Zip Codes with the Most Births per 1,000 Women in Labor Force in Baltimore, MD

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Highest Birth Rate | In Labor Force
Population
Families and Households
Female Fertility
Female Fertility (Unmarried)
Race (Community Size)
Race (Percentage)
Ancestry (Community Size)
AfghanAfricanAlaska NativeAlbanianAmericanArabArgentineanArmenianAustralianAustrianBahamianBarbadianBasqueBelgianBelizeanBermudanBhutaneseBlackfeetBolivianBrazilianBritishBritish West IndianBulgarianBurmeseCajunCanadianCape VerdeanCentral AmericanCentral American IndianCherokeeChickasawChileanChineseChippewaChoctawColombianCosta RicanCreekCroatianCubanCzechCzechoslovakianDanishDelawareDominicanDutchDutch West IndianEastern EuropeanEcuadorianEgyptianEnglishEstonianEthiopianEuropeanFilipinoFinnishFrenchFrench CanadianGermanGhanaianGreekGuamanian / ChamorroGuatemalanGuyaneseHaitianHonduranHungarianIcelanderIndian (Asian)IndonesianIranianIraqiIrishIroquoisIsraeliItalianJamaicanJapaneseJordanianKenyanKoreanLaotianLatvianLebaneseLiberianLithuanianLumbeeMalaysianMalteseMexicanMexican American IndianMoroccanNative HawaiianNavajoNew ZealanderNicaraguanNigerianNorthern EuropeanNorwegianOkinawanPakistaniPalestinianPanamanianParaguayanPennsylvania GermanPeruvianPolishPortuguesePuerto RicanRomanianRussianSalvadoranSamoanScandinavianScotch-IrishScottishSeminoleSenegaleseSerbianSierra LeoneanSiouxSlavicSlovakSloveneSouth AfricanSouth AmericanSouth American IndianSpaniardSpanishSri LankanSubsaharan AfricanSudaneseSwedishSwissSyrianThaiTrinidadian and TobagonianTurkishUgandanUkrainianVenezuelanVietnameseWelshWest IndianYugoslavianZimbabwean
Ancestry (Percentage)
AfghanAfricanAlaska NativeAlbanianAmericanArabArgentineanArmenianAustralianAustrianBahamianBarbadianBasqueBelgianBelizeanBermudanBhutaneseBlackfeetBolivianBrazilianBritishBritish West IndianBulgarianBurmeseCajunCanadianCape VerdeanCentral AmericanCentral American IndianCherokeeChickasawChileanChineseChippewaChoctawColombianCosta RicanCreekCroatianCubanCzechCzechoslovakianDanishDelawareDominicanDutchDutch West IndianEastern EuropeanEcuadorianEgyptianEnglishEstonianEthiopianEuropeanFilipinoFinnishFrenchFrench CanadianGermanGhanaianGreekGuamanian / ChamorroGuatemalanGuyaneseHaitianHonduranHungarianIcelanderIndian (Asian)IndonesianIranianIraqiIrishIroquoisIsraeliItalianJamaicanJapaneseJordanianKenyanKoreanLaotianLatvianLebaneseLiberianLithuanianLumbeeMalaysianMalteseMexicanMexican American IndianMoroccanNative HawaiianNavajoNew ZealanderNicaraguanNigerianNorthern EuropeanNorwegianOkinawanPakistaniPalestinianPanamanianParaguayanPennsylvania GermanPeruvianPolishPortuguesePuerto RicanRomanianRussianSalvadoranSamoanScandinavianScotch-IrishScottishSeminoleSenegaleseSerbianSierra LeoneanSiouxSlavicSlovakSloveneSouth AfricanSouth AmericanSouth American IndianSpaniardSpanishSri LankanSubsaharan AfricanSudaneseSwedishSwissSyrianThaiTrinidadian and TobagonianTurkishUgandanUkrainianVenezuelanVietnameseWelshWest IndianYugoslavianZimbabwean
Immigrant Origin (Total)
AfghanistanAfricaArgentinaArmeniaAsiaAustraliaAustriaAzoresBahamasBangladeshBarbadosBelarusBelgiumBoliviaBosnia and HerzegovinaBrazilBulgariaBurma / MyanmarCameroonCanadaCaribbeanCentral AmericaChileChinaColombiaCongoCosta RicaCubaCzechoslovakiaDenmarkDominicaDominican RepublicEastern AfricaEastern AsiaEastern EuropeEcuadorEgyptEl SalvadorEnglandEritreaEthiopiaEuropeFranceGermanyGhanaGreeceGrenadaGuatemalaGuyanaHaitiHondurasHong KongHungaryIndiaIndonesiaIranIraqIrelandIsraelItalyJamaicaJapanJordanKenyaKoreaLaosLatin AmericaLatviaLebanonLiberiaMalaysiaMexicoMiddle AfricaMoroccoNepalNetherlandsNicaraguaNigeriaNorthern AfricaNorthern EuropeOceaniaPakistanPanamaPeruPhilippinesPolandPortugalRomaniaRussiaSaudi ArabiaScotlandSenegalSerbiaSierra LeoneSingaporeSouth AfricaSouth AmericaSouth Central AsiaSouth Eastern AsiaSouthern EuropeSpainSri LankaSudanSwedenSwitzerlandSyriaTaiwanThailandTrinidad and TobagoTurkeyUgandaUkraineVenezuelaVietnamWest IndiesWestern AfricaWestern AsiaWestern EuropeYemenZaireZimbabwe
Immigrant Origin (Percentage)
AfghanistanAfricaArgentinaArmeniaAsiaAustraliaAustriaAzoresBahamasBangladeshBarbadosBelarusBelgiumBoliviaBosnia and HerzegovinaBrazilBulgariaBurma / MyanmarCameroonCanadaCaribbeanCentral AmericaChileChinaColombiaCongoCosta RicaCubaCzechoslovakiaDenmarkDominicaDominican RepublicEastern AfricaEastern AsiaEastern EuropeEcuadorEgyptEl SalvadorEnglandEritreaEthiopiaEuropeFranceGermanyGhanaGreeceGrenadaGuatemalaGuyanaHaitiHondurasHong KongHungaryIndiaIndonesiaIranIraqIrelandIsraelItalyJamaicaJapanJordanKenyaKoreaLaosLatin AmericaLatviaLebanonLiberiaMalaysiaMexicoMiddle AfricaMoroccoNepalNetherlandsNicaraguaNigeriaNorthern AfricaNorthern EuropeOceaniaPakistanPanamaPeruPhilippinesPolandPortugalRomaniaRussiaSaudi ArabiaScotlandSenegalSerbiaSierra LeoneSingaporeSouth AfricaSouth AmericaSouth Central AsiaSouth Eastern AsiaSouthern EuropeSpainSri LankaSudanSwedenSwitzerlandSyriaTaiwanThailandTrinidad and TobagoTurkeyUgandaUkraineVenezuelaVietnamWest IndiesWestern 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
Baltimore
Compare Zip Codes
Comparison Subject

