Zip Codes with the Highest Male / Female Ratio in Ohio

RELATED REPORTS & OPTIONS

Male / Female Ratio
Population
Families and Households
Female Fertility
Female Fertility (Unmarried)
Race (Community Size)
Race (Percentage)
Ancestry (Community Size)
AfghanAfricanAlaska NativeAlaskan AthabascanAlbanianAleutAlsatianAmericanApacheArabArapahoArgentineanArmenianAssyrian / Chaldean / SyriacAustralianAustrianBahamianBangladeshiBarbadianBasqueBelgianBelizeanBermudanBhutaneseBlackfeetBolivianBrazilianBritishBritish West IndianBulgarianBurmeseCajunCambodianCanadianCape VerdeanCarpatho RusynCelticCentral AmericanCentral American IndianCherokeeCheyenneChickasawChileanChineseChippewaChoctawColombianColvilleComancheCosta RicanCreeCreekCroatianCrowCubanCypriotCzechCzechoslovakianDanishDelawareDominicanDutchDutch West IndianEastern EuropeanEcuadorianEgyptianEnglishEstonianEthiopianEuropeanFijianFilipinoFinnishFrenchFrench American IndianFrench CanadianGermanGerman RussianGhanaianGreekGuamanian / ChamorroGuatemalanGuyaneseHaitianHmongHonduranHopiHoumaHungarianIcelanderIndian (Asian)IndonesianInupiatIranianIraqiIrishIroquoisIsraeliItalianJamaicanJapaneseJordanianKenyanKiowaKoreanLaotianLatvianLebaneseLiberianLithuanianLumbeeLuxembourgerMacedonianMalaysianMalteseMarshalleseMenomineeMexicanMexican American IndianMongolianMoroccanNative HawaiianNavajoNepaleseNew ZealanderNicaraguanNigerianNorthern EuropeanNorwegianOkinawanOsageOttawaPaiutePakistaniPalestinianPanamanianParaguayanPennsylvania GermanPeruvianPimaPolishPortuguesePotawatomiPuebloPuerto RicanPuget Sound SalishRomanianRussianSalvadoranSamoanScandinavianScotch-IrishScottishSeminoleSenegaleseSerbianShoshoneSierra LeoneanSiouxSlavicSlovakSloveneSomaliSouth AfricanSouth AmericanSouth American IndianSoviet UnionSpaniardSpanishSpanish AmericanSpanish American IndianSri LankanSubsaharan AfricanSudaneseSwedishSwissSyrianTaiwaneseThaiTlingit-HaidaTohono O'OdhamTonganTrinidadian and TobagonianTsimshianTurkishU.S. Virgin IslanderUgandanUkrainianUruguayanUteVenezuelanVietnameseWelshWest IndianYakamaYaquiYugoslavianYumanYup'ikZimbabwean
Ancestry (Percentage)
AfghanAfricanAlaska NativeAlaskan AthabascanAlbanianAleutAlsatianAmericanApacheArabArapahoArgentineanArmenianAssyrian / Chaldean / SyriacAustralianAustrianBahamianBangladeshiBarbadianBasqueBelgianBelizeanBermudanBhutaneseBlackfeetBolivianBrazilianBritishBritish West IndianBulgarianBurmeseCajunCambodianCanadianCape VerdeanCarpatho RusynCelticCentral AmericanCentral American IndianCherokeeCheyenneChickasawChileanChineseChippewaChoctawColombianColvilleComancheCosta RicanCreeCreekCroatianCrowCubanCypriotCzechCzechoslovakianDanishDelawareDominicanDutchDutch West IndianEastern EuropeanEcuadorianEgyptianEnglishEstonianEthiopianEuropeanFijianFilipinoFinnishFrenchFrench American IndianFrench CanadianGermanGerman RussianGhanaianGreekGuamanian / ChamorroGuatemalanGuyaneseHaitianHmongHonduranHopiHoumaHungarianIcelanderIndian (Asian)IndonesianInupiatIranianIraqiIrishIroquoisIsraeliItalianJamaicanJapaneseJordanianKenyanKiowaKoreanLaotianLatvianLebaneseLiberianLithuanianLumbeeLuxembourgerMacedonianMalaysianMalteseMarshalleseMenomineeMexicanMexican American IndianMongolianMoroccanNative HawaiianNavajoNepaleseNew ZealanderNicaraguanNigerianNorthern EuropeanNorwegianOkinawanOsageOttawaPaiutePakistaniPalestinianPanamanianParaguayanPennsylvania