Immigrants from Bangladesh vs German Community Comparison

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Immigrants from Bangladesh
Race
Ancestry
AfghanAfricanAlaska NativeAlaskan AthabascanAlbanianAleutAlsatianAmericanApacheArabArapahoArgentineanArmenianAssyrian/Chaldean/SyriacAustralianAustrianBahamianBangladeshiBarbadianBasqueBelgianBelizeanBermudanBhutaneseBlackfeetBolivianBrazilianBritishBritish West IndianBulgarianBurmeseCajunCambodianCanadianCape VerdeanCarpatho RusynCelticCentral AmericanCentral American IndianCherokeeCheyenneChickasawChileanChineseChippewaChoctawColombianColvilleComancheCosta RicanCreeCreekCroatianCrowCubanCypriotCzechCzechoslovakianDanishDelawareDominicanDutchDutch West IndianEastern EuropeanEcuadorianEgyptianEnglishEstonianEthiopianEuropeanFijianFilipinoFinnishFrenchFrench American IndianFrench CanadianGerman 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
Immigration
NonimmigrantsImmigrantsAfghanistanAfricaAlbaniaArgentinaArmeniaAsiaAustraliaAustriaBahamasBangladeshBarbadosBelarusBelgiumBelizeBoliviaBosnia and HerzegovinaBrazilBulgariaBurma/MyanmarCabo VerdeCambodiaCameroonCanadaCaribbeanCentral AmericaChileChinaColombiaCongoCosta RicaCroatiaCubaCzechoslovakiaDenmarkDominicaDominican RepublicEastern AfricaEastern AsiaEastern EuropeEcuadorEgyptEl SalvadorEnglandEritreaEthiopiaEuropeFijiFranceGermanyGhanaGreeceGrenadaGuatemalaGuyanaHaitiHondurasHong KongHungaryIndiaIndonesiaIranIraqIrelandIsraelItalyJamaicaJapanJordanKazakhstanKenyaKoreaKuwaitLaosLatin AmericaLatviaLebanonLiberiaLithuaniaMalaysiaMexicoMicronesiaMiddle AfricaMoldovaMoroccoNepalNetherlandsNicaraguaNigeriaNorth AmericaNorth MacedoniaNorthern AfricaNorthern EuropeNorwayOceaniaPakistanPanamaPeruPhilippinesPolandPortugalRomaniaRussiaSaudi ArabiaScotlandSenegalSerbiaSierra LeoneSingaporeSomaliaSouth AfricaSouth AmericaSouth Central AsiaSouth Eastern AsiaSouthern EuropeSpainSri LankaSt. Vincent and the GrenadinesSudanSwedenSwitzerlandSyriaTaiwanThailandTrinidad and TobagoTurkeyUgandaUkraineUruguayUzbekistanVenezuelaVietnamWest IndiesWestern AfricaWestern AsiaWestern EuropeYemenZaireZimbabweAzores
German
Race
Ancestry
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
Immigration
NonimmigrantsImmigrantsAfghanistanAfricaAlbaniaArgentinaArmeniaAsiaAustraliaAustriaBahamasBarbadosBelarusBelgiumBelizeBoliviaBosnia and HerzegovinaBrazilBulgariaBurma/MyanmarCabo VerdeCambodiaCameroonCanadaCaribbeanCentral AmericaChileChinaColombiaCongoCosta RicaCroatiaCubaCzechoslovakiaDenmarkDominicaDominican RepublicEastern AfricaEastern AsiaEastern EuropeEcuadorEgyptEl SalvadorEnglandEritreaEthiopiaEuropeFijiFranceGermanyGhanaGreeceGrenadaGuatemalaGuyanaHaitiHondurasHong KongHungaryIndiaIndonesiaIranIraqIrelandIsraelItalyJamaicaJapanJordanKazakhstanKenyaKoreaKuwaitLaosLatin AmericaLatviaLebanonLiberiaLithuaniaMalaysiaMexicoMicronesiaMiddle AfricaMoldovaMoroccoNepalNetherlandsNicaraguaNigeriaNorth AmericaNorth MacedoniaNorthern AfricaNorthern EuropeNorwayOceaniaPakistanPanamaPeruPhilippinesPolandPortugalRomaniaRussiaSaudi ArabiaScotlandSenegalSerbiaSierra LeoneSingaporeSomaliaSouth AfricaSouth AmericaSouth Central AsiaSouth Eastern AsiaSouthern EuropeSpainSri LankaSt. Vincent and the GrenadinesSudanSwedenSwitzerlandSyriaTaiwanThailandTrinidad and TobagoTurkeyUgandaUkraineUruguayUzbekistanVenezuelaVietnamWest IndiesWestern AfricaWestern AsiaWestern EuropeYemenZaireZimbabweAzores
Social Comparison
Social Comparison
Income
Poverty
Unemployment
Labor Participation
Family Structure
Vehicle Availability
Education Level
Disability

