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

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Highest 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 Most Births per 1,000 Women Below Poverty Level in Minnesota

0.0
500.0
Zip Codes with the Most Births per 1,000 Women Below Poverty Level in Minnesota Map

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

Zip Code Births / 1,000 Women vs State vs National
1.56565417.058.0(+359)#153.0(+364)#241
2.56327356.058.0(+298)#253.0(+303)#331
3.56030333.058.0(+275)#353.0(+280)#387
4.56688300.058.0(+242)#453.0(+247)#457
5.55602281.058.0(+223)#553.0(+228)#521
6.56724273.058.0(+215)#653.0(+220)#554
7.56139269.058.0(+211)#753.0(+216)#567
8.56236267.058.0(+209)#853.0(+214)#578
9.56566255.058.0(+197)#953.0(+202)#635
10.56371250.058.0(+192)#1053.0(+197)#665
11.55765241.058.0(+183)#1153.0(+188)#708
12.56115234.058.0(+176)#1253.0(+181)#746
13.55919222.058.0(+164)#1353.0(+169)#818
14.55962218.058.0(+160)#1453.0(+165)#848
15.56385203.058.0(+145)#1553.0(+150)#946
16.56263200.058.0(+142)#1653.0(+147)#979
17.56356200.058.0(+142)#1753.0(+147)#982
18.55029200.058.0(+142)#1853.0(+147)#990
19.56323197.058.0(+139)#1953.0(+144)#1,020
20.56553190.058.0(+132)#2053.0(+137)#1,104
21.56732189.058.0(+131)#2153.0(+136)#1,112
22.55615189.058.0(+131)#2253.0(+136)#1,113
23.56369185.058.0(+127)#2353.0(+132)#1,167
24.56355184.058.0(+126)#2453.0(+131)#1,175
25.56173184.058.0(+126)#2553.0(+131)#1,178
26.56634183.058.0(+125)#2653.0(+130)#1,183
27.56579179.058.0(+121)#2753.0(+126)#1,227
28.55612176.058.0(+118)#2853.0(+123)#1,271
29.56287174.058.0(+116)#2953.0(+121)#1,310
30.56231172.058.0(+114)#3053.0(+119)#1,340
31.56651170.058.0(+112)#3153.0(+117)#1,372
32.56518167.058.0(+109)#3253.0(+114)#1,436
33.56032167.058.0(+109)#3353.0(+114)#1,439
34.56581167.058.0(+109)#3453.0(+114)#1,444
35.56016166.058.0(+108)#3553.0(+113)#1,465
36.56757161.058.0(+103)#3653.0(+108)#1,539
37.56536157.058.0(+99.0)#3753.0(+104)#1,625
38.56673154.058.0(+96.0)#3853.0(+101)#1,667
39.56134154.058.0(+96.0)#3953.0(+101)#1,671
40.56091152.058.0(+94.0)#4053.0(+99.0)#1,716
41.55946147.058.0(+89.0)#4153.0(+94.0)#1,808
42.55959147.058.0(+89.0)#4253.0(+94.0)#1,812
43.56662147.058.0(+89.0)#4353.0(+94.0)#1,821
44.55017146.058.0(+88.0)#4453.0(+93.0)#1,844
45.56156145.058.0(+87.0)#4553.0(+92.0)#1,854
46.56570145.058.0(+87.0)#4653.0(+92.0)#1,864
47.56155145.058.0(+87.0)#4753.0(+92.0)#1,871
48.56221143.058.0(+85.0)#4853.0(+90.0)#1,921
49.56147143.058.0(+85.0)#4953.0(+90.0)#1,934
50.56680143.058.0(+85.0)#5053.0(+90.0)#1,935
51.56313143.058.0(+85.0)#5153.0(+90.0)#1,940
52.56686141.058.0(+83.0)#5253.0(+88.0)#1,974
53.55723138.058.0(+80.0)#5353.0(+85.0)#2,060
