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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 Most Births per 1,000 Women in Labor Force in New York

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Comparison Scope

Common Questions

What are the Top 10 Zip Codes with the Most Births per 1,000 Women in Labor Force in New York?
Top 10 Zip Codes with the Most Births per 1,000 Women in Labor Force in New York are:
#1
1,000.0
#2
1,000.0
#3
714.0
#4
617.0
#5
545.0
#6
534.0
#7
524.0
#8
489.0
#9
447.0
#10
446.0
What zip code has the Most Births per 1,000 Women in Labor Force in New York?
13020 has the Most Births per 1,000 Women in Labor Force in New York with 1,000.0.
What is the Number of Births per 1,000 Women in Labor Force in the State of New York?
Number of Births per 1,000 Women in Labor Force in New York is 46.0.
What is the Number of Births per 1,000 Women in Labor Force in the United States?
Number of Births per 1,000 Women in Labor Force in the United States is 47.0.

Map of Zip Codes with the Most Births per 1,000 Women in Labor Force in New York

0.0
1,000.0
Zip Codes with the Most Births per 1,000 Women in Labor Force in New York Map

Zip Codes with the Most Births per 1,000 Women in Labor Force in New York

Zip Codes with the Most Births per 1,000 Women in Labor Force in New York Chart
Zip Code Births / 1,000 Women vs State vs National
1.130201,000.046.0(+954)#147.0(+953)#41
2.134361,000.046.0(+954)#247.0(+953)#42
3.14026714.046.0(+668)#347.0(+667)#68
4.12420617.046.0(+571)#447.0(+570)#88
5.14069545.046.0(+499)#547.0(+498)#116
6.13621534.046.0(+488)#647.0(+487)#123
7.13774524.046.0(+478)#747.0(+477)#130
8.12960489.046.0(+443)#847.0(+442)#153
9.14842447.046.0(+401)#947.0(+400)#180
10.13838446.046.0(+400)#1047.0(+399)#183
11.12989444.046.0(+398)#1147.0(+397)#184
12.12460429.046.0(+383)#1247.0(+382)#200
13.12165429.046.0(+383)#1347.0(+382)#201
14.13786400.046.0(+354)#1447.0(+353)#229
15.12517391.046.0(+345)#1547.0(+344)#243
16.12160385.046.0(+339)#1647.0(+338)#254
17.12932379.046.0(+333)#1747.0(+332)#260
18.13756379.046.0(+333)#1847.0(+332)#262
19.14480371.046.0(+325)#1947.0(+324)#269
20.11804360.046.0(+314)#2047.0(+313)#285
21.12751354.046.0(+308)#2147.0(+307)#293
22.12952333.046.0(+287)#2247.0(+286)#333
23.13633333.046.0(+287)#2347.0(+286)#336
24.12732329.046.0(+283)#2447.0(+282)#350
25.12451324.046.0(+278)#2547.0(+277)#357
26.12847324.046.0(+278)#2647.0(+277)#361
27.13655310.046.0(+264)#2747.0(+263)#385
28.12190310.046.0(+264)#2847.0(+263)#389
29.13153305.046.0(+259)#2947.0(+258)#410
30.12838299.046.0(+253)#3047.0(+252)#424
31.12729297.046.0(+251)#3147.0(+250)#432
32.12469288.046.0(+242)#3247.0(+241)#457
33.13687287.046.0(+241)#3347.0(+240)#459
34.12512274.046.0(+228)#3447.0(+227)#500
35.14864272.046.0(+226)#3547.0(+225)#515
