Zip Codes with the Most Births per 1,000 Women Below Poverty Level in South 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
South Dakota
Compare Zip Codes
Comparison Subject

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

0.0
1,000.0
Zip Codes with the Most Births per 1,000 Women Below Poverty Level in South Dakota Map

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

Zip Code Births / 1,000 Women vs State vs National
1. 57475 1,000.0 66.0 (+934)#1 53.0 (+947)#35
2. 57574 1,000.0 66.0 (+934)#2 53.0 (+947)#39
3. 57640 1,000.0 66.0 (+934)#3 53.0 (+947)#53
4. 57272 653.0 66.0 (+587)#4 53.0 (+600)#108
5. 57238 594.0 66.0 (+528)#5 53.0 (+541)#131
6. 57750 522.0 66.0 (+456)#6 53.0 (+469)#158
7. 57646 464.0 66.0 (+398)#7 53.0 (+411)#203
8. 57271 444.0 66.0 (+378)#8 53.0 (+391)#219
9. 57755 440.0 66.0 (+374)#9 53.0 (+387)#223
10. 57335 412.0 66.0 (+346)#10 53.0 (+359)#249
11. 57420 412.0 66.0 (+346)#11 53.0 (+359)#250
12. 57242 364.0 66.0 (+298)#12 53.0 (+311)#315
13. 57467 343.0 66.0 (+277)#13 53.0 (+290)#352
14. 57794 314.0 66.0 (+248)#14 53.0 (+261)#415
15. 57437 303.0 66.0 (+237)#15 53.0 (+250)#445
16. 57568 301.0 66.0 (+235)#16 53.0 (+248)#449
17. 57061 278.0 66.0 (+212)#17 53.0 (+225)#535
18. 57521 273.0 66.0 (+207)#18 53.0 (+220)#551
19. 57024 263.0 66.0 (+197)#19 53.0 (+210)#593
20. 57329 263.0 66.0 (+197)#20 53.0 (+210)#595
21. 57422 250.0 66.0 (+184)#21 53.0 (+197)#660
22. 57477 250.0 66.0 (+184)#22 53.0 (+197)#664
23. 57429 250.0 66.0 (+184)#23 53.0 (+197)#668
24. 57456 248.0 66.0 (+182)#24 53.0 (+195)#676
25. 57012 243.0 66.0 (+177)#25 53.0 (+190)#699
26. 57073 241.0 66.0 (+175)#26 53.0 (+188)#709
27. 57536 236.0 66.0 (+170)#27 53.0 (+183)#738
28. 57748 232.0 66.0 (+166)#28 53.0 (+179)#761
29. 57472 230.0 66.0 (+164)#29 53.0 (+177)#773
30. 57775 228.0 66.0 (+162)#30 53.0 (+175)#785
31. 57227 210.0 66.0 (+144)#31 53.0 (+157)#888
32. 57245 208.0 66.0 (+142)#32 53.0 (+155)#906
33. 57569 205.0 66.0 (+139)#33 53.0 (+152)#930
34. 57312 204.0 66.0 (+138)#34 53.0 (+151)#937
35. 57059 199.0 66.0 (+133)#35 53.0 (+146)#1,003
36. 57328 198.0 66.0 (+132)#36 53.0 (+145)#1,007
37. 57353 195.0 66.0 (+129)#37 53.0 (+142)#1,042
38. 57075 194.0 66.0 (+128)#38 53.0 (+141)#1,050
39. 57448 194.0 66.0 (+128)#39 53.0 (+141)#1,056
40. 57468 194.0 66.0 (+128)#40 53.0 (+141)#1,058
41. 57540 188.0 66.0 (+122)#41 53.0 (+135)#1,128
42. 57340 179.0 66.0 (+113)#42 53.0 (+126)#1,236
43. 57455 179.0 66.0 (+113)#43 53.0 (+126)#1,237
44. 57221 178.0 66.0 (+112)#44 53.0 (+125)#1,244
45. 57232 169.0 66.0 (+103)#45 53.0 (+116)#1,387
46. 57461 167.0 66.0 (+101)#46 53.0 (+114)#1,441
47. 57224 167.0 66.0 (+101)#47 53.0 (+114)#1,448
48. 57722 167.0 66.0 (+101)#48 53.0 (+114)#1,452
49. 57660 167.0 66.0 (+101)#49 53.0 (+114)#1,454
50. 57450 165.0 66.0 (+99.0)#50 53.0 (+112)#1,476
51. 57248 164.0 66.0 (+98.0)#51 53.0 (+111)#1,486
52. 57062 162.0 66.0 (+96.0)#52 53.0 (+109)#1,517
53. 57058 160.0 66.0 (+94.0)#53 53.0 (+107)#1,552
54. 57323 160.0 66.0 (+94.0)#54 53.0 (+107)#1,566
55. 57367 159.0 66.0 (+93.0)#55 53.0 (+106)#1,584