54.56678138.058.0(+80.0)#5453.0(+85.0)#2,061
55.56552138.058.0(+80.0)#5553.0(+85.0)#2,075
56.56075136.058.0(+78.0)#5653.0(+83.0)#2,142
57.56110135.058.0(+77.0)#5753.0(+82.0)#2,158
58.55753135.058.0(+77.0)#5853.0(+82.0)#2,167
59.56280135.058.0(+77.0)#5953.0(+82.0)#2,177
60.56548134.058.0(+76.0)#6053.0(+81.0)#2,204
61.56285133.058.0(+75.0)#6153.0(+80.0)#2,236
62.55953132.058.0(+74.0)#6253.0(+79.0)#2,271
63.56350130.058.0(+72.0)#6353.0(+77.0)#2,347
64.55973130.058.0(+72.0)#6453.0(+77.0)#2,350
65.55367128.058.0(+70.0)#6553.0(+75.0)#2,411
66.55934126.058.0(+68.0)#6653.0(+73.0)#2,485
67.56314125.058.0(+67.0)#6753.0(+72.0)#2,530
68.56118125.058.0(+67.0)#6853.0(+72.0)#2,535
69.56174125.058.0(+67.0)#6953.0(+72.0)#2,537
70.56660125.058.0(+67.0)#7053.0(+72.0)#2,538
71.56249125.058.0(+67.0)#7153.0(+72.0)#2,541
72.56207125.058.0(+67.0)#7253.0(+72.0)#2,545
73.56279124.058.0(+66.0)#7353.0(+71.0)#2,585
74.56572123.058.0(+65.0)#7453.0(+70.0)#2,608
75.56045123.058.0(+65.0)#7553.0(+70.0)#2,631
76.56453123.058.0(+65.0)#7653.0(+70.0)#2,635
77.55366123.058.0(+65.0)#7753.0(+70.0)#2,640
78.55976122.058.0(+64.0)#7853.0(+69.0)#2,650
79.56181122.058.0(+64.0)#7953.0(+69.0)#2,671
80.56058119.058.0(+61.0)#8053.0(+66.0)#2,771
81.56010119.058.0(+61.0)#8153.0(+66.0)#2,790
82.56655116.058.0(+58.0)#8253.0(+63.0)#2,936
83.56670116.058.0(+58.0)#8353.0(+63.0)#2,938
84.56149115.058.0(+57.0)#8453.0(+62.0)#2,994
85.56033115.058.0(+57.0)#8553.0(+62.0)#3,007
86.55325114.058.0(+56.0)#8653.0(+61.0)#3,032
87.56557114.058.0(+56.0)#8753.0(+61.0)#3,040
88.56293113.058.0(+55.0)#8853.0(+60.0)#3,100
89.56219111.058.0(+53.0)#8953.0(+58.0)#3,215
90.56331110.058.0(+52.0)#9053.0(+57.0)#3,283
91.55735110.058.0(+52.0)#9153.0(+57.0)#3,287
92.55924110.058.0(+52.0)#9253.0(+57.0)#3,293
93.56235110.058.0(+52.0)#9353.0(+57.0)#3,306
94.55130109.058.0(+51.0)#9453.0(+56.0)#3,310
95.55088109.058.0(+51.0)#9553.0(+56.0)#3,329
96.55716109.058.0(+51.0)#9653.0(+56.0)#3,356
97.56069108.058.0(+50.0)#9753.0(+55.0)#3,388
98.56215108.058.0(+50.0)#9853.0(+55.0)#3,390
99.55310108.058.0(+50.0)#9953.0(+55.0)#3,406
100.56633107.058.0(+49.0)#10053.0(+54.0)#3,446

Common Questions

What are the Top 10 Zip Codes with the Most Births per 1,000 Women Below Poverty Level in Minnesota?
Top 10 Zip Codes with the Most Births per 1,000 Women Below Poverty Level in Minnesota are:
#1
417.0
#2
356.0
#3
333.0
#4
300.0
#5
281.0
#6
273.0
#7
269.0
#8
267.0
#9
255.0
#10
250.0
What zip code has the Most Births per 1,000 Women Below Poverty Level in Minnesota?
56565 has the Most Births per 1,000 Women Below Poverty Level in Minnesota with 417.0.
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.