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
1.490841,000.053.0(+947)#153.0(+947)#60
2.48896632.053.0(+579)#253.0(+579)#115
3.49929517.053.0(+464)#353.0(+464)#161
4.49881361.053.0(+308)#453.0(+308)#324
5.49627326.053.0(+273)#553.0(+273)#394
6.49791286.053.0(+233)#653.0(+233)#505
7.48050274.053.0(+221)#753.0(+221)#546
8.49320260.053.0(+207)#853.0(+207)#610
9.49827250.053.0(+197)#953.0(+197)#646
10.48434250.053.0(+197)#1053.0(+197)#662
11.49959242.053.0(+189)#1153.0(+189)#704
12.49710236.053.0(+183)#1253.0(+183)#737
13.49874225.053.0(+172)#1353.0(+172)#802
14.49745222.053.0(+169)#1453.0(+169)#819
15.49892209.053.0(+156)#1553.0(+156)#891
16.49818208.053.0(+155)#1653.0(+155)#901
17.49796197.053.0(+144)#1753.0(+144)#1,024
18.48122192.053.0(+139)#1853.0(+139)#1,070
19.48845192.053.0(+139)#1953.0(+139)#1,072
20.49853190.053.0(+137)#2053.0(+137)#1,094
21.48157187.053.0(+134)#2153.0(+134)#1,135
22.49288174.053.0(+121)#2253.0(+121)#1,298
23.49971174.053.0(+121)#2353.0(+121)#1,307
24.49921167.053.0(+114)#2453.0(+114)#1,438
25.49628167.053.0(+114)#2553.0(+114)#1,445
26.49261165.053.0(+112)#2653.0(+112)#1,478
27.48014162.053.0(+109)#2753.0(+109)#1,513
28.48628158.053.0(+105)#2853.0(+105)#1,593
29.49125155.053.0(+102)#2953.0(+102)#1,647
30.49716146.053.0(+93.0)#3053.0(+93.0)#1,842
31.49611146.053.0(+93.0)#3153.0(+93.0)#1,846
32.49259139.053.0(+86.0)#3253.0(+86.0)#2,026
33.49834136.053.0(+83.0)#3353.0(+83.0)#2,136
34.48754132.053.0(+79.0)#3453.0(+79.0)#2,269
35.48051128.053.0(+75.0)#3553.0(+75.0)#2,386
36.49026127.053.0(+74.0)#3653.0(+74.0)#2,453
37.49970127.053.0(+74.0)#3753.0(+74.0)#2,469
38.48890126.053.0(+73.0)#3853.0(+73.0)#2,489
39.49709125.053.0(+72.0)#3953.0(+72.0)#2,519
40.49083124.053.0(+71.0)#4053.0(+71.0)#2,560
41.49726123.053.0(+70.0)#4153.0(+70.0)#2,628
42.49326122.053.0(+69.0)#4253.0(+69.0)#2,659
43.49310122.053.0(+69.0)#4353.0(+69.0)#2,662
44.49665121.053.0(+68.0)#4453.0(+68.0)#2,698
45.48427121.053.0(+68.0)#4553.0(+68.0)#2,705
46.48846118.053.0(+65.0)#4653.0(+65.0)#2,805
47.49436118.053.0(+65.0)#4753.0(+65.0)#2,833
48.48852118.053.0(+65.0)#4853.0(+65.0)#2,863
49.48847117.053.0(+64.0)#4953.0(+64.0)#2,880
50.49010115.053.0(+62.0)#5053.0(+62.0)#2,963
51.49968115.053.0(+62.0)#5153.0(+62.0)#2,987
52.49267113.053.0(+60.0)#5253.0(+60.0)#3,082
53.49645113.053.0(+60.0)#5353.0(+60.0)#3,092
54.49459112.053.0(+59.0)#5453.0(+59.0)#3,156
55.48144111.053.0(+58.0)#5553.0(+58.0)#3,185
56.49249111.053.0(+58.0)#5653.0(+58.0)#3,201
57.49744111.053.0(+58.0)#5753.0(+58.0)#3,216
58.49412110.053.0(+57.0)#5853.0(+57.0)#3,252
59.48412110.053.0(+57.0)#5953.0(+57.0)#3,265
60.49448110.053.0(+57.0)#6053.0(+57.0)#3,271
61.48027110.053.0(+57.0)#6153.0(+57.0)#3,278
62.49065108.053.0(+55.0)#6253.0(+55.0)#3,383
63.49631108.053.0(+55.0)#6353.0(+55.0)#3,387
64.49248108.053.0(+55.0)#6453.0(+55.0)#3,415
65.49935107.053.0(+54.0)#6553.0(+54.0)#3,440
66.48428107.053.0(+54.0)#6653.0(+54.0)#3,441
67.49969107.053.0(+54.0)#6753.0(+54.0)#3,484
68.49950107.053.0(+54.0)#6853.0(+54.0)#3,488
69.49965107.053.0(+54.0)#6953.0(+54.0)#3,493
70.49031106.053.0(+53.0)#7053.0(+53.0)#3,518
71.48756106.053.0(+53.0)#7153.0(+53.0)#3,529
72.49425106.053.0(+53.0)#7253.0(+53.0)#3,532
73.49895106.053.0(+53.0)#7353.0(+53.0)#3,558
74.49836104.053.0(+51.0)#7453.0(+51.0)#3,689
75.48657103.053.0(+50.0)#7553.0(+50.0)#3,714
76.49615103.053.0(+50.0)#7653.0(+50.0)#3,734
77.49452103.053.0(+50.0)#7753.0(+50.0)#3,746
78.49102103.053.0(+50.0)#7853.0(+50.0)#3,759
79.49343102.053.0(+49.0)#7953.0(+49.0)#3,805
80.49330102.053.0(+49.0)#8053.0(+49.0)#3,807
81.48876100.053.0(+47.0)#8153.0(+47.0)#3,944
82.4823899.053.0(+46.0)#8253.0(+46.0)#4,022
83.4904599.053.0(+46.0)#8353.0(+46.0)#4,045
84.4841799.053.0(+46.0)#8453.0(+46.0)#4,061
85.4874298.053.0(+45.0)#8553.0(+45.0)#4,144
86.4989498.053.0(+45.0)#8653.0(+45.0)#4,158
87.4845797.053.0(+44.0)#8753.0(+44.0)#4,208
88.4966397.053.0(+44.0)#8853.0(+44.0)#4,214
89.4883696.053.0(+43.0)#8953.0(+43.0)#4,296
90.4927096.053.0(+43.0)#9053.0(+43.0)#4,320
91.4968896.053.0(+43.0)#9153.0(+43.0)#4,343
92.4860395.053.0(+42.0)#9253.0(+42.0)#4,375
93.4850595.053.0(+42.0)#9353.0(+42.0)#4,383
94.4887195.053.0(+42.0)#9453.0(+42.0)#4,438
95.4870195.053.0(+42.0)#9553.0(+42.0)#4,452
96.4851994.053.0(+41.0)#9653.0(+41.0)#4,506
97.4909093.053.0(+40.0)#9753.0(+40.0)#4,578
98.4980193.053.0(+40.0)#9853.0(+40.0)#4,581
99.4970693.053.0(+40.0)#9953.0(+40.0)#4,593
100.4930393.053.0(+40.0)#10053.0(+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.