Cities with the Most Births per 1,000 Women Below Poverty Level in Maryland

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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
Maryland
Compare Cities
Comparison Subject

Map of Cities with the Most Births per 1,000 Women Below Poverty Level in Maryland

0.0
1,000.0
Cities with the Most Births per 1,000 Women Below Poverty Level in Maryland Map

Cities with the Most Births per 1,000 Women Below Poverty Level in Maryland

City Births / 1,000 Women vs State vs National
1.Pondsville1,000.052.0(+948)#153.0(+947)#22
2.Dargan636.052.0(+584)#253.0(+583)#152
3.Antietam571.052.0(+519)#353.0(+518)#189
4.Friendship464.052.0(+412)#453.0(+411)#267
5.Brookview400.052.0(+348)#553.0(+347)#355
6.Corriganville367.052.0(+315)#653.0(+314)#407
7.Aquasco356.052.0(+304)#753.0(+303)#433
8.Fishing Creek321.052.0(+269)#853.0(+268)#538
9.Bagtown318.052.0(+266)#953.0(+265)#557
10.Flintstone280.052.0(+228)#1053.0(+227)#724
11.Edgemont255.052.0(+203)#1153.0(+202)#856
12.Accident253.052.0(+201)#1253.0(+200)#867
13.Goldsboro244.052.0(+192)#1353.0(+191)#940
14.Zihlman235.052.0(+183)#1453.0(+182)#1,000
15.Cedar Heights227.052.0(+175)#1553.0(+174)#1,068
16.Konterra212.052.0(+160)#1653.0(+159)#1,215
17.Naval Academy198.052.0(+146)#1753.0(+145)#1,374
18.Midland190.052.0(+138)#1853.0(+137)#1,466
19.Piney Point182.052.0(+130)#1953.0(+129)#1,582
20.Eden180.052.0(+128)#2053.0(+127)#1,623
21.Andrews Afb171.052.0(+119)#2153.0(+118)#1,773
22.Lansdowne165.052.0(+113)#2253.0(+112)#1,891
23.Hancock163.052.0(+111)#2353.0(+110)#1,940
24.North Brentwood154.052.0(+102)#2453.0(+101)#2,161
25.Leonardtown149.052.0(+97.0)#2553.0(+96.0)#2,298
26.Pocomoke City149.052.0(+97.0)#2653.0(+96.0)#2,300
27.Westernport145.052.0(+93.0)#2753.0(+92.0)#2,430
28.Shaft140.052.0(+88.0)#2853.0(+87.0)#2,652
29.Abingdon136.052.0(+84.0)#2953.0(+83.0)#2,750
30.Bladensburg128.052.0(+76.0)#3053.0(+75.0)#3,072
31.Hughesville128.052.0(+76.0)#3153.0(+75.0)#3,085
32.Federalsburg126.052.0(+74.0)#3253.0(+73.0)#3,173
33.Easton125.052.0(+73.0)#3353.0(+72.0)#3,196
34.Arden On The Severn124.052.0(+72.0)#3453.0(+71.0)#3,276
35.Beaver Creek119.052.0(+67.0)#3553.0(+66.0)#3,543
36.Jessup118.052.0(+66.0)#3653.0(+65.0)#3,559
37.Fairmount Heights116.052.0(+64.0)#3753.0(+63.0)#3,695
38.Garrett Park116.052.0(+64.0)#3853.0(+63.0)#3,705
39.Edmonston115.052.0(+63.0)#3953.0(+62.0)#3,751
40.Maryland Park113.052.0(+61.0)#4053.0(+60.0)#3,886
41.Mardela Springs110.052.0(+58.0)#4153.0(+57.0)#4,101
42.Baden106.052.0(+54.0)#4253.0(+53.0)#4,324
43.Berwyn Heights105.052.0(+53.0)#4353.0(+52.0)#4,372
44.Sudlersville105.052.0(+53.0)#4453.0(+52.0)#4,409
45.Woodlawn Cdp Prince George S County104.052.0(+52.0)#4553.0(+51.0)#4,432
46.Darlington104.052.0(+52.0)#4653.0(+51.0)#4,481
47.Kensington101.052.0(+49.0)#4753.0(+48.0)#4,683
48.Marydel100.052.0(+48.0)#4853.0(+47.0)#4,811
49.Redland99.052.0(+47.0)#4953.0(+46.0)#4,831
50.Arbutus96.052.0(+44.0)#5053.0(+43.0)#5,063
51.Seabrook95.052.0(+43.0)#5153.0(+42.0)#5,170
52.Princess Anne95.052.0(+43.0)#5253.0(+42.0)#5,196
