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

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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
Michigan
Compare Zip Codes
Comparison Subject

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

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

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

Zip Code Births / 1,000 Women vs State vs National
1. 49084 1,000.0 53.0 (+947)#1 53.0 (+947)#60
2. 48896 632.0 53.0 (+579)#2 53.0 (+579)#115
3. 49929 517.0 53.0 (+464)#3 53.0 (+464)#161
4. 49881 361.0 53.0 (+308)#4 53.0 (+308)#324
5. 49627 326.0 53.0 (+273)#5 53.0 (+273)#394
6. 49791 286.0 53.0 (+233)#6 53.0 (+233)#505
7. 48050 274.0 53.0 (+221)#7 53.0 (+221)#546
8. 49320 260.0 53.0 (+207)#8 53.0 (+207)#610
9. 49827 250.0 53.0 (+197)#9 53.0 (+197)#646
10. 48434 250.0 53.0 (+197)#10 53.0 (+197)#662
11. 49959 242.0 53.0 (+189)#11 53.0 (+189)#704
12. 49710 236.0 53.0 (+183)#12 53.0 (+183)#737
13. 49874 225.0 53.0 (+172)#13 53.0 (+172)#802
14. 49745 222.0 53.0 (+169)#14 53.0 (+169)#819
15. 49892 209.0 53.0 (+156)#15 53.0 (+156)#891
16. 49818 208.0 53.0 (+155)#16 53.0 (+155)#901
17. 49796 197.0 53.0 (+144)#17 53.0 (+144)#1,024
18. 48122 192.0 53.0 (+139)#18 53.0 (+139)#1,070
19. 48845 192.0 53.0 (+139)#19 53.0 (+139)#1,072
20. 49853 190.0 53.0 (+137)#20 53.0 (+137)#1,094
21. 48157 187.0 53.0 (+134)#21 53.0 (+134)#1,135
22. 49288 174.0 53.0 (+121)#22 53.0 (+121)#1,298
23. 49971 174.0 53.0 (+121)#23 53.0 (+121)#1,307
24. 49921 167.0 53.0 (+114)#24 53.0 (+114)#1,438
25. 49628 167.0 53.0 (+114)#25 53.0 (+114)#1,445
26. 49261 165.0 53.0 (+112)#26 53.0 (+112)#1,478
27. 48014 162.0 53.0 (+109)#27 53.0 (+109)#1,513
28. 48628 158.0 53.0 (+105)#28 53.0 (+105)#1,593
29. 49125 155.0 53.0 (+102)#29 53.0 (+102)#1,647
30. 49716 146.0 53.0 (+93.0)#30 53.0 (+93.0)#1,842
31. 49611 146.0 53.0 (+93.0)#31 53.0 (+93.0)#1,846
32. 49259 139.0 53.0 (+86.0)#32 53.0 (+86.0)#2,026
33. 49834 136.0 53.0 (+83.0)#33 53.0 (+83.0)#2,136
34. 48754 132.0 53.0 (+79.0)#34 53.0 (+79.0)#2,269
35. 48051 128.0 53.0 (+75.0)#35 53.0 (+75.0)#2,386
36. 49026 127.0 53.0 (+74.0)#36 53.0 (+74.0)#2,453
37. 49970 127.0 53.0 (+74.0)#37 53.0 (+74.0)#2,469
38. 48890 126.0 53.0 (+73.0)#38 53.0 (+73.0)#2,489
39. 49709 125.0 53.0 (+72.0)#39 53.0 (+72.0)#2,519
40. 49083 124.0 53.0 (+71.0)#40 53.0 (+71.0)#2,560
41. 49726 123.0 53.0 (+70.0)#41 53.0 (+70.0)#2,628
42. 49326 122.0 53.0 (+69.0)#42 53.0 (+69.0)#2,659
43. 49310 122.0 53.0 (+69.0)#43 53.0 (+69.0)#2,662
44. 49665 121.0 53.0 (+68.0)#44 53.0 (+68.0)#2,698
45. 48427 121.0 53.0 (+68.0)#45 53.0 (+68.0)#2,705
46. 48846 118.0 53.0 (+65.0)#46 53.0 (+65.0)#2,805
47. 49436 118.0 53.0 (+65.0)#47 53.0 (+65.0)#2,833
48. 48852 118.0 53.0 (+65.0)#48 53.0 (+65.0)#2,863
49. 48847 117.0 53.0 (+64.0)#49 53.0 (+64.0)#2,880
50. 49010 115.0 53.0 (+62.0)#50 53.0 (+62.0)#2,963
51. 49968 115.0 53.0 (+62.0)#51 53.0 (+62.0)#2,987
52. 49267 113.0 53.0 (+60.0)#52 53.0 (+60.0)#3,082
53. 49645 113.0 53.0 (+60.0)#53 53.0 (+60.0)#3,092
54. 49459 112.0 53.0 (+59.0)#54 53.0 (+59.0)#3,156
