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Demographic Comparison
Population
Highest PopulationHighest Population DensityLowest Population DensityMale / Female RatioFemale / Male RatioOldest PopulationOldest Population | MaleOldest Population | FemaleYoungest PopulationYoungest Population | MaleYoungest Population | Female
Families and Households
Largest Family SizeLargest Household SizeSmallest Family SizeSmallest Household Size
Female Fertility
Highest Birth Rate | All WomenHighest Birth Rate | Women 15-19Highest Birth Rate | Women 35+Highest Birth Rate | Below PovertyHighest Birth Rate | Public IncomeHighest Birth Rate | In Labor ForceLowest Birth Rate | All WomenLowest Birth Rate | Women 15-19Lowest Birth Rate | Women 35+Lowest Birth Rate | Below PovertyLowest Birth Rate | Public IncomeLowest Birth Rate | In Labor Force
Female Fertility (Unmarried)
Highest Illegitimacy | All WomenHighest Illegitimacy | Women 15-19Highest Illegitimacy | Women 35+Lowest Illegitimacy | All WomenLowest Illegitimacy | Women 15-19Lowest Illegitimacy | Women 35+
Race (Community Size)
AsianBlack / African AmericanHawaiian / PacificHispanic or LatinoNative / AlaskanWhite / Caucasian
Race (Percentage)
AsianBlack / African AmericanHawaiian / PacificHispanic or LatinoNative / AlaskanWhite / Caucasian
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
Economic Comparison
Income
Highest Per Capita IncomeHighest Earnings | MaleHighest Earnings | FemaleHighest Wage/Income Gap ($)Highest Wage/Income Gap (%)Highest Inequality / Gini IndexLowest Per Capita IncomeLowest Earnings | MaleLowest Earnings | FemaleLowest Wage/Income Gap ($)Lowest Wage/Income Gap (%)Lowest Inequality / Gini Index
Income (Families)
Highest Family IncomeLowest Family IncomeFamily Income | $0-10kFamily Income | $100k+Family Income | $200k+
Income (Households)
Highest Household IncomeLowest Household IncomeHousehold Income | $0-10kHousehold Income | $200k+Household Income | $100k+
Poverty
Highest PovertyHighest Poverty | MaleHighest Poverty | FemaleHighest Poverty | Female 18-24Highest Poverty | Female 25-34Highest Poverty | Child 0-5Highest Poverty | Child 0-16Highest Poverty | Boys 0-16Highest Poverty | Girls 0-16Highest Poverty | Seniors 65+Highest Poverty | Seniors 75+ Lowest PovertyLowest Poverty | MaleLowest Poverty | FemaleLowest Poverty | Child 0-5Lowest Poverty | Child 0-16Lowest Poverty | Boys 0-16Lowest Poverty | Girls 0-16Lowest Poverty | Seniors 65+Lowest Poverty | Seniors 75+
Poverty (Families)
Highest Family PovertyHighest Poverty | Married CoupleHighest Poverty | Single MaleHighest Poverty | Single FemaleHighest Poverty | Single FatherHighest Poverty | Single MotherLowest Family PovertyLowest Poverty | Married CoupleLowest Poverty | Single MaleLowest Poverty | Single FemaleLowest Poverty | Single FatherLowest Poverty | Single Mother
Unemployment
