Zip Codes with the Highest Population in Ohio

Q: What are the Top 10 Zip Codes with the Highest Population in Ohio?

Top 10 Zip Codes with the Highest Population in Ohio are: #1 45011 73,596 . #2 43123 66,365 . #3 43081 64,746 . #4 43026 64,633 . #5 44256 64,186 . #6 43055 62,460 . #7 43130 62,187 . #8 44035 62,050 . #9 44060 59,932 . #10 43068 58,916 .

On this page

Comparison Map Comparison Data Common Questions

RELATED REPORTS & OPTIONS

Highest Population

Population

Highest PopulationHighest Population Density Lowest Population Density Male / Female Ratio Female / Male Ratio Oldest Population Oldest Population | Male Oldest Population | Female Youngest Population Youngest Population | Male Youngest Population | Female

Families and Households

Largest Family Size Largest Household Size Most Single Fathers Most Single Mothers Fewest Single Fathers Fewest Single Mothers Smallest Family Size Smallest Household Size

Female Fertility

Female Fertility (Unmarried)

Race (Community Size)

Asian Black / African American Hawaiian / Pacific Hispanic or Latino Native / Alaskan White / Caucasian

Race (Percentage)

Asian Black / African American Hawaiian / Pacific Hispanic or Latino Native / Alaskan White / Caucasian

Ancestry (Community Size)

Afghan African Alaska Native Alaskan Athabascan Albanian Aleut Alsatian American Apache Arab Arapaho Argentinean Armenian Assyrian / Chaldean / Syriac Australian Austrian Bahamian Bangladeshi Barbadian Basque Belgian Belizean Bermudan Bhutanese Blackfeet Bolivian Brazilian British British West Indian Bulgarian Burmese Cajun Cambodian Canadian Cape Verdean Carpatho Rusyn Celtic Central American Central American Indian Cherokee Cheyenne Chickasaw Chilean Chinese Chippewa Choctaw Colombian Colville Comanche Costa Rican Cree Creek Croatian Crow Cuban Cypriot Czech Czechoslovakian Danish Delaware Dominican Dutch Dutch West Indian Eastern European Ecuadorian Egyptian English Estonian Ethiopian European Fijian Filipino Finnish French French American Indian French Canadian German German Russian Ghanaian Greek Guamanian / Chamorro Guatemalan Guyanese Haitian Hmong Honduran Hopi Houma Hungarian Icelander Indian (Asian)Indonesian Inupiat Iranian Iraqi Irish Iroquois Israeli Italian Jamaican Japanese Jordanian Kenyan Kiowa Korean Laotian Latvian Lebanese Liberian Lithuanian Lumbee Luxembourger Macedonian Malaysian Maltese Marshallese Menominee Mexican Mexican American Indian Mongolian Moroccan Native Hawaiian Navajo Nepalese New Zealander Nicaraguan Nigerian Northern European Norwegian Okinawan Osage Ottawa Paiute Pakistani Palestinian Panamanian Paraguayan Pennsylvania German Peruvian Pima Polish Portuguese Potawatomi Pueblo Puerto Rican Puget Sound Salish Romanian Russian Salvadoran Samoan Scandinavian Scotch-Irish Scottish Seminole Senegalese Serbian Shoshone Sierra Leonean Sioux Slavic Slovak Slovene Somali South African South American South American Indian Soviet Union Spaniard Spanish Spanish American Spanish American Indian Sri Lankan Subsaharan African Sudanese Swedish Swiss Syrian Taiwanese Thai Tlingit-Haida Tohono O'Odham Tongan Trinidadian and Tobagonian Tsimshian Turkish U.S. Virgin Islander Ugandan Ukrainian Uruguayan Ute Venezuelan Vietnamese Welsh West Indian Yakama Yaqui Yugoslavian Yuman Yup'ik Zimbabwean

Ancestry (Percentage)

Immigrant Origin (Total)

Afghanistan Africa Albania Argentina Armenia Asia Australia Austria Azores Bahamas Bangladesh Barbados Belarus Belgium Belize Bolivia Bosnia and Herzegovina Brazil Bulgaria Burma / Myanmar Cabo Verde Cambodia Cameroon Canada Caribbean Central America Chile China Colombia Congo Costa Rica Croatia Cuba Czechoslovakia Denmark Dominica Dominican Republic Eastern Africa Eastern Asia Eastern Europe Ecuador Egypt El Salvador England Eritrea Ethiopia Europe Fiji France Germany Ghana Greece Grenada Guatemala Guyana Haiti Honduras Hong Kong Hungary India Indonesia Iran Iraq Ireland Israel Italy Jamaica Japan Jordan Kazakhstan Kenya Korea Kuwait Laos Latin America Latvia Lebanon Liberia Lithuania Malaysia Mexico Micronesia Middle Africa Moldova Morocco Nepal Netherlands Nicaragua Nigeria North Macedonia Northern Africa Northern Europe Norway Oceania Pakistan Panama Peru Philippines Poland Portugal Romania Russia Saudi Arabia Scotland Senegal Serbia Sierra Leone Singapore Somalia South Africa South America South Central Asia South Eastern Asia Southern Europe Spain Sri Lanka St. Vincent and the Grenadines Sudan Sweden Switzerland Syria Taiwan Thailand Trinidad and Tobago Turkey Uganda Ukraine Uruguay Uzbekistan Venezuela Vietnam West Indies Western Africa Western Asia Western Europe Yemen Zaire Zimbabwe

