Zip Codes with the Most Births per 1,000 Women in Labor Force in Minnesota

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Highest 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
Minnesota
Compare Zip Codes
Comparison Subject

Map of Zip Codes with the Most Births per 1,000 Women in Labor Force in Minnesota

0.0
1,000.0
Zip Codes with the Most Births per 1,000 Women in Labor Force in Minnesota Map

Zip Codes with the Most Births per 1,000 Women in Labor Force in Minnesota

Zip Code Births / 1,000 Women vs State vs National
1.560301,000.054.0(+946)#148.0(+952)#52
2.56566439.054.0(+385)#248.0(+391)#228
3.55602429.054.0(+375)#348.0(+381)#237
4.56327365.054.0(+311)#448.0(+317)#318
5.56236313.054.0(+259)#548.0(+265)#435
6.56139302.054.0(+248)#648.0(+254)#463
7.56371294.054.0(+240)#748.0(+246)#488
8.56724273.054.0(+219)#848.0(+225)#568
9.56670271.054.0(+217)#948.0(+223)#573
10.55962266.054.0(+212)#1048.0(+218)#590
11.56173259.054.0(+205)#1148.0(+211)#621
12.56287250.054.0(+196)#1248.0(+202)#668
13.56666247.054.0(+193)#1348.0(+199)#674
14.56221238.054.0(+184)#1448.0(+190)#722
15.56385235.054.0(+181)#1548.0(+187)#736
16.56323226.054.0(+172)#1648.0(+178)#791
17.56732225.054.0(+171)#1748.0(+177)#800
18.56174222.054.0(+168)#1848.0(+174)#818
19.55615219.054.0(+165)#1948.0(+171)#845
20.56553211.054.0(+157)#2048.0(+163)#912
21.56016207.054.0(+153)#2148.0(+159)#934
22.56231204.054.0(+150)#2248.0(+156)#963
23.56263203.054.0(+149)#2348.0(+155)#970
24.56134203.054.0(+149)#2448.0(+155)#972
25.56115200.054.0(+146)#2548.0(+152)#982
26.56032200.054.0(+146)#2648.0(+152)#992
27.56688200.054.0(+146)#2748.0(+152)#1,009
28.55029200.054.0(+146)#2848.0(+152)#1,014
29.56155193.054.0(+139)#2948.0(+145)#1,081
30.56355192.054.0(+138)#3048.0(+144)#1,086
31.56651185.054.0(+131)#3148.0(+137)#1,153
32.56686184.054.0(+130)#3248.0(+136)#1,163
33.56091184.054.0(+130)#3348.0(+136)#1,171
34.56678181.054.0(+127)#3448.0(+133)#1,198
35.56356179.054.0(+125)#3548.0(+131)#1,221
36.55716179.054.0(+125)#3648.0(+131)#1,222
37.55612176.054.0(+122)#3748.0(+128)#1,245
38.56285175.054.0(+121)#3848.0(+127)#1,259
39.55366175.054.0(+121)#3948.0(+127)#1,264
40.56156173.054.0(+119)#4048.0(+125)#1,283
41.56552167.054.0(+113)#4148.0(+119)#1,390
42.56118167.054.0(+113)#4248.0(+119)#1,391
43.56369167.054.0(+113)#4348.0(+119)#1,393
44.55946164.054.0(+110)#4448.0(+116)#1,426
45.56570163.054.0(+109)#4548.0(+115)#1,449
46.56248158.054.0(+104)#4648.0(+110)#1,539
47.56579156.054.0(+102)#4748.0(+108)#1,574
48.55959154.054.0(+100.0)#4848.0(+106)#1,607
49.55973154.054.0(+100.0)#4948.0(+106)#1,616
50.55723150.054.0(+96.0)#5048.0(+102)#1,679
51.56757149.054.0(+95.0)#5148.0(+101)#1,703
52.55735148.054.0(+94.0)#5248.0(+100.0)#1,717
53.56572147.054.0(+93.0)#5348.0(+99.0)#1,736
54.55976144.054.0(+90.0)#5448.0(+96.0)#1,795
