Zip Codes with the Most Births per 1,000 Women Over the Age of 35 in Maryland

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Highest Birth Rate | Women 35+
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 Over the Age of 35 in Maryland

0.0
1,000.0
Zip Codes with the Most Births per 1,000 Women Over the Age of 35 in Maryland Map

Zip Codes with the Most Births per 1,000 Women Over the Age of 35 in Maryland

Zip Code Births / 1,000 Women vs State vs National
1. 20687 1,000.0 38.0 (+962)#1 32.0 (+968)#11
2. 21714 1,000.0 38.0 (+962)#2 32.0 (+968)#17
3. 21622 294.0 38.0 (+256)#3 32.0 (+262)#233
4. 20674 273.0 38.0 (+235)#4 32.0 (+241)#265
5. 20711 270.0 38.0 (+232)#5 32.0 (+238)#276
6. 20650 215.0 38.0 (+177)#6 32.0 (+183)#412
7. 20754 195.0 38.0 (+157)#7 32.0 (+163)#498
8. 20637 177.0 38.0 (+139)#8 32.0 (+145)#593
9. 20779 175.0 38.0 (+137)#9 32.0 (+143)#614
10. 20896 165.0 38.0 (+127)#10 32.0 (+133)#693
11. 21733 156.0 38.0 (+118)#11 32.0 (+124)#756
12. 21650 152.0 38.0 (+114)#12 32.0 (+120)#803
13. 21639 146.0 38.0 (+108)#13 32.0 (+114)#840
14. 20611 137.0 38.0 (+99.0)#14 32.0 (+105)#935
15. 21919 113.0 38.0 (+75.0)#15 32.0 (+81.0)#1,277
16. 20879 108.0 38.0 (+70.0)#16 32.0 (+76.0)#1,352
17. 20762 103.0 38.0 (+65.0)#17 32.0 (+71.0)#1,469
18. 21227 100.0 38.0 (+62.0)#18 32.0 (+68.0)#1,527
19. 21837 99.0 38.0 (+61.0)#19 32.0 (+67.0)#1,573
20. 20877 97.0 38.0 (+59.0)#20 32.0 (+65.0)#1,616
21. 21601 96.0 38.0 (+58.0)#21 32.0 (+64.0)#1,642
22. 20759 91.0 38.0 (+53.0)#22 32.0 (+59.0)#1,807
23. 21034 91.0 38.0 (+53.0)#23 32.0 (+59.0)#1,815
24. 21032 89.0 38.0 (+51.0)#24 32.0 (+57.0)#1,868
25. 21220 87.0 38.0 (+49.0)#25 32.0 (+55.0)#1,929
26. 21659 87.0 38.0 (+49.0)#26 32.0 (+55.0)#1,953
27. 21001 86.0 38.0 (+48.0)#27 32.0 (+54.0)#1,971
28. 20781 84.0 38.0 (+46.0)#28 32.0 (+52.0)#2,050
29. 20710 82.0 38.0 (+44.0)#29 32.0 (+50.0)#2,137
30. 21625 82.0 38.0 (+44.0)#30 32.0 (+50.0)#2,157
31. 21562 81.0 38.0 (+43.0)#31 32.0 (+49.0)#2,198
32. 20639 80.0 38.0 (+42.0)#32 32.0 (+48.0)#2,223
33. 21875 80.0 38.0 (+42.0)#33 32.0 (+48.0)#2,228
34. 21084 80.0 38.0 (+42.0)#34 32.0 (+48.0)#2,229
35. 21401 79.0 38.0 (+41.0)#35 32.0 (+47.0)#2,263
36. 21629 79.0 38.0 (+41.0)#36 32.0 (+47.0)#2,278
37. 21111 79.0 38.0 (+41.0)#37 32.0 (+47.0)#2,286
38. 21113 77.0 38.0 (+39.0)#38 32.0 (+45.0)#2,356
39. 21750 77.0 38.0 (+39.0)#39 32.0 (+45.0)#2,387
40. 21013 76.0 38.0 (+38.0)#40 32.0 (+44.0)#2,442
41. 21207 75.0 38.0 (+37.0)#41 32.0 (+43.0)#2,458
42. 21849 75.0 38.0 (+37.0)#42 32.0 (+43.0)#2,497
43. 20910 74.0 38.0 (+36.0)#43 32.0 (+42.0)#2,523
44. 20695 74.0 38.0 (+36.0)#44 32.0 (+42.0)#2,542
45. 20720 70.0 38.0 (+32.0)#45 32.0 (+38.0)#2,796
46. 21152 70.0 38.0 (+32.0)#46 32.0 (+38.0)#2,822
47. 20903 69.0 38.0 (+31.0)#47 32.0 (+37.0)#2,873
48. 21236 68.0 38.0 (+30.0)#48 32.0 (+36.0)#2,928
49. 21014 68.0 38.0 (+30.0)#49 32.0 (+36.0)#2,930
50. 20904 67.0 38.0 (+29.0)#50 32.0 (+35.0)#2,993
51. 21144 67.0 38.0 (+29.0)#51 32.0 (+35.0)#3,000
52. 20784 67.0 38.0 (+29.0)#52 32.0 (+35.0)#3,004
53. 21211 67.0 38.0 (+29.0)#53 32.0 (+35.0)#3,031
54. 21851 66.0 38.0 (+28.0)#54 32.0 (+34.0)#3,131
