Safest Cities Ohio - header

Ohio – A midwestern state in the Great Lakes area, Ohio became one of the major industrial powerhouses of the US in the 19th and 20th centuries and was famous for its automobile industry. Well known politically as a swing and bellwether state, it suffered significant hardships in its manufacturing base in the late 20th and early 21st centuries. This has been offset more recently by a switch to an information and services economy although its industrial output remains large. It is the 8th state in terms of state GDP.

Ohio has a large population at 11.6 million, making it the 7th state in population terms and the 10th for population density. Incomes in Ohio are significantly lower than US averages. Average household income levels are around $54,000. Individual income is around $30,000. Both figures are in the region of 7-10% under the US average.

1.95 Average violent crime per 1,000
24.25 Average property crime per 1,000

Ohio’s crime statistics are significantly below overall US averages. Overall fiugres show:

  • It’s the 16th safest state for property crime (where 1st = lowest crime)
  • The violent crime rate is roughly half the national average with a ratio of 0.56 based upon 1.95 crimes per 1,000 versus a national average of 3.47. This makes it the 8th safest state in the US for violent crime
  • Property crime is also just over half the US average being 24.25 per 1,000 compared to the national average of 40.43.

As elsewhere, in Ohio, some areas are safer than others. The top safest areas statistically are:

  1. Brecksville
  2. Sylvania
  3. Solon
  4. Seven Hills
  5. North Ridgeville

Safest Cities in Ohio, 2019

RankCityViolent CrimesProperty CrimesViolent Crime RateProperty Crime Rate
1Brecksville2520.1493.871
2Sylvania6860.3174.548
3Solon131820.5657.905
4Seven Hills3500.2574.285
5North Ridgeville171400.5064.168
6New Albany4920.3698.489
7Avon Lake81240.3365.202
8Brunswick211940.6035.569
9Wickliffe91520.71011.988
10Springboro101220.5376.548
11Poland Township3530.2524.446
12Powell61030.4617.905
13Clearcreek Township11740.7084.765
14Berea81400.4247.419
15Lyndhurst181801.32513.249
16Aurora31870.18811.737
17Clayton51180.3808.974
18Maumee53050.36222.087
19Perrysburg Township51670.39113.063
20Amherst51570.41412.986
21Worthington112670.74918.173
22Hilliard174040.47011.178
23Macedonia52060.41617.128
24Miamisburg142570.70312.896
25Centerville143730.58915.684
26Bedford252281.97818.037
27Blue Ash162781.30622.698
28Copley Township151630.8689.433
29Mason123570.35910.687
30Shawnee Township141351.15711.161
31Harrison61820.53416.184
32Parma1419061.77711.419
33North Olmsted264700.81814.790
34Richmond Heights192061.82119.747
35Kettering708601.26915.593
36Kent444511.45414.899
37Mentor729081.54319.459
38Pierce Township51510.43012.991
39Wadsworth243331.02614.238
40Vandalia263101.73120.636
41Cleveland Heights1318792.94219.742
42Upper Arlington125120.34114.540
43Streetsboro113430.67521.033
44Strongsville188520.40219.036
45Greenville402743.13221.453
46Eastlake143300.77518.276
47Ashland253751.22018.306
48Monroe194061.18725.372
49Norton91860.75015.503
50Bowling Green415871.29018.471
51Gahanna257910.70922.444
52Lakewood741,1991.47623.908
53Forest Park504352.67923.306
54Troy385021.46919.408
55Delhi Township154160.50614.045
56Fairborn827232.41621.305
57Delaware646971.62817.729
58Van Wert223302.05430.804
59West Carrollton232851.78322.096
60Xenia558112.08930.800
61Fairfield909322.11121.864
62Bexley204201.45230.494
63Reading282912.71728.233
64Springfield Township, Hamilton County736741.99618.430
65Elyria1911,1463.56421.386
66Stow326900.92219.889
67Cuyahoga Falls491,2090.99724.601
68Union Township, Clermont County398910.80918.480
69Miami Township, Clermont County346250.80314.757
70Zanesville1001,1573.92845.449
71Huber Heights779512.02725.029
72Defiance264641.56727.962
73Youngstown4472,3626.99736.970
74Austintown627891.75622.349
75Cincinnati2,83315,1059.47150.499
76Reynoldsburg991,0622.62628.167
77Salem213481.76729.276
78Findlay1281,3043.08631.441
79Beavercreek381,1110.81623.856
80Englewood194431.40732.805
81Alliance758003.43436.633
82Sidney428222.05240.164
83Mount Vernon226211.32937.516
84Lorain3732,0195.85831.709
85Columbus4,47834,4085.13439.449
86Akron1,3778,3606.97542.348
87Sandusky709952.81640.023
88Barberton1038813.95433.820
89Lancaster1271,7063.17342.622
90Washington Court House415482.90038.766
91Hamilton3122,6085.02542.001
92Wooster1029163.75433.711
93Piqua548192.57539.050
94Wilmington236451.85251.949
95Urbana254042.20235.592
96Lima2751,9827.38953.251
97Whitehall1251,2696.63767.375
98Heath235982.15355.987
99Circleville577144.08051.102
100Warren2271,6085.72640.562
101Steubenville491,1322.72562.962
102Colerain Township1001,7081.69528.951
103Middletown2492,9565.10060.539
104Fairfield Township267581.15433.653
105Springfield3704,0246.28868.385
106American Township12090.08217.120

METHODOLOGY

To identify the safest cities in Ohio, we reviewed the most recent FBI Uniform Crime Report statistics. A total of 7,639 cities were factored into this ranking with populations ranging from 7,639 to 4,007,147. However, we eliminated any cities that failed to submit a complete crime report to the FBI and removed cities with populations under 10,000.

Overall, data from 8,793 law enforcement agencies that represented more 193 million of the US population helped us draw interesting insights between the size of the police force and incidence of crime.

There are two broad classifications of crimes: violent crimes and non-violent crimes. According to the FBI, “Violent crime is composed of four offenses: murder and non-negligent manslaughter, rape, robbery, and aggravated assault. Violent crimes are defined in the UCR Program as those offenses that involve force or threat of force. Property crime includes the offenses of burglary, larceny-theft, motor vehicle theft, and arson. The object of the theft-type offenses is the taking of money or property, but there is no force or threat of force against the victims. ”

We computed the total number of crimes reported by each city by adding violent crimes and property crimes. We then rated them using the population of the city and created a crime rate as the number of crimes per 1,000 population. Then we transformed the total crime rate variable so that the skewness was reduced and we normalized it so the final number became a score between 0 and 1.

Next, we computed a new variable called Police Adequacy (TotalCrimes / Number of police employees). We consider that the smaller the police adequacy statistic is, the safer the city is. We transformed and normalized this police adequacy variable also, resulting in a score between 0 and 1. Finally, we combined the two scores to create a safety score for each city.

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