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PantryPath Research · WIC Coverage Atlas

WIC in Missouri

53.0% coverage

Missouri's WIC program reaches 53.0% of eligible residents — an estimated 87,000 participants out of 164,000 who qualify. That leaves 77,000 pregnant women, infants, and young children eligible but not receiving WIC's food package or nutrition counseling.

164K

WIC eligibles

87K

Participants (FY2024 avg)

77K

Unserved eligibles

115

Counties

Missouri by county

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Toggle between estimated WIC eligibles, unserved gap, low-income child counts, and child-poverty share. Hover a county for its exact value.

Note: USDA does not publish sub-state WIC participation, so every county in Missouri inherits the state's 53.0% coverage rate. County-level eligibles are allocated from state totals in proportion to the county's share of low-income children under 6 (ACS B17024). See methodology.

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Missouri at a glance

Coverage rate

53.0%

Participants ÷ eligibles

Participation gap

46.9%

1 − coverage

Eligibles

164K

USDA FNS FY2022

Participants

87K

Monthly avg FY2024

Unserved

77K

Eligibles − participants

Kids < 6 low-income

160K

37.4% of universe

County-level hotspots

Top five counties across 115 counties in Missouri.

Most WIC eligibles

Estimated eligible population

  1. 1 Jackson 24K
  2. 2 St. Louis 20K
  3. 3 St. Louis 9K
  4. 4 Greene 9K
  5. 5 Clay 6K

Largest unserved gap

Eligibles not receiving WIC

  1. 1 Jackson 11K
  2. 2 St. Louis 9K
  3. 3 St. Louis 4K
  4. 4 Greene 4K
  5. 5 Clay 3K

Highest child-poverty share

Children < 6 at ≤185% FPL

  1. 1 Oregon 85.3%
  2. 2 Wayne 77.1%
  3. 3 Pemiscot 75.8%
  4. 4 Hickory 75.4%
  5. 5 Reynolds 69.1%

Every county in Missouri

All 115 counties with WIC eligibility estimates, unserved gap, and ACS child-poverty context.

