 0.78
Cumberland 3 1,018 78.2% 100% 68.1% 33.0% 0.89
Daviess 26 15,563 61.9% 81% 51.4% 17.7% 0.75
Edmonson 5 1,856 61.6% 100% 54.5% 22.8% 0.81
Elliott 4 911 71.8% 100% 66.6% 26.2% 0.86
Estill 5 2,150 68.2% 100% 63.7% 25.0% 0.84
Fayette 62 39,582 50.8% 68% 45.7% 17.2% 0.66
Fleming 5 2,209 59.0% 100% 56.1% 22.4% 0.80
Floyd 13 5,288 78.6% 92% 72.9% 28.1% 0.87
Franklin 14 7,012 57.3% 100% 51.3% 14.9% 0.79
Fulton 4 906 78.5% 100% 73.1% 33.0% 0.89
Gallatin 4 1,482 61.4% 100% 5.1% 17.6% 0.81
Garrard 5 2,487 62.3% 100% 58.1% 25.3% 0.81
Grant 10 4,199 67.8% 100% 57.7% 17.8% 0.84
Graves 11 5,844 62.8% 100% 59.0% 20.3% 0.81
Grayson 7 4,013 64.8% 86% 58.2% 23.7% 0.78
Green 4 1,653 63.5% 100% 57.1% 22.0% 0.82
Greenup 14 5,688 56.7% 71% 50.4% 16.9% 0.70
Hancock 4 1,467 54.4% 0% 46.3% 12.8% 0.47
Hardin 27 16,727 51.0% 96% 45.1% 16.4% 0.74
Harlan 12 4,267 81.9% 100% 78.6% 31.5% 0.91
Harrison 6 2,922 58.5% 100% 53.0% 17.1% 0.79
Hart 8 2,698 68.7% 100% 64.0% 22.2% 0.84
Henderson 12 6,593 55.6% 100% 53.8% 17.6% 0.78
Henry 8 2,996 65.6% 100% 47.0% 18.1% 0.83
Hickman 2 717 60.8% 100% 55.5% 26.3% 0.80
Hopkins 14 6,820 60.8% 100% 57.8% 19.4% 0.80
Jackson 5 2,001 72.3% 100% 67.0% 29.1% 0.86
Jefferson 137 90,046 58.5% 97% 55.0% 19.7% 0.78
Jessamine 11 8,241 54.7% 100% 51.4% 13.0% 0.77
Johnson 9 3,929 60.7% 100% 55.5% 26.8% 0.80
Kenton 36 22,116 53.3% 71% 45.4% 14.1% 0.67
Knott 7 2,072 75.0% 100% 73.4% 30.6% 0.88
Knox 13 5,181 75.6% 100% 72.0% 38.0% 0.88
Larue 5 2,381 55.2% 100% 49.6% 22.0% 0.78
Laurel 17 9,118 69.2% 94% 62.0% 27.1% 0.83
Lawrence 6 2,360 65.2% 100% 62.6% 22.2% 0.83
Lee 2 902 63.5% 100% 0.7% 36.1% 0.82
Leslie 5 1,649 68.7% 100% 64.3% 29.5% 0.84
Letcher 9 2,945 72.3% 100% 68.5% 27.8% 0.86
Lewis 6 1,981 74.2% 100% 50.4% 30.5% 0.87
Lincoln 7 3,305 71.0% 100% 64.4% 22.9% 0.86
Livingston 4 1,049 61.1% 100% 58.3% 22.6% 0.81
Logan 9 4,363 59.3% 100% 52.5% 18.1% 0.80
Lyon 3 973 47.1% 100% 43.0% 16.1% 0.74
Madison 21 12,225 56.8% 100% 51.2% 14.8% 0.78
Magoffin 5 1,946 72.7% 100% 69.4% 33.2% 0.86
Marion 7 3,000 60.1% 100% 54.8% 17.1% 0.80
Marshall 9 4,276 59.5% 100% 51.7% 15.6% 0.80
Martin 5 1,718 67.1% 100% 66.3% 56.4% 0.84
Mason 4 2,616 64.5% 100% 59.0% 20.0% 0.82
McCracken 17 9,844 59.1% 100% 52.8% 21.0% 0.80
McCreary 4 2,241 82.5% 100% 76.7% 39.2% 0.91
McLean 5 1,386 57.1% 100% 52.7% 16.1% 0.79
Meade 8 4,893 48.4% 100% 42.2% 13.0% 0.74
Menifee 2 922 74.8% 100% 71.2% 35.2% 0.87
Mercer 5 3,172 60.7% 100% 53.3% 16.4% 0.80
Metcalfe 3 1,460 73.7% 100% 67.3% 35.7% 0.87
Monroe 5 1,823 70.3% 100% 61.1% 27.4% 0.85
Montgomery 6 4,435 60.7% 100% 56.9% 17.5% 0.80