Immigrant Origin (Percentage)

Income

Highest Per Capita Income Highest Earnings | Male Highest Earnings | Female Highest Wage/Income Gap ($)Highest Wage/Income Gap (%)Highest Inequality / Gini Index Lowest Per Capita Income Lowest Earnings | Male Lowest Earnings | Female Lowest Wage/Income Gap ($)Lowest Wage/Income Gap (%)Lowest Inequality / Gini Index

Income (Families)

Highest Family Income Lowest Family Income Family Income | $0-10k Family Income | $100k+Family Income | $200k+

Income (Households)

Highest Household Income Lowest Household Income Household Income | $0-10k Household Income | $200k+Household Income | $100k+

Poverty

Poverty (Families)

Unemployment

Employment Occupations

Architecture & Engineering Arts, Media & Entertainment Business & Financial Cleaning & Maintenance Community & Social Service Computer & Mathematics Computer, Engineering & Science Construction & Extraction Education Instruction & Library Education, Arts & Media Farming, Fishing & Forestry Firefighting & Prevention Food Preparation & Serving Health Diagnosing & Treating Health Technologists Healthcare Support Installation, Maintenance & Repair Law Enforcement Legal Services & Support Life, Physical & Social Science Management Material Moving Office & Administration Personal Care and Service Production Sales & Related Security & Protection Transportation

Employment Industries

Accommodation & Food Services Administrative & Support Services Agriculture, Fishing & Hunting Arts, Entertainment & Recreation Construction Educational Services Enterprise Management Finance & Insurance Health Care & Social Assistance Information & Technology Manufacturing Mining, Quarrying, & Extraction Professional & Scientific Services Public Administration Real Estate, Rental & Leasing Retail Trade Transportation & Warehousing Utilities Wholesale Trade

Employer Class

Private Company Employees Self-Employed / Incorporated Self-Employed / Not Incorporated Not-for-profit Organizations Local Government Employees State Government Employees Federal Government Employees Unpaid Family Workers

Commute Time

Longest Commute Longest Commute | Male Longest Commute | Female Shortest Commute Shortest Commute | Male Shortest Commute | Female

Commute Means

Drive | Alone Drive | Carpool Public Transit Taxi / Cab Walk to Work Work from Home

School Enrollment

In Private School Nursery / Preschool Kindergarten Elementary School Middle School High School College University

Education by Degree Field

Computers and Mathematics Bio, Nature & Agricultural Physical and Health Sciences Psychology Social Sciences Engineering Multidisciplinary Studies Science and Engineering Business Education Literature and Languages Liberal Arts and History Visual and Performing Arts Communications Arts and Humanities

Occupancy

Highest Owner-Occupied Highest Renter-Occupied Lowest Owner-Occupied Lowest Renter-Occupied

Finances

Highest Median Housing Costs Highest Property Prices Highest Owner Housing Costs Highest Renter Housing Costs Highest Housing Costs / Income Lowest Median Housing Costs Lowest Property Prices Lowest Owner Housing Costs Lowest Renter Housing Costs Lowest Housing Costs / Income

Physical Characteristics

Detached Home Residency Condo/Apartment Residency Utility Gas Heating Bottled Gas / LP Heating Electrical Heating Fuel Oil Heating Coal / Coke Heating Fuel-less Heating Households without a Cars Households with 1 or more Cars Households with 2 or more Cars Households with 3 or more Cars

