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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 New York

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Select Geography Level
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Comparison Scope

Common Questions

What are the Top 10 Zip Codes with the Lowest Births per 1,000 Women in Labor Force in New York?
Top 10 Zip Codes with the Lowest Births per 1,000 Women in Labor Force in New York are:
#1
2.0
#2
3.0
#3
3.0
#4
4.0
#5
4.0
#6
4.0
#7
4.0
#8
5.0
#9
5.0
#10
6.0
What zip code has the Lowest Births per 1,000 Women in Labor Force in New York?
14530 has the Lowest Births per 1,000 Women in Labor Force in New York with 2.0.
What is the Number Births per 1,000 Women in Labor Force in the State of New York?
Number Births per 1,000 Women in Labor Force in New York is 46.0.
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 New York

20.0
0.0
Zip Codes with the Lowest Births per 1,000 Women in Labor Force in New York Map

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

Zip Codes with the Lowest Births per 1,000 Women in Labor Force in New York Chart
Zip Code Births / 1,000 Women vs State vs National
1.145302.046.0(-44.0)#147.0(-45.0)#16
2.121543.046.0(-43.0)#247.0(-44.0)#68
3.109733.046.0(-43.0)#347.0(-44.0)#74
4.110204.046.0(-42.0)#447.0(-43.0)#108
5.129864.046.0(-42.0)#547.0(-43.0)#111
6.130534.046.0(-42.0)#647.0(-43.0)#113
7.134604.046.0(-42.0)#747.0(-43.0)#121
8.100385.046.0(-41.0)#847.0(-42.0)#147
9.117495.046.0(-41.0)#947.0(-42.0)#201
10.109306.046.0(-40.0)#1047.0(-41.0)#256
11.148216.046.0(-40.0)#1147.0(-41.0)#293
12.121676.046.0(-40.0)#1247.0(-41.0)#308
13.147446.046.0(-40.0)#1347.0(-41.0)#310
14.144276.046.0(-40.0)#1447.0(-41.0)#313
15.100197.046.0(-39.0)#1547.0(-40.0)#333
16.149037.046.0(-39.0)#1647.0(-40.0)#370
17.123057.046.0(-39.0)#1747.0(-40.0)#372
18.138627.046.0(-39.0)#1847.0(-40.0)#387
19.121377.046.0(-39.0)#1947.0(-40.0)#412
20.148367.046.0(-39.0)#2047.0(-40.0)#435
21.117678.046.0(-38.0)#2147.0(-39.0)#450
22.141038.046.0(-38.0)#2247.0(-39.0)#462
23.144828.046.0(-38.0)#2347.0(-39.0)#471
24.133408.046.0(-38.0)#2447.0(-39.0)#480
25.137538.046.0(-38.0)#2547.0(-39.0)#486
26.120258.046.0(-38.0)#2647.0(-39.0)#492
27.129468.046.0(-38.0)#2747.0(-39.0)#500
28.105488.046.0(-38.0)#2847.0(-39.0)#505
29.119788.046.0(-38.0)#2947.0(-39.0)#511
30.134088.046.0(-38.0)#3047.0(-39.0)#515
31.134768.046.0(-38.0)#3147.0(-39.0)#518
32.100399.046.0(-37.0)#3247.0(-38.0)#562
33.121709.046.0(-37.0)#3347.0(-38.0)#622
34.138119.046.0(-37.0)#3447.0(-38.0)#631
35.125209.046.0(-37.0)#3547.0(-38.0)#643
36.134249.046.0(-37.0)#3647.0(-38.0)#655
37.137559.046.0(-37.0)#3747.0(-38.0)#683
38.1282810.046.0(-36.0)#3847.0(-37.0)#725
