Zip Codes with the Highest Child Poverty Level Among Girls Under the Age of 16 in Miami, FL

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Highest Poverty | Girls 0-16
Population
Families and Households
Female Fertility
Female Fertility (Unmarried)
Race (Community Size)
Race (Percentage)
Ancestry (Community Size)
AfghanAfricanAlbanianAmericanApacheArabArgentineanArmenianAustralianAustrianBahamianBarbadianBasqueBelgianBelizeanBermudanBhutaneseBlackfeetBolivianBrazilianBritishBritish West IndianBulgarianBurmeseCanadianCelticCentral AmericanCentral American IndianCherokeeChickasawChileanChippewaChoctawColombianComancheCosta RicanCreekCroatianCubanCypriotCzechCzechoslovakianDanishDominicanDutchDutch West IndianEastern EuropeanEcuadorianEgyptianEnglishEstonianEthiopianEuropeanFilipinoFinnishFrenchFrench American IndianFrench CanadianGermanGreekGuamanian / ChamorroGuatemalanGuyaneseHaitianHonduranHungarianIcelanderIndian (Asian)IndonesianInupiatIranianIraqiIrishIroquoisIsraeliItalianJamaicanJapaneseJordanianKenyanKoreanLaotianLatvianLebaneseLithuanianMacedonianMalaysianMalteseMexicanMexican American IndianMongolianMoroccanNative HawaiianNavajoNew ZealanderNicaraguanNigerianNorthern EuropeanNorwegianPakistaniPalestinianPanamanianParaguayanPennsylvania GermanPeruvianPolishPortuguesePuerto RicanRomanianRussianSalvadoranSamoanScandinavianScotch-IrishScottishSeminoleSenegaleseSerbianSiouxSlavicSlovakSloveneSouth AfricanSouth AmericanSouth American IndianSpaniardSpanishSpanish AmericanSpanish American IndianSri LankanSubsaharan AfricanSudaneseSwedishSwissSyrianThaiTrinidadian and TobagonianTurkishU.S. Virgin IslanderUkrainianUruguayanVenezuelanVietnameseWelshWest IndianYugoslavianZimbabwean
Ancestry (Percentage)
AfghanAfricanAlbanianAmericanApacheArabArgentineanArmenianAustralianAustrianBahamianBarbadianBasqueBelgianBelizeanBermudanBhutaneseBlackfeetBolivianBrazilianBritishBritish West IndianBulgarianBurmeseCanadianCelticCentral AmericanCentral American IndianCherokeeChickasawChileanChippewaChoctawColombianComancheCosta RicanCreekCroatianCubanCypriotCzechCzechoslovakianDanishDominicanDutchDutch West IndianEastern EuropeanEcuadorianEgyptianEnglishEstonianEthiopianEuropeanFilipinoFinnishFrenchFrench American IndianFrench CanadianGermanGreekGuamanian / ChamorroGuatemalanGuyaneseHaitianHonduranHungarianIcelanderIndian (Asian)IndonesianInupiatIranianIraqiIrishIroquoisIsraeliItalianJamaicanJapaneseJordanianKenyanKoreanLaotianLatvianLebaneseLithuanianMacedonianMalaysianMalteseMexicanMexican American IndianMongolianMoroccanNative HawaiianNavajoNew ZealanderNicaraguanNigerianNorthern EuropeanNorwegianPakistaniPalestinianPanamanianParaguayanPennsylvania GermanPeruvianPolishPortuguesePuerto RicanRomanianRussianSalvadoranSamoanScandinavianScotch-IrishScottishSeminoleSenegaleseSerbianSiouxSlavicSlovakSloveneSouth AfricanSouth AmericanSouth American IndianSpaniardSpanishSpanish AmericanSpanish American IndianSri LankanSubsaharan AfricanSudaneseSwedishSwissSyrianThaiTrinidadian and TobagonianTurkishU.S. Virgin IslanderUkrainianUruguayanVenezuelanVietnameseWelshWest IndianYugoslavianZimbabwean