Morgan 6 1,723 72.0% 100% 64.5% 27.2% 0.86
Muhlenberg 8 4,295 62.2% 100% 58.6% 26.0% 0.81
Nelson 15 7,018 52.3% 100% 45.0% 15.3% 0.76
Nicholas 2 1,091 65.5% 100% 65.3% 24.2% 0.83
Ohio 8 3,834 66.0% 100% 60.3% 19.2% 0.83
Oldham 17 12,080 22.9% 29% 18.9% 4.7% 0.40
Owen 3 1,687 58.9% 100% 52.8% 18.7% 0.79
Owsley 2 742 84.5% 100% 71.6% 44.2% 0.92
Pendleton 4 2,201 60.5% 100% 55.1% 17.2% 0.80
Perry 10 4,478 71.1% 100% 67.0% 32.8% 0.86
Pike 20 8,824 67.5% 90% 57.5% 25.1% 0.81
Powell 5 2,049 71.4% 100% 67.4% 27.8% 0.86
Pulaski 17 9,990 68.7% 100% 60.5% 21.7% 0.84
Robertson 1 459 75.4% 100% 68.2% 24.9% 0.88
Rockcastle 5 2,746 63.6% 100% 61.0% 25.6% 0.82
Rowan 7 3,369 66.7% 100% 61.3% 22.3% 0.83
Russell 5 3,064 72.6% 100% 65.8% 23.9% 0.86
Scott 15 9,787 43.4% 100% 40.3% 11.3% 0.72
Shelby 13 6,932 48.1% 92% 43.6% 12.9% 0.72
Simpson 5 2,984 68.8% 100% 50.5% 17.2% 0.84
Spencer 5 3,281 38.8% 0% 32.0% 7.7% 0.39
Taylor 7 3,988 63.6% 100% 58.8% 22.5% 0.82
Todd 4 1,856 61.1% 100% 53.1% 22.6% 0.81
Trigg 4 1,953 62.8% 100% 54.4% 18.8% 0.81
Trimble 3 1,248 55.8% 100% 50.6% 16.4% 0.78
Union 6 2,033 62.1% 100% 56.1% 19.1% 0.81
Warren 30 22,115 60.3% 100% 52.8% 14.6% 0.80
Washington 4 1,741 59.2% 100% 52.8% 15.5% 0.80
Wayne 5 3,021 79.6% 100% 73.7% 37.0% 0.90
Webster 6 2,173 63.7% 100% 60.3% 19.2% 0.82
Whitley 16 7,034 71.8% 100% 66.1% 27.9% 0.86
Wolfe 5 1,054 75.7% 100% 71.5% 38.4% 0.88
Woodford 6 3,986 39.2% 100% 38.1% 11.6% 0.70

Kentucky school meals guide

How free and reduced-price school lunch eligibility works, application steps, and what to do if your child's school is not in CEP.

School meals guide

Summer meals

When the school year ends, NSLP and CEP stop. The Summer Food Service Program and Summer EBT fill the gap for the 375,449 children who rely on school meals in Kentucky.

Summer meals guide

Families with children

SNAP, WIC, Head Start, and the full federal-program stack for households with kids — the assistance ecosystem around the school cafeteria.

Families guide

Kentucky child poverty

The sibling atlas — county-level child poverty across Kentucky. Free/reduced eligibility and child poverty track each other closely but not perfectly.

Kentucky child poverty atlas

Kentucky pantries

Verified food pantries, food banks, and meal programs across Kentucky — open weeknights, weekends, and through the summer gap.

Kentucky pantry directory

Methodology

How we aggregated NCES Common Core of Data school-level records to counties, proxied CEP from lunch_program == 2, and layered SAIPE school-age poverty — plus the access-score formula.

Full methodology