Ohio

Compare Zip Codes

Comparison Subject

Compare States Compare CitiesCompare Zip Codes

Map of Zip Codes with the Highest Population in Ohio

20,000

80,000

Zip Codes with the Highest Population in Ohio

	Zip Code	People	vs State	vs National
1.	45011	73,596	11,774,683(-11.7m)#1	331,097,593(-331m)#174
2.	43123	66,365	11,774,683(-11.7m)#2	331,097,593(-331m)#301
3.	43081	64,746	11,774,683(-11.7m)#3	331,097,593(-331m)#342
4.	43026	64,633	11,774,683(-11.7m)#4	331,097,593(-331m)#347
5.	44256	64,186	11,774,683(-11.7m)#5	331,097,593(-331m)#357
6.	43055	62,460	11,774,683(-11.7m)#6	331,097,593(-331m)#400
7.	43130	62,187	11,774,683(-11.7m)#7	331,097,593(-331m)#412
8.	44035	62,050	11,774,683(-11.7m)#8	331,097,593(-331m)#421
9.	44060	59,932	11,774,683(-11.7m)#9	331,097,593(-331m)#493
10.	43068	58,916	11,774,683(-11.7m)#10	331,097,593(-331m)#531
11.	44077	58,369	11,774,683(-11.7m)#11	331,097,593(-331m)#551
12.	43230	58,079	11,774,683(-11.7m)#12	331,097,593(-331m)#562
13.	43015	57,745	11,774,683(-11.7m)#13	331,097,593(-331m)#577
14.	43228	57,406	11,774,683(-11.7m)#14	331,097,593(-331m)#587
15.	45040	57,214	11,774,683(-11.7m)#15	331,097,593(-331m)#594
16.	45601	56,300	11,774,683(-11.7m)#16	331,097,593(-331m)#635
17.	43701	55,531	11,774,683(-11.7m)#17	331,097,593(-331m)#660
18.	45069	55,414	11,774,683(-11.7m)#18	331,097,593(-331m)#663
19.	45140	55,364	11,774,683(-11.7m)#19	331,097,593(-331m)#669
20.	43229	55,168	11,774,683(-11.7m)#20	331,097,593(-331m)#689
21.	43302	55,090	11,774,683(-11.7m)#21	331,097,593(-331m)#694
22.	45840	54,557	11,774,683(-11.7m)#22	331,097,593(-331m)#713
23.	45044	53,909	11,774,683(-11.7m)#23	331,097,593(-331m)#750
24.	45013	52,953	11,774,683(-11.7m)#24	331,097,593(-331m)#803
25.	44107	50,676	11,774,683(-11.7m)#25	331,097,593(-331m)#948
26.	44130	50,548	11,774,683(-11.7m)#26	331,097,593(-331m)#960
27.	45424	50,221	11,774,683(-11.7m)#27	331,097,593(-331m)#990
28.	44646	48,507	11,774,683(-11.7m)#28	331,097,593(-331m)#1,105
29.	45238	47,154	11,774,683(-11.7m)#29	331,097,593(-331m)#1,206
30.	43232	46,881	11,774,683(-11.7m)#30	331,097,593(-331m)#1,226
31.	43147	46,058	11,774,683(-11.7m)#31	331,097,593(-331m)#1,299
32.	45014	46,023	11,774,683(-11.7m)#32	331,097,593(-331m)#1,303
33.	43207	46,010	11,774,683(-11.7m)#33	331,097,593(-331m)#1,304
34.	44212	45,874	11,774,683(-11.7m)#34	331,097,593(-331m)#1,316
35.	43235	45,462	11,774,683(-11.7m)#35	331,097,593(-331m)#1,349
36.	43065	45,067	11,774,683(-11.7m)#36	331,097,593(-331m)#1,387
37.	44691	44,775	11,774,683(-11.7m)#37	331,097,593(-331m)#1,423
38.	43016	44,092	11,774,683(-11.7m)#38	331,097,593(-331m)#1,491
39.	43204	43,990	11,774,683(-11.7m)#39	331,097,593(-331m)#1,502
40.	43224	43,391	11,774,683(-11.7m)#40	331,097,593(-331m)#1,564
41.	43551	42,914	11,774,683(-11.7m)#41	331,097,593(-331m)#1,613
42.	45036	42,346	11,774,683(-11.7m)#42	331,097,593(-331m)#1,681
43.	44102	42,078	11,774,683(-11.7m)#43	331,097,593(-331m)#1,712
44.	43017	41,837	11,774,683(-11.7m)#44	331,097,593(-331m)#1,737
45.	45231	41,466	11,774,683(-11.7m)#45	331,097,593(-331m)#1,780
46.	44118	41,037	11,774,683(-11.7m)#46	331,097,593(-331m)#1,844
47.	44111	40,940	11,774,683(-11.7m)#47	331,097,593(-331m)#1,865
48.	45324	40,623	11,774,683(-11.7m)#48	331,097,593(-331m)#1,906
49.	44124	40,208	11,774,683(-11.7m)#49	331,097,593(-331m)#1,955