Immigrant Origin (Total)
AfghanistanAfricaAlbaniaArgentinaArmeniaAsiaAustraliaAustriaBahamasBangladeshBarbadosBelarusBelgiumBelizeBoliviaBosnia and HerzegovinaBrazilBulgariaBurma / MyanmarCambodiaCameroonCanadaCaribbeanCentral AmericaChileChinaColombiaCosta RicaCroatiaCubaCzechoslovakiaDenmarkDominicaDominican RepublicEastern AfricaEastern AsiaEastern EuropeEcuadorEgyptEl SalvadorEnglandEthiopiaEuropeFranceGermanyGreeceGrenadaGuatemalaGuyanaHaitiHondurasHong KongHungaryIndiaIndonesiaIranIraqIrelandIsraelItalyJamaicaJapanJordanKazakhstanKenyaKoreaKuwaitLaosLatin AmericaLatviaLebanonLithuaniaMalaysiaMexicoMiddle AfricaMoldovaMoroccoNepalNetherlandsNicaraguaNigeriaNorthern AfricaNorthern EuropeNorwayOceaniaPakistanPanamaPeruPhilippinesPolandPortugalRomaniaRussiaSaudi ArabiaScotlandSerbiaSingaporeSouth AfricaSouth AmericaSouth Central AsiaSouth Eastern AsiaSouthern EuropeSpainSri LankaSt. Vincent and the GrenadinesSudanSwedenSwitzerlandSyriaTaiwanThailandTrinidad and TobagoTurkeyUgandaUkraineUruguayUzbekistanVenezuelaVietnamWest IndiesWestern AfricaWestern AsiaWestern EuropeZaireZimbabwe
Immigrant Origin (Percentage)
AfghanistanAfricaAlbaniaArgentinaArmeniaAsiaAustraliaAustriaBahamasBangladeshBarbadosBelarusBelgiumBelizeBoliviaBosnia and HerzegovinaBrazilBulgariaBurma / MyanmarCambodiaCameroonCanadaCaribbeanCentral AmericaChileChinaColombiaCosta RicaCroatiaCubaCzechoslovakiaDenmarkDominicaDominican RepublicEastern AfricaEastern AsiaEastern EuropeEcuadorEgyptEl SalvadorEnglandEthiopiaEuropeFranceGermanyGreeceGrenadaGuatemalaGuyanaHaitiHondurasHong KongHungaryIndiaIndonesiaIranIraqIrelandIsraelItalyJamaicaJapanJordanKazakhstanKenyaKoreaKuwaitLaosLatin AmericaLatviaLebanonLithuaniaMalaysiaMexicoMiddle AfricaMoldovaMoroccoNepalNetherlandsNicaraguaNigeriaNorthern AfricaNorthern EuropeNorwayOceaniaPakistanPanamaPeruPhilippinesPolandPortugalRomaniaRussiaSaudi ArabiaScotlandSerbiaSingaporeSouth AfricaSouth AmericaSouth Central AsiaSouth Eastern AsiaSouthern EuropeSpainSri LankaSt. Vincent and the GrenadinesSudanSwedenSwitzerlandSyriaTaiwanThailandTrinidad and TobagoTurkeyUgandaUkraineUruguayUzbekistanVenezuelaVietnamWest IndiesWestern AfricaWestern AsiaWestern EuropeZaireZimbabwe
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
Miami
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Compare Zip Codes
Comparison Subject