55. 20622 66.0 38.0 (+28.0)#55 32.0 (+34.0)#3,137
56. 20751 66.0 38.0 (+28.0)#56 32.0 (+34.0)#3,153
57. 21054 65.0 38.0 (+27.0)#57 32.0 (+33.0)#3,202
58. 20677 65.0 38.0 (+27.0)#58 32.0 (+33.0)#3,245
59. 21162 63.0 38.0 (+25.0)#59 32.0 (+31.0)#3,411
60. 21040 62.0 38.0 (+24.0)#60 32.0 (+30.0)#3,468
61. 21791 62.0 38.0 (+24.0)#61 32.0 (+30.0)#3,514
62. 20707 60.0 38.0 (+22.0)#62 32.0 (+28.0)#3,648
63. 20705 60.0 38.0 (+22.0)#63 32.0 (+28.0)#3,659
64. 21057 59.0 38.0 (+21.0)#64 32.0 (+27.0)#3,802
65. 20814 58.0 38.0 (+20.0)#65 32.0 (+26.0)#3,859
66. 21773 58.0 38.0 (+20.0)#66 32.0 (+26.0)#3,915
67. 21521 58.0 38.0 (+20.0)#67 32.0 (+26.0)#3,943
68. 20646 57.0 38.0 (+19.0)#68 32.0 (+25.0)#3,990
69. 20613 56.0 38.0 (+18.0)#69 32.0 (+24.0)#4,118
70. 21231 56.0 38.0 (+18.0)#70 32.0 (+24.0)#4,119
71. 20706 55.0 38.0 (+17.0)#71 32.0 (+23.0)#4,200
72. 21201 55.0 38.0 (+17.0)#72 32.0 (+23.0)#4,243
73. 20906 54.0 38.0 (+16.0)#73 32.0 (+22.0)#4,313
74. 20740 54.0 38.0 (+16.0)#74 32.0 (+22.0)#4,333
75. 20602 53.0 38.0 (+15.0)#75 32.0 (+21.0)#4,460
76. 20744 52.0 38.0 (+14.0)#76 32.0 (+20.0)#4,570
77. 21228 52.0 38.0 (+14.0)#77 32.0 (+20.0)#4,572
78. 20901 52.0 38.0 (+14.0)#78 32.0 (+20.0)#4,584
79. 21742 52.0 38.0 (+14.0)#79 32.0 (+20.0)#4,588
80. 21154 52.0 38.0 (+14.0)#80 32.0 (+20.0)#4,647
81. 20747 51.0 38.0 (+13.0)#81 32.0 (+19.0)#4,708
82. 20886 51.0 38.0 (+13.0)#82 32.0 (+19.0)#4,719
83. 20783 50.0 38.0 (+12.0)#83 32.0 (+18.0)#4,833
84. 21133 50.0 38.0 (+12.0)#84 32.0 (+18.0)#4,854
85. 21771 50.0 38.0 (+12.0)#85 32.0 (+18.0)#4,855
86. 21239 50.0 38.0 (+12.0)#86 32.0 (+18.0)#4,864
87. 21787 50.0 38.0 (+12.0)#87 32.0 (+18.0)#4,923
88. 20871 49.0 38.0 (+11.0)#88 32.0 (+17.0)#5,048
89. 20785 48.0 38.0 (+10.00)#89 32.0 (+16.0)#5,179
90. 21754 48.0 38.0 (+10.00)#90 32.0 (+16.0)#5,258
91. 20623 48.0 38.0 (+10.00)#91 32.0 (+16.0)#5,289
92. 21224 47.0 38.0 (+9.00)#92 32.0 (+15.0)#5,332
93. 21075 47.0 38.0 (+9.00)#93 32.0 (+15.0)#5,345
94. 21225 47.0 38.0 (+9.00)#94 32.0 (+15.0)#5,347
95. 21046 47.0 38.0 (+9.00)#95 32.0 (+15.0)#5,395
96. 21131 47.0 38.0 (+9.00)#96 32.0 (+15.0)#5,425
97. 21204 46.0 38.0 (+8.00)#97 32.0 (+14.0)#5,560
98. 20855 46.0 38.0 (+8.00)#98 32.0 (+14.0)#5,569
99. 21074 46.0 38.0 (+8.00)#99 32.0 (+14.0)#5,575
100. 21638 46.0 38.0 (+8.00)#100 32.0 (+14.0)#5,606

Common Questions

What are the Top 10 Zip Codes with the Most Births per 1,000 Women Over the Age of 35 in Maryland?
Top 10 Zip Codes with the Most Births per 1,000 Women Over the Age of 35 in Maryland are:
#1
1,000.0
#2
1,000.0
#3
294.0
#4
273.0
#5
270.0
#6
215.0
#7
195.0
#8
177.0
#9
175.0
#10
165.0
What zip code has the Most Births per 1,000 Women Over the Age of 35 in Maryland?
20687 has the Most Births per 1,000 Women Over the Age of 35 in Maryland with 1,000.0.
What is the Number of Births per 1,000 Women Over the Age of 35 in the State of Maryland?
Number of Births per 1,000 Women Over the Age of 35 in Maryland is 38.0.
What is the Number of Births per 1,000 Women Over the Age of 35 in the United States?
Number of Births per 1,000 Women Over the Age of 35 in the United States is 32.0.