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

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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
North Dakota
Compare Zip Codes
Comparison Subject

Map of Zip Codes with the Most Births per 1,000 Women Below Poverty Level in North Dakota

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800.0
Zip Codes with the Most Births per 1,000 Women Below Poverty Level in North Dakota Map

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

Zip Code Births / 1,000 Women vs State vs National
1.58488733.068.0(+665)#153.0(+680)#81
2.58477667.068.0(+599)#253.0(+614)#102
3.58794563.068.0(+495)#353.0(+510)#142
4.58486471.068.0(+403)#453.0(+418)#197
5.58223467.068.0(+399)#553.0(+414)#200
6.58422462.068.0(+394)#653.0(+409)#204
7.58439413.068.0(+345)#753.0(+360)#247
8.58731390.068.0(+322)#853.0(+337)#270
9.58029357.068.0(+289)#953.0(+304)#330
10.58331350.068.0(+282)#1053.0(+297)#342
11.58426316.068.0(+248)#1153.0(+263)#409
12.58058316.068.0(+248)#1253.0(+263)#410
13.58046304.068.0(+236)#1353.0(+251)#440
14.58377296.068.0(+228)#1453.0(+243)#468
15.58063292.068.0(+224)#1553.0(+239)#479
16.58445286.068.0(+218)#1653.0(+233)#506
17.58727273.068.0(+205)#1753.0(+220)#553
18.58067268.068.0(+200)#1853.0(+215)#573
19.58645261.068.0(+193)#1953.0(+208)#603
20.58418254.068.0(+186)#2053.0(+201)#637
21.58847250.068.0(+182)#2153.0(+197)#653
22.58650237.068.0(+169)#2253.0(+184)#734
23.58015234.068.0(+166)#2353.0(+181)#749
24.58241230.068.0(+162)#2453.0(+177)#777
25.58755230.068.0(+162)#2553.0(+177)#778
26.58490222.068.0(+154)#2653.0(+169)#822
27.58451222.068.0(+154)#2753.0(+169)#827
28.58736212.068.0(+144)#2853.0(+159)#871
29.58227206.068.0(+138)#2953.0(+153)#917
30.58784199.068.0(+131)#3053.0(+146)#998
31.58772194.068.0(+126)#3153.0(+141)#1,062
32.58549192.068.0(+124)#3253.0(+139)#1,079
33.58030186.068.0(+118)#3353.0(+133)#1,153
34.58335185.068.0(+117)#3453.0(+132)#1,162
35.58758178.068.0(+110)#3553.0(+125)#1,247
36.58631176.068.0(+108)#3653.0(+123)#1,267
37.58274174.068.0(+106)#3753.0(+121)#1,303
38.58544167.068.0(+99.0)#3853.0(+114)#1,431
39.58788165.068.0(+97.0)#3953.0(+112)#1,473
40.58838164.068.0(+96.0)#4053.0(+111)#1,489
41.58785158.068.0(+90.0)#4153.0(+105)#1,596
42.58853155.068.0(+87.0)#4253.0(+102)#1,655
43.58566154.068.0(+86.0)#4353.0(+101)#1,673
44.58852145.068.0(+77.0)#4453.0(+92.0)#1,861
45.58487144.068.0(+76.0)#4553.0(+91.0)#1,902
46.58081143.068.0(+75.0)#4653.0(+90.0)#1,922
47.58027141.068.0(+73.0)#4753.0(+88.0)#1,972
48.58845141.068.0(+73.0)#4853.0(+88.0)#1,976
49.58346141.068.0(+73.0)#4953.0(+88.0)#1,977
50.58324140.068.0(+72.0)#5053.0(+87.0)#1,993
51.58374140.068.0(+72.0)#5153.0(+87.0)#2,002
52.58012139.068.0(+71.0)#5253.0(+86.0)#2,025
53.58456137.068.0(+69.0)#5353.0(+84.0)#2,101
