Zip Codes with the Highest Male / Female Ratio in San Diego, CA

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Male / Female Ratio
Population
Families and Households
Female Fertility
Female Fertility (Unmarried)
Race (Community Size)
Race (Percentage)
Ancestry (Community Size)
AfghanAfricanAlaska NativeAlbanianAleutAmericanApacheArabArgentineanArmenianAssyrian / Chaldean / SyriacAustralianAustrianBahamianBangladeshiBarbadianBasqueBelgianBelizeanBhutaneseBlackfeetBolivianBrazilianBritishBritish West IndianBulgarianBurmeseCajunCambodianCanadianCape VerdeanCelticCentral AmericanCentral American IndianCherokeeChickasawChileanChineseChippewaChoctawColombianComancheCosta RicanCreekCroatianCubanCypriotCzechCzechoslovakianDanishDelawareDominicanDutchEastern EuropeanEcuadorianEgyptianEnglishEstonianEthiopianEuropeanFijianFilipinoFinnishFrenchFrench American IndianFrench CanadianGermanGhanaianGreekGuamanian / ChamorroGuatemalanGuyaneseHaitianHonduranHungarianIcelanderIndian (Asian)IndonesianIranianIraqiIrishIroquoisIsraeliItalianJamaicanJapaneseJordanianKenyanKiowaKoreanLaotianLatvianLebaneseLiberianLithuanianLumbeeLuxembourgerMacedonianMalaysianMalteseMenomineeMexicanMexican American IndianMongolianMoroccanNative HawaiianNavajoNepaleseNew ZealanderNicaraguanNigerianNorthern EuropeanNorwegianOsagePakistaniPalestinianPanamanianParaguayanPennsylvania GermanPeruvianPimaPolishPortuguesePotawatomiPuebloPuerto RicanRomanianRussianSalvadoranSamoanScandinavianScotch-IrishScottishSeminoleSerbianSierra LeoneanSiouxSlavicSlovakSloveneSomaliSouth AfricanSouth AmericanSouth American IndianSpaniardSpanishSpanish AmericanSpanish American IndianSri LankanSubsaharan AfricanSudaneseSwedishSwissSyrianThaiTlingit-HaidaTohono O'OdhamTonganTrinidadian and TobagonianTsimshianTurkishUgandanUkrainianUruguayanVenezuelanVietnameseWelshWest IndianYaquiYugoslavianYumanZimbabwean
Ancestry (Percentage)
AfghanAfricanAlaska NativeAlbanianAleutAmericanApacheArabArgentineanArmenianAssyrian / Chaldean / SyriacAustralianAustrianBahamianBangladeshiBarbadianBasqueBelgianBelizeanBhutaneseBlackfeetBolivianBrazilianBritishBritish West IndianBulgarianBurmeseCajunCambodianCanadianCape VerdeanCelticCentral AmericanCentral American IndianCherokeeChickasawChileanChineseChippewaChoctawColombianComancheCosta RicanCreekCroatianCubanCypriotCzechCzechoslovakianDanishDelawareDominicanDutchEastern EuropeanEcuadorianEgyptianEnglishEstonianEthiopianEuropeanFijianFilipinoFinnishFrenchFrench American IndianFrench CanadianGermanGhanaianGreekGuamanian / ChamorroGuatemalanGuyaneseHaitianHonduranHungarianIcelanderIndian (Asian)IndonesianIranianIraqiIrishIroquoisIsraeliItalianJamaicanJapaneseJordanianKenyanKiowaKoreanLaotianLatvianLebaneseLiberianLithuanianLumbeeLuxembourgerMacedonianMalaysianMalteseMenomineeMexicanMexican American IndianMongolianMoroccanNative HawaiianNavajoNepaleseNew ZealanderNicaraguanNigerianNorthern EuropeanNorwegianOsagePakistaniPalestinianPanamanianParaguayanPennsylvania GermanPeruvianPimaPolishPortuguesePotawatomiPuebloPuerto RicanRomanianRussianSalvadoranSamoanScandinavianScotch-IrishScottishSeminoleSerbianSierra LeoneanSiouxSlavicSlovakSloveneSomaliSouth AfricanSouth AmericanSouth American IndianSpaniardSpanishSpanish AmericanSpanish American IndianSri LankanSubsaharan AfricanSudaneseSwedishSwissSyrianThaiTlingit-HaidaTohono O'OdhamTonganTrinidadian and TobagonianTsimshianTurkishUgandanUkrainianUruguayanVenezuelanVietnameseWelshWest IndianYaquiYugoslavianYumanZimbabwean
Immigrant Origin (Total)