Highest UnemploymentHighest Unemployment | MaleHighest Unemployment | FemaleHighest Unemployment | Youth < 25Highest Unemployment | Senior > 65Lowest UnemploymentLowest Unemployment | MaleLowest Unemployment | FemaleLowest Unemployment | Youth < 25Lowest Unemployment | Senior > 65
Employment Occupations
Architecture & EngineeringArts, Media & EntertainmentBusiness & FinancialCleaning & MaintenanceCommunity & Social Service Computer & MathematicsComputer, Engineering & ScienceConstruction & ExtractionEducation Instruction & LibraryEducation, Arts & MediaFarming, Fishing & ForestryFirefighting & PreventionFood Preparation & ServingHealth Diagnosing & TreatingHealth TechnologistsHealthcare SupportInstallation, Maintenance & RepairLaw EnforcementLegal Services & SupportLife, Physical & Social ScienceManagementMaterial MovingOffice & AdministrationPersonal Care and ServiceProductionSales & RelatedSecurity & ProtectionTransportation
Employment Industries
Accommodation & Food ServicesAdministrative & Support ServicesAgriculture, Fishing & HuntingArts, Entertainment & RecreationConstructionEducational ServicesEnterprise ManagementFinance & InsuranceHealth Care & Social AssistanceInformation & TechnologyManufacturingMining, Quarrying, & ExtractionProfessional & Scientific ServicesPublic AdministrationReal Estate, Rental & LeasingRetail TradeTransportation & WarehousingUtilitiesWholesale Trade
Employer Class
Private Company EmployeesSelf-Employed / IncorporatedSelf-Employed / Not IncorporatedNot-for-profit OrganizationsLocal Government EmployeesState Government EmployeesFederal Government EmployeesUnpaid Family Workers
Commute Time
Longest CommuteLongest Commute | MaleLongest Commute | FemaleShortest CommuteShortest Commute | MaleShortest Commute | Female
Commute Means
Drive | AloneDrive | CarpoolPublic TransitTaxi / CabWalk to WorkWork from Home
Education Comparison
School Enrollment
In Private SchoolNursery / PreschoolKindergartenElementary SchoolMiddle SchoolHigh SchoolCollegeUniversity
Education by Degree Field
Computers and MathematicsBio, Nature & AgriculturalPhysical and Health SciencesPsychologySocial SciencesEngineeringMultidisciplinary StudiesScience and EngineeringBusinessEducationLiterature and LanguagesLiberal Arts and HistoryVisual and Performing ArtsCommunicationsArts and Humanities
Housing Comparison
Occupancy
Highest Owner-OccupiedHighest Renter-OccupiedLowest Owner-OccupiedLowest Renter-Occupied
Finances
Highest Median Housing CostsHighest Property PricesHighest Owner Housing CostsHighest Renter Housing CostsHighest Housing Costs / IncomeLowest Median Housing CostsLowest Property PricesLowest Owner Housing CostsLowest Renter Housing CostsLowest Housing Costs / Income
Physical Characteristics
Detached Home ResidencyCondo/Apartment ResidencyUtility Gas HeatingBottled Gas / LP HeatingElectrical HeatingFuel Oil HeatingCoal / Coke HeatingFuel-less HeatingHouseholds without a CarsHouseholds with 1 or more CarsHouseholds with 2 or more CarsHouseholds with 3 or more Cars