36.12765257.046.0(+211)#3647.0(+210)#561
37.12457254.046.0(+208)#3747.0(+207)#578
38.14555253.046.0(+207)#3847.0(+206)#580
39.14783250.046.0(+204)#3947.0(+203)#601
40.13694246.046.0(+200)#4047.0(+199)#618
41.12726244.046.0(+198)#4147.0(+197)#625
42.12485239.046.0(+193)#4247.0(+192)#660
43.13670231.046.0(+185)#4347.0(+184)#704
44.10952227.046.0(+181)#4447.0(+180)#725
45.13833218.046.0(+172)#4547.0(+171)#772
46.12919216.046.0(+170)#4647.0(+169)#783
47.11980213.046.0(+167)#4747.0(+166)#798
48.13740213.046.0(+167)#4847.0(+166)#802
49.11934210.046.0(+164)#4947.0(+163)#823
50.13040210.046.0(+164)#5047.0(+163)#826
51.14040208.046.0(+162)#5147.0(+161)#835
52.12978207.046.0(+161)#5247.0(+160)#848
53.12125205.046.0(+159)#5347.0(+158)#853
54.12531203.046.0(+157)#5447.0(+156)#869
55.13839203.046.0(+157)#5547.0(+156)#870
56.12419202.046.0(+156)#5647.0(+155)#881
57.12768200.046.0(+154)#5747.0(+153)#896
58.14871198.046.0(+152)#5847.0(+151)#927
59.13328197.046.0(+151)#5947.0(+150)#937
60.12779194.046.0(+148)#6047.0(+147)#960
61.13470193.046.0(+147)#6147.0(+146)#979
62.12515179.046.0(+133)#6247.0(+132)#1,117
63.14860179.046.0(+133)#6347.0(+132)#1,118
64.12409179.046.0(+133)#6447.0(+132)#1,120
65.14422178.046.0(+132)#6547.0(+131)#1,125
66.13485177.046.0(+131)#6647.0(+130)#1,136
67.13101174.046.0(+128)#6747.0(+127)#1,169
68.12064172.046.0(+126)#6847.0(+125)#1,204
69.13136172.046.0(+126)#6947.0(+125)#1,205
70.13327169.046.0(+123)#7047.0(+122)#1,231
71.11109168.046.0(+122)#7147.0(+121)#1,239
72.10962164.046.0(+118)#7247.0(+117)#1,304
73.12466163.046.0(+117)#7347.0(+116)#1,318
74.10004160.046.0(+114)#7447.0(+113)#1,357
75.13132160.046.0(+114)#7547.0(+113)#1,359
76.14723159.046.0(+113)#7647.0(+112)#1,381
77.12077158.046.0(+112)#7747.0(+111)#1,386
78.13825158.046.0(+112)#7847.0(+111)#1,390
79.13334158.046.0(+112)#7947.0(+111)#1,398
80.12204157.046.0(+111)#8047.0(+110)#1,410
81.14080157.046.0(+111)#8147.0(+110)#1,414
82.11968156.046.0(+110)#8247.0(+109)#1,429
83.13652154.046.0(+108)#8347.0(+107)#1,463
84.12035154.046.0(+108)#8447.0(+107)#1,472
85.14037152.046.0(+106)#8547.0(+105)#1,503
86.12754151.046.0(+105)#8647.0(+104)#1,515
87.13361149.046.0(+103)#8747.0(+102)#1,567
88.12428148.046.0(+102)#8847.0(+101)#1,574
89.11954148.046.0(+102)#8947.0(+101)#1,579
90.14591148.046.0(+102)#9047.0(+101)#1,589
91.11219146.046.0(+100.0)#9147.0(+99.0)#1,628
92.12809145.046.0(+99.0)#9247.0(+98.0)#1,651
93.10923141.046.0(+95.0)#9347.0(+94.0)#1,742
94.12758141.046.0(+95.0)#9447.0(+94.0)#1,748
95.12565141.046.0(+95.0)#9547.0(+94.0)#1,753
96.14416140.046.0(+94.0)#9647.0(+93.0)#1,768
97.13844140.046.0(+94.0)#9747.0(+93.0)#1,777
98.13778139.046.0(+93.0)#9847.0(+92.0)#1,786
99.13317136.046.0(+90.0)#9947.0(+89.0)#1,843
100.12975136.046.0(+90.0)#10047.0(+89.0)#1,864
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