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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 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 New York?
Top 10 Zip Codes with the Most Births per 1,000 Women in New York are:
#1
1,000.0
#2
1,000.0
#3
714.0
#4
617.0
#5
500.0
#6
429.0
#7
413.0
#8
408.0
#9
405.0
#10
400.0
What zip code has the Most Births per 1,000 Women in New York?
13643 has the Most Births per 1,000 Women in New York with 1,000.0.
What is the Number of Births per 1,000 Women in the State of New York?
Number of Births per 1,000 Women in New York is 47.0.
What is the Number of Births per 1,000 Women in the United States?
Number of Births per 1,000 Women in the United States is 51.0.

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

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

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

Zip Codes with the Most Births per 1,000 Women in New York Chart
Zip Code Births / 1,000 Women vs State vs National
1.136431,000.047.0(+953)#151.0(+949)#44
2.124831,000.047.0(+953)#251.0(+949)#45
3.14026714.047.0(+667)#351.0(+663)#78
4.12420617.047.0(+570)#451.0(+566)#112
5.12922500.047.0(+453)#551.0(+449)#157
6.12165429.047.0(+382)#651.0(+378)#204
7.14511413.047.0(+366)#751.0(+362)#217
8.12036408.047.0(+361)#851.0(+357)#223
9.12190405.047.0(+358)#951.0(+354)#225
10.13786400.047.0(+353)#1051.0(+349)#232
11.12517391.047.0(+344)#1151.0(+340)#250
12.13864390.047.0(+343)#1251.0(+339)#251
13.12989384.047.0(+337)#1351.0(+333)#262
14.13655380.047.0(+333)#1451.0(+329)#268
15.13756379.047.0(+332)#1551.0(+328)#269
16.13621374.047.0(+327)#1651.0(+323)#275
17.13633371.047.0(+324)#1751.0(+320)#278
18.12786353.047.0(+306)#1851.0(+302)#307
19.12160337.047.0(+290)#1951.0(+286)#336
20.13832333.047.0(+286)#2051.0(+282)#344
21.12732329.047.0(+282)#2151.0(+278)#364
22.14480320.047.0(+273)#2251.0(+269)#378
23.12932298.047.0(+251)#2351.0(+247)#412
24.13687287.047.0(+240)#2451.0(+236)#448
25.13020286.047.0(+239)#2551.0(+235)#455
26.12849279.047.0(+232)#2651.0(+228)#473
27.12451278.047.0(+231)#2751.0(+227)#474
28.12852276.047.0(+229)#2851.0(+225)#480
29.12952274.047.0(+227)#2951.0(+223)#490
30.12512274.047.0(+227)#3051.0(+223)#491
31.12460273.047.0(+226)#3151.0(+222)#496
32.12466269.047.0(+222)#3251.0(+218)#509
33.13153269.047.0(+222)#3351.0(+218)#512
34.12960262.047.0(+215)#3451.0(+211)#533
35.14842260.047.0(+213)#3551.0(+209)#544
36.11804259.047.0(+212)#3651.0(+208)#546
37.13355259.047.0(+212)#3751.0(+208)#547
38.12847255.047.0(+208)#3851.0(+204)#573
39.12838254.047.0(+207)#3951.0(+203)#578
40.13335240.047.0(+193)#4051.0(+189)#657
41.14864230.047.0(+183)#4151.0(+179)#701
42.14555230.047.0(+183)#4251.0(+179)#702
43.13838229.047.0(+182)#4351.0(+178)#706
44.12751225.047.0(+178)#4451.0(+174)#731
45.13628224.047.0(+177)#4551.0(+173)#736
46.13328223.047.0(+176)#4651.0(+172)#737
47.12409222.047.0(+175)#4751.0(+171)#741
48.12485216.047.0(+169)#4851.0(+165)#790
49.12765216.047.0(+169)#4951.0(+165)#791
50.14069207.047.0(+160)#5051.0(+156)#855
51.12978207.047.0(+160)#5151.0(+156)#857
52.13361206.047.0(+159)#5251.0(+155)#860
53.12729204.047.0(+157)#5351.0(+153)#876
54.13774204.047.0(+157)#5451.0(+153)#879
55.13603203.047.0(+156)#5551.0(+152)#880
56.14726199.047.0(+152)#5651.0(+148)#931
57.12740199.047.0(+152)#5751.0(+148)#935
58.11980195.047.0(+148)#5851.0(+144)#962
59.10952192.047.0(+145)#5951.0(+141)#986
60.13363190.047.0(+143)#6051.0(+139)#1,007
61.12726190.047.0(+143)#6151.0(+139)#1,010
62.12985189.047.0(+142)#6251.0(+138)#1,020
63.12919188.047.0(+141)#6351.0(+137)#1,034
64.12419186.047.0(+139)#6451.0(+135)#1,065
65.13694183.047.0(+136)#6551.0(+132)#1,085
66.14614183.047.0(+136)#6651.0(+132)#1,086
67.13436182.047.0(+135)#6751.0(+131)#1,103
68.12469179.047.0(+132)#6851.0(+128)#1,126
69.13740175.047.0(+128)#6951.0(+124)#1,182
70.14040173.047.0(+126)#7051.0(+122)#1,211
71.12064172.047.0(+125)#7151.0(+121)#1,227
72.11960171.047.0(+124)#7251.0(+120)#1,236
73.14711167.047.0(+120)#7351.0(+116)#1,290
74.11109166.047.0(+119)#7451.0(+115)#1,312
75.13684165.047.0(+118)#7551.0(+114)#1,330
76.12843165.047.0(+118)#7651.0(+114)#1,335
77.14422163.047.0(+116)#7751.0(+112)#1,361
78.14858162.047.0(+115)#7851.0(+111)#1,382
79.12183160.047.0(+113)#7951.0(+109)#1,411
80.13040158.047.0(+111)#8051.0(+107)#1,443
81.14416157.047.0(+110)#8151.0(+106)#1,459
82.13860157.047.0(+110)#8251.0(+106)#1,474
83.13315155.047.0(+108)#8351.0(+104)#1,508
84.14591154.047.0(+107)#8451.0(+103)#1,527
85.12125153.047.0(+106)#8551.0(+102)#1,554
86.11934152.047.0(+105)#8651.0(+101)#1,563
87.13493150.047.0(+103)#8751.0(+99.0)#1,618
88.13839148.047.0(+101)#8851.0(+97.0)#1,661
89.10004146.047.0(+99.0)#8951.0(+95.0)#1,700
90.13060146.047.0(+99.0)#9051.0(+95.0)#1,703
91.13327146.047.0(+99.0)#9151.0(+95.0)#1,706
92.14717146.047.0(+99.0)#9251.0(+95.0)#1,718
93.14613145.047.0(+98.0)#9351.0(+94.0)#1,724
94.14464143.047.0(+96.0)#9451.0(+92.0)#1,765
95.12779143.047.0(+96.0)#9551.0(+92.0)#1,772
96.13796143.047.0(+96.0)#9651.0(+92.0)#1,778
97.14871140.047.0(+93.0)#9751.0(+89.0)#1,861
98.10950139.047.0(+92.0)#9851.0(+88.0)#1,889
99.12151139.047.0(+92.0)#9951.0(+88.0)#1,912
100.14418138.047.0(+91.0)#10051.0(+87.0)#1,937
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