Risk Factors

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Number of Children Arrested for a Serious Crime, 2014: by County

Counties of Minnesota Chisago Isanti Ramsey Anoka Washington Hennepin Benton Wright Dakota Scott Carver McLeod Mille Lacs Kanabec Wabasha Goodhue Rice Le Sueur Sibley Sherburne Meeker Renville Chippewa Stearns Morrison Pine Crow Wing Aitkin Brown Yellow Medicine Lac qui Parle Big Stone Traverse Wilkin Todd Wadena Cass Polk Red Lake Clearwater Becker Carlton Hubbard Norman Clay Mahnomen Beltrami Itasca Pennington Marshall Kittson Roseau Lake of the Woods Koochiching St. Louis Lake Cook Redwood Cottonwood Watonwan Steele Dodge Otter Tail Grant Douglas Stevens Pope Lyon Nicollet Lincoln Kandiyohi Swift Pepestone Murray Blue Earth Olmsted Winona Waseca Rock Nobles Jackson Martin Faribault Freeborn Mower Fillmore Houston
  • >43 to ≤1,905
  • >6 to ≤43
  • >0 to ≤6
  • 0
  • No data available

About the Indicator:

Children under 18 arrested for Part I crimes: murder, rape, robbery, aggravated assault, burglary, larceny, vehicle theft, and arson. Not all children arrested for serious crimes committed these crimes, and some children are not arrested for crimes that they actually committed. The rate per 1,000 is the total number of children arrested for Part I crimes divided by the estimated number of children ages 10-17 multiplied by 1,000. These rates are useful for comparison purposes and trends, but may be low because of the inclusion of children in the younger age ranges and the inclusion of girls, both of whom have few arrests.  For more on this see the Annie E. Casey Foundation Kids Count Data Center at http://datacenter.kidscount.org/

Data Source: Minnesota Crime Information, Minnesota Bureau of Criminal Apprehension

Description: Minnesota Crime Information is a statistical report detailing the amount of criminal activity within the State as collected and prepared from data submitted by individual law enforcement agencies. The criminal activity consists of measurements involving offenses, clearances, and arrests.

Sponsored by: Minnesota Department of Public Safety, Bureau of Criminal Apprehension, Criminal Justice Information System

Geographic Level: State

Aggregated data at the state and county level do not reveal disparities that may exist within a given geographic area.

Frequency: Data collected and reported annually

Characteristics: Race/ethnicity is often determined by law enforcement and therefore may not be as accurate as self-reported status.