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

21.0
83.0
Zip Codes with the Most Births per 1,000 Women in Labor Force in Baltimore Map

Zip Codes with the Most Births per 1,000 Women in Labor Force in Baltimore, MD

Zip Code Births / 1,000 Women vs State vs National
1. 21205 83.0 50.0 (+33.0)#61 48.0 (+35.0)#4,914
2. 21239 59.0 50.0 (+9.00)#119 48.0 (+11.0)#8,957
3. 21224 58.0 50.0 (+8.00)#120 48.0 (+10.00)#9,161
4. 21215 57.0 50.0 (+7.00)#125 48.0 (+9.00)#9,397
5. 21211 51.0 50.0 (+1.000)#156 48.0 (+3.00)#11,157
6. 21209 50.0 50.0 (=0.000)#165 48.0 (+2.00)#11,381
7. 21213 50.0 50.0 (=0.000)#166 48.0 (+2.00)#11,390
8. 21216 49.0 50.0 (-1.000)#172 48.0 (+1.000)#11,706
9. 21212 45.0 50.0 (-5.00)#188 48.0 (-3.00)#12,862
10. 21218 43.0 50.0 (-7.00)#193 48.0 (-5.00)#13,466
11. 21230 43.0 50.0 (-7.00)#194 48.0 (-5.00)#13,509
12. 21201 43.0 50.0 (-7.00)#195 48.0 (-5.00)#13,588
13. 21229 40.0 50.0 (-10.00)#211 48.0 (-8.00)#14,482
14. 21206 36.0 50.0 (-14.0)#238 48.0 (-12.0)#15,811
15. 21202 36.0 50.0 (-14.0)#240 48.0 (-12.0)#15,902
16. 21231 35.0 50.0 (-15.0)#246 48.0 (-13.0)#16,228
17. 21223 33.0 50.0 (-17.0)#251 48.0 (-15.0)#16,814
18. 21214 30.0 50.0 (-20.0)#269 48.0 (-18.0)#17,761
19. 21210 22.0 50.0 (-28.0)#294 48.0 (-26.0)#20,023
20. 21217 21.0 50.0 (-29.0)#299 48.0 (-27.0)#20,225

Common Questions

What are the Top 10 Zip Codes with the Most Births per 1,000 Women in Labor Force in Baltimore, MD?
Top 10 Zip Codes with the Most Births per 1,000 Women in Labor Force in Baltimore, MD are:
#1
83.0
#2
59.0
#3
58.0
#4
57.0
#5
51.0
#6
50.0
#7
50.0
#8
49.0
#9
45.0
#10
43.0
What zip code has the Most Births per 1,000 Women in Labor Force in Baltimore, MD?
21205 has the Most Births per 1,000 Women in Labor Force in Baltimore, MD with 83.0.
What is the Number of Births per 1,000 Women in Labor Force in Baltimore, MD?
Number of Births per 1,000 Women in Labor Force in Baltimore is 45.0.
What is the Number of Births per 1,000 Women in Labor Force in Maryland?
Number of Births per 1,000 Women in Labor Force in Maryland is 50.0.
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 48.0.