39.1303010.046.0(-36.0)#3947.0(-37.0)#770
40.1213810.046.0(-36.0)#4047.0(-37.0)#786
41.1452510.046.0(-36.0)#4147.0(-37.0)#790
42.1364610.046.0(-36.0)#4247.0(-37.0)#795
43.1332010.046.0(-36.0)#4347.0(-37.0)#797
44.1216810.046.0(-36.0)#4447.0(-37.0)#801
45.1334310.046.0(-36.0)#4547.0(-37.0)#806
46.1414111.046.0(-35.0)#4647.0(-36.0)#888
47.1216611.046.0(-35.0)#4747.0(-36.0)#952
48.1404812.046.0(-34.0)#4847.0(-35.0)#1,010
49.1218212.046.0(-34.0)#4947.0(-35.0)#1,012
50.1270112.046.0(-34.0)#5047.0(-35.0)#1,014
51.1136312.046.0(-34.0)#5147.0(-35.0)#1,043
52.1150712.046.0(-34.0)#5247.0(-35.0)#1,047
53.1151412.046.0(-34.0)#5347.0(-35.0)#1,066
54.1194412.046.0(-34.0)#5447.0(-35.0)#1,067
55.1360812.046.0(-34.0)#5547.0(-35.0)#1,127
56.1360712.046.0(-34.0)#5647.0(-35.0)#1,128
57.1000313.046.0(-33.0)#5747.0(-34.0)#1,171
58.1230813.046.0(-33.0)#5847.0(-34.0)#1,206
59.1252813.046.0(-33.0)#5947.0(-34.0)#1,209
60.1000513.046.0(-33.0)#6047.0(-34.0)#1,228
61.1059413.046.0(-33.0)#6147.0(-34.0)#1,257
62.1314013.046.0(-33.0)#6247.0(-34.0)#1,267
63.1473513.046.0(-33.0)#6347.0(-34.0)#1,283
64.1205713.046.0(-33.0)#6447.0(-34.0)#1,295
65.1340913.046.0(-33.0)#6547.0(-34.0)#1,296
66.1278913.046.0(-33.0)#6647.0(-34.0)#1,301
67.1206213.046.0(-33.0)#6747.0(-34.0)#1,313
68.1480413.046.0(-33.0)#6847.0(-34.0)#1,315
69.1375713.046.0(-33.0)#6947.0(-34.0)#1,317
70.1342813.046.0(-33.0)#7047.0(-34.0)#1,320
71.1484613.046.0(-33.0)#7147.0(-34.0)#1,337
72.1123614.046.0(-32.0)#7247.0(-33.0)#1,353
73.1002914.046.0(-32.0)#7347.0(-33.0)#1,354
74.1135414.046.0(-32.0)#7447.0(-33.0)#1,355
75.1176314.046.0(-32.0)#7547.0(-33.0)#1,365
76.1172614.046.0(-32.0)#7647.0(-33.0)#1,377
77.1455914.046.0(-32.0)#7747.0(-33.0)#1,387
78.1173314.046.0(-32.0)#7847.0(-33.0)#1,391
79.1441114.046.0(-32.0)#7947.0(-33.0)#1,400
80.1322414.046.0(-32.0)#8047.0(-33.0)#1,418
81.1003215.046.0(-31.0)#8147.0(-32.0)#1,559
82.1142215.046.0(-31.0)#8247.0(-32.0)#1,569
83.1001215.046.0(-31.0)#8347.0(-32.0)#1,584
84.1154515.046.0(-31.0)#8447.0(-32.0)#1,610
85.1098315.046.0(-31.0)#8547.0(-32.0)#1,641
86.1211715.046.0(-31.0)#8647.0(-32.0)#1,675
87.1210615.046.0(-31.0)#8747.0(-32.0)#1,691
88.1471115.046.0(-31.0)#8847.0(-32.0)#1,694
89.1373615.046.0(-31.0)#8947.0(-32.0)#1,695
90.1474115.046.0(-31.0)#9047.0(-32.0)#1,701
91.1405415.046.0(-31.0)#9147.0(-32.0)#1,714
92.1123716.046.0(-30.0)#9247.0(-31.0)#1,741
93.1385016.046.0(-30.0)#9347.0(-31.0)#1,760
94.1490116.046.0(-30.0)#9447.0(-31.0)#1,775
95.1060116.046.0(-30.0)#9547.0(-31.0)#1,792
96.1257016.046.0(-30.0)#9647.0(-31.0)#1,818
97.1057716.046.0(-30.0)#9747.0(-31.0)#1,821
98.1480216.046.0(-30.0)#9847.0(-31.0)#1,836
99.1348016.046.0(-30.0)#9947.0(-31.0)#1,859
100.1051116.046.0(-30.0)#10047.0(-31.0)#1,882
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