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

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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
North Dakota
Compare Zip Codes
Comparison Subject

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

0.0
800.0
Zip Codes with the Most Births per 1,000 Women in Labor Force in North Dakota Map

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

Zip Code Births / 1,000 Women vs State vs National
1.58794720.059.0(+661)#148.0(+672)#73
2.58477667.059.0(+608)#248.0(+619)#88
3.58331538.059.0(+479)#348.0(+490)#139
4.58486533.059.0(+474)#448.0(+485)#143
5.58439481.059.0(+422)#548.0(+433)#187
6.58422474.059.0(+415)#648.0(+426)#192
7.58223467.059.0(+408)#748.0(+419)#198
8.58426462.059.0(+403)#848.0(+414)#203
9.58727429.059.0(+370)#948.0(+381)#239
10.58731397.059.0(+338)#1048.0(+349)#267
11.58046376.059.0(+317)#1148.0(+328)#297
12.58058375.059.0(+316)#1248.0(+327)#302
13.58029357.059.0(+298)#1348.0(+309)#334
14.58445343.059.0(+284)#1448.0(+295)#361
15.58418341.059.0(+282)#1548.0(+293)#365
16.58063333.059.0(+274)#1648.0(+285)#378
17.58377308.059.0(+249)#1748.0(+260)#446
18.58067306.059.0(+247)#1848.0(+258)#453
19.58015297.059.0(+238)#1948.0(+249)#480
20.58374286.059.0(+227)#2048.0(+238)#514
21.58549263.059.0(+204)#2148.0(+215)#606
22.58645261.059.0(+202)#2248.0(+213)#615
23.58335250.059.0(+191)#2348.0(+202)#644
24.58227231.059.0(+172)#2448.0(+183)#757
25.58755230.059.0(+171)#2548.0(+182)#772
26.58490222.059.0(+163)#2648.0(+174)#819
27.58838214.059.0(+155)#2748.0(+166)#886
28.58788213.059.0(+154)#2848.0(+165)#892
29.58768200.059.0(+141)#2948.0(+152)#991
30.58229200.059.0(+141)#3048.0(+152)#1,015
31.58784196.059.0(+137)#3148.0(+148)#1,045
32.58576176.059.0(+117)#3248.0(+128)#1,241
33.58274176.059.0(+117)#3348.0(+128)#1,242
34.58348171.059.0(+112)#3448.0(+123)#1,326
35.58541169.059.0(+110)#3548.0(+121)#1,356
36.58012167.059.0(+108)#3648.0(+119)#1,372
37.58324167.059.0(+108)#3748.0(+119)#1,380
38.58566162.059.0(+103)#3848.0(+114)#1,471
39.58639159.059.0(+100.0)#3948.0(+111)#1,516
40.58646159.059.0(+100.0)#4048.0(+111)#1,520
41.58344158.059.0(+99.0)#4148.0(+110)#1,536
42.58538155.059.0(+96.0)#4248.0(+107)#1,596
43.58472154.059.0(+95.0)#4348.0(+106)#1,613
44.58210154.059.0(+95.0)#4448.0(+106)#1,615
45.58561152.059.0(+93.0)#4548.0(+104)#1,646
46.58081150.059.0(+91.0)#4648.0(+102)#1,684
47.58544149.059.0(+90.0)#4748.0(+101)#1,707
48.58259147.059.0(+88.0)#4848.0(+99.0)#1,752
49.58001147.059.0(+88.0)#4948.0(+99.0)#1,754
50.58455145.059.0(+86.0)#5048.0(+97.0)#1,791
51.58785144.059.0(+85.0)#5148.0(+96.0)#1,801
52.58710143.059.0(+84.0)#5248.0(+95.0)#1,834
53.58379143.059.0(+84.0)#5348.0(+95.0)#1,841
54.58464143.059.0(+84.0)#5448.0(+95.0)#1,845
