Zip Codes with the Fewest Births per 1,000 Women Below Poverty Level in Minnesota

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Lowest Birth Rate | Below Poverty
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
Minnesota
Compare Zip Codes
Comparison Subject

Map of Zip Codes with the Fewest Births per 1,000 Women Below Poverty Level in Minnesota

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Zip Codes with the Fewest Births per 1,000 Women Below Poverty Level in Minnesota Map

Zip Codes with the Fewest Births per 1,000 Women Below Poverty Level in Minnesota

Zip Code Births / 1,000 Women vs State vs National
1. 55981 2.0 58.0 (-56.0)#1 53.0 (-51.0)#25
2. 55710 3.0 58.0 (-55.0)#2 53.0 (-50.0)#80
3. 55395 4.0 58.0 (-54.0)#3 53.0 (-49.0)#120
4. 55339 4.0 58.0 (-54.0)#4 53.0 (-49.0)#134
5. 56425 6.0 58.0 (-52.0)#5 53.0 (-47.0)#217
6. 55771 7.0 58.0 (-51.0)#6 53.0 (-46.0)#329
7. 55955 8.0 58.0 (-50.0)#7 53.0 (-45.0)#404
8. 55047 8.0 58.0 (-50.0)#8 53.0 (-45.0)#409
9. 56576 9.0 58.0 (-49.0)#9 53.0 (-44.0)#560
10. 56683 9.0 58.0 (-49.0)#10 53.0 (-44.0)#574
11. 55030 10.0 58.0 (-48.0)#11 53.0 (-43.0)#664
12. 56443 10.0 58.0 (-48.0)#12 53.0 (-43.0)#665
13. 55726 10.0 58.0 (-48.0)#13 53.0 (-43.0)#676
14. 56157 10.0 58.0 (-48.0)#14 53.0 (-43.0)#682
15. 56023 10.0 58.0 (-48.0)#15 53.0 (-43.0)#692
16. 56684 10.0 58.0 (-48.0)#16 53.0 (-43.0)#697
17. 55073 11.0 58.0 (-47.0)#17 53.0 (-42.0)#759
18. 55705 12.0 58.0 (-46.0)#18 53.0 (-41.0)#904
19. 56218 12.0 58.0 (-46.0)#19 53.0 (-41.0)#968
20. 56043 12.0 58.0 (-46.0)#20 53.0 (-41.0)#972
21. 55414 13.0 58.0 (-45.0)#21 53.0 (-40.0)#977
22. 55403 13.0 58.0 (-45.0)#22 53.0 (-40.0)#986
23. 55012 13.0 58.0 (-45.0)#23 53.0 (-40.0)#1,071
24. 56713 13.0 58.0 (-45.0)#24 53.0 (-40.0)#1,100
25. 56051 13.0 58.0 (-45.0)#25 53.0 (-40.0)#1,108
26. 56760 13.0 58.0 (-45.0)#26 53.0 (-40.0)#1,121
27. 55397 14.0 58.0 (-44.0)#27 53.0 (-39.0)#1,202
28. 55775 14.0 58.0 (-44.0)#28 53.0 (-39.0)#1,241
29. 56271 14.0 58.0 (-44.0)#29 53.0 (-39.0)#1,243
30. 55957 14.0 58.0 (-44.0)#30 53.0 (-39.0)#1,263
31. 56363 14.0 58.0 (-44.0)#31 53.0 (-39.0)#1,282
32. 55077 15.0 58.0 (-43.0)#32 53.0 (-38.0)#1,312
33. 55709 15.0 58.0 (-43.0)#33 53.0 (-38.0)#1,361
34. 56450 15.0 58.0 (-43.0)#34 53.0 (-38.0)#1,443
35. 55935 15.0 58.0 (-43.0)#35 53.0 (-38.0)#1,449
36. 55805 16.0 58.0 (-42.0)#36 53.0 (-37.0)#1,508
37. 56511 16.0 58.0 (-42.0)#37 53.0 (-37.0)#1,589
38. 56332 16.0 58.0 (-42.0)#38 53.0 (-37.0)#1,597
39. 56516 16.0 58.0 (-42.0)#39 53.0 (-37.0)#1,645
40. 55751 17.0 58.0 (-41.0)#40 53.0 (-36.0)#1,779
41. 55703 17.0 58.0 (-41.0)#41 53.0 (-36.0)#1,792
42. 56578 17.0 58.0 (-41.0)#42 53.0 (-36.0)#1,802
43. 56151 17.0 58.0 (-41.0)#43 53.0 (-36.0)#1,803
44. 56710 17.0 58.0 (-41.0)#44 53.0 (-36.0)#1,807
45. 56590 17.0 58.0 (-41.0)#45 53.0 (-36.0)#1,810
46. 55127 18.0 58.0 (-40.0)#46 53.0 (-35.0)#1,836
47. 55910 18.0 58.0 (-40.0)#47 53.0 (-35.0)#1,968
48. 55757 18.0 58.0 (-40.0)#48 53.0 (-35.0)#1,983
49. 55764 18.0 58.0 (-40.0)#49 53.0 (-35.0)#1,990
50. 56594 18.0 58.0 (-40.0)#50 53.0 (-35.0)#1,991
51. 56089 18.0 58.0 (-40.0)#51 53.0 (-35.0)#1,995
52. 56377 19.0 58.0 (-39.0)#52 53.0 (-34.0)#2,025