Social Comparison

Immigrants from Bangladesh

Germans

Poor
Good
2,108
SOCIAL INDEX
18.6/ 100
SOCIAL RATING
269th/ 347
SOCIAL RANK
6,819
SOCIAL INDEX
65.7/ 100
SOCIAL RATING
140th/ 347
SOCIAL RANK

German Integration in Immigrants from Bangladesh Communities

The statistical analysis conducted on geographies consisting of 203,642,833 people shows a weak negative correlation between the proportion of Germans within Immigrant from Bangladesh communities in the United States with a correlation coefficient (R) of -0.297. On average, for every 1% (one percent) increase in Immigrants from Bangladesh within a typical geography, there is a decrease of 0.360% in Germans. To illustrate, in a geography comprising of 100,000 individuals, a rise of 1,000 Immigrants from Bangladesh corresponds to a decrease of 360.3 Germans.
Immigrants from Bangladesh Integration in German Communities

Immigrants from Bangladesh vs German Income

When considering income, the most significant differences between Immigrants from Bangladesh and German communities in the United States are seen in wage/income gap (20.9% compared to 29.2%, a difference of 39.2%), householder income ages 45 - 64 years ($92,208 compared to $100,224, a difference of 8.7%), and median family income ($94,665 compared to $102,254, a difference of 8.0%). Conversely, both communities are more comparable in terms of median earnings ($45,532 compared to $45,935, a difference of 0.89%), per capita income ($41,709 compared to $43,067, a difference of 3.3%), and median household income ($80,722 compared to $83,358, a difference of 3.3%).
Immigrants from Bangladesh vs German Income
Income MetricImmigrants from BangladeshGerman
Per Capita Income
Poor
$41,709
Fair
$43,067
Median Family Income
Tragic
$94,665
Average
$102,254
Median Household Income
Tragic
$80,722
Fair
$83,358
Median Earnings
Fair
$45,532
Fair
$45,935
Median Male Earnings
Tragic
$51,642
Good
$54,974
Median Female Earnings
Good
$39,910
Tragic
$37,986
Householder Age | Under 25 years
Exceptional
$54,714
Tragic
$50,804
Householder Age | 25 - 44 years
Tragic
$90,448
Fair
$93,531
Householder Age | 45 - 64 years
Tragic
$92,208
Average
$100,224
Householder Age | Over 65 years
Tragic
$55,394
Fair
$59,730
Wage/Income Gap
Exceptional
20.9%
Tragic
29.2%

