Zip Codes with the Oldest Population in Ohio

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

Top 10 Zip Codes with the Oldest Population in Ohio are: #1 43972 83.1 . #2 44670 77.6 . #3 43007 76.3 . #4 45428 75.5 . #5 45051 74.9 . #6 45112 74.1 . #7 43439 72.3 . #8 45727 71.5 . #9 44687 68.3 . #10 44619 67.7 .

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Oldest Population

Population

Highest Population Highest Population Density Lowest Population Density Male / Female Ratio Female / Male RatioOldest PopulationOldest 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

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Map of Zip Codes with the Oldest Population in Ohio

50.0

100.0

Zip Codes with the Oldest Population in Ohio

	Zip Code	Median Age	vs State	vs National
1.	43972	83.1	39.6 (+43.5)#1	38.5 (+44.6)#20
2.	44670	77.6	39.6 (+38.0)#2	38.5 (+39.1)#70
3.	43007	76.3	39.6 (+36.7)#3	38.5 (+37.8)#80
4.	45428	75.5	39.6 (+35.9)#4	38.5 (+37.0)#96
5.	45051	74.9	39.6 (+35.3)#5	38.5 (+36.4)#111
6.	45112	74.1	39.6 (+34.5)#6	38.5 (+35.6)#136
7.	43439	72.3	39.6 (+32.7)#7	38.5 (+33.8)#185
8.	45727	71.5	39.6 (+31.9)#8	38.5 (+33.0)#207
9.	44687	68.3	39.6 (+28.7)#9	38.5 (+29.8)#423
10.	44619	67.7	39.6 (+28.1)#10	38.5 (+29.2)#469
11.	43446	67.4	39.6 (+27.8)#11	38.5 (+28.9)#499
12.	45893	65.7	39.6 (+26.1)#12	38.5 (+27.2)#666
13.	43438	65.3	39.6 (+25.7)#13	38.5 (+26.8)#718
14.	43805	64.8	39.6 (+25.2)#14	38.5 (+26.3)#797
15.	43006	64.7	39.6 (+25.1)#15	38.5 (+26.2)#810
16.	44690	64.6	39.6 (+25.0)#16	38.5 (+26.1)#826
17.	43925	64.6	39.6 (+25.0)#17	38.5 (+26.1)#827
18.	44697	64.2	39.6 (+24.6)#18	38.5 (+25.7)#888
19.	43931	63.6	39.6 (+24.0)#19	38.5 (+25.1)#970
20.	44610	63.3	39.6 (+23.7)#20	38.5 (+24.8)#1,028
21.	43788	62.8	39.6 (+23.2)#21	38.5 (+24.3)#1,123
22.	43717	62.6	39.6 (+23.0)#22	38.5 (+24.1)#1,179
23.	43951	62.5	39.6 (+22.9)#23	38.5 (+24.0)#1,208
24.	45055	62.0	39.6 (+22.4)#24	38.5 (+23.5)#1,347
25.	43440	61.1	39.6 (+21.5)#25	38.5 (+22.6)#1,531
26.	45740	60.5	39.6 (+20.9)#26	38.5 (+22.0)#1,704
27.	45698	60.1	39.6 (+20.5)#27	38.5 (+21.6)#1,842
28.	45147	60.1	39.6 (+20.5)#28	38.5 (+21.6)#1,861
29.	43934	59.5	39.6 (+19.9)#29	38.5 (+21.0)#2,035
30.	45317	59.4	39.6 (+19.8)#30	38.5 (+20.9)#2,055
31.	45866	59.3	39.6 (+19.7)#31	38.5 (+20.8)#2,107
32.	44454	59.1	39.6 (+19.5)#32	38.5 (+20.6)#2,163
33.	44452	58.9	39.6 (+19.3)#33	38.5 (+20.4)#2,208
34.	43939	58.9	39.6 (+19.3)#34	38.5 (+20.4)#2,221
35.	45780	58.5	39.6 (+18.9)#35	38.5 (+20.0)#2,325
36.	44699	58.3	39.6 (+18.7)#36	38.5 (+19.8)#2,395
37.	45761	57.5	39.6 (+17.9)#37	38.5 (+19.0)#2,659
38.	43523	57.4	39.6 (+17.8)#38	38.5 (+18.9)#2,720
39.	45111	57.0	39.6 (+17.4)#39	38.5 (+18.5)#2,873
40.	45734	57.0	39.6 (+17.4)#40	38.5 (+18.5)#2,875
41.	43030	57.0	39.6 (+17.4)#41	38.5 (+18.5)#2,883
42.	44839	56.8	39.6 (+17.2)#42	38.5 (+18.3)#2,924
43.	43786	56.8	39.6 (+17.2)#43	38.5 (+18.3)#2,957