Zip Codes with the Lowest Births per 1,000 Women in Labor Force in Kentucky

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Common Questions

What are the Top 10 Zip Codes with the Lowest Births per 1,000 Women in Labor Force in Kentucky?
Top 10 Zip Codes with the Lowest Births per 1,000 Women in Labor Force in Kentucky are:
#1
2.0
#2
3.0
#3
3.0
#4
3.0
#5
5.0
#6
5.0
#7
5.0
#8
5.0
#9
5.0
#10
6.0
What zip code has the Lowest Births per 1,000 Women in Labor Force in Kentucky?
40390 has the Lowest Births per 1,000 Women in Labor Force in Kentucky with 2.0.
What is the Number Births per 1,000 Women in Labor Force in the State of Kentucky?
Number Births per 1,000 Women in Labor Force in Kentucky is 49.0.
What is the Number Births per 1,000 Women in Labor Force in the United States?
Number Births per 1,000 Women in Labor Force in the United States is 47.0.

Map of Zip Codes with the Lowest Births per 1,000 Women in Labor Force in Kentucky

40.0
0.0
Zip Codes with the Lowest Births per 1,000 Women in Labor Force in Kentucky Map

Zip Codes with the Lowest Births per 1,000 Women in Labor Force in Kentucky

Zip Codes with the Lowest Births per 1,000 Women in Labor Force in Kentucky Chart
Zip Code Births / 1,000 Women vs State vs National
1.403902.049.0(-47.0)#147.0(-45.0)#15
2.400783.049.0(-46.0)#247.0(-44.0)#70
3.420493.049.0(-46.0)#347.0(-44.0)#80
4.424623.049.0(-46.0)#447.0(-44.0)#82
5.400065.049.0(-44.0)#547.0(-42.0)#191
6.403475.049.0(-44.0)#647.0(-42.0)#197
7.412245.049.0(-44.0)#747.0(-42.0)#198
8.421605.049.0(-44.0)#847.0(-42.0)#218
9.423505.049.0(-44.0)#947.0(-42.0)#228
10.414726.049.0(-43.0)#1047.0(-41.0)#253
11.408316.049.0(-43.0)#1147.0(-41.0)#278
12.424426.049.0(-43.0)#1247.0(-41.0)#292
13.427657.049.0(-42.0)#1347.0(-40.0)#373
14.411697.049.0(-42.0)#1447.0(-40.0)#381
15.427577.049.0(-42.0)#1547.0(-40.0)#395
16.400117.049.0(-42.0)#1647.0(-40.0)#408
17.4011910.049.0(-39.0)#1747.0(-37.0)#798
18.4246410.049.0(-39.0)#1847.0(-37.0)#810
19.4160110.049.0(-39.0)#1947.0(-37.0)#826
20.4222011.049.0(-38.0)#2047.0(-36.0)#895
21.4153712.049.0(-37.0)#2147.0(-35.0)#1,078
22.4203112.049.0(-37.0)#2247.0(-35.0)#1,092
23.4031213.049.0(-36.0)#2347.0(-34.0)#1,252
24.4043713.049.0(-36.0)#2447.0(-34.0)#1,262
25.4235113.049.0(-36.0)#2547.0(-34.0)#1,263
26.4205513.049.0(-36.0)#2647.0(-34.0)#1,292
27.4005013.049.0(-36.0)#2747.0(-34.0)#1,305
28.4205613.049.0(-36.0)#2847.0(-34.0)#1,311
29.4050814.049.0(-35.0)#2947.0(-33.0)#1,371
30.4110214.049.0(-35.0)#3047.0(-33.0)#1,384
31.4074014.049.0(-35.0)#3147.0(-33.0)#1,454
32.4004514.049.0(-35.0)#3347.0(-33.0)#1,471
33.4105914.049.0(-35.0)#3447.0(-33.0)#1,472
34.4214015.049.0(-34.0)#3547.0(-32.0)#1,723
35.4202516.049.0(-33.0)#3647.0(-31.0)#1,764
36.4245016.049.0(-33.0)#3747.0(-31.0)#1,845
37.4100216.049.0(-33.0)#3847.0(-31.0)#1,871