GermanPeruvianPimaPolishPortuguesePotawatomiPuebloPuerto RicanPuget Sound SalishRomanianRussianSalvadoranSamoanScandinavianScotch-IrishScottishSeminoleSenegaleseSerbianShoshoneSierra LeoneanSiouxSlavicSlovakSloveneSomaliSouth AfricanSouth AmericanSouth American IndianSoviet UnionSpaniardSpanishSpanish AmericanSpanish American IndianSri LankanSubsaharan AfricanSudaneseSwedishSwissSyrianTaiwaneseThaiTlingit-HaidaTohono O'OdhamTonganTrinidadian and TobagonianTsimshianTurkishU.S. Virgin IslanderUgandanUkrainianUruguayanUteVenezuelanVietnameseWelshWest IndianYakamaYaquiYugoslavianYumanYup'ikZimbabwean
Immigrant Origin (Total)
AfghanistanAfricaAlbaniaArgentinaArmeniaAsiaAustraliaAustriaAzoresBahamasBangladeshBarbadosBelarusBelgiumBelizeBoliviaBosnia and HerzegovinaBrazilBulgariaBurma / MyanmarCabo VerdeCambodiaCameroonCanadaCaribbeanCentral AmericaChileChinaColombiaCongoCosta RicaCroatiaCubaCzechoslovakiaDenmarkDominicaDominican RepublicEastern AfricaEastern AsiaEastern EuropeEcuadorEgyptEl SalvadorEnglandEritreaEthiopiaEuropeFijiFranceGermanyGhanaGreeceGrenadaGuatemalaGuyanaHaitiHondurasHong KongHungaryIndiaIndonesiaIranIraqIrelandIsraelItalyJamaicaJapanJordanKazakhstanKenyaKoreaKuwaitLaosLatin AmericaLatviaLebanonLiberiaLithuaniaMalaysiaMexicoMicronesiaMiddle AfricaMoldovaMoroccoNepalNetherlandsNicaraguaNigeriaNorth MacedoniaNorthern AfricaNorthern EuropeNorwayOceaniaPakistanPanamaPeruPhilippinesPolandPortugalRomaniaRussiaSaudi ArabiaScotlandSenegalSerbiaSierra LeoneSingaporeSomaliaSouth AfricaSouth AmericaSouth Central AsiaSouth Eastern AsiaSouthern EuropeSpainSri LankaSt. Vincent and the GrenadinesSudanSwedenSwitzerlandSyriaTaiwanThailandTrinidad and TobagoTurkeyUgandaUkraineUruguayUzbekistanVenezuelaVietnamWest IndiesWestern AfricaWestern AsiaWestern EuropeYemenZaireZimbabwe
Immigrant Origin (Percentage)
AfghanistanAfricaAlbaniaArgentinaArmeniaAsiaAustraliaAustriaAzoresBahamasBangladeshBarbadosBelarusBelgiumBelizeBoliviaBosnia and HerzegovinaBrazilBulgariaBurma / MyanmarCabo VerdeCambodiaCameroonCanadaCaribbeanCentral AmericaChileChinaColombiaCongoCosta RicaCroatiaCubaCzechoslovakiaDenmarkDominicaDominican RepublicEastern AfricaEastern AsiaEastern EuropeEcuadorEgyptEl SalvadorEnglandEritreaEthiopiaEuropeFijiFranceGermanyGhanaGreeceGrenadaGuatemalaGuyanaHaitiHondurasHong KongHungaryIndiaIndonesiaIranIraqIrelandIsraelItalyJamaicaJapanJordanKazakhstanKenyaKoreaKuwaitLaosLatin AmericaLatviaLebanonLiberiaLithuaniaMalaysiaMexicoMicronesiaMiddle AfricaMoldovaMoroccoNepalNetherlandsNicaraguaNigeriaNorth MacedoniaNorthern AfricaNorthern EuropeNorwayOceaniaPakistanPanamaPeruPhilippinesPolandPortugalRomaniaRussiaSaudi ArabiaScotlandSenegalSerbiaSierra LeoneSingaporeSomaliaSouth AfricaSouth AmericaSouth Central AsiaSouth Eastern AsiaSouthern EuropeSpainSri LankaSt. Vincent and the GrenadinesSudanSwedenSwitzerlandSyriaTaiwanThailandTrinidad and TobagoTurkeyUgandaUkraineUruguayUzbekistanVenezuelaVietnamWest IndiesWestern AfricaWestern AsiaWestern EuropeYemenZaireZimbabwe
Income
Income (Families)
Income (Households)
Poverty
Poverty (Families)
Unemployment
Employment Occupations
Employment Industries
Employer Class
Commute Time
Commute Means
School Enrollment
Education by Degree Field
Occupancy
Finances
Physical Characteristics
Ohio
Compare Zip Codes
Comparison Subject

