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

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Lowest Birth Rate | In Labor Force
Population
Families and Households
Female Fertility
Female Fertility (Unmarried)
Race (Community Size)
Race (Percentage)
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
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
Maryland
Compare Zip Codes
Comparison Subject

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

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

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

Zip Code Births / 1,000 Women vs State vs National
1. 21620 4.0 50.0 (-46.0)#1 48.0 (-44.0)#100
2. 20769 4.0 50.0 (-46.0)#2 48.0 (-44.0)#115
3. 21651 5.0 50.0 (-45.0)#3 48.0 (-43.0)#219
4. 21623 5.0 50.0 (-45.0)#4 48.0 (-43.0)#220
5. 21643 8.0 50.0 (-42.0)#5 48.0 (-40.0)#473
6. 21140 9.0 50.0 (-41.0)#6 48.0 (-39.0)#610
7. 20905 10.0 50.0 (-40.0)#7 48.0 (-38.0)#691
8. 21402 11.0 50.0 (-39.0)#8 48.0 (-37.0)#944
9. 21649 11.0 50.0 (-39.0)#9 48.0 (-37.0)#951
10. 21659 11.0 50.0 (-39.0)#10 48.0 (-37.0)#972
11. 21861 11.0 50.0 (-39.0)#11 48.0 (-37.0)#985
12. 21078 13.0 50.0 (-37.0)#12 48.0 (-35.0)#1,183
13. 21163 13.0 50.0 (-37.0)#13 48.0 (-35.0)#1,236
14. 20616 13.0 50.0 (-37.0)#14 48.0 (-35.0)#1,239
15. 21536 13.0 50.0 (-37.0)#15 48.0 (-35.0)#1,271
16. 20607 14.0 50.0 (-36.0)#16 48.0 (-34.0)#1,390
17. 20833 14.0 50.0 (-36.0)#17 48.0 (-34.0)#1,415
18. 21658 14.0 50.0 (-36.0)#18 48.0 (-34.0)#1,450
19. 21738 14.0 50.0 (-36.0)#19 48.0 (-34.0)#1,451
20. 20754 15.0 50.0 (-35.0)#20 48.0 (-33.0)#1,616
21. 20685 15.0 50.0 (-35.0)#21 48.0 (-33.0)#1,621
22. 21801 16.0 50.0 (-34.0)#22 48.0 (-32.0)#1,741
23. 21673 17.0 50.0 (-33.0)#23 48.0 (-31.0)#2,046
24. 21913 17.0 50.0 (-33.0)#24 48.0 (-31.0)#2,100
25. 21090 18.0 50.0 (-32.0)#25 48.0 (-30.0)#2,189
26. 21678 18.0 50.0 (-32.0)#26 48.0 (-30.0)#2,280
27. 20745 19.0 50.0 (-31.0)#27 48.0 (-29.0)#2,342
28. 21108 20.0 50.0 (-30.0)#28 48.0 (-28.0)#2,605
29. 21029 20.0 50.0 (-30.0)#29 48.0 (-28.0)#2,627
30. 21219 20.0 50.0 (-30.0)#30 48.0 (-28.0)#2,649
31. 21217 21.0 50.0 (-29.0)#31 48.0 (-27.0)#2,828
32. 20746 21.0 50.0 (-29.0)#32 48.0 (-27.0)#2,832
33. 21204 21.0 50.0 (-29.0)#33 48.0 (-27.0)#2,864
34. 21226 21.0 50.0 (-29.0)#34 48.0 (-27.0)#2,943
35. 21161 21.0 50.0 (-29.0)#35 48.0 (-27.0)#2,949
36. 21053 21.0 50.0 (-29.0)#36 48.0 (-27.0)#2,984
37. 21541 21.0 50.0 (-29.0)#37 48.0 (-27.0)#3,014
38. 20816 22.0 50.0 (-28.0)#38 48.0 (-26.0)#3,133
39. 21210 22.0 50.0 (-28.0)#39 48.0 (-26.0)#3,140
40. 21795 22.0 50.0 (-28.0)#40 48.0 (-26.0)#3,163
41. 21776 22.0 50.0 (-28.0)#41 48.0 (-26.0)#3,193
42. 21005 22.0 50.0 (-28.0)#42 48.0 (-26.0)#3,237
43. 20733 22.0 50.0 (-28.0)#43 48.0 (-26.0)#3,238
44. 21042 23.0 50.0 (-27.0)#44 48.0 (-25.0)#3,328
45. 21727 23.0 50.0 (-27.0)#45 48.0 (-25.0)#3,446
46. 20748 24.0 50.0 (-26.0)#46 48.0 (-24.0)#3,590
47. 21015 24.0 50.0 (-26.0)#47 48.0 (-24.0)#3,616
48. 20841 24.0 50.0 (-26.0)#48 48.0 (-24.0)#3,709
49. 20777 24.0 50.0 (-26.0)#49 48.0 (-24.0)#3,773
50. 20842 24.0 50.0 (-26.0)#50 48.0 (-24.0)#3,802
51. 21044 25.0 50.0 (-25.0)#51 48.0 (-23.0)#3,874