AfghanistanAfricaAlbaniaArgentinaArmeniaAsiaAustraliaAustriaBahamasBangladeshBarbadosBelarusBelgiumBelizeBoliviaBosnia and HerzegovinaBrazilBulgariaBurma / MyanmarCambodiaCameroonCanadaCaribbeanCentral AmericaChileChinaColombiaCongoCosta RicaCroatiaCubaCzechoslovakiaDenmarkDominican RepublicEastern AfricaEastern AsiaEastern EuropeEcuadorEgyptEl SalvadorEnglandEritreaEthiopiaEuropeFijiFranceGermanyGhanaGreeceGuatemalaGuyanaHaitiHondurasHong KongHungaryIndiaIndonesiaIranIraqIrelandIsraelItalyJamaicaJapanJordanKazakhstanKenyaKoreaKuwaitLaosLatin AmericaLatviaLebanonLiberiaLithuaniaMalaysiaMexicoMiddle AfricaMoldovaMoroccoNepalNetherlandsNicaraguaNigeriaNorth MacedoniaNorthern AfricaNorthern EuropeNorwayOceaniaPakistanPanamaPeruPhilippinesPolandPortugalRomaniaRussiaSaudi ArabiaScotlandSenegalSerbiaSierra LeoneSingaporeSomaliaSouth AfricaSouth AmericaSouth Central AsiaSouth Eastern AsiaSouthern EuropeSpainSri LankaSt. Vincent and the GrenadinesSudanSwedenSwitzerlandSyriaTaiwanThailandTrinidad and TobagoTurkeyUgandaUkraineUruguayUzbekistanVenezuelaVietnamWestern AfricaWestern AsiaWestern EuropeYemenZaireZimbabwe
Immigrant Origin (Percentage)
AfghanistanAfricaAlbaniaArgentinaArmeniaAsiaAustraliaAustriaBahamasBangladeshBarbadosBelarusBelgiumBelizeBoliviaBosnia and HerzegovinaBrazilBulgariaBurma / MyanmarCambodiaCameroonCanadaCaribbeanCentral AmericaChileChinaColombiaCongoCosta RicaCroatiaCubaCzechoslovakiaDenmarkDominican RepublicEastern AfricaEastern AsiaEastern EuropeEcuadorEgyptEl SalvadorEnglandEritreaEthiopiaEuropeFijiFranceGermanyGhanaGreeceGuatemalaGuyanaHaitiHondurasHong KongHungaryIndiaIndonesiaIranIraqIrelandIsraelItalyJamaicaJapanJordanKazakhstanKenyaKoreaKuwaitLaosLatin AmericaLatviaLebanonLiberiaLithuaniaMalaysiaMexicoMiddle AfricaMoldovaMoroccoNepalNetherlandsNicaraguaNigeriaNorth MacedoniaNorthern AfricaNorthern EuropeNorwayOceaniaPakistanPanamaPeruPhilippinesPolandPortugalRomaniaRussiaSaudi ArabiaScotlandSenegalSerbiaSierra LeoneSingaporeSomaliaSouth AfricaSouth AmericaSouth Central AsiaSouth Eastern AsiaSouthern EuropeSpainSri LankaSt. Vincent and the GrenadinesSudanSwedenSwitzerlandSyriaTaiwanThailandTrinidad and TobagoTurkeyUgandaUkraineUruguayUzbekistanVenezuelaVietnamWestern 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
San Diego
States
California Cities
AlamedaAlhambraAnaheimAntiochApple ValleyArcadiaAuburnBakersfieldBerkeleyBeverly HillsBreaBuena ParkBurbankCamarilloCanoga ParkCanyon CountryCarlsbadCarsonCastro ValleyChicoChinoChula VistaCitrus HeightsClovisComptonConcordCoronaCosta MesaCovinaCulver CityDaly CityDanvilleDavisDesert Hot SpringsDowneyDuarteEdwardsEl CajonEl MonteElk GroveEncinoEscondidoEurekaFairfieldFontanaFremontFresnoFullertonGarden GroveGardenaGlendaleGlendoraGrass ValleyHaywardHemetHesperiaHuntington BeachIndioInglewoodIrvineLa JollaLa MesaLa MiradaLa PuenteLake ElsinoreLakewoodLancasterLemooreLivermoreLodiLoma LindaLompocLong BeachLos AltosLos AngelesLos GatosMaderaMalibuMantecaMenifeeMercedMission ViejoModestoMontereyMonterey ParkMoragaMoreno ValleyMountain ViewMurrietaNapaNewport BeachNorth HollywoodNorthridgeNovatoOaklandOceansideOntarioOrangeOrovilleOxnardPalm DesertPalm SpringsPalmdalePalo AltoPasadenaPerrisPetalumaPleasantonPomonaPortervilleRancho CordovaRancho CucamongaRancho Santa FeReddingRedlandsRedondo BeachRedwood CityRialtoRichmondRiversideRocklinRosevilleSacramentoSalinasSan BernardinoSan ClementeSan DiegoSan FranciscoSan GabrielSan JacintoSan JoseSan LeandroSan Luis ObispoSan MarcosSan MateoSan PedroSan RafaelSan RamonSanta AnaSanta BarbaraSanta ClaraSanta ClaritaSanta CruzSanta MariaSanta MonicaSanta RosaSherman OaksSimi ValleySpring ValleyStocktonSunnyvaleTemeculaThousand OaksTorranceTrabuco CanyonTracyTurlockTustinTwentynine PalmsUplandVacavilleValenciaVallejoVan NuysVenturaVictorvilleVisaliaVistaWalnut CreekWest CovinaWest SacramentoWhittierWoodlandWoodland HillsYorba LindaYuba City
Compare Zip Codes
Comparison Subject

