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

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Highest Birth Rate | All Women
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 Most Births per 1,000 Women in Maryland

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

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

Zip Code Births / 1,000 Women vs State vs National
1. 20667 1,000.0 51.0 (+949)#1 52.0 (+948)#27
2. 21634 630.0 51.0 (+579)#2 52.0 (+578)#116
3. 20758 414.0 51.0 (+363)#3 52.0 (+362)#241
4. 20687 413.0 51.0 (+362)#4 52.0 (+361)#243
5. 20608 405.0 51.0 (+354)#5 52.0 (+353)#253
6. 21524 351.0 51.0 (+300)#6 52.0 (+299)#334
7. 21156 333.0 51.0 (+282)#7 52.0 (+281)#363
8. 21714 255.0 51.0 (+204)#8 52.0 (+203)#625
9. 21733 234.0 51.0 (+183)#9 52.0 (+182)#731
10. 20611 219.0 51.0 (+168)#10 52.0 (+167)#825
11. 20674 204.0 51.0 (+153)#11 52.0 (+152)#918
12. 20670 198.0 51.0 (+147)#12 52.0 (+146)#988
13. 21071 197.0 51.0 (+146)#13 52.0 (+145)#1,004
14. 21869 190.0 51.0 (+139)#14 52.0 (+138)#1,084
15. 20711 186.0 51.0 (+135)#15 52.0 (+134)#1,128
16. 20645 183.0 51.0 (+132)#16 52.0 (+131)#1,165
17. 21622 176.0 51.0 (+125)#17 52.0 (+124)#1,253
18. 21542 170.0 51.0 (+119)#18 52.0 (+118)#1,356
19. 20762 156.0 51.0 (+105)#19 52.0 (+104)#1,605
20. 21798 141.0 51.0 (+90.0)#20 52.0 (+89.0)#1,943
21. 21636 140.0 51.0 (+89.0)#21 52.0 (+88.0)#1,974
22. 20650 138.0 51.0 (+87.0)#22 52.0 (+86.0)#2,024
23. 21155 134.0 51.0 (+83.0)#23 52.0 (+82.0)#2,170
24. 21851 132.0 51.0 (+81.0)#24 52.0 (+80.0)#2,227
25. 20860 132.0 51.0 (+81.0)#25 52.0 (+80.0)#2,234
26. 21647 132.0 51.0 (+81.0)#26 52.0 (+80.0)#2,248
27. 20781 130.0 51.0 (+79.0)#27 52.0 (+78.0)#2,274
28. 20710 128.0 51.0 (+77.0)#28 52.0 (+76.0)#2,362
29. 21034 127.0 51.0 (+76.0)#29 52.0 (+75.0)#2,409
30. 21082 127.0 51.0 (+76.0)#30 52.0 (+75.0)#2,429
31. 20637 123.0 51.0 (+72.0)#31 52.0 (+71.0)#2,577
32. 20602 118.0 51.0 (+67.0)#32 52.0 (+66.0)#2,780
33. 20779 117.0 51.0 (+66.0)#33 52.0 (+65.0)#2,877
34. 20896 116.0 51.0 (+65.0)#34 52.0 (+64.0)#2,920
35. 20759 115.0 51.0 (+64.0)#35 52.0 (+63.0)#2,945
36. 20751 115.0 51.0 (+64.0)#36 52.0 (+63.0)#2,962
37. 20754 107.0 51.0 (+56.0)#37 52.0 (+55.0)#3,407
38. 21227 106.0 51.0 (+55.0)#38 52.0 (+54.0)#3,470
39. 21520 106.0 51.0 (+55.0)#39 52.0 (+54.0)#3,505
40. 21601 105.0 51.0 (+54.0)#40 52.0 (+53.0)#3,533
41. 21850 104.0 51.0 (+53.0)#41 52.0 (+52.0)#3,624
42. 21650 103.0 51.0 (+52.0)#42 52.0 (+51.0)#3,744
43. 21562 100.0 51.0 (+49.0)#43 52.0 (+48.0)#3,916
44. 21837 99.0 51.0 (+48.0)#44 52.0 (+47.0)#4,016
45. 20664 98.0 51.0 (+47.0)#45 52.0 (+46.0)#4,093
46. 21561 97.0 51.0 (+46.0)#46 52.0 (+45.0)#4,181
47. 21084 95.0 51.0 (+44.0)#47 52.0 (+43.0)#4,341
48. 21162 95.0 51.0 (+44.0)#48 52.0 (+43.0)#4,352
49. 20877 93.0 51.0 (+42.0)#49 52.0 (+41.0)#4,506
50. 21713 93.0 51.0 (+42.0)#50 52.0 (+41.0)#4,519
51. 21009 92.0 51.0 (+41.0)#51 52.0 (+40.0)#4,590
52. 21758 92.0 51.0 (+41.0)#52 52.0 (+40.0)#4,627