52. 20855 26.0 50.0 (-24.0)#52 48.0 (-22.0)#4,230
53. 21804 27.0 50.0 (-23.0)#53 48.0 (-21.0)#4,474
54. 21629 27.0 50.0 (-23.0)#54 48.0 (-21.0)#4,587
55. 21722 27.0 50.0 (-23.0)#55 48.0 (-21.0)#4,610
56. 21904 27.0 50.0 (-23.0)#56 48.0 (-21.0)#4,614
57. 20740 28.0 50.0 (-22.0)#57 48.0 (-20.0)#4,763
58. 20634 28.0 50.0 (-22.0)#58 48.0 (-20.0)#4,890
59. 20714 28.0 50.0 (-22.0)#59 48.0 (-20.0)#4,923
60. 20838 28.0 50.0 (-22.0)#60 48.0 (-20.0)#5,021
61. 20705 29.0 50.0 (-21.0)#61 48.0 (-19.0)#5,073
62. 20657 29.0 50.0 (-21.0)#62 48.0 (-19.0)#5,102
63. 21550 29.0 50.0 (-21.0)#63 48.0 (-19.0)#5,130
64. 20812 29.0 50.0 (-21.0)#64 48.0 (-19.0)#5,313
65. 20770 30.0 50.0 (-20.0)#65 48.0 (-18.0)#5,381
66. 21214 30.0 50.0 (-20.0)#66 48.0 (-18.0)#5,419
67. 21660 30.0 50.0 (-20.0)#67 48.0 (-18.0)#5,527
68. 21635 30.0 50.0 (-20.0)#68 48.0 (-18.0)#5,564
69. 20735 31.0 50.0 (-19.0)#69 48.0 (-17.0)#5,629
70. 21403 31.0 50.0 (-19.0)#70 48.0 (-17.0)#5,656
71. 21783 31.0 50.0 (-19.0)#71 48.0 (-17.0)#5,756
72. 21132 31.0 50.0 (-19.0)#72 48.0 (-17.0)#5,834
73. 21093 32.0 50.0 (-18.0)#73 48.0 (-16.0)#5,937
74. 21286 32.0 50.0 (-18.0)#74 48.0 (-16.0)#6,004
75. 21770 32.0 50.0 (-18.0)#75 48.0 (-16.0)#6,072
76. 21638 32.0 50.0 (-18.0)#76 48.0 (-16.0)#6,105
77. 21028 32.0 50.0 (-18.0)#77 48.0 (-16.0)#6,139
78. 21668 32.0 50.0 (-18.0)#78 48.0 (-16.0)#6,171
79. 21223 33.0 50.0 (-17.0)#79 48.0 (-15.0)#6,350
80. 21128 33.0 50.0 (-17.0)#80 48.0 (-15.0)#6,376
81. 20851 33.0 50.0 (-17.0)#81 48.0 (-15.0)#6,383
82. 21617 33.0 50.0 (-17.0)#82 48.0 (-15.0)#6,402
83. 21875 33.0 50.0 (-17.0)#83 48.0 (-15.0)#6,421
84. 21017 33.0 50.0 (-17.0)#84 48.0 (-15.0)#6,432
85. 21655 33.0 50.0 (-17.0)#85 48.0 (-15.0)#6,448
86. 21221 34.0 50.0 (-16.0)#86 48.0 (-14.0)#6,592
87. 20815 34.0 50.0 (-16.0)#87 48.0 (-14.0)#6,629
88. 21409 34.0 50.0 (-16.0)#88 48.0 (-14.0)#6,680
89. 21157 35.0 50.0 (-15.0)#89 48.0 (-13.0)#6,908
90. 21208 35.0 50.0 (-15.0)#90 48.0 (-13.0)#6,915
91. 20723 35.0 50.0 (-15.0)#91 48.0 (-13.0)#6,922
92. 20814 35.0 50.0 (-15.0)#92 48.0 (-13.0)#6,933
93. 21231 35.0 50.0 (-15.0)#93 48.0 (-13.0)#7,004
94. 21755 35.0 50.0 (-15.0)#94 48.0 (-13.0)#7,058
95. 21206 36.0 50.0 (-14.0)#95 48.0 (-12.0)#7,181
96. 21037 36.0 50.0 (-14.0)#96 48.0 (-12.0)#7,268
97. 21202 36.0 50.0 (-14.0)#97 48.0 (-12.0)#7,272
98. 21131 36.0 50.0 (-14.0)#98 48.0 (-12.0)#7,345
99. 20782 37.0 50.0 (-13.0)#99 48.0 (-11.0)#7,533
100. 20876 37.0 50.0 (-13.0)#100 48.0 (-11.0)#7,570

Common Questions

What are the Top 10 Zip Codes with the Lowest Births per 1,000 Women in Labor Force in Maryland?
Top 10 Zip Codes with the Lowest Births per 1,000 Women in Labor Force in Maryland are:
#1
4.0
#2
4.0
#3
5.0
#4
5.0
#5
8.0
#6
9.0
#7
10.0
#8
11.0
#9
11.0
#10
11.0
What zip code has the Lowest Births per 1,000 Women in Labor Force in Maryland?
21620 has the Lowest Births per 1,000 Women in Labor Force in Maryland with 4.0.
What is the Number Births per 1,000 Women in Labor Force in the State of Maryland?
Number Births per 1,000 Women in Labor Force in Maryland is 50.0.
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 48.0.