55.56581143.054.0(+89.0)#5548.0(+95.0)#1,843
56.56313143.054.0(+89.0)#5648.0(+95.0)#1,854
57.55605141.054.0(+87.0)#5748.0(+93.0)#1,888
58.56279140.054.0(+86.0)#5848.0(+92.0)#1,907
59.56010140.054.0(+86.0)#5948.0(+92.0)#1,908
60.56314139.054.0(+85.0)#6048.0(+91.0)#1,939
61.56655138.054.0(+84.0)#6148.0(+90.0)#1,965
62.56660138.054.0(+84.0)#6248.0(+90.0)#1,980
63.55934136.054.0(+82.0)#6348.0(+88.0)#2,017
64.56033136.054.0(+82.0)#6448.0(+88.0)#2,030
65.56249136.054.0(+82.0)#6548.0(+88.0)#2,032
66.56075136.054.0(+82.0)#6648.0(+88.0)#2,035
67.56662135.054.0(+81.0)#6748.0(+87.0)#2,056
68.55017128.054.0(+74.0)#6848.0(+80.0)#2,253
69.56518127.054.0(+73.0)#6948.0(+79.0)#2,301
70.56240125.054.0(+71.0)#7048.0(+77.0)#2,360
71.56331124.054.0(+70.0)#7148.0(+76.0)#2,397
72.56045124.054.0(+70.0)#7248.0(+76.0)#2,407
73.55376123.054.0(+69.0)#7348.0(+75.0)#2,409
74.55953122.054.0(+68.0)#7448.0(+74.0)#2,461
75.56262122.054.0(+68.0)#7548.0(+74.0)#2,462
76.56468120.054.0(+66.0)#7648.0(+72.0)#2,513
77.55931120.054.0(+66.0)#7748.0(+72.0)#2,532
78.56207120.054.0(+66.0)#7848.0(+72.0)#2,535
79.55742118.054.0(+64.0)#7948.0(+70.0)#2,624
80.56557117.054.0(+63.0)#8048.0(+69.0)#2,647
81.56149117.054.0(+63.0)#8148.0(+69.0)#2,660
82.56721116.054.0(+62.0)#8248.0(+68.0)#2,667
83.56433116.054.0(+62.0)#8348.0(+68.0)#2,691
84.56144116.054.0(+62.0)#8448.0(+68.0)#2,699
85.56289116.054.0(+62.0)#8548.0(+68.0)#2,702
86.56744116.054.0(+62.0)#8648.0(+68.0)#2,703
87.55711116.054.0(+62.0)#8748.0(+68.0)#2,704
88.56522116.054.0(+62.0)#8848.0(+68.0)#2,705
89.56633115.054.0(+61.0)#8948.0(+67.0)#2,721
90.55307114.054.0(+60.0)#9048.0(+66.0)#2,761
91.56551114.054.0(+60.0)#9148.0(+66.0)#2,766
92.55945114.054.0(+60.0)#9248.0(+66.0)#2,776
93.56556114.054.0(+60.0)#9348.0(+66.0)#2,777
94.55367114.054.0(+60.0)#9448.0(+66.0)#2,780
95.56069113.054.0(+59.0)#9548.0(+65.0)#2,805
96.55325112.054.0(+58.0)#9648.0(+64.0)#2,843
97.56280111.054.0(+57.0)#9748.0(+63.0)#2,921
98.56260109.054.0(+55.0)#9848.0(+61.0)#3,032
99.56027109.054.0(+55.0)#9948.0(+61.0)#3,037
100.56536109.054.0(+55.0)#10048.0(+61.0)#3,040

Common Questions

What are the Top 10 Zip Codes with the Most Births per 1,000 Women in Labor Force in Minnesota?
Top 10 Zip Codes with the Most Births per 1,000 Women in Labor Force in Minnesota are:
#1
1,000.0
#2
439.0
#3
429.0
#4
365.0
#5
313.0
#6
302.0
#7
294.0
#8
273.0
#9
271.0
#10
266.0
What zip code has the Most Births per 1,000 Women in Labor Force in Minnesota?
56030 has the Most Births per 1,000 Women in Labor Force in Minnesota with 1,000.0.
What is the Number of Births per 1,000 Women in Labor Force in the State of Minnesota?
Number of Births per 1,000 Women in Labor Force in Minnesota is 54.0.
What is the Number of Births per 1,000 Women in Labor Force in the United States?
Number of Births per 1,000 Women in Labor Force in the United States is 48.0.