50.	44870	40,067	11,774,683(-11.7m)#50	331,097,593(-331m)#1,979
51.	44720	39,942	11,774,683(-11.7m)#51	331,097,593(-331m)#1,999
52.	45385	39,699	11,774,683(-11.7m)#52	331,097,593(-331m)#2,035
53.	43615	39,405	11,774,683(-11.7m)#53	331,097,593(-331m)#2,065
54.	44224	38,715	11,774,683(-11.7m)#54	331,097,593(-331m)#2,170
55.	44203	38,714	11,774,683(-11.7m)#55	331,097,593(-331m)#2,171
56.	43110	38,235	11,774,683(-11.7m)#56	331,097,593(-331m)#2,237
57.	44240	38,208	11,774,683(-11.7m)#57	331,097,593(-331m)#2,245
58.	44109	38,026	11,774,683(-11.7m)#58	331,097,593(-331m)#2,272
59.	44134	37,914	11,774,683(-11.7m)#59	331,097,593(-331m)#2,289
60.	45373	37,714	11,774,683(-11.7m)#60	331,097,593(-331m)#2,314
61.	45211	37,303	11,774,683(-11.7m)#61	331,097,593(-331m)#2,366
62.	45458	37,128	11,774,683(-11.7m)#62	331,097,593(-331m)#2,399
63.	44094	36,958	11,774,683(-11.7m)#63	331,097,593(-331m)#2,442
64.	43213	36,724	11,774,683(-11.7m)#64	331,097,593(-331m)#2,476
65.	43040	36,678	11,774,683(-11.7m)#65	331,097,593(-331m)#2,484
66.	44122	36,522	11,774,683(-11.7m)#66	331,097,593(-331m)#2,507
67.	45342	36,127	11,774,683(-11.7m)#67	331,097,593(-331m)#2,576
68.	45103	35,908	11,774,683(-11.7m)#68	331,097,593(-331m)#2,613
69.	44039	35,625	11,774,683(-11.7m)#69	331,097,593(-331m)#2,646
70.	43221	35,164	11,774,683(-11.7m)#70	331,097,593(-331m)#2,708
71.	43035	34,661	11,774,683(-11.7m)#71	331,097,593(-331m)#2,803
72.	43201	34,651	11,774,683(-11.7m)#72	331,097,593(-331m)#2,805
73.	44120	34,050	11,774,683(-11.7m)#73	331,097,593(-331m)#2,915
74.	44145	34,027	11,774,683(-11.7m)#74	331,097,593(-331m)#2,919
75.	45150	33,853	11,774,683(-11.7m)#75	331,097,593(-331m)#2,951
76.	44281	33,768	11,774,683(-11.7m)#76	331,097,593(-331m)#2,963
77.	44105	33,667	11,774,683(-11.7m)#77	331,097,593(-331m)#2,975
78.	45701	33,363	11,774,683(-11.7m)#78	331,097,593(-331m)#3,028
79.	43082	33,195	11,774,683(-11.7m)#79	331,097,593(-331m)#3,048
80.	44121	32,840	11,774,683(-11.7m)#80	331,097,593(-331m)#3,107
81.	44512	32,821	11,774,683(-11.7m)#81	331,097,593(-331m)#3,110
82.	43560	32,717	11,774,683(-11.7m)#82	331,097,593(-331m)#3,127
83.	44601	32,716	11,774,683(-11.7m)#83	331,097,593(-331m)#3,129
84.	45503	32,714	11,774,683(-11.7m)#84	331,097,593(-331m)#3,130
85.	44095	32,635	11,774,683(-11.7m)#85	331,097,593(-331m)#3,145
86.	44266	32,530	11,774,683(-11.7m)#86	331,097,593(-331m)#3,172
87.	44070	32,244	11,774,683(-11.7m)#87	331,097,593(-331m)#3,230
88.	43613	32,231	11,774,683(-11.7m)#88	331,097,593(-331m)#3,234
89.	43219	32,136	11,774,683(-11.7m)#89	331,097,593(-331m)#3,257
90.	45005	31,739	11,774,683(-11.7m)#90	331,097,593(-331m)#3,323
91.	43062	31,566	11,774,683(-11.7m)#91	331,097,593(-331m)#3,362
92.	43402	31,472	11,774,683(-11.7m)#92	331,097,593(-331m)#3,381
93.	44805	31,447	11,774,683(-11.7m)#93	331,097,593(-331m)#3,384
94.	44004	31,348	11,774,683(-11.7m)#94	331,097,593(-331m)#3,408
95.	44133	31,144	11,774,683(-11.7m)#95	331,097,593(-331m)#3,447
96.	43050	31,064	11,774,683(-11.7m)#96	331,097,593(-331m)#3,465
97.	45215	31,006	11,774,683(-11.7m)#97	331,097,593(-331m)#3,477
98.	43004	31,002	11,774,683(-11.7m)#98	331,097,593(-331m)#3,478
99.	44312	30,508	11,774,683(-11.7m)#99	331,097,593(-331m)#3,578
100.	43537	29,859	11,774,683(-11.7m)#100	331,097,593(-331m)#3,699