Zip Codes with the Most Births per 1,000 Women in Labor Force in Maryland

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Highest 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
Maryland
Compare Zip Codes
Comparison Subject

Map of Zip Codes with the Most Births per 1,000 Women in Labor Force in Maryland

0.0
1,000.0
Zip Codes with the Most Births per 1,000 Women in Labor Force in Maryland Map

Zip Codes with the Most Births per 1,000 Women in Labor Force in Maryland

Zip Code Births / 1,000 Women vs State vs National
1.216501,000.050.0(+950)#148.0(+952)#11
2.206671,000.050.0(+950)#248.0(+952)#24
3.20758750.050.0(+700)#348.0(+702)#67
4.21634630.050.0(+580)#448.0(+582)#108
5.20645429.050.0(+379)#548.0(+381)#236
6.20608424.050.0(+374)#648.0(+376)#246
7.20687413.050.0(+363)#748.0(+365)#254
8.21156378.050.0(+328)#848.0(+330)#295
9.21524320.050.0(+270)#948.0(+272)#418
10.20611264.050.0(+214)#1048.0(+216)#596
11.21071264.050.0(+214)#1148.0(+216)#598
12.21733255.050.0(+205)#1248.0(+207)#631
13.21647240.050.0(+190)#1348.0(+192)#714
14.20674233.050.0(+183)#1448.0(+185)#745
15.21542216.050.0(+166)#1548.0(+168)#867
16.21798214.050.0(+164)#1648.0(+166)#880
17.21869198.050.0(+148)#1748.0(+150)#1,031
18.21082191.050.0(+141)#1848.0(+143)#1,091
19.20860170.050.0(+120)#1948.0(+122)#1,334
20.21155154.050.0(+104)#2048.0(+106)#1,606
21.20650150.050.0(+100.0)#2148.0(+102)#1,669
22.20710149.050.0(+99.0)#2248.0(+101)#1,691
23.20637149.050.0(+99.0)#2348.0(+101)#1,692
24.20623140.050.0(+90.0)#2448.0(+92.0)#1,897
25.20779137.050.0(+87.0)#2548.0(+89.0)#1,998
26.21850134.050.0(+84.0)#2648.0(+86.0)#2,073
27.21034133.050.0(+83.0)#2748.0(+85.0)#2,105
28.20896133.050.0(+83.0)#2848.0(+85.0)#2,111
29.21530131.050.0(+81.0)#2948.0(+83.0)#2,157
30.20762129.050.0(+79.0)#3048.0(+81.0)#2,214
31.20664129.050.0(+79.0)#3148.0(+81.0)#2,217
32.21853127.050.0(+77.0)#3248.0(+79.0)#2,268
33.21084127.050.0(+77.0)#3348.0(+79.0)#2,271
34.21851127.050.0(+77.0)#3448.0(+79.0)#2,272
35.21601124.050.0(+74.0)#3548.0(+76.0)#2,379
36.20602117.050.0(+67.0)#3648.0(+69.0)#2,625
37.21162114.050.0(+64.0)#3748.0(+66.0)#2,756
38.21625111.050.0(+61.0)#3848.0(+63.0)#2,898
39.20677110.050.0(+60.0)#3948.0(+62.0)#2,966
40.20880110.050.0(+60.0)#4048.0(+62.0)#2,983
41.20759109.050.0(+59.0)#4148.0(+61.0)#3,001
42.21758109.050.0(+59.0)#4248.0(+61.0)#3,006
43.21754108.050.0(+58.0)#4348.0(+60.0)#3,055
44.20781106.050.0(+56.0)#4448.0(+58.0)#3,145
45.21074103.050.0(+53.0)#4548.0(+55.0)#3,310
46.20695103.050.0(+53.0)#4648.0(+55.0)#3,314
47.21032100.050.0(+50.0)#4748.0(+52.0)#3,499
48.21874100.050.0(+50.0)#4848.0(+52.0)#3,518
49.2087796.050.0(+46.0)#4948.0(+48.0)#3,761
50.2070692.050.0(+42.0)#5048.0(+44.0)#4,029
51.2122792.050.0(+42.0)#5148.0(+44.0)#4,033
52.2156292.050.0(+42.0)#5248.0(+44.0)#4,068
53.2063691.050.0(+41.0)#5348.0(+43.0)#4,122