54.58775136.068.0(+68.0)#5453.0(+83.0)#2,141
55.58001135.068.0(+67.0)#5553.0(+82.0)#2,180
56.58204133.068.0(+65.0)#5653.0(+80.0)#2,231
57.58237132.068.0(+64.0)#5753.0(+79.0)#2,258
58.58576130.068.0(+62.0)#5853.0(+77.0)#2,333
59.58639126.068.0(+58.0)#5953.0(+73.0)#2,490
60.58051124.068.0(+56.0)#6053.0(+71.0)#2,577
61.58577124.068.0(+56.0)#6153.0(+71.0)#2,578
62.58472123.068.0(+55.0)#6253.0(+70.0)#2,642
63.58642122.068.0(+54.0)#6353.0(+69.0)#2,685
64.58538118.068.0(+50.0)#6453.0(+65.0)#2,830
65.58461117.068.0(+49.0)#6553.0(+64.0)#2,910
66.58041116.068.0(+48.0)#6653.0(+63.0)#2,935
67.58768115.068.0(+47.0)#6753.0(+62.0)#3,008
68.58704111.068.0(+43.0)#6853.0(+58.0)#3,194
69.58069111.068.0(+43.0)#6953.0(+58.0)#3,242
70.58238111.068.0(+43.0)#7053.0(+58.0)#3,243
71.58318109.068.0(+41.0)#7153.0(+56.0)#3,321
72.58256109.068.0(+41.0)#7253.0(+56.0)#3,341
73.58341108.068.0(+40.0)#7353.0(+55.0)#3,397
74.58646108.068.0(+40.0)#7453.0(+55.0)#3,413
75.58561107.068.0(+39.0)#7553.0(+54.0)#3,485
76.58455107.068.0(+39.0)#7653.0(+54.0)#3,495
77.58348106.068.0(+38.0)#7753.0(+53.0)#3,560
78.58541106.068.0(+38.0)#7853.0(+53.0)#3,562
79.58261105.068.0(+37.0)#7953.0(+52.0)#3,617
80.58849104.068.0(+36.0)#8053.0(+51.0)#3,686
81.58533104.068.0(+36.0)#8153.0(+51.0)#3,690
82.58790103.068.0(+35.0)#8253.0(+50.0)#3,761
83.58757103.068.0(+35.0)#8353.0(+50.0)#3,764
84.58357103.068.0(+35.0)#8453.0(+50.0)#3,778
85.58464103.068.0(+35.0)#8553.0(+50.0)#3,786
86.58759100.068.0(+32.0)#8653.0(+47.0)#3,993
87.58230100.068.0(+32.0)#8753.0(+47.0)#3,996
88.58424100.068.0(+32.0)#8853.0(+47.0)#3,999
89.58210100.068.0(+32.0)#8953.0(+47.0)#4,011
90.5852399.068.0(+31.0)#9053.0(+46.0)#4,054
91.5874099.068.0(+31.0)#9153.0(+46.0)#4,088
92.5825999.068.0(+31.0)#9253.0(+46.0)#4,093
93.5863698.068.0(+30.0)#9353.0(+45.0)#4,157
94.5850197.068.0(+29.0)#9453.0(+44.0)#4,189
95.5807597.068.0(+29.0)#9553.0(+44.0)#4,207
96.5873596.068.0(+28.0)#9653.0(+43.0)#4,368
97.5855293.068.0(+25.0)#9753.0(+40.0)#4,620
98.5806492.068.0(+24.0)#9853.0(+39.0)#4,737
99.5860191.068.0(+23.0)#9953.0(+38.0)#4,751
100.5822991.068.0(+23.0)#10053.0(+38.0)#4,852

Common Questions

What are the Top 10 Zip Codes with the Most Births per 1,000 Women Below Poverty Level in North Dakota?
Top 10 Zip Codes with the Most Births per 1,000 Women Below Poverty Level in North Dakota are:
#1
733.0
#2
667.0
#3
563.0
#4
471.0
#5
467.0
#6
462.0
#7
413.0
#8
390.0
#9
357.0
#10
350.0
What zip code has the Most Births per 1,000 Women Below Poverty Level in North Dakota?
58488 has the Most Births per 1,000 Women Below Poverty Level in North Dakota with 733.0.
What is the Number of Births per 1,000 Women Below Poverty Level in the State of North Dakota?
Number of Births per 1,000 Women Below Poverty Level in North Dakota is 68.0.
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.