County Eligibles est. Participants est. Unserved est. Kids < 6 low-income Poverty share
Adair 687 365 322 669 40.1%
Andrew 380 202 178 370 30.8%
Atchison 156 83 73 152 55.7%
Audrain 1,161 616 545 1,130 63.7%
Barry 1,308 694 614 1,273 53.1%
Barton 457 243 214 445 52.8%
Bates 500 265 235 487 43.9%
Benton 560 297 263 545 56.1%
Bollinger 260 138 122 253 42.1%
Boone 3,884 2,061 1,823 3,781 31.8%
Buchanan 3,179 1,687 1,492 3,095 53.8%
Butler 1,999 1,061 938 1,946 63.4%
Caldwell 151 80 71 147 27.5%
Callaway 929 493 436 904 32.0%
Camden 1,033 548 485 1,006 40.8%
Cape Girardeau 2,056 1,090 966 2,001 39.3%
Carroll 255 135 120 248 50.2%
Carter 231 123 108 225 65.6%
Cass 2,507 1,330 1,177 2,440 33.1%
Cedar 662 351 311 644 57.5%
Chariton 314 167 147 306 57.2%
Christian 2,110 1,119 991 2,054 31.1%
Clark 214 113 101 208 41.5%
Clay 5,864 3,111 2,753 5,708 30.9%
Clinton 456 242 214 444 31.3%
Cole 1,377 730 647 1,340 26.0%
Cooper 403 214 189 392 29.5%
Crawford 550 292 258 535 34.9%
Dade 321 170 151 312 64.9%
Dallas 852 452 400 829 61.2%
Daviess 377 200 177 367 55.9%
DeKalb 176 93 83 171 27.8%
Dent 570 302 268 555 57.6%
Douglas 399 211 188 388 45.1%
Dunklin 1,087 577 510 1,058 51.0%
Franklin 2,156 1,144 1,012 2,099 29.1%
Gasconade 443 235 208 431 50.3%
Gentry 215 114 101 209 40.1%
Greene 8,818 4,678 4,140 8,584 43.3%
Grundy 305 162 143 297 36.5%
Harrison 328 174 154 319 49.1%
Henry 645 342 303 628 40.9%
Hickory 314 167 147 306 75.4%
Holt 155 82 73 151 61.4%
Howard 284 150 134 276 38.8%
Howell 1,173 622 551 1,142 41.4%
Iron 311 165 146 303 53.4%
Jackson 23,584 12,511 11,073 22,957 42.5%
Jasper 4,662 2,473 2,189 4,538 47.8%
Jefferson 4,576 2,427 2,149 4,454 28.9%
Johnson 1,528 810 718 1,487 39.4%
Knox 112 59 53 109 31.2%
Laclede 1,521 807 714 1,481 53.5%
Lafayette 952 505 447 927 44.0%
Lawrence 1,509 801 708 1,469 50.7%
Lewis 202 107 95 197 34.8%
Lincoln 1,310 695 615 1,275 25.2%
Linn 475 252 223 462 60.6%
Livingston 360 191 169 350 38.2%
Macon 409 217 192 398 39.5%
Madison 403 214 189 392 47.5%
Maries 209 111 98 203 39.0%
Marion 938 498 440 913 39.3%
McDonald 1,032 548 484 1,005 57.1%
Mercer 137 72 65 133 47.7%
Miller 634 336 298 617 33.8%
Mississippi 501 266 235 488 68.4%
Moniteau 419 222 197 408 36.8%
Monroe 325 172 153 316 54.6%
Montgomery 343 182 161 334 40.1%
Morgan 833 442 391 811 46.8%
New Madrid 677 359 318 659 55.3%
Newton 1,905 1,010 895 1,854 42.5%
Nodaway 498 264 234 485 40.6%
Oregon 513 272 241 499 85.3%
Osage 181 96 85 176 22.1%
Ozark 195 104 91 190 48.2%
Pemiscot 978 519 459 952 75.8%
Perry 427 227 200 416 33.6%
Pettis 1,683 893 790 1,638 44.3%
Phelps 1,297 688 609 1,263 44.2%
Pike 563 299 264 548 41.4%
Platte 1,725 915 810 1,679 22.4%
Polk 1,274 676 598 1,240 52.1%
Pulaski 1,784 947 837 1,737 44.1%
Putnam 186 99 87 181 51.1%
Ralls 260 138 122 253 38.3%
Randolph 792 420 372 771 48.7%
Ray 646 343 303 629 40.2%
Reynolds 214 113 101 208 69.1%
Ripley 318 169 149 310 41.9%
Saline 599 318 281 583 37.8%
Schuyler 110 58 52 107 26.0%
Scotland 196 104 92 191 40.5%
Scott 1,414 750 664 1,376 46.9%
Shannon 222 118 104 216 49.7%
Shelby 191 101 90 186 45.1%
St. Charles 3,976 2,109 1,867 3,870 14.0%
St. Clair 352 187 165 343 59.5%
St. Francois 1,969 1,045 924 1,917 46.2%
St. Louis 19,694 10,448 9,246 19,171 28.5%
St. Louis 9,342 4,956 4,386 9,094 45.2%
Ste. Genevieve 180 95 85 175 13.4%
Stoddard 1,130 599 531 1,100 52.6%
Stone 883 469 414 860 58.7%
Sullivan 156 83 73 152 39.2%
Taney 1,378 731 647 1,341 38.1%
Texas 886 470 416 862 52.9%
Vernon 750 398 352 730 54.4%
Warren 1,101 584 517 1,072 49.3%
Washington 916 486 430 892 53.7%
Wayne 447 237 210 435 77.1%
Webster 1,662 882 780 1,618 49.4%
Worth 66 35 31 64 53.8%
Wright 722 383 339 703 53.0%

Apply for WIC in Missouri

Income limits, food-package rules, clinic locator, and application instructions specific to Missouri's WIC agency.

Missouri WIC guide

Families with children

Our population-specific guide: WIC, SNAP, school meals, Summer EBT, and pantry programs for families with kids in Missouri.

Families guide

Missouri SNAP

SNAP recipients are automatically income-eligible for WIC through adjunctive eligibility — often the fastest path to enrollment.

Missouri SNAP guide

Find a food pantry

Search Missouri's verified pantries — many partner with WIC clinics and distribute infant formula, baby food, and diapers.

Missouri food pantries

WIC methodology

How we estimated county-level eligibles, why state coverage rates can't be disaggregated, and which data sources we used.

Full methodology