Map of Zip Codes with the Highest Male / Female Ratio in Ohio

0.00
8,000.00
Zip Codes with the Highest Male / Female Ratio in Ohio Map

Zip Codes with the Highest Male / Female Ratio in Ohio

Zip Code Males / 100 Females vs State vs National
1.454287,050.0097.56(+6.95k)#198.38(+6.95k)#15
2.43439550.0097.56(+452)#298.38(+452)#136
3.43951511.1197.56(+414)#398.38(+413)#151
4.43733466.6797.56(+369)#498.38(+368)#172
5.45166455.5697.56(+358)#598.38(+357)#176
6.43791354.5597.56(+257)#698.38(+256)#245
7.43842348.9897.56(+251)#798.38(+251)#251
8.43007330.0097.56(+232)#898.38(+232)#274
9.45267300.0097.56(+202)#998.38(+202)#331
10.43711287.5097.56(+190)#1098.38(+189)#350
11.44690284.6297.56(+187)#1198.38(+186)#356
12.45789265.0097.56(+167)#1298.38(+167)#396
13.43018260.8797.56(+163)#1398.38(+162)#407
14.43972250.0097.56(+152)#1498.38(+152)#438
15.44274249.4697.56(+152)#1598.38(+151)#443
16.43735242.6197.56(+145)#1698.38(+144)#468
17.43142241.6797.56(+144)#1798.38(+143)#474
18.44856240.0097.56(+142)#1898.38(+142)#480
19.43934239.1397.56(+142)#1998.38(+141)#484
20.45888232.2997.56(+135)#2098.38(+134)#510
21.45115214.0897.56(+117)#2198.38(+116)#635
22.44503213.7397.56(+116)#2298.38(+115)#638
23.45815213.3397.56(+116)#2398.38(+115)#645
24.44068213.2197.56(+116)#2498.38(+115)#647
25.43736200.0097.56(+102)#2598.38(+102)#755
26.45734198.1797.56(+101)#2698.38(+99.8)#778
27.45870191.5697.56(+94.0)#2798.38(+93.2)#858
28.44678190.7797.56(+93.2)#2898.38(+92.4)#866
29.44825189.2397.56(+91.7)#2998.38(+90.8)#887
30.44430188.3997.56(+90.8)#3098.38(+90.0)#903
31.43434188.3797.56(+90.8)#3198.38(+90.0)#904
32.45316183.6797.56(+86.1)#3298.38(+85.3)#963
33.43029182.9897.56(+85.4)#3398.38(+84.6)#977
34.44905179.2397.56(+81.7)#3498.38(+80.8)#1,037
35.44304178.6797.56(+81.1)#3598.38(+80.3)#1,047
36.43717175.0097.56(+77.4)#3698.38(+76.6)#1,116
37.43146173.7297.56(+76.2)#3798.38(+75.3)#1,139
38.44699172.8797.56(+75.3)#3898.38(+74.5)#1,154
39.45677168.4297.56(+70.9)#3998.38(+70.0)#1,248
40.43330166.6797.56(+69.1)#4098.38(+68.3)#1,294
41.43432165.0397.56(+67.5)#4198.38(+66.7)#1,323
42.43158164.4797.56(+66.9)#4298.38(+66.1)#1,340
43.43767164.3897.56(+66.8)#4398.38(+66.0)#1,344
44.45172164.0097.56(+66.4)#4498.38(+65.6)#1,349
45.43536163.4197.56(+65.9)#4598.38(+65.0)#1,366
46.45894163.1897.56(+65.6)#4698.38(+64.8)#1,370
47.44640161.2997.56(+63.7)#4798.38(+62.9)#1,418
48.43788161.0997.56(+63.5)#4898.38(+62.7)#1,423
49.43928160.4797.56(+62.9)#4998.38(+62.1)#1,445
50.43343157.8097.56(+60.2)#5098.38(+59.4)#1,512
51.45716156.8697.56(+59.3)#5198.38(+58.5)#1,560
52.43724156.0197.56(+58.4)#5298.38(+57.6)#1,591
53.43761155.5697.56(+58.0)#5398.38(+57.2)#1,609
54.43967152.6397.56(+55.1)#5498.38(+54.2)#1,711
55.44032151.3897.56(+53.8)#5598.38(+53.0)#1,761