56. 57544 158.0 66.0 (+92.0)#56 53.0 (+105)#1,605
57. 57331 154.0 66.0 (+88.0)#57 53.0 (+101)#1,674
58. 57332 150.0 66.0 (+84.0)#58 53.0 (+97.0)#1,755
59. 57633 149.0 66.0 (+83.0)#59 53.0 (+96.0)#1,779
60. 57725 147.0 66.0 (+81.0)#60 53.0 (+94.0)#1,827
61. 57559 144.0 66.0 (+78.0)#61 53.0 (+91.0)#1,898
62. 57773 139.0 66.0 (+73.0)#62 53.0 (+86.0)#2,044
63. 57033 137.0 66.0 (+71.0)#63 53.0 (+84.0)#2,086
64. 57068 135.0 66.0 (+69.0)#64 53.0 (+82.0)#2,156
65. 57361 135.0 66.0 (+69.0)#65 53.0 (+82.0)#2,183
66. 57216 132.0 66.0 (+66.0)#66 53.0 (+79.0)#2,266
67. 57555 131.0 66.0 (+65.0)#67 53.0 (+78.0)#2,289
68. 57632 130.0 66.0 (+64.0)#68 53.0 (+77.0)#2,338
69. 57330 130.0 66.0 (+64.0)#69 53.0 (+77.0)#2,343
70. 57004 128.0 66.0 (+62.0)#70 53.0 (+75.0)#2,399
71. 57621 127.0 66.0 (+61.0)#71 53.0 (+74.0)#2,470
72. 57042 125.0 66.0 (+59.0)#72 53.0 (+72.0)#2,505
73. 57274 125.0 66.0 (+59.0)#73 53.0 (+72.0)#2,522
74. 57369 125.0 66.0 (+59.0)#74 53.0 (+72.0)#2,523
75. 57365 125.0 66.0 (+59.0)#75 53.0 (+72.0)#2,534
76. 57212 124.0 66.0 (+58.0)#76 53.0 (+71.0)#2,575
77. 57724 120.0 66.0 (+54.0)#77 53.0 (+67.0)#2,767
78. 57626 119.0 66.0 (+53.0)#78 53.0 (+66.0)#2,793
79. 57661 119.0 66.0 (+53.0)#79 53.0 (+66.0)#2,802
80. 57601 118.0 66.0 (+52.0)#80 53.0 (+65.0)#2,818
81. 57620 118.0 66.0 (+52.0)#81 53.0 (+65.0)#2,850
82. 57639 118.0 66.0 (+52.0)#82 53.0 (+65.0)#2,858
83. 57078 117.0 66.0 (+51.0)#83 53.0 (+64.0)#2,869
84. 57380 117.0 66.0 (+51.0)#84 53.0 (+64.0)#2,886
85. 57756 116.0 66.0 (+50.0)#85 53.0 (+63.0)#2,948
86. 57623 115.0 66.0 (+49.0)#86 53.0 (+62.0)#2,999
87. 57441 115.0 66.0 (+49.0)#87 53.0 (+62.0)#3,004
88. 57652 114.0 66.0 (+48.0)#88 53.0 (+61.0)#3,061
89. 57445 113.0 66.0 (+47.0)#89 53.0 (+60.0)#3,091
90. 57032 110.0 66.0 (+44.0)#90 53.0 (+57.0)#3,256
91. 57350 109.0 66.0 (+43.0)#91 53.0 (+56.0)#3,313
92. 57772 108.0 66.0 (+42.0)#92 53.0 (+55.0)#3,408
93. 57257 108.0 66.0 (+42.0)#93 53.0 (+55.0)#3,421
94. 57528 107.0 66.0 (+41.0)#94 53.0 (+54.0)#3,487
95. 57424 107.0 66.0 (+41.0)#95 53.0 (+54.0)#3,498
96. 57233 107.0 66.0 (+41.0)#96 53.0 (+54.0)#3,501
97. 57339 106.0 66.0 (+40.0)#97 53.0 (+53.0)#3,549
98. 57317 105.0 66.0 (+39.0)#98 53.0 (+52.0)#3,622
99. 57451 104.0 66.0 (+38.0)#99 53.0 (+51.0)#3,670
100. 57218 103.0 66.0 (+37.0)#100 53.0 (+50.0)#3,783

Common Questions

What are the Top 10 Zip Codes with the Most Births per 1,000 Women Below Poverty Level in South Dakota?
Top 10 Zip Codes with the Most Births per 1,000 Women Below Poverty Level in South Dakota are:
#1
1,000.0
#2
1,000.0
#3
1,000.0
#4
653.0
#5
594.0
#6
522.0
#7
464.0
#8
444.0
#9
440.0
#10
412.0
What zip code has the Most Births per 1,000 Women Below Poverty Level in South Dakota?
57475 has the Most Births per 1,000 Women Below Poverty Level in South Dakota with 1,000.0.
What is the Number of Births per 1,000 Women Below Poverty Level in the State of South Dakota?
Number of Births per 1,000 Women Below Poverty Level in South Dakota is 66.0.
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.