38.4228616.049.0(-33.0)#3947.0(-31.0)#1,887
39.4232717.049.0(-32.0)#4047.0(-30.0)#2,072
40.4234917.049.0(-32.0)#4147.0(-30.0)#2,123
41.4213318.049.0(-31.0)#4247.0(-29.0)#2,346
42.4096219.049.0(-30.0)#4347.0(-28.0)#2,443
43.4212919.049.0(-30.0)#4447.0(-28.0)#2,498
44.4183119.049.0(-30.0)#4547.0(-28.0)#2,576
45.4210320.049.0(-29.0)#4647.0(-27.0)#2,652
46.4002320.049.0(-29.0)#4747.0(-27.0)#2,725
47.4274921.049.0(-28.0)#4847.0(-26.0)#2,972
48.4005721.049.0(-28.0)#4947.0(-26.0)#2,989
49.4210422.049.0(-27.0)#5047.0(-25.0)#3,100
50.4223422.049.0(-27.0)#5147.0(-25.0)#3,276
51.4020823.049.0(-26.0)#5247.0(-24.0)#3,422
52.4114323.049.0(-26.0)#5347.0(-24.0)#3,433
53.4212223.049.0(-26.0)#5447.0(-24.0)#3,490
54.4272623.049.0(-26.0)#5547.0(-24.0)#3,497
55.4272123.049.0(-26.0)#5647.0(-24.0)#3,516
56.4082323.049.0(-26.0)#5747.0(-24.0)#3,519
57.4003723.049.0(-26.0)#5847.0(-24.0)#3,533
58.4106323.049.0(-26.0)#5947.0(-24.0)#3,539
59.4225423.049.0(-26.0)#6047.0(-24.0)#3,603
60.4044724.049.0(-25.0)#6147.0(-23.0)#3,736
61.4037924.049.0(-25.0)#6247.0(-23.0)#3,774
62.4051425.049.0(-24.0)#6347.0(-22.0)#3,954
63.4221125.049.0(-24.0)#6447.0(-22.0)#3,978
64.4116825.049.0(-24.0)#6547.0(-22.0)#4,041
65.4015525.049.0(-24.0)#6647.0(-22.0)#4,110
66.4022326.049.0(-23.0)#6747.0(-21.0)#4,208
67.4103526.049.0(-23.0)#6847.0(-21.0)#4,258
68.4114426.049.0(-23.0)#6947.0(-21.0)#4,272
69.4029927.049.0(-22.0)#7047.0(-20.0)#4,452
70.4107627.049.0(-22.0)#7147.0(-20.0)#4,521
71.4100827.049.0(-22.0)#7247.0(-20.0)#4,582
72.4041927.049.0(-22.0)#7347.0(-20.0)#4,605
73.4050328.049.0(-21.0)#7447.0(-19.0)#4,764
74.4020228.049.0(-21.0)#7547.0(-19.0)#4,867
75.4002628.049.0(-21.0)#7647.0(-19.0)#4,877
76.4220628.049.0(-21.0)#7747.0(-19.0)#4,885
77.4263428.049.0(-21.0)#7847.0(-19.0)#4,975
78.4232528.049.0(-21.0)#7947.0(-19.0)#4,980
79.4110129.049.0(-20.0)#8047.0(-18.0)#5,115
80.4021729.049.0(-20.0)#8147.0(-18.0)#5,154
81.4241029.049.0(-20.0)#8247.0(-18.0)#5,272
82.4042230.049.0(-19.0)#8347.0(-17.0)#5,386
83.4020430.049.0(-19.0)#8447.0(-17.0)#5,432
84.4006730.049.0(-19.0)#8547.0(-17.0)#5,499
85.4262930.049.0(-19.0)#8647.0(-17.0)#5,506
86.4051630.049.0(-19.0)#8747.0(-17.0)#5,537
87.4093530.049.0(-19.0)#8847.0(-17.0)#5,549
88.4203630.049.0(-19.0)#8947.0(-17.0)#5,584
89.4035131.049.0(-18.0)#9047.0(-16.0)#5,710
90.4046131.049.0(-18.0)#9147.0(-16.0)#5,862
91.4202331.049.0(-18.0)#9247.0(-16.0)#5,866
92.4182231.049.0(-18.0)#9347.0(-16.0)#5,876
93.4021932.049.0(-17.0)#9447.0(-15.0)#5,967
94.4200332.049.0(-17.0)#9547.0(-15.0)#6,001
95.4010832.049.0(-17.0)#9647.0(-15.0)#6,062
96.4271732.049.0(-17.0)#9747.0(-15.0)#6,128
97.4073432.049.0(-17.0)#9847.0(-15.0)#6,157
98.4240432.049.0(-17.0)#9947.0(-15.0)#6,196
99.4237232.049.0(-17.0)#10047.0(-15.0)#6,220
100.4245332.049.0(-17.0)#10147.0(-15.0)#6,248
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