55. 48144 111.0 53.0 (+58.0)#55 53.0 (+58.0)#3,185
56. 49249 111.0 53.0 (+58.0)#56 53.0 (+58.0)#3,201
57. 49744 111.0 53.0 (+58.0)#57 53.0 (+58.0)#3,216
58. 49412 110.0 53.0 (+57.0)#58 53.0 (+57.0)#3,252
59. 48412 110.0 53.0 (+57.0)#59 53.0 (+57.0)#3,265
60. 49448 110.0 53.0 (+57.0)#60 53.0 (+57.0)#3,271
61. 48027 110.0 53.0 (+57.0)#61 53.0 (+57.0)#3,278
62. 49065 108.0 53.0 (+55.0)#62 53.0 (+55.0)#3,383
63. 49631 108.0 53.0 (+55.0)#63 53.0 (+55.0)#3,387
64. 49248 108.0 53.0 (+55.0)#64 53.0 (+55.0)#3,415
65. 49935 107.0 53.0 (+54.0)#65 53.0 (+54.0)#3,440
66. 48428 107.0 53.0 (+54.0)#66 53.0 (+54.0)#3,441
67. 49969 107.0 53.0 (+54.0)#67 53.0 (+54.0)#3,484
68. 49950 107.0 53.0 (+54.0)#68 53.0 (+54.0)#3,488
69. 49965 107.0 53.0 (+54.0)#69 53.0 (+54.0)#3,493
70. 49031 106.0 53.0 (+53.0)#70 53.0 (+53.0)#3,518
71. 48756 106.0 53.0 (+53.0)#71 53.0 (+53.0)#3,529
72. 49425 106.0 53.0 (+53.0)#72 53.0 (+53.0)#3,532
73. 49895 106.0 53.0 (+53.0)#73 53.0 (+53.0)#3,558
74. 49836 104.0 53.0 (+51.0)#74 53.0 (+51.0)#3,689
75. 48657 103.0 53.0 (+50.0)#75 53.0 (+50.0)#3,714
76. 49615 103.0 53.0 (+50.0)#76 53.0 (+50.0)#3,734
77. 49452 103.0 53.0 (+50.0)#77 53.0 (+50.0)#3,746
78. 49102 103.0 53.0 (+50.0)#78 53.0 (+50.0)#3,759
79. 49343 102.0 53.0 (+49.0)#79 53.0 (+49.0)#3,805
80. 49330 102.0 53.0 (+49.0)#80 53.0 (+49.0)#3,807
81. 48876 100.0 53.0 (+47.0)#81 53.0 (+47.0)#3,944
82. 48238 99.0 53.0 (+46.0)#82 53.0 (+46.0)#4,022
83. 49045 99.0 53.0 (+46.0)#83 53.0 (+46.0)#4,045
84. 48417 99.0 53.0 (+46.0)#84 53.0 (+46.0)#4,061
85. 48742 98.0 53.0 (+45.0)#85 53.0 (+45.0)#4,144
86. 49894 98.0 53.0 (+45.0)#86 53.0 (+45.0)#4,158
87. 48457 97.0 53.0 (+44.0)#87 53.0 (+44.0)#4,208
88. 49663 97.0 53.0 (+44.0)#88 53.0 (+44.0)#4,214
89. 48836 96.0 53.0 (+43.0)#89 53.0 (+43.0)#4,296
90. 49270 96.0 53.0 (+43.0)#90 53.0 (+43.0)#4,320
91. 49688 96.0 53.0 (+43.0)#91 53.0 (+43.0)#4,343
92. 48603 95.0 53.0 (+42.0)#92 53.0 (+42.0)#4,375
93. 48505 95.0 53.0 (+42.0)#93 53.0 (+42.0)#4,383
94. 48871 95.0 53.0 (+42.0)#94 53.0 (+42.0)#4,438
95. 48701 95.0 53.0 (+42.0)#95 53.0 (+42.0)#4,452
96. 48519 94.0 53.0 (+41.0)#96 53.0 (+41.0)#4,506
97. 49090 93.0 53.0 (+40.0)#97 53.0 (+40.0)#4,578
98. 49801 93.0 53.0 (+40.0)#98 53.0 (+40.0)#4,581
99. 49706 93.0 53.0 (+40.0)#99 53.0 (+40.0)#4,593
100. 49303 93.0 53.0 (+40.0)#100 53.0 (+40.0)#4,633

Common Questions

What are the Top 10 Zip Codes with the Most Births per 1,000 Women Below Poverty Level in Michigan?
Top 10 Zip Codes with the Most Births per 1,000 Women Below Poverty Level in Michigan are:
#1
1,000.0
#2
632.0
#3
517.0
#4
361.0
#5
326.0
#6
286.0
#7
274.0
#8
260.0
#9
250.0
#10
250.0
What zip code has the Most Births per 1,000 Women Below Poverty Level in Michigan?
49084 has the Most Births per 1,000 Women Below Poverty Level in Michigan with 1,000.0.
What is the Number of Births per 1,000 Women Below Poverty Level in the State of Michigan?
Number of Births per 1,000 Women Below Poverty Level in Michigan is 53.0.
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.