Immigrants from Bangladesh vs German Poverty

When considering poverty, the most significant differences between Immigrants from Bangladesh and German communities in the United States are seen in married-couple family poverty (7.5% compared to 4.0%, a difference of 85.5%), receiving food stamps (15.9% compared to 9.7%, a difference of 63.2%), and seniors poverty over the age of 65 (14.1% compared to 9.0%, a difference of 57.2%). Conversely, both communities are more comparable in terms of single female poverty (22.3% compared to 21.8%, a difference of 2.4%), single mother poverty (31.1% compared to 30.0%, a difference of 3.8%), and female poverty among 18-24 year olds (21.8% compared to 20.4%, a difference of 6.6%).
Immigrants from Bangladesh vs German Poverty
Poverty MetricImmigrants from BangladeshGerman
Poverty
Tragic
15.3%
Exceptional
11.1%
Families
Tragic
11.7%
Exceptional
7.7%
Males
Tragic
14.1%
Exceptional
10.1%
Females
Tragic
16.4%
Exceptional
12.2%
Females 18 to 24 years
Tragic
21.8%
Fair
20.4%
Females 25 to 34 years
Tragic
14.8%
Average
13.6%
Children Under 5 years
Tragic
20.1%
Excellent
16.5%
Children Under 16 years
Tragic
19.8%
Exceptional
14.5%
Boys Under 16 years
Tragic
19.9%
Exceptional
14.8%
Girls Under 16 years
Tragic
19.9%
Exceptional
14.9%
Single Males
Fair
13.0%
Tragic
13.9%
Single Females
Tragic
22.3%
Tragic
21.8%
Single Fathers
Average
16.3%
Tragic
17.7%
Single Mothers
Tragic
31.1%
Tragic
30.0%
Married Couples
Tragic
7.5%
Exceptional
4.0%
Seniors Over 65 years
Tragic
14.1%
Exceptional
9.0%
Seniors Over 75 years
Tragic
15.8%
Exceptional
10.4%
Receiving Food Stamps
Tragic
15.9%
Exceptional
9.7%

Immigrants from Bangladesh vs German Unemployment

When considering unemployment, the most significant differences between Immigrants from Bangladesh and German communities in the United States are seen in unemployment (6.5% compared to 4.5%, a difference of 44.3%), female unemployment (6.5% compared to 4.5%, a difference of 44.0%), and male unemployment (6.6% compared to 4.7%, a difference of 39.9%). Conversely, both communities are more comparable in terms of unemployment among women with children ages 6 to 17 years (8.8% compared to 9.2%, a difference of 4.4%), unemployment among women with children under 6 years (8.8% compared to 8.0%, a difference of 10.8%), and unemployment among seniors over 75 years (9.1% compared to 10.3%, a difference of 13.0%).
Immigrants from Bangladesh vs German Unemployment
Unemployment MetricImmigrants from BangladeshGerman
Unemployment
Tragic
6.5%
Exceptional
4.5%
Males
Tragic
6.6%
Exceptional
4.7%
Females
Tragic
6.5%
Exceptional
4.5%
Youth < 25
Tragic
14.2%
Exceptional
10.5%
Age | 16 to 19 years
Tragic
21.5%
Exceptional
15.7%
Age | 20 to 24 years
Tragic
12.6%
Exceptional
9.6%
Age | 25 to 29 years
Tragic
7.5%
Excellent
6.5%
Age | 30 to 34 years
Tragic
6.4%
Good
5.3%
Age | 35 to 44 years
Tragic
5.3%
Exceptional
4.3%
Age | 45 to 54 years
Tragic
5.4%
Exceptional
4.1%
Age | 55 to 59 years
Tragic
5.9%
Exceptional
4.5%
Age | 60 to 64 years
Tragic
6.0%
Exceptional
4.5%
Age | 65 to 74 years
Tragic
5.9%
Exceptional
5.1%
Seniors > 65
Tragic
5.7%
Exceptional
4.9%
Seniors > 75
Tragic
9.1%
Tragic
10.3%
Women w/ Children < 6
Tragic
8.8%
Tragic
8.0%
Women w/ Children 6 to 17
Good
8.8%
Tragic
9.2%
Women w/ Children < 18
Tragic
6.4%
Exceptional
4.9%