44.	44702	56.5	39.6 (+16.9)#44	38.5 (+18.0)#3,041
45.	44660	56.5	39.6 (+16.9)#45	38.5 (+18.0)#3,063
46.	44080	56.4	39.6 (+16.8)#46	38.5 (+17.9)#3,105
47.	43468	56.2	39.6 (+16.6)#47	38.5 (+17.7)#3,174
48.	44417	56.0	39.6 (+16.4)#48	38.5 (+17.5)#3,243
49.	43337	56.0	39.6 (+16.4)#49	38.5 (+17.5)#3,260
50.	43463	55.9	39.6 (+16.3)#50	38.5 (+17.4)#3,302
51.	45340	55.8	39.6 (+16.2)#51	38.5 (+17.3)#3,351
52.	44639	55.8	39.6 (+16.2)#52	38.5 (+17.3)#3,354
53.	44403	55.7	39.6 (+16.1)#53	38.5 (+17.2)#3,363
54.	45848	55.5	39.6 (+15.9)#54	38.5 (+17.0)#3,471
55.	44286	55.3	39.6 (+15.7)#55	38.5 (+16.8)#3,521
56.	45864	55.0	39.6 (+15.4)#56	38.5 (+16.5)#3,703
57.	44285	54.9	39.6 (+15.3)#57	38.5 (+16.4)#3,756
58.	43836	54.8	39.6 (+15.2)#58	38.5 (+16.3)#3,805
59.	43791	54.8	39.6 (+15.2)#59	38.5 (+16.3)#3,810
60.	43720	54.6	39.6 (+15.0)#60	38.5 (+16.1)#3,870
61.	44424	54.6	39.6 (+15.0)#61	38.5 (+16.1)#3,902
62.	45062	54.5	39.6 (+14.9)#62	38.5 (+16.0)#3,938
63.	43716	54.4	39.6 (+14.8)#63	38.5 (+15.9)#3,985
64.	44625	54.4	39.6 (+14.8)#64	38.5 (+15.9)#3,995
65.	43341	54.4	39.6 (+14.8)#65	38.5 (+15.9)#4,000
66.	45387	54.1	39.6 (+14.5)#66	38.5 (+15.6)#4,129
67.	44672	54.1	39.6 (+14.5)#67	38.5 (+15.6)#4,131
68.	45821	54.1	39.6 (+14.5)#68	38.5 (+15.6)#4,149
69.	45808	53.8	39.6 (+14.2)#69	38.5 (+15.3)#4,304
70.	43033	53.7	39.6 (+14.1)#70	38.5 (+15.2)#4,354
71.	43452	53.6	39.6 (+14.0)#71	38.5 (+15.1)#4,372
72.	44634	53.5	39.6 (+13.9)#72	38.5 (+15.0)#4,417
73.	45168	53.4	39.6 (+13.8)#73	38.5 (+14.9)#4,479
74.	45621	53.3	39.6 (+13.7)#74	38.5 (+14.8)#4,542
75.	43915	53.1	39.6 (+13.5)#75	38.5 (+14.6)#4,633
76.	44856	53.0	39.6 (+13.4)#76	38.5 (+14.5)#4,710
77.	43001	52.9	39.6 (+13.3)#77	38.5 (+14.4)#4,720
78.	44418	52.9	39.6 (+13.3)#78	38.5 (+14.4)#4,727
79.	45688	52.9	39.6 (+13.3)#79	38.5 (+14.4)#4,749
80.	45622	52.8	39.6 (+13.2)#80	38.5 (+14.3)#4,787
81.	43755	52.7	39.6 (+13.1)#81	38.5 (+14.2)#4,822
82.	44695	52.7	39.6 (+13.1)#82	38.5 (+14.2)#4,825
83.	43811	52.7	39.6 (+13.1)#83	38.5 (+14.2)#4,832
84.	44026	52.5	39.6 (+12.9)#84	38.5 (+14.0)#4,902
85.	45888	52.5	39.6 (+12.9)#85	38.5 (+14.0)#4,946
86.	43111	52.5	39.6 (+12.9)#86	38.5 (+14.0)#4,953
87.	43738	52.4	39.6 (+12.8)#87	38.5 (+13.9)#5,006
88.	44436	52.3	39.6 (+12.7)#88	38.5 (+13.8)#5,021
89.	43432	52.2	39.6 (+12.6)#89	38.5 (+13.7)#5,097
90.	45677	52.2	39.6 (+12.6)#90	38.5 (+13.7)#5,121
91.	43331	52.1	39.6 (+12.5)#91	38.5 (+13.6)#5,133
92.	45862	52.1	39.6 (+12.5)#92	38.5 (+13.6)#5,145
93.	44442	52.0	39.6 (+12.4)#93	38.5 (+13.5)#5,186
94.	45776	52.0	39.6 (+12.4)#94	38.5 (+13.5)#5,217
95.	45160	52.0	39.6 (+12.4)#95	38.5 (+13.5)#5,218
96.	45052	51.9	39.6 (+12.3)#96	38.5 (+13.4)#5,243
97.	44117	51.8	39.6 (+12.2)#97	38.5 (+13.3)#5,296
98.	43153	51.8	39.6 (+12.2)#98	38.5 (+13.3)#5,329
99.	45711	51.8	39.6 (+12.2)#99	38.5 (+13.3)#5,334
100.	45898	51.8	39.6 (+12.2)#100	38.5 (+13.3)#5,340