53. 55409 19.0 58.0 (-39.0)#53 53.0 (-34.0)#2,049
54. 56185 19.0 58.0 (-39.0)#54 53.0 (-34.0)#2,186
55. 55933 19.0 58.0 (-39.0)#55 53.0 (-34.0)#2,192
56. 55384 20.0 58.0 (-38.0)#56 53.0 (-33.0)#2,347
57. 56540 20.0 58.0 (-38.0)#57 53.0 (-33.0)#2,348
58. 55314 20.0 58.0 (-38.0)#58 53.0 (-33.0)#2,381
59. 55315 21.0 58.0 (-37.0)#59 53.0 (-32.0)#2,517
60. 56521 21.0 58.0 (-37.0)#60 53.0 (-32.0)#2,635
61. 56748 21.0 58.0 (-37.0)#61 53.0 (-32.0)#2,643
62. 56734 21.0 58.0 (-37.0)#62 53.0 (-32.0)#2,644
63. 55982 21.0 58.0 (-37.0)#63 53.0 (-32.0)#2,646
64. 55408 22.0 58.0 (-36.0)#64 53.0 (-31.0)#2,668
65. 55436 22.0 58.0 (-36.0)#65 53.0 (-31.0)#2,707
66. 55614 22.0 58.0 (-36.0)#66 53.0 (-31.0)#2,797
67. 56628 22.0 58.0 (-36.0)#67 53.0 (-31.0)#2,826
68. 56223 22.0 58.0 (-36.0)#68 53.0 (-31.0)#2,829
69. 56050 22.0 58.0 (-36.0)#69 53.0 (-31.0)#2,832
70. 55724 22.0 58.0 (-36.0)#70 53.0 (-31.0)#2,871
71. 56339 23.0 58.0 (-35.0)#71 53.0 (-30.0)#3,111
72. 56257 23.0 58.0 (-35.0)#72 53.0 (-30.0)#3,131
73. 56165 23.0 58.0 (-35.0)#73 53.0 (-30.0)#3,133
74. 55731 24.0 58.0 (-34.0)#74 53.0 (-29.0)#3,262
75. 55965 24.0 58.0 (-34.0)#75 53.0 (-29.0)#3,316
76. 56169 24.0 58.0 (-34.0)#76 53.0 (-29.0)#3,374
77. 55319 25.0 58.0 (-33.0)#77 53.0 (-28.0)#3,540
78. 56057 25.0 58.0 (-33.0)#78 53.0 (-28.0)#3,562
79. 55114 25.0 58.0 (-33.0)#79 53.0 (-28.0)#3,569
80. 56587 25.0 58.0 (-33.0)#80 53.0 (-28.0)#3,630
81. 56727 25.0 58.0 (-33.0)#81 53.0 (-28.0)#3,639
82. 55926 25.0 58.0 (-33.0)#82 53.0 (-28.0)#3,643
83. 56170 25.0 58.0 (-33.0)#83 53.0 (-28.0)#3,659
84. 55120 26.0 58.0 (-32.0)#84 53.0 (-27.0)#3,792
85. 56150 26.0 58.0 (-32.0)#85 53.0 (-27.0)#3,826
86. 55054 26.0 58.0 (-32.0)#86 53.0 (-27.0)#3,834
87. 56167 26.0 58.0 (-32.0)#87 53.0 (-27.0)#3,899
88. 56649 27.0 58.0 (-31.0)#88 53.0 (-26.0)#4,021
89. 56101 27.0 58.0 (-31.0)#89 53.0 (-26.0)#4,044
90. 55373 27.0 58.0 (-31.0)#90 53.0 (-26.0)#4,050
91. 55798 27.0 58.0 (-31.0)#91 53.0 (-26.0)#4,169
92. 56145 27.0 58.0 (-31.0)#92 53.0 (-26.0)#4,176
93. 55702 27.0 58.0 (-31.0)#93 53.0 (-26.0)#4,177
94. 55987 28.0 58.0 (-30.0)#94 53.0 (-25.0)#4,218
95. 55301 28.0 58.0 (-30.0)#95 53.0 (-25.0)#4,283
96. 55352 28.0 58.0 (-30.0)#96 53.0 (-25.0)#4,301
97. 55037 28.0 58.0 (-30.0)#97 53.0 (-25.0)#4,333
98. 56284 28.0 58.0 (-30.0)#98 53.0 (-25.0)#4,373
99. 55312 28.0 58.0 (-30.0)#99 53.0 (-25.0)#4,396
100. 55941 28.0 58.0 (-30.0)#100 53.0 (-25.0)#4,405

Common Questions

What are the Top 10 Zip Codes with the Fewest Births per 1,000 Women Below Poverty Level in Minnesota?
Top 10 Zip Codes with the Fewest Births per 1,000 Women Below Poverty Level in Minnesota are:
#1
2.0
#2
3.0
#3
4.0
#4
4.0
#5
6.0
#6
7.0
#7
8.0
#8
8.0
#9
9.0
#10
9.0
What zip code has the Fewest Births per 1,000 Women Below Poverty Level in Minnesota?
55981 has the Fewest Births per 1,000 Women Below Poverty Level in Minnesota with 2.0.
What is the Number of Births per 1,000 Women Below Poverty Level in the State of Minnesota?
Number of Births per 1,000 Women Below Poverty Level in Minnesota is 58.0.
What is the Number of Births per 1,000 Women Below Poverty Level in the United States?
Number of Births per 1,000 Women Below Poverty Level in the United States is 53.0.