DRUG SCIENCE

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Indiana Marijuana Possession Arrest Rates by County and Age Groups Under 30 (2006)

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Age 10 to 14
Age 15 to 19
Age 20 to 24
Age 25 to 29
County
Arrests
Rate
Pct.
Arrests
Rate
Pct.
Arrests
Rate
Pct.
Arrests
Rate
Pct.
Adams 1 88 8% 4 372 33% 4 441 33% 1 109 8%
Allen 10 40 1% 138 583 20% 208 952 31% 125 571 18%
Bartholomew 9 168 2% 108 2,266 29% 106 2,650 29% 47 1,010 13%
Blackford 0 0 0% 10 1,178 31% 10 1,397 31% 7 736 22%
Brown 0 0 0% 9 928 43% 3 335 14% 3 317 14%
Carroll 0 0 0% 3 1,528 25% 7 3,965 58% 1 498 8%
Cass 0 0 0% 3 107 50% 2 88 33% 0 0 0%
Clark 2 31 1% 49 855 31% 43 737 27% 21 280 13%
Clay 0 0 0% 4 726 11% 29 5,349 76% 4 656 11%
Clinton 2 169 3% 23 2,042 35% 17 1,687 26% 10 801 15%
Daviess 0 0 0% 18 1,280 31% 12 1,063 20% 11 774 19%
De Kalb 0 0 0% 11 1,245 30% 13 1,715 35% 4 421 11%
Dearborn 0 0 0% 2 632 7% 6 2,182 22% 3 1,027 11%
Decatur 0 0 0% 10 1,512 24% 14 2,510 34% 4 469 10%
Delaware 3 44 2% 49 451 32% 49 361 32% 14 180 9%
Dubois 0 0 0% 17 1,837 30% 17 1,962 30% 12 1,390 21%
Elkhart 13 87 3% 148 1,081 33% 113 945 25% 60 374 13%
Fayette 1 102 2% 6 718 11% 19 2,590 36% 15 1,310 28%
Floyd 4 78 1% 59 1,147 22% 79 1,731 29% 64 1,492 23%
Fountain 1 91 10% 3 301 30% 2 245 20% 0 0 0%
Franklin 0 0 0% 3 196 17% 3 230 17% 5 314 28%
Grant 3 64 2% 32 538 17% 46 825 24% 36 883 19%
Greene 0 0 0% 2 115 6% 14 917 45% 7 430 23%
Hamilton 3 20 1% 158 1,304 42% 95 830 25% 43 308 12%
Hancock 0 0 0% 19 447 25% 19 443 25% 10 209 13%
Harrison 0 0 0% 6 239 67% 2 83 22% 0 0 0%
Hendricks 5 135 5% 46 1,313 43% 22 657 20% 17 396 16%
Henry 0 0 0% 6 196 14% 12 480 27% 7 240 16%
Howard 2 34 1% 119 2,214 33% 99 2,194 28% 48 805 13%
Huntington 0 0 0% 0 0 0% 0 0 0% 2 73 67%
Jackson 1 76 1% 27 2,400 29% 26 2,604 28% 9 604 10%
Jay 1 211 4% 6 1,416 21% 12 4,012 43% 2 495 7%
Jefferson 2 236 5% 15 1,562 37% 9 992 22% 4 479 10%
Johnson 5 55 1% 143 1,653 35% 117 1,410 29% 51 531 13%
Knox 0 0 0% 0 0 0% 1 66 100% 0 0 0%
Kosciusko 1 79 1% 30 2,633 35% 21 2,038 25% 11 878 13%
La Porte 13 193 5% 70 1,065 29% 65 1,006 27% 30 401 12%
Lake 9 32 1% 261 970 31% 268 1,074 31% 145 622 17%
Lawrence 0 0 0% 17 678 25% 19 902 28% 15 490 22%
Madison 7 142 3% 77 1,561 32% 54 1,185 23% 30 596 13%
Marion 67 111 3% 568 990 28% 617 1,237 30% 331 556 16%
Marshall 0 0 0% 22 2,898 37% 19 2,833 32% 8 913 13%
Monroe 0 0 0% 153 1,149 58% 61 283 23% 15 130 6%
Montgomery 0 0 0% 20 1,827 20% 36 3,942 36% 14 1,319 14%
Morgan 1 61 1% 24 1,543 29% 25 1,866 30% 10 597 12%
Newton 0 0 0% 5 509 38% 4 446 31% 1 94 8%
Noble 2 54 1% 71 2,156 22% 86 2,963 27% 47 1,300 15%
Owen 0 0 0% 33 2,021 100% 0 0 0% 0 0 0%
Perry 0 0 0% 10 2,117 43% 5 914 22% 1 155 4%
Porter 13 132 3% 174 1,669 45% 95 836 24% 37 357 10%
Posey 0 0 0% 0 0 0% 1 201 20% 1 279 20%
Putnam 0 0 0% 11 502 19% 15 585 26% 8 411 14%
Randolph 0 0 0% 4 1,302 80% 0 0 0% 0 0 0%
Rush 1 227 2% 21 5,247 38% 12 4,129 22% 6 1,650 11%
Scott 0 0 0% 11 2,861 69% 1 280 6% 2 386 13%
Shelby 5 271 6% 22 1,281 26% 24 1,564 29% 8 463 10%
St Joseph 19 101 3% 176 823 26% 194 901 28% 123 776 18%
Starke 0 0 0% 2 122 11% 5 343 28% 5 370 28%
Steuben 0 0 0% 15 597 17% 34 1,417 40% 9 398 10%
Tippecanoe 4 47 1% 210 1,305 32% 231 893 35% 99 730 15%
Tipton 0 0 0% 2 594 12% 8 2,396 47% 2 811 12%
Union 1 190 5% 0 0 0% 6 1,364 30% 6 1,211 30%
Vanderburgh 11 102 2% 148 1,178 25% 153 1,130 25% 92 810 15%
Vermillion 0 0 0% 3 959 27% 3 978 27% 1 325 9%
Vigo 2 53 1% 71 1,521 37% 52 915 27% 26 634 13%
Wabash 1 55 3% 11 508 35% 6 299 19% 6 342 19%
Warrick 0 0 0% 25 631 25% 24 669 24% 20 538 20%
Washington 0 0 0% 4 908 33% 5 1,294 42% 1 197 8%
Wayne 6 136 2% 63 1,379 19% 95 2,190 29% 49 1,229 15%
Wells 0 0 0% 6 304 32% 5 268 26% 4 209 21%
White 0 0 0% 15 975 21% 20 1,503 28% 10 653 14%
Whitley 0 0 0% 6 873 30% 6 965 30% 2 271 10%

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Notes:

Rates: Arrrest rates are per 100,000 population.

Source: Uniform Crime Reporting Program Data

Because of incomplete reporting the arrest totals presented in tables with data on age, sex, and race will NOT always correspond to totals presented in other tables. Please review the following background material for More Information on Source Data.