53.New Windsor95.052.0(+43.0)#5353.0(+42.0)#5,217
54.Fairplay94.052.0(+42.0)#5453.0(+41.0)#5,322
55.Ocean Pines93.052.0(+41.0)#5553.0(+40.0)#5,348
56.Greensboro93.052.0(+41.0)#5653.0(+40.0)#5,376
57.Landover92.052.0(+40.0)#5753.0(+39.0)#5,438
58.Mount Airy92.052.0(+40.0)#5853.0(+39.0)#5,447
59.Hyattsville91.052.0(+39.0)#5953.0(+38.0)#5,527
60.Linganore90.052.0(+38.0)#6053.0(+37.0)#5,632
61.Fort Meade90.052.0(+38.0)#6153.0(+37.0)#5,636
62.Washington Grove90.052.0(+38.0)#6253.0(+37.0)#5,700
63.Perryman89.052.0(+37.0)#6353.0(+36.0)#5,758
64.Takoma Park87.052.0(+35.0)#6453.0(+34.0)#5,918
65.Ferndale87.052.0(+35.0)#6553.0(+34.0)#5,919
66.Huntingtown87.052.0(+35.0)#6653.0(+34.0)#5,955
67.Bartonsville87.052.0(+35.0)#6753.0(+34.0)#5,965
68.Laytonsville87.052.0(+35.0)#6853.0(+34.0)#5,993
69.Middle River86.052.0(+34.0)#6953.0(+33.0)#6,016
70.Frostburg86.052.0(+34.0)#7053.0(+33.0)#6,039
71.Charlotte Hall86.052.0(+34.0)#7153.0(+33.0)#6,075
72.Landover Hills85.052.0(+33.0)#7253.0(+32.0)#6,159
73.Largo84.052.0(+32.0)#7353.0(+31.0)#6,223
74.Paramount Long Meadow84.052.0(+32.0)#7453.0(+31.0)#6,258
75.Langley Park83.052.0(+31.0)#7553.0(+30.0)#6,324
76.Springdale83.052.0(+31.0)#7653.0(+30.0)#6,352
77.Brentwood83.052.0(+31.0)#7753.0(+30.0)#6,358
78.Prince Frederick83.052.0(+31.0)#7853.0(+30.0)#6,370
79.Chevy Chase Section Five83.052.0(+31.0)#7953.0(+30.0)#6,397
80.White Oak82.052.0(+30.0)#8053.0(+29.0)#6,476
81.Mayo82.052.0(+30.0)#8153.0(+29.0)#6,485
82.Taneytown82.052.0(+30.0)#8253.0(+29.0)#6,490
83.Burnt Mills82.052.0(+30.0)#8353.0(+29.0)#6,507
84.Rising Sun82.052.0(+30.0)#8453.0(+29.0)#6,515
85.Waldorf81.052.0(+29.0)#8553.0(+28.0)#6,589
86.Hagerstown81.052.0(+29.0)#8653.0(+28.0)#6,594
87.Long Beach81.052.0(+29.0)#8753.0(+28.0)#6,655
88.North Chevy Chase81.052.0(+29.0)#8853.0(+28.0)#6,682
89.Barton81.052.0(+29.0)#8953.0(+28.0)#6,684
90.New Carrollton80.052.0(+28.0)#9053.0(+27.0)#6,724
91.Cheverly80.052.0(+28.0)#9153.0(+27.0)#6,747
92.Deale80.052.0(+28.0)#9253.0(+27.0)#6,761
93.Romancoke80.052.0(+28.0)#9353.0(+27.0)#6,789
94.South Kensington78.052.0(+26.0)#9453.0(+25.0)#6,988
95.Fruitland78.052.0(+26.0)#9553.0(+25.0)#6,997
96.Mount Aetna78.052.0(+26.0)#9653.0(+25.0)#7,071
97.Burtonsville77.052.0(+25.0)#9753.0(+24.0)#7,107
98.Four Corners77.052.0(+25.0)#9853.0(+24.0)#7,116
99.Ridgely77.052.0(+25.0)#9953.0(+24.0)#7,158
100.Wildewood76.052.0(+24.0)#10053.0(+23.0)#7,279

Common Questions

What are the Top 10 Cities with the Most Births per 1,000 Women Below Poverty Level in Maryland?
Top 10 Cities with the Most Births per 1,000 Women Below Poverty Level in Maryland are:
#1
1,000.0
#2
636.0
#3
571.0
#4
464.0
#5
400.0
#6
367.0
#7
356.0
#8
321.0
#9
318.0
#10
280.0
What city has the Most Births per 1,000 Women Below Poverty Level in Maryland?
Pondsville has the Most Births per 1,000 Women Below Poverty Level in Maryland with 1,000.0.
What is the Number of Births per 1,000 Women Below Poverty Level in the State of Maryland?
Number of Births per 1,000 Women Below Poverty Level in Maryland is 52.0.
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.