Zip Codes with the Lowest Births per 1,000 Women in Labor Force in South Dakota

RELATED REPORTS & OPTIONS

Lowest 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
South Dakota
Compare Zip Codes
Comparison Subject

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

80.0
0.0
Zip Codes with the Lowest Births per 1,000 Women in Labor Force in South Dakota Map

Zip Codes with the Lowest Births per 1,000 Women in Labor Force in South Dakota

Zip Code Births / 1,000 Women vs State vs National
1. 57732 4.0 59.0 (-55.0)#1 48.0 (-44.0)#157
2. 57260 6.0 59.0 (-53.0)#2 48.0 (-42.0)#302
3. 57241 6.0 59.0 (-53.0)#3 48.0 (-42.0)#304
4. 57018 7.0 59.0 (-52.0)#4 48.0 (-41.0)#393
5. 57279 9.0 59.0 (-50.0)#5 48.0 (-39.0)#660
6. 57370 9.0 59.0 (-50.0)#6 48.0 (-39.0)#667
7. 57031 10.0 59.0 (-49.0)#7 48.0 (-38.0)#823
8. 57532 11.0 59.0 (-48.0)#8 48.0 (-37.0)#939
9. 57268 13.0 59.0 (-46.0)#9 48.0 (-35.0)#1,341
10. 57572 14.0 59.0 (-45.0)#10 48.0 (-34.0)#1,497
11. 57638 16.0 59.0 (-43.0)#11 48.0 (-32.0)#1,877
12. 57071 17.0 59.0 (-42.0)#12 48.0 (-31.0)#2,038
13. 57014 17.0 59.0 (-42.0)#13 48.0 (-31.0)#2,071
14. 57006 18.0 59.0 (-41.0)#14 48.0 (-30.0)#2,147
15. 57442 18.0 59.0 (-41.0)#15 48.0 (-30.0)#2,270
16. 57234 18.0 59.0 (-41.0)#16 48.0 (-30.0)#2,291
17. 57259 18.0 59.0 (-41.0)#17 48.0 (-30.0)#2,313
18. 57570 19.0 59.0 (-40.0)#18 48.0 (-29.0)#2,484
19. 57783 20.0 59.0 (-39.0)#19 48.0 (-28.0)#2,609
20. 57016 20.0 59.0 (-39.0)#20 48.0 (-28.0)#2,785
21. 57522 20.0 59.0 (-39.0)#21 48.0 (-28.0)#2,789
22. 57436 20.0 59.0 (-39.0)#22 48.0 (-28.0)#2,791
23. 57465 20.0 59.0 (-39.0)#23 48.0 (-28.0)#2,793
24. 57220 22.0 59.0 (-37.0)#24 48.0 (-26.0)#3,286
25. 57720 22.0 59.0 (-37.0)#25 48.0 (-26.0)#3,295
26. 57793 23.0 59.0 (-36.0)#26 48.0 (-25.0)#3,516
27. 57063 23.0 59.0 (-36.0)#27 48.0 (-25.0)#3,548
28. 57314 23.0 59.0 (-36.0)#28 48.0 (-25.0)#3,559
29. 57434 23.0 59.0 (-36.0)#29 48.0 (-25.0)#3,563
30. 57265 23.0 59.0 (-36.0)#30 48.0 (-25.0)#3,569
31. 57533 24.0 59.0 (-35.0)#31 48.0 (-24.0)#3,811
32. 57048 24.0 59.0 (-35.0)#32 48.0 (-24.0)#3,825
33. 57368 25.0 59.0 (-34.0)#33 48.0 (-23.0)#4,113
34. 57266 25.0 59.0 (-34.0)#34 48.0 (-23.0)#4,129
35. 57270 26.0 59.0 (-33.0)#35 48.0 (-22.0)#4,420
36. 57717 27.0 59.0 (-32.0)#36 48.0 (-21.0)#4,602
37. 57366 27.0 59.0 (-32.0)#37 48.0 (-21.0)#4,663
38. 57580 29.0 59.0 (-30.0)#38 48.0 (-19.0)#5,203
39. 57745 29.0 59.0 (-30.0)#39 48.0 (-19.0)#5,259
40. 57315 29.0 59.0 (-30.0)#40 48.0 (-19.0)#5,284
41. 57375 29.0 59.0 (-30.0)#41 48.0 (-19.0)#5,301
42. 57438 30.0 59.0 (-29.0)#42 48.0 (-18.0)#5,584
43. 57035 31.0 59.0 (-28.0)#43 48.0 (-17.0)#5,865
44. 57703 32.0 59.0 (-27.0)#44 48.0 (-16.0)#6,018
45. 57623 32.0 59.0 (-27.0)#45 48.0 (-16.0)#6,212
46. 57045 33.0 59.0 (-26.0)#46 48.0 (-15.0)#6,521
47. 57428 33.0 59.0 (-26.0)#47 48.0 (-15.0)#6,547
48. 57264 33.0 59.0 (-26.0)#48 48.0 (-15.0)#6,556
49. 57311 34.0 59.0 (-25.0)#49 48.0 (-14.0)#6,817
50. 57223 35.0 59.0 (-24.0)#50 48.0 (-13.0)#7,140
51. 57383 35.0 59.0 (-24.0)#51 48.0 (-13.0)#7,152
52. 57069 36.0 59.0 (-23.0)#52 48.0 (-12.0)#7,312
53. 57730 36.0 59.0 (-23.0)#53 48.0 (-12.0)#7,363