56.45671150.8597.56(+53.3)#5698.38(+52.5)#1,792
57.43140150.4297.56(+52.9)#5798.38(+52.0)#1,812
58.43340149.1997.56(+51.6)#5898.38(+50.8)#1,882
59.45848148.6597.56(+51.1)#5998.38(+50.3)#1,913
60.43837148.4497.56(+50.9)#6098.38(+50.1)#1,921
61.44044147.8297.56(+50.3)#6198.38(+49.4)#1,957
62.45070147.5497.56(+50.0)#6298.38(+49.2)#1,974
63.44660147.0697.56(+49.5)#6398.38(+48.7)#1,998
64.44099146.2497.56(+48.7)#6498.38(+47.9)#2,038
65.45893144.6297.56(+47.1)#6598.38(+46.2)#2,116
66.43360144.5497.56(+47.0)#6698.38(+46.2)#2,119
67.43322144.2697.56(+46.7)#6798.38(+45.9)#2,134
68.45782144.1997.56(+46.6)#6898.38(+45.8)#2,138
69.44424144.1297.56(+46.6)#6998.38(+45.7)#2,143
70.43909144.0097.56(+46.4)#7098.38(+45.6)#2,151
71.44702143.3997.56(+45.8)#7198.38(+45.0)#2,180
72.43716143.3497.56(+45.8)#7298.38(+45.0)#2,182
73.44308142.7197.56(+45.2)#7398.38(+44.3)#2,220
74.44619142.0097.56(+44.4)#7498.38(+43.6)#2,263
75.44325141.8897.56(+44.3)#7598.38(+43.5)#2,276
76.43778141.7697.56(+44.2)#7698.38(+43.4)#2,283
77.45378141.4497.56(+43.9)#7798.38(+43.1)#2,306
78.43548140.7597.56(+43.2)#7898.38(+42.4)#2,348
79.43739140.6997.56(+43.1)#7998.38(+42.3)#2,350
80.45301140.3097.56(+42.7)#8098.38(+41.9)#2,384
81.43341139.9497.56(+42.4)#8198.38(+41.6)#2,411
82.45616138.8197.56(+41.2)#8298.38(+40.4)#2,495
83.43760137.3897.56(+39.8)#8398.38(+39.0)#2,602
84.44214137.2997.56(+39.7)#8498.38(+38.9)#2,608
85.43950137.1897.56(+39.6)#8598.38(+38.8)#2,621
86.44113136.8797.56(+39.3)#8698.38(+38.5)#2,654
87.43462136.7897.56(+39.2)#8798.38(+38.4)#2,663
88.43437136.7397.56(+39.2)#8898.38(+38.3)#2,671
89.45685136.4697.56(+38.9)#8998.38(+38.1)#2,706
90.45821135.6297.56(+38.1)#9098.38(+37.2)#2,798
91.45131135.2597.56(+37.7)#9198.38(+36.9)#2,834
92.43905134.3697.56(+36.8)#9298.38(+36.0)#2,913
93.43505134.1597.56(+36.6)#9398.38(+35.8)#2,938
94.45054133.9297.56(+36.4)#9498.38(+35.5)#2,966
95.43002133.7397.56(+36.2)#9598.38(+35.4)#2,987
96.44661133.3397.56(+35.8)#9698.38(+34.9)#3,025
97.44030133.1797.56(+35.6)#9798.38(+34.8)#3,051
98.43463133.0497.56(+35.5)#9898.38(+34.7)#3,063
99.45761133.0297.56(+35.5)#9998.38(+34.6)#3,066
100.43101132.4897.56(+34.9)#10098.38(+34.1)#3,127

Common Questions

What are the Top 10 Zip Codes with the Highest Male / Female Ratio in Ohio?
Top 10 Zip Codes with the Highest Male / Female Ratio in Ohio are:
#1
7,050.00
#2
550.00
#3
511.11
#4
466.67
#5
455.56
#6
354.55
#7
348.98
#8
330.00
#9
300.00
#10
287.50
What zip code has the Highest Male / Female Ratio in Ohio?
45428 has the Highest Male / Female Ratio in Ohio with 7,050.00.
What is the Male to Female Ratio in the State of Ohio?
Male to Female Ratio in Ohio is 97.56.
What is the Male to Female Ratio in the United States?
Male to Female Ratio in the United States is 98.38.