Map of Zip Codes with the Highest Child Poverty Level Among Girls Under the Age of 16 in Miami

0.48%
55.0%
Zip Codes with the Highest Child Poverty Level Among Girls Under the Age of 16 in Miami Map

Zip Codes with the Highest Child Poverty Level Among Girls Under the Age of 16 in Miami, FL

Zip Code Child Poverty (Girls) vs State vs National
1. 33136 55.0% 17.8% (+37.2)#32 17.0% (+38.1)#1,611
2. 33150 43.6% 17.8% (+25.8)#60 17.0% (+26.6)#2,797
3. 33127 37.9% 17.8% (+20.1)#97 17.0% (+21.0)#3,739
4. 33147 35.7% 17.8% (+17.9)#113 17.0% (+18.7)#4,237
5. 33125 33.5% 17.8% (+15.7)#132 17.0% (+16.5)#4,751
6. 33142 33.3% 17.8% (+15.5)#134 17.0% (+16.3)#4,839
7. 33167 33.2% 17.8% (+15.4)#136 17.0% (+16.3)#4,851
8. 33161 32.1% 17.8% (+14.3)#148 17.0% (+15.2)#5,130
9. 33135 30.5% 17.8% (+12.7)#163 17.0% (+13.5)#5,593
10. 33177 26.5% 17.8% (+8.72)#223 17.0% (+9.55)#6,922
11. 33181 26.0% 17.8% (+8.18)#229 17.0% (+9.01)#7,127
12. 33130 25.0% 17.8% (+7.17)#246 17.0% (+8.01)#7,590
13. 33168 24.0% 17.8% (+6.15)#260 17.0% (+6.98)#7,965
14. 33137 23.5% 17.8% (+5.69)#269 17.0% (+6.52)#8,165
15. 33166 20.4% 17.8% (+2.58)#325 17.0% (+3.42)#9,643
16. 33126 17.7% 17.8% (-0.159)#395 17.0% (+0.675)#11,104
17. 33175 17.5% 17.8% (-0.358)#399 17.0% (+0.476)#11,224
18. 33193 17.4% 17.8% (-0.369)#401 17.0% (+0.464)#11,231
19. 33138 17.1% 17.8% (-0.677)#413 17.0% (+0.156)#11,439
20. 33190 16.9% 17.8% (-0.904)#418 17.0% (-0.070)#11,577
21. 33157 16.7% 17.8% (-1.14)#423 17.0% (-0.302)#11,689
22. 33128 16.3% 17.8% (-1.55)#438 17.0% (-0.716)#11,963
23. 33172 16.2% 17.8% (-1.64)#441 17.0% (-0.811)#12,015
24. 33173 15.9% 17.8% (-1.89)#447 17.0% (-1.05)#12,169
25. 33186 15.4% 17.8% (-2.40)#459 17.0% (-1.56)#12,480
26. 33144 15.0% 17.8% (-2.83)#472 17.0% (-2.00)#12,777
27. 33169 14.9% 17.8% (-2.87)#473 17.0% (-2.04)#12,806
28. 33189 14.1% 17.8% (-3.73)#499 17.0% (-2.90)#13,365
29. 33155 14.0% 17.8% (-3.80)#500 17.0% (-2.97)#13,406
30. 33162 14.0% 17.8% (-3.86)#503 17.0% (-3.03)#13,449
31. 33196 13.3% 17.8% (-4.53)#519 17.0% (-3.69)#13,911
32. 33145 11.9% 17.8% (-5.93)#565 17.0% (-5.10)#14,866
33. 33133 10.5% 17.8% (-7.28)#613 17.0% (-6.45)#15,851
34. 33156 10.4% 17.8% (-7.37)#615 17.0% (-6.54)#15,914
35. 33178 10.2% 17.8% (-7.63)#623 17.0% (-6.79)#16,114
36. 33180 9.8% 17.8% (-7.98)#632 17.0% (-7.15)#16,372
37. 33179 8.2% 17.8% (-9.60)#669 17.0% (-8.77)#17,673
38. 33183 8.1% 17.8% (-9.66)#670 17.0% (-8.83)#17,720
39. 33174 7.8% 17.8% (-10.0)#684 17.0% (-9.19)#17,989
40. 33170 7.4% 17.8% (-10.4)#698 17.0% (-9.62)#18,422
41. 33165 7.2% 17.8% (-10.7)#704 17.0% (-9.82)#18,581
42. 33143 6.7% 17.8% (-11.1)#716 17.0% (-10.3)#18,958
43. 33176 6.4% 17.8% (-11.4)#724 17.0% (-10.5)#19,174
44. 33134 5.4% 17.8% (-12.4)#751 17.0% (-11.6)#20,029
45. 33184 5.3% 17.8% (-12.5)#753 17.0% (-11.7)#20,163
46. 33187 3.7% 17.8% (-14.1)#792 17.0% (-13.2)#21,557
47. 33185 3.7% 17.8% (-14.1)#794 17.0% (-13.3)#21,601
48. 33182 2.3% 17.8% (-15.5)#829 17.0% (-14.7)#22,780
49. 33131 0.69% 17.8% (-17.1)#860 17.0% (-16.3)#23,963
50. 33194 0.48% 17.8% (-17.3)#862 17.0% (-16.5)#24,037

Common Questions

What are the Top 10 Zip Codes with the Highest Child Poverty Level Among Girls Under the Age of 16 in Miami, FL?
Top 10 Zip Codes with the Highest Child Poverty Level Among Girls Under the Age of 16 in Miami, FL are:
#1
55.0%
#2
43.6%
#3
37.9%
#4
35.7%
#5
33.5%
#6
33.3%
#7
33.2%
#8
32.1%
#9
30.5%
#10
26.5%
What zip code has the Highest Child Poverty Level Among Girls Under the Age of 16 in Miami, FL?
33136 has the Highest Child Poverty Level Among Girls Under the Age of 16 in Miami, FL with 55.0%.
What is the Poverty Level Among Girls Under the Age of 16 in Miami, FL?
Poverty Level Among Girls Under the Age of 16 in Miami is 23.9%.
What is the Poverty Level Among Girls Under the Age of 16 in Florida?
Poverty Level Among Girls Under the Age of 16 in Florida is 17.8%.
What is the Poverty Level Among Girls Under the Age of 16 in the United States?
Poverty Level Among Girls Under the Age of 16 in the United States is 17.0%.