54. 57301 37.0 59.0 (-22.0)#54 48.0 (-11.0)#7,608
55. 57005 37.0 59.0 (-22.0)#55 48.0 (-11.0)#7,660
56. 57747 37.0 59.0 (-22.0)#56 48.0 (-11.0)#7,709
57. 57719 38.0 59.0 (-21.0)#57 48.0 (-10.00)#7,962
58. 57013 38.0 59.0 (-21.0)#58 48.0 (-10.00)#8,033
59. 57235 38.0 59.0 (-21.0)#59 48.0 (-10.00)#8,118
60. 57328 39.0 59.0 (-20.0)#61 48.0 (-9.00)#8,437
61. 57273 39.0 59.0 (-20.0)#62 48.0 (-9.00)#8,438
62. 57262 40.0 59.0 (-19.0)#63 48.0 (-8.00)#8,694
63. 57430 41.0 59.0 (-18.0)#64 48.0 (-7.00)#9,093
64. 57523 41.0 59.0 (-18.0)#65 48.0 (-7.00)#9,114
65. 57039 42.0 59.0 (-17.0)#66 48.0 (-6.00)#9,388
66. 57077 42.0 59.0 (-17.0)#67 48.0 (-6.00)#9,454
67. 57249 42.0 59.0 (-17.0)#68 48.0 (-6.00)#9,469
68. 57201 43.0 59.0 (-16.0)#69 48.0 (-5.00)#9,598
69. 57754 43.0 59.0 (-16.0)#70 48.0 (-5.00)#9,730
70. 57362 43.0 59.0 (-16.0)#71 48.0 (-5.00)#9,768
71. 57026 43.0 59.0 (-16.0)#72 48.0 (-5.00)#9,777
72. 57312 43.0 59.0 (-16.0)#73 48.0 (-5.00)#9,800
73. 57648 44.0 59.0 (-15.0)#74 48.0 (-4.00)#10,108
74. 57053 45.0 59.0 (-14.0)#75 48.0 (-3.00)#10,398
75. 57225 45.0 59.0 (-14.0)#76 48.0 (-3.00)#10,405
76. 57248 45.0 59.0 (-14.0)#77 48.0 (-3.00)#10,428
77. 57716 45.0 59.0 (-14.0)#78 48.0 (-3.00)#10,456
78. 57579 46.0 59.0 (-13.0)#79 48.0 (-2.00)#10,729
79. 57319 46.0 59.0 (-13.0)#80 48.0 (-2.00)#10,741
80. 57702 47.0 59.0 (-12.0)#81 48.0 (-1.000)#10,815
81. 57110 47.0 59.0 (-12.0)#82 48.0 (-1.000)#10,872
82. 57785 47.0 59.0 (-12.0)#83 48.0 (-1.000)#10,931
83. 57015 47.0 59.0 (-12.0)#84 48.0 (-1.000)#11,046
84. 57334 50.0 59.0 (-9.00)#85 48.0 (+2.00)#11,936
85. 57022 51.0 59.0 (-8.00)#86 48.0 (+3.00)#12,147
86. 57313 51.0 59.0 (-8.00)#87 48.0 (+3.00)#12,218
87. 57276 51.0 59.0 (-8.00)#88 48.0 (+3.00)#12,225
88. 57274 52.0 59.0 (-7.00)#89 48.0 (+4.00)#12,475
89. 57214 53.0 59.0 (-6.00)#90 48.0 (+5.00)#12,800
90. 57105 54.0 59.0 (-5.00)#91 48.0 (+6.00)#12,903
91. 57469 55.0 59.0 (-4.00)#92 48.0 (+7.00)#13,319
92. 57072 55.0 59.0 (-4.00)#93 48.0 (+7.00)#13,373
93. 57052 56.0 59.0 (-3.00)#94 48.0 (+8.00)#13,635
94. 57049 57.0 59.0 (-2.00)#95 48.0 (+9.00)#13,796
95. 57790 59.0 59.0 (=0.000)#96 48.0 (+11.0)#14,342
96. 57348 59.0 59.0 (=0.000)#97 48.0 (+11.0)#14,344
97. 57231 60.0 59.0 (+1.000)#98 48.0 (+12.0)#14,541
98. 57701 62.0 59.0 (+3.00)#99 48.0 (+14.0)#14,793
99. 57104 62.0 59.0 (+3.00)#100 48.0 (+14.0)#14,848
100. 57325 62.0 59.0 (+3.00)#101 48.0 (+14.0)#14,966

Common Questions

What are the Top 10 Zip Codes with the Lowest Births per 1,000 Women in Labor Force in South Dakota?
Top 10 Zip Codes with the Lowest Births per 1,000 Women in Labor Force in South Dakota are:
#1
4.0
#2
6.0
#3
6.0
#4
7.0
#5
9.0
#6
9.0
#7
10.0
#8
11.0
#9
13.0
#10
14.0
What zip code has the Lowest Births per 1,000 Women in Labor Force in South Dakota?
57732 has the Lowest Births per 1,000 Women in Labor Force in South Dakota with 4.0.
What is the Number Births per 1,000 Women in Labor Force in the State of South Dakota?
Number Births per 1,000 Women in Labor Force in South Dakota is 59.0.
What is the Number Births per 1,000 Women in Labor Force in the United States?
Number Births per 1,000 Women in Labor Force in the United States is 48.0.