53. 21625 92.0 51.0 (+41.0)#53 52.0 (+40.0)#4,645
54. 20706 90.0 51.0 (+39.0)#54 52.0 (+38.0)#4,792
55. 20623 90.0 51.0 (+39.0)#55 52.0 (+38.0)#4,856
56. 20880 90.0 51.0 (+39.0)#56 52.0 (+38.0)#4,883
57. 20912 89.0 51.0 (+38.0)#57 52.0 (+37.0)#4,902
58. 20636 89.0 51.0 (+38.0)#58 52.0 (+37.0)#4,916
59. 20755 87.0 51.0 (+36.0)#59 52.0 (+35.0)#5,148
60. 20677 87.0 51.0 (+36.0)#60 52.0 (+35.0)#5,199
61. 21639 85.0 51.0 (+34.0)#61 52.0 (+33.0)#5,411
62. 21853 84.0 51.0 (+33.0)#62 52.0 (+32.0)#5,527
63. 21530 83.0 51.0 (+32.0)#63 52.0 (+31.0)#5,696
64. 21074 82.0 51.0 (+31.0)#64 52.0 (+30.0)#5,780
65. 20695 82.0 51.0 (+31.0)#65 52.0 (+30.0)#5,790
66. 21220 80.0 51.0 (+29.0)#66 52.0 (+28.0)#6,061
67. 20785 80.0 51.0 (+29.0)#67 52.0 (+28.0)#6,064
68. 21032 80.0 51.0 (+29.0)#68 52.0 (+28.0)#6,114
69. 21144 79.0 51.0 (+28.0)#69 52.0 (+27.0)#6,218
70. 20871 79.0 51.0 (+28.0)#70 52.0 (+27.0)#6,231
71. 21001 79.0 51.0 (+28.0)#71 52.0 (+27.0)#6,235
72. 21750 79.0 51.0 (+28.0)#72 52.0 (+27.0)#6,303
73. 21742 78.0 51.0 (+27.0)#73 52.0 (+26.0)#6,377
74. 21826 78.0 51.0 (+27.0)#74 52.0 (+26.0)#6,451
75. 20879 77.0 51.0 (+26.0)#75 52.0 (+25.0)#6,545
76. 21874 77.0 51.0 (+26.0)#76 52.0 (+25.0)#6,635
77. 21754 76.0 51.0 (+25.0)#77 52.0 (+24.0)#6,786
78. 21757 76.0 51.0 (+25.0)#78 52.0 (+24.0)#6,817
79. 21774 75.0 51.0 (+24.0)#79 52.0 (+23.0)#6,909
80. 21849 75.0 51.0 (+24.0)#80 52.0 (+23.0)#6,959
81. 21631 75.0 51.0 (+24.0)#81 52.0 (+23.0)#6,968
82. 20904 74.0 51.0 (+23.0)#82 52.0 (+22.0)#7,025
83. 21610 74.0 51.0 (+23.0)#83 52.0 (+22.0)#7,196
84. 20707 73.0 51.0 (+22.0)#84 52.0 (+21.0)#7,227
85. 20866 73.0 51.0 (+22.0)#85 52.0 (+21.0)#7,276
86. 21842 73.0 51.0 (+22.0)#86 52.0 (+21.0)#7,298
87. 21237 72.0 51.0 (+21.0)#87 52.0 (+20.0)#7,461
88. 20837 72.0 51.0 (+21.0)#88 52.0 (+20.0)#7,538
89. 21791 72.0 51.0 (+21.0)#89 52.0 (+20.0)#7,555
90. 20794 71.0 51.0 (+20.0)#90 52.0 (+19.0)#7,708
91. 21205 71.0 51.0 (+20.0)#91 52.0 (+19.0)#7,713
92. 20722 71.0 51.0 (+20.0)#92 52.0 (+19.0)#7,745
93. 20906 70.0 51.0 (+19.0)#93 52.0 (+18.0)#7,848
94. 20886 70.0 51.0 (+19.0)#94 52.0 (+18.0)#7,872
95. 21054 70.0 51.0 (+19.0)#95 52.0 (+18.0)#7,921
96. 21632 70.0 51.0 (+19.0)#96 52.0 (+18.0)#7,954
97. 21521 70.0 51.0 (+19.0)#97 52.0 (+18.0)#8,014
98. 21659 70.0 51.0 (+19.0)#98 52.0 (+18.0)#8,022
99. 20783 69.0 51.0 (+18.0)#99 52.0 (+17.0)#8,061
100. 20737 69.0 51.0 (+18.0)#100 52.0 (+17.0)#8,116

Common Questions

What are the Top 10 Zip Codes with the Most Births per 1,000 Women in Maryland?
Top 10 Zip Codes with the Most Births per 1,000 Women in Maryland are:
#1
1,000.0
#2
630.0
#3
414.0
#4
413.0
#5
405.0
#6
351.0
#7
333.0
#8
255.0
#9
234.0
#10
219.0
What zip code has the Most Births per 1,000 Women in Maryland?
20667 has the Most Births per 1,000 Women in Maryland with 1,000.0.
What is the Number of Births per 1,000 Women in the State of Maryland?
Number of Births per 1,000 Women in Maryland is 51.0.
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 52.0.