Immigrants from Bangladesh vs German Labor Participation

When considering labor participation, the most significant differences between Immigrants from Bangladesh and German communities in the United States are seen in in labor force | age 16-19 (30.0% compared to 44.2%, a difference of 47.0%), in labor force | age 20-24 (70.6% compared to 78.6%, a difference of 11.3%), and in labor force | age 45-54 (80.7% compared to 83.1%, a difference of 2.9%). Conversely, both communities are more comparable in terms of in labor force | age > 16 (64.5% compared to 64.4%, a difference of 0.20%), in labor force | age 30-34 (83.6% compared to 84.8%, a difference of 1.5%), and in labor force | age 35-44 (82.9% compared to 84.7%, a difference of 2.1%).
Immigrants from Bangladesh vs German Labor Participation
Labor Participation MetricImmigrants from BangladeshGerman
In Labor Force | Age > 16
Tragic
64.5%
Tragic
64.4%
In Labor Force | Age 20-64
Tragic
77.9%
Good
79.7%
In Labor Force | Age 16-19
Tragic
30.0%
Exceptional
44.2%
In Labor Force | Age 20-24
Tragic
70.6%
Exceptional
78.6%
In Labor Force | Age 25-29
Tragic
83.0%
Exceptional
85.3%
In Labor Force | Age 30-34
Tragic
83.6%
Good
84.8%
In Labor Force | Age 35-44
Tragic
82.9%
Exceptional
84.7%
In Labor Force | Age 45-54
Tragic
80.7%
Excellent
83.1%

Immigrants from Bangladesh vs German Family Structure

When considering family structure, the most significant differences between Immigrants from Bangladesh and German communities in the United States are seen in single mother households (6.9% compared to 5.8%, a difference of 19.5%), single father households (2.1% compared to 2.4%, a difference of 14.9%), and married-couple households (43.1% compared to 49.2%, a difference of 14.1%). Conversely, both communities are more comparable in terms of family households (63.9% compared to 64.4%, a difference of 0.92%), family households with children (27.6% compared to 27.1%, a difference of 1.7%), and births to unmarried women (30.9% compared to 32.0%, a difference of 3.6%).
Immigrants from Bangladesh vs German Family Structure
Family Structure MetricImmigrants from BangladeshGerman
Family Households
Poor
63.9%
Good
64.4%
Family Households with Children
Good
27.6%
Tragic
27.1%
Married-couple Households
Tragic
43.1%
Exceptional
49.2%
Average Family Size
Exceptional
3.36
Tragic
3.09
Single Father Households
Exceptional
2.1%
Fair
2.4%
Single Mother Households
Tragic
6.9%
Exceptional
5.8%
Currently Married
Tragic
43.6%
Exceptional
49.6%
Divorced or Separated
Exceptional
11.0%
Tragic
12.5%
Births to Unmarried Women
Good
30.9%
Fair
32.0%

Immigrants from Bangladesh vs German Vehicle Availability

When considering vehicle availability, the most significant differences between Immigrants from Bangladesh and German communities in the United States are seen in no vehicles in household (25.8% compared to 6.7%, a difference of 285.7%), 4 or more vehicles in household (3.9% compared to 7.5%, a difference of 91.2%), and 3 or more vehicles in household (12.5% compared to 22.7%, a difference of 81.7%). Conversely, both communities are more comparable in terms of 1 or more vehicles in household (74.3% compared to 93.6%, a difference of 26.0%), 2 or more vehicles in household (38.8% compared to 61.6%, a difference of 58.8%), and 3 or more vehicles in household (12.5% compared to 22.7%, a difference of 81.7%).
Immigrants from Bangladesh vs German Vehicle Availability
Vehicle Availability MetricImmigrants from BangladeshGerman
No Vehicles Available
Tragic
25.8%
Exceptional
6.7%
1+ Vehicles Available
Tragic
74.3%
Exceptional
93.6%
2+ Vehicles Available
Tragic
38.8%
Exceptional
61.6%
3+ Vehicles Available
Tragic
12.5%
Exceptional
22.7%
4+ Vehicles Available
Tragic
3.9%
Exceptional
7.5%