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

84.98
7,286.84
Zip Codes with the Highest Male / Female Ratio in San Diego Map

Zip Codes with the Highest Male / Female Ratio in San Diego, CA

Zip Code Males / 100 Females vs State vs National
1. 92140 7,286.84 100.31 (+7.19k)#2 98.38 (+7.19k)#14
2. 92145 830.46 100.31 (+730)#14 98.38 (+732)#81
3. 92134 731.03 100.31 (+631)#15 98.38 (+633)#95
4. 92135 711.11 100.31 (+611)#16 98.38 (+613)#97
5. 92136 384.16 100.31 (+284)#23 98.38 (+286)#216
6. 92101 129.25 100.31 (+28.9)#190 98.38 (+30.9)#3,498
7. 92109 116.23 100.31 (+15.9)#302 98.38 (+17.8)#6,197
8. 92121 114.25 100.31 (+13.9)#339 98.38 (+15.9)#6,875
9. 92123 112.81 100.31 (+12.5)#355 98.38 (+14.4)#7,378
10. 92108 111.10 100.31 (+10.8)#390 98.38 (+12.7)#8,135
11. 92103 111.00 100.31 (+10.7)#392 98.38 (+12.6)#8,178
12. 92154 110.12 100.31 (+9.81)#412 98.38 (+11.7)#8,602
13. 92126 107.36 100.31 (+7.04)#485 98.38 (+8.97)#10,139
14. 92107 107.19 100.31 (+6.87)#491 98.38 (+8.80)#10,260
15. 92116 107.06 100.31 (+6.75)#498 98.38 (+8.68)#10,347
16. 92122 105.30 100.31 (+4.99)#569 98.38 (+6.92)#11,541
17. 92131 105.11 100.31 (+4.79)#579 98.38 (+6.72)#11,688
18. 92117 105.01 100.31 (+4.69)#581 98.38 (+6.62)#11,755
19. 92104 104.20 100.31 (+3.89)#628 98.38 (+5.82)#12,391
20. 92105 104.03 100.31 (+3.71)#638 98.38 (+5.64)#12,533
21. 92114 103.64 100.31 (+3.32)#655 98.38 (+5.25)#12,861
22. 92106 101.94 100.31 (+1.63)#747 98.38 (+3.56)#14,440
23. 92110 101.51 100.31 (+1.20)#776 98.38 (+3.13)#14,835
24. 92113 100.61 100.31 (+0.295)#850 98.38 (+2.23)#15,730
25. 92102 99.85 100.31 (-0.469)#912 98.38 (+1.46)#16,555
26. 92120 99.05 100.31 (-1.27)#982 98.38 (+0.662)#17,395
27. 92129 97.25 100.31 (-3.06)#1,098 98.38 (-1.13)#19,347
28. 92124 96.48 100.31 (-3.83)#1,144 98.38 (-1.90)#20,136
29. 92127 95.89 100.31 (-4.42)#1,182 98.38 (-2.49)#20,750
30. 92115 95.79 100.31 (-4.52)#1,188 98.38 (-2.59)#20,850
31. 92111 95.69 100.31 (-4.63)#1,197 98.38 (-2.70)#20,955
32. 92130 95.34 100.31 (-4.97)#1,225 98.38 (-3.04)#21,302
33. 92128 95.31 100.31 (-5.00)#1,228 98.38 (-3.07)#21,337
34. 92147 93.55 100.31 (-6.77)#1,339 98.38 (-4.84)#23,146
35. 92139 93.08 100.31 (-7.24)#1,370 98.38 (-5.30)#23,604
36. 92119 84.98 100.31 (-15.3)#1,605 98.38 (-13.4)#28,760

Common Questions

What are the Top 10 Zip Codes with the Highest Male / Female Ratio in San Diego, CA?
Top 10 Zip Codes with the Highest Male / Female Ratio in San Diego, CA are:
#1
7,286.84
#2
830.46
#3
731.03
#4
711.11
#5
384.16
#6
129.25
#7
116.23
#8
114.25
#9
112.81
#10
111.10
What zip code has the Highest Male / Female Ratio in San Diego, CA?
92140 has the Highest Male / Female Ratio in San Diego, CA with 7,286.84.
What is the Male to Female Ratio in San Diego, CA?
Male to Female Ratio in San Diego is 104.28.
What is the Male to Female Ratio in California?
Male to Female Ratio in California is 100.31.
What is the Male to Female Ratio in the United States?
Male to Female Ratio in the United States is 98.38.