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

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Lowest 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 Lowest Child Poverty Level Among Girls Under the Age of 16 in Miami

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

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

Zip Code Child Poverty (Girls) vs State vs National
1. 33194 0.48% 17.8% (-17.3)#3 17.0% (-16.5)#72
2. 33131 0.69% 17.8% (-17.1)#5 17.0% (-16.3)#146
3. 33182 2.3% 17.8% (-15.5)#36 17.0% (-14.7)#1,329
4. 33185 3.7% 17.8% (-14.1)#71 17.0% (-13.3)#2,508
5. 33187 3.7% 17.8% (-14.1)#73 17.0% (-13.2)#2,551
6. 33184 5.3% 17.8% (-12.5)#112 17.0% (-11.7)#3,946
7. 33134 5.4% 17.8% (-12.4)#114 17.0% (-11.6)#4,080
8. 33176 6.4% 17.8% (-11.4)#141 17.0% (-10.5)#4,935
9. 33143 6.7% 17.8% (-11.1)#149 17.0% (-10.3)#5,149
10. 33165 7.2% 17.8% (-10.7)#161 17.0% (-9.82)#5,528
11. 33170 7.4% 17.8% (-10.4)#167 17.0% (-9.62)#5,687
12. 33174 7.8% 17.8% (-10.0)#181 17.0% (-9.19)#6,120
13. 33183 8.1% 17.8% (-9.66)#195 17.0% (-8.83)#6,389
14. 33179 8.2% 17.8% (-9.60)#196 17.0% (-8.77)#6,436
15. 33180 9.8% 17.8% (-7.98)#233 17.0% (-7.15)#7,737
16. 33178 10.2% 17.8% (-7.63)#242 17.0% (-6.79)#7,995
17. 33156 10.4% 17.8% (-7.37)#250 17.0% (-6.54)#8,195
18. 33133 10.5% 17.8% (-7.28)#252 17.0% (-6.45)#8,258
19. 33145 11.9% 17.8% (-5.93)#300 17.0% (-5.10)#9,243
20. 33196 13.3% 17.8% (-4.53)#346 17.0% (-3.69)#10,198
21. 33162 14.0% 17.8% (-3.86)#362 17.0% (-3.03)#10,660
22. 33155 14.0% 17.8% (-3.80)#365 17.0% (-2.97)#10,703
23. 33189 14.1% 17.8% (-3.73)#366 17.0% (-2.90)#10,744
24. 33169 14.9% 17.8% (-2.87)#392 17.0% (-2.04)#11,303
25. 33144 15.0% 17.8% (-2.83)#393 17.0% (-2.00)#11,332
26. 33186 15.4% 17.8% (-2.40)#406 17.0% (-1.56)#11,629
27. 33173 15.9% 17.8% (-1.89)#418 17.0% (-1.05)#11,940
28. 33172 16.2% 17.8% (-1.64)#424 17.0% (-0.811)#12,094
29. 33128 16.3% 17.8% (-1.55)#427 17.0% (-0.716)#12,146
30. 33157 16.7% 17.8% (-1.14)#442 17.0% (-0.302)#12,420
31. 33190 16.9% 17.8% (-0.904)#447 17.0% (-0.070)#12,532
32. 33138 17.1% 17.8% (-0.677)#452 17.0% (+0.156)#12,670
33. 33193 17.4% 17.8% (-0.369)#464 17.0% (+0.464)#12,878
34. 33175 17.5% 17.8% (-0.358)#466 17.0% (+0.476)#12,885
35. 33126 17.7% 17.8% (-0.159)#470 17.0% (+0.675)#13,005
36. 33166 20.4% 17.8% (+2.58)#540 17.0% (+3.42)#14,466
37. 33137 23.5% 17.8% (+5.69)#596 17.0% (+6.52)#15,944
38. 33168 24.0% 17.8% (+6.15)#605 17.0% (+6.98)#16,144
39. 33130 25.0% 17.8% (+7.17)#619 17.0% (+8.01)#16,519
40. 33181 26.0% 17.8% (+8.18)#636 17.0% (+9.01)#16,982
41. 33177 26.5% 17.8% (+8.72)#642 17.0% (+9.55)#17,187
42. 33135 30.5% 17.8% (+12.7)#702 17.0% (+13.5)#18,516
43. 33161 32.1% 17.8% (+14.3)#717 17.0% (+15.2)#18,979
44. 33167 33.2% 17.8% (+15.4)#729 17.0% (+16.3)#19,258
45. 33142 33.3% 17.8% (+15.5)#731 17.0% (+16.3)#19,270
46. 33125 33.5% 17.8% (+15.7)#733 17.0% (+16.5)#19,358
47. 33147 35.7% 17.8% (+17.9)#752 17.0% (+18.7)#19,872
48. 33127 37.9% 17.8% (+20.1)#768 17.0% (+21.0)#20,370
49. 33150 43.6% 17.8% (+25.8)#805 17.0% (+26.6)#21,312
50. 33136 55.0% 17.8% (+37.2)#833 17.0% (+38.1)#22,498

Common Questions

What are the Top 10 Zip Codes with the Lowest Child Poverty Level Among Girls Under the Age of 16 in Miami, FL?
Top 10 Zip Codes with the Lowest Child Poverty Level Among Girls Under the Age of 16 in Miami, FL are:
#1
0.0%
#2
0.0%
#3
0.0%
#4
0.0%
#5
0.0%
#6
0.48%
#7
0.69%
#8
2.3%
#9
3.7%
#10
3.7%
What zip code has the Lowest Child Poverty Level Among Girls Under the Age of 16 in Miami, FL?
33194 has the Lowest Child Poverty Level Among Girls Under the Age of 16 in Miami, FL with 0.48%.
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%.