55.58051140.059.0(+81.0)#5548.0(+92.0)#1,902
56.58631140.059.0(+81.0)#5648.0(+92.0)#1,910
57.58736140.059.0(+81.0)#5748.0(+92.0)#1,912
58.58346138.059.0(+79.0)#5848.0(+90.0)#1,974
59.58650138.059.0(+79.0)#5948.0(+90.0)#1,977
60.58237136.059.0(+77.0)#6048.0(+88.0)#2,013
61.58577134.059.0(+75.0)#6148.0(+86.0)#2,075
62.58261130.059.0(+71.0)#6248.0(+82.0)#2,185
63.58256129.059.0(+70.0)#6348.0(+81.0)#2,232
64.58463125.059.0(+66.0)#6448.0(+77.0)#2,366
65.58852124.059.0(+65.0)#6548.0(+76.0)#2,398
66.58533123.059.0(+64.0)#6648.0(+75.0)#2,433
67.58849122.059.0(+63.0)#6748.0(+74.0)#2,458
68.58069120.059.0(+61.0)#6848.0(+72.0)#2,537
69.58632118.059.0(+59.0)#6948.0(+70.0)#2,621
70.58318114.059.0(+55.0)#7048.0(+66.0)#2,758
71.58341111.059.0(+52.0)#7148.0(+63.0)#2,895
72.58356111.059.0(+52.0)#7248.0(+63.0)#2,903
73.58036111.059.0(+52.0)#7348.0(+63.0)#2,928
74.58581111.059.0(+52.0)#7448.0(+63.0)#2,930
75.58758111.059.0(+52.0)#7548.0(+63.0)#2,933
76.58238111.059.0(+52.0)#7648.0(+63.0)#2,940
77.58027109.059.0(+50.0)#7748.0(+61.0)#3,024
78.58552108.059.0(+49.0)#7848.0(+60.0)#3,075
79.58424105.059.0(+46.0)#7948.0(+57.0)#3,238
80.58384105.059.0(+46.0)#8048.0(+57.0)#3,241
81.58655104.059.0(+45.0)#8148.0(+56.0)#3,295
82.58064104.059.0(+45.0)#8248.0(+56.0)#3,296
83.58204103.059.0(+44.0)#8348.0(+55.0)#3,345
84.58041101.059.0(+42.0)#8448.0(+53.0)#3,471
85.58327100.059.0(+41.0)#8548.0(+52.0)#3,537
86.5870498.059.0(+39.0)#8648.0(+50.0)#3,644
87.5873597.059.0(+38.0)#8748.0(+49.0)#3,756
88.5825196.059.0(+37.0)#8848.0(+48.0)#3,804
89.5824395.059.0(+36.0)#8948.0(+47.0)#3,878
90.5842894.059.0(+35.0)#9048.0(+46.0)#3,955
91.5823092.059.0(+33.0)#9148.0(+44.0)#4,096
92.5841691.059.0(+32.0)#9248.0(+43.0)#4,187
93.5827791.059.0(+32.0)#9348.0(+43.0)#4,199
94.5876390.059.0(+31.0)#9448.0(+42.0)#4,248
95.5852389.059.0(+30.0)#9548.0(+41.0)#4,347
96.5842589.059.0(+30.0)#9648.0(+41.0)#4,375
97.5873788.059.0(+29.0)#9748.0(+40.0)#4,485
98.5807887.059.0(+28.0)#9848.0(+39.0)#4,489
99.5804587.059.0(+28.0)#9948.0(+39.0)#4,557
100.5848787.059.0(+28.0)#10048.0(+39.0)#4,578

Common Questions

What are the Top 10 Zip Codes with the Most Births per 1,000 Women in Labor Force in North Dakota?
Top 10 Zip Codes with the Most Births per 1,000 Women in Labor Force in North Dakota are:
#1
720.0
#2
667.0
#3
538.0
#4
533.0
#5
481.0
#6
474.0
#7
467.0
#8
462.0
#9
429.0
#10
397.0
What zip code has the Most Births per 1,000 Women in Labor Force in North Dakota?
58794 has the Most Births per 1,000 Women in Labor Force in North Dakota with 720.0.
What is the Number of Births per 1,000 Women in Labor Force in the State of North Dakota?
Number of Births per 1,000 Women in Labor Force in North Dakota is 59.0.
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.