Immigrants from Bangladesh vs German Education Level

When considering education level, the most significant differences between Immigrants from Bangladesh and German communities in the United States are seen in no schooling completed (3.1% compared to 1.4%, a difference of 132.0%), master's degree (15.5% compared to 14.0%, a difference of 10.4%), and professional degree (4.4% compared to 4.1%, a difference of 8.9%). Conversely, both communities are more comparable in terms of associate's degree (45.2% compared to 45.5%, a difference of 0.54%), nursery school (96.9% compared to 98.7%, a difference of 1.9%), and kindergarten (96.8% compared to 98.7%, a difference of 1.9%).
Immigrants from Bangladesh vs German Education Level
Education Level MetricImmigrants from BangladeshGerman
No Schooling Completed
Tragic
3.1%
Exceptional
1.4%
Nursery School
Tragic
96.9%
Exceptional
98.7%
Kindergarten
Tragic
96.8%
Exceptional
98.7%
1st Grade
Tragic
96.8%
Exceptional
98.7%
2nd Grade
Tragic
96.7%
Exceptional
98.7%
3rd Grade
Tragic
96.6%
Exceptional
98.6%
4th Grade
Tragic
96.2%
Exceptional
98.5%
5th Grade
Tragic
96.0%
Exceptional
98.4%
6th Grade
Tragic
95.4%
Exceptional
98.2%
7th Grade
Tragic
94.0%
Exceptional
97.7%
8th Grade
Tragic
93.6%
Exceptional
97.5%
9th Grade
Tragic
92.4%
Exceptional
96.7%
10th Grade
Tragic
91.0%
Exceptional
95.8%
11th Grade
Tragic
89.5%
Exceptional
94.7%
12th Grade, No Diploma
Tragic
88.0%
Exceptional
93.3%
High School Diploma
Tragic
85.5%
Exceptional
91.7%
GED/Equivalency
Tragic
81.9%
Exceptional
87.9%
College, Under 1 year
Tragic
61.3%
Average
65.6%
College, 1 year or more
Tragic
56.6%
Fair
58.9%
Associate's Degree
Fair
45.2%
Fair
45.5%
Bachelor's Degree
Average
37.8%
Poor
36.1%
Master's Degree
Good
15.5%
Poor
14.0%
Professional Degree
Average
4.4%
Poor
4.1%
Doctorate Degree
Average
1.8%
Fair
1.8%

Immigrants from Bangladesh vs German Disability

When considering disability, the most significant differences between Immigrants from Bangladesh and German communities in the United States are seen in disability age under 5 (0.85% compared to 1.7%, a difference of 101.7%), hearing disability (2.4% compared to 3.7%, a difference of 53.9%), and disability age 18 to 34 (5.6% compared to 7.7%, a difference of 37.1%). Conversely, both communities are more comparable in terms of disability age 65 to 74 (23.6% compared to 23.3%, a difference of 1.3%), disability age over 75 (48.0% compared to 46.3%, a difference of 3.8%), and ambulatory disability (6.2% compared to 6.5%, a difference of 4.0%).
Immigrants from Bangladesh vs German Disability
Disability MetricImmigrants from BangladeshGerman
Disability
Exceptional
11.0%
Tragic
12.8%
Males
Exceptional
10.3%
Tragic
12.7%
Females
Exceptional
11.8%
Tragic
12.9%
Age | Under 5 years
Exceptional
0.85%
Tragic
1.7%
Age | 5 to 17 years
Exceptional
5.2%
Tragic
6.1%
Age | 18 to 34 years
Exceptional
5.6%
Tragic
7.7%
Age | 35 to 64 years
Excellent
10.9%
Tragic
12.3%
Age | 65 to 74 years
Fair
23.6%
Average
23.3%
Age | Over 75 years
Tragic
48.0%
Exceptional
46.3%
Vision
Good
2.1%
Poor
2.2%
Hearing
Exceptional
2.4%
Tragic
3.7%
Cognitive
Tragic
17.8%
Exceptional
16.7%
Ambulatory
Fair
6.2%
Tragic
6.5%
Self-Care
Tragic
2.6%
Excellent
2.4%