54.2179791.050.0(+41.0)#5448.0(+43.0)#4,127
55.2075191.050.0(+41.0)#5548.0(+43.0)#4,157
56.2087190.050.0(+40.0)#5648.0(+42.0)#4,213
57.2171388.050.0(+38.0)#5748.0(+40.0)#4,418
58.2179187.050.0(+37.0)#5848.0(+39.0)#4,537
59.2191886.050.0(+36.0)#5948.0(+38.0)#4,637
60.2100185.050.0(+35.0)#6048.0(+37.0)#4,702
61.2120583.050.0(+33.0)#6148.0(+35.0)#4,914
62.2075583.050.0(+33.0)#6248.0(+35.0)#4,926
63.2171683.050.0(+33.0)#6348.0(+35.0)#4,939
64.2072282.050.0(+32.0)#6448.0(+34.0)#5,055
65.2065381.050.0(+31.0)#6548.0(+33.0)#5,145
66.2111180.050.0(+30.0)#6648.0(+32.0)#5,301
67.2122079.050.0(+29.0)#6748.0(+31.0)#5,362
68.2078579.050.0(+29.0)#6848.0(+31.0)#5,363
69.2100979.050.0(+29.0)#6948.0(+31.0)#5,366
70.2087979.050.0(+29.0)#7048.0(+31.0)#5,373
71.2166379.050.0(+29.0)#7148.0(+31.0)#5,427
72.2112078.050.0(+28.0)#7248.0(+30.0)#5,534
73.2183777.050.0(+27.0)#7348.0(+29.0)#5,689
74.2072074.050.0(+24.0)#7448.0(+26.0)#6,030
75.2086673.050.0(+23.0)#7548.0(+25.0)#6,205
76.2101373.050.0(+23.0)#7648.0(+25.0)#6,250
77.2191973.050.0(+23.0)#7748.0(+25.0)#6,265
78.2152073.050.0(+23.0)#7848.0(+25.0)#6,270
79.2071572.050.0(+22.0)#7948.0(+24.0)#6,350
80.2178272.050.0(+22.0)#8048.0(+24.0)#6,417
81.2114471.050.0(+21.0)#8148.0(+23.0)#6,499
82.2174271.050.0(+21.0)#8248.0(+23.0)#6,501
83.2123771.050.0(+21.0)#8348.0(+23.0)#6,511
84.2067071.050.0(+21.0)#8448.0(+23.0)#6,620
85.2070770.050.0(+20.0)#8548.0(+22.0)#6,671
86.2170470.050.0(+20.0)#8648.0(+22.0)#6,703
87.2087270.050.0(+20.0)#8748.0(+22.0)#6,723
88.2104569.050.0(+19.0)#8848.0(+21.0)#6,836
89.2115869.050.0(+19.0)#8948.0(+21.0)#6,870
90.2089569.050.0(+19.0)#9048.0(+21.0)#6,879
91.2177769.050.0(+19.0)#9148.0(+21.0)#6,969
92.2060168.050.0(+18.0)#9248.0(+20.0)#7,072
93.2184268.050.0(+18.0)#9348.0(+20.0)#7,116
94.2071168.050.0(+18.0)#9448.0(+20.0)#7,132
95.2163168.050.0(+18.0)#9548.0(+20.0)#7,164
96.2175768.050.0(+18.0)#9648.0(+20.0)#7,165
97.2152168.050.0(+18.0)#9748.0(+20.0)#7,182
98.2105467.050.0(+17.0)#9848.0(+19.0)#7,294
99.2182666.050.0(+16.0)#9948.0(+18.0)#7,518
100.2101465.050.0(+15.0)#10048.0(+17.0)#7,611

Common Questions

What are the Top 10 Zip Codes with the Most Births per 1,000 Women in Labor Force in Maryland?
Top 10 Zip Codes with the Most Births per 1,000 Women in Labor Force in Maryland are:
#1
1,000.0
#2
1,000.0
#3
750.0
#4
630.0
#5
429.0
#6
424.0
#7
413.0
#8
378.0
#9
320.0
#10
264.0
What zip code has the Most Births per 1,000 Women in Labor Force in Maryland?
21650 has the Most Births per 1,000 Women in Labor Force in Maryland with 1,000.0.
What is the Number of Births per 1,000 Women in Labor Force in the State of Maryland?
Number of Births per 1,000 Women in Labor Force in Maryland is 50.0.
What is the Number of Births per 1,000 Women in Labor Force in the United States?
Number of Births per 1,000 Women in Labor Force in the United States is 48.0.